Search Results (336)

Deforestation and land-use changes lead to significant soil degradation and erosion, particularly in Amazonian ecosystems, due to the region’s climate and geology. This study characterizes soil quality using physical, chemical, and biological parameters across different land uses. It uses a soil quality index (SQI) based on a minimum data set (MDS), from 19 evaluated parameters. The land uses evaluated were cacao monoculture (CMC), agroforestry systems associated with fruit and timber species (FAFS and TAFS, respectively), and a secondary forest. The SQI was composed of six variables, bulk density (BD), soil organic matter (SOM), urease activity (UR), pH, dehydrogenase activity (DH), and leaf litter, which are considered relevant indicators that allow for an adequate evaluation of soil quality. According to the SQI assessment, FAFS has a moderate-quality rating (0.40), followed by secondary forest (0.35), TAFS (0.33), and CMC (0.30), the last three categorized as low-quality. The methods used are replicable and efficient for evaluating changes in soil properties based on different land uses and management systems in landscapes similar to those of the Ecuadorian Amazon. Also worth mentioning is the potential of agroforestry as a sustainable land-use strategy that can enhance above- and below-ground biodiversity and nutrient cycling. Therefore, implementing agroforestry practices can contribute to long-term soil conservation and the resilience of tropical ecosystems. Full article

Deforestation driven by plantations, such as Pinus patula Schiede ex Schltdl. et Cham., is a major cause of biodiversity and functional loss in tropical ecosystems. We assessed the diversity and composition of lichens and bryophytes in four size categories of pine cones, small (3–5 cm), medium (5.1–8 cm), large (8.1–10 cm), and very large (10.1–13 cm), with a total of 150 pine cones examined, where the occurrence and cover of lichen and bryophyte species were recorded. Identification keys based on morpho-anatomical features were used to identify lichens and bryophytes. In addition, for lichens, secondary metabolites were tested using spot reactions with potassium hydroxide, commercial bleach, and Lugol’s solution, and by examining the specimens under ultraviolet light. To evaluate the effect of pine cone size on species richness, the Kruskal–Wallis test was conducted, and species composition among cones sizes was compared using multivariate analysis. A total of 48 taxa were recorded on cones, including 41 lichens and 7 bryophytes. A total of 39 species were found on very large cones, 37 species on large cones, 35 species on medium cones, and 24 species on small cones. This is comparable to the diversity found in epiphytic communities of pine plantations. Species composition was influenced by pine cone size, differing from small in comparison with very large ones. The PERMANOVA analyses revealed that lichen and bryophyte composition varied significantly among the pine cone categories, explaining 21% of the variance. Very large cones with specific characteristics harbored different communities than those on small pine cones. The presence of lichen and bryophyte species on the pine cones from managed Ecuadorian P. patula plantations may serve as refugia for the conservation of biodiversity. Pine cones and their scales (which range from 102 to 210 per cone) may facilitate colonization of new areas by dispersal agents such as birds and rodents. The scales often harbor lichen and bryophyte propagules as well as intact thalli, which can be effectively dispersed, when the cones are moved. The prolonged presence of pine cones in the environment further enhances their role as possible dispersal substrates over extended periods. To our knowledge, this is the first study worldwide to examine pine cones as substrates for lichens and bryophytes, providing novel insights into their potential role as microhabitats within P. patula plantations and forest landscapes across both temperate and tropical zones. Full article

