This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1002/pan3.10609. This is version 1 of this Preprint.
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Abstract
There is a cross-sectoral push amongst conservation practitioners to simultaneously mitigate biodiversity loss and climate change, especially as the latter increasingly threatens the former. Growing evidence demonstrates that animals can have substantial impacts on carbon cycling and as such, there are increasing calls to use animal conservation and trophic rewilding to help dually overcome biodiversity loss and climate change. Trophic rewilding is a complex conservation approach to mitigating climate change because it requires accurate baseline estimates of carbon cycling and species impacts on a system, social support for the project, and the actual reintroduction of a species. We join the growing excitement around this potential but caution that rewilding cannot always be justified on carbon benefits alone: a species’ net impact on ecosystem carbon dynamics is context dependent. The need for caution intensifies whenever biodiversity conservation (including rewilding), climate change mitigation, and human welfare do not readily align. Hence, these burgeoning efforts must avoid sweeping generalizations. To bolster reliable outcomes, we highlight the regional social and ecological context dependencies that can drastically vary outcomes in a rewilded carbon cycle and provide ethical considerations for successful implementation. We conclude with an overview of the available technology to predict and monitor progress toward both biodiversity and climate mitigation goals.
DOI
https://doi.org/10.32942/X2PS3W
Subjects
Life Sciences
Keywords
biodiversity, Carbon cycle, carbon offset, conservation decision-making, conservation prioritization, conservation ethics, nature-based climate solutions, Rewilding
Dates
Published: 2023-05-30 01:42
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Language:
English
Conflict of interest statement:
None
Data and Code Availability Statement:
Not applicable
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