Rates Of Forest Loss Research Articles

Small forest patches in West Africa: mapping how they are changing to better inform their conservation

Summary In West Africa, vast areas are being deforested; the remnant forest patches provide a wealth of ecosystem services and biodiversity conservation potential, yet they are threatened by human activity. Forest patches <100 ha have not been widely catalogued before; we mapped forest loss of small forest patches outside of protected areas in the Guinean savannah and humid Guineo-Congolian bioclimatic regions of Togo, Benin, Nigeria and Cameroon between 2000 and 2022. Focusing on the dynamics of small patches, without considering the splitting process of larger patches, we quantified changes in their number and area and the rate and trend of forest loss. Small forest patches are widespread, yet their area and number have decreased, while the forest loss rate is increasing. Primary forest patches lost almost half of their area annually – twice as much as secondary forests, and this loss was especially pronounced across small patches (0.5 – 10 ha), suggesting deforestation preferentially occurs in the smallest patches of primary forest. If forest loss continues at the current rate, 14% of the total forest area mapped in this study will have disappeared by 2032, jeopardizing their potential to provide ecosystem services and emphasizing the need for measures to counter their deforestation.

A Bayesian network approach to assess the ecosystem integrity of mangroves in Tampamachoco, Veracruz, Mexico

Given the alarming rates of mangrove forest loss, resource managers must count on information regarding the condition of the mangrove forests. We propose a Bayesian network (BN) to assess mangrove forests' ecosystem integrity (EI) to support a mangrove monitoring system in Mexico. This approach allowed us to infer the system's condition based on variables on forest structure and function. We defined the BN structure based on informal interviews with specialists on vegetation and coastal geomorphology. We applied the expectation-maximization learning algorithm to train the model. Data from plots in two mangrove areas of an Avicennia germinans forest, defined based on their undisturbed and disturbed conditions, were used as training datasets. We applied sensitivity analysis to determine the degree of influence of each model variable. We evaluated the prediction capacity of the BN with a k-fold cross-validation (the process is repeated five times, starting from the database in 2 parts). The variables selected for the model were the Holdridge complexity index (HCI, Holdridge et al., 1971), Leaf area index (LAI), litter production (g/month/m2), leaf C, N and P concentration (%), and leaf N:P ratio. The most critical variable to infer mangrove condition was leaf N:P (Variance reduction = 11%), followed by forest structure variables HCI and LAI (Variance reduction > 5%). The cross-validation to test the model resulted in a minimum square error of 0.3, which indicates a reasonable capacity to predict the condition of mangrove integrity. The BN constructed can diagnose the integrity of a monospecific mangrove forest with acceptable precision, considering the environmental factors that define the forest structure and functioning locally. We then asked the experts to review and modify the model to apply to multispecies mangrove ecosystems and environmental contexts.

Expanding forest carbon sinks to mitigate climate change in Africa

Forests significantly contribute to climate change mitigation by acting as carbon sinks, sequestering atmospheric carbon dioxide, and keeping it in soil and biomass. Covering 22 % of its land, African forests offer numerous benefits to millions of people. Nevertheless, they face threats from human activities like deforestation and degradation. A holistic approach encompassing social, economic, and environmental factors is necessary to sustain forests as carbon sinks for maximum carbon sequestration potential. This study used carbon dioxide emissions, forest loss and gain, and land use change to investigate the level of carbon dioxide emissions and their relationship to forest loss and climate change in Africa from 1992 to 2020. Using ArcGIS, land use change was reclassified, InVEST model calculated carbon storage and sequestration, and annual changes in forest cover were assessed using the K and S indices. In the last two decades, 77.36 % of African countries had greater forest losses than gains, leading to 32 × 103 kha net loss, resulting in 15.73 Pg C of carbon dioxide emissions. Annual forest loss rate is 1.6 × 103 kha, equivalent to 0.786 Pg C, and that of carbon storage and sequestration decreased to −0.69 and −1.37, respectively. Results indicate that deforestation, particularly in the Democratic Republic of the Congo, significantly contributes to carbon emissions, and persistent tropical deforestation will affect future greenhouse gas concentrations. This research provides a detailed spatiotemporal analysis, highlighting areas experiencing severe forest cover change and carbon loss, underscoring the importance of forest conservation in mitigating climate change, and promoting effective land management policies.