The Millard’s rat (Dacnomys millardi), a threatened murid endemic to Southeast Asian montane rainforests and the sole member of its monotypic genus, faces escalating endangered risks as a Near Threatened species in China’s Biodiversity Red List. This ecologically specialized rodent exhibits diagnostic morphological adaptations—hypertrophied upper molars and cryptic pelage—that underpin niche differentiation in undisturbed tropical/subtropical forests. Despite its evolutionary distinctiveness, the conservation prioritization given to Dacnomys is hindered due to a deficiency of data and unresolved phylogenetic relationships. Here, we integrated morphological analyses with the first complete mitogenome (16,289 bp in size; no structural rearrangements) of D. millardi to validate its phylogenetic placement within the subfamily Murinae and provide novel insights into genetic diversity erosion. Bayesian and maximum likelihood phylogenies robustly supported Dacnomys as sister to Leopoldamys (PP = 1.0; BS = 100%), with an early Pliocene divergence (~4.8 Mya, 95% HPD: 3.65–5.47 Mya). Additionally, based on its basal phylogenetic position within Murinae, we propose reclassifying Micromys from Rattini to the tribe Micromyini. Codon usage bias analyses revealed pervasive purifying selection (Ka/Ks < 1), constraining mitogenome evolution. Genetic diversity analyses showed low genetic variation (CYTB: π = 0.0135 ± 0.0023; COX1: π = 0.0101 ± 0.0025) in fragmented populations. We propose three new insights into this genetic diversity erosion. (1) Evolutionary constraints: genome-wide evolutionary conservation and shallow evolutionary history (~4.8 Mya) limited mutation accumulation. (2) Anthropogenic pressures: deforestation-driven fragmentation of habitats (>20,000 km²/year loss since 2000) has reduced effective population size, exacerbating genetic drift. (3) Ecological specialization: long-term adaptation to stable niches favored genomic optimization over adaptive flexibility. These findings necessitate suitable conservation action by enforcing protection of core habitats to prevent deforestation-driven population collapses and advocating IUCN reclassification of D. millardi from Data Deficient to Near Threatened. Full article

The environmental detriments of the growing global production and overconsumption of beef, including greenhouse gas emissions, deforestation, and biodiversity loss, are well-documented. However, public awareness of how dietary choices affect the environment remains limited. This study examines sustainability views on beef consumption and the potential for behavioral change as a step toward more sustainable intake levels. An observational web-based survey was conducted (n = 1367) to assess respondents’ current beef intake frequency, views on beef consumption related to planetary health, tropical deforestation, greenhouse gas emissions, and climate change, and willingness to modify beef consumption behavior. Chi-square tests were used for group comparisons, and weighted average scores were applied to rank levels of resistance to reducing beef intake. Environmental concern related to beef consumption was associated with greater beef cutback intentions and lower long-term intake reduction resistance amongst beef eaters. Beef eaters who strongly agreed that global beef consumption negatively impacts the environment were considerably more likely to express intentions to reduce their long-term beef intake compared to those who strongly disagreed (94.4% vs. 19.6%). Overall, 76.6% of beef eaters indicated wanting to eat less beef or phase it out entirely (30.7% reduce, 29.4% minimize, 16.6% stop), with only 23.4% of them intending to keep their consumption unchanged. Compelling messages that help translate awareness into action, such as the #NoBeefWeek concept explored in this study, may support individuals in adopting more sustainable food choices. These cross-national findings provide evidence for a ‘knowledge–intent’ gap in sustainable diet research, with relevance for health communicators and policymakers. Future research could examine the factors and motivations influencing decisions to modify beef consumption, including the barriers to achieving sustainable consumption levels and the role of suitable alternatives in facilitating this transition. Full article

Scientific research in Amazonia plays a fundamental role in identifying pathways to sustainable development for the region, addressing the challenges posed by climate change, preserving its unique ecosystems, and aligning with societal challenges and rights advocated by its diverse populations. This paper encompasses a broad range of scientific publications, spanning from 1977 to 2024, and highlights key research areas, analyzing their results and trends to inform future developments. It also identifies areas that require deeper investigation. The results emphasize a focus on agricultural, biological, and environmental sciences. On the other hand, there is a need for more extensive research within the social sciences. As shown, research on indigenous land rights, cultural heritage, and the socio-economic impacts of environmental disruptions is essential for developing comprehensive conservation strategies. Furthermore, research on governance, policy, and socio-political dynamics in Amazonia can provide innovative approaches to addressing the challenges and opportunities for its people, biodiversity, and role in climate regulation, as demonstrated by the findings. The strategic research fields identified in this paper provide a guide for future studies and policy development aimed at protecting the forest and its inhabitants. This study emphasizes the need for approaches that integrate both natural and social sciences as essential for addressing the complex ecological and socio-economic challenges that continue to shape the contemporary research landscape. Furthermore, this paper highlights the importance of unity and cooperation among Amazonian countries and research institutions in achieving these goals. In this context, reinforcing long-term, large-scale research programs such as the LBA (Large-Scale Biosphere–Atmosphere Experiment in Amazonia) and the Scientific Panel for the Amazon (SPA) are crucial to advancing integrated, policy-relevant science for the sustainable future of the region. Full article

