Search Results (383)

Human-driven land-use change has significantly altered forest ecosystems and carbon dynamics in mountainous regions. This study aims to quantify land cover transitions and associated forest carbon stocks changes in Bhutan. It also seeks to support the development of a national measurement, reporting, and verification system. Using Landsat-based satellite imagery and object-based image classification techniques, we assessed forest cover transitions, stand structure variations, and forest type changes across temporal intervals. The analysis revealed a consistent increase in agricultural and built-up areas. It also showed a concomitant decline in coniferous forest cover. In particular, agricultural land increased by approximately 0.77 million ha, while coniferous forest decreased by approximately 0.19 million ha over the study period. These changes were driven by both climatic shifts and socio-economic factors. Approximately 57% of Bhutan’s population depends on agriculture. Correspondingly, forest carbon stocks declined from approximately 570 million tC in 1995 to 405 million tC in 2017. This decline was largely attributed to coniferous forest loss and climate-induced mortality. Bhutan has made significant preparations for the implementation of the Warsaw REDD+ framework under the United Nations Framework Convention on Climate Change. These preparations include the establishment of a forest reference emission level for submission. However, challenges remain in detecting small-scale land use changes. Additional challenges include addressing spectral misclassification in mountainous regions. Our study provides a scientific baseline to support national forest monitoring and carbon accounting systems. It also offers policy-relevant insights for achieving Bhutan’s nationally determined contributions and enhancing its carbon sink potential. Full article

Land use and land cover (LULC) change strongly influences national carbon dynamics and the effectiveness of forest-based climate mitigation strategies, particularly in mountainous developing countries. This study integrates scenario-based LULC modeling, spatially explicit carbon accounting, and economic valuation to assess how alternative development pathways affect carbon storage and its economic value in Nepal over the 2020–2050 period. LULC projections for four scenarios: Business-as-Usual (BAU), Rapid Urban Development (RUD), Forest Degradation and Terai Contraction (FDTC), and Agricultural Land Abandonment and Ecological Recovery (ALER), were generated using the TerrSet Land Change Modeler, with 2020 as the baseline. These projections were then used as inputs to the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Carbon Storage and Sequestration model to estimate changes in ecosystem carbon stocks, integrating aboveground biomass, belowground biomass, soil organic carbon, and dead organic matter pools. Carbon stock changes were monetized using a constant carbon price of USD 5/tCO₂e and a 3% discount rate to estimate net present values (NPV). Results reveal strong divergence across scenarios. National carbon storage remains near-neutral under BAU (−0.46% by 2050), declines under RUD (−2.42%) and FDTC (−5.32%), and increases substantially under ALER (+11.74%). These biophysical outcomes translate into contrasting economic values: BAU yields a small negative NPV, RUD and FDTC generate large discounted losses, and ALER produces a strongly positive NPV exceeding USD 800 million by 2050. Spatially, forest and other wooded land dominate national carbon dynamics, while urban expansion and forest degradation drive disproportionate losses. Overall, the study results demonstrate that recovery-oriented land-use pathways offer substantially greater long-term carbon and economic benefits than development trajectories dominated by urban expansion or forest degradation, providing a policy-relevant framework to support Reducing Emissions from Deforestation and Forest Degradation, together with conservation, sustainable forest management, and enhancement of forest carbon stocks (REDD+) planning and long-term mitigation assessment in Nepal. Full article

