This Box_occupancy_readme.txt file was generated on 2022-01-29 by Sandra Pschonny



GENERAL INFORMATION

1. Title of Dataset: Data from: What makes a good bat box? How box occupancy depends on box characteristics and landscape-level variables

2. Author Information
	A. Corresponding Investigator
		Name: Sandra Pschonny
		Institution: Terrestrial Ecology Research Group, Department of Ecology and Ecosystem Management, School of Life Sciences Weihenstephan, Technische Universität München
		Email: sandra.pschonny@tum.de

	B. Co-investigator 1
		Name: Jan Leidinger
		Institution: Terrestrial Ecology Research Group, Department of Ecology and Ecosystem Management, School of Life Sciences Weihenstephan, Technische Universität München  
		Email: jan.leidinger@tum.de

	C. Co-investigator 2
		Name: Wolfgang W. Weisser
		Institution: Terrestrial Ecology Research Group, Department of Ecology and Ecosystem Management, School of Life Sciences Weihenstephan, Technische Universität München 
		Email: wolfgang.weisser@tum.de 

	D. Co-investigator 3
		Name: Rudolf Leitl
		Email: info@rudinatur.de 

3. Date of data collection: June - October 2017

4. Geographic location of data collection: forests in Upper Palatinate district, Northern Bavaria, Germany 

5. Information about funding sources that supported the collection of the data: 
Box checks in 2017 were financed by the following institutions: 
Bayerische Staatsforsten – BaySF (“Bavarian state forestry”), 
Bayerische Forstverwaltung – LWF (“Bavarian State Institute of Forestry”) 
and Koordinationsstelle für Fledermausschutz Nordbayern (“Coordination Office of Bat Protection of Northern Bavaria”), an advisory centre on behalf of the Bayerisches Landesamt für Umwelt - LfU (“Bavarian State Office of Environment”). 



SHARING/ACCESS INFORMATION

1. Licenses/restrictions placed on the data: GPS points with blur of 100m to protect bats from disturbance; data of evaluation was more precise

2. Links to publications that cite or use the data: https://www.bestellen.bayern.de/application/applstarter?APPL=eshop&DIR=eshop&ACTIONxSETVAL(artdtl.htm,APGxNODENR:34,AARTxNR:lfu_nat_00380,AARTxNODENR:357675,USERxBODYURL:artdtl.htm,KATALOG:StMUG,AKATxNAME:StMUG,ALLE:x)=X

3. Forest cover was extracted from CORINE Land Cover data at a 10 ha resolution: GeoBasis-DE/BKG. 2016. CORINE Landcover. Bundesamt für Kartographie und Geodäsie.

4. Recommended citation for this dataset: 
Pschonny, S.; Leidinger, J., Leitl, R.; Weisser, W. (2022). Data from: What makes a good bat box? How box occupancy depends on box characteristics and landscape-level variables. Ecological Solutions and Evidence.



DATA & FILE OVERVIEW

1. File List: 

File 1a Name: 1_box occupancy.txt
File 1a Description: Data of overall box occupancy of bats ("FM" 0/1) in relation to 13 different box variables

File 1b Name: 1_What makes a good bat box_box occupancy.txt
File 1b Description: R-script for the probability of box occupancy by bats including graphs

File 2a Name: 2_only adult bats.txt
File 2a Description: Data of box occupancy of only adult bats ("FM" 0/1) in relation to 13 different box variables

File 2b Name: 2_What makes a good bat box_only adult bats.txt
File 2b Description: R-script for the probability of box occupancy by only adult bats including graphs

File 3a Name: 3_nursery_groups.txt
File 3a Description: Data of box occupancy of nursery groups ("FM" 0/1) in relation to 13 different box variables

File 3b Name: 3_What makes a good bat box_nursery_groups.txt
File 3b Description: R-script for the probability of box occupancy by nursery groups including graphs

File 4a Name: 4_P_pip.txt
File 4a Description: Data of box occupancy of Pipistrellus pipistrellus ("FM" 0/1) in relation to 13 different box variables

