Benchmark maps of 33 years of secondary forest age for Brazil

Mapping of secondary forest age in China using stacked generalization and Landsat time series

A national distribution of secondary forest age (SFA) is essential for understanding the forest ecosystem and carbon stock in China. While past studies have mainly used various change detection algorithms to detect forest disturbance, which cannot adequately characterize the entire forest landscape. This study developed a data-driven approach for improving performances of the Vegetation Change Tracker (VCT) and Continuous Change Detection and Classification (CCDC) algorithms for detecting the establishment of forest stands. An ensemble method for mapping national-scale SFA by determining the establishment time of secondary forest stands using change detection algorithms and dense Landsat time series was proposed. A dataset of national secondary forest age for China (SFAC) for 1 to 34 and with a 30-m spatial resolution was produced from the optimal ensemble model. This dataset provides national, continuous spatial SFA information and can improve understanding of secondary forests and the estimation of forest carbon storage in China.

Coupling remote sensing and eDNA to monitor environmental impact: A pilot to quantify the environmental benefits of sustainable agriculture in the Brazilian Amazon

Monitoring is essential to ensure that environmental goals are being achieved, including those of sustainable agriculture. Growing interest in environmental monitoring provides an opportunity to improve monitoring practices. Approaches that directly monitor land cover change and biodiversity annually by coupling the wall-to-wall coverage from remote sensing and the site-specific community composition from environmental DNA (eDNA) can provide timely, relevant results for parties interested in the success of sustainable agricultural practices. To ensure that the measured impacts are due to the environmental projects and not exogenous factors, sites where projects have been implemented should be benchmarked against counterfactuals (no project) and control (natural habitat) sites. Results can then be used to calculate diverse sets of indicators customized to monitor different projects. Here, we report on our experience developing and applying one such approach to assess the impact of shaded cocoa projects implemented by the Instituto de Manejo e Certificação Florestal e Agrícola (IMAFLORA) near São Félix do Xingu, in Pará, Brazil. We used the Continuous Degradation Detection (CODED) and LandTrendr algorithms to create a remote sensing-based assessment of forest disturbance and regeneration, estimate carbon sequestration, and changes in essential habitats. We coupled these remote sensing methods with eDNA analyses using arthropod-targeted primers by collecting soil samples from intervention and counterfactual pasture field sites and a control secondary forest. We used a custom set of indicators from the pilot application of a coupled monitoring framework called TerraBio. Our results suggest that, due to IMAFLORA's shaded cocoa projects, over 400 acres were restored in the intervention area and the community composition of arthropods in shaded cocoa is closer to second-growth forests than that of pastures. In reviewing the coupled approach, we found multiple aspects worked well, and we conclude by presenting multiple lessons learned.

Collective property rights lead to secondary forest growth in the Brazilian Amazon

Forests serve a crucial role in our fight against climate change. Secondary forests provide important potential for conservation of biodiversity and climate change mitigation. In this paper, we explore whether collective property rights in the form of indigenous territories (ITs) lead to higher rates of secondary forest growth in previously deforested areas. We exploit the timing of granting of property rights, the geographic boundaries of ITs and two different methods, regression discontinuity design and difference-in-difference, to recover causal estimates. We find strong evidence that indigenous territories with secure tenure not only reduce deforestation inside their lands but also lead to higher secondary forest growth on previously deforested areas. After receiving full property rights, land inside ITs displayed higher secondary forest growth than land outside ITs, with an estimated effect of 5% using our main RDD specification, and 2.21% using our difference-in-difference research design. Furthermore, we estimate that the average age of secondary forests was 2.2 y older inside ITs with secure tenure using our main RDD specification, and 2.8 y older when using our difference-in-difference research design. Together, these findings provide evidence for the role that collective property rights can play in the push to restore forest ecosystems.

Potential cultivation areas of Euterpe edulis (Martius) for rainforest recovery, repopulation and açai production in Santa Catarina, Brazil

Euterpe edulis is an endangered palm species that provides the most important non-timber forest product exploited in its natural habitat, the Brazilian Atlantic Forest hotspot^1,4. From 1991 to 2017, pasturelands, agriculture, and monoculture of tree plantations were responsible for 97% of Atlantic Forest deforested areas in Brazil and Santa Catarina was one of the Brazilian states with the greatest loss of forest area¹⁴. In the last decade, E. edulis fruits reached their highest commercial value, producing the southeastern equivalent of Amazonian ''açai'' (Euterpe oleracea)^5,7,8. As a shade-tolerant species, E. edulis adapts very well to agroforestry systems^8,10. To evaluate potential areas for cultivation of E. edulis through agroforestry systems, we developed and applied a spatial model for mapping suitable areas. To accomplish this, we analyzed multisource biophysical data and E. edulis distribution data from the Forest Inventory of Santa Catarina. We identified two areas with potential occurrence of the species, one in the domains of coastal Dense Ombrophilous Forest where the species is more common and another in the domains of inland Deciduous Seasonal Forest where its occurrence was suspected, but not proven, until 2021. Today, Deciduous Seasonal Forest is the most fragmented and impacted by agriculture. Our model, together with confirmed areas of occurrence, indicates that deciduous seasonal forest region should be prioritized for production and recovery of E. edulis through agroforestry systems.

