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0 text {Contributor code} 2 sources Sources 3 derived {Overall indicator status} 4 textblock {Collection method} 5 textblock {Data requirements} 6 text Unit 8 textblock Costs 9 textblock Confidence/uncertainty 10 textblock Observations/Remarks 1 modified {Last modification} 11 textblock {Indicator description} 12 checkgroup {RSC affiliation} 14 text {Original name} 15 list {DPSIR stage} 16 list {Main attribute} 17 table {Underlying variable types} 18 list {Algorithm type} 19 checkgroup {Ecosystem services}


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3 {{oid} {set st [db eval {select avid from oas where oid=$oid and apid=8}]; if {[lsearch $st 35] > -1} {set avid 35} elseif {[lsearch $st 36] > -1} {set avid 36} elseif {[lsearch $st 37] > -1} {set avid 37} else {return ""}; return [list [list [db onecolumn {select value from attributesValues where avid=$avid}] {}]]}} 12 {{HELCOM coreset} {OSPAR common indicator} {Barcelona convention indicator} {Bucharest convention indicator}} 15 {Pressure State Impact} 16 {{Indicator Species} {Target Groups} {Physiological Condition} {Population Ecology} {Community Structure} {Life Traits} Production Foodweb {Thermodinamically Oriented} {Biotope Features} {Climate Change} {Anthropogenic Activities}} 18 {Categorical/Labelled {Simple statistics} {Complex statistics} Modelling} 19 {{Food provision} {Climate regulation} {Disturbance prevention or moderation} {Bioremediation of waste} {Biological control} {Leisure and recreation} {Aesthetic experience}}


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Author textblock 0 Year text 1 Title textblock 2 {Bibliographic information} textblock 3 Link link 4


item: welcomeMessage
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{DEVOTES Catalogue of Indicators} headerFont "\n\nThis is version 8 of the Catalogue of Indicators of the FP7 project DEVOTES that aims at supporting the implementation of the EU MSFD. This catalogue of indicators is an inventory of existing methods. The metadata have been updated and extended since deiverable D3-1 of the project. You can learn more about the DEVOTES project at: http://www.devotes-project.eu" {} "\n\nAll data are provided without a guarantee of correctness or completeness. We are aware of some errors in the database content and are continuously working on correcting these and on supplementing the content with new metadata.\n\nWhen the computer running this software is connected to the internet, DEVOTool will check whether a new version of the indicator catalogue is available and notify you accordingly. For newer versions of the software, please check the DEVOTES website.\n\nBy using this software, you accept the license conditions as outlined in section 6 of the software manual distributed together with this software." {}


item: objectsCustomDefinitions_17
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0 {Biomass Abundance {Taxonomic Composition} {Traits Composition} {Trophic Data} {Spatial Distribution} {Physio-/Morphological Data} {Demography and Population Dynamics} {Isotopic Data} {Biochemical Markers} {Molecular markers} {Abiotic Data} {Hazardous Substances} {Toxicicological Data} {Socio-Economic Data}}


# objects

name: By-catch of marine mammals and waterbirds in fishing gears
_0: SYKE-LU 14
_5: Number of drowned birds and mammals
_12: {HELCOM coreset}
_14: Drowned marine mammals and waterbirds in fishing gears
_15: Pressure
_16: Anthropogenic Activities
_18: Simple statistics
_10:
Pressure indicator. Documentation at http://www.helcom.fi/Core%20Indicators/HELCOM-CoreIndicator-Number_of_drowned_mammals_and_waterbirds_in_fishing_gear.pdf


name: Abundance of selected (coastal) fish species
_0: SYKE-LU 15
_4: Experimental gill-netting
_5: Species abundance
_6: Catch per unit effort
_12: {HELCOM coreset}
_14: Abundance of key species of coastal fish
_15: State
_16: Target Groups
_18: Simple statistics
_19: {Leisure and recreation}
_11:
Coastal fish monitoring using gill-nets is performed annually all over the Baltic Sea (Figure 5), coordinated within the HELCOM Fish PRO expert network. The network includes data from monitoring areas in Finland, Estonia, Latvia,  Lithuania and Sweden. The calculations are based on catch per unit effort data (CPUE) from annual averages of all sampling stations in each  monitoring area. The coastal fish monitoring typically takes place in August and reflects trends in species that occur in  coastal areas during the warm season of the year


name: Population structure of long-lived macrozoobenthic species
_0: SYKE-LU 21
_5: size measurements of selected bivalve species
_6: size frequency of bivalves
_12: {HELCOM coreset}
_13: Are these measuring the same things in the same way? Are they equivalent: SYKE-LU 21/71/77
_14: Population structure of long-lived macrozoobenthic species
_15: State
_16: Population Ecology
_18: Simple statistics
_10:
 Documentation:  http://www.helcom.fi/Core%20Indicators/HELCOM-CoreIndicator_Population_structure_of_long-lived_macrozoobenthic_species.pdf

_11:
The size-frequency-distribution indicator described in this report is twofold:  (1) Soft-bottom bivalve indicator is focused on physical disturbance or hypoxia. The response characteristics might differ between the two impacts. Large and long-living species often play key roles in the functioning of the benthic communities and the re-establishment of the population structure of those  species is the most lasting step after a severe impact.  (2) Hard-bottom mussel indicator is focused on the pressure from siltation/sedimentation of organic and inorganic matter and reflects therefore eutrophication in general (e.g. decaying blooms of phytoplankton and macroalgae), riverine run-off of organic and inorganic matter, dredging and disposal of the dredged material as well as shipping. The indicator may be based on three alternative methods:  1. the deviation from the natural full size-spectrum,  2. the deviation from a mean size, or  3. the proportion of specimen above a certain size class 


name: Trends in arrival of new non-indigenous species
_0: SYKE-LU 22
_5: number of new arrivals of non-indigernous species
_6: number of new arrivals
_12: {HELCOM coreset}
_14: Trends in arrival of new non-indigenous species
_15: Pressure
_16: Target Groups
_18: Simple statistics
_19: {Biological control}
_10:
Documentation: http://www.helcom.fi/Core%20Indicators/HELCOM-CoreIndicator-Trends_in_arrival_of_new_non-indigenous_species.pdf

_11:
The indicator follows numbers of non-indigenous species found in Baltic Sea sub-basins within an assessment period of six years. The indicator is based on a baseline study, identifying the number of already arrived non-indigenous 
species. Every new non-indigenous species (NIS) arriving after the baseline year is counted as a new species. New NIS comprises not only established organisms but all new encountered species even if they will not establish (because 
species which cannot establish stable populations will also be regarded as failed management). In the end of the assessment period, the number of new NIS is summed per assessment unit. The assessment period after that will start again from zero and assess the number of NIS arriving during that period. 


name: State of benthic communities
_0: SYKE-LU 23
_5: Species abundances, ind/m2
_6: N/A
_12: {HELCOM coreset}
_14: State of the soft-bottom macrofauna community
_15: State
_16: Target Groups
_19: {Bioremediation of waste}
_11:
The indicator assesses the state of the macrozoobenthic communities by various indices which have been developed for national assessments on the state of the surface waters under the EU Water Framework Directive and for the HELCOM Thematic Assessment on Eutrophication.

_13:
MariLim: SYKE - Settings - geography: We don't understand Area 48 (Atlantic, Antarctic) in this context of the Baltic Sea.


name: Abundance or biomass of key species in the coastal waters
_0: SYKE-LU 28
_6: abundance or biomass of selected species
_14: Abundance or biomass of key species in the coastal waters
_15: State
_16: Target Groups
_18: Simple statistics
_19: {Biological control}
_13:
Could taxa name be remoed to a specific column and removed from indicators name? then these entries (KUCORPI-MBAZ 1,2,3,4,5,6,7) could be merged. Move 'Coastal waters'under adequate fields


name: Abundance or biomass of key functional groups in the coastal waters
_0: SYKE-LU 40
_14: Abundance or biomass of key functional groups in the coastal waters
_15: State
_16: Target Groups
_18: Simple statistics
_13:
For me coastal should be indicated under the "Habitat type" fields in the CATAL. Move 'Coastal waters'under adequate fields


name: Trophic level of coastal fish communities
_0: SYKE-LU 41, JRC-HT
_5: I (LU) would imagine the indicator uses the Swedish experimental fishing data.
_13: not enough info reported very difficult to discern/analyse
_14: Trophic level of coastal fish communities
_15: State
_16: Foodweb
_18: Simple statistics
_10:
Recent studies state that this indicator is a better indicator of fishing pattern and pressure than of ecosystem state, but this would depend on the type of data  used to calculate it (Shannon et al MEPS 2014) (source: Shannon L, Coll M, Bundy a, Gascuel D, Heymans J, Kleisner K, Lynam C, Piroddi C, Tam J, Travers-Trolet M, Shin Y (2014) Trophic level-based indicators to track fishing impacts across marine ecosystems. Mar Ecol Prog Ser 512:115–140). 

According to our understanding of the indicator it uses experimental fishing data from selected sites, and it is meant to be a state indicator. (To be confirmed with Jens Olsson, the Swedish MSFD fish person and chair of the HELCOM Fish-Pro group.)

_11:
No information available from the Swedish Marine Strategy, beyond: "Fish community's trophic level does not deviate from a base level. If base level cannot be identified, a trend target will be set." 


name: Ratio of non-mature sea trouts
_0: SYKE-LU 47
_14: Proportion of non-mature sea trouts in the sea trout catch
_15: Pressure
_16: Population Ecology
_18: Simple statistics
_10:
This list of Finnish indicators is based on the excel summary sheet made for HELCOM's Roof Report document. Finland's Marine Strategy doesn't spell out which indicators are corresponding to which Commission Decision indicators; in the Roof Report document this is detailed, and this information is followed here.

I (LU) have had to make some educated guesses in filling the catalogue: there is no concise documentation of the operational and proposed indicators available at the time.

Marine sub-divisions or ecological assessments areas: all - I mean all Finland's waters in the case of Finland's indicators


name: Trends in the arrival of new invasive species
_0: SYKE-LU 53
_5: Monitoring of new invasive species.
_6: number of n ew species
_14: Appearance of new invasive species
_15: Pressure
_16: Target Groups
_18: Simple statistics
_19: {Biological control}
_11:
The aim is that no new invasive species will appear. The mid-term aim is to decrease the rate of new invasions.


name: Ratio between invasive and indigenous species in selected well-known groups
_0: SYKE-LU 57
_15: Pressure
_16: Target Groups
_18: Simple statistics
_14:
Ratio between invasive and indigenous species in selected well-known groups (fish, shrimps and mussels)


name: Reproduction capacity of white tailed eagle
_0: SYKE-LU 59
_14: Reporoduction capacity of white tailed eagle
_15: State
_16: Population Ecology
_18: Simple statistics
_13:
are these equivalent (SYKE-LU 59/63/62/64/89)?  Could they be merged and "biodivesity componentns" referred to in the adequate fields


name: Population stucture of hardbottom plant and invertebrate animals
_0: SYKE-LU 71
_10: On a conceptual stage, to be developed by 2018.
_14: Population stucture of hardbottom plant and invertebrate animals
_15: State
_16: Community Structure
_18: Simple statistics
_13:
Are these measuring the same things in the same way? Are they equivalent: SYKE-LU 21/71/77 / is this a single index or are plant and invert. info used separately?


_0: SYKE-LU 80
_15: State
_16: Target Groups
_18: Simple statistics
name:
Number of species mentioned in birds directive and habitat directive that are on the suitable protection level

_14:
Number of species mentioned in birds directive and habitat directive that are on the suitable protection level


_0: SYKE-LU 82
_5: Commercial and recreational catch data
_15: Pressure
_16: Anthropogenic Activities
_18: Simple statistics
name:
Proportion on non-mature sea trout, sander, and whitefish in the commercial and recreational catch along the coast

_14:
Proportion on non-mature sea trout, sander, and whitefish in the commercial and recreational catch along the coast


_0: SYKE-LU 83
_10: Conceptual indicator, details are under development
_15: State
_16: Target Groups
name:
Distribution and abundance of flounder and sea-spawning whitefish fry in shallow sand-bottom habitats

_14:
Distribution and abundance of flounder and sea-spawning whitefish fry in shallow sand-bottom habitats


name: State of typical species and communities in various habitats
_0: SYKE-LU 84
_5: State assessments of selected species and communities
_13: MariLim: SYKE are angiosperms really NOT part of this indicator?
_14: State of typical species and communities in various habitats
_15: State
_16: Target Groups
_11:
Index assessing the state of selected species and communities (fish, macroalgae, benthic invertebrates) in variuos habitats


name: Impacts of anthropogenic under-water noise on marine mammals
_0: SYKE-LU 97
_12: {HELCOM coreset}
_14: Impacts of anthropogenic under-water noise on marine mammals
_15: State
_16: Target Groups
_18: Modelling
_5:
Monitoring and modelling of underwater noise; abundance surveys of marine mammals; mammal habitat modelling. 


name: BTA - Biological Traits Analysis
_0: IMAR-HV 108
_5: Species lists; Abundance/biomass of species; List of functional indicator traits.
_6: N/A
_9: N/A
_13: are these two (IMAR-HV 108 and UHULL-KM 190) calculated in the same way? If so merge
_14: Biological Traits Analysis (BTA)
_15: State
_16: Life Traits
_18: Complex statistics
_4:
No standardised methodology for collection; taxonomic identification preferentially to species level

_10:
BTA is an analytical approach/method for describing functioning based on traits exhibited by members of biological assemblages and its application can be very versatile. It has been applied to diferent systems (freshwater, marine, estuarine, terrestrial), regions (EU and non-EU) and using different biological elements (benthos, fish, plants). Nevertheless it was never approved or considered by any national/international law or convention. In this way, we felt sometimes, difficulty to assign BTA using the MSFD requirements. Please feel free to contact us in case of doubt or if you think that any field has not been completed properly. 

_11:
Biological Traits Analysis (BTA) is an analytical approach aiming to provide a description of multiple aspects of functioning based on features of the biological ecosystem component. It does this by utilising specific species traits as indicators of functioning and examining the occurrence of these traits over assemblages (Bremner et al., 2008).


name: Abundance and distribution each of harbour and grey seals (M3)
_0: Cefas-SN 110; JRC-HT
_4: Coastal surveys
_5: Range and counts: Harbour seals - haul out counts; grey seals - pup counts or moult counts
_12: {OSPAR common indicator}
_14: M3 Abundance and distribution each of harbour and grey seals*
_15: State
_16: Population Ecology
_18: Simple statistics
_8:
Relatively low as seal colonies are onshore; monitoring combined with M5(pup production) and delivering data also for M6(by-catch).

_10:
* This indicator is the result of a merger of two OSPAR common indicators: M1 seal distribution and M3 seal abundance.

_11:
Indicator metric is defined for abundance only. An indicator metric for distribution needs to be defined.
Harbour Seal: Estimated population size, Estimated true population size, Number of haul‐out sites within each assessment unit
Grey seal: Estimated population size (pup counts), Estimated population size (adult counts), Number of breeding sites within each assessment unit


name: Abundance and distribution of cetaceans (M4)
_0: Cefas-SN 111, JRC-HT
_5: Strandings data, distribution, relative abundance and population trends
_8: Various techniques for different species vary from quite cheap to very expensive.
_12: {OSPAR common indicator}
_14: M4 Abundance and distribution of cetaceans*
_15: State
_16: Population Ecology
_18: Simple statistics
_4:
Biological and pathological investigations; visual surveys from vessels or planes; towed hydrophone arrays; static acoustic monitoring; mark-recapture techniques using photo identification.

_10:
*This indicator is the result of a merger of two common indicators: M-2 cetacean distribution range and pattern and M-4 cetacean abundance.

OSPAR Threatened and Declining Species included in indicator: harbour porpoise, bottlenose dolphin.

_11:
Abundance of the population of the cetacean species: abundance to be assessed at the relevant spatial and temporal scale.
Occupancy by the species of an area: occupancy of an area over the range of the species (eg. number of cells occupied) could be easier to assess than to estimate abundance with precision. The entire range needs coverage to evaluate at what point the change noted is significant. Changes in distribution within range can be assessed, although difficult to set targets against which changes should be evaluated. (see Sources for details) 

_13:
Field 'Country' was "Ospar Contracting Parties". This has been removed since it is no country. Please update Data->Settings accordingly.


name: Grey seal pup production (M5)
_0: Cefas - SN 112, JRC-HT
_4: Grey seals pup counts
_5: Number of pups per colony vs size of colony
_11: Pup production is estimated from counts of pups at breeding colonies.
_12: {OSPAR common indicator}
_14: M5 Grey seal pup production
_15: State
_16: Population Ecology
_18: Simple statistics
_8:
Relatively low as seal colonies inshore; monitoring combined with M1 (distributional range) and M3 (abundance)


name: Marine mammals by-catch (M6)
_0: Cefas - SN 113
_4: Bycatch rates
_5: Numbers of bycatch in fishing gear
_6: Percentage of best population estimate
_12: {OSPAR common indicator}
_14: M6 Mortality rate of seals and cetaceans due to bycatch
_15: Pressure
_16: Anthropogenic Activities
_18: Simple statistics
_8:
High if independent observers on board; cheaper methods such as cameras or voluntary reporting by fishermen


name: Species‐specific trends in relative abundance of non‐breeding and breeding marine birds (B1)
_0: Cefas-SN 114; JRC-HT
_5: Time series of annual estimates of abundance of individual species
_6: Percentage
_8: High if aerial and ship-based surveys repeatedly used to capture seasonal variation.
_12: {OSPAR common indicator}
_14: B1 Species-specific trends in relative abundance of non-breeding and breeding marine birds
_15: State
_16: Target Groups
_18: Simple statistics
_4:
Counts of birds or pairs at breeding sites, counts of shorebirds in intertidal areas. Aerial and ship-based surveys for off-shore species.

_11:
The indicator metric is relative abundance: annual abundance as a percentage of the baseline. Species are previously assigned to functional groups.

_13:
Field 'Country' was "Ospar Contracting Parties". This has been removed since it is no country. Please update Data->Settings accordingly.


name: Breeding success of kittiwake (B2)
_0: Cefas-SN 115, JRC-HT
_4: One or two observers visiting a colony and recording progress from laying.
_5: No of chicks fledged per pair at colonies of black-legged kittiwake (Rissa tridactyla).
_6: Breeding success (no. offspring per pair )
_8: Mostly minimal if volunteers used, for professional observers depends on accessibility of colonies.
_10: B2 is an OSPAR Candidate Indicator.
_12: {OSPAR common indicator}
_14: B2 Annual breeding success of kittiwake
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_11:
Annual mean breeding success (no. offspring per pair ) of kittiwake at sampled colonies.
This species is sensitive to changes in food availability and there is good evidence that they are negatively affected by fishing.

_13:
Field 'Country' was "Ospar Contracting Parties". This has been removed since it is no country. Please update Data->Settings accordingly.


name: Breeding success/failure of marine bird species (B3)
_0: Cefas-SN 116; JRC-HT
_4: One or two observers visiting a colony and recording progress from laying.
_5: Annual mean breeding success of marine bird species at colonies.
_6: Percentage of colonies
_8: Mostly minimal if volunteers used, for professional observers depends on accessibility of colonies.
_12: {OSPAR common indicator}
_14: B3 Breeding success/failure of marine bird species
_15: State
_16: Population Ecology
_18: Simple statistics
_11:
‘Annual colony failure rate’ i.e. the percentage of colonies failing per year, per species. The indicator should include all species monitored, but should group species according to the functional groups.


name: By-catch of marine birds (B5)
_0: Cefas - SN 118
_5: Number of birds caught of each species accidentally caught by commercial fishing gear
_6: Estimated mortality
_8: Cost covered by requirement of EU-PoA
_12: {OSPAR common indicator}
_15: Pressure
_16: Anthropogenic Activities
_18: Simple statistics
_4:
Accurate recording by observers, routine submission of data to facilitate analysis, and standard reporting format

_10:
B5 is an OSPAR Candidate Indicator.

"Abundance index of by-caught birds": http://www.sea.ee/marmoni/marmoni_pulk/docs/L47.pdf

_14:
B5 Mortality of marine birds from fishing (bycatch) and aquaculture, Abundance index of by-caught birds


name: Distributional pattern of breeding and non-breeding marine birds (B6)
_0: Cefas - SN 119
_4: Using sample size units (e.g.2kmx2km squares) to measure distributional range
_6: Percentage
_12: {OSPAR common indicator}
_14: B6 Distributional pattern of breeding and non-breeding marine birds
_15: State
_16: Target Groups
_18: Simple statistics
_5:
Distributional pattern of species of marine birds that aggregate in inshore areas, or at onshore breeding or roosting sites

_8:
All colonies to be surveyed periodically as part of census, in addition to annual monitoring programme so additional resources required for this

_10:
B6 is an OSPAR Candidate Indicator.

"Distribution of wintering waterbird species": http://www.sea.ee/marmoni/marmoni_pulk/docs/L39.pdf

"Distribution of wintering waterbirds (multi-species)":  http://www.sea.ee/marmoni/marmoni_pulk/docs/L40.pdf

"Distribution of wintering waterbirds of different feeding guilds (multi-species)": http://www.sea.ee/marmoni/marmoni_pulk/docs/L41.pdf

"Distribution of breeding waterbird species": http://www.sea.ee/marmoni/marmoni_pulk/docs/L42.pdf


name: Abundance of selected fish species and cephalopods (FC1)
_0: Cefas - SN 120a
_4: Data come from scientific fisheries surveys, annually, with standard gear
_5: Size of catchable proportion of fish populations by survey (weight or numbers)
_6: Trend in abundance/biomass
_8: High, but primarily met under existing national programmes. Gap analysis necessary.
_12: {OSPAR common indicator}
_14: FC1 Population abundance/biomass of a suite of selected species
_15: State
_16: Target Groups
_18: Simple statistics
_10:
MariLim: We had to split indicator AZTI-JGR 164 to abundance and biomass to be consistent with other indicators.


name: Body length of demersal fish and elasmobranchs (FC3)
_0: Cefas - SN 122, JRC-HT
_5: Size based indicator to measure the life history composition of the fish community
_6: Trend
_8: High, but primarily met under existing national programmes. Gap analysis necessary.
_10: FC3 is no longer in the list of OSPAR Common Indicators.
_12: {OSPAR common indicator}
_14: FC3 Mean maximum length of demersal fish and elasmobranchs
_15: State
_16: Population Ecology
_18: Simple statistics
_4:
Scientific fisheries surveys that sample the whole fish community, annually in same area with standard gear


name: Typical species composition (BH1)
_0: Cefas - SN 124, JRC-HT
_5: Species lists and distribution.
_8: High, but overlap with BH5 and BH2
_10: BH1 is one of the prioritised OSPAR Candidate Indicators.
_12: {OSPAR common indicator}
_14: BH1 Typical species composition
_15: State
_16: Community Structure
_19: {Bioremediation of waste}
_4:
Depends on habitat type; optical non-destructive methods (underwater video), grabs or corers, dredges or beam trawls.

_13:
MariLim: Cefas - Please specify this indicator in terms of indicator description, are the values for the different biological components combined somehow? Is it then a multimetric indicator?


name: Physical damage of predominant and special habitats (BH3)
_0: Cefas - SN 126, JRC-HT
_4: Largely dependent upon data already available.
_8: Low
_12: {OSPAR common indicator}
_14: BH3 Physical damage of predominant and special habitats
_15: State
_16: Biotope Features
_18: Simple statistics
_5:
Distribution and sensitivity of habitats components (selection of habitats based on pre-defined criteria);
Distribution and intensity of human activities and pressures causing physical damage (EIAs and VMS data, Data Collection Framework);
Exposure matrices combining pressure intensity and habitat sensitivity.

_10:
BH3 is one of the prioritised OSPAR Candidate Indicators, proposed for promotion.
This indicator should not overlap with assessments and outputs already addressed by BH2 - MMI.

_11:
BH3 is measuring the surface area of damaged habitat, by analysing the state of habitats and the distribution and intensity of anthropogenic pressures impacting upon them. 
This indicator is particularly useful to target larger sea areas with relatively low effort.


name: Size-frequency distribution of bivalve or other sensitive/indicator species (BH5)
_0: Cefas - SN 128
_5: Number of individuals per size class
_8: High
_10: BH5 is an OSPAR Candidate Indicator.
_12: {OSPAR common indicator}
_14: BH5 Size-frequency distribution of bivalve or other sensitive/indicator species
_15: State
_16: Indicator Species
_18: Simple statistics
_4:
Varied depending on habitat types and pressures; vessels scuba diving, equipment (box core samplers, grabs, dredges), laboratories for analysis, qualified personnel.


name: MCI - Microplankton Community Index (PH1/FW5)
_0: Cefas - SN 129, JRC-HT
_4: Continuous plankton recorder survey
_5: Plankton abundance or biomass (per taxa).
_6: Ratios of plankton (%)
_8: Low
_10: Can be calculated from various samplers and a range of techniques.
_12: {OSPAR common indicator}
_14: PH1/FW5 Microplankton Community Index (MCI)
_15: State
_16: Life Traits
_18: Simple statistics
_11:
Indicator based on the ratio of functional groups (in terms of life-form pairs). Ratios of plankton can provide information on ecosystem structure and flow. Combination of life-form pairs will depend on the habitat and the objective of the indicator (regional adaptation will be needed). Proposed plankton life-form pairs differ per MSFD Descriptor and Pressure (see Sources for details):
D1: Diatoms/Dinoflagellates; Large copepods/Small copepods; Copepod grazers/Non‐copepod Grazers
D1.7: All lifeform pair combinations
D4: Gelatinous zooplankton/Fish larvae; Copepods/Phytoplankton; Holoplankton/Meroplankton
D5: Diatoms (Si users)/ Dinoflagellates (non‐Si users); Ciliates/Microflagellates; Psuedo‐nitzschia spp./Potentially toxin Producing dinoflagellates
D6: Holoplankton/Meroplankton


name: Plankton biomass and/or abundance (PH2)
_0: Cefas - CL 130a, JRC-HT
_5: Phytoplankton and zooplankton abundance and/or biomass as appropriate.
_8: Low
_11: Indicator metrics can vary by country (see Sources for details).
_12: {OSPAR common indicator}
_14: PH2 Plankton biomass and/or abundance
_15: State
_16: Target Groups
_18: Simple statistics
_19: {Climate regulation}
_4:
Can be calculated from various samplers and a range of techniques:
microscopy, flow cytometry or Continuous Plankton Recorder survey.