The rapid growth of renewable integration and active consumer participation has made modern power grids increasingly complex and dynamic, where maintaining balanced and efficient energy distribution remains a central challenge. This paper introduces a symmetry-aware optimized fuzzy deep reinforcement learning-gated recurrent unit (OF-DRL-GRU) model that exploits the natural symmetry and asymmetry in demand–generation behavior to achieve stable and adaptive load balancing. The proposed architecture consists of four core modules: a fuzzy logic layer that formulates symmetrically distributed membership functions for interpretable and balanced state transitions; a DRL agent that governs decision actions through a symmetry-preserving reward mechanism balancing exploration and exploitation; a GRU network that models temporal symmetries while performing controlled symmetry-breaking during dynamic fluctuations to enhance generalization; and an improved multi-objective biogeography-based optimization (IMOBBO) algorithm that optimizes fuzzy parameters and model hyper-parameters through adaptive migration alternating between symmetry preservation and deliberate asymmetry, ensuring efficient convergence and global diversity. The synergy among these modules forms a unified symmetry-aware optimization paradigm, reflecting how symmetric structures sustain stability while purposeful asymmetry enhances robustness and adaptivity. The proposed framework is evaluated using three benchmark datasets (UK-DALE, Pecan Street, and REDD) and compared against several advanced and competitive models. Experimental outcomes show that the proposed OF-DRL-GRU model achieves 99.23% accuracy, 99.69% recall, and 99.83% area under the curve (AUC), alongside faster runtime, lower variance, and improved convergence stability. These results demonstrate that incorporating symmetry–asymmetry principles within AI-driven optimization significantly enhances interpretability, resilience, and energy efficiency, paving the way for intelligent, self-adaptive load management in next-generation smart grids. Full article

Fine sediment infiltration is widely discussed as a stressor to wild salmonids’ spawning success, but its mechanisms and severity in wild salmonid redds are difficult to measure. This study examined wild Atlantic salmon (Salmo salar) redd survival using emergence traps in two small coastal streams with differing agricultural land-use intensities on Prince Edward Island, Canada. Measured environmental parameters included stream and hyporheic dissolved oxygen, water velocity, water level, redd temperature, redd substrate composition, and stream suspended solids. Wild Atlantic salmon redds were equipped with emergence traps during May to June in two study years to evaluate survival. No single environmental factor was strongly associated with the success of individual redd emergence. However, the West River exhibited approximately two-fold-higher portions of silt and clay in redd substrates. Despite this, only modest reductions in hyporheic dissolved oxygen were observed and appeared to be related to high discharge events rather than sediment accumulation. Mortality rates were highly variable across all study sites on both rivers, which may be attributed to fertilization success rather than environmental conditions, as natural mortality was at least 50%. Entombment of alevin from accumulated fine sediments was noted in several redds on the West River, suggesting this mechanism may contribute to mortality even when oxygen levels are adequate. Overall, the study highlights the resilience of salmon embryos with moderate hypoxic episodes and the challenges of linking sediment metrics to mortality in wild Atlantic salmon redds. Full article

Africa is a continent experiencing the highest yearly rate of deforestation. As a result, there is debate about the causes and consequences of this phenomenon, as well as on the effectiveness of actions undertaken to address this problem. This study offers insights into economic aspects of deforestation in Africa with regard to the use of econometric and spatial data analysis and the inclusion of determinants not considered by previous research. Special attention is paid to the participation of African countries in UN-REDD (United Nations Collaborative Program on Reducing Emissions from Deforestation and Forest Degradation in Developing Countries) and grouping countries according to the level of their forest cover. We demonstrate a negative relationship between economic activity and forest cover using both econometric modeling and spatial data analysis, and present some moderate arguments in favor of the UN-REDD program and its effectiveness in mitigating deforestation in Africa. Importantly, there are no universal patterns across countries characterized by different levels of forest cover. Therefore, we conclude that advancement of this research area requires new methodological approaches based on big data, machine learning, and artificial intelligence to supplement existing approaches and enhance our understanding of the interplay between forest loss and economic growth. Full article

