Yulia Egorova, Gabriel Reygondeau, William W. L. Cheung, Evgeny A. Pakhomov
{"title":"中上层中浮游生物群落的物种分布模型","authors":"Yulia Egorova, Gabriel Reygondeau, William W. L. Cheung, Evgeny A. Pakhomov","doi":"10.1111/jbi.15011","DOIUrl":null,"url":null,"abstract":"AimWe aimed to enhance our understanding of the distribution of mesopelagic mesozooplankton (MM) using species distribution models, assess the performance of various modelling techniques, identify key environmental predictors for MM distribution and compute their habitat suitability indices.LocationOur study focused on the mesopelagic zone globally, with data analysed from different oceans.TaxonOur focus was primarily on mesopelagic mesozooplankton, gathering data on 861 different species from the Mesopelagic Mesozooplankton and Micronekton (MMM) Database.MethodsWe used an ensemble of species distribution models, applying 10 different modelling algorithms and three multi‐model ensemble approaches. We explored two important factors that can affect model performance: subsampling and the choice of background points. We also estimated the relative importance of various environmental conditions such as mixed layer depth, temperature, salinity, net primary productivity, euphotic zone depth and dissolved nitrate concentration on the distribution of these species.ResultsEuphotic zone depth, salinity and dissolved nitrate concentration were identified as the most important variables for explaining the distribution of mesopelagic mesozooplankton. The ensemble modelling results were robust in areas with abundant observational records, but high uncertainty was observed in data‐limited regions. We found a patchy habitat suitability map for zooplankton when modelled within their native range, largely due to uneven sampling. Unrestricted range models yielded smoother patterns but could inaccurately project species in areas where they do not occur.Main ConclusionsOur study highlights the need for increased sampling effort in data‐limited regions to improve the accuracy of mesopelagic species distribution models. Despite some inaccuracies, unrestricted range models, assuming ecological equivalence (where different species occupying a similar ecological niche in different geographical regions or different ecosystems exhibit similar adaptations and behaviours), provide a reasonable comparison for habitat suitability maps and model performance. It also confirms the significant impact of certain environmental conditions on mesozooplankton distribution.","PeriodicalId":15299,"journal":{"name":"Journal of Biogeography","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Species Distribution Models for Mesopelagic Mesozooplankton Community\",\"authors\":\"Yulia Egorova, Gabriel Reygondeau, William W. L. Cheung, Evgeny A. Pakhomov\",\"doi\":\"10.1111/jbi.15011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"AimWe aimed to enhance our understanding of the distribution of mesopelagic mesozooplankton (MM) using species distribution models, assess the performance of various modelling techniques, identify key environmental predictors for MM distribution and compute their habitat suitability indices.LocationOur study focused on the mesopelagic zone globally, with data analysed from different oceans.TaxonOur focus was primarily on mesopelagic mesozooplankton, gathering data on 861 different species from the Mesopelagic Mesozooplankton and Micronekton (MMM) Database.MethodsWe used an ensemble of species distribution models, applying 10 different modelling algorithms and three multi‐model ensemble approaches. We explored two important factors that can affect model performance: subsampling and the choice of background points. We also estimated the relative importance of various environmental conditions such as mixed layer depth, temperature, salinity, net primary productivity, euphotic zone depth and dissolved nitrate concentration on the distribution of these species.ResultsEuphotic zone depth, salinity and dissolved nitrate concentration were identified as the most important variables for explaining the distribution of mesopelagic mesozooplankton. The ensemble modelling results were robust in areas with abundant observational records, but high uncertainty was observed in data‐limited regions. We found a patchy habitat suitability map for zooplankton when modelled within their native range, largely due to uneven sampling. Unrestricted range models yielded smoother patterns but could inaccurately project species in areas where they do not occur.Main ConclusionsOur study highlights the need for increased sampling effort in data‐limited regions to improve the accuracy of mesopelagic species distribution models. Despite some inaccuracies, unrestricted range models, assuming ecological equivalence (where different species occupying a similar ecological niche in different geographical regions or different ecosystems exhibit similar adaptations and behaviours), provide a reasonable comparison for habitat suitability maps and model performance. It also confirms the significant impact of certain environmental conditions on mesozooplankton distribution.\",\"PeriodicalId\":15299,\"journal\":{\"name\":\"Journal of Biogeography\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Biogeography\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1111/jbi.15011\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biogeography","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1111/jbi.15011","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
Species Distribution Models for Mesopelagic Mesozooplankton Community
AimWe aimed to enhance our understanding of the distribution of mesopelagic mesozooplankton (MM) using species distribution models, assess the performance of various modelling techniques, identify key environmental predictors for MM distribution and compute their habitat suitability indices.LocationOur study focused on the mesopelagic zone globally, with data analysed from different oceans.TaxonOur focus was primarily on mesopelagic mesozooplankton, gathering data on 861 different species from the Mesopelagic Mesozooplankton and Micronekton (MMM) Database.MethodsWe used an ensemble of species distribution models, applying 10 different modelling algorithms and three multi‐model ensemble approaches. We explored two important factors that can affect model performance: subsampling and the choice of background points. We also estimated the relative importance of various environmental conditions such as mixed layer depth, temperature, salinity, net primary productivity, euphotic zone depth and dissolved nitrate concentration on the distribution of these species.ResultsEuphotic zone depth, salinity and dissolved nitrate concentration were identified as the most important variables for explaining the distribution of mesopelagic mesozooplankton. The ensemble modelling results were robust in areas with abundant observational records, but high uncertainty was observed in data‐limited regions. We found a patchy habitat suitability map for zooplankton when modelled within their native range, largely due to uneven sampling. Unrestricted range models yielded smoother patterns but could inaccurately project species in areas where they do not occur.Main ConclusionsOur study highlights the need for increased sampling effort in data‐limited regions to improve the accuracy of mesopelagic species distribution models. Despite some inaccuracies, unrestricted range models, assuming ecological equivalence (where different species occupying a similar ecological niche in different geographical regions or different ecosystems exhibit similar adaptations and behaviours), provide a reasonable comparison for habitat suitability maps and model performance. It also confirms the significant impact of certain environmental conditions on mesozooplankton distribution.
期刊介绍:
Papers dealing with all aspects of spatial, ecological and historical biogeography are considered for publication in Journal of Biogeography. The mission of the journal is to contribute to the growth and societal relevance of the discipline of biogeography through its role in the dissemination of biogeographical research.