_10:
Plankton biomass and plankton abundance are measured in different ways both within and between member states; however relative changes (trends) in each time‐series can be compared between datasets.

Phytoplankton biomass: Operational
Phytoplankton abundance: Already developed but not operational yet.
Zooplankton abundance or biomass: Already developed but not operational yet.


name: Reproductive success of marine birds in relation to food availability (FW1)
_0: Cefas - CL 132, JRC-HT
_4: One or two observers visiting a colony and recording progress from laying.
_6: Percentage of colonies
_8: Mostly minimal if volunteers used, for professional observers depends on accessibility of colonies.
_12: {OSPAR common indicator}
_14: FW1 Reproductive success of marine birds in relation to food availability
_15: State
_16: Population Ecology
_18: Simple statistics
_5:
Annual mean breeding success of marine bird species at colonies (no. chicks fledged per pair). 
Depending in species and area, the parameter may be derived from data hatching success (i.e. number of eggs hatched per pair).
Hatching/fledging success is monitored for a selection of species sensitive to changes in pressures.

_10:
FW1 is an OSPAR Candidate Indicator.

The FW1 indicator is intended to complement another proposed indicator on annual
breeding success of kittiwakes in relation to sandeel availability (under 1.3.1), in order to keep a watching-brief on the population condition of other species.

_11:
‘Annual colony failure rate’ i.e. the percentage of colonies failing per year, per species (see Sources Cook et al. 2012).


name: Production of phytoplankton (FW2)
_0: Cefas - CL 133, JRC-HT
_4: HPLC, flouresence, or remote sensing
_6: C m-2 yr-1
_8: Low
_12: {OSPAR common indicator}
_14: FW2 Production of phytoplankton
_15: State
_16: Production
_18: Simple statistics
_5:
Phytoplankton Biomass (carbon from biovolume, particulate organic cardon, or chlorophyll concentration)

_10:
Can be calculated from various samplers and a range of techniques.

FW2 is an OSPAR Candidate Indicator, proposed for promotion.

_11:
In a food web context, primary production is an appropriate measure since it is a flux indicator of the potential for higher trophic levels to produce biomass. Moreover, considering primary production at different size ranges could provide information on the trophic efficiency between different parts of the food web.
Parameters to be measured are phytoplankton production and the P:B ratio (P:B ratio gives an indication of the functioning of the foodweb).


name: Biomass and abundance of functional groups (FW7)
_0: Cefas - CL 137a, JRC-HT
_8: High, but primarily met under existing national programmes. Gap analysis necessary.
_10: FW7 is an OSPAR Candidate Indicator.
_12: {OSPAR common indicator}
_14: FW7 Biomass and abundance of functional groups
_15: State
_16: Life Traits
_18: Simple statistics
_4:
Scientific fisheries surveys that sample the whole fish community, annually in same area with standard gear.

_5:
Fish species composition and abundance (number or weight) per haul/survey. Biomass of fish can be calculated from abundance data using existing scientific survey data.
Biomass of invertebrates can be estimated from abundance data and length-weight distributions of species.
Species will need to be assigned to feeding groups or trophic guilds, based on information from dietary analyses.

_11:
Abundances of fishes and benthic invertebrates by functional group. Fish (and benthic species) abundance and biomass are expected to decrease in exploited populations.
Contrasting other indicators for food web ecological status, this indicator relates to absolute biomasses.


name: Changes in the distribution of biomass and species over trophic levels or body size (BTS) (FW8)
_0: Cefas - CL 138, JRC-HT
_8: High, but primarily met under existing national programmes. Gap analysis necessary.
_10: FW8 is an OSPAR Candidate Indicator. Can also be assessed through modelling.
_12: {OSPAR common indicator}
_14: FW8 Changes in the distribution of biomass and species over trophic levels or body size (BTS)
_15: State
_16: Foodweb
_18: Simple statistics
_4:
Scientific fisheries surveys that sample the whole fish community, annually in same area with standard gear

_5:
Mean trophic levels of species will need to be estimated on a regional/sub-regional scale.
Catchable proportion of fish+invertebrate populations by survey (weight or numbers).

_11:
Biomass Trophic Spectrum (BTS) is an ecosystem-based indicator that allows a more holistic view of the food web structure than species/population indicators.
Abundances per species or group (usually expressed in tons/km2) are distributed on a range of trophic levels around the mean trophic level of the species or group, and according to the variability between individuals. The trophic level(TL) expresses the position of an organism in a food web, and is estimated using diet data. Mean TLs can be derived either (and preferably) from local gut contents and isotopes analyses, or from trophic models such as Ecopath, or by using estimates from online data portals, such as FishBase. BTS are usually built using an empirical smooth function distributing each population or group across TLs according to a lognormal distribution whose standard error increases with TLs. The BTS is the sum of the distributions for all species or groups.


name: Energy flows and transfer efficiencies among trophic levels or functional groups
_0: Cefas - AR 139
_5: fitted EcoPath model / production at trophic level or functional group
_8: low
_14: energy flows and transfer efficiencies among trophic levels or functional groups
_15: State
_16: Foodweb
_18: Modelling
_13:
MariLim: Please specify this indicator a little bit more in indicator description, it is hard to understand, what this indicator is rally calculating.


Shouldn't this indicator be under Catalogue of model derived indicators under WP4? If it is already there remove here. If not, I suggest to add it to WP4CAT instead


name: Strength of conventional bottom-up effect in marine size spectrum
_0: Cefas - AR 140
_5: size spectrum
_14: strength of conventional bottom-up effect in marine size spectrum
_15: State
_16: Population Ecology
_13:
MariLim: Please specify this indicator a little bit more in indicator description, it is hard to understand, what this indicator is really calculating and how it differs from Cefas - AR 142 (besides different pressures that you have chosen)


name: Strength of top-down cascade in marine size spectrum
_0: Cefas - AR 141
_5: size spectrum
_14: strength of top-down cascade in marine size spectrum
_15: State
_16: Population Ecology
_13:
MariLim: Please specify this indicator a little bit more in indicator description, it is hard to understand, what this indicator is really calculating.


name: Strength of bottom-up cascade in marine size spectrum
_0: Cefas - AR 142
_5: size spectrum
_14: strength of botttom-up cascade in marine size spectrum
_15: State
_16: Population Ecology
_4:
e.g., Quinones, R. A., Platt, T., Rodrıguez, J., 2003. Patterns of biomass-size spectra from oligotrophic waters of the Northwest Atlantic. Progress in Oceanography 57, 405–427.  Sprules, W. G., Goyke, A. P., 1994. Size-based structure and production in the pelagia of Lakes Ontario and Michigan. Canadian Journal of Fisheries and Aquatic Sciences 51, 2603–2611. 

_13:
MariLim: Please specify this indicator a little bit more in indicator description, it is hard to understand, what this indicator is really calculating and how it differs from Cefas - AR 140 (besides different pressures that you have chosen)


name: Distributional range of selected fish species
_0: Cefas - CL 148
_8: High, but primarily met under existing national programmes. Gap analysis necessary.
_14: Distributional range of fish (sensitive species)
_15: State
_16: Target Groups
_18: Simple statistics
_5:
Proportion of sampled ICES rectangles (for shelf seas) or depth bands (for shelf edge) in which the species occurs. 

_6:
Recovery trend-based metric for each species: current year value should be in the upper 25 percentile of all metric values in reference period (full time-series)


name: Population abundance of a suite of selected species
_0: Cefas - CL 150
_8: High, but primarily met under existing national programmes. Gap analysis necessary.
_14: Population abundance of a suite of selected species
_15: State
_16: Indicator Species
_18: Simple statistics
_5:
log abundance estimates standardised to a defined area appropriate to the survey for a suite of senstive species

_6:
Recovery trend-based metric for each species: current year value should be in the upper 25 percentile of all metric values in reference period (full time-series)


name: Population biomass of a suite of selected species
_0: Cefas - CL 151
_8: High, but primarily met under existing national programmes. Gap analysis necessary.
_14: Population biomass of a suite of selected species
_15: State
_16: Target Groups
_18: Simple statistics
_5:
log biomass estimates (directly weighed or from LW relationships) standardised to a defined area appropriate to the survey for a suite of senstive species

_6:
Recovery trend-based metric for each species: current year value should be in the upper 25 percentile of all metric values in reference period (full time-series)


name: Species diversity (Hills index) for fish and invertebrates
_0: Cefas - CL 153
_5: species composition, abundance or biomass data
_8: High, but primarily met under existing national programmes. Gap analysis necessary.
_14: Hills N1 indicator of species diversity
_15: State
_16: Community Structure
_18: Simple statistics
_11:
Catchable proportion of fish+invertebrate populations by survey (weight or numbers) standardised to a defined area appropriate to the survey for a suite of senstive species

_13:
MariLim: Cefas - Please specify this indicator in terms of biological component, you mentioned invertebrates in description, but not in biological component. Please correct this accordingly.


name: WFD SHWAP - Schleswig-Holstein Wadden Sea Assessment of Phytobenthos
_0: MariLim-KF 35
_4: aerial survey and direct GPS- mapping
_6: EQR (unitless)
_14: Schleswig-Holstein Wadden Sea Assessment of Phytobenthos (SHWAP)
_15: State
_16: Biotope Features
_19: {Climate regulation} {Disturbance prevention or moderation} {Bioremediation of waste}
_10:
This multivatiate system combines  indicators, listed  partly separately (see  indicator MariLim-KF_27 and MariLim-KF_72).

_11:
Multimetric assessment system (5 metrics) using total areal extent, areal extent of a specific coverage degree and species composition for intetidal eelgrass  and total areal extent, areal extent of a specific coverage degree of intertidal opportunistic green algae


name: WFD BALCOSIS - Macrophyte index
_0: MariLim-KF 39
_4: depth limits by video or diving, coverage and biomass data by diving
_6: EQR (unitless)
_15: State
_16: Biotope Features
_19: {Climate regulation} {Disturbance prevention or moderation}
_10:
This multivatiate system combines indicators, listed partly separately (see  indicator Marilim-KF_27 and Marilim-KF_72)

_11:
Multimetric assessment system (7 metrics) using depth limit of sensitive species and species composition (coverage and biomass) data in separate habitats (eelgrass beds, Fucus and red algae phytal).

_14:
Assessment system for macroalgae and angiosperms in the outer coastal waters of the Baltic (BALCOSIS)


name: WFD ELBO - German Macrophyte index
_0: MariLim-KF 40
_4: depth limits by video or diving, coverage data by diving
_5: species-specific depth limits, species-specific cover data, species composition
_6: EQR (unitless)
_14: Assessment system for angiosperms and charophytes in the inner coastal waters of the Baltic (ELBO)
_15: State
_16: Biotope Features
_19: {Climate regulation} {Disturbance prevention or moderation}
_11:
Multimetric index (3 metrics) assessing EQR values for BQE Angiosperms and Macroalgae using depth limits and species composition (coverage) data


name: MarBIT - Marine Biotic Index Tool
_0: MariLim-KF 55
_4: grab or frame sampling for in- and epifaunal communities
_6: EQR (unitless)
_14: Marine Biotic Index Tool (MarBIT)
_15: State
_16: Life Traits
_18: Simple statistics
_5:
species composition, abundance data, autecological species information (sensitive/tolerante classification)

_11:
Multimetric index  (4 metrics) assessing EQR values for BQE Benthic invertebrates based on for taxonomical composition (TSI),  log-normal abundance curves and a classification of sensitive and tolerant species on basis of abundance data and autecological species information


name: Areal extent of intertidal opportunistic green algae
_0: MariLim-KF 72
_4: aerial survey (several times during summer)
_5: Areal extent data
_6: % of whole intertidal area
_10: This is one parameter/metric/method of a multivariate system (see indicator Marilim-KF_35)
_14: Areal extent of intertidal opportunistic green algae
_15: State
_16: Indicator Species
_18: Simple statistics
_19: {Bioremediation of waste} {Biological control} {Leisure and recreation} {Aesthetic experience}
_11:
Aereal extent of intertidal opportunistic green algae compared to the reference area of opportunistic green algae extent

_13:
leave as unique indicator or consider under a broader group? 
KF: I would suggest to keep it as a unique indicator, but this should finally be discussed at the Bilbao meeting.


name: WFD German Ecological phytoplankton assessment with Chl a and Phaeocystis blooms
_0: MariLim-KF 108
_5: chl a measurements, species composition, cell counts
_6: EQR (unitless)
_14: Ecological phytoplankton assessment with Chl a and Phaeocystis blooms
_15: State
_16: Community Structure
_19: {Biological control}
_11:
Multimetric index (2 metrics) assessing EQR values for BQE Phytoplankton using Chl a concentrations and frequency + intensity of Phaeocystis blooms  (between mrc and sep)


name: WFD German Ecological phytoplankton assessment with Chl a and biovolume
_0: MariLim-KF 109
_5: chl a measurements, biovolume measurements, species composition, cell counts
_6: EQR (unitless)
_14: Ecological phytoplankton assessment with Chl a and biovolume
_15: State
_16: Community Structure
_19: {Climate regulation}
_11:
Multimetric index (2 metrics) assessing EQR values for BQE Phytoplankton using Chl a concentrations and biovolume  (yearly means)


name: Depth limit of spermatophytes
_0: MariLim-KF 112
_4: assessment of coverage by video or diving
_5: spermatophyte cover (%) per water depth
_6: m
_10: This is one parameter/metric/method of a multivariate system (see indicator Marilim-KF_40)
_14: Depth limit of spermatophytes
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
Spermatophyte cover (%) with information on water depth and position, the 10 % spermatophyte cover value marks the depth limit

_19:
{Climate regulation} {Disturbance prevention or moderation} {Leisure and recreation} {Aesthetic experience}


name: Depth limit of charophytes
_0: MariLim-KF 113
_4: assessment of coverage by video or diving
_5: charophyte cover (%) per water depth
_6: m
_10: This is one parameter/metric/method of a multivariate system (see indicator Marilim-KF_40)
_14: Depth limit of charophytes
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
Charophyte cover (%) with information on water depth and position, the 10 % charophyte cover value marks the depth limit


name: Depth limit of attached perennial macroalgae
_0: MariLim-KF 114
_4: assessment of coverage by video or diving
_5: Perennial macroalgae (substrate specific) cover (%) per water depth
_6: m
_14: Depth limit of attached perennial macroalgae
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
Perennial macroalgae cover (%) with information on water depth and position, the 10 % perennial macroalgae cover value marks the depth limit


name: Depth limit of Fucus spp.
_0: MariLim-KF 115
_4: assessment of coverage by video or diving
_5: Fucus (substrate specific) cover (%) per water depth
_6: m
_10: This is one parameter/metric/method of a multivariate system (see indicator Marilim-KF_39)
_14: Depth limit of Fucus spp.
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
Fucus cover (%) with information on water depth and position, the 10 % Fucus cover value marks the depth limit

_19:
{Climate regulation} {Disturbance prevention or moderation} {Leisure and recreation} {Aesthetic experience}


name: Macrophyte species reduction (reduced species list)
_0: MariLim-KF 117
_4: macrophyte frame sampling by diving
_5: species composition
_6: % of reference species list
_10: This is one parameter/metric/method of a multivariate system (see indicator Marilim-KF_39)
_14: Macrophyte species reduction (reduced species list)
_15: State
_16: Community Structure
_18: Simple statistics
_11:
Assessment of the species number in macroalgae communities compared with a reference species list (only steady and characteristic key-species for the area/habitat are regarded)


name: HPI - Helgoland Phytobenthic Index
_0: MariLim-KF 119
_4: Assessment of depth limits by diving and cover assessment by frames.
_5: species-specific depth limits, species composition, cover data
_6: EQR (unitless)
_10: WFD German Macroalgae index
_14: Helgoland Phytobenthic Index (HPI)
_15: State
_16: Biotope Features
_11:
Multimetric index  (4 metrics) assessing EQR values for BQE Macroalgae based on depth limit of sensitive species, species cover of Fucus spp and Ulva and species composition (reduced species list).


name: Species diversity and landscape quality index
_0: MariLim-KF 121
_6: % of target value
_10: National Strategy on Biological Diversity
_14: Species diversity and landscape quality
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_5:
percentage of population sizes (number of territories or breeding pairs) of 10 different seabird species

_11:
Index calculating population changes in selected bird species (representative of the coast and sea landscape, habitat types)


name: Endangered species index
_0: MariLim-KF 122
_6: % of different Red List categories
_14: Endangered species
_15: State
_16: Target Groups
_18: Simple statistics
_5:
The underlying data are the assessments of species in Red List categories. The final index is a single figure representing the degree of endangerment for all assessed species.

_11:
Index (percentage index) based on the rankings of selected species groups in  specific Red List categories (German Red Lists of endangered species)


name: Conservation status of habitats and species
_0: MariLim-KF 123
_6: % of target value
_14: Conservation status of Habitats Directive habitats and species
_15: State
_16: Target Groups
_18: Simple statistics
_11:
Index (percentage index) of assessments of conservation status of Habitats Directive Annex I habitat types and Annex II, IV and V species in the biogeo- graphical regions of Germany


name: Number of species of Black List of Invasive Alien Species
_0: MariLim-KF 124
_6: number of species
_14: Black List of Invasive Alien Species
_15: Pressure
_16: Target Groups
_18: Simple statistics
_11:
Number of species in the Black List of Invasive Alien Species, stated separately for the action list and the management list


name: Ratio of area of protected area/total area
_0: MariLim-KF 125
_6: % of total area
_14: Total size of protected areas
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
Total size of strictly protected areas (nature conservation areas and national parks) as a percentage of the German land surface


name: Ratio of surface water bodies in good ecological status
_0: MariLim-KF 126
_6: % of total water bodies
_14: Ecological status of surface waters
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
Proportion of surface water bodies – sections of rivers, streams, lakes, transitional waters and coastal waters – having good or high ecological status as a percentage of all assessed water bodies


name: AETV - Estuary Typology Procedure
_0: MariLim-KF 128
_4: Van Veen grabs
_5: species composition, abundance data, autecological species information
_6: EQR (unitless)
_10: WFD AETV - German Estuary Typology Procedure
_14: Estuary Typology Procedure (AETV)
_15: State
_16: Life Traits
_18: Simple statistics
_11:
Multimetric index  (4 metrics) assessing EQR values for BQE Benthic invertebrates combining species number (richness),  abundance and autecological species information

_13:
(Heliana) are we keeping estuarine only indicies here? Most from WFD I have not included, only if they were also applicable for Coastal Waters.


name: Distributional range of whales
_0: AZTI-JGR 125
_14: [whales] Distributional range
_15: State
_16: Target Groups
_19: {Leisure and recreation} {Aesthetic experience}
_11:
distribution based on sea mammals stranding, bycatch data, opportunistic sightings and monitoring surveys or coastal sightings


name: Abundance of cephalopds
_0: AZTI-JGR 154a
_14: [Cephalopods] population abundance and/or biomass
_15: State
_16: Target Groups
_18: Simple statistics
_19: {Food provision} {Leisure and recreation} {Aesthetic experience}
_10:
MariLim: We had to split indicator AZTI-JGR 154 to abundance and biomass to be consistant with other indicators.


name: Ratio of fish species in good ecological status
_0: AZTI-JGR 158
_13: AZTI to complete: not enough info to understand what is this indicator ("Description" fields empty)
_14: [Demersal fishes] percent of species in good ecological status
_15: State
_16: Target Groups
_18: Simple statistics
_19: {Leisure and recreation}
_10:
Each species has a criteria for reaching the good ecological status. This criteria depends on the kind of the species: opportunistic (r-strategy), vulnerable (or k–strategy).


name: Abundance of demersal elasmobranchs - representation for georeferenced data (GIS)
_0: AZTI-JGR 160
_13: is this the same as AZTI-JGR 115?
_14: [Demersal elasmobranchs] representation for georeferenced data (GIS)
_15: State
_16: Target Groups
_19: {Food provision} {Leisure and recreation} {Aesthetic experience}
_10:
AZTI-JGR 115 is D1C1 Species distribution 1.1.1/1.1.2 and AZTI-JGR 160 is D1C2 Population size 1.2.1


name: Abundance of toxic phytoplankton taxa
_0: AZTI-JGR 162
_5: count of species from toxic taxa
_10: count of species from toxic taxa
_14: [phytoplankton] abundance of toxic taxa
_15: State
_16: Indicator Species
_18: Simple statistics
_19:
{Food provision} {Bioremediation of waste} {Biological control} {Leisure and recreation} {Aesthetic experience}


name: Abundance of whales
_0: AZTI-JGR 168
_5: density based on sightings
_14: [whales] density based on sightings
_15: State
_16: Target Groups
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_13:
should this be grouped under abundance? (and sighttings indicated under methodology): density based on sightings


name: Body length distribution of sea-turtles (longest shell)
_0: AZTI-JGR 178a
_15: State
_16: Population Ecology
_19: {Leisure and recreation} {Aesthetic experience}
_14:
[sea-turtles] demographic characteristics, longest shell, fecundity rate, mortality rate, genetic structure


name: Presence rank of phytoplankton
_0: AZTI-JGR 181
_14: [Phytoplankton] rank of the percentage of sites at which the presence or absence of each taxon
_15: State
_16: Community Structure
_18: Simple statistics
_11:
For each taxon, percentage of sites where it appears is calculated. For taxon with highest presence (more percentages of sites), we give it range 1, for second highest frequent taxon, range 2...

_13:
the name seems incomplete it is not easy to undersatnd what it uses. The name is also like this in the original file submitted. See AZTI-JGR 183 / move info to "Biodiv. Comp." fields


name: Presence rank of zooplankton taxa
_0: AZTI-JGR 184
_14: [Zooplankton] rank of the percentage of sites at which the presence or absence of each taxon
_15: State
_16: Community Structure
_18: Simple statistics
_11:
For each taxon, percentage of sites where it appears is calculated. For taxon with highest presence (more percentages of sites), we give it range 1, for second highest frequent taxon, range 2...

