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# ATLAS Deliverable 4.5: Integrated management considering connectivity patterns

Arnaud-Haond, S; Fox, A; Cunha, M; Carlsson, J; Roterman, C

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<identifier identifierType="DOI">10.5281/zenodo.4658929</identifier>
<creators>
<creator>
<creatorName>Arnaud-Haond, S</creatorName>
<givenName>S</givenName>
<familyName>Arnaud-Haond</familyName>
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<creator>
<creatorName>Fox, A</creatorName>
<givenName>A</givenName>
<familyName>Fox</familyName>
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<creator>
<creatorName>Cunha, M</creatorName>
<givenName>M</givenName>
<familyName>Cunha</familyName>
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<creator>
<creatorName>Carlsson, J</creatorName>
<givenName>J</givenName>
<familyName>Carlsson</familyName>
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<creator>
<creatorName>Roterman, C</creatorName>
<givenName>C</givenName>
<familyName>Roterman</familyName>
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<titles>
<title>ATLAS Deliverable 4.5: Integrated management considering connectivity patterns</title>
</titles>
<publisher>Zenodo</publisher>
<publicationYear>2021</publicationYear>
<dates>
<date dateType="Issued">2021-04-01</date>
</dates>
<resourceType resourceTypeGeneral="Other"/>
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<relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/atlas</relatedIdentifier>
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<rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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<descriptions>
<description descriptionType="Abstract">&lt;p&gt;Connectivity was assessed during ATLAS for a diversity of organisms, from the corals that structure Vulnerable Marine Ecosystems (VMEs) to economically important fishery species using two main pathways. Predicted connectivity patterns were obtained through simulated larval Lagrangian particle modelling, based on oceanographic data gained in WP1 and reproductive knowledge produced in WP4. Realised connectivity was inferred using population genetics on sets of samples gathered before and during ATLAS, focusing on a subset of the target species initially listed, for which enough samples could be gathered to perform comprehensive population genetics analysis.&lt;br&gt;
Lagrangian modelling of larval dispersal within ATLAS unravelled the effect of long-term ocean variability (Atlantic Meridional Overturning Circulation - AMOC, subpolar gyre strength - SPG and North Atlantic Oscillation - NAO) and larval behaviour on particle transport pathways and population connectivity (Fox et al., 2016), the contribution of man-made structures to connectivity (Henry et al., 2018) and the application of these results to marine planning and the development of ecologically coherent marine protected area networks. This work has underlined the crucial need for data on reproductive and larval biology to inform these predictions (Fox et al., 2016). This proved to be even more important for deep-sea species due to the vast extent of the water column through which larvae can disperse. Very different outcomes can be expected depending not only on the timing of reproduction or the length of pelagic larval duration (PLD), but also on the behaviour of larvae remaining on the seafloor or migrating more or less along the water column. The relationship between PLD and &amp;ldquo;realised connectivity&amp;rdquo; as estimated through population genetics is far from easily predictable, despite some relationship existing (Riginos et al., 2011). This is likely to be worse in the deep sea as exemplified by recent models where extensive PLD resulted in extreme variance of predicted connectivity (Ross et al., 2019), possibly due to the importance of the third dimension (depth) in the space potentially explored by larvae. Nevertheless, the new method developed in ATLAS (Fox et al., 2019) allows a generic approach to optimise multi objectives in the design of MPAs. This showed that for highly dispersive behaviours, all the Northern Atlantic could in theory be connected with a favoured anti-clockwise dispersal along the slopes. Results also underlined that seamount populations may act as crucial stepping stones (hubs) in the broad scale connectivity, placing them in the priority list to maintain connectivity for a broad range of species. This important role of seamounts and offshore banks was also demonstrated through Lagrangian modelling based on the reef coral Lophelia pertusa&amp;rsquo;s reproductive and larval biology (Fox et al., 2016).&amp;nbsp;As for inferences of &amp;ldquo;realised&amp;rdquo; connectivity, population genetics and genomics allow identification of distinct management units (MUs; Palsb&amp;oslash;ll et al., 2007), i.e. populations of conspecific individuals among which the degree of connectivity is sufficiently low so that each population should be monitored and managed separately, for example along the Northeast Atlantic coasts and the Mediterranean where the majority of samples analysed within ATLAS framework could be gathered. These samples laid also the foundations for a basin-scale analysis in the coming years in collaboration with partners from the northwest Atlantic under the leadership of the EU-funded project iAtlantic (see below). Importantly, genetically differentiated populations are not only demographically independent but may also shelter singular genetic diversity, one of the three components of biodiversity in need for conservation but too long neglected by management and conservation plans (Laikre et al., 2010). This was true for VMEs species such as Madrepora oculata, but also the commensal polychaete Eunice norvegica where at least one cryptic species was identified in the Atlantic. As for Lophelia pertusa, homogeneity was found in the Bay of Biscay despite some hints of differentiation of SE Rockall bank (Boavida et al., 2019b). The occurrence of those