A holistic approach to assessing REDD+ forest loss baselines through ex post analysis

Abstract The implementation of REDD+ (Reducing Emissions from Deforestation and Forest Degradation) projects has become a key Nature Based Solutions (NBS) strategy to protect at-risk forests using the sale of verified emission reductions (carbon credits) as financing, generated by reducing forest loss against counterfactual baseline scenarios. Controversy over the reasonableness of such baseline scenarios has thrown this nascent market mechanism into disarray. While new technical approaches to baseline-setting that promise wider market acceptance are set to roll out in the coming years, existing projects are becoming unviable, as carbon credit buyers reduce investment due to lost confidence in the integrity of emissions reduction claims. Transparent, reproducible methods to assess existing REDD+ project baselines are needed in order to provide a clearer picture of the real impact of projects, and provide an objective basis on which investment decisions can be made today. Here we introduce such a method. .. In contrast to existing studies which utilize only one method to create a single “control,” we integrate actual forest loss rates from a variety of control sites to establish a “zone of reasonable accuracy (or ZORA)”. Application of our method in Cambodia, using two geospatial datasets (one global and one locally calibrated), shows that all three project baselines fall within or below ZORA. This approach is fully reproducible, and provides a transparent way for analysts to assess REDD+ baselines during this critical time when investment in forest protection must increase dramatically and without delay.

Frontier Constellations: A History of Land-use Regimes in Paraguay’s Pilcomayo River Basin

ABSTRACT The Paraguayan Chaco is increasingly known for the extreme rates of forest loss caused by the rapid expansion of cattle ranching and crop farming over the last few decades. Knowledge of its twentieth-century land-use history, however, remains limited. In this article, I address that gap by discussing land-use dynamics since the 1900s in the Pilcomayo River basin, a part of the Chaco that borders Argentina and Bolivia, and hosts a great diversity of actors and land uses. Using the concept of land-use regimes, I show that the area, once characterized by what can be called an Indigenous mixed-use regime, transitioned to a land-use regime dominated by livestock herding by Argentine Criollo settlers after the Chaco War (1932–35), and then again to one of large cattle ranches managed by absentee owners toward the end of the twentieth century. No land-use regime ever completely dominated the area, however, and I use this fact as a starting point to then discuss how using the concept of land regimes can help direct attention to the coexistence of regimes in space and to their relationships in a way that helps refine our understanding of land-use transitions.

Characteristics and Driving Mechanisms of Understory Vegetation Diversity Patterns in Central and Southern China

Large-scale forest restoration projects significantly reduce the net rates of forest loss. However, as a key component of forest restoration, planted forests have failed to restore biodiversity. China has implemented a large-scale afforestation program, which includes pure planted forests in particular, leading to various changes in ecosystem processes. Despite this, a comprehensive analysis of understory vegetation diversity patterns in these pure planted forests is still lacking. This study aimed to analyze the data on understory vegetation diversity from three typical pure and natural forest ecosystems of Hunan ecological forests to reveal their diversity patterns. The results revealed no significant difference in the understory diversity index between natural and pure forest types, although natural forests had a bigger species pool. The Zipf–Mandelbrot model was a better fit for species abundance distribution. The fitted results suggested that both environmental filtering and neutral processes affected the species abundance distribution and pure understory communities during restoration succession. Natural forests had the most stable understory diversity structure, whereas pure Phyllostachys heterocycla (Carr.) Mitford forests had the least stable structure. Multivariate regression tree analysis identified indicator species for each community. The gradient boosting model indicated that isothermality and slope direction were the most important factors affecting diversity. The β-diversity analysis showed that community establishment in the four forest types was affected via different mechanisms. The findings of this study have significant implications for understanding the impact of afforestation on the mechanisms for maintaining diversity.