_13:
the name seems incomplete it is not easy to undersatnd what it uses. The name is also like this in the original file submitted. See AZTI-JGR 181 / move info to "Biodiv. Comp." fields


name: Demographic characteristics of mammals
_0: AZTI-JGR 186
_14: [Mammals] demographic characteristics
_15: State
_16: Population Ecology
_19: {Leisure and recreation} {Aesthetic experience}
_5:
Multimetric index with: size at first maturity, fecundity rate, survival rate, new born survival rate, juvenile survival rate, birth rate, population growth rate, birth interval and stomach contents based on stranding, bycatch and survey data


name: Productivity of seabirds (annual breeding success)
_0: AZTI-JGR 187
_14: [seabirds] Breeding success (annual productivity)
_15: State
_16: Production
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_10:
"Breeding success: clutch and brood size of breeding species": http://www.sea.ee/marmoni/marmoni_pulk/docs/L43.pdf

_11:
(The Marmoni indicator:)
This is a set of single species indicators and it reflects breeding success and productivity of the particular species. Indicator has two values:
1. clutch size or number of eggs per clutch laid
2. number of juveniles per breeding female.


name: Survival rate of birds
_0: AZTI-JGR 189
_14: [seabirds] Survival rate
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_13:
MariLim: Please specify, what this indicator exactly is. Description, data used for calculation, ...


name: Index of shape complexity
_0: AZTI-JGR 223
_5: [Infralittoral soft bottom habitats]
_14: index of shape complexity
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
Index calculating the sum of the perimeters of all polygons of rocky habit" to the square root of the "area occupied"

_13:
MariLim: An index for rocky habitat which is calculated for infralittoral soft bottom habitats. Must be a mistake? Pease delete infralittoral soft bottom habitats.


name: Perimeters (mean) of rocky habitats
_0: AZTI-JGR 224
_5: [Infralittoral soft bottom habitats]
_14: mean of the perimeters of all polygons of rocky habitat
_15: State
_16: Biotope Features
_18: Simple statistics
_13:
MariLim: habitat in indicator name, metadata settings, and field 'data requirements' do not correspond 


name: Ratio perimeters/areal extent of rocky habitats
_0: AZTI-JGR 226
_5: [Infralittoral soft bottom habitats]
_15: State
_16: Biotope Features
_18: Simple statistics
_13:
Habitat assignment unclear: The name states rocky habitats, the data requirements state: Infralittoral soft bottom habitats

_14:
patch boundary density (ratio of "sum of the perimeters of all polygons of rocky habitat" to "area occupied")


name: Patch size standard deviation
_0: AZTI-JGR 227
_5: [Infralittoral soft bottom habitats]
_14: patch size standard deviation
_15: State
_16: Biotope Features
_18: Simple statistics
_13:
MariLim: habitat requirements in field 'data requirements' is not the same as the chosen habitat type in metadata settings


name: Perimeters (sum) of rocky habitats
_0: AZTI-JGR 228
_5: [Infralittoral soft bottom habitats]
_14: sum of the perimeters of all polygons of rocky habitat
_15: State
_16: Biotope Features
_18: Simple statistics
_13:
ariLim: habitat in indicator name, metadata settings, and field 'data requirements' do not correspond


name: Areal extent of infralittoral rocky biogenic habitats
_0: AZTI-JGR 234
_14: infralittoral rocky biogenic habitat area
_15: State
_16: Biotope Features
_18: Simple statistics
_19: {Leisure and recreation}
_13:
consider splitting informations across adequate fields in the catalogue ("Habitat" fields) and simplify name


name: Areal extent of dead Posidonia oceanica meadows
_0: AZTI-JGR 239
_11: Surface of dead meadows (Posidonia oceanica).
_14: Surface of dead meadows (Posidonia oceanica)
_15: State
_16: Biotope Features
_18: Simple statistics
_19:
{Disturbance prevention or moderation} {Bioremediation of waste} {Leisure and recreation} {Aesthetic experience}


_0: AZTI-JGR 241
_15: State
_16: Biotope Features
_18: Simple statistics
name:
Frequency of occurrence of habitats per square (in those cases without spatial continuity in cartography)

_14:
[Habitat] frequency of occurrence per square (in those cases without spatial continuity in cartography)


name: Species diversity (Shannon index)
_0: AZTI-JGR 251
_14: Shannon diversity index
_15: State
_16: Community Structure
_18: Simple statistics
_13:
MariLim: AZTI - Please specify this indicator in terms of indicator description, data requirements and biological components. Which diversity indices is it and are indices of different components combined? Is it then a multimetric index? What is the difference to AZTI-JGR 253?


name: Species diversity (Shannon index) of selected habitats
_0: AZTI-JGR 253
_11: circalittoral and bathial soft bottom
_14: species diversity (Shannon)
_15: State
_16: Community Structure
_18: Simple statistics
_13:
MariLim: AZTI - Please specify this indicator in terms of indicator description, data requirements and biological components. Is it only referring to benthic invertebrates or are fish and invertebrates diversity indices somehow combined. Is it then a multimetric index?


name: CYMOX Index for lagoons
_0: AZTI-JGR 262, JRC-HT
_6: EQR [0-1]
_15: State
_16: Biotope Features
_18: Complex statistics
_10:
The ecological status of sites obtained applying CYMOX correlated significantly with the environmental gradient, validating its adequacy to reflect ecosystem health. 
The metrics used are relevant for different levels of biological organisation, including the physiological (i.e. nutrient content, stable isotopic signals), the individual (i.e. shoot size), the population (i. e. root weight ratio) and the community (i.e. epiphyte load) levels, and with some metallic pollution indicators as well. This represents a large amount of biological information that can eventually help in the diagnosis of specific stressors causing environmental impairment.

_11:
The CYMOX index is a multimetric index, constituted by 10 metrics encompassing the physiological (δ15N, δ34S, % N, % P content of rhizomes), individual (shoot size), population (root weight ratio), and community (epiphytes load) organization levels, and some metallic pollution descriptors (Cd, Cu and Zn content of rhizomes). These metrics are integrated into a single index (CYMOX) using the scores of the sites on the first axis of a PCA. These scores are reduced to a 0–1 (Ecological Quality Ratio) scale by referring the values to the optimal (reference) and worst (most degraded) conditions.
CYMOX index is a biotic index that is applied only to habitats  with the seagrass Cymodocea nodosa.

_14:
[Lagoons] composition and abundance of macroalgae and angiosperm (richness, diversity, percentage of opportunistic species, percentage of sensitive species, CYMOX index)


name: Abundance and composition of riparian vegetation
_0: AZTI-JGR 263
_11: Abundance and composition of riparian vegetation in lagoons
_14: [Lagoons] composition and abundance of riparian vegetation
_15: State
_16: Biotope Features
_18: Simple statistics
_13:
MariLim: Please specify the difference to Indicators Abundance ... or Species diversity ... - What is exactly calculated? To which biological component this is connected (we choose angiosperms). Is it connected to seabed or land vegetation. If it is land vegetation please delete this indicator


name: Abundance, composition and age structure of fishes in lagoons
_0: AZTI-JGR 264
_10: Done!
_14: [Lagoons] composition, abundance and age structure of fishes
_15: State
_16: Population Ecology
_19: {Food provision} {Leisure and recreation}
_13:
"(it is proposed to develop Index of Biotic Integrity similar to Sostoa et al., 2003)" -  add this to comments - remove from "Indicator name" field


name: Density of Pinna nobilis
_0: AZTI-JGR 266a
_11: Pinna nobilis density.
_14: [Pinna nobilis] density, age-frequency distribution and population demographics
_15: State
_16: Indicator Species
_18: Simple statistics
_10:
MariLim: We had to split indicator AZTI-JGR 266 in its three parameters to be consistant with other indicators. 
JRC: To be checked, because it is not clear how the metrics in the original indicator name are used, together or separately.


name: Spatio-temporal variation of structural descriptors of Posidonia oceanica seagrass
_0: AZTI-JGR 270
_14: spatio-temporal variation of structural descriptors of Posidonia oceanica seagrass
_15: State
_16: Biotope Features
_13:
MariLim: AZTI-JGR Please specify this indicator in terms of indicator description, data requirements, now we have not enough info to understand if this is a multimetric index or several indicators used separately.

_19:
{Climate regulation} {Disturbance prevention or moderation} {Bioremediation of waste} {Leisure and recreation} {Aesthetic experience}


name: Abundance and composition of functional groups in selected habitats
_0: AZTI-JGR 281, AZTI-JGR 277, JRC-HT
_5: Species composition and abundance data, species-specific functional group definition
_14: composition and abundance of functional groups
_15: State
_16: Life Traits
_11:
Abundance and species composition of selected functional groups in circalittoral and bathial soft bottom habitats

_13:
MariLim: Please specify the difference to indicators with abundance ... or species diversity ... - What is exactly calculated? To which biological component is it connected (we choose benthic invertebrates)


name: Abundance of keystone species or associated species
_0: AZTI-JGR 282
_5: [Infralittoral soft bottom habitats]
_14: density of keystone species or associated species
_15: State
_16: Indicator Species
_18: Simple statistics
_13:
MariLim: AZTI-JGR the indicator description is to unprecise. Please specify to which biological components this applies and how the indicator is calculated (per habitat or per biological component, ...)


name: Biomass of functional groups
_0: AZTI-JGR 294
_14: relative biomass of functional groups
_15: State
_16: Production
_18: Simple statistics
_19: {Bioremediation of waste}
_5:
Samples from Circalittoral and depth habitats (maerl, coraline, soft bottom and circalittoral rocky habitats)


name: Species richness of birds (in the Important Bird Areas network)
_0: AZTI-JGR 297
_10: Richness
_14: Biodiversity of birds in the Important Bird Areas network
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_13:
MariLim: AZTI - Please specify this indicator in terms of indicator description and biological component


name: Areal extent of biogenic/vulnerable habitats
_0: AZTI-JGR 319
_10: They are independients
_14: Area occupied by biogenic/vulnerable habitat
_15: State
_16: Biotope Features
_18: Simple statistics
_13:
Just area accupied or should it be considered a new indicator since it is a specific type biogenic/vulnerable (not possible to indicate in our other general fileds)? There are other examples similar - check and decide

_19:
{Disturbance prevention or moderation} {Bioremediation of waste} {Leisure and recreation} {Aesthetic experience}


name: Biomass (per unit of surface) of structuring/engineering species (per habitat)
_0: AZTI-JGR 322b
_10: AZTI-JGR 278,280,286 could be merged (D1), but AZTI-JGR 322 is D6
_14: biomass or abundance (per unit of surface) of structuring/engineering species (per habitat)
_15: State
_16: Biotope Features
_18: Simple statistics
_13:
MariLim: AZTI, please specify this indicator in terms of the indicator description. Also add all relevant taxonomic groups, not only the too general "Angiosperms"/alternatively make the indicator name more specific

_19:
{Disturbance prevention or moderation} {Bioremediation of waste} {Leisure and recreation} {Aesthetic experience}


name: Species diversity of benthic communities
_0: AZTI-JGR 329
_11: benthic communities
_14: diversity of benthic communities
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Bioremediation of waste} {Leisure and recreation}
_13:
MariLim: AZTI - Please specify this indicator in terms of indicator description and data requirements. The term biodiversity is meaningless in this context. Is it a certain index, which data are you using to calculate it?


name: Number of protected areas with occurrences of common seal
_0: AU-DKJ/JHA 109
_14: The number of protected areas with occurrences of common seal
_15: State
_16: Target Groups
_5:
The number of breeding sites; the areal extent of suitable breeding sites (in protected areas of the North sea and the Baltic sea)


name: Distributional range of selected bird species
_0: AU-DKJ/JHA 110
_14: Area of distributional range of divers, common scoter, eider and long-tailed duck
_15: State
_16: Target Groups
_10:
Relevant areas:
divers = North Sea, N. Kattegat
common scooter = N. Kattegat
long-tailed duck = Bornholm


name: Biomass of selected fish species (SSB - spawning stock biomass)
_0: AU-DKJ/JHA 126
_9: see examples in tables of link
_14: SSB (spawning stock biomass) of selected fish species
_15: State
_16: Production
_18: Simple statistics
_5:
Fish species include cod, sole, hering, plaice, haddock, saithe, sandeel, norway pout, sprat, south estaren NS, depending on area


name: State of selected habitats
_0: AU-DKJ/JHA 134
_14: Quality of sandeel habitats
_15: State
_16: Biotope Features
_18: Simple statistics
_13:
MariLim: AU- Information quality too low. Please specify this indicator in terms of indicator description, descriptors, criteria, biological componentes and geography settings.


name: Distributional range of horse mussel banks
_0: AU-DKJ/JHA 137
_13: merge similar / move info to "Biodiv. Comp." fields
_14: The occurrence of horse mussel banks
_15: State
_16: Biotope Features
_5:
Method non-specified. Relevant for Kattegat and the Danish Straits. Study of possible occurrences of horse mussels in connection with bottom trawling studies of the North Sea.


_0: AU-DKJ/JHA 139
_13: MariLim: AU please specify further. No information given to describe this indicator
_15: State
_16: Biotope Features
_18: Simple statistics
name:
Deposition of fine-grained sediments in sandeel areas from construction works in the marine environment

_14:
Deposition of fine-grained sediments in sandeel areas from construction works in the marine environment.


name: Impacts of anthropogenic physical disturbance on the sea pen community
_0: AU-DKJ/JHA 140
_14: Monitoring of human-induced physical disturbance in selected areas with the sea pen community.
_15: State
_16: Biotope Features
_13:
MariLim: AU, please specifiy this indicator in terms of the indicator decription field

"Biodiversity component" field for sea pen community: add other groups?


name: Depth limit of macroalgae
_0: AU-DKJ/JHA 144/LU-SYKE
_4: SCUBA diving
_6: m
_9: see examples in tables of link
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L19.pdf
_14: Macroalgae max depth limit / Depth distribution of selected perennial macroalgae
_15: State
_16: Biotope Features
_18: Simple statistics
_5:
Relevant in Little Belt and possibly in other areas where lack of hard substrate is not a limiting factor

_11:
Macroalgae maximum depth limit.

Marmoni indicator "Depth distribution of selected perennial macroalgae": "The indicator describes the long-term changes in water quality through measurements of the lower depth limit of a coverage of ≥ 0,1% of the indicator species. It has been shown that human-based eutrophication has an effect on the vertical depth distribution of macroalgae by decreasing water transparency and thus light penetration in the water column." 


name: Chemical and physical variables from existing monitoring programmes
_0: AU-DKJ/JHA 146
_14: Chemical and physical variables from existing monitoring programmes
_15: State
_16: Biotope Features
_18: Simple statistics
_13:
AU-DKJ/JHA to broad, specify indicators/parameters and if they are used in a multimetric index or as separate indices, otherwise remove entry


name: Abundance of bacterioplankton
_0: MHI-AG 108
_4: standard method
_5: Cell counts of plankton species and/or groups
_6: cells/ml
_11: Total bacterioplankton abundance within water column
_14: Total bacterioplankton abundance
_15: State
_16: Community Structure
_18: Simple statistics
_10:
Reference point and targets could be assessed based on spatial and temporal (seasonal/interannual) dynamics  


name: Biomass ratio of selected phytoplankton taxa groups
_0: MHI-AG 109
_4: method of inverse filtration
_8: Not available
_14: Phytoplankton taxonomic group ratio
_15: State
_16: Community Structure
_18: Simple statistics
_5:
Phytoplankton  species biomass  of the main taxonomic groups - Diatoms, Dinoflagellates, Coccolithophores 

_10:
Reference point and targets could be assessed based on spatial and temporal (seasonal/interannual) dynamics  


name: Biomass of phytoplankton
_0: MHI-AG 111
_4: inverse filtration
_5: Phytoplankton biomass within water column
_6: mg/m3
_8: Not available
_14: Total phytoplankton biomass
_15: State
_16: Production
_18: Simple statistics
_19: {Climate regulation}
_10:
Reference point and targets could be assessed based on spatial and temporal (seasonal/interannual) dynamics  
Could be merged with JRC-HT 105


name: Production of phytoplankton
_0: MHI-OK 112
_4: C 14 method ; FRRF -using method
_5: photosynthetic rate of phytoplankton within water column
_6: mg C/m^3
_8: Not available
_14: Phytoplankton primary production
_15: State
_16: Production
_18: Simple statistics
_10:
Reference point and targets could be assessed based on spatial and temporal (seasonal/interannual) dynamics  
ould be merged with CEFAS-CL 134


name: Species diversity of phytoplankton
_0: MHI-OK 113
_4: inverse filtration
_5: Phytoplankton species composition, their abundance/biomass
_8: Not available
_14: Phytoplankton Diversity Index
_15: State
_16: Community Structure
_18: Simple statistics
_13:
MariLim: MHI-OH - Please specify this indicator in terms of indicator description. Is it Shannon Index or another index? Just species diversity index is not very meaningful in this context. It it is Shannon, we can combine it with other indicators.


name: Biomass ratio of selected zooplankton taxa groups
_0: MHI-AG 115b
_4: Jeddy net-150 (UML)
_8: Not available
_14: Zooplankton taxonomic group ratio
_15: State
_16: Community Structure
_18: Simple statistics
_5:
Zooplankton Abundance/biomass of the maın taxonomıc groups - Copepoda, Cladocera,Jellyfish, Others. 


name: By-catch ratio of cetaceans
_0: MHI-OK 137
_4: Count of bycatch mammals
_8: Not available
_14: Cetacean by-catch rate
_15: Pressure
_16: Anthropogenic Activities
_18: Simple statistics
_5:
Number of individuals in fishing gear (by fishing gear type and cetacean species, and where possible by gender and maturity)


name: Macroalgae-diversity indices
_0: HCMR-NP 108a, JRC-HT
_5: Species composition and abundance
_11: Multimetric index using species number, evenness (Pielou) and diversity (Shannon index).
_14: Macroalgae-diversity indices
_15: State
_16: Community Structure
_19: {Bioremediation of waste}
_10:
The three (3) above mentioned indexes have been applied by Cyprus (Good Environmental Status Report) in order to tackle Criterion 1.1 (Species Distribution) for Descriptor 1. The variation of different macroalgal diversity indices (species number, Pielou’s Evenness “J‟, Shannon “H‟) was studied on a hierarchy of spatial and temporal scales in Cyprus rocky coasts monitored during WFD program.

_13:
MariLim: It is still not clear if the different indices are used separately or in form of a mulimetric index integrating all three parameters in ONE index. Pleas specify. If they are used separately, we have to split it into three parameters (what we have already done) and delete this one!


name: Zoobenthos-diversity indices
_0: HCMR-NP 109a, JRC-HT, LU-SYKE
_5: Species number, Pielou’s Evenness “J”, Shannon diversity “H‟, ZKI index
_14: Zoobenthos-diversity indices
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Bioremediation of waste}
_10:
The three (3) above mentioned indexes have been applied by Cyprus (Good Environmental Status Report) in order to tackle Criterion 1.1 (Species Distribution) for Descriptor 1. The spatial variation of different benthic invertebrate diversity indices (species number, Pielou’s Evenness “J‟, Shannon diversity “H‟) was studied across an anthropogenic gradient in eight Cyprus sedimentary sites within the WFD monitoring program.

"Macrozoobenthos community index (ZKI): http://www.sea.ee/marmoni/marmoni_pulk/docs/L22.pdf

_13:
MariLim: It is still not clear if the different indices are used separately or in form of a mulimetric index integrating all three parameters in ONE index. Please specify. If they are used separately, we have to split it into three parameters (what we have already done) and delete this one!


name: Areal extent of marine angiosperms
_0: HCMR-NP 112
_6: (Area in ha).
_14: Extent and distribution of marine angiosperms.
_15: State
_16: Biotope Features
_10:
This indicator has been used by Cyprus (Good Environmental Status Report) in order to evaluate Criterion 1.5 (Habitat extent) of MSFD Descriptor 1. 

_11:
Posidonia and Cymodocea meadows form priority habitat types (Habitat Directive 92/43) of diverse macroalgal and faunal communities in Cyprus coastal waters. 

_13:
HCMR - redistribute information in "indicator name" field across the correspondent fields in catalogue

_19:
{Climate regulation} {Disturbance prevention or moderation} {Bioremediation of waste} {Leisure and recreation} {Aesthetic experience}


name: Abundance of perennial seaweeds
_0: HCMR- NP 115a
_15: State
_16: Biotope Features
_18: Simple statistics
_19: {Climate regulation} {Disturbance prevention or moderation} {Bioremediation of waste}
_10:
MariLim: We had to split indicator HCMR-NP 115 into its single parameters to be consistent with other indicators

_11:
1)	Abundance of perennial seaweeds (ESG IA): In oligotrophic and highly transparent pristine rocky coasts, slow growing, non-plastic Cystoseira species (ESG IA) may dominate by efficiently using their internally stored nutrient reserves to support growth during periods of nutrient shortage (Orfanidis et al. 2011). The variation of perennial (ESG IA) macroalgal abundance (% coverage) was studied on a hierarchy of spatial (site) and temporal (time) scales in Cyprus rocky coasts monitored during WFD program. 

_14:
Abundance of perennial seaweeds, Abundance of shade-adapted, slow growing calcareous species, Abundance of opportunistic macroalgae, Ecological Evaluation Index (EEI), PREI index (Posidonia), BENTIX index


name: Abundance of seaturtle spawning population
_0: HCMR- NP 116
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_10:
MariLim: We had to split indicator HCMR-NP 111 in its single parameters to be consistent with other indicators.

_14:
Size of the seal Monachus monachus population in Greek waters and number of colonies, Population size of Caretta caretta spawning.


name: BFI - Biomass Fractionation Index
_0: HCMR-NP 123, JRC-HT
_5: Biomass
_6: ratio
_14: Proportion of biomass or number of individuals in the macrobenthos above some specified length/size
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Food provision}
_10:
For this indicator Cyprus has done nothing due to lack of data, while Greece has suggested the use of BFI Index (biomass fractionation Index) by Lampadariou et al. (2008). 

_11:
The Biomass Fractionation Index (BFI) is estimated as follows: biomass having passed through 1.0mm and retained on 0.5mm sieve only/total biomass (biomass retained on 1.0mm+0.5mm sieve).


name: Areal extent of intertidal rock
_0: UHULL-KM 138
_4: GPS/dGPS
_5: Habitat area
_6: Km^2 or linear extent
_8: Low-medium cost component of wider survey costs
_14: Area of intertidal rock
_15: State
_16: Biotope Features
_18: Simple statistics
_13:
Field 'Country' was "UK/OSPAR". While 'UK' has been kept, 'OSPAR' been removed since it is no country. Please update Data->Settings accordingly.


name: Species diversity in selected habitats (sponge, anthozoan community)
_0: UHULL-KM 144
_5: Abundance of taxa and/or % cover of taxon groups or diversity indices
_6: Abundance of taxa and/or % cover of taxon groups or diversity indices
_15: State
_16: Community Structure
_18: Simple statistics
_13:
MariLim: UHULL - Please specify this indicator in terms of indicator description. The term species diversity is meaningless in this context. Is it a certain diversity index, is it multimetric?

_14:
Subtidal species composition & abundance (sponge, anthozoan community) (condition of the typical species/communities)


name: Morphological diversity of sponges
_0: UHULL-KM 145
_5: Morphological richness and diversity measures
_6: Morphological richness and diversity measures
_14: Sponge morphological diversity (Condition of the typical species/communities)
_15: State
_16: Life Traits
_18: Simple statistics
_13:
Which indices exactly? Is this a multimetric or several indicators used separately? Clarify and split entries if needed, otherwise consider removing entry


name: Abundance and composition of intertidal macroalgae
_0: UHULL-KM 146
_5: Abundance as % cover or biomass ? - Please specify
_6: Abundance and presence of species from the full land and reduced lists
_11: Abundance and presence of species from full land reduced lists
_14: Intertidal species composition and abundance (condition of typical species/communities)
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Climate regulation} {Disturbance prevention or moderation} {Bioremediation of waste}
_10:
BSSKM
presumably this indicator should be renamed to indicate that it refers specifically to macroalgae and not faunal species

_13:
MariLim: you have chosen "benthic invertebrates" as biological component in the first version. We have changed this to macroalgae. Please check again. Because at habitat settings you have also chosen "Littoral sediment", which is wrong, when it hsould be macroalgae
Please specify description "full land reduced list" and data requirements


name: Boulder turning index (condition of typical species/communities)
_0: UHULL-KM 148
_5: Percentage cover of key species
_6: %
_14: Boulder turning index(Condition of typical species/communities)
_15: State
_16: Community Structure
_18: Simple statistics
_13:
UHULL, check if the index name is correct as is

Field 'Country' was "UK/OSPAR". While 'UK' has been kept, 'OSPAR' been removed since it is no country. Please update Data->Settings accordingly.


_0: UHULL-KM 159
_5: Area of biogenic feature / number of units of occurrence
_6: ha OR number of units/unit area (e.g. 5 km^2)
_11: Areal extent of subtidal biogenic structures.
_15: State
_16: Biotope Features
_18: Simple statistics
name:
Areal extent of subtidal biogenic structures (type, abundance, biomass and areal extent of relevant biogenic substrata)

_13:
what is the difference between these two entered by UHULL: #137and 159. MERGE? / indicator name lost in this entry when exported

Field 'Country' was "UK/OSPAR". While 'UK' has been kept, 'OSPAR' been removed since it is no country. Please update Data->Settings accordingly.

_14:
Area of subtidal biogenic structures (type, abundance, biomass and areal extent of relevant biogenic substrata)


_0: UHULL-KM 160
_5: Number of species
_6: Number of species/unit area
_11: Density of biogenic reef forming species.
_15: State
_16: Biotope Features
_18: Simple statistics
name:
Density of biogenic reef forming species (type, abundance, biomass and areal extent of relevant biogenic substratum)

_13:
are UHULL-KM 143 and 160 the same? MERGE

Field 'Country' was "UK/OSPAR". While 'UK' has been kept, 'OSPAR' been removed since it is no country. Please update Data->Settings accordingly.

_14:
Density of biogenic reef forming species (type, abundance, biomass and areal extent of relevant biogenic substratum)


name: Distributional range of selected habitats
_0: UHULL-KM 161
_5: Location
_6: NGR/lat/long
_11: (applies to rock, biogenic reef andsediment habitats)
_14: Distributional range of habitat (applies to rock, biogenic reef andsediment habitats)
_15: State
_16: Biotope Features
_13:
indicate habitats in other fields and merge under same type of indicator? Merge UHULL 135 and 161?

Field 'Country' was "UK/OSPAR". While 'UK' has been kept, 'OSPAR' been removed since it is no country. Please update Data->Settings accordingly.


name: Areal extent of sediment habitat
_0: UHULL-KM 163
_5: Spatial extent of habitat
_6: ha
_14: Area of sediment habitat
_15: State
_16: Biotope Features
_18: Simple statistics
_13:
MERGE what is the difference between these two entered by UHULL: #163 and 164

Field 'Country' was "UK/OSPAR". While 'UK' has been kept, 'OSPAR' been removed since it is no country. Please update Data->Settings accordingly.


name: Biomass ratio of opportunistic macroalgae/total
_0: UHULL-KM 167
_6: % cover in habitat / g/m2
_14: Opportunistic macroalgae
_15: State
_16: Indicator Species
_18: Simple statistics
_19: {Bioremediation of waste} {Biological control}
_5:
Ecological Quality Ratio based on identification and collection (e.g. for biomass) of opportunistic, nuissance weed


name: WFD British Saltmarsh classification tool
_0: UHULL-KM 168
_14: WFD saltmarsh classification tool
_15: State
_16: Biotope Features
_11:
Multimetric index assessing EQR values for BQE Angiosperms based on the diversity, extent and zonation of intertidal saltmarsh habitats


_0: UHULL-KM 182
_5: % are occupied by key/typical species
_6: %
_14: %area with benthic invertebrates known to be associated with particular substrata
_15: State
_16: Target Groups
_18: Simple statistics
name:
Ratio of area inhabited by selected benthic invertebrate species to total area of their particular substrata


name: Marine Biological Valuation Methodology
_0: IMAR-HV 108
_5: All available biological and ecological information for a study area
_14: Marine Biological Valuation Methodology
_15: State
_16: Community Structure
_10:
 This methodology can be used in every marine environment, independent of the amount and quality of the available biological data or the habitat type.

