| _version_ | 1866901425579098112 |
|---|---|
| author | Neubaum, Daniel J. Aagaard, Kevin |
| author_facet | Neubaum, Daniel J. Aagaard, Kevin |
| contents | (Uploaded by Plazi for the Bat Literature Project) Abstract Numerous processes operating at landscape scales threaten bats (e.g., habitat loss, disease). Temperate bat species are rarely examined at commensurate scales because of logistical and modeling constraints. Recent modeling approaches now allow for presence‐only datasets, like those often available for bats, to assist with the development of predictive distribution models. We describe the use of presence‐only data and rigorous predictive distribution models to examine habitat selection by bats across Colorado, USA. We applied hierarchical Bayesian models to bat locations from 1906–2018 to examine relationships of 13 species with landscape covariates. We considered differences in type of activity (foraging, roosting, hibernation), seasonality (summer vs. winter), and scale (1, 5, 10, and 15‐km buffers). These findings generated statewide probability of use models to guide management of bat species in response to threats (e.g., white‐nose syndrome [WNS]). Analysis of buffers suggest selection of land cover and environmental covariates occurs at different scales depending on the species and activity. Pinyon ( Pinus spp.)‐juniper ( Juniperus spp.) appeared as a positive association in the highest number of models, followed by montane woodland, supporting the importance of these forest types to bats in Colorado. Other covariates commonly associated with bats in Colorado include westerly longitudes, and negative associations with montane shrubland. Mechanical treatments within pinyon‐juniper and montane woodlands should be conducted with caution to avoid harming bat communities. We developed hibernation models for only 2 species, making apparent the lack of winter records for bat species in the state. We also provide a composite predictive surface of small‐bodied bats in Colorado that delineates where these species, vulnerable to WNS, converge. This tool provides managers with focal points to apply surveillance and response strategies for the impending arrival of the disease. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_13439433 |
| institution | Zenodo |
| language | |
| publishDate | 2022 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Use of predictive distribution models to describe habitat selection by bats in Colorado, USA Neubaum, Daniel J. Aagaard, Kevin Biodiversity Mammalia Chiroptera Chordata Animalia bats bat (Uploaded by Plazi for the Bat Literature Project) Abstract Numerous processes operating at landscape scales threaten bats (e.g., habitat loss, disease). Temperate bat species are rarely examined at commensurate scales because of logistical and modeling constraints. Recent modeling approaches now allow for presence‐only datasets, like those often available for bats, to assist with the development of predictive distribution models. We describe the use of presence‐only data and rigorous predictive distribution models to examine habitat selection by bats across Colorado, USA. We applied hierarchical Bayesian models to bat locations from 1906–2018 to examine relationships of 13 species with landscape covariates. We considered differences in type of activity (foraging, roosting, hibernation), seasonality (summer vs. winter), and scale (1, 5, 10, and 15‐km buffers). These findings generated statewide probability of use models to guide management of bat species in response to threats (e.g., white‐nose syndrome [WNS]). Analysis of buffers suggest selection of land cover and environmental covariates occurs at different scales depending on the species and activity. Pinyon ( Pinus spp.)‐juniper ( Juniperus spp.) appeared as a positive association in the highest number of models, followed by montane woodland, supporting the importance of these forest types to bats in Colorado. Other covariates commonly associated with bats in Colorado include westerly longitudes, and negative associations with montane shrubland. Mechanical treatments within pinyon‐juniper and montane woodlands should be conducted with caution to avoid harming bat communities. We developed hibernation models for only 2 species, making apparent the lack of winter records for bat species in the state. We also provide a composite predictive surface of small‐bodied bats in Colorado that delineates where these species, vulnerable to WNS, converge. This tool provides managers with focal points to apply surveillance and response strategies for the impending arrival of the disease. |
| title | Use of predictive distribution models to describe habitat selection by bats in Colorado, USA |
| topic | Biodiversity Mammalia Chiroptera Chordata Animalia bats bat |
| url | https://doi.org/10.5281/zenodo.13439433 |