Potential of different governance mechanisms for achieving Global Biodiversity Framework goals

Author:

Negret Pablo Jose1,Rincon Victor2,Novoa Sidney3,Quispe Marvin3,Valdés-Velásquez Armando4,Forero-Medina German5,Amano Tatsuya6ORCID,Saravia Miguel7,Schleicher Judith8,Zaehringer Julie Gwendolin1

Affiliation:

1. Wyss Academy for Nature, Bern, Switzerland; Centre for Development and Environment, University of Bern, Switzerland; Institute of Geography, University of Bern, Switzerland

2. Instituto de Investigación de Recursos Biológicos Alexander Von Humboldt, Bogotá, Colombia

3. Asociación para la Conservación de la Cuenca Amazónica, Lima, Perú

4. Wyss Academy for Nature, Bern, Switzerland; Laboratorio de EcoSalud y Ecología Urbana, Universidad Peruana Cayetano Heredia, Peru

5. Wildlife Conservation Society, Cali, Colombia

6. The University of Queensland, School of The Environment, Queensland, Australia

7. Wyss Academy for Nature, Bern, Switzerland

8. Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Eschborn, Germany

Abstract

Abstract The Kunming-Montreal Global Biodiversity Framework includes a target of 30% of land protected by 2030 and refers to other effective area based conservation measures (OECMs) as complementary to PAs, but robust evaluations of the effectiveness of governance mechanisms that could act as OECMs in preventing forest loss and carbon emissions remain sparse. Here we assessed the impact of PAs and two potential OECMS: Indigenous Lands (ILs), and Non-Timber Forest products Concessions (NTCs) on forest loss and its associated carbon emissions in the Peruvian Amazon from 2000 to 2021. We also assessed two governance mechanisms with a commercial extractive use, Logging (LCs) and Mining Concessions (MCs). We used a robust before–after control intervention study design, with statistical matching, to account for the non-random spatial distribution of deforestation pressure and the governance mechanisms analysed. PAs were the most effective, having avoided 88% of the expected forest loss, followed by NTCs (64%) and ILs (44%). LCs also reduced expected forest loss by 29%, while MCs increased expected forest loss by 24%, showing that extractive governance mechanisms can have marked differences in their impact to forest cover. Our study provides evidence of long-term positive impacts of potential OECMs and other mechanisms at preventing forest loss and reducing carbon emission. This information is key to more effectively achieve targets from the Kunming-Montreal Global Biodiversity Framework and the UN Framework Convention on Climate Change.

Publisher

Research Square Platform LLC

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