The carbon sink of secondary and degraded humid tropical forests

The globally important carbon sink of intact, old-growth tropical humid forests is declining because of climate change, deforestation and degradation from fire and logging^1-3. Recovering tropical secondary and degraded forests now cover about 10% of the tropical forest area⁴, but how much carbon they accumulate remains uncertain. Here we quantify the aboveground carbon (AGC) sink of recovering forests across three main continuous tropical humid regions: the Amazon, Borneo and Central Africa^5,6. On the basis of satellite data products^4,7, our analysis encompasses the heterogeneous spatial and temporal patterns of growth in degraded and secondary forests, influenced by key environmental and anthropogenic drivers. In the first 20 years of recovery, regrowth rates in Borneo were up to 45% and 58% higher than in Central Africa and the Amazon, respectively. This is due to variables such as temperature, water deficit and disturbance regimes. We find that regrowing degraded and secondary forests accumulated 107 Tg C year^-1 (90-130 Tg C year^-1) between 1984 and 2018, counterbalancing 26% (21-34%) of carbon emissions from humid tropical forest loss during the same period. Protecting old-growth forests is therefore a priority. Furthermore, we estimate that conserving recovering degraded and secondary forests can have a feasible future carbon sink potential of 53 Tg C year^-1 (44-62 Tg C year^-1) across the main tropical regions studied.

Biases and limitations of Global Forest Change and author-generated land cover maps in detecting deforestation in the Amazon

Studying land use change in protected areas (PAs) located in tropical forests is a major conservation priority due to high conservation value (e.g., species richness and carbon storage) here, coupled with generally high deforestation rates. Land use change researchers use a variety of land cover products to track deforestation trends, including maps they produce themselves and readily available products, such as the Global Forest Change (GFC) dataset. However, all land cover maps should be critically assessed for limitations and biases to accurately communicate and interpret results. In this study, we assess deforestation in PA complexes located in agricultural frontiers in the Amazon Basin. We studied three specific sites: Amboró and Carrasco National Parks in Bolivia, Jamanxim National Forest in Brazil, and Tambopata National Reserve and Bahuaja-Sonene National Park in Peru. Within and in 20km buffer areas around each complex, we generated land cover maps using composites of Landsat imagery and supervised classification, and compared deforestation trends to data from the GFC dataset. We then performed a dissimilarity analysis to explore the discrepancies between the two remote sensing products. Both the GFC and our supervised classification showed that deforestation rates were higher in the 20km buffer than inside the PAs and that Jamanxim National Forest had the highest deforestation rate of the PAs we studied. However, GFC maps showed consistently higher rates of deforestation than our maps. Through a dissimilarity analysis, we found that many of the inconsistencies between these datasets arise from different treatment of mixed pixels or different parameters in map creation (for example, GFC does not detect reforestation after 2012). We found that our maps underestimated deforestation while GFC overestimated deforestation, and that true deforestation rates likely fall between our two estimates. We encourage users to consider limitations and biases when using or interpreting our maps, which we make publicly available, and GFC’s maps.

Forest-to-pasture conversion modifies the soil bacterial community in Brazilian dry forest Caatinga

Soils comprise a huge fraction of the world's biodiversity, contributing to several crucial ecosystem functions. However, how the forest-to-pasture conversion impact soil bacterial diversity remains poorly understood, mainly in the Caatinga biome, the largest tropical dry forest of the world. Here, we hypothesized that forest-to-pasture conversion would shape the microbial community. Thus, the soil bacterial community was assessed using the 16S rRNA gene sequencing into the Illumina MiSeq platform. Then, we analyzed ecological patterns and correlated the bacterial community with environmental parameters in forest, and two distinct pastures areas, one less productive and another more productive. The variation in soil properties in pastures and forest influenced the structure and diversity of the bacterial community. Thus, the more productive pasture positively influenced the proportion of specialists and the co-occurrence network compared to the less productive pasture. Also, Proteobacteria, Acidobacteria, and Verrucomicrobia were abundant under forest, while Actinobacteria, Firmicutes, and Chloroflexi were abundant under pastures. Also, the more productive pasture presented a higher bacterial diversity, which is important since that a more stable and connected bacterial community could benefit the agricultural environment and enhance plant performance, as can be observed by the highest network complexity in this pasture. Together, our findings elucidate a significant shift in soil bacterial communities as a consequence of forest-to-pasture conversion and bring important information for the development of preservation strategies.