File 4b Name: 4_What makes a good bat box_P_pip.txt
File 4b Description: R-script for the probability of box occupancy by Pipistrellus pipistrellus including graphs

File 5a Name: 5_M_nat.txt
File 5a Description: Data of box occupancy of Myotis nattereri ("FM" 0/1) in relation to 13 different box variables

File 5b Name: 5_What makes a good bat box_M_nat.txt
File 5b Description: R-script for the probability of box occupancy by Myotis nattereri including graphs


2. Relationship between files: File 2 - 5 are subsets of File 1
	File 2: 2_only adult bats.txt: We excluded boxes with only indirect evidence of bat occupancy and boxes with nursery groups.
	File 3: 3_nursery_groups.txt: We excluded boxes with only indirect evidence of bat occupancy and boxes with only adult bats.
	File 4: 4_P_pip.txt: We only considered areas where P. pipistrellus and M. nattereri occurred together. Boxes with indirect evidence of bat occupancy or boxes with unidentified individuals were excluded. Multiple species boxes that were occupied by species other than P. pipistrellus were removed from the dataset.
	File 5: 5_M_nat.txt: We only considered areas where P. pipistrellus and M. nattereri occurred together. Boxes with indirect evidence of bat occupancy or boxes with unidentified individuals were excluded. Multiple species boxes that were occupied by species other than M. nattereri were removed from the dataset.



METHODOLOGICAL INFORMATION

1. Description of methods used for collection/generation of data: 
During 2017, 13634 boxes were surveyed by volunteers that acted independently of one another. 
There was no systematic sampling design, volunteers were asked to check boxes at least once between June and October, on a cold day to avoid bat fly out and locally asynchronous to avoid double counting.
For every box, northing (HW), easting (RW), elevation (hNN), calendar week of the check (altKW), box type (Kastentyp), mounting height (h) and age (Alter) was recorded. A box was considered occupied when a bat was present (FM) or when indirect evidence of bat box use was obtained. Also, other species groups (fb) were recorded.
Landscape-level variables (Wald1, x50, Max_Alter1, dist_mind50, near_FM) included the land cover around the box, and the spatial placement of boxes and were calculated with ArcGIS version 10.4.1.

2. Methods for processing the data: 
The data of 13634 boxes included 26 box types of varying ages and mounting heights. Boxes older than 16 years were dominated by one box type, mostly installed at a height of 1–1.5m and up to 100m to its nearest neighbour. Boxes installed later were predominantly placed at a height of 3–4m, in groups of 4–8 boxes. In addition, boxes within the same area often were of the same box type and age. 
Due to this unbalanced data structure, we decided to focus on three woodcrete box types: Gable box, Colony box and Flat box, where each had more than 1000 replicates in areas where they occurred together resulting in our dataset "1_box occupancy".

3. Instrument- or software-specific information needed to interpret the data: 
RStudio, version 4.0.3: R Core Team. 2020. R: A language and environment for statistical computing. 
used packeges:
- DHARMa: Hartig, F. 2019. DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. R package.
- rsq: Zhang, D. 2018. rsq: R-Squared and Related Measures. https://CRAN.R-project.org/package=rsq.
- effects: Fox, J. 2003. Effect Displays in R for Generalised Linear Models. Journal of Statistical Software 8(15):1-27. 
- multcomp: Torsten, H. F., Bretz; Peter, Westfall 2008. Simultaneous Inference in General Parametric Models. Biometrical Journal 50:347-363. 
- emmeans: Lenth, R. 2018. emmeans: Estimated Marginal Means, aka Least-Squares Means. https://CRAN.R-project.org/package=emmeans.
- car: Fox, J & Weisberg, S. 2019. An {R} Companion to Applied Regression, Third Edition. Thousand Oaks CA: Sage. https://socialsciences.mcmaster.ca/jfox/Books/Companion/

7. People involved with sample collection, processing, analysis and/or submission: 
Data acquisition and preparation was supported by members of BaySF, LWF, LfU, NATURA 2000-Team Upper Palatinate (Ministry of Food, Agriculture and Forestry Ambeg) and NATURA 2000-Team Lower Bavaria (Ministry of Food, Agriculture and Forestry Landau) and the Coordination Office of Bat Protection of Northern Bavaria. 



