The increase in intensity and duration of heat waves in the Caribbean and Central American regions over the last 80 years. The interaction between both dimensions is assessed by calculating the MCI, which represents the yearly average cumulative intensity.
Climate change is a multifaceted phenomenon that defies simplistic measurements. While many metrics exist to gauge its effects, they often overlook the multidimensionality of extreme weather events (EWEs). These events vary in frequency, duration, and intensity and can manifest in different forms, such as temperature extremes, precipitation anomalies, and violent wind speeds.
In a new study published today in Climatic Change, a team of scientists has unveiled a novel approach to understanding the complex relationship between extreme climate change and biodiversity. The research, led by Juan David González Trujillo and Miguel Bastos Araújo, introduces a conceptual framework that classifies and interprets a wide range of climate change metrics in the context of their foreseeable impacts on biodiversity.
“As our planet grapples with the ongoing impacts of climate change, it becomes increasingly imperative to transcend simplistic, one-dimensional assessments and embrace the intricate multidimensionality of extreme weather events,” emphasizes Bastos Araújo, senior author of the study. “Our research uncovers the remarkable complexity in extreme weather events—a complexity of such magnitude that surpasses conventional expectations and defies easy classification using existing metrics. It underscores the urgent need to account for the diverse facets of these events, encompassing not only their spatial patterns but also their profound ecological implications.”
The study draws on empirical evidence from the Caribbean and Central America, revealing that climate change metrics can illuminate unequal spatial patterns of exposure across regions. “Understanding these patterns is key to addressing threats to biological populations,” adds first author Dr. González Trujillo. “By using ecologically informed metrics, we can better relate extreme weather events to critical biological processes, such as mangrove recovery.”
Mesoamerica and the Caribbean have earned the moniker of a miner’s canary in the context of climate change due to the notable surge in extreme weather events within this region. Nowhere else in the world do so many climate hazards converge upon a global hotspot of biodiversity, all against a backdrop of pronounced socioeconomic vulnerability. While the region is renowned for its frequent hurricanes and cyclones, it also grapples with the recurrent challenges of droughts and heatwaves.
Despite the region’s vulnerability to climate extremes, a comprehensive assessment of extreme weather events (EWEs) has yet to be undertaken, considering their myriad dimensions and diverse climatic variables. This research is a pioneering effort to bridge this knowledge gap, providing critical insights into how EWEs impact the intricate web of life in these ecologically significant regions.
The research underscores the complexity of extreme weather event trajectories affecting biodiversity. “To truly grasp the intricacies of climate change’s impact on biodiversity, we must harness a diverse array of climate change metrics,” explains González Trujillo. “Our proposed framework represents a significant step forward from assessments relying on single dimensions or averages of highly variable timeseries.”
This groundbreaking study not only expands our understanding of the intricate relationship between climate change and biodiversity but also provides a comprehensive framework for future research and policy development. With climate change accelerating, the need for multidimensional assessments has never been more urgent.
Data and code, as well as a dynamic overview of the spatiotemporal of EWE in the region is available in a GitHub repository.
A framework for evaluating multiple dimensions of extreme weather events and the corresponding potential threats to biodiversity. It starts with the selection of the dimension and climatic variable to be assessed (A); then the threshold that determines the extremeness of the event is chosen (B); and finally the spatial and temporal resolution at which the exposure will be analysed (C). The patterns resulting from each dimension may be associated with one or more demographic processes of the biological populations (D).