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Ecosystem tipping points in an evolving world.

Vasilis Dakos¹, Blake Matthews², Andrew P Hendry³

¹Institute des Sciences de l'Évolution, Université de Montpellier, CNRS, IRD, EPHE, Montpellier, France. vasilis.dakos@umontpellier.fr.

Nature Ecology & Evolution

|February 20, 2019

Summary

This summary is machine-generated.

Ecosystem tipping points, abrupt shifts due to environmental thresholds, are influenced by trait variation. Understanding ecological and evolutionary interactions is crucial for predicting and managing these critical transitions.

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Area of Science:

Ecology
Evolutionary Biology
Environmental Science

Background:

Ecosystems face tipping points when environmental thresholds are crossed, leading to abrupt, irreversible state shifts.
These shifts can incur significant societal costs and are influenced by biotic feedbacks.
Trait variation within populations plays a key role in ecosystem stability and response to environmental change.

Purpose of the Study:

To investigate how evolutionary changes in trait distributions over time impact the occurrence of ecosystem tipping points.
To explore the reciprocal interactions between large-scale ecological shifts and trait dynamics.

Main Methods:

This study is primarily theoretical, focusing on conceptualizing the interplay between ecological and evolutionary processes.
It synthesizes existing knowledge on ecosystem dynamics, trait variation, and environmental change.

Main Results:

Trait variation is central to the feedbacks that maintain alternative ecosystem states.
The dynamics of trait distributions are critical in determining the likelihood and nature of tipping points.
Reciprocal interactions between ecological shifts and trait evolution are poorly understood but significant.

Conclusions:

Interactions between ecological and evolutionary processes are fundamental to understanding ecosystem tipping points.
A combined ecological and evolutionary perspective is necessary for accurate modeling and management of ecosystem stability.
Future research should focus on integrating these coupled dynamics to better predict critical transitions in nature.