Data from: Complex patch geometries maximize species richness at the expense of forest specialists

# Complex patch geometries maximize species richness at the expense of forest specialists This README file was generated on 2024-01-31 by Stephanie Clements. GENERAL INFORMATION 1\. Title of Dataset: Complex patch geometries maximize species richness at the expense of forest specialists. 2\. Author Information A. Corresponding Author Name: Stephanie L. Clements Institution: University of Miami Address: CORAL GABLES, FL, USA Email: B. Additional Author Name: Dunia Villalobos Alpízar Institution: N/A Address: Copal, Agua Buena, San Vito de Coto Brus, Puntarenas, Costa Rica Email: C. Principal Investigator Name: Christopher A. Searcy Institution: University of Miami Address: CORAL GABLES, FL, USA Email: 3\. Date of data collection (single date, range, approximate date): March 2019, June/July 2019, March 2020 4\. Geographic location of data collection: Las Cruces Biological Station and surrounding landscape, Costa Rica 5\. Information about funding sources that supported the collection of the data: Organization for Tropical Studies Pilot Research Award, Organization for Tropical Studies Thesis Grant, Sigma Xi Grant-in-Aid-of-Research Award, University of Miami Institute for Advanced Study of the Americas (UMIA) Pilot Research Grant, UMIA Research Fellowship, University of Miami Department of Biology Awards including the Aldridge Graduate Fellowship in Tropical Biology, Kushlan Fund, and Savage Fund. SHARING/ACCESS INFORMATION 1\. Licenses/restrictions placed on the data: CC0 2\. Links to publications that cite or use the data: Clements, S. L., Villalobos Alpizar, D., Searcy, C.A. (2024). Complex patch geometries maximize species richness at the expense of forest specialists. Biotropica. 3\. Links to other publicly accessible locations of the data: None 4\. Links/relationships to ancillary data sets: None 5\. Was data derived from another source? No A. If yes, list source(s): NA 6\. Recommended citation for this dataset: Clements, S. L., Villalobos Alpizar, D., Searcy, C.A. (2024). Complex patch geometries maximize species richness at the expense of forest specialists. Dryad Digital Repository. DATA & FILE OVERVIEW 1\. File List: A) DataSets_BITR23188_Clementsetal2024.xls a. Sheet 1 – FinalData_FullMatrix b. Sheet 2 – SppMatrixForCommunityAnalyses c. Sheet 3 - Metadata 2\. Relationship between files, if important: Sheet 1 is full dataset. Sheet 2 is modified dataset for community analysis only. Sheet 3 explains the 2 datasets. 3\. Additional related data collected that was not included in the current data package: None 4\. Are there multiple versions of the dataset? No A. If yes, name of file(s) that was updated: NA i. Why was the file updated? NA ii. When was the file updated? NA \######################################################################### DATA-SPECIFIC INFORMATION FOR: FinalData_FullMatrix (Sheet 1) 1\. Number of columns: 108 2\. Number of cases/rows: 54 3\. Column List: * Site: Site Number where data was collected (C = Connected, D = Disconnected, P = Patch, M = Matrix, X = Corridor, Reference = Reference Forest) * Species: Columns B – AZ are species names found. * Abundance: Total # of individuals at the site * Ln(Abundance): Abundance after a natural log transformation for normality. Note that any column that says “Ln” was natural log transformed. * Richness: The # of species found at the site * RichnessWUnIDs: This species matrix does not include individuals that were not identified to species, but the “Richness with Un-ID’s” column reflects the richness at a site when taking those species into account. For example, if an unidentified lizard was seen at a site, but there were no other lizards recorded there, it would count as one additional richness. * GeneralistAbundance: The abundance of species we defined as “generalists” (if > 20 % of identified individuals were found in the matrix) * Specialist Abundance: The abundance of species we defined as “specialists” (if > 80 % of identified individuals were found in the forests) \* Generalist Richness: The # of species we defined as “generalists” within that site. \* Specialist Richness: The # of species we defined as “specialists” within that site. * EstSppRich: Estimated species richness (using second-order jackknife calculation) * %SppObs: The richness divided by the estimated richness * ArcSine(%SppObs): The %SppObs column after using an ArcSine transformation. Any columns with “ArcSine” in front indicate that the variable was transformed using an ArcSine transformation \* HabitatType: The Habitat Type of the surveyed site (can be patch, matrix, corridor, or reference forest) \* Location: This is the site number # without the habitat type (for example, C1 means connected 1, but that location has 3 habitat types, patch, corridor, and matrix) \* Connected: Only for Patches – can be connected or disconnected. N/A for