Wild meat consumption in tropical forests spares a significant carbon footprint from the livestock production sector
Research output: Contribution to journal › Journal article › peer-review
Documents
- Wild meat consumption in tropical forests spares a significant carbon footprint from the livestock production sector
Final published version, 3.92 MB, PDF document
Whether sustainable or not, wild meat consumption is a reality for millions of tropical forest dwellers. Yet estimates of spared greenhouse gas (GHG) emissions from consuming wild meat, rather than protein from the livestock sector, have not been quantified. We show that a mean per capita wild meat consumption of 41.7 kg yr−1 for a population of ~ 150,000 residents at 49 Amazonian and Afrotropical forest sites can spare ~ 71 MtCO2-eq annually under a bovine beef substitution scenario, but only ~ 3 MtCO2-eq yr−1 if this demand is replaced by poultry. Wild meat offtake by these communities could generate US$3M or US$185K in carbon credit revenues under an optimistic scenario (full compliance with the Paris Agreement by 2030; based on a carbon price of US$50/tCO2-eq) and US$1M or US$77K under a conservative scenario (conservative carbon price of US$20.81/tCO2-eq), representing considerable incentives for forest conservation and potential revenues for local communities. However, the wild animal protein consumption of ~ 43% of all consumers in our sample was below the annual minimum per capita rate required to prevent human malnutrition. We argue that managing wild meat consumption can serve the interests of climate change mitigation efforts in REDD + accords through avoided GHG emissions from the livestock sector, but this requires wildlife management that can be defined as verifiably sustainable.
Original language | English |
---|---|
Article number | 19001 |
Journal | Scientific Reports |
Volume | 11 |
Number of pages | 11 |
ISSN | 2045-2322 |
DOIs | |
Publication status | Published - 2021 |
Bibliographical note
Publisher Copyright:
© 2021, The Author(s).
Number of downloads are based on statistics from Google Scholar and www.ku.dk
ID: 282035731