Environmental Predictability in Phylogenetic Comparative Analysis: How to Measure It and Does It Matter?

Journal article

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.

Authors: Liu, M; Bell‐Roberts, L; Botero, CA; Cornwallis, CK; West, SA

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: Global Ecology and Biogeography
• Volume: 34
• Issue: 8
• Article number: e70108
• Publication date: 2025-08-16
• Acceptance date: 2025-07-29
• DOI: 10.1111/geb.70108
• EISSN: 1466-8238
• ISSN: 1466822X and 1466-822X
• Language: English
• Keywords: climate change; cooperation; macroecology; global climatic dataset; harsh environment; climatic time series