Recent Hydrological Droughts in Brazil and Their Impact on Hydropower Generation

Brazil has endured the worst droughts in recorded history over the last decade, resulting in severe socioeconomic and environmental impacts. The country is heavily reliant on water resources, with 77.7% of water consumed for agriculture (irrigation and livestock), 9.7% for the industry, and 11.4% for human supply. Hydropower plants generate about 64% of all electricity consumed. The aim of this study was to improve the current state of knowledge regarding hydrological drought patterns in Brazil, hydrometeorological factors, and their effects on the country’s hydroelectric power plants. The results show that since the drought occurred in 2014/2015 over the Southeast region of Brazil, several basins were sharply impacted and remain in a critical condition until now. Following that event, other regions have experienced droughts, with critical rainfall deficit and high temperatures, causing a pronounced impact on water availability in many of the studied basins. Most of the hydropower plants end the 2020–2021 rainy season by operating at a fraction of their total capacity, and thus the country’s hydropower generation was under critical regime.

Modeling Carbon Release of Brazilian Highest Economic Pole and Major Urban Emitter: Comparing Classical Methods and Artificial Neural Networks

Despite the concern about climate change and the associated negative impacts, fossil fuels continue to prevail in the global energy consumption. This paper aimed to propose the first model that relates CO2 emissions of Sao Paulo, the main urban center emitter in Brazil, with gross national product and energy consumption. Thus, we investigated the accuracy of three different methods: multivariate linear regression, elastic-net regression, and multilayer perceptron artificial neural networks. Comparing the results, we clearly demonstrated the superiority of artificial neural networks when compared with the other models. They presented better results of mean absolute percentage error (MAPE = 0.76%) and the highest possible coefficient of determination (R2 = 1.00). This investigation provides an innovative integrated climate-economic approach for the accurate prediction of carbon emissions. Therefore, it can be considered as a potential valuable decision-support tool for policymakers to design and implement effective environmental policies.

Mapping Land Suitability to Guide Landscape Restoration in the Amazon

Beyond reducing deforestation, the control of forest degradation, the promotion of forest restoration, and the improvement of agricultural practices in the Brazilian Amazon are becoming increasingly important for sustainable development. To enable farmers and authorities to organize their landscapes and optimize both agricultural practices and the provision of ecosystem services, mapping land suitability is essential, but it is lacking in the region. In this paper, we present a method for mapping land suitability at a fine scale (30-m pixels), adapted to the needs of farmers and municipalities, to not only optimize agricultural production but also the ecosystem services provided by forests. We used topographic data from the Brazilian municipality of Paragominas to produce four maps, one each of soil texture, slope, floodplains, and hydrography, that we then combined into a single land suitability map. This map has been incorporated into a spatial database, which also contains information on land use, remoteness, and land tenure. We performed spatial analyses to measure the process of land use change, and to define indicators that enable local stakeholders to organize landscape restoration. We highlight an organic link between agricultural intensification and forest restoration, and provide a spatial tool for landscape design, assessment, and monitoring.

Large carbon sink potential of secondary forests in the Brazilian Amazon to mitigate climate change

Tropical secondary forests sequester carbon up to 20 times faster than old-growth forests. This rate does not capture spatial regrowth patterns due to environmental and disturbance drivers. Here we quantify the influence of such drivers on the rate and spatial patterns of regrowth in the Brazilian Amazon using satellite data. Carbon sequestration rates of young secondary forests (<20 years) in the west are ~60% higher (3.0 ± 1.0 Mg C ha^-1 yr^-1) compared to those in the east (1.3 ± 0.3 Mg C ha^-1 yr^-1). Disturbances reduce regrowth rates by 8-55%. The 2017 secondary forest carbon stock, of 294 Tg C, could be 8% higher by avoiding fires and repeated deforestation. Maintaining the 2017 secondary forest area has the potential to accumulate ~19.0 Tg C yr^-1 until 2030, contributing ~5.5% to Brazil's 2030 net emissions reduction target. Implementing legal mechanisms to protect and expand secondary forests whilst supporting old-growth conservation is, therefore, key to realising their potential as a nature-based climate solution.