Detection of forest disturbance across California using deep-learning on PlanetScope imagery

California forests have recently experienced record breaking wildfires and tree mortality from droughts, However, there is inadequate monitoring, and limited data to inform policies and management strategies across the state. Although forest surveys and satellite observations of forest cover changes exist at medium to coarse resolutions (30–500 m) annually, they remain less effective in mapping small disturbances of forest patches (<5 m) occurring multiple times a year. We introduce a novel method of tracking California forest cover using a supervised U-Net deep learning architecture and PlanetScope’s Visual dataset which provides 3-band RGB (Red, Green, and Blue) mosaicked imagery. We created labels of forest and non-forest to train the U-Net model to map tree cover based on a semi-unsupervised classification method. We then detected changes of tree cover and disturbance with the U-Net model, achieving an overall accuracy of 98.97% over training data set, and 95.5% over an independent validation dataset, obtaining a precision of 82%, and a recall of 74%. With the predicted tree cover mask, we created wall to wall monthly tree cover maps over California at 4.77 m resolution for 2020, 2021, and 2022. These maps were then aggregated in a post-processing step to develop annual maps of disturbance, while accounting for the time of disturbance and other confounding factors such as topography, phenological and snow cover variability. We compared our high-resolution disturbance maps with wildfire GIS survey data from CALFIRE, and satellite-based forest cover changes and achieved an F-1 score of 54% and 88% respectively. The results suggest that high-resolution maps capture variability of forest disturbance and fire that wildfire surveys and medium resolution satellite products cannot. From 2020 to 2021, California maintained 30,923.5 sq km of forest while 5,994.9 sq km were disturbed. The highest observed forest loss rate was located at the Sierra Nevada mountains at 21.4% of the forested area being disturbed between 2020 and 2021. Our findings highlight the strong potential of deep learning and high-resolution RGB optical imagery for mapping complex forest ecosystems and their changes across California, as well as the application of these techniques on a national to global scale.

Long-term riparian forest loss around streams, lakes, and wetlands in ecologically diverse managed and unmanaged landscapes

Riparian forests are at risk from the cumulative effects of human and natural disturbance. We assessed the magnitude and rate of forest loss adjacent to freshwater features in the province of British Columbia, Canada, from 2000 to 2021. We used Global Forest Change data to quantify percent tree cover lost annually across six ecologically and topographically diverse ecosections containing 361,370 streams, lakes, and wetlands. We stratified the aquatic features into large and small size classes within and outside parks. We hypothesized that cumulative forest loss would be greater outside of parks as a consequence of human-caused and natural disturbance. Also, we hypothesized greater rates of forest loss around small aquatic features that generally receive less protection outside of parks. Loss of riparian forest was consistently greater outside of parks (median losses of 3.20% versus 1.29%), and adjacent to small streams (median = 3.31%) and wetlands regardless of size (median = 3.10%). Rates of cumulative riparian forest loss were nonlinear, increasing substantially in 2013. Though the annual riparian forest losses were small, the cumulative losses from 2000 to 2021 were substantial. We anticipate the continued loss of riparian forest as climate changes and natural disturbances intensify. We recommend further investigation of the implications of these observed trends for ecosystem values that are found within or adjacent to riparian forest across managed and unmanaged landscapes.

