DOI: 10.5061/dryad.gb5mkkwsk
title: Mapping multiscale breeding bird species distributions across the United States and evaluating their conservation applications

description: Species distribution models are vital to management decisions that require
 understanding habitat use patterns, particularly for species of
 conservation concern. However, the production of distribution maps for
 individual species is often hampered by data scarcity, and existing
 species maps are rarely spatially validated due to limited occurrence
 data. Furthermore, community-level maps based on stacked species
 distribution models lack important community assemblage information (e.g.,
 competitive exclusion) relevant to conservation. Thus, multispecies,
 guild, or community models are often used in conservation practice
 instead. To address these limitations, we aimed to generate fine-scale,
 spatially-continuous, nationwide maps for species represented in the North
 American Breeding Bird Survey (BBS) between 1992-2019. We generated
 ensemble models for each species at three spatial resolutions – 0.5, 2.5,
 and 5 km – across the conterminous United States. We also compared species
 richness patterns from stacked single-species models with those of 19
 functional guilds developed using the same data to assess the similarity
 between predictions. We successfully modeled 192 bird species at 5-km
 resolution, 160 species at 2.5-km resolution, and 80 species at 0.5-km
 resolution. However, the species we could model represent only 28-56% of
 species found in the conterminous US BBS surveys across resolutions owing
 to data limitations. We found stacked maps and guild maps generally had
 high correlations across resolutions (median = 84%), but spatial agreement
 varied regionally by resolution and was most pronounced between the East
 and West at the 5-km resolution. The spatial differences between our
 stacked maps and guild maps illustrate the importance of spatial
 validation in conservation planning. Overall, our species maps are useful
 for single-species conservation and can support fine-scale decision-making
 across the United States, and can also support community-level
 conservation when used in tandem with guild maps. However, there are still
 data scarcity issues for many species of conservation concern when using
 the BBS for single-species models.
description: # Mapping multiscale breeding bird species distributions across the United
 States and evaluating their conservation applications
 [https://doi.org/10.5061/dryad.gb5mkkwsk](https://doi.org/10.5061/dryad.gb5mkkwsk) Kathleen A. Carroll1\*, Anna M. Pidgeon1, Paul R. Elsen2, Laura S. Farwell3, David Gudex-Cross4, Benjamin Zuckerberg1, Volker C. Radeloff1 1\. Department of Forest and Wildlife Ecology\, University of Wisconsin\-Madison\, 1630 Linden Drive\, Madison WI 53706\, USA\. 2\. Wildlife Conservation Society\, USA 3\. Birds Habitat Joint Venture\, Portland\, OR 97215\, USA\. 4\. RedCastle Resources\, Inc\. Forest Service Contractor\, USA * corresponding author: kcarroll7@wisc.edu ## Description of the data and file structure Maps are labeled by species common names. Naming conventions: cont = continuous ci = confidence interval (upper or lower) mean = mean ensemble model 5km = 5-km resolution/route 2p5km = 2.5-km resolution/10-stop 500m = 0.5-km resolution/1-stop Folders | Folder Name | Description | | ----------- | ----------- | | route.zip | Maps for 192 species at the route level/ 5-km resolution. For each species, there are three .tif files: one each for upper and lower confidence intervals (CI) and mean. Each file is named as follows: \_CommonName\_cont\_mean or ci\_ 5km. For some files, there are also xlmfiles that can be ignored. The \*.aux.xml File is ArcGIS specific. ArcGIS stores information there – e.g. after calculating statistics – so this information is available later and were generated during data mapping. | | tenstop.zip | Maps for 160 species at the route level/ 2.5-km resolution. For each species, there are .tif files for upper and lower confidence intervals (CI) and mean. Each file is named as follows: \_CommonName\_cont\_mean or ci\_ 2p5km. For some files, there are also xlmfiles that can be ignored. The \*.aux.xml File is ArcGIS specific. ArcGIS stores information there – e.g. after calculating