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240311s2024 xx |||||o 00| ||eng c |
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|a 10.1111/gcb.17232
|2 doi
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|a pubmed25n1231.xml
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|a eng
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| 100 |
1 |
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|a Thonis, Anna
|e verfasserin
|4 aut
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| 245 |
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|a Unravelling the role of tropical cyclones in shaping present species distributions
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|c 2024
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|a Date Completed 12.03.2024
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|a Date Revised 12.03.2024
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|a published: Print
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|a Citation Status MEDLINE
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|a © 2024 John Wiley & Sons Ltd.
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|a Driven by climate change, tropical cyclones (TCs) are predicted to change in intensity and frequency through time. Given these forecasted changes, developing an understanding of how TCs impact insular wildlife is of heightened importance. Previous work has shown that extreme weather events may shape species distributions more strongly than climatic averages; however, given the coarse spatial and temporal scales at which TC data are often reported, the influence of TCs on species distributions has yet to be explored. Using TC data from the National Hurricane Center, we developed spatially and temporally explicit species distribution models (SDMs) to examine the role of TCs in shaping present-day distributions of Puerto Rico's 10 Anolis lizard species. We created six predictor variables to represent the intensity and frequency of TCs. For each occurrence of a species, we calculated these variables for TCs that came within 500 km of the center of Puerto Rico and occurred within the 1-year window prior to when that occurrence was recorded. We also included predictor variables related to landcover, climate, topography, canopy cover and geology. We used random forests to assess model performance and variable importance in models with and without TC variables. We found that the inclusion of TC variables improved model performance for the majority of Puerto Rico's 10 anole species. The magnitude of the improvement varied by species, with generalist species that occur throughout the island experiencing the greatest improvements in model performance. Range-restricted species experienced small, almost negligible, improvements but also had more predictive models both with and without the inclusion of TC variables compared to generalist species. Our findings suggest that incorporating data on TCs into SDMs may be important for modeling insular species that are prone to experiencing these types of extreme weather events
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|a Journal Article
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|a Anolis
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| 650 |
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|a MaxEnt
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| 650 |
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4 |
|a extreme weather events
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| 650 |
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4 |
|a random forest
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| 650 |
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4 |
|a species distribution models
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| 650 |
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4 |
|a tropical cyclones
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| 700 |
1 |
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|a Stansfield, Alyssa
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Akçakaya, H Resit
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t Global change biology
|d 1999
|g 30(2024), 3 vom: 20. März, Seite e17232
|w (DE-627)NLM098239996
|x 1365-2486
|7 nnas
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| 773 |
1 |
8 |
|g volume:30
|g year:2024
|g number:3
|g day:20
|g month:03
|g pages:e17232
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| 856 |
4 |
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|u http://dx.doi.org/10.1111/gcb.17232
|3 Volltext
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