Multiple dimensions of extreme weather events and their impacts on biodiversity

被引:0
|
作者
Juan David González-Trujillo
Rosa M. Román-Cuesta
Aarón Israel Muñiz-Castillo
Cibele H. Amaral
Miguel B. Araújo
机构
[1] Consejo Superior de Investigaciones Científicas,Museo Nacional de Ciencias Naturales
[2] Environment and Development & CHANGE – Global Change and Sustainability Institute,“Rui Nabeiro” Biodiversity Chair, MED – Mediterranean Institute for Agriculture
[3] Universidade de Évora,Laboratory of Geo
[4] Wageningen University & Research,Information Science and Remote Sensing
[5] European University Institute,Florence School of Regulation
[6] Healthy Reefs for Healthy People Initiative,Earth Lab, Cooperative Institute for Research in Environmental Sciences
[7] University of Colorado Boulder,undefined
来源
Climatic Change | 2023年 / 176卷
关键词
Climate change; Vulnerability assessment; Extreme climate; Population demography; Biodiversity threats;
D O I
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中图分类号
学科分类号
摘要
Climate change is a multidimensional phenomenon. As such, no single metric can capture all trajectories of change and associated impacts. While numerous metrics exist to measure climate change, they tend to focus on central tendencies and neglect the multidimensionality of extreme weather events (EWEs). EWEs differ in their frequency, duration, and intensity, and can be described for temperature, precipitation, and wind speed, while considering different thresholds defining “extremeness.” We review existing EWE metrics and outline a framework for classifying and interpreting them in light of their foreseeable impacts on biodiversity. Using an example drawn from the Caribbean and Central America, we show that metrics reflect unequal spatial patterns of exposure across the region. Based on available evidence, we discuss how such patterns relate to threats to biological populations, empirically demonstrating how ecologically informed metrics can help relate EWEs to biological processes such as mangrove recovery. Unveiling the complexity of EWE trajectories affecting biodiversity is only possible through mobilisation of a plethora of climate change metrics. The proposed framework represents a step forward over assessments using single dimensions or averages of highly variable time series.
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