Hidden destruction of older forests threatens Brazil's Atlantic Forest and challenges restoration programs

Understanding the dynamics of native forest loss and gain is critical for biodiversity conservation and ecosystem services, especially in regions experiencing intense forest transformations. We quantified native forest cover dynamics on an annual basis from 1990 to 2017 in Brazil's Atlantic Forest. Despite the relative stability of native forest cover during this period (~28 Mha), the ongoing loss of older native forests, mostly on flatter terrains, have been hidden by the increasing gain of younger native forest cover, mostly on marginal lands for mechanized agriculture. Changes in native forest cover and its spatial distribution increased forest isolation in 36.4% of the landscapes. The clearance of older forests associated with the recut of 27% of younger forests has resulted in a progressive rejuvenation of the native forest cover. We highlight the need to include native forest spatiotemporal dynamics into restoration programs to better estimate their expected benefits and unexpected problems.

Drivers of Fire Anomalies in the Brazilian Amazon: Lessons Learned from the 2019 Fire Crisis

The 2019 fire crisis in Amazonia dominated global news and triggered fundamental questions about the possible causes behind it. Here we performed an in-depth investigation of the drivers of active fire anomalies in the Brazilian Amazon biome. We assessed a 2003–2019 time-series of active fires, deforestation, and water deficit and evaluated potential drivers of active fire occurrence in 2019, at the biome-scale, state level, and local level. Our results revealed abnormally high monthly fire counts in 2019 for the states of Acre, Amazonas, and Roraima. These states also differed from others by exhibiting in this year extreme levels of deforestation. Areas in 2019 with active fire occurrence significantly greater than the average across the biome had, on average, three times more active fires in the three previous years, six times more deforestation in 2019, and five times more deforestation in the five previous years. Approximately one-third of yearly active fires from 2003 to 2019 occurred up to 1 km from deforested areas in the same year, and one-third of deforested areas in a given year were located up to 500 m from deforested areas in the previous year. These findings provide critical information to support strategic decisions for fire prevention policies and fire combat actions.

Assessing Land Use and Land Cover Changes in the Direct Influence Zone of the Braço Norte Hydropower Complex, Brazilian Amazonia

Over the decades, hydropower complexes have been built in several hydrographic basins of Brazil including the Amazon region. Therefore, it is important to understand the effects of these constructions on the environment and local communities. This work presents a land use and land cover change temporal analysis considering a 33-year period (1985–2018) in the direct influence zone of the Braço Norte Hydropower Complex, Brazilian Amazonia, using the Collection 4.1 level 3 of the freely available MapBiomas dataset. Additionally, we have assessed the Brazilian Amazon large-scale deforestation process acting as a land use and land cover change driver in the study area. Our findings show that the most impacted land cover was forest formation (from 414 km2 to 287 km2, a reduction of 69%), which primarily shifted into pasturelands (increase of 664%, from 40 km2 to 299 km2). The construction of the hydropower complex also triggered indirect impacts such as the presence of urban areas in 2018 and the consequent increased local demand for crops. Together with the ongoing large-scale Amazonian deforestation process, the construction of the complex has intensified changes in the study area as 56.42% of the pixels were changed between 1985 and 2018. This indicates the importance of accurate economic and environmental impact studies for assessing social and environmental consequences of future construction in this unique region. Our results reveal the need for adopting special policies to minimize the impact of these constructions, for example, the creation of Protected Areas and the definition of locally-adjusted parameters for the ecological-economic zoning considering environmental and social circumstances derived from the local actors that depend on the natural environment to subsist such as indigenous peoples, riverine population, and artisanal fishermen.

Persistent collapse of biomass in Amazonian forest edges following deforestation leads to unaccounted carbon losses

Deforestation is the primary driver of carbon losses in tropical forests, but it does not operate alone. Forest fragmentation, a resulting feature of the deforestation process, promotes indirect carbon losses induced by edge effect. This process is not implicitly considered by policies for reducing carbon emissions in the tropics. Here, we used a remote sensing approach to estimate carbon losses driven by edge effect in Amazonia over the 2001 to 2015 period. We found that carbon losses associated with edge effect (947 Tg C) corresponded to one-third of losses from deforestation (2592 Tg C). Despite a notable negative trend of 7 Tg C year^-1 in carbon losses from deforestation, the carbon losses from edge effect remained unchanged, with an average of 63 ± 8 Tg C year^-1 Carbon losses caused by edge effect is thus an additional unquantified flux that can counteract carbon emissions avoided by reducing deforestation, compromising the Paris Agreement's bold targets.