Insight into the imbalance of forest cover change at county level in mainland China during 2000–2020: From the perspective of subdividing forest cover change into forest gain and loss

The significant growth of China's forest resources presents a remarkable case in global vegetation dynamics. However, there is spatial imbalance in forest cover changes, which is not only reflected in regional imbalances, but also between total and net changes. There is still a lack of knowledge in this imbalance. In our comprehensive study, we subdivided forest cover change into forest gain and loss, and calculated the total and net forest change across 2850 county-level administrative units in mainland China, utilizing the Global Forest Change Dataset. The univariate linear regression and the Sen + Mann-Kendall test is utilized to explore the temporal trends in forest loss. Additionally, spatial autocorrelation models were employed to examine the spatial differentiation of forest cover change. Our findings unveiled a wide spectrum of forest loss rates ranging from 0% to 27%, and gain rates ranging from 0% to 10%, with the highest rates observed in the southern counties. We observed that the forest loss trends in southeastern counties showed significant and slight increases, while the northwestern counties experienced significant and slight decreases, with the Huhuanyong Line serving as the demarcation. In terms of spatial patterning, quite a number of the southern counties displayed a “large net change, large total change” state, which contrasted with diverse patterns observed in certain western regions. Spatial autocorrelation analysis showed that the High-high clusters of both forest gain and loss were primarily observed in southern counties, with the Low-low clusters in the northwest. This detailed analysis provides valuable insights into the dynamics of forest cover changes, offering a robust scientific foundation for developing informed and region-specific conservation policies.

Two decades of accelerated deforestation in Peruvian forests: a national and regional analysis (2000–2020)

The global tree cover has kept reducing in the last two decades, mainly in tropical forests, despite the global efforts to conserve biodiversity and the ecosystem services that provides. Considering South America is the region that had the highest rate of net forest loss (2000–2020), it is crucial to understand the deforestation dynamics of each country and their regions for the evaluation of effective national conservation actions. Here, we carried out a spatiotemporal analysis of the deforestation rates from 2000 to 2020 on a national and regional scale, including the forest loss inside protected areas, in Peru. It was found that Peru lost 3.4 million ha of forest between 2000 and 2020, mainly in the Not Flooded Rainforest region. National deforestation rates accelerated, while within protected areas rates showed a very small increase. Regional deforestation rates followed the national pattern with one exception—the Coast region. Our results evidence the success of the national conservation strategy based on protected areas to avoid deforestation in all regions, except in the Andean. Moreover, the increment in deforestation rates is aligned with the growth in road infrastructure; increments in anthropic activities; and the more frequent and intense natural extreme events that vary according to the region. Therefore, it is urgent to differentiate the drivers of deforestation that operate at the national versus the regional scale, consider the inclusion of all forest types in the monitoring system, and the strengthening of policies related to land use change at all scales.

Overlapping extractive land use rights increases deforestation and forest degradation in managed natural production forests

Guyana manages an estimated 5.3 million hectares of old-growth tropical forests, 29% of its total forest area, for timber extraction. Individuals and companies can apply for time-limited leases that allocate access, management, and extraction rights for timber through a concession system. In many tropical regions, including Guyana, a lack of integrated land use planning often leads to overlapping extractive and forest use rights for logging and mining. Overlapping land rights in turn create uncertainty and limit investments toward sustainable forest management, affecting deforestation and forest degradation rates. In this study, we use matched fixed-effect and difference-in-differences panel data models to quantify the impact of establishing logging tenure on deforestation and forest degradation. We assess the impact of different tenure use allocations for Guyana, a high forest cover low deforestation country, utilizing a 31-year (1990–2020) remotely sensed annual time series dataset on deforestation and forest degradation. The rate of forest loss (deforestation plus degradation) in public forests managed by the State with no authorized use allocation activities were 0.062% per year. The issuance of timber concessions increases the probability of deforestation by 33.5% and forest degradation by 8.9% compared to unallocated state forests. Forests with overlapping use rights for timber and mining had a 156% and 19.1% higher probability of deforestation and degradation relative to unallocated public forests and forests where only timber harvesting was authorized, respectively. We conclude that overlapping land use allocations result in conflicting resource use strategies that ultimately will limit sustainability and climate goals related to reducing deforestation and degradation.

