Data: Mapping bee diversity with landscape-level models to inform conservation

Fine-Scale Models of Bee Species Diversity and Habitat in New York StateMark A. Buckner*, Erin L. White, Timothy G. Howard, Matthew D. Schlesinger, Bryan N. Danforth*Corresponding AuthorSupplemental Data<pre>```<br>NYSBeeDiversityBucknerEtal/<br>├─ diversityMetric/<br>│  ├─ diversityMetric_climateCommunity_ssp1_CCE_NYS_1995_2085.tif<br>│  ├─ diversityMetric_climateCommunity_ssp5_CCE_NYS_1995_2085.tif<br>│  ├─ diversityMetric_climateVelocity_ssp1_VoCC_NYS_1995_2085.tif<br>│  ├─ diversityMetric_climateVelocity_ssp5_VoCC_NYS_1995_2085.tif<br>│  ├─ diversityMetric_ecologicalUniqueness_LCBD_NYS_1971_2023.tif<br>│  ├─ diversityMetric_rangeSizeRarity_SSDM_NYS_1971_2023.tif<br>│  ├─ metadata_diversityMetric.xml<br>├─ speciesDistribution/<br>│  ├─ speciesDistribution_{GENUS}_{SPECIES}_SSDM_NYS_1971_2023.tif<br>│  ├─ metadata_speciesDistribution.xml<br>├─ speciesRichness/<br>│  ├─ speciesRichness_{SUBSET}_SSDM_NYS_1971_2023.tif<br>│  ├─ metadata_speciesRichness.xml<br>├─ speciesThreshold/<br>│  ├─ speciesThreshold_{GENUS}_{SPECIES}_SSDM_NYS_1971_2023.tif<br>│  ├─ metadata_speciesThreshold.xml<br>├─ pbkg_data_conus.gpkg<br>├─ test_pbkg_data_conus.gpkg<br>├─ speciesList.txt<br>├─ README.md<br>```</pre>Diversity Metrics (<code>diversityMetric/</code>)Includes output layers for each of the diversity and climate metrics.Climate Change:Community Climate Exposure: <code>climateCommunity</code>Climate Velocity: <code>climateVelocity</code>Ecological Uniqueness: <code>ecologicalUniqueness</code>Range-Size Rarity: <code>rangeSizeRarity</code>Species Distribution (<code>speciesDistribution/</code>)Probability predictions for each of the 269 species included in this study.Species Richness (<code>speciesRichness/</code>)Includes subsets for major life history groups and other groups of interest.All species: <code>allSpecies</code>Bumble Bees: <code>bombus</code>Life history groups:Nesting:<code>cavityAbove</code>: Above ground nesting species including cavity, rotting wood, and stem nesters<code>cavityBelow</code>: Preexisting below ground cavity nesters, excludes soil nesting species<code>soil</code>: Soil/ground nesting speciesSociality:<code>parasite</code>: Nest parasites (cleptoparasitic) or socially parasitic species<code>social</code>: Eusocial bees<code>solitary</code>: Solitary speciesForaging:<code>applePollinators</code>: Known apple orchard pollinators<code>generalists</code>: Species with no host plant specialization<code>specialists</code>: Species specialized on host plant/s (e.g., Oligolectic spp.)Native range:<code>native</code>: Species known to natively occur in NYS<code>nonNative</code>: Introduced and invasive bee speciesSpecies Thresholds (<code>speciesThreshold/</code>)Binary threshold predictions for each species created using probability ranking rules.Processed training dataA post-processing presence/background dataset (<code>pbkg_data_conus.gpkg</code>) is provided with permission of contributors for model reproducibility. <code>test_pbkg_data_conus.gpkg</code> is a reduced test file including records for only a fraction of the species.Dataset CitationPlease cite the dataset and reference publication.<pre>```<br>@article{Buckner2024,<br> author = "Mark A. Buckner and Erin L. White and Timothy G. Howard and Matthew D. Schlesinger and Bryan N. Danforth",<br> title = "{Data: Mapping bee diversity with landscape-level models to inform conservation}",<br> year = "2024",<br> month = "7",<br> url = "https://figshare.com/articles/software/Code_Fine-Scale_Models_of_Bee_Species_Diversity_and_Habitat_in_New_York_State/25884169",<br> doi = "10.6084/m9.figshare.25884169.v2"<br>}<br>```</pre>Reference Publication<pre>```<br>@article {Buckner2025,<br> author = {Buckner, Mark A and White, Erin L and Howard, Timothy G and Schlesinger, Matthew D and Danforth, Bryan N},<br> title = {Mapping bee diversity with landscape-level models to inform conservation},<br> journal = {Conservation Science and Practice},<br> year = {2025},<br> doi = {10.1111/csp2.70239},<br> abstract = {Anthropogenic drivers of global change threaten bee diversity, and the pollination services they provide. Despite the importance of bees, their conservation is complicated by limited and often heavily biased occurrence data. A recent state-wide survey of insect pollinators across New York, United States generated a large spatial dataset of bee species occurrence records from community scientists, historical collections, and recent surveys. To predict the distributions of most of the state{\textquoteright}s bee species, we combined the state survey records with occurrence data from across the contiguous United States, before applying an ensemble modeling approach consisting of balanced random forest and small bivariate generalized linear models. We predicted the spatial distribution of bee species richness using a stacked species distribution model with climate, land cover, and soil covariates. To inform bee diversity conservation, we predicted spatial variation for each species and groups of species sharing similar life history traits. We also estimated statewide distribution of range-size rarity, ecological uniqueness, and climate exposure. We found that the richness of modeled species is high across the state, with the greatest richness in regions with low soil clay content and intermediate forest cover. The fine spatial scale and extent of our gridded data layers match the scale of conservation action in the state, providing an opportunity to incorporate wild bee diversity into broader statewide conservation planning. Conserving bee pollinators is not straightforward, and decisions should be based on broader conservation priorities that incorporate bee biodiversity indicators into decision-making. Here, we present a roadmap for the inclusion of these vital pollinators in conservation decisions by leveraging the best available data and methods robust to small sample sizes to provide spatially explicit data products representing the distribution of bee diversity.}<br>}<br>```<br></pre><br>