distinct MUs, or even distinct evolutionary significant units (ESUs; Ryder, 1986) in the case of Eunice sp., is essential for conservation, for each of them should be treated as distinct diversity entities, with no demographic (Brown Kodric-Brown, 1977) interdependence. This also means in case one MU would collapse, no evolutionary (Orr Unckless, 2014; Tomasini Peischl) rescue effect can be expected from the others, which needs to be accounted for in monitoring and management plans. Fish species studied in ATLAS were chosen among the target listed at the origin of the project for both their economic interest and, likewise invertebrates, the availability of samples to allow assessing connectivity over broad scales with a sufficient number of samples. Distinct MUs were also detected in the boarfish Capros aper, the horse mackerel Trachurus trachurus, and the Norway lobster Nephrops norvegicus. These MUs are demographically independent populations, thus multiple stocks expected to respond independently to harvesting and management. While the MUs in the boarfish largely agreed with the areas defined by the International Council for the Exploration of the Sea (ICES) (one exception though being noticed in the southern border), uncertainties remain for the horse mackerel and clear mismatches were revealed between MUs defined with genetic data and management areas for the Norway lobster, calling for a revision of management plans.&lt;br&gt;
In this report, we also develop detailed explanations of the difference between genetic and demographic independency that are essential to understand the power and limitation of population genomics, but also to account for connectivity data in management plans. We believe those explanations are essential to share with managers and stakeholders, as well as scientific colleagues&amp;nbsp;expert in fields other than population genetics who are interested in applying population genetics to management and conservation.&lt;br&gt;
On the basis of the results obtained in ATLAS, guidelines could be provided for future management plans, whether through the identification of mismatch between fisheries management units and the genetic differentiation of stocks, or the identification of genetically specific and disconnected populations for benthic organisms characterising VMEs. In fact, nearly every species showed a singular spatial delineation of MUs, resulting in a mosaic of patterns illustrating the challenge of multispecies purpose MPAs. One result is to account for the most limited connectivity potential in management plans, to ensure the maintenance of exchanges. In fact accounting for very limited dispersal to include connectivity in spatial planning showed the need to design large areas and to favour contiguous prioritisation units for conservation (Combes et al., in prep.).&lt;br&gt;
Remaining uncertainties in areas where no genetic differentiation was detected is also important to consider and is different among taxa. Compared to those species for which clear MUs (or even ESUs) could be recognised, there were species and areas where no genetic differentiation could be detected (such as Lophelia pertusa in the Bay of Biscay), or no signature of bottleneck could be encountered (as was the case for most populations studied in ATLAS), despite extensive referenced exploitation or habitat destruction. In such cases it is very difficult to disentangle the real absence of barrier to gene flow and/or bottleneck from the insufficient power of the molecular method used. As demonstrated recently through simulations (Bailleul et al., 2018), there is a time lag between the moment barriers to connectivity or bottleneck occur and their signature can be detected through population genetics. This was designed as the &amp;ldquo;grey zone effect&amp;rdquo; and its duration depends on the statistical power delivered by the set of genetic markers used, but can encompass several tens to a thousand years. New generation high density genome scan analysis can help increasing the statistical power to detect such events. However, these methods are very demanding in terms of DNA quality and not all collections examined in ATLAS, particularly the older ones, gave such high quality DNA. Much work was thus dedicated during ATLAS to resolving DNA extraction protocols so that important existing deep-sea sample collections could be used. First results obtained on the two reef framework-forming corals and their associated commensal polychaete (Eunice spp., for we now know it encompasses at least two species), as well as the coral Dendrophyllia cornigera. For the last two species some samples liberated high quality DNA to build libraries that are being produced, and will allow to inferring our ability to detect hitherto ignored disruption of connectivity or bottlenecks. These data will be completed, analysed and interpreted beyond ATLAS, in the framework of iAtlantic using lessons learnt from genomic issues met and circumvented during ATLAS.&amp;nbsp;Due to issues related to DNA quality, RADSeq analysis on a dozen species for which just a handful of specimens met DNA quality standards allows the provision of genomic resources to be used with protocols requiring a lower DNA quality standard. These new resources will allow optimisation of the use of old but precious specimens and DNA collections of deep-sea organisms. Along with the basin scale analysis forecast for the two main reef framework-forming corals taxa in collaboration with US partners, those are important perspectives of development beyond ATLAS, that are planned to emerge during the iAtlantic project.&amp;nbsp;&lt;/p&gt;</description>
</descriptions>
<fundingReferences>
<fundingReference>
<funderName>European Commission</funderName>
<funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
<awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/678760/">678760</awardNumber>
<awardTitle>A Trans-AtLantic Assessment and deep-water ecosystem-based Spatial management plan for Europe</awardTitle>
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