Multiple dimensions of extreme weather events and their impacts on biodiversity

Abstract

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.

Exposure of protected areas in Central America to extreme weather events

“…Although absence of knowledge on species-specific responses to EWEs might hinder effective management and conservation efforts (Bailey & van de Pol 2016;Urban et al, 2016), the use of metrics can provide valuable insights for guiding urgent and priority conservation actions (Buenafe et al, 2023;Garcia et al, 2014;González-Trujillo et al, 2023). Our results underscore how each metric lends unique perspectives on the multiple dimensions of EWEs.…”

“…Adapting PAs to EWEs is more challenging than adjusting to gradual warming because biodiversity responses to EWEs depend on the specific dimension of change involved, ranging from rapid and severe disruptions to lagged long-term effects (González-Trujillo et al, 2023). For example, the more intense cyclones anticipated for the area can rapidly increase mortality rates across all developmental stages of a population, triggering mass mortality events and decreasing postdisturbance survival rates (Frederiksen et al 2008;Neilson et al, 2020).…”

“…A wide array of metrics exists to describe the multiple dimensions of EWEs (González-Trujillo et al, 2023). Metrics can be used to describe an EWE in terms of its unusual frequency, intensity, or duration and be based on different sets of variables, such as temperature, precipitation, and wind speed.…”

Predicting organismal response to marine heatwaves using mechanistic thermal landscape models

“…Conversely, experiments and models that describe physiological responses to temperature rarely capture variability found in MHWs and rely on responses to mean conditions, thereby ignoring non-linear responses and the effects of Jensen's inequality (Buckley & Kingsolver, 2021;Dowd et al, 2015;Gerhard et al, 2023;Harris et al, 2018;Morash et al, 2018). We lack coherent models that mechanistically link MHWs to observed responses in organisms and ecosystems (González-Trujillo et al, 2023;van de Pol et al, 2017).…”