DATA-SPECIFIC INFORMATION FOR: 1_box occupancy.txt

1. Number of variables: 14

2. Number of cases/rows: 5222

3. Variable List: 
HW: northing of bat box (continuous)
RW: easting of bat box (continuous)
FM: bat evidence (1/0)
hNN: elevation (continuous)
altKW: calendar week (continuous)
fb: occupancy by other species groups (1/0)
Wald1: percentage of forest cover (continuous)
X50: box group size (continuous)
Max_Alter1: maximum community age of boxes (continuous)
dist_mind50: box isolation (continuous)
near_FM: occupancy of the nearest neighbouring box (1/0)
Kastentyp: box type (three level factor variable)
Alter: box age (continuous)
h: box mounting height (continuous)

4. Missing data codes: 
None



DATA-SPECIFIC INFORMATION FOR: 2_only adult bats.txt

1. Number of variables: 14

2. Number of cases/rows: 3884

3. Variable List: 
HW: northing of bat box (continuous)
RW: easting of bat box (continuous)
FM: bat evidence for only adult bats (1/0)
hNN: elevation (continuous)
altKW: calendar week (continuous)
fb: occupancy by other species groups (1/0)
Wald1: percentage of forest cover (continuous)
X50: box group size (continuous)
Max_Alter1: maximum community age of boxes (continuous)
dist_mind50: box isolation (continuous)
near_FM: occupancy of the nearest neighbouring box (1/0)
Kastentyp: box type (three level factor variable)
Alter: box age (continuous)
h: box mounting height (continuous)

4. Missing data codes: 
None



DATA-SPECIFIC INFORMATION FOR: 3_nursery_groups.txt

1. Number of variables: 14

2. Number of cases/rows: 3361

3. Variable List: 
HW: northing of bat box (continuous)
RW: easting of bat box (continuous)
FM: bat evidence for nursery groups (1/0)
hNN: elevation (continuous)
altKW: calendar week (continuous)
fb: occupancy by other species groups (1/0)
Wald1: percentage of forest cover (continuous)
X50: box group size (continuous)
Max_Alter1: maximum community age of boxes (continuous)
dist_mind50: box isolation (continuous)
near_FM: occupancy of the nearest neighbouring box (1/0)
Kastentyp: box type (three level factor variable)
Alter: box age (continuous)
h: box mounting height (continuous)

4. Missing data codes: 
None



DATA-SPECIFIC INFORMATION FOR: 4_P_pip.txt

1. Number of variables: 14

2. Number of cases/rows: 2049

3. Variable List: 
HW: northing of bat box (continuous)
RW: easting of bat box (continuous)
FM: evidence for Pipistrellus pipistrellus (1/0)
hNN: elevation (continuous)
altKW: calendar week (continuous)
fb: occupancy by other species groups (1/0)
Wald1: percentage of forest cover (continuous)
X50: box group size (continuous)
Max_Alter1: maximum community age of boxes (continuous)
dist_mind50: box isolation (continuous)
near_FM: occupancy of the nearest neighbouring box (1/0)
Kastentyp: box type (three level factor variable)
Alter: box age (continuous)
h: box mounting height (continuous)

4. Missing data codes: 
None



DATA-SPECIFIC INFORMATION FOR: 5_M_nat.txt

1. Number of variables: 14

2. Number of cases/rows: 1910

3. Variable List: 
HW: northing of bat box (continuous)
RW: easting of bat box (continuous)
FM: evidence for Myotis nattereri (1/0)
hNN: elevation (continuous)
altKW: calendar week (continuous)
fb: occupancy by other species groups (1/0)
Wald1: percentage of forest cover (continuous)
X50: box group size (continuous)
Max_Alter1: maximum community age of boxes (continuous)
dist_mind50: box isolation (continuous)
near_FM: occupancy of the nearest neighbouring box (1/0)
Kastentyp: box type (three level factor variable)
Alter: box age (continuous)
h: box mounting height (continuous)

4. Missing data codes: 
None