Tropical montane cloud forests (TMCFs) are biodiversity hotspots that have been increasingly cleared to cultivate coffee under full sun exposure, replacing traditional shaded agroforestry systems. This study evaluated the impact of TMCF clearing on soil quality by analyzing 108 samples from undisturbed primary and secondary forests and deforested coffee plantations in the Dominican Republic and Haiti. Our findings indicate that forest clearing has a substantial adverse impact on soil nutrient status. Soils from undisturbed plots had total organic carbon (TOC) concentrations 4.83 units higher than those from cleared plots. Nitrogen levels were reduced by 28–61%, and available potassium declined by 23–51% in soils that had been cleared. Conversely, the available phosphorus levels exhibited a modest increase (ranging from 23% to 27%) following the clearing process, presumably attributable to diminished plant uptake and augmented mineralization in conditions characterized by diminished organic matter. However, given that phosphorus is not a limiting factor for coffee growth, this marginal gain does not compensate for the broader degradation of soil fertility. The study emphasizes that allowing TMCFs to be used for sun-grown coffee results in long-term nutrient depletion through erosion and leaching, which poses a threat to both the productivity of the soil and the ecological integrity of these valuable forest systems. Full article

Water is scarce in semi-arid regions due to environmental limitations; this situation is aggravated by changes in land use and land cover (LULC). In this respect, the basic ecological functions of Permanent Preservation Areas (PPAs) help to maintain water resources. The aim of this study was to evaluate the relationship between the LULC and water quality in PPAs in a semi-arid watershed, from 2009 to 2016. The following limnological data were analyzed: chlorophyll-a, transparency, total nitrogen and total phosphorus. The changes in LULC were obtained by classifying images from Landsat 5, 7 and 8 into three types: Open Dry Tropical Forest (ODTF), Dense Dry Tropical Forest (DDTF) and Exposed Soil (ES). Spearman correlation and principal component analysis were applied to evaluate the relationships between the parameters. There was a significant positive correlation between DDTF and the best limnological conditions. However, ES showed a significant negative relationship with transparency and a positive relationship with chlorophyll-a, indicating a greater input of sediments and nutrients into the water. The PCA corroborated the results of the correlation. It is therefore essential to prioritize the preservation and restoration of the vegetation in these sensitive areas to ensure the sustainability of water resources. Future studies should assess the impact of specific human activities, such as agriculture, deforestation and livestock farming, on water quality in the PPAs. Full article

While the role of expanding agriculture in deforestation and the loss of other natural ecosystems is well known, the specific drivers in the context of small- and large-scale agriculture remain poorly understood. In this study, we employed satellite data and a deep learning algorithm to map the agricultural landscape of Central Africa (Cameroon, Central Africa Republic, Congo, Democratic Republic of Congo, Equatorial Guinea, and Gabon) into large- (including for plantations and intensively cultivated areas) and small-scale tree crops and non-tree crop cover. This permits the assessment of forest loss between the years 2000 and 2022 as a result of small- and large-scale agriculture. Thematic [user’s] accuracy ranged between 91.2 ± 2.5 percent (large-scale oil palm) and 17.8 ± 3.9 percent (large-scale non-tree crops). Small-scale tree crops achieved relatively low accuracy (63.5 ± 5.9 percent), highlighting the difficulties of reliably mapping crop types at a regional scale. In general, we observed that small-scale agriculture is fifteen times the size of large-scale agriculture, as area estimates of small-scale non-tree crops and small-scale tree crops ranged between 164,823 ± 4224 km² and 293,249 ± 12,695 km², respectively. Large-scale non-tree crops and large-scale tree crops ranged between 20,153 ± 1195 km² and 7436 ± 280 km², respectively. Small-scale cropping activities represent 12 percent of the total land cover and have led to dramatic encroachment into tropical moist forests in the past two decades in all six countries. We summarized key recommendations to help the forest conservation effort of existing policy frameworks. Full article

