Quantifying ecosystem degradation via energetic deficits

Abstract Ecosystem degradation is accelerating, posing critical threats to both biodiversity and human economies. A central challenge is to quantify degradation relative to a reference baseline in a way that supports restoration planning and resource allocation. Here, we address this challenge by examining the energetics of population dynamics, where energy inputs, such as sunlight, are transformed into embodied energy in the form of biomass. This perspective enables a unifying energetic framework to assess degradation through the concept of the energetic ecodeficit: the additional energy input a degraded ecosystem would require to return to a specified reference state. This energetic deficit can further be translated into a monetary ecodeficit, which represents the economic cost of restoration based on the local cost of embodied energy. We derive closed-form predictions for a trophic-chain instantiation of this framework, appropriate when dominant energy pathways can be parametrized as trophic transfers among biomass compartments. Our analysis reveals nonlinear relationships between biomass loss and energetic ecodeficit, including thresholds beyond which restoration becomes economically infeasible. We apply this framework to quantify current mammal biomass deficits across the African savannah, showing that the associated monetary ecodeficit is nearly two orders of magnitude greater than existing estimates. By embedding energetic principles into conservation planning, this approach provides a scalable and integrative tool for ecosystem valuation.

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Publication Details

Journal
Royal Society Open Science
Published
2026-09-30
DOI
https://doi.org/10.1098/rsos.260268
Primary Topic
Sustainability and Ecological Systems Analysis
Type
article
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article

Quantifying ecosystem degradation via energetic deficits

Yitong Liu, Serguei Saavedra, Marco Tulio Angulo, Dan Morris
Royal Society Open Science
Sustainability and Ecological Systems Analysis
article

Quantifying ecosystem degradation via energetic deficits

Yitong Liu, Serguei Saavedra, Marco Tulio Angulo, Dan Morris
article en

Abstract

Abstract Ecosystem degradation is accelerating, posing critical threats to both biodiversity and human economies. A central challenge is to quantify degradation relative to a reference baseline in a way that supports restoration planning and resource allocation. Here, we address this challenge by examining the energetics of population dynamics, where energy inputs, such as sunlight, are transformed into embodied energy in the form of biomass. This perspective enables a unifying energetic framework to assess degradation through the concept of the energetic ecodeficit: the additional energy input a degraded ecosystem would require to return to a specified reference state. This energetic deficit can further be translated into a monetary ecodeficit, which represents the economic cost of restoration based on the local cost of embodied energy. We derive closed-form predictions for a trophic-chain instantiation of this framework, appropriate when dominant energy pathways can be parametrized as trophic transfers among biomass compartments. Our analysis reveals nonlinear relationships between biomass loss and energetic ecodeficit, including thresholds beyond which restoration becomes economically infeasible. We apply this framework to quantify current mammal biomass deficits across the African savannah, showing that the associated monetary ecodeficit is nearly two orders of magnitude greater than existing estimates. By embedding energetic principles into conservation planning, this approach provides a scalable and integrative tool for ecosystem valuation.

Royal Society Open ScienceVol. 13(9)
Google (United States) (US), Santa Fe Institute (US), Massachusetts Institute of Technology (US), Universidad Nacional Autónoma de México (MX), Tsinghua University (CN)
Life in Land
Openalex Percentile: Top 19%
Sustainability and Ecological Systems Analysis
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Quantifying ecosystem degradation via energetic deficits — Yitong Liu, Serguei Saavedra, et al. · Royal Society Open Science (2026) | TGRS Research Map | TGRS