Inviting oversight: Effects of forest certification on deforestation in the Brazilian Amazon

In the American tropics, logging is almost always highly selective, leaving most of the forest standing and available for future harvest under sustainable forest management. However, forest that has been logged is often more accessible to deforestation agents such as farmers. Thus, areas legally designated for sustainable forest management in reality may be more susceptible to illegal deforestation. Third-party certification of sustainable forest management is one strategy for protecting such forest. In this paper, we estimate the effect of certification by the Forest Stewardship Council (FSC) on deforestation, drawing on data from the years 2001 to 2019. We observe strong selection effects resulting in systematic differences between certified forest areas and other forest areas designated for sustainable forest management, and we find that after controlling for those selection effects, inviting oversight by FSC reduces the probability of deforestation. Our study design compares forests “treated” with FSC certification to “control” forests designated for sustainable forest management but not (yet) certified in the two Brazilian states of Pará and Rondônia. Adopting pixel-based analyses, we first create a matched sample of treated and control pixels and then estimate GLMM models, with two-way fixed effects (TWFE) models as a robustness check.We find that where forest managers have obtained certification and thus invited oversight by FSC auditors, rates of forest loss are lower (although the results are not fully robust across regions). The estimated effects vary across regions, likely due to varying socioeconomic and policy contexts and competing land uses. We conclude that especially in settings of low governance capacity and high deforestation pressure, certification can contribute to long-term forest conservation by reducing deforestation rates.

Using payment for ecosystem services to meet national reforestation commitments: impacts of 20+ years of forestry incentives in Guatemala

International environmental initiatives, such as the Bonn Challenge and the UN Decade on Restoration, have prompted countries to put the management and restoration of forest landscapes at the center of their land use and climate policies. To support these goals, many governments are promoting forest landscape restoration and management through financial forestry incentives, a form of payment for ecosystem services. Since 1996, Guatemala has implemented a series of forestry incentives that promote active forest landscape restoration and management on private and communal lands. These programs have been widely hailed as a success with nearly 600 000 ha enrolled since 1998. However, there has been no systematic assessment of the effectiveness of these programs on preserving and restoring Guatemalan forests. This study evaluates the impacts of over 16 000 individual PES projects funded through two incentive programs using a synthetic control counterfactual. Overall, a program for smallholders resulted in lower rates of forest loss, while a program for industrial timber owners led to greater gains in forest cover. Across policies, we found dramatically higher forest cover increases from restoration projects (15% forest cover increase) compared to plantation and agroforestry projects (3%–6% increase in forest cover). Projects that protected natural forest also showed a 6% reduction in forest loss. We found forest cover increases to be under 10% of total enrolled area, although positive local spillovers suggest this is an underestimate. Restoration projects show the most promise at promoting forest landscape restoration, but these benefits need to be weighed against priorities like resilience and rural development, which may be better served by other projects.

Planning for megafauna recovery in the tropical rainforests of Sumatra

Human-induced forest loss has had devastating impacts on biodiversity. Mammal populations in the tropics have been hit particularly hard by the resulting habitat loss, fragmentation and degradation, as well as by overhunting which often goes hand-in-hand. While declines in these populations are generally well documented, few studies offer a pathway for their recovery. Here, we test the association between changes in forest habitat and occupancy trends of Sumatran megafauna (elephant and tiger) and key tiger prey species (wild boar and sambar) in the Leuser Ecosystem: a large forest landscape on the Indonesian island of Sumatra. For elephant and tiger, we develop additional occupancy models to predict their respective spatial distribution under different scenarios of forest loss and gain (through restoration and increased connectivity) to provide a blueprint for avoiding future species loss and assisting with their population recovery. From 2000 to 2019, 254,722 ha (6.7%) of natural forest was converted, primarily to plantations and shrubs. The species-specific responses over the study period revealed that the occurrence of elephant declined along the west, with a range shift to the northeast of Leuser, whereas wild boar underwent a dramatic widespread decline and although sambar experienced losses around the forest edge, it remained widespread in the interior forest, while tiger occupancy remained stable. Modelling habitat loss and fragmentation led to an unsurprising demise of Sumatran megafauna, whereas strategic investments that reconnected several forest patches provided disproportionately large benefits for their recovery through the recolonization of former parts of their range. Indonesia has achieved six consecutive years of declining forest loss rates, and our study’s findings can build off this conservation success by supporting improved provincial spatial planning and field-based restoration efforts that avoid declines of threatened megafauna species and act as a catalyst for rewilding a landscape of global importance.