corridors, reference forests, and matrices \* Latitude: Latitude of the site. More precise locality data are available upon request. Coordinate accuracy was decreased to protect threatened or endangered species in the dataset. \* Longitude: Longitude of the site. More precise locality data are available upon request. Coordinate accuracy was decreased to protect threatened or endangered species in the dataset. \* Area (ha): The area of the site in hectares (only applicable for patches, corridors, and reference forests as the matrix is the space around the patch). The reference forests have 2 sites in each forest, so the second site does not have a separate area. \* Perimeter (meters): The perimeter of the site in meters (only applicable for patches, corridors, and reference forests as the matrix is the space around the patch). The reference forests have 2 sites in each forest, so the second site in a given forest does not have a separate perimeter. \* Shape Index: Perimeter divided by 2 multiplied by the square root of pi multiplied by the area. This is meant to account for the correlation between perimeter and area as discussed in Moser et al. 2002. A higher shape index means a more complex shape with a greater edge:area ratio. This is again only applicable for patches, corridors, and reference forests as the matrix is the space around the patch. \* DistancetoReference(m): The distance from the site to the refence forest in meters as measured in ArcMap (we only measured this for the patches and matrix sites). \* Reference Closest to: Which reference forest (1 or 2) the patch is closer to (patches only) \* Road (No/Gravel/Dirt/Paved): Whether a road lies between the patch and the nearest reference forest, and if so, what type of road it is (patches only). \* Reference Connected To: For Connected Patches only, which reference forest are they connected to via a corridor. \* Water Body At Transect: Whether or not there was a water body present at the survey site (Y = Yes, N = No) \* ElevationAtTransect: The elevation at the transect location (in meters) \* SlopeAtTransect: The slope at the transect location \* CanopyCover(mean): The mean Canopy Cover in a patch, corridor, or reference forest (as a %) \* CanopyCover(mean)Decimal: The mean canopy cover converted to decimal in order to do the ArcSine Transformation in the following column (Any columns with “decimal” indicate that the variable was transformed to decimal) * CanopyCoverMeanAroundPatch80mBuffer: The mean canopy cover (%) in an 80 meter buffer around the patch \* CanopyCoverMeanAroundPatch100mBuffer: The mean canopy cover (%) in a 100 meter buffer around the patch \* CanopyCoverMeanAroundCorridor80mBuffer: The mean canopy cover (%) in an 80 meter buffer around the corridor (for the patch sites, it’s the mean canopy over in an 80 m buffer around the corridor that is connected to that patch). This is N/A for reference forests and matrix sites. \* CorridorLength (km by hand): The length of the corridor traced by hand in Google Earth (in kilometers) (again, for the patch sites, it’s for the corridor that is connected to that patch) \* CorridorWidthByHand(meters) at narrowest point: The width of the corridor (in meters) measured at the narrowest point in Google Earth (again, for the patch sites, it’s for the corridor that is connected to that patch) \* ForestAge: The forest age at the site according to Zahawi et al. 2015, categorized as either old growth (> 72 years) or new growth (< 49 years). Not applicable for matrix sites. \* Szn1Rich: Richness from the first season of surveys (to compare richness across survey seasons). Richness and Abundance are calculated for each of the 3 seasons in the next few columns. \* CanopyAtTransectPt: The canopy cover (%) at the transect point for the matrix sites (because for patches, corridors, and reference forests, the canopy cover is measured for the full area of the patch, corridor, or reference forest). \* Canopy80mBufferAroundTransectPt: The canopy cover (%) in an 80 m buffer around the transect point 4\. Missing data codes: N/A 5\. Specialized formats or other abbreviations used: None \######################################################################### DATA-SPECIFIC INFORMATION FOR: SppMatrixForCommunityAnalyses (Sheet 2) 1\. Number of columns: 36 2\. Number of cases/rows: 54 3\. Column List: * Name: Site Number where data collected (C = Connected, D = Disconnected, P = Patch, M = Matrix, X = Corridor, Reference = Reference Forest) * Species: The rest of the columns are species names. While creating the community matrix for the community analyses, we combined certain species as deemed appropriate, or dropped species that were found at only one location. The decisions we made while creating the matrix for community analyses are available as supplemental materials with the published manuscript. 4\. Missing data codes: None 5\. Specialized formats or other abbreviations used: None