Accurate estimation of above-ground biomass (AGB) is vital for carbon accounting, biodiversity conservation, and sustainable forest management, especially in tropical regions under strong anthropogenic pressure. This study estimated and mapped AGB in the Atacora Mountain Chain, Togo, using a multi-source remote sensing approach within Google Earth Engine (GEE). Field data from 421 plots of the 2021 National Forest Inventory were combined with Sentinel-1 Synthetic Aperture Radar, Sentinel-2 multispectral imagery, bioclimatic variables from WorldClim, and topographic data. A Random Forest regression model evaluated the predictive capacity of different variable combinations. The best model, integrating SAR, optical, and climatic variables (S1S2allBio), achieved R² = 0.90, MAE = 13.42 Mg/ha, and RMSE = 22.54 Mg/ha, outperforming models without climate data. Dense forests stored the highest biomass (124.2 Mg/ha), while tree/shrub savannas had the lowest (25.38 Mg/ha). Spatially, ~60% of the area had biomass ≤ 50 Mg/ha. Precipitation correlated positively with AGB (r = 0.55), whereas temperature showed negative correlations. This work demonstrates the effectiveness of integrating multi-sensor satellite data with climatic predictors for accurate biomass mapping in complex tropical landscapes. The approach supports national forest monitoring, REDD+ programs, and ecosystem restoration, contributing to SDGs 13, 15, and 12 and offering a scalable method for other tropical regions. Full article

In recent years, load disaggregation and non-intrusive load-monitoring (NILM) methods have garnered widespread attention for optimizing energy management systems, becoming crucial tools for achieving energy efficiency and analyzing power consumption. However, existing NILM methods face challenges in accurately handling appliances with multiple operational states and suffer from low accuracy and poor computational efficiency, particularly in modeling long-term dependencies and complex appliance load patterns. This article proposes an improved NILM model optimized based on transformers. The model first utilizes a convolutional neural network (CNN) to extract features from the input sequence and employs a bidirectional long short-term memory (BiLSTM) network to model long-term dependencies. Subsequently, multiple transformer blocks are used to capture dependencies within the sequence. To validate the effectiveness of the proposed model, we applied it to real-world household energy datasets: UK-DALE and REDD. Compared with suboptimal models, our model significantly improves the F1 score by 24.5% and 22.8%. Full article

Forests are important biodiversity reservoirs and require sustainable management to prevent deforestation and forest degradation. Forest landscape restoration (FLR) has been proposed as a sustainable initiative aimed at restoring ecosystem functions and improving the well-being of surrounding populations. In 2005, the World Wildlife Fund (WWF) initiated a project to protect 200 ha of savanna in Manzonzi landscape, Democratic Republic of Congo, on the outskirts of the Luki Biosphere Reserve. The biodiversity changes related to this ecological restoration project remain unpublished. To address this knowledge gap, floristic inventories of the protected Manzonzi landscape were carried out over a 12-year period and we assessed how changes in the floral composition of this landscape evolved and affected the provision of ecosystem services (ES). We found that protection of the savanna by banning recurring bush fires and fencing off the area promoted the richness and abundance of forest species, such as Xylopia aethiopica (Dunal) A. Rich, Albizia adianthifolia (Schumach.) W. Wight. These forest taxa replaced grassland species, such as Hymenocardia acida Tul. and Maprounea africana Müll. Arg., and served to benefit the local population, who use these forest taxa as food, fuelwood, and medicines. This study revealed that protected savanna improved woody biomass, plant diversity (richness/abundance), and carbon storage, significantly boosting essential ES for communities; yet these positive trends reversed when active monitoring ceased. Protecting savannas improves the environment and benefits communities, but stopping protection efforts can undo these gains, emphasizing the need for ongoing conservation. Full article

In the context of climate change and greenhouse gas emissions, the forestry sector holds significant potential to contribute to global mitigation efforts. One of the primary drivers of deforestation is land expansion for livestock production. However, both sectors are closely linked to issues of food security and food sovereignty, with the livestock sector playing a crucial role in ensuring food availability. Integrating these two sectors through silvopastoral systems offers a promising solution that supports forest conservation while simultaneously addressing the global food crisis. Among the leading initiatives in forest conservation is REDD+, a mechanism under the UNFCCC that has proven effective in reducing deforestation and forest degradation, as well as in enhancing carbon stock conservation. Following the ratification of Article 6 of the Paris Agreement in 2024, REDD+ has gained recognition as a viable approach for generating international carbon credits. Given the intersection of the livestock and forestry sectors, and the potential of carbon credits to advance the goals of the Paris Agreement, silvopastoral systems could be considered for inclusion in REDD+ strategies under the framework of Article 6. Full article