Spatial analysis of deforestation in Indonesia in the period 1950–2017 and the role of protected areas

AbstractIndonesia is one of the countries with highest forest loss rates in the world. Protected areas (PAs) can have a key role in counteracting deforestation, especially if they are combined with the active involvement of local communities, rather than be only based on strict nature conservation. The study aims at assessing and measuring forest transformations in 1950–2017 through GIS-based spatial analyses, and to evaluate the role of PAs in preserving forests from deforestation. At national level forests dramatically decreased, passing from 78.3% of the total surface in 1950, to 63.8% in 1982 and to 46.8% in 2017. In the period 1950–2017, 35% of the national territory (over 66 million of hectares) has been affected by deforestation at an average rate of 985,200 ha/year; the areas where deforestation proceeded at higher rates are Sumatra (356,100 ha/year) and Kalimantan (303,360 ha/year). Deforestation occurred with higher intensity at lower altitudes and along the coast, due to the spread of modern plantations. The only exception is represented by Java and Bali as most of deforestation already occurred before 1950. PAs demonstrated to be effective in slowing down deforestation rates, but not in stopping it as deforestation is also affecting PAs. The study provided reliable spatial data on forest transformations in the last 67 years, highlighting differences related to geographical zone and altimetry, allowing the identification of the most vulnerable PAs. The amount of data produced at national and regional level could support further studies aimed at recognizing the best strategies to counteract deforestation, contributing to sustainable forests management and to forest preservation.

Abundance and activity patterns of the endangered margay (Leopardus wiedii) in temperate forest remnants from the avocado landscape in Mexico

Abstract A survey was done to estimate margay abundance and activity in the context of high forest loss rates from avocado plantations for the temperate forest region of Michoacán state. Camera trap surveys were conducted from November 2015 to April 2020, recording 21 Margay detections of seven individuals. The capture rate ranged from 0.09 to 0.83 records/100 trap nights. The mean temporal density was 0.12 ind./km2, with an activity peak between 04:00 and 05:00 h. The Margay could serve as indicator species for restoration and forest conservation initiatives.

Land use change and forest patch analysis as a decision‐making tool to sustainably develop plantation agriculture and optimize biodiversity conservation

AbstractEstablished for biodiversity conservation, protected areas (PAs) have been downsized, downgraded, and/or degazetted for socioeconomic development including plantation agriculture. Although studies have highlighted causes, implications for biodiversity conservation, and the need for policies governing Protected Area Downsizing, Downgrading, and Degazettement (PADDD), no study has proposed a methodology to inform PADDD events to help decision making that balance economic growth pursuit with ecological and environmental commitments. A methodology based on land use change and forest patch analysis has been applied to Buvuma Island to guide the choice of PAs that can undergo PADDD as well as identification of new areas that can be declared as PAs. Our results revealed that, over the last decade, natural vegetation of Buvuma Island has been highly degraded with forest depletion from 45.0% in 2007 to 15.8% in 2016. About 65% of the initial forest cover were lost. The average yearly forest loss rate was 3.2% or 712.8 ha. A total number of 19 PAs covering 3103 ha including 2816 ha of existing PAs and 287 ha of identified forest patches were selected for biodiversity conservation. This flexible methodology can be applied at various spatial and temporal scale to ensure sustainable plantation agriculture development.