The Atlantic Forest has undergone deforestation and prolonged droughts, affecting ecosystem services. This study assesses the water balance using hydrological observations from representative tree species within a Montane Semideciduous Seasonal Forest (MF) remnant. Gross precipitation (GP), canopy interception (CI), and effective precipitation (EP = Throughfall + Stemflow) were recorded daily, and soil moisture was measured down to 1.80 m every two days during the dry period of the 2023/2024 hydrological year. Additionally, aboveground biomass (AGB), fresh root biomass (BR), and soil hydrological properties in the soil profile were obtained to support the water balance results. The highest EP values were recorded in Miconia willdenowii, while the lowest were in Xylopia brasiliensis. Root zone water storage exhibited a declining trend, with the highest values in Miconia willdenowii. ET remained low, mainly in April, July, and September, with Miconia willdenowii and Copaifera langsdorffii showing the highest values, and AGB correlated with CI and ET. The dynamic of this ecosystem is apparent in the temporal variations (CVt) of soil moisture, influenced by EP and ET. The greatest variability was recorded in the surface layer (0–20 cm), stabilizing with depth, especially below 120 cm. The Temporal Stability Index (TSI) of soil water storage indicated greater stability in Blepharocalyx salicifolius. This study highlights the significance of soil water storage and ET in a tropical forest ecosystem, particularly under drought conditions, suggesting potential species that may be more effective in recovering degraded areas. Full article

Soil erosion poses a significant global environmental challenge, causing land degradation, deforestation, river siltation, and reduced agricultural productivity. Although the Revised Universal Soil Loss Equation (RUSLE) has been widely applied in Brazil, its use in the tropical river basins of the Amazon remains limited. This study aimed to apply a GIS-integrated RUSLE model and compare its soil loss estimates with multiple linear regression (MLR) models based on terrain attributes, aiming to identify priority areas and key geomorphometric drivers of soil erosion in a tropical Amazonian river basin. A digital elevation model based on Shuttle Radar Topography Mission (SRTM) data, land use and land cover (LULC) maps, and rainfall and soil data were applied to the GIS-integrated RUSLE model; we then defined six risk classes—slight (0–2.5 t ha⁻¹ yr⁻¹), slight–moderate (2.5–5), moderate (5–10), moderate–high (10–15), high (15–25), and very high (>25)—and identified priority zones as those in the top two risk classes. The Caeté River Basin (CRB) was classified into six erosion risk categories: low (81.14%), low to moderate (2.97%), moderate (11.88%), moderate to high (0.93%), high (0.03%), and very high (3.05%). The CRB predominantly exhibited a low erosion risk, with higher erosion rates linked to intense rainfall, gentle slopes covered by Arenosols, and human activities. The average annual soil loss was estimated at 2.0 t ha⁻¹ yr⁻¹, with a total loss of 1005.44 t ha⁻¹ yr⁻¹. Additionally, geomorphological and multiple linear regression (MLR) analyses identified seven key variables influencing soil erosion: the convergence index, closed depressions, the topographic wetness index, the channel network distance, and the local curvature, upslope curvature, and local downslope curvature. These variables collectively explained 26% of the variability in soil loss (R² = 0.26), highlighting the significant role of terrain characteristics in erosion processes. These findings indicate that soil erosion control efforts should focus primarily on areas with Arenosols and regions experiencing increased anthropogenic activity, where the erosion risks are higher. The identification of priority erosion areas enables the development of targeted conservation strategies, particularly for Arenosols and regions under anthropogenic pressure, where the soil losses exceed the tolerance threshold of 10.48 t ha⁻¹ yr⁻¹. These findings directly support the formulation of local environmental policies aimed at mitigating soil degradation by stabilizing vulnerable soils, regulating high-impact land uses, and promoting sustainable practices in critical zones. The GIS-RUSLE framework is supported by consistent rainfall data, as verified by a double mass curve analysis (R² ranging from 0.64 to 0.77), and offers a replicable methodology for soil conservation planning in tropical basins with similar erosion drivers. This approach offers a science-based foundation to guide soil conservation planning in tropical basins. While effective in identifying erosion-prone areas, it should be complemented in future studies by dynamic models and temporal analyses to better capture the complex erosion processes and land use change impacts in the Amazon. Full article

