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Using Generative Art to Convey Past and Future Climate Transitions

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

Species persistence under climate change: a geographical scale coexistence problem.

Jacob Usinowicz¹, Jonathan M Levine¹

¹Institute of Integrative Biology, ETH Zurich, 8092, Zurich, Switzerland.

Ecology Letters

|September 7, 2018

Summary

Spatial coexistence theory can predict species persistence under climate change. This framework quantifies competitive interactions and scales local data for range-wide biodiversity forecasts.

Keywords:

Climate change low-density growth rate persistence range dynamics species coexistence

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Area of Science:

Ecology
Climate Change Biology
Theoretical Ecology

Background:

Forecasting species' responses to climate change necessitates integrating competitive interactions into range dynamics and persistence predictions.
Spatial coexistence theory has extensively studied species coexistence in heterogeneous environments, offering a potential framework for climate change impacts.

Purpose of the Study:

To adapt spatial coexistence theory into a mathematical framework for predicting species persistence in competitive communities under climate change.
To demonstrate how spatial low-density growth rates serve as a key metric for species persistence along climate gradients.

Main Methods:

Analyzing a model of multiple migrating competitors to quantify competitive processes influencing low-density growth rates.
Investigating how asynchronous species migration under climate change alters the strength of these competitive processes.
Outlining the empirical utility of the framework for scaling from local measurements to range-scale persistence metrics.

Main Results:

The spatial low-density growth rate is identified as the critical metric for species persistence across climate gradients.
Mechanisms affecting low-density growth rates quantify competitive effects on persistence and their changes under climate change-induced asynchronous migration.
The framework demonstrates scalability from local species performance data to broad-scale persistence predictions.

Conclusions:

Adapting spatial coexistence theory provides a robust mathematical framework for understanding species persistence under climate change.
This approach enhances the predictability of biodiversity responses by integrating competitive dynamics into climate change impact assessments.
The framework bridges local ecological measurements with range-scale predictions, improving forecasts for competitive communities facing climate change.