Orthophosphate fluxes in scattered trees from fragmented Andean landscapes highlight a biogeochemical role of foliar traits in pioneer species

AbstractHighly diverse neotropical ecosystems exhibit a natural limitation of phosphorus in the soil, sufficient to limit productivity and structure. This is more pronounced in Andean ecosystems, with high forest fragmentation and forest loss rates aggravating the effect. Previous studies have highlighted the importance of precipitation and its interaction with the canopy on nutrient inputs into forests. However, few studies have quantified the potential effects of structural and morphological tree diversity on the dynamics of phosphorous inputs on these ecosystems. In this study, we determined the association between 12 morphological plant functional traits and the movement of water‐driven orthophosphate from the canopy into the soil in 20 individuals of five tree species, on single individuals scattered across a human‐disturbed montane landscape in the Colombian Andes: Croton magdalenensis, Andesanthus lepidotus, Vismia baccifera and Quercus humboldtii and a commonly planted exotic species Eucalyptus globulus. We quantified PO4‐P concentrations in precipitation, throughfall and stemflow in all trees for 14 isolated rainfall events. In general, our results show a general enrichment of PO4‐P concentration in the net precipitation after passing through tree canopies. One particular species, C. magdalenensis, an ecological pioneer, had notably higher values of PO4‐P concentration. This condition relates, potentially, to a particularly higher epiphyte load, high leaf area and high trichome density. This condition potentially facilitates biogeochemical exchange and improves ecological functions associated with early stages of forest recovery (where pioneer species dominate forest composition). Our results are particularly relevant given that the highest contributions of PO4‐P to the soil occur in native species, which become key structures in the recovery of fragmented Andean ecosystems.

Avifauna recovers faster in areas less accessible to trapping in regenerating tropical forests

Tropical forest restoration stands to deliver important conservation gains, particularly in lowland Southeast Asia, which has suffered some of the world's highest rates of recent forest loss and degradation. This promise, however, depends on the extent to which biodiversity at forest restoration sites continues to be exposed to threats. A key knowledge gap concerns the extent to which biodiversity recovery in naturally regenerating tropical forests is impacted by trapping for the multi-million-dollar wildlife trade. Here, we use a repeated survey dataset to quantify rates of avian community recovery under forest regeneration, at a flagship restoration site in the lowland rainforests of Sumatra, Indonesia. We show that over a decade, forest regeneration was associated with significant abundance increases for 43.8 % of bird species. However, the apparent negative impacts of trade-driven trapping on avian populations also intensified: the proportion of species dependent on very remote forests increased from 5.4 % to 16.2 %. Moreover, the overall accessibility of the forest increased. We found that 14 % of species did not recover as fast as predicted based on the observed forest regeneration over the study period. We found trapping to disproportionately impact species targeted for trade: compared to opportunistically trapped species, twice more species showed increased abundance only in very remote forests. Our results highlight the potential for rapid avifaunal recovery in regenerating tropical forests, but also emphasize the urgency of tackling the serious threat of wildlife trade to Southeast Asia's biodiversity.

Forest conservation in Indigenous territories and protected areas in the Brazilian Amazon

Conflicts between forest conservation and socio-economic development in the Brazilian Legal Amazon (BLA) have persisted for years but the effects of Indigenous territory (ITs) and protected area (PAs) status on deforestation there remain unclear. To address this issue, we analysed time-series satellite images and qualified annual forest area in the BLA under different governance and management regimes. Between 2000 and 2021, areas classified as ITs or PAs increased to cover 52% of forested areas in the BLA while accounting for only 5% of net forest loss and 12% of gross forest loss. In the years (2003–2021) after establishment, gross forest loss fell 48% in PAs subject to ‘strict protection’ and 11% in PAs subject to ‘sustainable use’. However, from 2018 to 2021 the percentage rate of annual gross forest loss in ITs/PAs was twice that of non-designated areas. Our findings reveal the vital role of, and substantial progress achieved by, ITs and PAs in Amazonian forest conservation as well as the dangers of recent weakening of Brazil’s forest policies. The Brazilian Legal Amazon (BLA) has Earth’s largest tropical rainforest and a history of tension around its fate. Between 2001 and 2018, this study finds that Indigenous territories and protected areas in the BLA have expanded and reduced deforestation markedly, with some gains eroded in recent areas.