Tropical forests provide essential ecosystem services, playing a critical role in climate regulation, biodiversity conservation, and regional hydrological cycles while also supporting livelihoods. However, they are increasingly threatened by deforestation and land-use change. Accurate land cover (LC) mapping is vital to monitor these changes, but mapping tropical forests is challenging due to complex spatial patterns, spectral similarities, and frequent cloud cover. This study aims to improve LC classification accuracy in such a heterogeneous tropical forest region in Southeast Asia, namely Kulen, Cambodia, which is characterized by natural forests, regrowth forests, and agricultural lands including cashew plantations and croplands, using Sentinel-2 imagery, recursive feature elimination (RFE), and Random Forest. We generated 65 variables of spectral bands, indices, bi-seasonal differences, and topographic data from Sentinel-2 Level-2A and Shuttle Radar Topography Mission datasets. These variables were extracted from 1000 random points per 12 LC classes from reference polygons based on observed GPS points, Uncrewed Aerial Vehicle imagery, and high-resolution satellite data. The random forest models were optimized through correlation-based filtering and recursive feature elimination with hyperparameter tuning to improve classification accuracy, validated via confusion matrices and comparisons with global and national-scale products. Our results highlight the significant role of topographic variables such as elevation and slope, along with red-edge spectral bands and spectral indices related to tillage, leaf water content, greenness, chlorophyll, and tasseled cap transformation for tropical land cover mapping. The integration of bi-seasonal datasets improved classification accuracy, particularly for challenging classes like semi-evergreen and deciduous forests. Furthermore, correlation-based filtering and recursive feature elimination reduced the variable set from 65 to 19, improving model efficiency without sacrificing accuracy. Combining these variable selection methods with hyperparameter tuning optimized the classification, providing a more reliable LC product that outperforms existing LC products and proves valuable for deforestation monitoring, forest management, biodiversity conservation, and land use studies. Full article

This study developed an integrated approach for estimating tropical forest aboveground biomass (AGB) by combining UAV–LiDAR structural metrics and Sentinel-2B spectral data, optimized through successive projections algorithm (SPA) feature selection and random forest (RF) regression. Field surveys across three tropical forest sites in Hainan Province (49 plots) provided ground-truth AGB measurements, while UAV–LiDAR (1 m resolution) and Sentinel-2B (10 m) data were processed to extract 98 and 69 features, respectively. The results showed that LiDAR-derived elevation metrics (e.g., percentiles and kurtosis) correlated strongly with the AGB measurements (r = 0.652–0.751), outperforming Sentinel-2B vegetation indices (max r = 0.520). SPA–RF models with selected features significantly improved accuracy compared to full-feature RF, achieving R² = 0.670 (LiDAR), 0.522 (Sentinel-2B), and 0.749 (coupled data), with the fusion model reducing errors by 46–54% in high-biomass areas. Despite Sentinel-2B’s spectral saturation limitations, its integration with LiDAR enhanced spatial heterogeneity representation, particularly in complex canopies. The 200-iteration randomized validation ensured a robust performance, with mean absolute relative errors of ≤0.071 for fused data. This study demonstrates that strategic multi-sensor fusion, coupled with SPA-optimized feature selection, significantly improves tropical AGB estimation accuracy, offering a scalable framework for carbon stock assessments in support of Reducing Emissions from Deforestation and Forest Degradation (REDD+) and climate mitigation initiatives. Full article

