{"title":"从探测数据中解耦居民和分散者改进栖息地选择模型:自然走廊中狼的案例研究","authors":"O. Dondina, A. Meriggi, L. Bani, V. Orioli","doi":"10.1080/03949370.2021.1988724","DOIUrl":null,"url":null,"abstract":"Resource selection analyses based on detection data are widely used to parametrize resistance surfaces used to identify ecological corridors. To successfully parametrize resistance, it is crucial to decouple resident and disperser behaviours yet to date connectivity studies using detection data have not addressed this issue. Here, we decoupled data of resident and dispersing wolves by analysing detection data collected within a natural corridor crossing a human dominated plain in Italy. To decouple residents and dispersers, we ran a Kernel Density analysis to investigate whether clusters of wolf detection points characterized by sharply higher points’ density exist and checked whether the areas outlined by these clusters (core areas) hold specific characteristics. Habitat selection analysis was then performed to compare the intensity of habitat selection carried out by putative residents and dispersers. We identified a high-density cluster of 30 detection points outlining a small core area stably located in the central part of the park. The dramatic differences of the R2 and the AUC of the habitat selection models performed inside (R2 = 0.506; AUC = 0.952) and outside (R2 = 0.037; AUC = 0.643) the core area corroborated the hypothesis that the core area effectively encloses detection points belonging to residents. Our results show that through simple space use analyses it is possible to roughly discriminate between detection points belonging to resident-behaving and disperser-behaving individuals and that habitat selection models separately performed on these data have extremely different results with strong possible effects on resistance surfaces parametrized from these models. Highlights We decoupled data of resident and dispersing wolves by analyzing detection data collected within a natural ecological corridor. Through space use analyses on detection data, it is possible to roughly discriminate between resident-behaving and disperser-behaving individuals. Habitat selection carried out by resident-behaving and disperser-behaving individuals is dramatically different.","PeriodicalId":55163,"journal":{"name":"Ethology Ecology & Evolution","volume":"91 1","pages":"617 - 635"},"PeriodicalIF":1.3000,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Decoupling residents and dispersers from detection data improve habitat selection modelling: the case study of the wolf in a natural corridor\",\"authors\":\"O. Dondina, A. Meriggi, L. Bani, V. Orioli\",\"doi\":\"10.1080/03949370.2021.1988724\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Resource selection analyses based on detection data are widely used to parametrize resistance surfaces used to identify ecological corridors. To successfully parametrize resistance, it is crucial to decouple resident and disperser behaviours yet to date connectivity studies using detection data have not addressed this issue. Here, we decoupled data of resident and dispersing wolves by analysing detection data collected within a natural corridor crossing a human dominated plain in Italy. To decouple residents and dispersers, we ran a Kernel Density analysis to investigate whether clusters of wolf detection points characterized by sharply higher points’ density exist and checked whether the areas outlined by these clusters (core areas) hold specific characteristics. Habitat selection analysis was then performed to compare the intensity of habitat selection carried out by putative residents and dispersers. We identified a high-density cluster of 30 detection points outlining a small core area stably located in the central part of the park. The dramatic differences of the R2 and the AUC of the habitat selection models performed inside (R2 = 0.506; AUC = 0.952) and outside (R2 = 0.037; AUC = 0.643) the core area corroborated the hypothesis that the core area effectively encloses detection points belonging to residents. Our results show that through simple space use analyses it is possible to roughly discriminate between detection points belonging to resident-behaving and disperser-behaving individuals and that habitat selection models separately performed on these data have extremely different results with strong possible effects on resistance surfaces parametrized from these models. Highlights We decoupled data of resident and dispersing wolves by analyzing detection data collected within a natural ecological corridor. Through space use analyses on detection data, it is possible to roughly discriminate between resident-behaving and disperser-behaving individuals. Habitat selection carried out by resident-behaving and disperser-behaving individuals is dramatically different.\",\"PeriodicalId\":55163,\"journal\":{\"name\":\"Ethology Ecology & Evolution\",\"volume\":\"91 1\",\"pages\":\"617 - 635\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2022-01-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ethology Ecology & Evolution\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1080/03949370.2021.1988724\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BEHAVIORAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ethology Ecology & Evolution","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1080/03949370.2021.1988724","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BEHAVIORAL SCIENCES","Score":null,"Total":0}
Decoupling residents and dispersers from detection data improve habitat selection modelling: the case study of the wolf in a natural corridor
Resource selection analyses based on detection data are widely used to parametrize resistance surfaces used to identify ecological corridors. To successfully parametrize resistance, it is crucial to decouple resident and disperser behaviours yet to date connectivity studies using detection data have not addressed this issue. Here, we decoupled data of resident and dispersing wolves by analysing detection data collected within a natural corridor crossing a human dominated plain in Italy. To decouple residents and dispersers, we ran a Kernel Density analysis to investigate whether clusters of wolf detection points characterized by sharply higher points’ density exist and checked whether the areas outlined by these clusters (core areas) hold specific characteristics. Habitat selection analysis was then performed to compare the intensity of habitat selection carried out by putative residents and dispersers. We identified a high-density cluster of 30 detection points outlining a small core area stably located in the central part of the park. The dramatic differences of the R2 and the AUC of the habitat selection models performed inside (R2 = 0.506; AUC = 0.952) and outside (R2 = 0.037; AUC = 0.643) the core area corroborated the hypothesis that the core area effectively encloses detection points belonging to residents. Our results show that through simple space use analyses it is possible to roughly discriminate between detection points belonging to resident-behaving and disperser-behaving individuals and that habitat selection models separately performed on these data have extremely different results with strong possible effects on resistance surfaces parametrized from these models. Highlights We decoupled data of resident and dispersing wolves by analyzing detection data collected within a natural ecological corridor. Through space use analyses on detection data, it is possible to roughly discriminate between resident-behaving and disperser-behaving individuals. Habitat selection carried out by resident-behaving and disperser-behaving individuals is dramatically different.
期刊介绍:
Ethology Ecology & Evolution is an international peer reviewed journal which publishes original research and review articles on all aspects of animal behaviour, ecology and evolution. Articles should emphasise the significance of the research for understanding the function, ecology, evolution or genetics of behaviour. Contributions are also sought on aspects of ethology, ecology, evolution and genetics relevant to conservation.
Research articles may be in the form of full length papers or short research reports. The Editor encourages the submission of short papers containing critical discussion of current issues in all the above areas. Monograph-length manuscripts on topics of major interest, as well as descriptions of new methods are welcome. A Forum, Letters to Editor and Book Reviews are also included. Special Issues are also occasionally published.