Community-managed forests within agroforestry landscapes are vital for both carbon sequestration and agricultural sustainability. This study assesses the Hariyali Community Forest (HCF) in western Nepal, emphasizing its role in carbon storage within a Sal (Shorea robusta)-dominated lowland forest containing diverse native and medicinal species. Stratified field inventories combined with satellite-derived biomass and land-use/land-cover data were used to quantify carbon stocks and spatial trends. In 2022, the mean aboveground carbon density was 165 tC ha⁻¹, totaling approximately 101,640 tC (~373,017 tCO₂e), which closely matches satellite-based trends and indicates consistent carbon accumulation. Remote sensing from 2015–2022 showed a net tree cover gain of 427 ha compared to a 2000 baseline of 188 ha, evidencing effective community-led regeneration. The 615 ha Sal-dominated landscape also sustains agroforestry, small-scale horticulture, and subsistence crops, integrating livelihoods with conservation. Temporary carbon declines between 2020 and 2022, linked to localized harvesting and management shifts, highlight the need for stronger governance and local capacity. This study, among the first integrated carbon assessments in Nepal’s lowland Sal forests, demonstrates how community forestry advances REDD+ (Reducing Emissions from Deforestation and Forest Degradation, and the role of conservation, sustainable management of forests, and enhancement of forest carbon stocks in developing countries) objectives while enhancing rural resilience. Linking field inventories with satellite-derived biomass and land-cover data situates community forestry within regional environmental change and SDG (Sustainable Development Goals) targets (13, 15, and 1) through measurable ecosystem restoration and livelihood gains. Full article

Natural products hold immense therapeutic potential, yet they remain underexplored due to challenges in activating or producing them in laboratory settings. Here, we investigate the regulatory capabilities of a new medium-sized Streptomyces Antibiotic Regulator Protein (SARP), Fzm_SARP, in comparison to the well-characterized small SARP, RedD, across 18 diverse actinobacterial strains. In addition to the conserved DNA-binding domains typical of SARP regulators, the medium-sized Fzm_SARP also contains an additional NTPase domain. Our study revealed that 327 of the 422 metabolites (77%) detected in 18 wild-type actinobacterial strains were up-regulated in the SARP over-expressing strains. Among these 422 metabolites, 55% were up-regulated in the two SARP over-expressing strains whereas 15% and 7% were specifically up-regulated in the RedD and Fzm_SARP over-expressing strains, respectively. Interestingly, 244 metabolites not previously detected in the wild-type strains were detected in the two SARP over-expressing strains, resulting in a 58% increase from 422 to 666 metabolites. 36% of these new 244 metabolites were up-regulated in the two SARP over-expressing strains whereas 37% and 27% of these metabolites were specifically up-regulated in the RedD and Fzm_SARP over-expressing strains, respectively. These regulator-specific metabolites also give rise to distinct bioactivity profiles observed for each SARP. Overall, these findings expand our understanding of SARP family regulators and offer valuable insights for future research and applications in microbial biotechnology and secondary metabolite production. Full article

Background: Regulated in development and DNA damage response 1 (REDD1) is a stress-related protein that is found to be involved in tumor progression. The role and internal regulatory mechanism of REDD1 in lung adenocarcinoma (LUAD) remain unidentified as of yet. Methods: Immunohistochemical and Western blot tests were performed to evaluate REDD1 expression in LUAD tissues. EdU staining, cell counting kit-8 assays, and colony formation analyses were conducted to estimate cell proliferation. Flow cytometry was applied to examine apoptosis, while migration was detected by a transwell assay. Results: REDD1 was upregulated in LUAD tissues, and hypoxia promoted the expression of REDD1 in LUAD cells. In addition, knockdown of REDD1 inhibited the increase in proliferation, migration, and colony formation induced by hypoxia in LUAD cells. Apoptosis was decreased by hypoxia and restored after REDD1 downregulation. Furthermore, p-ERK and p-JNK signaling pathways were involved in the changes in proliferation, apoptosis, and migration of LUAD cells following REDD1 knockdown under hypoxia. Conclusions: REDD1 may be a possible therapeutic target for LUAD. Full article