_11:
The marine biological valuation methodology is able to integrate all available biological information on an area into one indicator of intrinsic value of marine biodiversity, without reference to anthropogenic use. This methodology can be used in every marine environment, independent of the amount and quality of the available biological data or the habitat type. For environments for which data are available, subzones within a study area are scored against three first order criteria rarity and aggregation or fitness consequences, and two modifying criteria: naturalness and proportional importance. The purpose of marine biological valuation is to provide subzones within the target study area with a label of their intrinsic biological value (on a continuous or discrete value scale, e.g. high, medium and low value)(Derous et al., 2007).


name: Abundance ratio of opportunistic/sensitive species
_0: IMAR-HV 112a
_5: species abundance/biomass patterns in space/time
_14: Opportunistic-sensitive species proportion
_15: State
_16: Indicator Species
_18: Simple statistics
_10:
MariLim: We had to split indicator IMAR-HV 112 to abundance and biomass to be consistent with other indicators.


name: Abundance of seagrass
_0: IO-BAS 36
_5: seagrass abundance
_6: ind/m2
_11: seagrass abundance
_14: seagrass abundance
_15: State
_16: Target Groups
_18: Simple statistics
_13:
MariLim: IO-BAS please specify the indicator description, unit (ind/m-2) seems to be a mistake, do you mean shoots/m-2 or is it coverage (%)?

_19:
{Climate regulation} {Disturbance prevention or moderation} {Bioremediation of waste} {Aesthetic experience}


name: IBI - Integrated Biological Index
_0: IO-BAS 79, JRC-HT
_5: abundance, biomass and species composition
_6: EQR [0-1]
_14: Integrated Biological Index (IBI)
_15: State
_16: Community Structure
_18: Simple statistics
_11:
Multimetric index for phytoplankton using three parameters: taxonomic structure, abundance, biomass. 
The combination rule applied to the Integrated Biological Index (IBI-Ph) metrics assumes equal weight (1) (average metric scores) proposed by Spatharis S., G. Tsirtsis (2010), i.e., = arithmetic average of EQRs for the single metrics, after normalization of the EQRs boundaries.


name: Abundance ratio of selected dinoflagellates (C-strategy species)
_0: IO-BAS 80
_5: taxonomic structure, abundance
_6: %
_11: taxonomic structure, abundance
_15: State
_16: Life Traits
_18: Simple statistics
_19: {Bioremediation of waste}
_14:
abundance of dinoflagellate (C-strategy species)  as a % of the Total dinoflgellates abundance [DE%]


name: Abundance of selected phytoplankton species and taxa groups
_0: IO-BAS 81
_5: species composition, abundance
_6: %
_11: Relative abundance of microflagellates, euglenophyceae, cyanophyceae species [МЕС-%]
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Climate regulation} {Biological control}
_14:
Abundance  of Microflagellates, Euglenophyceae, Cyanophyceae species  in  % total phytoplankton abundance  [МЕС-%]


name: Ratio of non-indigenous/native species
_0: HCMR-NP 6
_5: ratio for main taxonomic groups (mollusca, crustacea, macroalgae, polychaets) at MSFD level
_14: Ratio of NIS/native species
_15: Pressure
_16: Target Groups
_18: Simple statistics
_10:
This is actually the definition of the MSFD indicator 2.2.1 (Ratio between invasive non-indigenous species and native species in some well studied taxonomic groups (e.g. Fish, macroalgae, molluscs) that may provide a measure of change in species composition) of criterion 2.2 (Environmental impact of invasive non-indigenous species ) of Descriptor 2. For this indicator Cyprus has done nothing due to lack of data, while Greece has proposed a sampling network covering large spatial scales.


name: Abundance of coral colonies alive
_0: KAUST-SC 108
_5: Live coral %
_11: Abundance of coral colonies alive expressed as cover per spatial unit
_14: Coral species cover
_15: State
_16: Biotope Features
_18: Simple statistics
_4:
quadrats at certain intervals (5m, 10m)  at areas with contrasting disturbance levels; quadrat sampling over one hour period (other time periods are also used) at several sites; IUCN (World Conservation Union (formerly International Union for the Conservation of Nature) quantitative line transect method

_10:
Note: this index has been applied in coral reefs worldwide. So, it has been applied in the Red Sea but was not developed specifically for the area. Neverthess, to my best knowledge no thresholds have been proposed yet. At Kaust, we want to do it in the near future at least for the Saudi Arabian Red Sea. So the reference here refers to the information presented and not to the authorship of the parameter being indicated


name: Species richness of corals
_0: KAUST-SC 110
_5: number of coral species
_10: Authors tested several indices and no specific index is being proposed
_14: Coral community diversity
_15: State
_16: Community Structure
_18: Simple statistics
_4:
Photo-transects. Ten frames per site; sites spaced by one meter intervals; transects established at different depths)


name: Body length distribution of herbivorous fish (Demographic skewness)
_0: KAUST-SC 111
_5: length of fishes
_6: mm
_14: Herbivorous fish size frequency (Demographic skewness)
_15: State
_16: Population Ecology
_18: Simple statistics
_4:
Ten 50 m line transects were randomly laid on the reef, each transect measuring 5meters wide (2.5 m on each side of the transect line). A minimum of 10 min after laid transect were waited before starting the recording in order to allow the more easily scared individuals/species to come out from their hiding places 


name: POSWARE
_0: JRC-HT 28
_4: diving
_6: 0-1 EQR
_14: POSWARE
_15: State
_16: Biotope Features
_18: Complex statistics
_19: {Climate regulation}
_5:
depth (m), density (number of shoots/m2), rhizome production (mg/year), rhizome elongation (mm/year), leaf production (number of leaves/year)

_10:
POSWARE index method of metrics aggregation (Gobert et al 2009): Combined in a datawarehouse (Autoclass C, miner 3D, and fuzzy clustering analyses) (Buia et al 2005).

_11:
POSWARE index is formulated on the base of the following set of descriptors: density of prairies (no. of bundles per sq m), primary production (assessed in terms of annual weight increase of rhizome), annual rhizome elongation and leaf production (no. of leaves produced per year).


name: CymoSkew
_0: JRC-HT 30
_4: diving
_5: leaf length (mm)
_6: N/A
_14: CymoSkew
_15: State
_16: Physiological Condition
_18: Simple statistics
_19: {Climate regulation}
_11:
CymoSkew index (Orfanidis et al. 2007, 2010) is a quantitative expression of leaf length asymmetry, on the meadow scale. 


name: WFD Valencian Region Method using Posidonia oceanica
_0: JRC-HT 31
_4: diving
_6: 0-1 EQR
_14: Valencian Region Method to Implement the WFD using Posidonia oceanica
_15: State
_16: Biotope Features
_18: Complex statistics
_5:
shoot density (number of shoots/m2), shoot foliar surface (cm2/shoot), % dead-matte cover, % meadow cover, herbivore pressure (% leaves with herbivore marks per shoot), rhizome baring/burial, necrosis (% leaves with necrosis marks per shoot), % plagiotropic rhizomes, epiphyte biomass (dry weight)

_11:
Proposed multimetric index assessing EQR values for BQE Angiosperms based on  seagrass demograpghic parameters and epiphyte biomass.
Metrics combination using a PCA.


name: EPI - Estonian Phytobenthos Index
_0: JRC-HT 32
_4: diving and underwater video camera
_5: Species composition with depth, biomass data (dry biomass, g/m2)
_6: 0-1 EQR
_13: Depth
_14: Estonian Phytobenthos Index
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
Multimetric index for macrophytes using three parameters: depth limit of total attached phytobenthos, depth limit of Fucus vesiculosus and biomass ratio of perennial species. For the calculation of the Estonian Phytobenthos Index (EPI) the average of standardized EQRs of the three above-mentioned metrics is used (Torn & Martin 2012).


name: Assessment of macrovegetation in coastal and transitional waters
_0: JRC-HT 33
_4: diving
_6: 0-1 EQR
_14: Assessment of Biological Quality Elements in coastal and transitional waters - macrovegetation
_15: State
_16: Biotope Features
_11:
Multimetric index assessing EQR values for BQE Angiosperms and Macroalgae using depth limits of key-species


name: WFD Polish Assessment system for coastal and transitional waters using macrophytes
_0: JRC-HT 34
_6: EQR (0-1)
_14: Assessment system for coastal and transitional waters using macrophytes
_15: State
_16: Biotope Features
_18: Simple statistics
_4:
diving; Frame DAK (small frame with collection bag and cuff which covers the upper part of the frame - Andrulewicz E., L. Kruk - Dowgiallo; Bernatowicz grab

_5:
species-specific dry weight (g/m2); taxonomical identification to species/genus level and classification of taxa into negative / positive taxa; % vegetation coverage; substrate cover

_11:
Multimetric index assessing EQR values for BQE Angiosperms and Macroalgae using biomass, cover and species composition (sensitive/toleant taxa ratio)


name: WFD Romanian Assessment system for coastal waters using macrophytes
_0: JRC-HT 36
_4: diving; underwater camera
_13: MariLim: Please specify this indicator in terms of indicator description
_14: Assessment system for coastal waters using macroalgae
_15: State
_16: Biotope Features
_5:
taxonomical id of taxa; presence/absence of species; number of individuals per m2; wet biomass weighted from a surface of 20cm * 20cm

_11:
Multimetric index assessing EQR values for BQE Angiosperms and Macroalgae using presence /absence of senitive species, xxx


name: WFD Dutch Eelgrass index
_0: JRC-HT 38
_4: aerial photography; satellite images
_5: % coverage area eelgrass species
_6: 0-1 EQR
_14: WFD-metrics for natural watertypes
_15: State
_16: Biotope Features
_18: Simple statistics
_19: {Disturbance prevention or moderation}
_13:
MariLim: Please specify this indicator in terms of indicator description, and geography settings (we have moved the relevant text for watertype CW-NEA4, K2 - Oosterschelde to geography, where it belongs to, please check , if it is correct)


name: BEQI - Benthic Ecosystem Quality Index
_0: JRC-HT 43
_4: Grab
_6: EQR (0-1)
_14: Benthic Ecosystem Quality Index (BEQI)
_15: State
_16: Production
_9:
A power analysis is used to determine the level of confidence of the analysis. The possibility to detect with a power of 75% a certain deviation from the median value for each evaluated parameter with the used sampling effort was evaluated. Four classes were defined: (1) when it is possible to detect changes with a factor < 2, the power is evaluated as GOOD; (2) changes with a factor 2-5, the power is evaluated as MODERATE; (3) changes with a factor 5-10, the power is evaluated as LOW; (4) changes with a factor > 10, the power is evaluated as VERY POOR.

_11:
Level 1 - At the ecosystem level, the BEQI uses the relationship between macrobenthic biomass (B) and system productivity (P).
Level 2 - Habitat surface area changes (not used for the Belgian Coastal Waters). Level 3 - At the third level the BEQI analyses and evaluates the benthic macrofauna community per habitat.
The BEQI level 3 uses four biological parameters: number of species, total density (ind./sqm), total biomass (g Ash Free Dry Weight/sqm), and similarity (Bray-Curtis similarity based on 4th root transformed density data).


name: BBI - Brackish water benthic index
_0: JRC-HT 46
_4: Grab
_6: EQR (0-1)
_14: Brackish water benthic index (BBI)
_15: State
_16: Community Structure
_18: Simple statistics
_11:
Multimetric index: BQI (taxonomical id & classification of taxa), Shannon-Wiener diversity, Total abundance, Relative abundance of sensitive and tolerant species, Species richness


name: ZKI - Estonian Multimetric macrozoobenthos community index
_0: JRC-HT 47
_4: Grab
_5: Species composition, species number and biomass (dry weights) data
_6: 0-1 EQR
_14: Macrozoobenthos community index (ZKI)
_15: State
_16: Community Structure
_18: Complex statistics
_11:
Multimetric Index using species composition, biomass, species richness and max. number of species as parameters


name: WFD Lithuanian Asssessment system for transitional and coastal waters using macrozoobenthos
_0: JRC-HT 49
_4: Grab
_6: EQR (0-1)
_14: Asssessment system for transitional and coastal waters using macrozoobenthos
_15: State
_16: Community Structure
_5:
abundance (individuals counts per area), species taxonomical identification (or lowest reliable taxon.level possible)

_11:
Multimetric index assessing EQR values for BQE Benthic invertebrates using species diversity (Margalef index), evenness (Pielou index) and Shannon-Wiener diversity


name: BAT - Benthic Assessment Tool
_0: JRC-HT 59
_4: Grab
_6: EQR (0-1)
_14: Benthic Assessment Tool (BAT)
_15: State
_16: Community Structure
_18: Complex statistics
_5:
species taxonomical identification (or lowest reliable taxon. level possible), abundance (individuals count per area), classification of species into 5 ecological groups (EG)

_11:
Multimetric index using: Margalef index (species richness), Shannon-Wiener Diversity (log2), AMBI (relative % of ‘sensitive’ / ‘tolerant’ taxa)


name: ITI - Trophic index
_0: JRC-HT 63
_4: Grab
_5: species composition, trophic group classification of taxa
_6: 0-100 (ITI scale)
_14: Trophic index (ITI)
_15: State
_16: Life Traits
_18: Simple statistics
_11:
Multimetric index using number of species; proportion of taxa in 4 trophic groups (species classified into 1: suspension feeders, 2: detritus feeders, 3: deposit feeders, 4: anaerobic substrate species)


name: NQI - Norwegian Quality Index
_0: JRC-HT 64
_4: Grab
_6: 0-1 EQR
_14: Norwegian Quality Index (NQI)
_15: State
_16: Community Structure
_18: Simple statistics
_5:
AMBI - relative proportion (abundance) of sensitive/tolerance taxa (5 EG); SN a diversity index - N number of individuals, S number of species


name: MAB Macroalgal Bloom Assessment (Opportunistic macroalgae)
_0: JRC-HT 65
_4: aerial photographs or equivalent imagery; field quadrats
_5: % cover, biomass data, species composition
_6: 0-1 EQR
_14: Macroalgal Bloom Assessment (Opportunistic macroalgae) (MAB)
_15: State
_16: Indicator Species
_18: Simple statistics
_19: {Biological control}
_9:
Confidence in class may be calculated for a single survey's data or for data from aggregated temporal surveys. A spreadsheet with embedded calculations is used to calculate the class, as per the standard equations and final EQR (face value class), but also calculates the probability of the water body being in each of the five WFD status classes. The face value class may not be the same as the most probable class given by the CofC assessment, because the EQR is constrained to be between 0 and 1. This typically occurs where the EQR is close to a boundary - the face value may be Good, but the CofC assessment may say there is a 40% chance of High, 50% of Good and 10% of Moderate. There is therefore 90% confidence of Good or better. The process allows the user to specify a relative standard deviation to represent the likely certainty (or error) in the measurement of parameters such as area of patch and AIH. Full details of the statistical methodology used in CAPTAIN are provided in the report "Confidence of Class for Marine Plant Tools". 

_11:
Multimetric index using five different parameters: cover of algae over the available intertidal area (average), total extent of the algal blooms measured in hectares, biomass of the algae taken as an average per squared meter over the available intertidal area, biomass of the algae taken as an average per squared meter over the affected bloom area only, presence of entrained algae calculated as a % of the total quadrats in which it is recorded


name: RSL - Macroalgae Rocky Shore Reduced Species List
_0: JRC-HT 66
_4: field counts/sampling
_6: 0-1 EQR
_13: can Macroalgae be moved to "Biodiv. Components" fields?
_14: Macroalgae Rocky Shore Reduced Species List (RSL)
_15: State
_16: Biotope Features
_18: Simple statistics
_5:
five parameters: Normalised number of macroalgal taxa (normalised to shore diversity); Proportion of Chlorophyta taxa; Proportion of Rhodophyta taxa; Proportion of opportunistic taxa; Ecological status group ratio

_9:
The uncertainty of the classification obtained has been quantified. Confidence in class may be calculated for a single survey's data or for data from aggregated temporal surveys. A spreadsheet with embedded calculations is used to calculate the class, as per the standard equations, and the final EQR (face value class), but it also calculates the probability of the water body being in each of the five WFD status classes. The face value class may not be the same as the most probable class given by the CofC assessment, because the EQR is constrained to be between 0 and 1. This typically occurs where the EQR is close to a boundary - the face value may be Good, but the CofC assessment may say there is a 40% chance of High, 50% of Good and 10% of Moderate. There is therefore 90% confidence of Good or better. Full details of the statistical methodology used are provided in the report "Confidence of Class for Marine Plant Tools". 


name: Depth limit of Furcellaria lumbricalis
_0: JRC-HT 69
_4: Diving
_5: Maximum depth limit of Furcellaria lumbricalis
_6: EQR (0-1)
_15: State
_16: Biotope Features
_18: Simple statistics
_14:
Assessment system for transitional and coastal waters using macroalgae (maximum depth limit of Furcellaria lumbricalis)


name: RSL - Rocky Intertidal Macroalgae - Reduced Species List
_0: JRC-HT 71
_4: field counts/sampling
_6: 0-1 EQR
_14: Rocky Intertidal Macroalgae - Reduced Species List (RSL)
_15: State
_16: Biotope Features
_18: Simple statistics
_5:
Number of green species Number of brown species Number of red species Number of opportunists Number of species in Ecological Status Group 1 Number of species in Ecological Status Group 2 Shore Description


name: MarMAT - Marine Macroalgae Assessment Tool
_0: JRC-HT 77
_4: field sampling, wire quadrats (0.2x0.2 m), photography
_5: species composition and cover data
_6: 0-1 EQR
_14: Marine Macroalgae Assessment Tool (MarMAT)
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
Multimetric index using species richness, proportion of green algae, proportion of red algae, ESG ratio, proportion of opportunists, shore description, coverage of opportunists (%)


name: Quality index of subtidal macroalgae of French Channel and Atlantic coast
_0: JRC-HT 82
_4: diving; quadrats counting
_5: species specific depth distributions, species composition, cover data
_6: 0-1 EQR
_14: Quality index of subtidal macroalgae of French Channel and Atlantic coast
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
Multimetric index assessing EQR values for BQE Macroalgae based on depth distribution (belts), density of selected species (kelps, Cystoseira spp., Halidrys siliquosa, ...), number of characteristic species, densities of opportunistic species, presence of "good ecological status species", biodiversity, stipe length and surface of epibionts of Laminaria hyperborea extent and zonation of intertidal saltmarsh habitats


name: WFD Estonian Assessment of ecological status of coastal waters using phytoplankton indicators
_0: JRC-HT 83
_14: Assessment of ecological status of coastal waters using phytoplankton indicators
_15: State
_16: Community Structure
_18: Simple statistics
_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings.


name: WFD Polish Phytoplankton classification methods
_0: JRC-HT 84
_5: chla measurements, species composition, cell counts, biovolume of species/taxa groups
_11: Multimetric index assessing EQR values for BQE Phytoplankton based on Chl a and biovolume
_15: State
_16: Community Structure
_18: Simple statistics
_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings (acan we ask a polish expert to do this?)

_14:
Monitoring and classification methods of biological quality elements for the assessment of ecological status of transitional and coastal marine water bodies


name: WFD Italian Assessment System for Coastal Waters Based on BQE "Phytoplankton"
_0: JRC-HT 85
_4: Water sampler
_6: EQR (0-1)
_14: Assessment System for Coastal Waters Based on BQE "Phytoplankton"
_15: State
_16: Production
_5:
Chlorophyll-a concentration as: mg/m3 (by fluorimetry method) and n. of cells/l (individual counts per volume; species/species groups taxonomical identification)

_11:
Multimetric index assessing EQR values for BQE Phytoplankton using Chlorophyll-a concentrations, nutrients concentration and species determination


name: WFD Slovenian Methodology for assessment of ecological status of coastal waters using phytoplankton
_0: JRC-HT 86
_5: quantification of biomass: Fluorometric determination of chlorophyll-a concentrations
_11: Yearly geomeans of integrated Chlorophyll-a concentrations.
_14: Methodology for assessment of ecological status of coastal waters using phytoplankton
_15: State
_16: Production
_18: Simple statistics
_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings (can we get access to a slovenian expert?)


name: Phytoplankton Toolkit
_0: JRC-HT 87
_13: MariLim: not enough info to see what this actually is
_14: Phytoplankton Toolkit
_15: State
_16: Community Structure
_18: Simple statistics
_5:
taxonomical identification: Level: Family, Genus, Other, Species/species groups; Determination of abundance: Individual counts, Abundance is related to: Volume, Unit of the record of abundance: cells per ml; Quantification of biomass: Chlorophyll-a concentration


name: WFD Lithuanian Assessment system for transitional and coastal waters for phytoplankton
_0: JRC-HT 88
_5: biomass through chlorophyll-a concentrations; Total phosphorus (TP); TN concentration
_14: Assessment system for transitional and coastal waters using phytoplankton indicators
_15: State
_16: Production
_18: Simple statistics
_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings (a lithuanian partner knowing WFD assessments should do this)


_0: JRC-HT 89
_14: Assessment system for coastal waters using chlorophyll-a as indicator of phytoplankton biomass
_15: State
_16: Production
_18: Simple statistics
name:
WFD Danish Assessment system for coastal waters using chlorophyll-a as indicator of phytoplankton biomass

_5:
list of biological metrics:
Summer (May-September) mean Chl-a concentration or 90th percentile of Chl-a concentration in samples collected from March through September

_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings (a danish partner knowing WFD assessments should do this). If it only chl a concentrations, then it is not an assessment system and should be listed in indicator "Concentration of Chla"


name: WFD Dutch phytoplankton index
_0: JRC-HT 92
_14: WFD-metrics for natural watertypes
_15: State
_16: Community Structure
_18: Simple statistics
_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings (a dutch partner knowing WFD assessments should do this)


name: Elevated Phytoplankton (Single Taxa) Counts Tool
_0: JRC-HT 94
_4: Water sampler: Bucket or a Standard Ruttner Water Sampler (depending on depth of sample)
_5: taxonomical identification of species/species groups; individual counts/volume (Cells/L)
_6: EQR (0-1)
_14: The Elevated Phytoplankton (Single Taxa) Counts Tool
_15: State
_16: Indicator Species
_18: Simple statistics
_19: {Biological control}
_11:
Single elevated taxa counts, assessing bloom frequency and intensity, taxonomic abundance (dominant taxa)


name: WFD Spanish Phytoplankton Tool for North East Atlantic Coastal Waters
_0: JRC-HT 95
_14: Spanish Phytoplankton Tool for North East Atlantic Coastal Waters
_15: State
_16: Community Structure
_18: Simple statistics
_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings (a spanish partner knowing WFD assessments should do this)


name: WFD Romanian Assessment system for coastal and transitional waters using phytoplankton
_0: JRC-HT 96
_14: Assessment system for coastal and transitional waters using phytoplankton
_15: State
_16: Community Structure
_18: Simple statistics
_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings


name: Assessment system for coastal and transitional waters: Phytoplankton
_0: JRC-HT 97
_14: Assessment system for coastal and transitional waters: Phytoplankton
_15: State
_16: Production
_18: Simple statistics
_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings (can we get contact to a swedish partner knowing WFD assessments?)


_0: JRC-HT 100
_4: Water sampler
_5: Median of all chlorophyll-a concentrations
_6: mg / m3
_15: State
_16: Production
_18: Simple statistics
name:
WFD Latvian Assessment method for phytoplankton status based on chlorophyll a concentrations in coastal and transitional water

_9:
Analysis of the decrease in the confidence intervall of mean log (Chl-a) with increasing number of samples collected within the available dataset. At approximately 30 samples per season further increase in sample size did not further increase the precision of the average. 

_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings. If it is only chl a concentrations, then it is not an assessment system and should be listed in indicator "Concentration of Chla"

_14:
Assessment method for phytoplankton status based on chlorophyll a concentrations in coastal and transitional water


_0: JRC-HT 101
_4: Water sampler
_5: Median of all phytoplankton biomass values
_6: mg wet-weight/m3
_11: Median of all phytoplankton biomass values
_15: State
_16: Production
_18: Simple statistics
name:
WFD Latvian Assessment method for phytoplankton status based on phytoplankton biomass in coastal and transitional waters

_9:
Analysis of the impact of sampling frequency on classification results, at least in a qualitative way. 

