勇闯未知:在非模拟气候条件下模拟外来物种时选择变量的重要性

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-10-28 DOI:10.1002/ece3.70490
Tom Vorstenbosch, Franz Essl, Bernd Lenzner, Johannes Wessely, Stefan Dullinger
{"title":"勇闯未知:在非模拟气候条件下模拟外来物种时选择变量的重要性","authors":"Tom Vorstenbosch,&nbsp;Franz Essl,&nbsp;Bernd Lenzner,&nbsp;Johannes Wessely,&nbsp;Stefan Dullinger","doi":"10.1002/ece3.70490","DOIUrl":null,"url":null,"abstract":"<p>Species distribution models (SDMs) are widely used to address species' responses to bioclimatic conditions in the fields of ecology, biogeography and conservation. Among studies that have addressed reasons for model prediction variability, the impact of climatic variable selection has received limited attention and is rarely assessed in sensitivity analyses. Here, we tested the assumption that this aspect of model design is a major source of uncertainty, especially when projections are made to non-analogue climates. As a study system, we used 142 alien plant species introduced to the sub-Antarctic islands. Based on global occurrence data, we fitted SDMs as functions of seven bioclimatic variable sets that only differed in the identity of two temperature variables. Moreover, we calculated the overlap between the island's climatic conditions and the niches the species have realised outside of the islands. Despite comparable internal evaluation metrics, projections of these models were in sharp contrast with each other, with some models predicting the sub-Antarctic islands' climate to be almost ubiquitously suitable to most species and others unsuitable to almost all species. In particular, the mean temperature of the warmest month led to strong underpredictions of the SDMs, while its replacement by the mean temperature of the coldest month led to massive overpredictions. Partitioning the variance in projections demonstrated that predictor identity was its most important source, followed by island and species identity. The size of area projected to be suitable was also related to the overlap in predictor values realised in the global range of species (outside of the islands) and on the islands. Our findings emphasise the importance of bioclimatic variable selection in SDMs, especially when making projections to non-analogue climates. Such extrapolations are often required, especially when using SDMs to assess invasion risk under both current and future climates.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.70490","citationCount":"0","resultStr":"{\"title\":\"Venturing Into the Unknown: The Importance of Variable Selection When Modelling Alien Species Under Non-Analogue Climatic Conditions\",\"authors\":\"Tom Vorstenbosch,&nbsp;Franz Essl,&nbsp;Bernd Lenzner,&nbsp;Johannes Wessely,&nbsp;Stefan Dullinger\",\"doi\":\"10.1002/ece3.70490\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Species distribution models (SDMs) are widely used to address species' responses to bioclimatic conditions in the fields of ecology, biogeography and conservation. Among studies that have addressed reasons for model prediction variability, the impact of climatic variable selection has received limited attention and is rarely assessed in sensitivity analyses. Here, we tested the assumption that this aspect of model design is a major source of uncertainty, especially when projections are made to non-analogue climates. As a study system, we used 142 alien plant species introduced to the sub-Antarctic islands. Based on global occurrence data, we fitted SDMs as functions of seven bioclimatic variable sets that only differed in the identity of two temperature variables. Moreover, we calculated the overlap between the island's climatic conditions and the niches the species have realised outside of the islands. Despite comparable internal evaluation metrics, projections of these models were in sharp contrast with each other, with some models predicting the sub-Antarctic islands' climate to be almost ubiquitously suitable to most species and others unsuitable to almost all species. In particular, the mean temperature of the warmest month led to strong underpredictions of the SDMs, while its replacement by the mean temperature of the coldest month led to massive overpredictions. Partitioning the variance in projections demonstrated that predictor identity was its most important source, followed by island and species identity. The size of area projected to be suitable was also related to the overlap in predictor values realised in the global range of species (outside of the islands) and on the islands. Our findings emphasise the importance of bioclimatic variable selection in SDMs, especially when making projections to non-analogue climates. Such extrapolations are often required, especially when using SDMs to assess invasion risk under both current and future climates.</p>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.70490\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/ece3.70490\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ece3.70490","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0

摘要

物种分布模型(SDMs)被广泛应用于生态学、生物地理学和自然保护领域,以解决物种对生物气候条件的反应问题。在针对模型预测变异性原因的研究中,气候变量选择的影响受到的关注有限,而且很少在敏感性分析中进行评估。在这里,我们检验了模型设计的这一方面是不确定性的主要来源这一假设,尤其是在对非模拟气候进行预测时。作为一个研究系统,我们使用了 142 种引入亚南极岛屿的外来植物物种。根据全球发生数据,我们将 SDM 拟合为七个生物气候变量集的函数,这些变量集仅在两个温度变量的特性上存在差异。此外,我们还计算了岛屿气候条件与物种在岛屿外实现的生态位之间的重叠度。尽管这些模型的内部评价指标具有可比性,但它们的预测结果却形成了鲜明的对比,有些模型预测亚南极岛屿的气候几乎普遍适合大多数物种,而有些模型则几乎不适合所有物种。特别是,用最暖月份的平均气温预测,SDMs 的预测结果严重偏低,而用最冷月份的平均气温预测,SDMs 的预测结果则严重偏高。对预测差异的划分表明,预测因子特性是其最重要的来源,其次是岛屿和物种特性。预测的适宜地区面积还与全球物种分布区(岛屿外)和岛屿上的预测值重叠有关。我们的研究结果强调了在 SDM 中选择生物气候变量的重要性,尤其是在对非类似气候进行预测时。这种推断通常是必需的,尤其是在使用可持续发展机制评估当前和未来气候下的入侵风险时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Venturing Into the Unknown: The Importance of Variable Selection When Modelling Alien Species Under Non-Analogue Climatic Conditions

Species distribution models (SDMs) are widely used to address species' responses to bioclimatic conditions in the fields of ecology, biogeography and conservation. Among studies that have addressed reasons for model prediction variability, the impact of climatic variable selection has received limited attention and is rarely assessed in sensitivity analyses. Here, we tested the assumption that this aspect of model design is a major source of uncertainty, especially when projections are made to non-analogue climates. As a study system, we used 142 alien plant species introduced to the sub-Antarctic islands. Based on global occurrence data, we fitted SDMs as functions of seven bioclimatic variable sets that only differed in the identity of two temperature variables. Moreover, we calculated the overlap between the island's climatic conditions and the niches the species have realised outside of the islands. Despite comparable internal evaluation metrics, projections of these models were in sharp contrast with each other, with some models predicting the sub-Antarctic islands' climate to be almost ubiquitously suitable to most species and others unsuitable to almost all species. In particular, the mean temperature of the warmest month led to strong underpredictions of the SDMs, while its replacement by the mean temperature of the coldest month led to massive overpredictions. Partitioning the variance in projections demonstrated that predictor identity was its most important source, followed by island and species identity. The size of area projected to be suitable was also related to the overlap in predictor values realised in the global range of species (outside of the islands) and on the islands. Our findings emphasise the importance of bioclimatic variable selection in SDMs, especially when making projections to non-analogue climates. Such extrapolations are often required, especially when using SDMs to assess invasion risk under both current and future climates.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
期刊最新文献
A Systematic Review of Sleep Disturbance in Idiopathic Intracranial Hypertension. Advancing Patient Education in Idiopathic Intracranial Hypertension: The Promise of Large Language Models. Anti-Myelin-Associated Glycoprotein Neuropathy: Recent Developments. Approach to Managing the Initial Presentation of Multiple Sclerosis: A Worldwide Practice Survey. Association Between LACE+ Index Risk Category and 90-Day Mortality After Stroke.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1