Explore the vast range of titles available.

Forest degradation is widespread around the world, due to multiple factors such as unsustainable logging, agriculture, invasive species, fire, fuelwood gathering, and livestock grazing. In the Brazilian Amazon forest degradation from August 2006 to July 2016 reached 1,1 869 800 ha. The processes of forest degradation are still poorly understood, being a missing component in anthropogenic CO2 emission estimates in tropical forests. In this work, we analyzed temporal trajectories of forest degradation from August 2006 to July 2016 in the Brazilian Amazon and assessed their impact on the regional carbon balance. We combined the degradation process with deforestation-related processes (clear-cut deforestation and secondary vegetation dynamics), using the spatially-explicit INPE-EM carbon emission model. The trajectory analysis showed that 13% of the degraded area ended up being cleared and converted in the period and 61% of the total degraded area experienced only one event of degradation throughout the whole period. Net emissions added up to 5.4 GtCO2, considering the emissions from forest degradation and deforestation, absorption from degraded forest recovery, and secondary vegetation dynamics. The results show an increase in the contribution of forest degradation to net emissions towards the end of the period, related to the decrease in clear-cut deforestation rates, decoupled from the forest degradation rates. The analysis also indicates that the regeneration of degraded forests absorbed 1.8 GtCO2 from August 2006 and July 2016—a component typically overlooked in the regional carbon balance.

Secondary vegetation (SV) from land abandonment is a common transition phase between agricultural uses following tropical deforestation. The impact of SV on carbon sequestration and habitat fragmentation across tropical forest frontiers therefore depends on SV dynamics and demographics. Here, we used time series of annual MapBiomas land cover data to generate the first estimates of SV extent, age, and net carbon uptake in the Brazilian Amazon between 1985 and 2017. SV increased over time, totaling 12 Mha in 2017, 44% of which was ≤5 years old. Between 1988 and 2017, 19.6 Mha of SV was cleared, adding 45.5% to the area of primary deforestation detected by the Brazilian monitoring system (PRODES). Rates of SV loss have exceeded PRODES deforestation since 2011. Based on the age and extent of gains and losses, SV was a small net carbon sink during this period (8.9 Tg C yr−1). As SV is not formally protected by national environmental legislation or monitored by PRODES, long-term benefits from SV in the Brazilian Amazon remain uncertain.

Purpose There is an increasing recognition that the priming effect (PE) induced by fresh organic matter (FOM) may greatly influence soil organic carbon (SOC) dynamics. However, the patterns of PE induced by substrates with different quality on soils from vegetation succession, as well as the underlying mechanisms, are still unclear. Methods We conducted a field investigation to explore the changes in soil properties and SOC stocks along a secondary vegetation succession (cropland → shrubland → forest); then, we examined the patterns of PE by incubating FOMs with soils from the different succession stages. The added FOMs included 13 C-labeled glucose (GLU) as well as labile organic matter (LOM) and recalcitrant organic matter (ROM) extracted from 13 C-labeled maize leaves. Results Increases in SOC stock and changes in soil properties were detected during the process of vegetation succession. FOMs with contrasting quality caused PEs in different magnitudes, with a higher PE generated after the GLU and LOM treatments compared with ROM. We also detected a higher soil fungi/bacteria (F/B) with ROM than the GLU and LOM treatment. Under a given substrate treatment, PE was generally higher on cropland soil than shrubland and forest soil. The variations of PE among succession stages were negatively correlated with soil aggregate stability, total inorganic nitrogen, and available phosphorus and positively correlated with pH and F/B ratio. Conclusions Soil properties and substrate quality determine the PE in soils from vegetation succession. The PE might be one of the potential mechanisms underlying soil C dynamics during the vegetation succession.

The Brazilian Cerrado, a global biodiversity hotspot, is under increasing pressure from agricultural expansion and native vegetation conversion, underscoring the need for efficient monitoring to support conservation and environmental policies. In heterogeneous landscapes, land use and land cover (LULC) mapping using supervised classification methods faces a major bottleneck: the need for extensive and high-quality training datasets. To address this challenge, we propose a semi-automated, clustering-based methodology for mapping secondary vegetation within previously deforested areas, reducing training-sample requirements and enabling scalable mapping through the clustering of satellite image time series. In the first stage, an unsupervised process integrates graphics processing unit (GPU)-accelerated Self-Organizing Maps and hierarchical clustering with Dynamic Time Warping to produce spectro-temporal clusters. In the second stage, specialists label and refine these clusters by visual interpretation, transferring expert knowledge from individual pixels to grouped spectro-temporal patterns. Applied to 692,000 km2 of previously deforested land in the Cerrado biome, the methodology produced a mapped secondary vegetation area of 81,209 km2 (11.74%). The design-based estimated area was 98,683 ± 10,071 km2, with an overall accuracy of 96.45 ± 1.52%, a user’s accuracy of 96.27 ± 2.40%, a producer’s accuracy of 79.22 ± 7.94%, and an F1-score of 86.90%. The initial cluster labeling accounted for 86.3% of the final secondary vegetation area and limited the interpretation task to approximately 3000 cluster-level decisions. Implemented in the TerraClass Cerrado 2024 cycle, the workflow reduced the secondary vegetation mapping phase from approximately two years to six months while maintaining the thematic accuracy required for large-scale operational monitoring.

