Uncovering global drivers threatening vegetation resilience

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Authors

Camille Fournier de Lauriere , Katharina Runge, Gabriel Smith, Vasilis Dakos , Sonia Kefi, Thomas W. Crowther, Miguel Berdugo

Abstract

1) Context: The resilience of the Earth's vegetation is changing heterogeneously, making it a challenge to unveil what causes these resilience changes. Understanding the driving forces of these changes can help us make informed management decisions to protect and restore ecosystems. Here, we address this gap by identifying the drivers that have caused the resilience of ecosystems to change during the last two decades.

2) Methods: We globally measured two complementary aspects of resilience, namely sensitivity and autocorrelation, which are respectively associated with the resisting and recovering ability of ecosystems. We used a machine learning approach to identify the main environmental, climatic, and anthropogenic drivers of changes in resilience between two periods (the period 2000-2010 vs. that of 2010-2020).

3) Results: We found that in 26% of regions worldwide, vegetation exhibits signs of resilience loss. Moreover, ecosystem’s properties (aridity, elevation, anthropization) affect the way vegetation resilience has changed over time. When controlling for these properties, different biomes (forest, grasslands, and savannas) will exhibit similar responses to changes in climate conditions. Regions experiencing intense warming (>0.2ºC/decade) have shown a major loss in vegetation resilience. Decreasing productivity is associated with reduced resilience and interacts with warming, exacerbating resilience loss of less productive lands (potentially showing signs of degradation).

4) Conclusions: Warming and degradation appear as major drivers of losses in vegetation resilience across vegetation types. These results raise concerns about the persistence of ecosystems under continued climate change and expected intensification of human activities which, highlights the importance of maintaining the resilience of ecosystems under changing environmental conditions.

DOI

https://doi.org/10.32942/X2DP4R

Subjects

Environmental Monitoring, Forest Biology

Keywords

Resistance, sensitivity, autocorrelation, recovery, climate change, degradation, Aridity

Dates

Published: 2023-09-25 10:28

Last Updated: 2023-09-25 14:28

License

CC-BY Attribution-NonCommercial 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
None.

Data and Code Availability Statement:
The data and code that support the findings of this study are not yet made openly available at this stage of publication. SHAP values plots from the models can be visualized using "https://cfournierdel.shinyapps.io/SHAPValuesFournier/"