statistics – so this information is available later and were generated during data mapping. | | onestop.zip | Maps for 80 species at the route level/ 500-m resolution. For each species, there are .tif for upper and lower confidence intervals (CI) and mean. Each file is named as follows: \_CommonName\_cont\_mean or ci\_ 500m. For some files, there are also xlmfiles that can be ignored. The \*.aux.xml File is ArcGIS specific. ArcGIS stores information there – e.g. after calculating statistics – so this information is available later and were generated during data mapping. | | stackedMaps.zip | Guild-level stacks for all guilds and resolutions. The 20 guilds are detailed in the paper and guild membership is detailed in the guild membership excel file. For each guild there is a mean .tif file for each of the 3 resolutions. The stacked maps were generated for comparison to the guild maps at [https://doi.org/10.5061/dryad.vq83bk3v0](https://doi.org/10.5061/dryad.vq83bk3v0) and should not be used for conservation purposes. For some files, there are also xlmfiles that can be ignored. The \*.aux.xml File is ArcGIS specific. ArcGIS stores information there – e.g. after calculating statistics – so this information is available later and were generated during data mapping. | | ConfidenceIntervals.zip | Guild-level CI stacks for all guilds and resolutions. For each guild there are six .tif files (one at each resolution for upper and lower). For some files, there are also xlmfiles that can be ignored. The \*.aux.xml File is ArcGIS specific. ArcGIS stores information there – e.g. after calculating statistics – so this information is available later and were generated during data mapping. | | BiodiversityPredictors.zip | SILVIS Lab-produced raster files used in the R and bash scripts detailed in the Files Section. The first subfolder level denotes the resolution of the predictors: 500m, 2500m (2.5 km), and 5000m (5 km). Sub-subfolders include many of the predictors used in the the analyses which are detailed in Appendix S1 in the associated publication. Files include cloud (cloud cover index), DHIs (three dynamic habitat indices), EVI (enhanced vegetation index), Housing (from Microsoft footprint), Texture\_CumDHI (nine vegetation texture metrics based on DHIs), Thermal (thermal heterogeneity, relative temperature, and temperature amplitude), and WinterHabIndices (snow duration, variability, and subnivium). Each of these folders has one or more raster files used in the modeling framework. These are also available individually from the SILVIS Lab Webpage. | Files | File Name | Description | | --------- | ----------- | | Guild\_Membership.csv | Lists of species in each guild. | | SpeciesModeled\_Feb2023.excel | List of all species modeled both successfully and unsuccessfully at each resolution. The species we attempted to model are included in the "tried\_model" tab and the species we successfully modeled are in the "succeeded" tab. | | specieslist\_route\_2023\_final.txt | List of species included in route.zip | | specieslist\_tenstop\_2023\_final.txt | List of species included in tenstop.zip | | specieslist\_onestop\_2023\_final.txt | List of species included in onestop.zip | | route.sh | Bash shell executable file for parallelize analysis on HTC cluster. This is the file for the route level, but can be easily modified for stop or 10-stop. | | route.sub | Bash submit file for parallelize analysis on HTC cluster. This is the file for the route level, but can be easily modified for stop or 10-stop. | | route\_feb2023.R | R code used to run (set up for bash HTC cluster analysis). This is the file for the route level, but can be easily modified for stop or 10-stop. | Guild maps: Carroll, Kathleen et al. (2022), Mapping breeding bird species richness at management-relevant resolutions across the United States, Dryad, Dataset, https://doi.org/10.5061/dryad.vq83bk3v0 ## Sharing/Access information This is a section for linking to other ways to access the data, and for linking to sources the data is derived from, if any. Links to other publicly accessible locations of the data: * [https://silvis.forest.wisc.edu/data/mapping-breeding-birds/](https://silvis.forest.wisc.edu/data/mapping-breeding-birds/) * All guild and predictor data can be accessed via the SILVLIS website (above).