A Multi-Scale Species Distribution Model for Migrating and Overwintering Western Monarch Butterflies: Climate Is the Best Predictor
Western Monarch butterflies (<i>Danaus plexippus</i>) migrate from inland breeding ranges to coastal overwintering grounds in California. Given that migratory individuals may make multi-scale habitat selection decisions, we considered a multi-scale species distribution model (SDM) using...
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MDPI AG
2024-10-01
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| author | Ashley R. Fisher William T. Bean Francis X. Villablanca |
| author_facet | Ashley R. Fisher William T. Bean Francis X. Villablanca |
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| description | Western Monarch butterflies (<i>Danaus plexippus</i>) migrate from inland breeding ranges to coastal overwintering grounds in California. Given that migratory individuals may make multi-scale habitat selection decisions, we considered a multi-scale species distribution model (SDM) using range-wide climatic and local landscape-level predictors of migratory and overwintering habitat and community-science presence data. The range-wide model output was included as a predictor in the local-scale model, generating multi-scale habitat suitability. The top range-wide predictor was the minimum temperature in December, contributing 83.7% to the model, and was positively associated with presence. At the local scale, the strongest predictors of presence were the range-wide output and percent coverage of low and medium levels of development, contributing > 95%, with 61–63% from the range-wide output, with local-scale suitability coinciding with the California coastal zones. Development’s positive association with overwintering monarch presence was counterintuitive. It is likely that our local-scale model is overfit to these development zones, but it is unclear whether this overfitting resulted from modeler choices, monarchs overwintering close to human development, biased detection near human development, or a combination of these factors. Therefore, alternative approaches to collecting local-scale attribute data are suggested while recognizing the primacy of climate in restricting overwinter sites. |
| format | Article |
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| institution | OA Journals |
| issn | 1424-2818 |
| language | English |
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| spelling | doaj-art-d29ce5dc5b10467ea1f715365c7881252025-08-20T02:11:05ZengMDPI AGDiversity1424-28182024-10-01161064010.3390/d16100640A Multi-Scale Species Distribution Model for Migrating and Overwintering Western Monarch Butterflies: Climate Is the Best PredictorAshley R. Fisher0William T. Bean1Francis X. Villablanca2Department of Biological Sciences, California Polytechnic State University, San Luis Obispo, CA 93407, USADepartment of Biological Sciences, California Polytechnic State University, San Luis Obispo, CA 93407, USADepartment of Biological Sciences, California Polytechnic State University, San Luis Obispo, CA 93407, USAWestern Monarch butterflies (<i>Danaus plexippus</i>) migrate from inland breeding ranges to coastal overwintering grounds in California. Given that migratory individuals may make multi-scale habitat selection decisions, we considered a multi-scale species distribution model (SDM) using range-wide climatic and local landscape-level predictors of migratory and overwintering habitat and community-science presence data. The range-wide model output was included as a predictor in the local-scale model, generating multi-scale habitat suitability. The top range-wide predictor was the minimum temperature in December, contributing 83.7% to the model, and was positively associated with presence. At the local scale, the strongest predictors of presence were the range-wide output and percent coverage of low and medium levels of development, contributing > 95%, with 61–63% from the range-wide output, with local-scale suitability coinciding with the California coastal zones. Development’s positive association with overwintering monarch presence was counterintuitive. It is likely that our local-scale model is overfit to these development zones, but it is unclear whether this overfitting resulted from modeler choices, monarchs overwintering close to human development, biased detection near human development, or a combination of these factors. Therefore, alternative approaches to collecting local-scale attribute data are suggested while recognizing the primacy of climate in restricting overwinter sites.https://www.mdpi.com/1424-2818/16/10/640multi-scale SDM<i>Danaus plexippus</i>western monarchoverwinteringclimatic predictorsoverfit |
| spellingShingle | Ashley R. Fisher William T. Bean Francis X. Villablanca A Multi-Scale Species Distribution Model for Migrating and Overwintering Western Monarch Butterflies: Climate Is the Best Predictor Diversity multi-scale SDM <i>Danaus plexippus</i> western monarch overwintering climatic predictors overfit |
| title | A Multi-Scale Species Distribution Model for Migrating and Overwintering Western Monarch Butterflies: Climate Is the Best Predictor |
| title_full | A Multi-Scale Species Distribution Model for Migrating and Overwintering Western Monarch Butterflies: Climate Is the Best Predictor |
| title_fullStr | A Multi-Scale Species Distribution Model for Migrating and Overwintering Western Monarch Butterflies: Climate Is the Best Predictor |
| title_full_unstemmed | A Multi-Scale Species Distribution Model for Migrating and Overwintering Western Monarch Butterflies: Climate Is the Best Predictor |
| title_short | A Multi-Scale Species Distribution Model for Migrating and Overwintering Western Monarch Butterflies: Climate Is the Best Predictor |
| title_sort | multi scale species distribution model for migrating and overwintering western monarch butterflies climate is the best predictor |
| topic | multi-scale SDM <i>Danaus plexippus</i> western monarch overwintering climatic predictors overfit |
| url | https://www.mdpi.com/1424-2818/16/10/640 |
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