Agricultural production in Zamora Chinchipe is primarily focused on dairy farming, an activity that constitutes a key component of land use in the region. Accordingly, the objectives of this study were as follows: (a) to estimate greenhouse gas (GHG) emissions from dairy farms using the GLEAM model and (b) to evaluate the influence of altitude and livestock management practices on soil properties and the estimated GHG emissions associated with cattle production. This study encompassed 100 dairy farms, where the GLEAM methodology was applied to quantify emissions-related data. In addition, 300 soil samples (three per farm) were collected, and the perimeter of each farm, as well as the remaining forest areas, was mapped. The results indicate that although the farms generate CO₂-equivalent emissions associated with livestock activities, the remaining forest areas contribute to mitigation by storing carbon in the soil. Altitude was found to positively influence soil quality, increasing organic matter and nitrogen content, whereas overgrazing negatively affected key soil properties and was associated with higher levels of GHG emissions. These findings underscore the need to implement sustainable management strategies that integrate agricultural production with the conservation of ecosystem services. Full article

REDD+ has emerged as a global strategy for reducing CO₂ emissions from deforestation and forest degradation and shows great promise for the Extractive Reserves of the Brazilian Amazon (RESEX). It is essential to assess whether REDD+ projects have effectively contributed to the conservation of these areas over time. To address this issue, we analyzed land use and cover dynamics in the RESEX Rio Preto-Jacundá (Rondônia) and its surroundings from 2004 to 2020 to evaluate the impacts of a certified REDD+ project. The following two trend scenarios were simulated: (i) pre-implementation (2004–2012), projected to 2020, and (ii) post-implementation (2012–2020), projected to 2028. Historical maps were derived from the TerraClass dataset, and future projections were generated using Markov Chains combined with Cellular Automata. Forest conservation was evaluated through structural metrics such as the number, size, and shape of forest fragments, and the type, frequency, and length of boundaries with other land uses, using ArcGIS tools and Patch Analyst. Carbon sequestration was estimated from the aboveground biomass values of primary and secondary forests. The results showed that the REDD+ mechanism did not achieve the expected environmental benefits, with a decrease in carbon stocks over time and potential negative effects on the richness and composition of local flora. Full article

Spawning habitat partitioning can be important for maintaining sympatric fish species. Likewise, critical spawning habitat loss may challenge the long-term persistence of sympatric fish species. The Bois Brule River, Wisconsin, USA, is a spring-fed, western Lake Superior tributary that supports five naturally reproducing populations of salmonids (native brook trout Salvelinus fontinalis; introduced brown trout Salmo trutta, rainbow trout Oncorhynchus mykiss, coho salmon O. kisutch, and chinook salmon O. tshawytscha). Given increases in recreational angler use and predicted climate-associated changes to trout stream habitat, a better understanding of species interactions during spawning is important to guide future management and conservation of these anthropogenically derived sympatric native and introduced salmonids. Our aim was to establish whether there was partitioning or overlapping in the redd site location preferences among native and introduced salmonids inhabiting the Bois Brule River. We mapped species-specific redd locations by canoe over a 15.3 river km section known to be important for salmonid spawning and evaluated physical, flow, and thermal conditions of these habitats of the Bois Brule River during 2021–2022. We found that spring spawning rainbow trout and fall spawning pacific salmonids and brown trout used the same spawning locations on mid-channel, larger gravel reefs downstream of riffle sections. Native brook trout spawned on smaller substrates with lower streamflow on the edges of the channel, with the highest spawning activity occurring in littoral areas of lentic portions of the river. Our findings provide valuable knowledge of critical spawning habitats for sympatric salmonids that may inform habitat conservation and enhancement efforts in the Bois Brule River and other Great Lakes tributaries with similar sympatric, naturally reproducing salmonids populations. Full article