Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts
Conservation increasingly operates at the landscape scale. For this to be effective, we need landscape scale information on species distributions and the environmental factors that underpin them. Species records are becoming increasingly available via data centres and online portals, but they are of...
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ftpubmed:oai:pubmedcentral.nih.gov:4460044 2023-05-15T17:48:39+02:00 Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts Bellamy, Chloe Altringham, John 2015-06-08 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4460044/ http://www.ncbi.nlm.nih.gov/pubmed/26053548 https://doi.org/10.1371/journal.pone.0128440 en eng Public Library of Science http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4460044/ http://www.ncbi.nlm.nih.gov/pubmed/26053548 http://dx.doi.org/10.1371/journal.pone.0128440 http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited CC-BY Research Article Text 2015 ftpubmed https://doi.org/10.1371/journal.pone.0128440 2015-07-05T00:08:52Z Conservation increasingly operates at the landscape scale. For this to be effective, we need landscape scale information on species distributions and the environmental factors that underpin them. Species records are becoming increasingly available via data centres and online portals, but they are often patchy and biased. We demonstrate how such data can yield useful habitat suitability models, using bat roost records as an example. We analysed the effects of environmental variables at eight spatial scales (500 m – 6 km) on roost selection by eight bat species (Pipistrellus pipistrellus, P. pygmaeus, Nyctalus noctula, Myotis mystacinus, M. brandtii, M. nattereri, M. daubentonii, and Plecotus auritus) using the presence-only modelling software MaxEnt. Modelling was carried out on a selection of 418 data centre roost records from the Lake District National Park, UK. Target group pseudoabsences were selected to reduce the impact of sampling bias. Multi-scale models, combining variables measured at their best performing spatial scales, were used to predict roosting habitat suitability, yielding models with useful predictive abilities. Small areas of deciduous woodland consistently increased roosting habitat suitability, but other habitat associations varied between species and scales. Pipistrellus were positively related to built environments at small scales, and depended on large-scale woodland availability. The other, more specialist, species were highly sensitive to human-altered landscapes, avoiding even small rural towns. The strength of many relationships at large scales suggests that bats are sensitive to habitat modifications far from the roost itself. The fine resolution, large extent maps will aid targeted decision-making by conservationists and planners. We have made available an ArcGIS toolbox that automates the production of multi-scale variables, to facilitate the application of our methods to other taxa and locations. Habitat suitability modelling has the potential to become a standard tool for ... Text Nyctalus noctula Pipistrellus pipistrellus PubMed Central (PMC) PLOS ONE 10 6 e0128440 |
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Research Article Bellamy, Chloe Altringham, John Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts |
topic_facet |
Research Article |
description |
Conservation increasingly operates at the landscape scale. For this to be effective, we need landscape scale information on species distributions and the environmental factors that underpin them. Species records are becoming increasingly available via data centres and online portals, but they are often patchy and biased. We demonstrate how such data can yield useful habitat suitability models, using bat roost records as an example. We analysed the effects of environmental variables at eight spatial scales (500 m – 6 km) on roost selection by eight bat species (Pipistrellus pipistrellus, P. pygmaeus, Nyctalus noctula, Myotis mystacinus, M. brandtii, M. nattereri, M. daubentonii, and Plecotus auritus) using the presence-only modelling software MaxEnt. Modelling was carried out on a selection of 418 data centre roost records from the Lake District National Park, UK. Target group pseudoabsences were selected to reduce the impact of sampling bias. Multi-scale models, combining variables measured at their best performing spatial scales, were used to predict roosting habitat suitability, yielding models with useful predictive abilities. Small areas of deciduous woodland consistently increased roosting habitat suitability, but other habitat associations varied between species and scales. Pipistrellus were positively related to built environments at small scales, and depended on large-scale woodland availability. The other, more specialist, species were highly sensitive to human-altered landscapes, avoiding even small rural towns. The strength of many relationships at large scales suggests that bats are sensitive to habitat modifications far from the roost itself. The fine resolution, large extent maps will aid targeted decision-making by conservationists and planners. We have made available an ArcGIS toolbox that automates the production of multi-scale variables, to facilitate the application of our methods to other taxa and locations. Habitat suitability modelling has the potential to become a standard tool for ... |
format |
Text |
author |
Bellamy, Chloe Altringham, John |
author_facet |
Bellamy, Chloe Altringham, John |
author_sort |
Bellamy, Chloe |
title |
Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts |
title_short |
Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts |
title_full |
Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts |
title_fullStr |
Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts |
title_full_unstemmed |
Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts |
title_sort |
predicting species distributions using record centre data: multi-scale modelling of habitat suitability for bat roosts |
publisher |
Public Library of Science |
publishDate |
2015 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4460044/ http://www.ncbi.nlm.nih.gov/pubmed/26053548 https://doi.org/10.1371/journal.pone.0128440 |
genre |
Nyctalus noctula Pipistrellus pipistrellus |
genre_facet |
Nyctalus noctula Pipistrellus pipistrellus |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4460044/ http://www.ncbi.nlm.nih.gov/pubmed/26053548 http://dx.doi.org/10.1371/journal.pone.0128440 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1371/journal.pone.0128440 |
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PLOS ONE |
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10 |
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