Ming Liu, Louis Bell-Roberts, Carlos A. Botero, Charlie K. Cornwallis, Stuart A. West
{"title":"Environmental Predictability in Phylogenetic Comparative Analysis: How to Measure It and Does It Matter?","authors":"Ming Liu, Louis Bell-Roberts, Carlos A. Botero, Charlie K. Cornwallis, Stuart A. West","doi":"10.1111/geb.70108","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Aim</h3>\n \n <p>Abiotic environmental conditions shape ecological and evolutionary processes, yet quantifying their influence on organisms remains challenging due to variation among metrics and their intercorrelations. This study evaluates the utility of temporal environmental predictability measures and assesses their explanatory power in phylogenetic comparative analyses.</p>\n </section>\n \n <section>\n \n <h3> Innovation</h3>\n \n <p>We systematically compare widely used metrics of predictability and explore their correlations with environmental means and variances in a global meteorological dataset. Using cooperative breeding birds as a case study, we assess the impact of including predictability metrics in phylogenetic comparative analyses. We demonstrate the consequences of choosing specific metrics and the trade-offs between increased data inclusion and model interpretability.</p>\n </section>\n \n <section>\n \n <h3> Main Conclusions</h3>\n \n <p>Predictability metrics, though intuitively meaningful, have been conceptualised and quantified with diverse approaches. We found that different measures of predictability can exhibit contrasting global patterns and strong correlations with other environmental quantities. Therefore, our findings caution against overloading statistical analyses with correlated predictors, highlighting the need for a thoughtful selection of environmental metrics to avoid spurious interpretations in ecological and evolutionary studies.</p>\n </section>\n </div>","PeriodicalId":176,"journal":{"name":"Global Ecology and Biogeography","volume":"34 8","pages":""},"PeriodicalIF":6.0000,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/geb.70108","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Ecology and Biogeography","FirstCategoryId":"93","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/geb.70108","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Aim
Abiotic environmental conditions shape ecological and evolutionary processes, yet quantifying their influence on organisms remains challenging due to variation among metrics and their intercorrelations. This study evaluates the utility of temporal environmental predictability measures and assesses their explanatory power in phylogenetic comparative analyses.
Innovation
We systematically compare widely used metrics of predictability and explore their correlations with environmental means and variances in a global meteorological dataset. Using cooperative breeding birds as a case study, we assess the impact of including predictability metrics in phylogenetic comparative analyses. We demonstrate the consequences of choosing specific metrics and the trade-offs between increased data inclusion and model interpretability.
Main Conclusions
Predictability metrics, though intuitively meaningful, have been conceptualised and quantified with diverse approaches. We found that different measures of predictability can exhibit contrasting global patterns and strong correlations with other environmental quantities. Therefore, our findings caution against overloading statistical analyses with correlated predictors, highlighting the need for a thoughtful selection of environmental metrics to avoid spurious interpretations in ecological and evolutionary studies.
期刊介绍:
Global Ecology and Biogeography (GEB) welcomes papers that investigate broad-scale (in space, time and/or taxonomy), general patterns in the organization of ecological systems and assemblages, and the processes that underlie them. In particular, GEB welcomes studies that use macroecological methods, comparative analyses, meta-analyses, reviews, spatial analyses and modelling to arrive at general, conceptual conclusions. Studies in GEB need not be global in spatial extent, but the conclusions and implications of the study must be relevant to ecologists and biogeographers globally, rather than being limited to local areas, or specific taxa. Similarly, GEB is not limited to spatial studies; we are equally interested in the general patterns of nature through time, among taxa (e.g., body sizes, dispersal abilities), through the course of evolution, etc. Further, GEB welcomes papers that investigate general impacts of human activities on ecological systems in accordance with the above criteria.