_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings. If it is only mean biomass of phytoplankton, then it is not an assessment system and should be listed in indicator "Biomass of phytoplankton"

_14:
Assessment method for phytoplankton status based on phytoplankton biomass in coastal and transitional waters


name: Water quality based on chlorophyll-a and bloom frequency
_0: JRC-HT 103
_14: Water quality based on chlorophyll-a and bloom frequency
_15: State
_16: Production
_18: Simple statistics
_11:
Multimetric index assessing EQR values for BQE Phytoplankton based on the Chlorophyll a and bloom frequency

_13:
MariLim: Please specify this indicator in terms of geography settings (a spanish partner knowing WFD assessments should do this) and check our preliminary entries for Indicator description, descriptors and criteria.


name: WFD Phytoplankton Quality in French Coastal Waters
_0: JRC-HT 104
_11: Multimetric index assessing EQR values for BQE Phytoplankton
_14: Phytoplankton Quality in French Coastal Waters
_15: State
_16: Target Groups
_18: Simple statistics
_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings (a french partner knowing WFD assessments should do this)


name: Rate of new introduction of NIS (per defined period) (NIS2)
_0: Cefas - CL 156, JRC-HT
_12: {OSPAR common indicator}
_14: NIS2 Rate of new introduction of NIS (per defined period)
_15: Pressure
_16: Target Groups
_18: Simple statistics
_5:
Species-parameter: list of NIS newly introduced into the assessment area during the assessment period.

_10:
NIS-2 is one of the prioritised OSPAR Candidate Indicators, proposed for promotion.

See Sources for Inventory‐parameter and Dispersal‐parameter.

_11:
The indicator incorporates three parameters: species, inventory and dispersal.
While all provide information for the understanding of NIS introductions, spread and management, only the Species-parameter will be used to assess targets at this stage in the indicator development: number of new NIS introduced into the assessment area during the assessment period.
By comparing the change in numbers of NIS recorded over the assessment period a rate of introduction can be calculated.


name: Abundance of cyprinids
_0: SYKE-LU 90 SYKE-LU 105
_5: Abundance data of fish in archipelago areas
_12: {HELCOM coreset}
_14: Abundance of cyprinids in archipelago areas
_15: State
_16: Population Ecology
_18: Simple statistics
_10:
No current monitoring. Methods are under development.

http://www.sea.ee/marmoni/marmoni_pulk/docs/L6.pdf


name: Abundance of waterbirds in the breeding season
_0: SYKE-LU 99 SYKE-LU 120 SYKE-LU 13 SYKE-LU 45 SYKE-LU 119
_4: Monitoring
_5: Abundance of species
_6: No. Of species reaching the species-specific targets
_14: Abundance of waterbirds in the breeding season
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_10:
OSPAR EcoQO. Several functional groups of birds.
Documentation: http://www.helcom.fi/Core%20Indicators/HELCOM-CoreIndicator-Abundance_of_waterbirds_in_the_breeding_season.pdf

"Abundance index of breeding waterbird species": http://www.sea.ee/marmoni/marmoni_pulk/docs/L37.pdf

"Breeding waterbird index (BWBI)": http://www.sea.ee/marmoni/marmoni_pulk/docs/L38.pdf

_11:
The proposed core indicator “Abundance of waterbirds in the breeding season” has two parameters: abundance and breeding success. The abundance parameter follows the OSPAR EcoQO1 procedure for the status of seabirds in the North Sea (ICES 2008, 2011), whereas the breeding success parameter will be developed separately for each bird species. 


name: Abundance of waterbirds in the wintering season
_0: SYKE-LU 27 SYKE-LU 44
_6: OSPAR EcoQO1
_12: {HELCOM coreset}
_14: Abundance of waterbirds in the wintering season
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_10:
Documentation: http://www.helcom.fi/Core%20Indicators/HELCOM-CoreIndicator_Abundance_of_waterbirds_in_the_wintering_season.pdf

_11:
The indicator follows the OSPAR EcoQO1 methodology for the status of seabirds in the North Sea (ICES 2008, 2011). The OSPAR EcoQO for abundance of seabirds was developed in the ICES WKSEQUIN workshop in 2008 (see the outcome here) and the most recent computation of the EcoQO was made by the ICES WGSE in 2011.


name: BPL - Biopollution Level index
_0: SYKE-LU 58, KUCORPI-MBAZ 13
_4: under development
_5: distribution, abundance, impact of species on communities, habitats, ecosystem functioning
_6: trend
_14: Biopollution Level index (BPL)
_15: Pressure
_16: Target Groups
_18: Simple statistics
_10:
More details at:
HELCOM http://helcom.fi/baltic-sea-trends/environment-fact-sheets/biodiversity/biopollution-level-index
and 
BINPAS (Biological Invasion Impact / Biopollution Assessment System)
http://www.corpi.ku.lt/databases/index.php/binpas/

_11:
The Biopollution level index (BPL) classifies the level of bioinvasion impacts. The index measures level of biopollution i.e. adverse environmental effects of NIS. Indicates the pressure level to the ecosystem. 


name: Distributional range of marine mammals
_0: SYKE-LU 95 SYKE-LU 24 SYKE-LU 25 SYKE-LU 42
_4: Acoustic monitoring, sightings and stranded porpoises
_5: Observations of marine mammals
_12: {HELCOM coreset}
_14: Distribution of marine mammals
_15: State
_16: Target Groups
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_6:
presence/absence (by the frequency of registrations in an area)
Distribution area of harbour porpoises
distribution area of seals


name: Nutritional status of marine mammals
_0: SYKE-LU 1 SYKE-LU 4 SYKE-LU 3 SYKE-LU 2
_6: mm
_14: Nutritional status of marine mammals
_15: State
_16: Physiological Condition
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_5:
- Sternum blubber thickness of grey seals aged 1-20 during the season of pregnancy
- Blubber thickness of harbour porpoises
- Sternum blubber thickness of harbour seals  aged 1-20 during the season of pregnancy
- Sternum blubber thickness of ringed seals aged 1-20 during the season of pregnancy

_10:
All HELCOM Core indicators will be monitored by all Contracting states. I'm not sure if the monitoring should hence be marked as "Regional Sea Convention"? Probably the states will adopt these as part of the national indicators for MSFD, which would then make them "EU Directives" monitored?


name: Population growth rate, abundance and distribution of marine mammals
_0: SYKE-LU 300 SYKE-LU 10 SYKE-LU 11 SYKE-LU 12
_14: Population growth rate, abundance and distribution of marine mammals
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_5:
Monitoring of grey seal abundance during the moulting period (DEN, EST, FIN, SWE).  Monitoring of harbour seal abundance during the moulting period (DEN, SWE).  Monitoring of ringed seal abundance during the breeding period (EST, FIN, SWE).  Harbour porpoise surveys (DEN, GER, SWE).  Project data and scientific literature.
Population growth rate %

_10:
The proposed core indicator follows the population growth rate, abundance and distribution of harbour porpoise, grey seal, ringed seal and harbour seal.  Population growth rate. Population growth rate should be positive until hampered by natural limitations. Deviations from the maximum rate of population growth during the phase of exponential increase are indicative of that the population is reaching its carrying capacity or is affected by human impacts in form of  excessive mortality or impaired fertility. Near or within the carrying capacity, the population fluctuates but a continuous decline indicates that the population is not in good environmental status (GES).  Abundance. Population abundances of the marine mammals are informative indicators of the state of the populations.  Distribution. The abundance of populations in different parts of the Baltic Sea gives an indication of the distribution of the population. The distribution indicator also shows also temporal trends of the abundance in the sub-regions.  Documentation at: http://www.helcom.fi/Core%20Indicators/HELCOM-CoreIndicator-Population_growth_rate_abundance_and_distribution_of_marine_mammals.pdf

_11:
The proposed core indicator follows the population growth rate, abundance and distribution of harbour porpoise, grey seal, ringed seal and harbour seal. 


name: Post-smolt mortality of salmon in the Gulf of Bothnia
_0: SYKE-LU 72 SYKE-LU 73 SYKE-LU 74
_5: Salmon population modelling results.
_14: Post-smolt mortality of salmon in the Gulf of Bothnia
_15: State
_16: Population Ecology
_18: Modelling
_11:
Post-smolt mortality is assumed to depend on the quality and availability of food items in the Bothnian Sea.


name: Pregnancy rates of marine mammals
_0: SYKE-LU 5, SYKE-LU 8, SYKE-LU 7, SYKE-LU 6, SYKE-LU 32, SYKE-LU 122, SYKE-LU 121, JRC-HT
_6: % pregnant females
_10: For supporting documentation see Sources.
_12: {HELCOM coreset}
_14: Pregnancy rates of marine mammals
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_5:
Pregnancy rate of grey seals aged 4-20
Pregnancy rate of harbour porposes, all mature females
Pregnancy rate of harbour seals aged 4-20
Pregnancy rate of ringed seals aged 4-20

Pregnancy rate is measured as the presence or absence of an embryo or foetus during the pregnancy period in mature females  (presence  of  an  ovarian Corpus  luteum,  CL). Pregnancy rate can also be  determined  on  the  basis of  Corpus  albicantia  (CA)  in  the  spring  sample  (between  ovulation  and implantation). 

_11:
This indicator considers fertility and is assessed by increasing pregnancy rate and supported by assessments of maturity of females and prevalence of uterine obstructions. The pregnancy rate of mature females can be affected by 
hazardous substances, particularly organochlorines. The boundary for good environmental status considering pregnancy rate is based on data from within and outside the Baltic Sea. 


name: Productivity of white-tailed eagle
_0: SYKE-LU 30 SYKE-LU 118
_5: Number of nestlings in whilte eagle nests
_6: unitless
_12: {HELCOM coreset}
_14: White-tailed eagle productivity
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_10:
Documentation: http://www.helcom.fi/Core%20Indicators/HELCOM-CoreIndicator-White-tail_eagle_productivity.pdf

_11:
The mean number of nestlings of at least three weeks of age, out of all occupied nests; average of last 5 years


name: Reproduction of birds
_0: SYKE-LU 63 SYKE-LU 62 SYKE-LU 64
_5: Observations of eggs laid, fledgings, etc.
_14: Reproduction of birds
_15: State
_16: Population Ecology
_18: Simple statistics
_11:
Reproduction of several bird species which share feeding habits. Three indiccators to be developed in finland include birds that feed on mussel, on coastal fish, and on offshore fish.


name: Abundance of sea trout spawners and parr
_0: SYKE-LU 18 SYKE-LU 103
_6: parr density
_12: {HELCOM coreset}
_14: Abundance of sea trout spawners and parr
_15: State
_16: Production
_18: Simple statistics
_19: {Leisure and recreation}
_5:
Sea trout parr densities (central); number of spawning rivers, fishing mortality, number of spawners (supporting)

_10:
Documentation: http://www.helcom.fi/Core%20Indicators/HELCOM-CoreIndicator-Abundance_of_sea_trout_spawners_and_parr.pdf

_11:
The proposed core indicator follows the sea trout parr densities and compares them with reference densities in good habitats of the spawning rivers. The parameter has a linkage to the number of adult spawners ascending the rivers and, hence, indirectly to fishing pressure at the sea and in the river, which are found very significant factors affecting the sea trout abundance. The indicator is supported by parameters following the number of rivers with wild sea trout spawning, fishing catches.
and smolt production. 
This core indicator report is based on the annual reports of the ICES Working Group on Baltic Salmon and Sea Trout 
(WGBAST). 


name: Body length distribution of selected (coastal) fish species
_0: SYKE-LU 34 SYKE-LU 36
_5: I (LU) assume the Swedish coastal experimental fishing data will be used.
_6: proportion of large individuals
_14: Size structure of coastal key fish species
_15: State
_16: Population Ecology
_18: Simple statistics
_11:
Swedish national indicators 1.3E & 4.2A, size distribution of key fish species in the coastal waters, and 1.6A, 3.1C & 4.2B, size structure of the coastal fish community. 


name: Abundance of salmon spawners and smolt
_0: SYKE-LU 19 SYKE-LU 102
_6: smolt production: target is to reach 75% of the potential by 70% probability in each river.
_14: Abundance of salmon spawners and smolt
_15: State
_16: Production
_18: Simple statistics
_19: {Leisure and recreation}
_4:
 Smolt abundance assessment, salmon population modelling. The proposed core indicator is based on the annual work of the ICES Working Group on Baltic Salmon and Sea Trout (WGBAST) and is supplemented by the results of the HELCOM SALAR project (HELCOM 2011). 

_5:
Salmon smolt production (central); number of spawning rivers of wild salmon, post.-smolt survival, fishing mortality, number of spawners (supporting)

_10:
Documentation: http://www.helcom.fi/Core%20Indicators/HELCOM-CoreIndicator-Abuncance_of_salmon_spawners_and_smolt.pdf

_11:
The main parameter of the proposed core indicator is: 
1. Smolt production in rivers, 
, and the core indicator is supported by the following parameters: 
2. Number of rivers with self-reproducing salmon populations, 
3. Number of spawners in the rivers
4. Post-smolt survival (relative rate) (Figure 7), 
5. Fishing catches (Figure 8). 


name: WFD German Eelgrass index (intertidal)
_0: MariLim-KF 27 JRC-HT 27
_4: Aerial mapping (flight) combined with (GPS-)field mapping
_5: Areal extent (km2), cover data, species composition
_6: EQR (0–1, unitless)
_14: Assessment tool for intertidal eelgrass in coastal and transitional waters
_15: State
_16: Biotope Features
_10:
This is part of another multivariate system (see indicator MariLim-KF 35) but combines also indicators, listed partly separately (see indicator MariLim-KF 111).

_11:
Multimetric index (2 metrics) using total areal extent and a combined metric of areal extent of a specific coverage degree and species composition of intertidal eelgrass


name: AMBI - AZTI Marine Biotic Index
_0: IO-BAS 7 IO-BAS 41 IO-BAS 49 IO-BAS 52 IO-BAS 58 IO-BAS 62 IO-BAS 65 IO-BAS 69 JRC-HT 108
_4: Grab
_6: 0-7 BC (Biotic Coefficient) units
_14: AZTI Marine Biotic Index (AMBI)
_15: State
_16: Life Traits
_18: Simple statistics
_5:
species abundance, taxonomic identification to lowest possible taxon, classification of taxa into 5 ecological groups (EG)

_11:
Relative proportion (abundance) of sensitive/tolerant taxa (previously classified into 5 ecological groups EG)

_13:
What does "(5 EG)" stand for in field "data requirements"? - CLARIFIED (JRC-HT)

(JRC-HT): the 2 references (Todorova 2013 and  Trayanova et al 2007) in Sources would be better placed next to the respective entries in the "Settings" part, since they address the application of AMBI in the Black Sea area particularly. Here maybe it should go only the reference correspondent to this index authorship (Borja et al, 2000).


name: BOPA - Benthic Opportunistic Annelida Amphipoda Index
_0: AZTI-JGR 283 JRC-HT 58
_4: Grab
_6: EQR (0-1)
_11: Relative abundance of sensitive/tolerance taxa (polychaete/amphipod ratio)
_14: Benthic Opportunistic Annelida Amphipoda Index (BOPA)
_15: State
_16: Life Traits
_18: Simple statistics
_5:
total number of individuals collected in the samples, the frequency of opportunistic polychaetes, and the frequency of amphipods (except the genus Jassa)


name: CARLIT-BENTHOS - Cartography of littoral and upper-sublittoral rocky-shore communities
_0: JRC-HT 75 AZTI-JGR 255 AZTI-JGR 370
_6: 0-1 EQR
_14: Cartography of littoral and upper-sublittoral rocky-shore communities (CARLIT-BENTHOS)
_15: State
_16: Biotope Features
_18: Simple statistics
_4:
near shoreline boat surveys; graphic support: aerial photographs, nautical carts or orto-photographs

_5:
meters of coastline covered by a specificly categorized community; abundance classes
[Infralittoral rocky bottom habitats] 

_13:
Consider to move habitat info in square brackets from "Data requirements" field to habitat field (under "Data" form).


name: DKI - Danish Quality Index
_0: JRC-HT 41 AU-DKJ/JHA 41
_4: Corer, Grab
_6: 0-1 EQR
_14: Danish Quality Index (DKI)
_15: State
_16: Community Structure
_18: Simple statistics
_11:
Shannon Diversity index, AZTI Marine Biotic Index (AMBI - taxonomical id & classification of taxa), Number of species, Number of individuals. Correction facot for salinity in version 2 of the index.

Status (DKI values) based on individual Van Veen samples are compared to the Good-Moderate border value using Wilcoxon signed ranks test. If DKI values from a site or area (water body) are significantly (p<0.05) above the border value, status is acceptable. See examples in tables of link (column p)


name: Depth limit of eelgrass
_0: MariLim-KF 23 JRC-HT 23
_4: assessment of coverage by video or diving
_5: eelgrass cover (%) per water depth
_6: m
_10: This is one parameter/metric/method of a multivariate system (see indicator MariLim-KF_39)
_14: Depth limit of eelgrass
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
Eelgrass cover (%) with information on water depth and position, the 10 % eelgrass cover value marks the depth limit


name: M-AMBI - Multivariate AZTI Marine Biotic Index
_4: Grab Van-Veen grabs, different corers
_5: Requires: richness, diversity and AMBI values calulated on macrobenthic communities.
_6: 0-1 EQR
_14: Multivariate AZTI Marine Biotic Index (M-AMBI)
_15: State
_16: Community Structure
_18: Complex statistics
_0:
AZTI-JGR 331
IMAR-HV 113
IO-BAS 50
IO-BAS 53
IO-BAS 59
IO-BAS 63
IO-BAS 66
IO-BAS 70
JRC-HT 50
MariLim-KF 50

_11:
Multimetric assessment system combining species number (richness), species diversity (Shannon) and the AMBI-Index (a sensitivity classification on basis of autecological species information)
Using historical data, expert judgement and multivariate analysis in assessing reference conditions and benthic ecological status, according to the European Water Framework Directive.


name: POMI - Posidonia oceanica Multivariate Index
_0: AZTI-JGR 366 JRC-HT 29 AZTI-JGR 268
_4: diving
_6: 0-1 EQR
_14: Posidonia oceanica Multivariate Index (POMI)
_15: State
_16: Biotope Features
_18: Complex statistics
_5:
shoot density (number of shoots/m2), shoot area cover (%), Plagiotropic rhizomes, Shoot Foliar Surface, Leaf Necrosis, N content in rhizome, P content in rhizomes, Sucrose in rhizomes, δ15N ratio in rhizomes, δ34S ratio in rhizomes, Epiphyte N content, [Cu] in rhizomes, [Pb] in rhizomes, [Zn] in rhizomes

_9:
Yes; a) by choosing three sampling sites, distant 100 m one from each other, and performing the entire protocol at each site, in eight of the meadows of the monitoring network, in two different sampling periods and in two deeps b) by performing a sensitivity test of the POMI (adding random variation to the descriptors)


name: Age-frequency distribution of fish
_0: AZTI-JGR 175b
_10: these parameters are used as separate indicators
_14: [fish] Population demographic characteristic
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Food provision} {Leisure and recreation}
_5:
length-frequency distribution, age-frequency distribution, fecundity rate, sex ratio, survival/mortality rate

_13:
MariLim: We had to split indicator AZTI-JGR 175 into its parameters to fit better with other indicators.


name: Sex ratio of fish
_0: AZTI-JGR 175d
_14: [fish] Population demographic characteristic
_15: State
_16: Population Ecology
_18: Simple statistics
_5:
length-frequency distribution, age-frequency distribution, fecundity rate, sex ratio, survival/mortality rate

_10:
MariLim: We had to split indicator AZTI-JGR 175 as parameters mentioned there are used separately and not combined.


name: Mortality rate of seaturtles
_0: AZTI-JGR 178c
_13: MariLim: Please specify this indicator in terms of indicator description and data requirements.
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_10:
MariLim: We had to split indicator AZTI-JGR 178 as parameters mentioned there are used separately and not combined.

_14:
[sea-turtles] demographic characteristics, longest shell, fecundity rate, mortality rate, genetic structure


name: Age-frequency distribution of Pinna nobilis
_0: AZTI-JGR 266b
_14: [Pinna nobilis] density, age-frequency distribution and population demographics
_15: State
_16: Indicator Species
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_10:
MariLim: We had to split indicator AZTI-JGR 266 in its three parameters to be consistant with other indicators. 
JRC: To be checked, because it is not clear how the metrics in the original indicator name are used, together or separately.

_13:
MariLim: We had to split indicator AZTI-JGR 266 into its parameters to fit better with other indicators.


name: Biomass of zooplankton
_0: AZTI-JGR 167b, AZTI-JGR 155b, JRC-HT
_10: For the use of abundance check entry 'Abundance of zooplankton' (AZTI-JGR 155a).
_14: [zooplankton] biomass and abundance
_15: State
_16: Community Structure
_18: Simple statistics
_5:
statistical descriptors (box-plot) of the biomass of functional groups (global, segmented by season, segmented by space).


name: Biomass of phytoplankton
_0: AZTI-JGR 164b
_10: split
_13: split or used toghether, clarify AZTI
_14: biomass and abundance
_15: State
_16: Production
_18: Simple statistics
_19: {Climate regulation}
_5:
statistical descriptors (box-plot) of the biomass and abundance of taxa (global, segmented by season, segmented by space).


name: Biomass, species composition and spatial distribution of zooplankton (FW6)
_0: Cefas - CL 136b, JRC-HT
_10: FW6 is an OSPAR Candidate Indicator.
_12: {OSPAR common indicator}
_14: FW6 Biomass, species composition and spatial distribution of zooplankton
_15: State
_16: Foodweb
_5:
Biomass (e.g. μg C/m2) is calculated using abundance of zooplankton and their individual weight or mean length. If length measurements are to be used, a species and/or size specific conversion factor will need to be applied.
Zooplankton community structure can be defined in terms of its species composition (diversity index) or in terms of its size structure (size spectra).

_11:
This indicator includes several parameters: biomass, community structure and spatial distribution of zooplankton.
Zooplankton constitutes a link between primary producers and higher trophic levels in the food web where they play an important role in the energy transfer. Long-term changes in the biomass, species composition and size structure of zooplankton communities can be used to indicate environmentally driven changes in the pelagic system (Beaugrand et al. 2005, Beaugrand et al. 2010), and the possible impact of anthropogenic pressures such as nutrient enrichment and oil spills (HELCOM 2012). The zooplankton indicator is not very specific since it can respond to multiple pressures, however, zooplankton groups have fast turnover rates and therefore respond rapidly to changes in the environment and anthropogenic pressures.


name: Species diversity (Simpson) of benthic invertebrates
_0: MHI-OK 123a
_4: to be checked
_5: Abundance and biomass of the main macrozoobenthos species
_8: Not available
_14: Zoobenthos Shannon/Simpson Diversity Index
_15: State
_16: Community Structure
_18: Simple statistics
_10:
MariLim: We had to split indicator MHI-OK 123 in its single parameters to be consistent with other indicators.


name: Body length distribution of zooplankton
_0: SYKE-LU 20 SYKE-LU 68
_5: Zooplankton monitoring data
_6: zooplankton abundance; zooplankton biomass
_14: Zooplankton mean size and total abundance
_10:
Documentation at http://www.helcom.fi/Core%20Indicators/HELCOM-CoreIndicator-Zooplankton_mean_size_and_total_abundance.pdf

_11:
In this proposed core indicator for food web structure, the mean zooplankter size (MeanSize) is presented as a ratio between the total zooplankton abundance (TZA) and total biomass (TZB). This metrics is complemented with an absolute measure of total zooplankton stock, TZA or TZB, to provide a two-dimensional index, MSTS (Mean Size and Total Stock). This represents a synthetic descriptor of zooplankton community structure (by MeanSize) and the stock size (by TZA or TZB).


name: PREI - Posidonia oceanica Rapid Easy Index
_0: HCMR-NP 114b, JRC-HT
_6: 0-1 EQR
_14: PREI index (Posidonia)
_15: State
_16: Biotope Features
_18: Simple statistics
_10:
The method is used to assess the Ecological Status along Mediterranean coasts according to the WFD recommendations (Gobert et al. 2009). 

PREI was implemented in three differently impacted sites across the sedimentary coasts of Cyprus within the WFD monitoring program. 

The index has been applied by Cyprus (Good Environmental Status Report) in order to tackle Indicator 1.7.1 (Composition and relative proportions of ecosystem components (habitats and species)) of Criterion 1.7 (Ecosystem structure) for Descriptor 1

_11:
The Posidonia oceanica Rapid Easy Index (PREI) is based on five metrics: shoot density, shoot leaf surface area, E/L ratio (epiphytic biomass/leaf biomass), depth of lower limit, and type of this lower limit. 
Index algorithm:  EQR defined as an index integrating the averaging of the chosen individual metrics: EQR’= (N density + N leaf surface area + N (E/L) + N lower limit)/3.5


name: Abundance of benthic invertebrates
_0: HCMR- NP 111b
_5: number of individuals
_13: Unit: is it ind/m2?
_14: Macroalgae-abundance, Zoobenthos-abundance, Fishes-abundance.
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Bioremediation of waste}
_10:
MariLim: We had to split indicator HCMR-NP 111 in its three parameters to be consistent with other indicators.

_11:
Zoobenthos-abundance: The variation of benthic invertebrate abundance (number of individuals) across an anthropogenic gradient in eight Cyprus sedimentary sites was studied within the WFD monitoring program.


name: Abundance of fish
_0: HCMR- NP 111c
_14: Macroalgae-abundance, Zoobenthos-abundance, Fishes-abundance.
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Food provision} {Leisure and recreation}
_10:
MariLim: We had to split indicator HCMR-NP 111 in its single parameters to be consistent with other indicators.

