How community forest management performs when REDD+ payments fail

The Reduced Emissions in Deforestation and Degradation (REDD+) initiative uses payments for ecosystem services as incentives for developing countries to manage and protect their forests. REDD+ initiatives also prioritize social (and environmental) co-benefits aimed at improving the livelihoods of communities that are dependent on forests. Despite the incorporation of co-benefits into REDD+ goals, carbon sequestration remains the primary metric for which countries can receive payments from REDD+, but after more than ten years of REDD+, many site-specific programs have failed to complete the carbon verification process. Here, we examine whether the REDD+ social co-benefits alone are sufficient to have slowed deforestation in the absence of carbon payments on Pemba, Tanzania. Using satellite imagery (Landsat archive), we quantified forest cover change for the period before (2001-2010) and after (2010-2018) the launch in 2010-11 of Pemba island’s REDD+ Readiness project. We then compared rates of forest cover change between shehia (administrative units) that were part of REDD+ Readiness intervention and those that were not, adjusting for confounding variables and the non-random selection of REDD+ shehia with a statistical matching procedure. Despite considerable variation in forest outcomes among shehia, the associated co-benefits with the Pemba REDD+ project had no discernible effect on forest cover change. Likewise, we did not detect an effect of socioecological covariates on forest cover change across all shehia, though island-wide human population growth since 2012 may have played a role. These findings are unsurprising given the failure to secure carbon payments on Pemba and indicate that co-benefits alone are insufficient to reduce deforestation. We conclude that better oversight of all-involved parties is needed to ensure that REDD+ interventions satisfactorily conclude the process of securing a mechanism for carbon payments, if slowing deforestation is to be achieved.

Data-Driven Forest Cover Change and Its Driving Factors Analysis in Africa

Forest cover plays an important role in sustaining ecological security to realize Sustainable Development Goals (SDGs). The research target area is composed of the African region which is experiencing unprecedented deforestation based on the data collection from 54 countries and regions between 2000 and 2020. Spatial autocorrelation analysis, global principal component analysis, and geographic detector model have been used as the core research tool. The temporal and spatial patterns of forest cover change in Africa and the driving effects of population growth, economic and trade, social development, arable land expansion, and other factors on forest cover change in different periods have been demonstrated. The findings are as follows: 1) extremely unequal distribution of Africa forest has caused forest area reduction in 20 years. The reduction quantity of forest has been illustrated from strong to weak: Central Africa (strongest), East Africa (higher strong), West Africa (medium), South Africa (higher weak), and North Africa (weakest). However, the forest reduction area in West Africa with the original ratio is the most significant. More than 80% of the forest area reduction in Africa has occurred in 14 countries, just five national forest areas to achieve the net growth, but the increase amount was only 1% of loss amount. 2) The spatial pattern of forest cover change in Africa contracted and clustered gradually, especially after 2012. Algeria was the hotspot cluster of Morocco and Tunisia, forming the increase area of forest cover in North Africa. Zambia, the coldest point, gathers Angola significantly, while the Democratic Republic of the Congo and Tanzania form a significantly reduced forest cover area. 3) Total population, land area, cultivated land, urban population, consumer price index, and birth rate are the main factors influencing the temporal evolution of forest cover change in Africa. It can be divided into four stages to interpret the different explanations and significance of each factor for forest cover change in the study area.

Understanding 34 Years of Forest Cover Dynamics across the Paraguayan Chaco: Characterizing Annual Changes and Forest Fragmentation Levels between 1987 and 2020

Over the past 40 years, Paraguay has lost the majority of its natural forest cover, thus becoming one of the countries with the highest deforestation rates in the world. The rapid expansion of the agricultural frontier, cattle ranching, and illegal logging between 1987 and 2012 resulted in the loss of 27% of original forest cover, equivalent to almost 44,000 km2. Within this context, the present research provides the first yearly analysis of forest cover change in the Paraguayan Chaco between the years 1987 and 2020. Remote sensing data obtained from Landsat images were applied to derive annual forest cover masks and deforestation rates over 34 years. Part of this study is a comprehensive assessment of the effectiveness of protected areas, as well as an analysis of the degree of fragmentation of the forest. All classification results obtained accuracies above 80% and revealed a total forest cover loss of approximately 64,700 km2. Forest clearing within protected areas was not frequent; however, some natural reserves presented losses of up to 25% of their forest cover. Through the consideration of several landscape metrics, this study reveals an onward fragmentation of forest cover, which endangers the natural habitat of numerous species.

Integrating Pixels, People, and Political Economy to Understand the Role of Armed Conflict and Geopolitics in Driving Deforestation: The Case of Myanmar

Armed conflict and geopolitics are a driving force of Land Use and Land Cover Change (LULCC), but with considerable variation in deforestation trends between broader and finer scales of analysis. Remotely-sensed annual deforestation rates from 1989 to 2018 are presented at the national and (sub-) regional scales for Kachin State in the north of Myanmar and in Kayin State and Tanintharyi Region in the southeast. We pair our multiscaled remote sensing analysis with our multisited political ecology approach where we conducted field-based interviews in study sites between 2018 and 2020. Our integrated analysis identified three common periods of deforestation spikes at the national and state/region level, but with some notable disparities between regions as well as across and within townships and village tracts. We found the rate and geography of deforestation were most influenced by the territorial jurisdictions of armed authorities, national political economic reforms and timber regulations, and proximity to national borders and their respective geopolitical relations. The absence or presence of ceasefires in the north and southeast did not solely explain deforestation patterns. Rather than consider ceasefire or war as a singular explanatory variable effecting forest cover change, we demonstrate the need to analyze armed conflict as a dynamic multisited and diffuse phenomenon, which is simultaneously integrated into broader political economy and geopolitical forces.