There is growing recognition of the potential of large-scale forest restoration in the Amazon as a ‘nature-based solution’ to climate change. However, our knowledge of forest loss and recovery beyond Brazil is limited, and carbon emissions and accumulation have not been estimated for the whole biome. Combining a 33 year land cover dataset with estimates of above-ground biomass and carbon sequestration rates, we evaluate forest loss and recovery across nine Amazonian countries and at a local scale. We also estimate the role of secondary forests in offsetting old-growth deforestation emissions and explore the temporal trends in forest loss and recovery. We find secondary forests across the biome to have offset just 9.7% of carbon emissions from old-growth deforestation, despite occupying 28.8% of deforested land. However, these numbers varied between countries ranging from 9.0% in Brazil to 23.8% in Guyana for carbon offsetting, and 24.8% in Brazil to 56.9% in Ecuador for forest area recovery. We reveal a strong, negative spatial relationship between old-growth forest loss and recovery by secondary forests, showing that regions with the greatest potential for large-scale restoration are also those that currently have the lowest recovery (e.g. Brazil dominates deforestation and emissions but has the lowest recovery). In addition, a temporal analysis of the regions that were >80% deforested in 1997 shows a continued decline in overall forest cover. Our findings identify three important challenges: (a) incentivising large-scale restoration in highly deforested regions, (b) protecting secondary forests without disadvantaging landowners who depend on farm-fallow systems, and (c) preventing further deforestation. Combatting all these successfully is essential to ensuring that the Amazon biome achieves its potential in mitigating anthropogenic climate change.

The objective of this study was to evaluate the influence of the composition and diversity of plant species browsed in a tropical dry forest, on the selection and voluntary intake (VI) by cattle during two seasons of the year. Plant species selection and VI of nine adult cattle (390 ± 13 kg of live weight) was evaluated for 7 weeks during the dry and rainy seasons on secondary vegetation (acahual). The composition, structure, diversity and importance value index were measured for fodder species browsed by cattle. The bite frequency (BF), preference index (PI) and VI of plants were also recorded. A total of 4882 plants belonging to 26 species and 17 families were registered, with a Shannon–Wiener diversity (H′) of 2.45. The species with the highest BF, PI and VI (P < 0.05) were Gymnopodium floribundum, Neomillspaughia emarginata, Mimosa bahamensis, Diospyros anisandra and Randia obcordata. The VI was higher (P < 0.05) in the rainy season than in the dry season (12.48 and 10.26 kg of DM/animal/day, respectively) and corresponded with a higher intake (P < 0.05) of nutrients and secondary metabolites. The density of species in the acahual played a determinant role in the VI of cattle, and the secondary metabolite content of plants did not interfere with the VI. We concluded, that the acahual vegetation provides sufficient forage for ruminant given its high plant diversity, guaranteeing the VI and adequate provision of nutrients for cattle.

Deforestation is a major threat to forest conservation in the Amazon, affecting biodiversity, climate balance, and natural resources. The beef cattle market targets deforestation-free products. This study aims to assess the extension of Secondary Vegetation (SV) in the Pará State, quantify SV deforestation in rural properties, and measure potential deforestation leakage in SV. The study analyzed the SV dynamics at the property level by accessing the CAR database, selecting properties within the Pará State and filtering the database according to criteria. The dissolved CAR layer was used to remove overlapping properties and classify properties by class size. Properties with no deforestation from 2009 to 2022 were selected as potential purchasing zone. SV areas with regeneration ages greater than five years were considered. In 2022, the Pará State had 2.55 million hectares of SV areas over five years of age, with 136,831 properties in the potential purchasing zone of cattle beef. From 2009 to 2022, 45% of selected properties did not have PRODES alerts, however 82% had SV deforestation events between 2009 and 2022. If SV deforestation was a criterion, 51,065 properties would be out of business, and only 10,887 properties were free from SV deforestation. Deforestation analysis showed that not all forest resources are protected. To achieve a deforestation-free beef cattle market, the TAC must include an SV conservation strategy, to protect all forest resources.