_11:
The variation of fish abundance index (individuals km-2) was studied on a hierarchy of two spatial scales (depth zone, haul) along the Cyprus coasts. 


name: Species diversity (Margalef index) of plankton
_0: Cefas - CL 131b
_8: Low
_12: {OSPAR common indicator}
_14: PH3 Plankton biodiversity indices
_15: State
_16: Community Structure
_18: Simple statistics
_4:
Continuous plankton recorder survey or other, can be calculated from various samplers and a range of techniques

_6:
various - indices of diversity (eg Shannon, Menhinick, Simpson), richness (eg Margalef), eveness (eg Pielou) or dominance (eg Breger-Parker)

_13:
MariLim: We had to split indicator Cefas-CL 131 in its single parameters to be consistent with other indicators. Please check and precise your entries - Margalef index is a diversity index and not species richness, isn't it?


name: Species dominance (Breger-Parker) of plankton
_0: Cefas - CL 131f
_8: Low
_12: {OSPAR common indicator}
_14: PH3 Plankton biodiversity indices
_15: State
_16: Community Structure
_18: Simple statistics
_4:
Continuous plankton recorder survey or other
Can be calculated from various samplers and a range of techniques


name: Evenness of sandeelbanks
_0: AU-DKJ/JHA 135b
_9: see examples in tables of link
_14: Sandeelbankrichness and evenness
_15: State
_16: Community Structure
_18: Simple statistics
_13:
JRC: Which indicators are these exactly, please specify. And how are the indicators used here, together or separate?
MariLim: Specify Evenness Index: Pielou, Sheldon ... and for which components (benthic invertebrates, fish, ...?)


name: Areal extent of maerl-type biogenic sediments
_0: HCMR-NP 118b
_11: Mapping of the Maerl-type biogenic sediments.
_14: Mapping of the Maerl-type biogenic sediments
_15: State
_16: Biotope Features
_18: Simple statistics
_19: {Disturbance prevention or moderation} {Leisure and recreation} {Aesthetic experience}
_10:
Marine sub-divisions: 20, 22 & 23.
The two (2) above mentioned indexes have been suggested by Greece (Technical Report) in order to tackle Indicator 1.5.1 (Habitat Area) of Criterion 1.5 (Habitat Extent) for Descriptor 1. Both these habitats are considered protected and are inhabited by a large number of species, some of them endemic, while they also offer refuge for juveniles of other species. 

MariLim: We had to split indicator HCMR-NP 118 in its single parameters to be consistent with other indicators.

_13:
these are two indices or a single one? Mapping of the Posidonia oceanica meadows, Mapping of the Maerl-type biogenic sediments


name: WFD German Saltmarsh index
_0: MariLim-KF 26 JRC-HT 26
_4: aerial survey and direct surveys along transects
_6: EQR (unitless)
_14: Assessment for saltmarshes and reed beds in coastal and transitional waters
_15: State
_16: Biotope Features
_18: Simple statistics
_5:
extent of saltmarsh area within the water body (% cover), zonation of saltmarsh (% specific saltmarsh zone within the saltmarsh area)

_11:
Multimetric index assessing EQR values for BQE Angiosperms combining areal extent, width of vegetation zones and species composition.
Combination rule for multi-metrics: Weighted average metric scores.


name: WFD German Eastern Baltic Phytoplankton index
_0: JRC-HT 107 MariLim-KF 110
_5: chla measurements, species composition, cell counts, biovolume of species/taxa groups
_6: 0-1 EQR (unitless)
_14: Multimetric ecological phytoplankton assessment
_15: State
_16: Community Structure
_18: Simple statistics
_11:
Multimetric index assessing EQR values for BQE Phytoplankton using Chl a concentrations, biovolume, Cyanophyceae and  Chlorophyceae concentrations  (between may and sep).
Combination rule for multi-metrics: Weighted average metric scores.


name: Zooplankton species population size
_0: MHI-AG 117a, JRC-HT
_4: Jeddy net-150 (UML)
_5: Species composition, Abundance/biomass of zooplankton species
_14: Zooplankton species population size
_15: State
_16: Community Structure
_13:
Cefas - CL: used together in an index or as separate indicators  please clarify and split entries if necessary

Field 'Country' was "Ospar Contracting Parties". This has been removed since it is no country. Please update Data->Settings accordingly.


name: Catch per unit effort (CPUE) of selected fish species
_0: AZTI-JGR 317 AZTI-JGR 306 AZTI-JGR 305
_15: State
_16: Target Groups
_18: Simple statistics
_19: {Food provision}
_13:
MariLim: Please check if scientific names are correct and if tuna is really something else (and then which species) or just a repetition.

_14:
[Tuna] catch per unit effort (CPUE)
[Yellowfin-tuna] catch per unit effort (CPUE)
[Bluefin-tuna] catch per unit effort (CPUE)


name: CFR - Multimetric CFR index (Quality of Rocky Bottoms)
_0: AZTI-JGR 332 JRC-HT 74
_4: field visual surveys
_5: % cover; species composition
_6: 0-1 EQR
_10: CFR Index website: http://cfr.ihcantabria.com/cfr-index/
_14: CFR index (Quality of Rocky Bottoms) Quality of Rocky Bottoms (CFR)
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
A multimetric index using several parameters like cover of selected macroalgae species, ratio of opportunistic species (%) and species richness.


name: Concentration of nutrients
_0: MHI-OK 141 AU-DKJ/JHA 149
_14: Inorganic nutrients concentration nutrient concentration
_15: State
_16: Biotope Features
_18: Simple statistics
_5:
MHI-OK 141: DIN, DIP, Si concenrations within the water column
AU-DKJ/JHA 149: annual mean of TN, TP, winter mean of DIN, DIP


name: Concentration of oxygen at the bottom
_0: MHI-OK 142 IMAR-HV 111
_5: Oxygen concentrations
_6: mg/ l
_14: Near bottom O2 concentration Concentration of dissolved oxygen in the bottom water
_15: State
_16: Biotope Features
_18: Simple statistics
_19: {Bioremediation of waste}
_11:
Concentration of dissolved oxygen in the bottom water and/or in the upper sediment layer of the seafloor.


name: Conservation status of fish
_0: Cefas - SN 130 AZTI-JGR 295
_15: State
_16: Target Groups
_18: Categorical/Labelled
_14:
FC5 Conservation status of elasmobranch and demersal bony fish species (IUCN)
Conservation Status of Fish (CSFa, Piet et al., 2007)


name: Eveness (Pielou) of selected biological components
_0: HCMR- NP 109c HCMR- NP 110c HCMR- NP 108c Cefas - CL 131c
_4: For Plankton: Continuous plankton recorder survey or other
_5: Abundance and species composition data
_8: Plankton: Low
_15: State
_16: Community Structure
_18: Simple statistics
_10:
MariLim: We had to split indicator HCMR-NP 108, 109, 110, in its single parameters to be consistent with other indicators.

_14:
Zoobenthos-diversity indices
Fishes-diversity indices
Macroalgae-diversity indices.
PH3 Plankton biodiversity indices


name: Genetic population structure of selected biological components
_0: AZTI-JGR 185 AZTI-JGR 197 AZTI-JGR 178d AZTI-JGR 269
_15: State
_16: Community Structure
_10:
MariLim: We had to split indicator AZTI-JGR 178 as parameters mentioned there are used separately and not combined.

_14:
[Mammals] population genetic structure based stable isotope profiles and genetic markers
[seaturtles] genetic structure
[sea-turtles] demographic characteristics, longest shell, fecundity rate, mortality rate, genetic structure
[Seagrass] population genetic structure


name: MEDOCC
_0: AZTI-JGR 284 JRC-HT 57 AZTI-JGR 261
_4: Grab
_5: Relative abundance of sensitive/tolerant species
_6: 0-1 EQR
_15: State
_16: Life Traits
_18: Simple statistics
_11:
Multimetric index based on percentages of ecological groups of species grouped according to their sensitivity

_14:
MEDOCC
[Lagoons] composition and abundance of benthic invertebrates (diversity, percentage of sensitive species, percentage of opportunistic species, MEDOCC index)


name: Secchi depth
_0: AU-DKJ/JHA 148 MHI-OK 140 IO-BAS 19 IO-BAS 23
_4: Secci disc
_5: AU-DKJ/JHA: summer mean values
_6: m
_9: AU-DKJ/JHA: see examples in tables of link
_11: Measuremtns of Secchi depth
_14: Secchi depth Water transparency water column transparancy
_15: State
_16: Biotope Features
_18: Simple statistics
_19: {Climate regulation}
_13:
MariLim: IO-BAS Please specify why there exist two targets/references values - maybe for different geographical areas? If so please use use MS official subdivision in settings to specify the area. 


name: Abundance of macroalgae (total cover)
_0: AU-DKJ/JHA 78 HCMR- NP 111a KAUST-SC 113 JRC-HT 78
_4: replicate line transects diver observations
_6: %
_11: Cover of the macroalgal community with information on water depth
_15: State
_16: Biotope Features
_18: Simple statistics
_19: {Climate regulation} {Leisure and recreation} {Aesthetic experience}
_5:
total macroalgal cover (%), water depth, position, cover of hard substratum, macroalgal community (cover of individual species)

_9:
U-DKJ/JHA: see examples in tables of Source Andersen et al. 2012
We analysed the sensitivity of the algal variables through evaluation of the stochastic variation of the variables and through power analyses. Power analyses were conducted on the basis of the three components of stochastic variation associated with each algal variable, i.e. variation due to divers, variation between sites and residual variation/variation between replicates.

_10:
MariLim: We had to split indicator HCMR-NP 111 in its single parameters to be consistent with other indicators.

_14:
Total macroalgal cover (at specific depths)
Macroalgae-abundance, Zoobenthos-abundance, Fishes-abundance.
Algal cover
Total macroalgal cover


name: Abundance of demersal elasmobranchs
_0: AZTI-JGR 157a AZTI-JGR 172
_5: mean abundances
_11: Mean abundance of demersal elasmobranchs
_15: State
_16: Target Groups
_18: Simple statistics
_19: {Food provision} {Leisure and recreation} {Aesthetic experience}
_10:
MariLim: We had to split indicator AZTI-JGR 157 to abundance and biomass to be consistant with other indicators.

_14:
[Demersal elasmobranchs] population abundance and/or biomass
[demersal elasmobranchs] mean abundance


name: Species diversity (Shannon index) of benthic invertebrates
_4: Grab
_5: abundance and species composition data
_6: bit/ind bits/indiv (H' log2)
_11: Assessing the diversity of benthic invertebrate communities by using the Shannon Index.
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Bioremediation of waste}
_0:
MHI-OK 123a, IO-BAS 6, IO-BAS 40, IO-BAS 48, IO-BAS 51, IO-BAS 57, IO-BAS 61, IO-BAS 64, IO-BAS 68, JRC-HT 42, HCMR-NP 7b, HCMR-NP 109d

_10:
MariLim: We had to split indicator HCMR-NP 7 and 109 in its three parameters to be consistent with other indicators.

_14:
Index of Sannon-Weaver, Shannon-Wiener diversity index (H'), H' index (Shannon Index), Zoobenthos-diversity indices


name: Surface area/biomass ratio of selected macroalgae species
_0: IO-BAS 15 IO-BAS 25 MHI-OK 131
_4: (Morozova-Vodianitskaija 1936). (Kalugina-Gutnik 1975).
_5: surface area, biomass, species composition
_11: Surface area/ volume (weight) ratios of dominant macropytobenthos sp.
_14: Index of population surface Benthic flora morphofunctional Index
_15: State
_16: Community Structure
_18: Simple statistics
_13:
MariLim: please specify surface area - is this maybe cover (in %) per suitable substrate area or thallus surface?


name: Species richness of fish
_0: AU-DKJ/JHA 129 KAUST-SC 16 HCMR- NP 110b
_5: Number of fish species
_9: AU-DKJ/JHS: see examples in tables of link
_14: Species richness (fish) Fish population diversity Fishes-diversity indices
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_4:
KAUST-SC: quadrats at certain intervals (5m, 10m)  at areas with contrasting disturbance levels; quadrat sampling over one hour period (other time periods are also used) at several sites; IUCN (World Conservation Union (formerly International Union for the Conservation of Nature) quantitative line transect method

_10:
MariLim: We had to split indicator HCMR-NP 110 in its single parameters to be consistent with other indicators.


name: Species richness of macroalgae
_0: AU-DKJ/JHA 123 HCMR- NP 108b
_4: AU-DKJ/JHA: diver observations - Danish marine monitoring programme
_5: species number
_9: AU-DKJ/JHA: see examples in tables of link
_14: Macroalgae species richness Macroalgae-diversity indices.
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Bioremediation of waste}
_10:
MariLim: We had to split indicator HCMR-NP 108 in its single parameters to be consistent with other indicators.


name: Species richness of plankton
_0: SYKE-LU 113 AU-DKJ/JHA 124 AZTI-JGR 265a
_6: unitless
_9: AU-DK/JHA: see examples in tables of link
_11: SYKE-LU: Indicator describes how zooplankton species richness changes in an area.
_15: State
_16: Community Structure
_18: Simple statistics
_5:
SYKE-LU: Zooplankton count data. Ratio between the number of species observed in the area and number of species registered in the area. 1 = no change, <1 -> decrease, >1 -> invasions

_10:
MariLim: We had to split indicator AZTI-JGR 265 as parameters mentioned there are used separately and not combined.

_13:
MariLim: AU-DK/JHA have named the indicator "zoobenthos species richness", but chosen "zooplankton" as biological component. Please confirm, which component it is.

_14:
Species richness
Zoobenthos species richness
[Lagoons] composition, abundance and biomass of phytoplankton species (diversity indices, evenness, etc.)


name: Species diversity (Shannon index) of plankton
_0: AZTI-JGR 265b Cefas - CL 131a
_5: Species composition and abundance data
_6: unitless
_8: Low
_15: State
_16: Community Structure
_18: Simple statistics
_4:
Continuous plankton recorder survey or other
Can be calculated from various samplers and a range of techniques

_10:
MariLim: We had to split indicator AZTI-JGR 265 and Cefas-CL 131 as parameters mentioned  are used separately and not combined.

_14:
[Lagoons] composition, abundance and biomass of phytoplankton species (diversity indices, evenness, etc.)
PH3 Plankton biodiversity indices


name: Species diversity (Shannon index) of fish
_0: KUCORPI-MBAZ 10 HCMR- NP 110d IO-BAS 1
_4: nets and trawl sampling
_6: unitless bit/ind
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_5:
abundance of species, species composition
IO-BAS: Abundance of fish species of non-comercial importance 

_10:
MariLim: We had to split indicator HCMR-NP 110 in its single parameters to be consistent with other indicators.

_14:
Community Diversity Index (Shannon index)
Fishes-diversity indices
Index of biodiversity Sannon -Weaver


name: Mortality rate of fish
_0: AZTI-JGR 175f AU-DKJ/JHA 127
_9: see examples in tables of link
_14: [fish] Population demographic characteristic F (fishery mortality) of selected fish species
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Food provision}
_5:
mortality rate
AU-DKJ/JHA: selected fish species: cod, sole, hering, plaice, haddock, saithe depending on area

_10:
MariLim: We had to split indicator AZTI-JGR 178 as parameters mentioned there are used separately and not combined.

_13:
MariLim: How is the mortality rate calculated? Based on by-Catch? Please specify this indicator in terms of descrition and data requirements.


name: MTI - Marine Trophic Index
_0: Cefas - CL 135 IMAR-HV 110
_6: abundance * TL
_8: High, but primarily met under existing national programmes. Gap analysis necessary.
_9: The mean trophic level of landings is a numerical value that ranges from 1 to 5.
_15: State
_16: Foodweb
_18: Simple statistics
_4:
Cefas-CL: Scientific fisheries surveys that sample the whole fish community, annually in same area with standard gear

_5:
Data from the commercial landings of exploited species (i.e., algae, invertebrates, fish, marine mammals) (Pauly  et al., 1998); can also be calculated from any measure of biomass or abundance derived from routine fishery-independent surveys, for different spatial and temporal scales; Also, the index could be applied to any assemblage (not just fish) for which there is abundance data for species at known TL.
Two data sets are needed to calculate the indicator: (i) catch data by taxonomic groups, and (ii) one estimate of trophic level for each of these groups.

_10:
‘Marine Trophic Index’ (MTI), as endorsed by the Convention on Biological Diversity; The term ‘MTI’ is in fact the CBD’s name for the mean trophic level (TL) of fisheries landings, originally used by Pauly et al. (1998) 

_11:
The marine trophic index is a state indicator which measures the change in mean trophic level of fisheries landings by region and globally. Trophic level is defined as the position of an organism in the food chain, and ranges from a value of 1 for primary producers up to a level of 5 for some marine mammals. Trophic level also changes through the life history of fish, with juveniles having lower trophic levels than adults. Unsustainable fisheries lead to a depletion of large bodied and higher trophic level species (particularly piscivorous fish) eventually leading to rarity or absence of such species and dominance of small-bodied species with high rates of population turnover, usually from lower trophic levels (CBD, 2004).

_14:
FW-4 Changes in average trophic level of marine predators (e.g. Marine Trophic Index)
Marine  Trophic Index (MTI)


name: Impacts of anthropogenic removal of target species
_0: UHULL-KM 154 UHULL-KM 173
_5: Level of exposure of habitat to pressure 'removal of target species'
_15: Pressure
_16: Anthropogenic Activities
_10:
MariLim: It was impossible for us to identify the difference of the two indicators based on your catalogue entries. 

_14:
Impact/vulnerability of habitats to removal of target species (biological pressure) (Condition of typical species and communities)
Impact/vulnerability of habitat to 'removal of target species' (Biological pressure) (Condition of typical species and communities)


name: Impacts of anthropogenic removal of non-target species
_0: UHULL-KM 174 UHULL-KM 155
_15: Pressure
_16: Anthropogenic Activities
_5:
Level of exposure of habitat to pressure 'removal of non-target species'
Level of exposure to pressure 'removal of non-target species'

_10:
MariLim: It was impossible for us to identify the difference of the three indicators based on your catalogue entries. 

_14:
Impact/vulnerability of habitat to 'removal of non-target species' (Biological pressure) (Condition of typical species and communities)
Impact/vulnerability of habitats to removal of non-target species (biological pressure) (condition of typical species/communities)


name: Impacts of anthropogenic sediment penetration and/or disturbance below the seabed surface
_0: UHULL-KM 156 UHULL-KM 151 UHULL-KM 175 UHULL-KM 170
_11: Impacts to the seabed due to anthropogenic penetration and/or disturbance
_15: Pressure
_16: Anthropogenic Activities
_5:
Level of exposure to pressure 'penetration and /or disturbance to the substratum below the surface of the seabed
Level of exposure of habitat to pressure 'penetration and/or disturbance of the substratum below the surface of the seabed'
Level of exposure of habitat to pressure 'penetration and/or disturbance of the substratum below the surface of the seabed'
Level of exposure of habitat to pressure 'penetration and/or disturbance of the substratum below the surface of the seabed'

_14:
Impact /vulnerability of habitat to 'penetration and/or disturbance of the substratum below the surface of the seabed' (physical pressure) (Extent of seabed significantly affected by human activities for differnet substratum types
Impact/vulnerability of habitat to penetration and/or disturbance below the surface of the seabed (physical pressure) (Condition of typical species/communities)
Impact/vulnerability of habitat to 'penetration and /or disturbance of the substratum below the surface of the seabed (physical damage) (extent of seabed significantly affected by human activities for different substratum types)
Impact/vulnerability of habitat to 'penetration and /or disturbance of the substratum below the surface of the seabed (physical damage) (condition of typical species and communities)


name: Impacts of anthropogenic shallow abrasion/penetration damage to seabed surface
_15: Pressure
_16: Anthropogenic Activities
_0:
UHULL-KM 158
UHULL-KM 177
UHULL-KM 172
UHULL-KM 152
UHULL-KM 157
UHULL-KM 176
UHULL-KM 153
UHULL-KM 171

_5:
Level of exposure to pressure 'surface abrasion:damage to seabed surface features'
Level of exposure to pressure ' surface abrasion: damage to seabed surface features'
Level of exposure to pressure ' surface abrasion: damage to seabed surface features'
Level of exposure of habitat to pressure 'shallow abrasion/penetration:damage to seabed surface and penetration'
Level of exposure of habitat to pressure 'shallow abrasion/penetration:damage to seabed surface and penetration'
Level of exposure of habitat to pressure 'shallow abrasion/penetration: damage to seabed surface and penetration
Level of exposure of habitat to pressure 'surface abrasion: damage to seabed surface features'
Level of exposure of habitat to pressure 'shallow abrasion/penetration: damage to seabed surface and penetration

_10:
MariLim: It was impossible for us to identify the difference of the three indicators based on your catalogue entries. 

_14:
Impact/vulnerability of habitat to 'surface abrasion: damage to seabed surface features (physical pressure) (Extent of seabed significantly affected by human activities for the different substratum types.
Impact/vulnerability of habitat to 'surface abrasion: damage to seabed surface features (physical pressure) (Extent of the seabed significantly affected by human activities for the different substratum types)
Impact/vulnerability of habitat to 'surface abrasion: damage to seabed surface features (physical pressure) (condition of typical species and communities)
Impact/vulnerability of habitat to shallow abrasion/penetration: damage to seabed surface and penetration (physical pressure) (Condition of typical species/communities)
Impact/vulnerability to shallow abrasion/penetration: damage to seabed surface and penetration (physical pressure) (extent of seabed significantly affected by human activities for the different substratum types)
Impact/vulnerability of habitat to 'shallow abrasion/penetration damage to seabed surface and penetration (Physical damage) (Extent of seabed significantly affected by human activities for the different substratum types)
Impact/vulnerability of habitat to surface abrasion: damage to seabed surface features (physical pressure) (Condition of typical species/communities)
Impact/vulnerability of habitat to 'shallow abrasion/penetration damage to seabed surface and penetration (Physical damage) (condition of typical species and communities)


name: IQI - Infaunal Quality Index
_0: UHULL-KM 166 JRC-HT 44
_4: Grab
_6: 0-1 EQR
_14: Infaunal quality index Infaunal Quality Index IQI
_15: State
_16: Community Structure
_18: Simple statistics
_5:
species composition and abundance, AZTI Marine Biotic Index (AMBI - taxonomical id & classification of taxa

_9:
The variability of the IQI scores within an assessment is estimated and, in combination with the number of samples/stations/years, the Standard Error (SE) is derived. Uncertainty is established by comparing the average IQI from the samples (with associated SE) to each status boundary. This allows the estimation of the probability that the average IQI (from the samples in the assessment) lies within a different status class than the true IQI. Uncertainty is not incorporated within the IQI itself.

_11:
Multimetric index based on the sensitivity, richness and diversity (evenness) of benthic communities (AZTI Marine Biotic Index (AMBI - taxonomical id & classification of taxa), Simpsons Evenness Index (1-λ'), Taxa number (S))


name: Abundance of populations of selected bird species (winter)
_4: 1 operational
_5: abundance of species
_6: number
_15: State
_16: Target Groups
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_0:
KUCORPI-MBAZ 3
KUCORPI-MBAZ 4
KUCORPI-MBAZ 1
KUCORPI-MBAZ 6
KUCORPI-MBAZ 5
KUCORPI-MBAZ 7
KUCORPI-MBAZ 2

_10:
" Abundance index of wintering waterbird species": http://www.sea.ee/marmoni/marmoni_pulk/docs/L34.pdf

"Wintering waterbird index": http://www.sea.ee/marmoni/marmoni_pulk/docs/L35.pdf

"Wintering indices for waterbirds of different feeding guilds (WWBIFG)": http://www.sea.ee/marmoni/marmoni_pulk/docs/L36.pdf

_14:
Abundance of wintering populations of seabirds: common merganser (Megus merganser)
Abundance of wintering populations of seabirds: great crested grebe (Podiceps cristatus)
Abundance of wintering populations of seabirds: long-tailed duck (Clangula hyemalis)
Abundance of wintering populations of seabirds: common goldeneye (Bucephala clangula)
Abundance of wintering populations of seabirds: red-throated and black-throated divers (Gavia stellata, G. arctica)
Abundance of wintering populations of seabirds: Steller's eider (Polysticta stelleri)
Abundance of wintering populations of seabirds: velvet scoter (Melanitta fusca)


name: Abundance ratio of selected phytoplankton taxa groups
_0: AZTI-JGR 308a
_5: species composition and abundance (cell counts)
_11: ratio diatoms/dinoflagellates.
_14: Abundance of phytoplankton, diatoms, dinoflagellates; and ratio diatoms/dinoflagellates.
_15: State
_16: Life Traits
_18: Simple statistics
_10:
ariLim: We had to split indicator AZTI-JGR 308 to abundance and ratio to fit better with other indicators.


name: WFD British Seagrass index
_0: JRC-HT 25 JRC-HT 24 UHULL-KM 165
_6: 0-1 EQR
_14: Intertidal Seagrass Seagrass WFD seagrass tool
_15: State
_16: Biotope Features
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_4:
Ireland: field survey with quadrats and the perimeter walked with a GPS
UK: aerial survey, field survey with quadrat or the perimeter walked with a GPS

_5:
Ireland: seagrass species composition (no. taxa), bed area cover (%), shoot density (%)
UK: seagrass species composition (no. taxa), bed area cover (m2), shoot density (%)

_11:
Ecological quality ratio based on species composition, density and extent of cover of seagrass communities


name: WFD Finnish Assessment system for coastal waters for phytoplankton
_0: JRC-HT 99 JRC-HT 90
_5: total biomass (mg/l), chla concentrations
_11: Combined parameters: average EQR values of each metric.
_15: State
_16: Production
_18: Simple statistics
_13:
MariLim: Please specify this indicator in terms of indicator description, descriptors, criteria and geography settings (a finnish partner knowing WFD assessments should do this)

_14:
Assessment system for coastal waters using phytoplankton total biomass (mg/l)
Assessment system for coastal waters using phytoplankton chlorophyll-a


name: Species richness of selected habitats
_0: UHULL-KM 142 AZTI-JGR 252 AZTI-JGR 254 AU-DKJ/JHA 135a AZTI-JGR 257
_5: abundance, species composition data of different benthic species and communities
_9: AU-DKJ/JHA: see examples in tables of link
_15: State
_16: Community Structure
_18: Simple statistics
_11:
Index for species richness of different benthic species and communities per habitat type (e.g. circalittoral and bathial soft bottom habitats, biongenic reefs, infralittoral rocky bottom habitats)

_13:
MariLim: AZTI-JGR - Please check our interpretation of the indicator in description. Otherwise we have to delete it, as it is not clear.
MariLim: AU-DKJ/JHA - Is it only species richness or a combination with evenness or are species richness and evenness calculated separately and not combined?
MariLim: U-HULL - Please check our interpretation of the indicator in description. Otherwise we have to delete it, as it is not clear, what this indicator is.

