Reducing natural vegetation loss in Amazonia critically depends on the formal recognition of indigenous lands

The Brazilian Amazon contains the world's largest tract of tropical forest, about 22 % of which is within demarcated indigenous territories. Formal governmental recognition of these traditional territories is often a critical deterrent to deforestation, but the relative conservation performance of Indigenous Lands (ILs) under different legal categories and geographic contexts remains poorly understood. We used 30-m resolution Landsat satellite imagery to quantitatively assess the land cover status and annual rates of natural vegetation loss between 1985 and 2020 for 381 indigenous territories amounting to ~115 million hectares. Using a comprehensive set of environmental and socio-economic covariates and a mixed-modelling approach, we found that all stages of formal IL recognition consistently inhibit natural vegetation loss throughout the Brazilian Amazon compared to adjacent unprotected areas. Formal physical demarcation and distance from roads were the main proximate drivers of avoided natural vegetation loss inside ILs. Forest loss associated with road access is substantially curbed by ILs, showing the importance of frontier expansion when assessing indigenous reserve performance in counteracting natural vegetation loss. Because loss of natural forest and savannah areas associated with agribusiness frontiers and infrastructure projects are likely to intensify, the importance of ecosystem services provided by ILs is expected to increase across the Brazilian Amazon. Cultural profile and human density exerted no impacts on IL effectiveness in precluding natural vegetation loss. Given widespread encroachment of timber extraction and agribusiness, formal recognition of indigenous territories is a critical factor in decelerating primary habitat conversion across the Amazon

Reconstructing 34 Years of Fire History in the Wet, Subtropical Vegetation of Hong Kong Using Landsat

Peer reviewed: TrueFunder: Bill & Melinda Gates FoundationBurn-area products from remote sensing provide the backbone for research in fire ecology, management, and modelling. Landsat imagery could be used to create an accurate burn-area map time series at ecologically relevant spatial resolutions. However, the low temporal resolution of Landsat has limited its development in wet tropical and subtropical regions due to high cloud cover and rapid burn-area revegetation. Here, we describe a 34-year Landsat-based burn-area product for wet, subtropical Hong Kong. We overcame technical obstacles by adopting a new LTS fire burn-area detection pipeline that (1) Automatically uniformized Landsat scenes by weighted histogram matching; (2) Estimated pixel resemblance to burn areas based on a random forest model trained on the number of days between the fire event and the date of burn-area detection; (3) Iteratively merged features created by thresholding burn-area resemblance to generate burn-area polygons with detection dates; and (4) Estimated the burn severity of burn-area pixels using a time-series compatible approach. When validated with government fire records, we found that the LTS fire product carried a low area of omission (11%) compared with existing burn-area products, such as GABAM (49%), MCD64A1 (72%), and FireCCI51 (96%) while effectively controlling commission errors. Temporally, the LTS fire pipeline dated 76.9% of burn-area polygons within two months of the actual fire event. The product represents the first Landsat-based burn-area product in wet tropical and subtropical Asia that covers the entire time series. We believe that burn-area products generated from algorithms like LTS fire will effectively bridge the gap between remote sensing and field-based studies on wet tropical and subtropical fire ecology.Gates Cambridge Trust (OPP1144

Reconstructing 34 Years of Fire History in the Wet, Subtropical Vegetation of Hong Kong Using Landsat

Burn-area products from remote sensing provide the backbone for research in fire ecology, management, and modelling. Landsat imagery could be used to create an accurate burn-area map time series at ecologically relevant spatial resolutions. However, the low temporal resolution of Landsat has limited its development in wet tropical and subtropical regions due to high cloud cover and rapid burn-area revegetation. Here, we describe a 34-year Landsat-based burn-area product for wet, subtropical Hong Kong. We overcame technical obstacles by adopting a new LTS fire burn-area detection pipeline that (1) Automatically uniformized Landsat scenes by weighted histogram matching; (2) Estimated pixel resemblance to burn areas based on a random forest model trained on the number of days between the fire event and the date of burn-area detection; (3) Iteratively merged features created by thresholding burn-area resemblance to generate burn-area polygons with detection dates; and (4) Estimated the burn severity of burn-area pixels using a time-series compatible approach. When validated with government fire records, we found that the LTS fire product carried a low area of omission (11%) compared with existing burn-area products, such as GABAM (49%), MCD64A1 (72%), and FireCCI51 (96%) while effectively controlling commission errors. Temporally, the LTS fire pipeline dated 76.9% of burn-area polygons within two months of the actual fire event. The product represents the first Landsat-based burn-area product in wet tropical and subtropical Asia that covers the entire time series. We believe that burn-area products generated from algorithms like LTS fire will effectively bridge the gap between remote sensing and field-based studies on wet tropical and subtropical fire ecology.Gates Cambridge Trust (OPP1144

A global evaluation of the effectiveness of voluntary REDD+ projects at reducing deforestation and degradation in the moist tropics.

Reducing emissions from deforestation and forest degradation (REDD+) projects aim to contribute to climate change mitigation by protecting and enhancing carbon stocks in tropical forests, but there have been no systematic global evaluations of their impact. We used a new data set for tropical humid forests and a standardized evaluation approach (based on pixel matching) to quantify the performance of a representative sample of 40 voluntary REDD+ projects in 9 countries certified under the Verified Carbon Standard (VCS). In the first 5 years of implementation, deforestation within project areas was reduced by 47% (95% confidence interval [CI]: 24-68) compared with matched counterfactual pixels, and degradation rates were 58% lower (95% CI: 49-63). Reductions were small in absolute terms but greater in sites located in high-deforestation settings and did not appear to be substantially undermined by leakage activities in forested areas within 10 km of project boundaries. At the 26th Conference of the Parties of the United Nations Framework Convention on Climate Change, the international community renewed its commitment to tackling tropical deforestation as a nature-based solution to climate change. Our results indicate that incentivizing forest conservation through voluntary site-based projects can slow tropical deforestation and highlight the particular importance of prioritizing financing for areas at greater risk of deforestation

Strong transparency required for carbon credit mechanisms

The credibility of carbon offset mechanisms is threatened by many issues related to their true effectiveness. We advocate that these issues cannot be effectively addressed without a dramatic improvement in transparency across the entire value chain of carbon offsetting, a crucial step for achieving a reduction in carbon emissions

Strong transparency required for carbon credit mechanisms

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordThe credibility of carbon offset mechanisms is threatened by many issues related to their true effectiveness. We advocate that these issues cannot be effectively addressed without a dramatic improvement in transparency across the entire value chain of carbon offsetting, a crucial step for achieving a reduction in carbon emissions.Natural Environment Research Council (NERC