The adverse effects of climate change, which are associated with the rise in greenhouse gases, impact all nations worldwide. In this context, tropical forests play a critical role in carbon sequestration. However, the significant anthropogenic pressure on these forests contributes to accelerated deforestation and a decrease in their capacity to regulate the climate. This study uses a comprehensive review of 176 published scientific articles and reports to assess the carbon sequestration capacity of rubber plantations, comparing their effectiveness with that of natural tropical forests. The findings are largely consistent and indicate that agricultural systems, such as rubber plantations, which were not traditionally associated with carbon sequestration, play a significant role in this area. Rubber plantations present a complementary alternative to the rapid deforestation of tropical forests, with the capacity to sequester substantial amounts of carbon. The range of carbon storage potential for rubber plantations, spanning from 30 to over 100 tons per hectare, rivals that of natural tropical forests, which can store over 300 tons per hectare. Furthermore, rubber plantations are notable for their indirect carbon sequestration potential. By providing a sustainable source of latex and wood, and thus income, they can reduce the pressure on natural tropical forests. However, challenges remain, particularly concerning sustainable management and the integration of rubber plantations into sustainable tropical forest management strategies. This analysis focuses on the opportunities and challenges of rubber plantations as an offset solution for carbon sequestration. It highlights the prospects for effectively integrating these plantations into sustainable tropical forest management policies. Full article

Human activities have led to an increased influx of carbon into lakes due to changes in land use that result in higher erosion rates, eutrophication, and the introduction of organic matter. This, in turn, causes greater carbon exports and carbon accumulation in sediments. In our study, we estimated the fluxes of total particulate carbon (F_TPC), particulate organic carbon (F_POC), and particulate inorganic carbon (F_PIC) in three lakes with different trophic statuses. Two lakes, one eutrophic (Bosque Azul) and one mesotrophic (San José), are in the anthropically impacted zone of the plateau. In contrast, an oligotrophic lake (Tziscao) is in the mountainous, pristine area of “Lagunas de Montebello” National Park, a tropical karst lake district in Chiapas, Mexico. Our findings revealed that the highest F_POC values were observed in the eutrophic lake (0.47 ± 0.2 g m⁻² d⁻¹), while the highest F_PIC were observed in the mesotrophic lake (1.11 ± 0.8 g m⁻² d⁻¹). In contrast, the oligotrophic lake exhibited the lowest fluxes. Eutrophication increased the levels of F_POC, while deforestation and erosion contributed to the rise in F_PIC. Eutrophication and erosion in the lakes of LMNP led to five-, two-, and sixteen-fold increases in the F_TPC, F_POC, and F_PIC, respectively. Full article

Isoprene emissions can affect the oxidizing capacity of the atmosphere and are likely to increase with an increase in the world’s biomass. The emission of isoprene is strongest in tropical forested regions, suggesting a major portion of tropospheric chemistry occurs in the tropics. As well as deforestation and reforestation having a direct impact on the world’s climate through land cover, there is also an indirect environmental impact (e.g., global warming, air pollution) through the resulting change in isoprene emissions. Previously, incomplete understanding of isoprene oxidation chemistry caused a model-measurement breakdown for concentrations of HO_x radicals observed over certain low-NO_x regions, such as the pristine Amazon rainforest. Over the last decade, however, understanding of isoprene oxidation chemistry has been vastly improved. Numerous research studies have provided evidence for the involvement of 1,6-H and 1,5-H shift reactions in the isoprene oxidation mechanism, which increases the level of HO_x recycling that occurs. As well as helping to reduce the model-measurement breakdown observed, the updated isoprene oxidation mechanism affects the tropospheric burdens of other species, including carbon monoxide (CO), methane (CH₄), ozone (O₃), organic peroxides (ROOH), secondary organic aerosol (SOA), and organic nitrates (RONO₂). There are still gaps in the understanding of the impacts and oxidation chemistry of isoprene emissions, which this literature review identifies and discusses. In the future, there is still much scope for further research, including modeling future reforestation scenarios with isoprene emissions and their impacts on both global and regional scales. Full article