_14:
Composition and abundance of typical species on biogenic reef (condition of the typical species and communities)
species richness per habitat
Sandeelbankrichness and evenness
number of key species per class or type of habitat


name: Species richness of benthic invertebrates
_0: HCMR- NP 109b AZTI-JGR 330
_5: Species number
_14: Zoobenthos-diversity indices richness of benthic communities
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Bioremediation of waste}
_10:
MariLim: We had to split indicator HCMR-NP 109 in its single parameters to be consistent with other indicators.


name: Species diversity (Menhinick) of plankton
_0: Cefas - CL 131d IO-BAS 77
_5: species composition, abundance
_8: Low
_11: Species diversity index of Menhinick for plankton communities
_12: {OSPAR common indicator}
_14: PH3 Plankton biodiversity indices Index of biodiversity Menhinick
_15: State
_16: Community Structure
_18: Simple statistics
_4:
Continuous plankton recorder survey or other, can be calculated from various samplers and a range of techniques

_10:
MariLim: We had to split indicator Cefas-CL 131 in its single parameters to be consistent with other indicators.


name: Abundance (per unit of surface) of structuring/engineering species (per habitat)
_0: AZTI-JGR 322a
_10: AZTI-JGR 278,280,286 could be merged (D1), but AZTI-JGR 322 is D6
_14: biomass or abundance (per unit of surface) of structuring/engineering species (per habitat)
_15: State
_16: Biotope Features
_18: Simple statistics
_13:
MariLim: AZTI, please specify this indicator in terms of the indicator description. Also add all relevant taxonomic groups, not only the general "Angiosperms"/alternatively make the indicator name more specific

_19:
{Climate regulation} {Disturbance prevention or moderation} {Bioremediation of waste} {Leisure and recreation} {Aesthetic experience}


name: Substrate condition
_0: AZTI-JGR 293 UHULL-KM 180 AZTI-JGR 291
_6: phi/µm/mm/%
_10: several metrics
_15: State
_16: Biotope Features
_18: Simple statistics
_5:
U-HULL-KM: Sediment grain size and proportion in bulk sediment classes (sand/silt/gravel)
AZTI-JGR: grain size, porosity, organic content, Eh, pollutans

_14:
hydrographic features, trophic characteristics, sediment characteristics 
Substratum composition/sediment character
sediment characteristics (grain size, porosity, organic content, Eh, pollutans) [Infralittoral soft bottom habitats]


name: Abundance ratio of fodder/non-fodder zooplankton
_0: MHI-AG 116a
_4: Jeddy net-150 (UML)
_5: species composition, abundance
_14: Zooplankton fodder/non-fodder ratio
_15: State
_16: Foodweb
_18: Simple statistics
_11:
The ratio of fodder/non-fodder zooplankton are trophic effect indicators and reflect for e.g. the inability of the system to deal with excess primary production, and may provide 'early-warning' signs when used together with other trophic indiators (in Vermaat et al. 2006 [book citation]: Vermaat, J., Bouwer, L., Turner, K., & Solomons, W. (2005). Managing European coasts. Past, present and future.).


name: Abundance of selected zooplankton species and taxa groups
_0: AZTI-JGR 165 AZTI-JGR 316a
_5: species composition and abundance data
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Biological control}
_10:
MariLim: We had to split indicator AZTI-JGR 316 to abundance and biomass to fit better with other indicators.

_14:
[zooplankton] abundance of taxa and characteristic species
Abundance/biomass of main zooplanktonic groups


name: Abundance of phytoplankton
_0: AZTI-JGR 156a AZTI-JGR 164a
_14: [Phytoplankton] population abundance and/or biomass biomass and abundance
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Climate regulation}
_5:
statistical descriptors (box-plot) of the biomass and abundance of taxa (global, segmented by season, segmented by space).

_10:
MariLim: We had to split indicator AZTI-JGR 156 to abundance and biomass to fit better with other indicators.
MariLim: We had to split indicator AZTI-JGR 164 to abundance and biomass to be consistent with other indicators.


name: Abundance of seals
_0: SYKE-LU 29 SYKE-LU 46 HCMR-NP 1
_6: abundance
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Leisure and recreation} {Aesthetic experience}
_10:
This is actually an environmental indicator adopted by Greece (Technical Report), concerning the Criteria (1.1: Species distribution, 1.2: Population size, 1.3: Population condition) of MSFD Descriptor 1.  

_14:
Abundance of seals
Abundance and long-term development of seal species (grey seal, ringed seal)
Size, characteristics and distribution of the population of monk seals in marine subareas


name: Abundance of selected benthic invertebrate species
_0: MHI-OK 120a IO-BAS 45 IO-BAS 42 IO-BAS 3 IO-BAS 38
_5: abundance
_6: ind./m2
_11: Average abundance of selected benthic invertebrate species
_14: Population size of key benthos fauna species abundance average abundance
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Food provision} {Bioremediation of waste} {Leisure and recreation} {Aesthetic experience}
_10:
MariLim: We had to split indicator MHI-JOK 120 in its parameters abundance and biomass to be consistant with other indicators.


name: Abundance of selected phytoplankton species and taxa groups
_0: AZTI-JGR 161 AZTI-JGR 308a
_5: species composition and abundance data
_11: Abundance of phytoplankton, diatoms, dinoflagellates; and ratio diatoms/dinoflagellates.
_15: State
_16: Community Structure
_18: Simple statistics
_19: {Climate regulation} {Biological control}
_10:
MariLim: We had to split indicator AZTI-JGR 308 to abundance and ratio to fit better with other indicators.

_14:
[phytoplankton] abundance of taxa and characteristic species
Abundance of phytoplankton, diatoms, dinoflagellates; and ratio diatoms/dinoflagellates.


name: Abundance of zooplankton
_0: AZTI-JGR 155a AZTI-JGR 167a KUCORPI-MBAZ 18a SYKE-LU 20 SYKE-LU 68
_6: mg/m3 or indv./m3 zooplankton abundance; zooplankton biomass
_15: State
_16: Community Structure
_18: Simple statistics
_5:
AZTI: statistical descriptors (box-plot) of the biomass and abundance of functional groups (global, segmented by season, segmented by space).
KUCORPI: mean biomass and total abundance of species
SYKE Zooplankton monitoring data

_10:
MariLim: We had to split indicator AZTI-JGR 155 to abundance and biomass to fit better with other indicators.
MariLim: We had to split indicator AZTI-JGR 167 to abundance and biomass to fit better with other indicators.
KUCORPI, SYKE: http://www.helcom.fi/Core%20Indicators/HELCOM-CoreIndicator-Zooplankton_mean_size_and_total_abundance.pdf

_11:
Kucorpi, SYKE: In this proposed core indicator for food web structure, the mean zooplankter size (MeanSize) is presented as a ratio between the total zooplankton abundance (TZA) and total biomass (TZB). This metrics is complemented with an absolute measure of total zooplankton stock, TZA or TZB, to provide a two-dimensional index, MSTS (Mean Size and Total Stock). This represents a synthetic descriptor of zooplankton community structure (by MeanSize) and the stock size (by TZA or TZB).

_14:
[Zooplankton] population abundance and/or biomass
[zooplankton] biomass and abundance
Zooplankton mean size and total abundance
Zooplankton mean size and total abundance


name: Areal extent of Posidonia oceanica meadows
_0: AZTI-JGR 238; HCMR-NP 118a
_14: Area occupied by Posidonia oceanica meadows; Mapping of the Posidonia oceanica meadows
_15: State
_16: Biotope Features
_18: Simple statistics
_10:
MariLim: We had to split indicator HCMR-NP 118 in two parameters to be consistent with other indicators.


name: Abundance of shade-adapted, slow growing calcareous species
_0: HCMR- NP 115b
_15: State
_16: Life Traits
_18: Simple statistics
_19: {Climate regulation}
_10:
The six (6) above mentioned indexes have been applied by Cyprus (Good Environmental Status Report) in order to tackle Criterion 6.2 (Condition of Benthic Community) for Descriptor 6. 

MariLim: We had to split indicator HCMR-NP 115 into its single parameters to be consistent with other indicators

_11:
Abundance of shade-adapted, slow growing calcareous species (ESG IC): At moderately impacted coasts, slow-growing, shade-adapted calcareous species (ESG IC) often dominate (Panayotidis et al. 2004). The variation of shade-adapted, slow growing calcareous (ESG IC) macroalgal abundance (% coverage) was studied on a hierarchy of spatial (site) and temporal (time) scales in Cyprus rocky coasts monitored during WFD program.

_14:
Abundance of perennial seaweeds, Abundance of shade-adapted, slow growing calcareous species, Abundance of opportunistic macroalgae, Ecological Evaluation Index (EEI), PREI index (Posidonia), BENTIX index


name: Abundance of opportunistic macroalgae
_0: HCMR- NP 115c
_15: State
_16: Indicator Species
_18: Simple statistics
_19: {Biological control}
_10:
MariLim: We had to split indicator HCMR-NP 115 into its single parameters to be consistent with other indicators

_11:
3)	Abundance of opportunistic macroalgae (ESG IIA): Nutrient excess and turbid conditions favour the growth of opportunistic macroalgae (Harlin 1995, Schramm and Nienhuis 1996, Viaroli et al. 2008) due to their efficient nutrient assimilation (Thompson and Valiela 1999). The variation of opportunistic (ESG IIA) macroalgal abundance (% coverage) was studied on a hierarchy of spatial (site) and temporal (time) scales in Cyprus rocky coasts monitored during WFD program.

_14:
Abundance of perennial seaweeds, Abundance of shade-adapted, slow growing calcareous species, Abundance of opportunistic macroalgae, Ecological Evaluation Index (EEI), PREI index (Posidonia), BENTIX index


name: EEI - Ecological Evaluation Index
_0: IO-BAS 26, IO-BAS 17, IO-BAS 27, HCMR-NP 114a
_4: Metallic frame; Box corer
_6: JRC: 0-1 EQR
_15: State
_16: Life Traits
_18: Simple statistics
_5:
JRC-HT: % coverage area Ecological State Group I, II species
IO-BAS: macroalgae community taxonomic structure (biomass)

_10:
Note that EEI and EEIc two versions of the index differ in algorithm and ecological status groups.

Although angiosperms are also covered by this method for soft bottom in coastal lagoons, they were not considered here, because coastal lagoons are out of the scope of the MSFD.

MariLim: We had to split inticator HCMR-NP 114 and 115 into its paramters to be consistent with other indicators.

_11:
macroalgae community taxonomic structure
The Ecological Evaluation Index (EEI) was inspired by the “alternative stable stages” theory. It is based on the well-known pattern where anthropogenic stress, for example eutrophication and heavy metal pollution, shifts the ecosystem from being pristine, where late-successional species are dominant, to a degraded state, where opportunistic, nitrophilous species are dominant (Orfanidis et al. 2011). EEI was implemented in three differently impacted sites of the rocky Cyprus coasts monitored within WFD program.
See EEI website for more details (link in Sources).

_14:
Ecological evaluation index (EEI), Ecological evaluation index (EEIc), Ecological Evaluation Index (EEI)


name: BENTIX
_0: HCMR-NP 7a, JRC-HT 51, HCMR-NP 114c
_4: Grab
_6: EQR (0-1)
_14: BENTIX index, BENTIX, BENTIX index
_15: State
_16: Life Traits
_18: Simple statistics
_5:
species taxonomical identification (or lowest reliable taxon. level possible), abundance (individuals count per area)

_9:
The software for the calculation of the index sets the limits of parameters under which the results are not within the confidence limits. These parameters are based on the lowest number of scoring species and the lowest number of the species in the matrix that is needed to calculated the index.

_10:
BENTIX has been used for the classification of benthic macroinvertebrates in Greek national monitoring project for WFD  in 80 operational and surveillance monitoring stations in the Ionian and Aegean Seas (Simboura et al., 2015).

BENTIX was also implemented in six differently impacted sites across the sedimentary coasts of Cyprus within the WFD monitoring program.

_11:
The BENTIX index was designed to fit the Mediterranean benthic ecosystem and to render a five step numerical scheme for the classification of benthic communities. It is a biotic index based on the concept of indicator groups and uses the relative contribution of tolerant and sensitive taxa in general, weighting them accordingly to the ratio of their occurrence in the benthic fauna by definition.
See BENTIX website for more details (link in Source).


name: Dietary functional group biomass
_0: Cefas - CL 154
_8: High, but primarily met under existing national programmes. Gap analysis necessary.
_14: Dietary functional group biomass
_15: State
_16: Foodweb
_18: Simple statistics
_4:
Scientific fisheries surveys that sample the whole fish community, annually in same area with standard gear.

_5:
Biomass of pelagic planktivores, pelagic piscivores, demersal benthivores, demersal planktivores and omnivores.


name: Biomass of structuring species
_0: AZTI-JGR 278 AZTI-JGR 286 AZTI-JGR 280
_15: State
_16: Biotope Features
_18: Simple statistics
_19: {Climate regulation} {Disturbance prevention or moderation} {Bioremediation of waste}
_14:
biomass of structure-forming species
biomass of structure-forming or bioconstructor species
biomass of structuring species


name: LFI - Large Fish indicator
_8: UK: High, but primarily met under existing national programmes. Gap analysis necessary.
_12: {HELCOM coreset} {OSPAR common indicator}
_15: State
_16: Foodweb
_18: Simple statistics
_19: {Food provision} {Leisure and recreation}
_0:
SYKE-LU 104, Cefas-SN 121, AZTI-JGR 304, AU-DKJ/JHA 133, IMAR-HV 109, SYKE-LU 16, SYKE-LU 37, JRC-HT

_4:
Fish catch statistics OR Scientific fisheries surveys that sample the whole fish community, annually in same area with standard gear OR Trawl gear

_5:
Fishery-dependent data, i.e. catch samples from commercial fishery; trawl survey data.

Estimates of biomass by size group and a size limit for each ecosystem is required

_10:
inclusion of pelagic species required for a food web indicator.

Documentation: http://www.helcom.fi/Core%20Indicators/HELCOM-CoreIndicator-Proportion_of_large_fish_in_the_community.pdf

http://www.sea.ee/marmoni/marmoni_pulk/docs/L4.pdf

_11:
OSPAR common indicator FC2.
Proportion of large fish by weight in assemblage.
The  LFI  is  an  indicator  of  fish  community  size composition. Has been specifically developed to support the  OSPAR EcoQO ecosystem approach to marine management (Greenstreet et al., 2011; Shephard et al., 2012). The LFI describes the proportion of fish biomass contributed by large individuals in the demersal fish community and is defined as  the ratio between the biomass of demersal fish above a length threshold over the  total fish biomass (Roumbouts et al., 2013)
The proportion of large fish in a community follows the structure of the fish community and particularly the proportion of large predatory fish, which are significant balancing features in a food web but at the same time target 
of commercial fishery. The ‘large fish indicator’ (LFI) is used as a proxy for anthropogenic influence on the ecosystem; while it shall not or only little be influenced by natural variability or processes, like recruitment. Fishing has a direct effect on the structure of fish communities, because it can lead to an increase in the relative abundance of small fish (Jennings et al., 1999) 
and reduces the mean body size within a population (Beverton and Holt, 1957). Based on this concept, the LFI maps the fishing pressure (Greenstreet et al., 2011). Several studies to understand and improve the LFI for different marine 
areas and surveys techniques are being prepared at the moment (Oesterwind et al., in prep.; Psuty et al., 2012a; Psuty et al., 2012b)

_14:
Large fish individuals from fishery-based data sources; FC2 OSPAR EcoQO for proportion of large fish (LFI); Large fish indicator (LF); Large Fish indicator (LFI); Proportion of large fish in the community; Abundance index of large (TL>250 mm) perch (Perca fluviatilis) in monitoring catches


name: Body length distribution of demersal fishes, elasmobranchs and invertebrates
_0: AZTI-JGR 177 AZTI-JGR 179
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Food provision} {Leisure and recreation}
_14:
[Demersal fishes and elasmobranchs] trends based upon 95th percentile of the fish length distribution
[Demersal fishes, elasmobranchs and  invertebrates] 95th percentile of the fish length distribution


name: Body length distribution of selected (long-living) benthic invertebrate species
_0: SYKE-LU 69 SYKE-LU 108
_6: ind/size class
_15: State
_16: Population Ecology
_18: Simple statistics
_14:
Size distribution of long-living macrozoobenthic animals
Size distribution of benthic long-living species


name: BQI - Benthic Quality Index
_0: MariLim-KF 129 SYKE-LU 38 SYKE-LU 39 JRC-HT 48 KUCORPI-MBAZ 20
_4: Van Veen graps
_5: taxonomic identification at species level, species count, species sensitivity classification
_6: EQR (0-1)
_14: Benthic Quality index (BQI)
_15: State
_16: Population Ecology
_18: Simple statistics
_19: {Bioremediation of waste}
_11:
Multimetric assessment system combining species number (richness),  abundance and autecological species information (sensitivity values)


name: CIMPAL - Cumulative IMPacts of invasive ALien species
_0: JRC-HT
_6: Unitless ranging from [0 - ∞]
_14: CIMPAL - Cumulative IMPacts of invasive ALien species
_15: Pressure
_16: Target Groups
_18: Simple statistics
_4:
Previous to index calculation the ecological impacts of each alien species considered in th calculation need to be identified (and the species-impact link needs to be associated to one of the habitat categories considered) and their magnitude assessed (quantitative or qualitatively).

_5:
- georeferenced species distribution data (abundance or presence-absence);
- georeferenced habitat distribution data;
- magnitude of all ecological impacts of a species in the ecosystem (be it on species, populations, community or habitat).

_8:
Not assessed.
However, the index can rely on global and regional datasets available and sampling already in place (e.g. EMODNET habitat maps or European Alien Species Information Network - EASIN), therefore its use would not require further monitoring efforts.

_9:
Five main sources of uncertainty have been identified for the CIMPAL index, which were associated to each of the parameters (n, m, Ai, Hj, wi,j) in the index algorithm. 
Uncertainty is presented following Mastrandrea et al. (2011). All details are published in Katsanevakis et al., (in review; to be updated soon).

_10:
The index is presented in Katsanevakis et al. (in review) and has been applied to the whole Mediterranean Sea.

_11:
The index is a standardized, quantitative method for mapping cumulative impacts of invasive alien species on marine ecosystems. It is based on a conservative additive model, according to which cumulative impact scores are estimated on the basis of the distributions of invasive species and ecosystems, the reported magnitude of ecological impacts and the strength of such evidence.
Criteria for which (or how many) alien species to include in the calculation depend on the user objectives.
A rise in the CIMPAL index score (Ic) indicates that IAS impacts on biodiversity are increasing, while impact scores approaching zero point to a decrease in the negative effects of IAS in biodiversity.


name: Common Size composition in fish communities (FW3)
_0: JRC-HT
_4: scientific fisheries surveys
_6: cm
_9: See Sources for details.
_12: {OSPAR common indicator}
_14: FW3 Common Size composition in fish communities (TyL)
_15: State
_16: Foodweb
_18: Simple statistics
_5:
number of fish in a sample (N)
body mass of each fish in a sample (M)
length of each fish in a sample (L)

_10:
Typical Length is an alternative indicator for fish community size structure, which does not contain a free parameter in its definition, as does e.g. the LFI OSPAR common indicator FC2, therefore the TyL facilites comparison and aggregation at larger-assessment scales.

_11:
Typical Length (TyL) is defined as the geometric mean length of fish, weighted 
by body mass.
The distribution of biomass over body sizes (size spectra) is an emergent property of food webs, thus size-based metrics that are sensitive and specific to pressures can be used as indicators of food web structure.


name: Changes in average trophic level of marine predators (FW4)
_0: JRC-HT
_5: species mean trophic level (TL) species biomass (only high trophic level species > 3.25)
_6: none
_12: {OSPAR common indicator}
_14: FW4 Changes in average trophic level of marine predators (Marine Trophic Index)
_15: State
_16: Foodweb
_18: Simple statistics
_4:
Biomass: fisheries catches and scientific survey data

TL: dietary analyses (estimated from local gut contents and isotopes analyses). Otherwise, estimates from trophic models such as Ecopath or estimates from online data portals, such as FishBase, can be used.

_11:
Marine Trophic Index (MTI) is calculated using both estimates of species biomass, usually derived from scientific surveys, and their mean trophic level. The trophic level (TL) expresses the position of an organism in a food web, and is estimated using data from dietary analyses. Only predators whose TL is higher than 3.25 are considered.
A decrease in Marine Trophic Index represents a decline in the abundance and diversity of fish species high in the food chain.


name: Ecological Network Analysis indicator (FW9)
_0: JRC-HT
_4: Most existing monitoring data for a certain region can be used to construct its food web.
_10: FW9 is an OSPAR Candidate Indicator. OSPAR Sources for this indicator to be soon updated.
_12: {OSPAR common indicator}
_14: FW9 Ecological Network Analysis indicator
_15: State
_16: Foodweb
_18: Modelling
_5:
The model will need information on the biomass of different trophic groups (e.g. production for phytoplankton) and dietary data that can be obtained from, e.g. stable isotopes, stomach contents, etc.
Minimum requirements are biomass of dominant compartments and the local primary production. Other variables for more precision: respiration, diets.

_8:
Relatively high, since data intensive. If data is available, then analysing the data (modelling) is not very costly but is time consuming and requires some expertise.

_11:
Two Ecological Network Analysis (ENA) indicators are proposed: flow diversity and trophic efficiency, for being holistic (represent the whole community) and functional (based on ecosystem functionning). 
Flow diversity is defined as Development Capacity/Total System Throughput; it encompasses both the numbers of interactions and the evenness of flows in the food web. A high value of flow diversity reflects a diverse and relatively stable food web, and can also be used as a link between food web characteristics and habitat diversity.
Trophic efficiency is the mean ratio of production of one trophic level to the production of the lower trophic level. A high value of Trophic Efficiency is supposed to be characteristic of a mature ecosystem.


name: Multimetric BENTIX
_0: JRC-HT
_6: 0-1 ES
_14: Multimetric BENTIX
_15: State
_16: Community Structure
_18: Simple statistics
_5:
BENTIX index; Shannon diversity index; Species richness.
(Search also respective catalogue entries for further details on BENTIX and Shannon diversity indices).

