26 citations as recorded by crossref.

1. Spind: a package for computing spatially corrected accuracy measures G. Carl & I. Kühn https://doi.org/10.1111/ecog.02593
2. Spatial Distribution of the Mexican Daisy, Erigeron karvinskianus, in New Zealand under Climate Change L. Hannah et al. https://doi.org/10.3390/cli7020024
3. IchthyMaps: A Database of Historical Distributions of Freshwater Fishes of the United States E. Frimpong et al. https://doi.org/10.1080/03632415.2016.1219948
4. Pure, shared, and coupling effects of climate change and sea level rise on the future distribution ofSpartina alternifloraalong the Chinese coast H. Gong et al. https://doi.org/10.1002/ece3.5129
5. Reclassifying the Wildland–Urban Interface Using Fire Occurrences for the United States B. Hanberry https://doi.org/10.3390/land9070225
6. Integrating habitat‐masked range maps with quantifications of prevalence to estimate area of occupancy in IUCN assessments R. Anderson https://doi.org/10.1111/cobi.14019
7. Classifying Large Wildfires in the United States by Land Cover B. Hanberry https://doi.org/10.3390/rs12182966
8. Potential expanded pollinator distributions in North America under future climate B. Hanberry https://doi.org/10.1002/2688-8319.70025
9. The effect of local species composition on the distribution of an avian invader T. Magory Cohen & R. Dor https://doi.org/10.1038/s41598-019-52256-9
10. When is variable importance estimation in species distribution modelling affected by spatial correlation? N. Harisena et al. https://doi.org/10.1111/ecog.05534
11. Beyond thinning: equalized sampling based on global sampling intensity gradients for species distribution models B. Hanberry https://doi.org/10.3389/fevo.2026.1831501
12. Defining and evaluating predictions of joint species distribution models D. Wilkinson et al. https://doi.org/10.1111/2041-210X.13518
13. Effects of Climate Change on the Climatic Niches of Warm-Adapted Evergreen Plants: Expansion or Contraction? K. Koo et al. https://doi.org/10.3390/f8120500
14. Model bigger to avoid unrepresentative species distribution models from truncated spatial extents, with the modulating influence of prevalence B. Hanberry https://doi.org/10.1016/j.envc.2026.101551
15. Preferential habitats prediction in syngnathids using species distribution models J. Hernández-Urcera et al. https://doi.org/10.1016/j.marenvres.2021.105488
16. Dealing with temporal variation and different life stages of whitemouth croaker Micropogonias furnieri (Actinopterygii, Sciaenidae) in species distribution modeling to improve essential estuarine fish habitat identification M. Costa et al. https://doi.org/10.1007/s10750-015-2348-4
17. Spatial Analysis of Maritime Disasters in the Philippines: Distribution Patterns and Identification of High-Risk Areas G. Aguilar et al. https://doi.org/10.3390/ijgi14010031
18. Potential Impacts of Climate Change on Native Plant Distributions in the Falkland Islands R. Upson et al. https://doi.org/10.1371/journal.pone.0167026
19. Validating ranges, georeferenced records, and species distribution models, for vertebrate and plant species globally B. Hanberry https://doi.org/10.1016/j.actao.2025.104137
20. Global invasion in progress: modeling the past, current and potential global distribution of the common myna T. Magory Cohen et al. https://doi.org/10.1007/s10530-018-1900-3
21. Predicted distribution of the glass sponge Vazella pourtalesi on the Scotian Shelf and its persistence in the face of climatic variability L. Beazley et al. https://doi.org/10.1371/journal.pone.0205505
22. Discovering Douglas-Fir Woodlands in the Historical Forests of Umatilla National Forest, Eastern Oregon and Washington B. Hanberry et al. https://doi.org/10.3390/f11101122
23. Climate-Change Refugia for the Bubblegum Coral Paragorgia arborea in the Northwest Atlantic S. Wang et al. https://doi.org/10.3389/fmars.2022.863693
24. Modeling Seasonal Fire Probability in Thailand: A Machine Learning Approach Using Multiyear Remote Sensing Data E. Bihari et al. https://doi.org/10.3390/rs17193378
25. Estimating species commonness and prevalence through unsupervised methods P. Bove et al. https://doi.org/10.1038/s41598-026-38900-1
26. Changing tree composition by life history strategy in a grassland‐forest landscape B. Hanberry et al. https://doi.org/10.1890/ES13-00345.1