Are indigenous territories and community-managed areas effective natural climate solutions? A neotropical analysis using matching methods and geographic discontinuity designs.

Background and context:

Preventing deforestation and forest degradation are critical ways to help reduce climate change. However, how to manage lands to best preserve forests is an open question. Protected areas can vary widely in the restrictions put on forest use, from strict limits on human entry to “sustainable use/multiple use” areas that permit sustainable logging. In tropical regions of the Americas, indigenous territories and community managed protected areas tend to be more forested than other lands [1] [2], which suggests that allocating such regions could help prevent forest loss and reduce climate change.

However, indigenous territories and community managed protected areas are not distributed randomly, but tend to be positioned on steeper slopes than unprotected lands, at higher altitudes, and farther from roads and cities. These geographical differences could contribute to the increased forest cover of protected regions, making it hard to tell whether an area’s designation as an indigenous territory or community managed protected area helps protect forests. To overcome this issue, prior researchers have used “matching analysis” to compare protected and unprotected lands with similar geographic features [3] [4].

While previous research has investigated the impact of indigenous territories and other types of protected lands on deforestation, here the authors measured the effect such lands have on total carbon stocks, which is a more comprehensive measure that also captures forest degradation. They also determine how the distance to the border of a protected area affects a region’s ability to protect carbon stocks, with the goal of addressing a serious spatial bias that is inherent to matching analysis.

Key findings:

1. Indigenous territories and other protected areas retain increased carbon stocks, compared to geographically matched unprotected areas

To analyze the carbon stocks of different regions, the researchers used previously produced carbon density maps [5], which were made by combining satellite images with field measurements of carbon stocks. These maps show changes caused by forest degradation as well as deforestation.

To find the impact of protected areas on carbon stocks, independent of other geographical features, the researchers performed matching analysis. To be included in the analysis, a protected region had to have approximately the same distance to roads, rivers, and large settlements, as well as the same elevation and slope, as an unprotected region. Similarly, unprotected regions were only included if they had about the same geographic values as a protected region. In other words, only regions that were sufficiently geographically similar were compared.

In all countries studied (Panama, Colombia, Ecuador, Peru, and Brazil), indigenous territories and other protected areas contained increased carbon stocks, compared to geographically similar unprotected lands. The size of this effect varied between countries, but in most countries, indigenous territories had protective effects comparable to other protected areas, ranging from about 3% to 10% more carbon stocks than unprotected lands in 2016. In Panama, where carbon stocks are much lower overall, the protective effects of indigenous territories and other protected areas were much greater (33% and 91% more carbon stocks than matched unprotected lands, respectively.) 

2. Community-managed protected areas outperform other kinds of protected areas in positive effects on carbon stocks

In Petén, Guatemala and Acre, Brazil, the researchers compared the effects of community managed protected areas, in which local communities share governance of a region, with other kinds of protected areas. Perhaps surprisingly, community managed protected areas had a greater protective effect on carbon stocks than “integral protected areas”, like national forests, which have stricter regulations on land use. Community managed areas also outperformed sustainable use protected areas in both regions studied.

3. The positive impact of protected areas increases with distance from the border

Matching analysis helps detect the impact of protected areas, but the matching process introduces spatial bias. Regions on either side of the border of a protected area tend to be geographically similar to each other, making border regions more likely to be included in the analysis. Indeed, when the researchers mapped all regions included in matching analysis, they clustered at borders, with few regions in the cores of protected areas.

To better understand how border regions affected analysis, the researchers investigated how distance from the boundary impacts the carbon-protecting effect of protected lands. They measured carbon stocks at various distances from boundaries, from 1km to 15km, again comparing protected regions to geographically similar unprotected regions. Increasing distance away from the boundary, toward the core of protected areas, was associated with modestly higher carbon stocks in all countries studied. This suggests that the centers of protected areas, which are underrepresented by matching analysis, may have a greater positive impact on carbon stocks than was detected.

Why I liked this preprint:

This research challenged one of my intuitive assumptions: that the strictest land-use regulations are the best solution to protect the environment. The finding that other types of land tenure, like community-managed protected areas and indigenous territories, do an equal or better job of protecting carbon stocks, was surprising to me. It was also profoundly hopeful; it suggests, for instance, that indigenous knowledge about land management can help humans use and inhabit forests sustainably.

I also appreciate that this preprint demonstrates and addresses a serious bias in a common method of analysis. Matching analysis is a powerful tool to sort out the influence of unwanted geographic variables, and I like that the authors took advantage of its strengths while clearly showing the spatial bias it introduces. Although the geographical differences in the centers of protected areas make them difficult to study, focusing on distance to the boundary in border-adjacent regions allowed the authors to make the reasonable claim that protective effects are stronger closer to protected areas’ cores.

Image source: Neil Palmer (CIAT). Aerial view of the Amazon Rainforest, taken April 2011. License available here.

Questions for the authors:

1. Did you look into whether your geographical covariates impacted which kinds of PAs are most effective? For instance, one might imagine that greater accessibility of a region could lead to more active community management.
2. You emphasize that, since regions on either side of a PA boundary tend to be very geographically similar, that boundary regions are overrepresented by matching analysis, as compared to core regions of protected areas. Regions of unprotected areas that are far from PA boundaries are also underrepresented – does this influence your analysis in a meaningful way?
3. You make a compelling argument that indigenous territories and local communities should be compensated by the Green Climate Fund for their positive environmental contributions. To your knowledge, is any climate-related funding being directed towards these communities, or has there been in the past?

References:

1. Walker WS, Gorelik SR, Baccini A, Aragon-Osejo JL, Josse C, Meyer C, et al. The role of forest conversion, degradation, and disturbance in the carbon dynamics of Amazon indigenous territories and protected areas. (2020). Proc Natl Acad Sci. 117(6):3015–25. http://www.pnas.org/lookup/doi/10.1073/pnas.1913321117
2. Hodgdon BD, Hayward J, Samayoa O. Putting the plus first: Community forest enterprise as the platform for REDD+ in the Maya biosphere reserve, Guatemala. (2013). Trop Conserv Sci 6(3):365–83. https://doi.org/10.1177/194008291300600305
3. Nolte C, Agrawal A, Silvius KM, Britaldo SSF. Governance regime and location influence avoided deforestation success of protected areas in the Brazilian Amazon. Proc Natl Acad Sci U S A. 2013;110(13):4956–61.
4. Vergara-Asenjo G, Potvin C. Forest protection and tenure status: THE key role of indigenous peoples and protected areas in Panama. (2018). Glob Environ Chang. 28(1):205–15. https://doi.org/10.1016/j.gloenvcha.2014.07.002
5. Baccini A, Goetz SJ, Walker WS, Laporte NT, Sun M, Sulla-Menashe D, et al. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. (2012). Nat Clim Chang [Internet]. 2(3):182–5. http://dx.doi.org/10.1038/nclimate1354

Tags: climate change, deforestation, ecology, indigenous lands, matching analysis

doi: https://doi.org/10.1242/prelights.26925

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