_11:
Multimetric Bentix was developed in order to integrate all indicators of benthic community conditions sensu the MSFD under the Sea-floor Integrity descriptor such as diversity, species richness, biotic indices (and provisionally size spectra indices) in a controlled way. This was decided after the realization that in the Mediterranean diversity indices did not show monotonic patterns of response to pressure gradients as the biotic indices did (WFD GIG, 2013). The method is an adaptation of a similar method applied across the MSFD descriptors in the Basque country (Borja et al., 2011) and assigns an increased weight to the biotic component. The scheme developed is a modular formula assigning weighting scores to each one of the components of a formula: one ‘biotic’ component and two ‘diversity’ components (and provisionally one ‘size’ component redistributing scores as 0.1 and 0.1 for Species richness and size component). Within the method, reference values for Diversity indices were set for calculating the EQRs.
The derived formula is as follows: 
Bentix EQR X 0.6 + Shannon EQR X 0.2 + Species richness EQR X 0.2 =ES


name: Accumulated cover of perennial macroalgae
_0: LU-SYKE
_4: drop-video
_5: Macroalgae coverage, %
_6: %
_14: Accumulated cover of perennial macroalgae
_15: State
_16: Target Groups
_18: Simple statistics
_10:
I've added MSFD relevance as indicated in the Marmoni indicators sheet.

http://www.sea.ee/marmoni/marmoni_pulk/docs/L9.pdf

_11:
This indicator reflects quantity of the perennial macroalgae community measured as accumulated cover, thus indicating biodiversity quantity as the amount of a diverse community of algae and species living on and among the algae. It indicates biodiversity quantity on shallow hard bottoms and may be used simultaneously with a vascular plant indicator for shallow soft bottoms. The measured unit is accumulated % cover and the assessment unit is the total aggregated accumulated cover within a predefined monitoring area.


name: Accumulated cover of submerged vascular plants
_0: LU-SYKE
_4: drop-video
_5: submerged vascular plant cover
_6: %
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L10.pdf
_14: Accumulated cover of submerged vascular plants
_15: State
_16: Target Groups
_18: Simple statistics
_11:
This indicator reflects quantity of the submerged vascular plant community measured as accumulated cover, thus indicating biodiversity quantity as the amount of the vascular plant community and associated species. It indicates biodiversity quantity on shallow soft bottoms in more sheltered areas and can be used simultaneously with the macroalgae indicator for shallow hard bottoms.


name: Beach wrack Macrovegetation Index (BMI)
_0: LU-SYKE
_4: Manual sampling on shore
_5: Sampled transects parallel to shore line
_6: unitless value between 0 and 1, 0 being high and 1 low
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L11.pdf
_14: Beach wrack Macrovegetation Index (BMI)
_15: State
_16: Target Groups
_18: Complex statistics
_11:
Indicator is based on the structure of macrovegetation of beach wrack. Representativeness of beach wrack data reflecting the biodiversity of macrovegetation in coastal area was tested during the study. Differences between submerged macrovegetation in coastal area and beach wrack samples were the smallest in July (table 1, Suursaar et al., 2014).


name: Indicator of macroalgal community structure (MCS)
_0: LU-SYKE
_4: diving or remote underwater video analysis
_5: coverage data of different functional and structural groups of macroalgae
_6: EQR - unitless value between 0 and 1
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L12.pdf
_14: Indicator of macroalgal community structure (MCS)
_15: State
_16: Target Groups
_18: Complex statistics
_11:
The indicator focuses on the phytobenthic community and its structural features. The macrophytes function both as a habitat and a food source for macrofauana and it is known that macrofaunal composition depends mainly on habitat architecture at a spatial microscale. Also that most faunal species show high mobility and dispersal rates and they colonize available habitats rapidly. Thus, though focusing only on plants, the indicator illustrates the macrofaunal community as well both in soht and hard substrates.


name: Habitat diversity index
_5: Habitat data on GIS format
_6: unitless
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L13.pdf
_14: Habitat diversity index
_15: State
_16: Biotope Features
_18: Simple statistics
_11:
Diversity of benthic habitats is one of the many aspects of marine biodiversity. High diversity of benthic habitats is important in order to maintain species diversity and ecosystem processes. Habitat diversity index indicates the level of diversity of marine benthic habitats by counting the number of different habitats in a predefined grid.


name: Seafloor exploitation index
_0: LU-SYKE
_5: Georeferenced data on direct anthropogenic disturbances on seabed
_6: %
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L14.pdf
_14: Seafloor exploitation index
_15: Pressure
_16: Anthropogenic Activities
_18: Simple statistics
_11:
Seafloor exploitation index measures the extent (area) of seabed that is impacted by direct physical anthropogenic disturbances.


name: Spectral variability index
_0: LU-SYKE
_4: Remote sensing
_5: Georeferenced remotely sensed imagery of a sea area
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L15.pdf
_14: Spectral variability index
_15: State
_16: Community Structure
_11:
Spectral variability index is based on the spectral variation hypothesis that predicts a positive correlation between spectral heterogeneity of a remotely sensed image and biodiversity. 


name: Condition of soft sediment habitats – the aRPD approach
_0: LU-SYKE
_5: RPD depth data
_6: cm
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L16.pdf
_14: Condition of soft sediment habitats – the aRPD approach
_15: State
_16: Biotope Features
_18: Simple statistics
_4:
The measure of RPD depth can be retrieved by several methods. Sediment profile imagery (SPI) has been widely used to assess the RPD depth

_11:
A soft bottom habitat in good condition can support a zoobenthic community able to sustain a favourable living environment e.g. through bioturbation processes and recirculation of organic material. The condition of the habitats is ultimately determined by oxygen conditions, which are as well pivotal in structuring the benthic communities (Cicchetti et al. 2006).


name: Population structure of Macoma balthica
_0: LU-SYKE
_4: Sampling of M. balthica
_5: size distribution of M. balthica
_6: EQR - unitless value between 0 and 1
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L17.pdf
_14: Population structure of Macoma balthica
_15: State
_16: Community Structure
_18: Simple statistics
_11:
Deviation from the natural size distribution within the population of a species can be used as an indicator of disturbance in reproduction and/or survival, thus indicating the state of the population.


name: Cladophora glomerata growth rate
_0: LU-SYKE
_4: sampling
_5: Growth rate of C. glomarata
_6: EQR - unitless value between 0 and 1
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L18.pdf
_14: Cladophora glomerata growth rate
_15: State
_16: Indicator Species
_18: Simple statistics
_11:
The indicator describes the abundance of Cladophora glomerata in an assessment unit. The abundance of the C. glomerata vegetation is expressed as growth rate, derived from information on frond length and the length of the growth period.


name: Number of functional traits (NFT)
_0: LU-SYKE
_5: number of functions (biological traits) in the system
_6: number of traits
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L21.pdf
_14: Number of functional traits (NFT)
_15: State
_16: Life Traits
_18: Simple statistics
_11:
The development of this diversity index is based on the evidence that the presence of various functional groups in a community hints the functional diversity and ecosystem services performed by the community.


name: Areal extent of reed belts
_0: LU-SYKE
_4: Remote sensing
_5: Extent of reed belts
_6: area
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L23.pdf
_14: Reed belt extent – the NDVI approach via high resolution satellite images
_15: State
_16: Indicator Species
_18: Simple statistics
_11:
The indicator expresses the extent of coastal reed belts, using information from remote sensing and exposition-depth data.


name: Age/sex ratio of waterbird species (ARI/SRI)
_0: LU-SYKE
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L44.pdf
_14: Age/sex ratio of waterbird species (ARI/SRI)
_15: State
_16: Target Groups
_11:
This indicator consists of two single species indicators reflecting population condition of particular species. Separate indices are calculated for age ratios and sex ratios. Indices are calculated for all species holding considerable populations in the Baltic Sea in any of the seasons where they have sex and/or age specific differences in plumage that are distinguishable using the selected data collection method.


name: Proportion of oiled waterbirds
_0: LU-SYKE
_6: EQR - unitless value between 0 and 1
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L45.pdf
_14: Proportion of oiled waterbirds
_15: Pressure
_18: Simple statistics
_11:
This indicator reflects impact and specific pressure of oil pollution to waterbirds in marine environment. 


name: Abundance index of beached birds
_0: LU-SYKE
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L46.pdf
_11: This indicator reflects mortality of birds due to different reasons
_14: Abundance index of beached birds
_15: Pressure
_16: Target Groups
_18: Simple statistics
_4:
Data for this indicator should be collected using coastal surveys and
recording all beached birds as well as possible cause of their death.


name: Indicator on condition of waterbirds
_0: LU-SYKE
_4: sampling of by-caught birds
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L48.pdf
_14: Indicator on condition of waterbirds
_15: Pressure
_16: Physiological Condition
_18: Categorical/Labelled
_11:
A body condition index based on condition of the pectoral flight muscles and the presence and quantity of subcutaneous and intestinal fat depots.


name: Feeding pressure on waterbird food sources
_0: LU-SYKE
_4: Field data collection: using any of the standard methods.
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L49.pdf
_14: Feeding pressure on waterbird food sources
_15: Pressure
_11:
This indicator reflects impact and specific pressure of feeding marine birds on their food resources/other organisms in their food-chain/structure and conditions of their habitat and its forming species.


name: Abundance and distribution of juvenile flounder
_0: LU-SYKE
_4: beach seine
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L1.pdf
_14: Abundance and distribution of juvenile flounder
_15: State
_18: Simple statistics
_11:
the abundance and distribution of juvenile flounders in shallow sandy habitats can be used as an indicator linked to fish reproduction and environmental status of coastal waters.


_0: LU-SYKE
_4: benthic trawl, benthic invertebrate monitoring
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L2.pdf
_15: State
_18: Simple statistics
name:
Long term abundance and distribution of demersal fish in relation to benthic communities (fourhorn sculpin Myoxocephalus quadricornis and  eelpout Zoarces viviparous example)

_11:
The indicator demonstrates trophic relationships between demersal fish and benthic fauna. Biomass of fourhorn sculpin (Myoxocephalus quadricornis) and eelpout (Zoarces viviparous) plotted against biomass of benthic invertebrates.

_14:
Long term abundance and distribution of demersal fish in relation to benthic communities (fourhorn sculpin Myoxocephalus quadricornis and  eelpout Zoarces viviparous example)


name: Abundance and impact of non-native fish species (round goby example)
_0: LU-SYKE
_4: Experimental fishing by coastal net series survey nets.
_6: mean biomass per one sampling station)
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L3.pdf
_14: Abundance and impact of non-native fish species (round goby example)
_15: State
_11:
Indicator reflects primary and secondary invasions of non-native species and is related to various pressures like shipping, ballast water discharge, climate change depending on introduction route of particular non-native species. The indicator describes relative abundance of particular non-native species within an area of concern and its impact on the biodiversity and food web at habitat/ecosystem level.


name: The length at sexual maturation of female pikeperch (Sander lucioperca) in monitoring catches
_4: experimental fishing, trawl or fyke-net
_6: cm
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L5.pdf
_14: The length at sexual maturation of female pikeperch (Sander lucioperca) in monitoring catches.
_15: State
_11:
The indicator describes the average size (TL) at which female pikeperch of monitored populations reach maturity. This indicator should be considered as index of the population’s size and age distribution and should be associated to fishing pressure (both commercial and recreational) on local fish communities. Decrease in the values of this indicator may be symptom of strong fishing pressure which may have lead to life-history shift in local pikeperch populations. The latter can further lead to decrease in the mean trophic level of the community, which in turn may lead to decline in local biodiversity.


name: Trophic diversity index of juvenile fish
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L7.pdf
_14: Trophic diversity index of juvenile fish
_15: State
_18: Simple statistics
_11:
This indicator reflects the diversity of juvenile fish weighted by the mean community trophic level of adults. A high value of the indicator should reflect an overall high diversity in terms of juvenile fish and favorable nursery habitats for key predatory fish species such as pike (Esox lucius), perch (Perca fluviatilis) and pikeperch (Sander lucioperca), which are important for the maintenance of food web integrity (Eriksson et al. 2009).


name: Habitat-related functional diversity of juvenile fish
_4: underwater detonations
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L8.pdf
_14: Habitat-related functional diversity of juvenile fish
_15: State
_18: Simple statistics
_11:
This indicator reflects the functional biodiversity of 0-group (juvenile) fish species in terms of habitat preference and is based on the diversity of species that have a preference for high temperatures and a strong affinity for vegetation. The classification of preference follows Sandström et al. (2005, Table 1). A high value of the indicator should reflect a high diversity of species within the defined functional group as well as warm and vegetated areas functioning as nursery areas for both pike (Esox lucius), perch (Perca fluviatilis) and many cyprinids.


name: Phytoplankton species assemblage clusters based on environmental factors
_5: phytoplankton biomass
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L24.pdf
_14: Phytoplankton species assemblage clusters based on environmental factors
_15: State
_18: Complex statistics
_11:
Indicator based on 7 summer phytoplankton species clusters obtained with a cluster analysis. Most clusters appeared at all stations at each sampling occasion, if a cluster was absent, it was assigned a biomass of 0. Relationships with environmental factors were tested with GAM models.


name: Cyanobacterial surface accumulations - the CSA-index
_4: remote sensing
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L26.pdf
_14: Cyanobacterial surface accumulations - the CSA-index
_15: State
_16: Target Groups
_11:
The indicator compares the recent (current) cyanobacterial surface accumulation
characteristics with past observations. It is based on information on the yearly intensity, duration and temporal volume of cyanobacterial blooms in the Baltic Sea. Information from these indicative variables is normalized and combined to produce a Cyanobacterial Surface Accumulation index (CSA-index). The CSA-index time series is used to provide the indicator target condition (2003-2010) and the current status (years 2011-2013). The principal data source for the indicator is satellite remote sensing, but the indicator can be complemented with observations obtained using other monitoring methods.


name: Phytoplankton trait- and dendrogram based functional diversity index (FD)
_5: microscopy results of phytoplankton
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L28.pdf
_14: Phytoplankton trait- and dendrogram based functional diversity index (FD)
_15: State
_16: Target Groups
_11:
The indicator aims to describe the trait-based functional diversity of phytoplankton with a functional diversity index (FD), which is calculated based on the dendrogram method
.


name: Spring bloom intensity index
_0: LU-SYKE
_4: FerryBox, remote sensing
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L29.pdf
_14: Spring bloom intensity index
_15: State
_16: Target Groups
_11:
The indicator estimates the annual total biomass of the phytoplankton spring bloom. Spring is a period of extensive and rapid phytoplankton growth, during which the main part of the annual phytoplankton production occurs


name: Copepod biomass
_0: LU-SYKE
_6: mg m3-1
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L30.pdf
_14: Copepod biomass
_15: State
_16: Target Groups
_11:
The indicator is based on the idea that zooplankton with a high mean size, i.e. copepods, would indicate good feeding conditions for zooplanktivorous fish as well as a high potential grazing on phytoplankton.


name: Zooplankton diversity
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L31.pdf
_14: Zooplankton diversity
_15: State
_18: Simple statistics
_11:
The indicator aims to describe the species diversity of zooplankton in the Baltic Sea by applying Shannon’s diversity index


name: Biomass of microphagous mesozooplankton
_0: LU-SYKE
_6: mg m-3
_10: http://www.sea.ee/marmoni/marmoni_pulk/docs/L32.pdf
_14: Microphagous mesozooplankton biomass
_15: State
_18: Simple statistics
_11:
The indicator is based on the idea that small-sized herbivorous zooplankton indicate a limitation in the ability of the zooplankton community to transfer energy from primary producers to higher trophic levels


name: Species distributional range (ComInd3)
_0: JRC-HT
_11: Species distributional range (related to marine mammals, seabirds, marine reptiles).
_12: {Barcelona convention indicator}
_15: State
_16: Target Groups
_18: Simple statistics
_14:
Species distributional range (related to marine mammals, seabirds, marine reptiles) (Common Indicator 3)


name: Population abundance of selected species (ComInd4)
_0: JRC-HT
_11: Population abundance of selected species (related to marine mammals, seabirds, marine reptiles).
_12: {Barcelona convention indicator}
_15: State
_16: Population Ecology
_14:
Population abundance of selected species (related to marine mammals, seabirds, marine reptiles) (Common Indicator 4)


name: Population demographic characteristics (ComInd5)
_0: JRC-HT
_12: {Barcelona convention indicator}
_15: State
_16: Population Ecology
_11:
Population demographic characteristics (e.g. body size or age class structure, sex ratio, fecundity rates, survival/mortality rates related to marine mammals, seabirds, marine reptiles).

_14:
Population demographic characteristics (e.g. body size or age class structure, sex ratio, fecundity rates, survival/mortality rates related to marine mammals, seabirds, marine reptiles) (Common Indicator 5)


_0: JRC-HT
_12: {Barcelona convention indicator}
_15: Pressure
_16: Target Groups
name:
Trends in abundance, temporal occurrence, and spatial distribution of NIS, particularly IAS, notably in risk areas (ComInd6)

_11:
Trends in abundance, temporal occurrence, and spatial distribution of non-indigenous species, particularly invasive, non-indigenous species, notably in risk areas (in relation to the main vectors and pathways of spreading of such species).

_14:
Trends in abundance, temporal occurrence, and spatial distribution of non-indigenous species, particularly invasive, non-indigenous species, notably in risk areas (Common Indicator 6)


name: Bycatch of vulnerable and non-target species (ComInd12)
_0: JRC-HT
_11: Bycatch of vulnerable and non-target species.
_12: {Barcelona convention indicator}
_14: Bycatch of vulnerable and non-target species (Common Indicator 12)
_15: Pressure
_16: Target Groups
_18: Categorical/Labelled
_10:
In the Barcelona Convention, the EO3 (equivalent to MSFD descriptor 3) related common indicators will be further developed and assessed by GFCM.


name: Location and extent of the habitats impacted directly by hydrographic alterations (ComInd15)
_0: JRC-HT
_11: Location and extent of the habitats impacted directly by hydrographic alterations.
_12: {Barcelona convention indicator}
_15: State
_16: Biotope Features
_18: Simple statistics
_10:
The Barcelona Convention Common Indicator 15 addresses EO7(i.e. D7) but also feeds the assessment of EO1 (i.e. D1) on habitat extent.

_14:
Location and extent of the habitats impacted directly by hydrographic alterations (Common Indicator 15)


_0: JRC-HT
_6: % and/or m
_11: Length of coastline subject to physical disturbance due to the influence of man-made structures.
_12: {Barcelona convention indicator}
_15: State
_16: Biotope Features
_18: Simple statistics
name:
Length of coastline subject to physical disturbance due to the influence of man-made structures (ComInd16)

_10:
The Barcelona Convention Common Indicator 16 addressing EO8 (on Coastal Ecosystems and Landscape, with no equivalente descriptor in the MSFD) is also feeding the assessment of EO1 (i.e. D1) on habitat extent.

_14:
Length of coastline subject to physical disturbance due to the influence of man-made structures (Common Indicator 16)


name: Chlorophyll-a concentration in water column (ComInd14)
_0: JRC-HT
_12: {Barcelona convention indicator}
_14: Chlorophyll-a concentration in water column (Common Indicator 14)
_15: State
_16: Production
_10:
In addition Barcelona Convention Contracting Parties, where appropriate, may continue using the existing different eutrophication assessment methods such as TRIX, Eutrophication scale, EI, HEAT, etc. at sub-regional or national levels for assessing eutrophication trends.

_11:
Chlorophyll-a concentration in water column.
It is recommended that the Contracting Parties rely on the classification scheme on chl-a concentration (μg/l) developed by MEDGIG as an assessment method that is easily applicable by all Mediterranean countries, based on the indicative thresholds and reference values adopted therein (see Source: EU Commission Decision 2013/480/EC).


name: MFCI - Marine Fish Community Index
_0: JRC-HR
_6: EQR - unitless value between 0 and 1
_14: Marine Fish Community Index (MFCI)
_15: State
_16: Community Structure
_18: Simple statistics
_5:
Total number of species;
Number of rare or uncommon species/total number of species;
Pelagic/demersal ratio (in number of species) (for intermediate and deep soft-bottoms);
Total Abundance (ln(n + 1)) (or simply Total Abundance for rocky subtidal);
Number of species that make up 90% of abundance excluding gregarious species (or simply Number of species that make up 90% of abundance for rocky subtidal);
Proportion of resident species (only for rocky subtidal);
Commercial/non-commercial ratio (in proportion of species) only for rocky subtidal);
Proportion of low and very-low resilience species (except for rocky subtidal);
Proportion of benthic-associated species (only for shallow soft-bottoms);
Proportion of individuals over the maturity size (except for rocky subtidal);
ABC curves (except for rocky subtidal);
Proportion of spawning species;
Proportion of cryptic, Symphodus sp. and Labrus sp. species (only for rocky subtidal);
Number of species with juveniles present (or Proportion of juveniles);
Proportion of invertivore species;
Proportion of piscivore and macrocarnivore species;
Proportion of zooplanktivore species (only for shallow and intermediate soft-bottoms);
Proportion of omnivore species (only for rocky subtidal);

_10:
It can be useful in the context of the Marine Strategy Framework Directive as well as in other contexts of conservation and sustainable management of the
marine environment.

_11:
The MFCI is a multimetric index that incorporates both functional and structural community information. The metrics composing the index vary in function of the habitat assessed (based on typical community): rocky subtidal; shallow, intermediate and deep soft-bottoms. The several metrics composing the index encompass general attributes such as diversity and composition, abundance, nursery function and trophic integrity. The ecological assessment given by the MFCI is based on a scoring system (with five possible score values per metric), whose reference conditions are habitat adjusted. See Source for further details.


name: Oceanic fronts
_0: JRC-HT
_4: Earth Observation (EO) data or modelling data.
_9: See Source Miller & Christodoulou, 2014.
_14: Oceanic fronts
_15: State
_16: Biotope Features
_18: Modelling
_5:
Use of thermal and colour fronts using Earth Observation (EO) data to develop frequent front maps. Front locations are  composited to calculate the mean frontal gradient (Fmean), the probability of detecting a front (Pfront), and the evidence for a feature in proximity (Fprox). These weighting factors a recombined as the composite front map (Fcomp)to provide optimal visualisation of all oceanic features observed during a given period. The threshold used to indicate a ‘strong’ front was Fcomp >= 0.015.These quantities are then used to generate seasonal maps of frequent fronts.

_11:
Many pelagic biodiversity hotspots are related to fronts. Remote sensing can provide valuable inforamtion in regions with insufficient species distribution data, since Oceanic Fronts may be used as a proxy for pelagic biodiversity. It can for example assist site selection for offshore engineering minimising impacts on marine animals (e.g.facilitating the deployment of offshore renewable energy devices), or can be used for supporting in the designation of Marine Protected Areas (MPAs).


name: Glophymed - Global phytoplankton Mediterranean
_0: JRC-HT
_6: EQR - unitless value between 0 and 1
_14: Glophymed - Global phytoplankton Mediterranean
_15: State
_16: Target Groups
_18: Simple statistics
_5:
The Biomass metric requires data on 90th percentile of Chl a (for a five-year period), both in the water body and in a reference site.
The Composition metric requires data on: Total Eukariotic cells, Cyanobacteria, Picocyanobacteria,Prymnesiophyceae, Diatom, Cryptophyceae.
The Bloom metric requires cell-density data to calculate bloom intensity and bloom frequency parameters.

_11:
The Glophymed - Global phytoplankton Mediterranean index includes the metrics: biomass, composition, and intensity and frequency of blooms. See Source for index calculation.


name: TL - Trophic Level-based indicators
_0: JRC-HT
_14: TL - Trophic Level-based indicators
_16: Foodweb
_4:
Landings data, surveys data or modelling data can be used depending on the objectives, each with advantages and constraints. See Source for details.

_5:
-TL (trophic level) of species i; 
-Total landings (for TL of the landings) or Total biomass (for TL of surveyed or modelled ecosystems);
-Landings or Biomass of species i. 

_11:
TL-based indicators (TLIND) are calculated as the mean trophic position of all species, weighted by the relative biomass of each species in the landings, in
the surveys or in the modelled community.
TL-based indicators often used to quantify fishing effects on the trophic
structure of food webs.


name: ESCA - Ecological Status of Coralligenous Assemblages
_0: JRC-HT
_5: presence/absence and abundance of sensitive taxa/groups assemblage taxonomic composition
_6: EQR - unitless value between 0 and 1
_14: ESCA - Ecological Status of Coralligenous Assemblages
_15: State
_16: Community Structure
_18: Simple statistics
_11:
Assemblage descriptors selected as metrics of the ESCA index were: (a) presence/absence and abundance of sensitive taxa/groups (expressed as sensitivity level of assemblages, SL), (b) diversity of assemblages (expressed as α-diversity) and (c) heterogeneity of assemblages (expressed as β-diversity). The three metrics were combined to give a final value for the multimetric ecological index, Ecological Quality Ratio (EQR), calculated as the ratio between the measured values and the value obtained in the reference condition. 


name: COARSE - COralligenous Assessment by ReefScape Estimate index
_0: JRC-HT
_6: Overall quality score (QO) [0-3]
_14: COralligenous Assessment by ReefScape Estimate index (COARSE)
_15: State
_16: Biotope Features
_18: Simple statistics
_4:
Uses a direct visual method - SCUBA diving observations and measurements, to gather data useful to evaluate the state of coralligenous reefs as an indicator of sea-floor integrity following the Rapid Visual Assessment (RVA) approach proposed by Gatti et al. (2012).

_5:
Biotic cover (%), conspicuous species richness, three-dimensional structure of coralligenous reefs (e.g. thickness and consistency of calcareous layer, erect calcified organisms, maximum height), necrosis status, traits (e.g. species sensitivity). See details in Sources: Gatti et al. 2015.

_11:
The COARSE index uses a seascape approach to provide information about the structure and the composition of coralligenous reefs in order to assess the sea-floor integrity.


name: CAI - Coralligenous Assemblage Index
_0: JRC-HT
_6: EQR - unitless value between 0 and 1
_11: The CAI is a coralligenous habitat classification mutlimetric index.
_14: Coralligenous Assemblage Index (CAI)
_15: State
_16: Biotope Features
_18: Simple statistics
_4:
Photographic quadrats along a transect, by CCUBA (Closed Circuit Underwater
Breathing Apparatus) divers.

_5:
Bryozoa percent cover, sludge percent cover, builder species percent cover;
(and depth as supporting parameter, not entering the index).

_8:
Cheap-cost sampling method with the advantage of providing objective and repeatable estimations thanks to a fast and non-destructive underwater work.


