Climate vulnerability assessment framework choice influences species prioritization and prediction of population decline
Abstract
Climate change vulnerability assessments (CCVAs) are regarded as an essential strategy to conservation strategies but are rarely used to inform conservation planning and prioritize species for management and adaptation. The main factor inhibiting its use is the challenge of combining exposure, sensitivity, and adaptive-capacity variables and, especially, of evaluating the ability of frameworks to predict species decline. This raises a fundamental challenge for conservation science: can climate vulnerability reliably identify species of conservation concern before widespread declines occur? Using extensive long-term monitoring data for 236 breeding bird species in North America, we compared a Trait-based Vulnerability Index (TVI), which combines variables into a fixed-weight composite index, with a Climate Vulnerability Model (CVM) that estimates the relative contribution of the same variables statistically. The two approaches showed limited agreement in the species identified as highly vulnerable (35.6% overlap), indicating that vulnerability estimates differed substantially among assessment frameworks. This divergence varied by guild and biome, with the greatest disagreement between frameworks found for seabirds, and CVM outperforming TVI in most biomes except for grassland-associated species. Exposure variables, particularly projected habitat loss and cumulative threat burden, outperformed intrinsic traits in predicting both climate-change threat listings and observed population decline. Species assigned higher model-based climate vulnerability were significantly more likely to exhibit long-term population declines, whereas sensitivity and adaptive-capacity traits provided comparatively little additional predictive information. Our study provides a rare empirical evaluation of climate vulnerability assessments and their ability to identify species experiencing biological decline. Our results suggest that different vulnerability assessments can lead to different conservation priorities, indicating that additional work is needed to improve and validate climate-risk frameworks. The positive associations between vulnerability estimates and demographic decline indicate that large-scale assessments can provide useful information for evaluating risk and prioritizing conservation action where direct demographic data are limited.
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BibTeX
@misc{serrano2026climate,
title = {{Climate vulnerability assessment framework choice influences species prioritization and prediction of population decline}},
author = {Janaína de Andrade Serrano and Andrea Brown and Laura J. Pollock},
howpublished = {EcoEvoRxiv},
year = {2026},
month = oct,
doi = {10.32942/x2ct22},
url = {https://ecoevorxiv.org/repository/view/15302/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Climate vulnerability assessment framework choice influences species prioritization and prediction of population decline
AU - Janaína de Andrade Serrano
AU - Andrea Brown
AU - Laura J. Pollock
PY - 2026
DA - 2026/10/01
PB - EcoEvoRxiv
DO - 10.32942/x2ct22
UR - https://ecoevorxiv.org/repository/view/15302/
AB - Climate change vulnerability assessments (CCVAs) are regarded as an essential strategy to conservation strategies but are rarely used to inform conservation planning and prioritize species for management and adaptation. The main factor inhibiting its use is the challenge of combining exposure, sensitivity, and adaptive-capacity variables and, especially, of evaluating the ability of frameworks to predict species decline. This raises a fundamental challenge for conservation science: can climate vulnerability reliably identify species of conservation concern before widespread declines occur? Using extensive long-term monitoring data for 236 breeding bird species in North America, we compared a Trait-based Vulnerability Index (TVI), which combines variables into a fixed-weight composite index, with a Climate Vulnerability Model (CVM) that estimates the relative contribution of the same variables statistically. The two approaches showed limited agreement in the species identified as highly vulnerable (35.6% overlap), indicating that vulnerability estimates differed substantially among assessment frameworks. This divergence varied by guild and biome, with the greatest disagreement between frameworks found for seabirds, and CVM outperforming TVI in most biomes except for grassland-associated species. Exposure variables, particularly projected habitat loss and cumulative threat burden, outperformed intrinsic traits in predicting both climate-change threat listings and observed population decline. Species assigned higher model-based climate vulnerability were significantly more likely to exhibit long-term population declines, whereas sensitivity and adaptive-capacity traits provided comparatively little additional predictive information. Our study provides a rare empirical evaluation of climate vulnerability assessments and their ability to identify species experiencing biological decline. Our results suggest that different vulnerability assessments can lead to different conservation priorities, indicating that additional work is needed to improve and validate climate-risk frameworks. The positive associations between vulnerability estimates and demographic decline indicate that large-scale assessments can provide useful information for evaluating risk and prioritizing conservation action where direct demographic data are limited.
ER -