The re-suppression of secondary vegetation (SV) in the Brazilian Amazon for agriculture or land speculation occurs mostly in the rainy season. The use of optical images to monitor such re-suppression during the rainy season is limited because of the persistent cloud cover. This study aimed to evaluate the potential of C- and L-band SAR data acquired in the rainy season to discriminate SV in an area of new hotspot of deforestation in the municipality of Colniza, northwestern of Mato Grosso State, Brazil. This is the first time that the potential of dual-frequency SAR data was analyzed to discriminate SV, with an emphasis on data acquired during the rainy season. The L-band ALOS/PALSAR-2 and the C-band Sentinel-1 data acquired in March 2018 were processed to obtain backscattering coefficients and nine textural attributes were derived from the gray level co-occurrence matrix method (GLCM). Then, we classified the images based on the non-parametric Random Forest (RF) and Support Vector Machine (SVM) algorithms. The use of SAR textural attributes improved the discrimination capability of different LULC classes found in the study area. The results showed the best performance of ALOS/PALSAR-2 data classified by the RF algorithm to discriminate the following representative land use and land cover classes of the study area: primary forest, secondary forest, shrubby pasture, clean pasture, and bare soil, with an overall accuracy and Kappa coefficient of 84% and 0.78, respectively. The RF outperformed the SVM classifier to discriminate these five LULC classes in 14% of overall accuracy for both ALOS-2 and Sentinel-1 data sets. This study also showed that the textural attributes derived from the GLCM method are highly sensitive to the moving window size to be applied to the GLCM method. The results of this study can assist the future development of an operation system based on dual-frequency SAR data to monitor re-suppression of SV in the Brazilian Amazon or in other tropical rainforests.

Rangelands in arid and semi-arid regions are the main source of livestock feed. The fragmentation of these ecosystems by continuous grazing gives rise to the modification of ecological processes, which alters the structure and functionality of plant communities. Therefore, the use of geographic information systems and the analysis of satellite images are important to monitor spatial changes and to evaluate these areas in the Tamaulipan Highlands of northeastern Mexico. This work aimed to evaluate the current state of the rangelands and to determine the percentage of modified areas as well as propose the time of permanence, succession, or recovery of five different areas destined for rangelands. For the analysis, Landsat satellite scenes from the period 1973–2020 were used: they were classified into four categories using segmentation and maximum likelihood analysis, as well as a cross-tabulation method to determine the degree of succession. An increase in rangelands was found in three of the five areas analyzed in the period from 1973 to 2020. As rangeland areas increase, the coverage of pine–oak forests, submontane–thorny scrub, and anthropogenic areas, decreases. The disturbance processes were not linear, and the increase in rangeland areas was greater in xerophilous scrub and secondary vegetation. This work is the first contribution that evaluates the changes in land use and cover in grazing areas compromised by continuous grazing in the Tamaulipan Highlands and Mexico. In addition, the results indicate the importance of performing studies based on the coexistence of wildlife and livestock as well as the interaction between soil degradation and plant diversity with the increase in rangelands.

We are experiencing a global crisis in conservation, which has led to the prioritization of targets, such as nations, regions, and animal groups, which are necessary while resources are disputed. Brazil is a priority not only because of its megadiversity, high rates of endemism, and frequent descriptions of new species but also because of its high levels of deforestation. Among the species groups prioritized for conservation is the anurans (Amphibia: Anura), the population of which is severely declining. One group of anurans is the genus , which includes 37 endemic species in the Brazilian Atlantic Rainforest. Some of these species have highly restricted distributions (<100 ha). Thirty new species have been described since 2000, and 55.3% of all species are threatened with extinction. was only recently described and remains restricted to its type locality. Because of its reduced geographical distribution (0.41 km ), it has been proposed to be considered as Vulnerable. The objective of this study is to reevaluate the conservation status of and propose conservation measures. We searched for new populations during 2016-2020, evaluated impacts and potential impacts on the species' population, and performed an analysis of the density of this population and estimated its size. International Union for Conservation of Nature (IUCN) criteria were used to assess the conservation status of the species. We recorded the species in seven new localities (from 715-1,140 m above sea level) in the state of São Paulo up to 33 km from the type locality of the species (in state of Paraná). We estimated the area of occupancy as 148.44 km , densities as one calling male per 4.05 m and 130.00 m , and a total population size of 4,429,722 adult individuals. Based on our finding, we proposed three lines of management: (1) formation of fire brigades, (2) management of residents' mules in the conservation unit and surrounding areas, and (3) management of degraded areas. We recommend changing the species' conservation status from Vulnerable to Endangered because of its fragmented distribution and decline in the area of occupancy and in the quality of its habitat. Our results have expanded the species previous geographic distribution and delimited areas without previous records. Our estimates of population density and size are in accordance with those verified for congeners. The conservation of this species benefits the environments and other species that inhabit them, being, therefore, strategic for receiving conservation actions that will spread throughout the ecosystem.