Environmental Management最新文献

Lake Tana, Ethiopia’s largest natural lake and the headwater of the Blue Nile, provides critical ecosystem services and socio-economic benefits. However, rapid agricultural expansion in the Lake Tana sub-basin has led to increased pesticide use, which raises serious environmental concerns. This systematic review synthesi zes information on agricultural pesticide use, their residues in fish, water, and sediments, and the associated ecological and human health risks. A total of 66 active ingredients were identified across 13 districts, with the highest pesticide use reported in Libokemkem, Fogera, and Gondar Zuria. Pesticide use was dominated by insecticides, including several WHO-classified hazardous compounds. Risk Quotients derived from fish body residues identified imidacloprid, oxamyl, and flazasulfuron as priority pesticides posing high to very high risks to Labeobarbus spp. In Lake Tana, legacy organochlorine pesticides (endosulfan, lindane, endrin, DDT, and dieldrin) posed high to very high risks to Oreochromis niloticus. Human health risk assessment based on fish consumption indicated negligible non-carcinogenic risks from both current-use and legacy pesticides. Potentially Affected Fraction (PAF) and multi-substance Potentially Affected Fraction (msPAF) analyses indicated severe ecological risks posed by the measured water concentrations across the Lake Tana sub-basin. Sediment-bound pesticides also posed consistently high ecological risks, particularly for persistent organochlorines (lindane, endrin, and dieldrin). Overall, these findings advocate the urgent need for improved pesticide regulation, better management of legacy contaminants, and the promotion of sustainable agricultural practices to protect the Lake Tana sub-basin and its vital ecosystem services.

In contemporary river valley floors, floodplain meadows are associated with rare grassland plant communities that are important for their conservation value. This article outlines a desk-based method to identify, map and record floodplain meadows as historic features in the landscape, based on physical forms embodying agricultural practices dating back to the medieval period. Mapping the former location, extent and distribution of floodplain meadows independently of the survival of habitat provides transparent, place-based evidence of the decline of floodplain meadow habitats. It also supports restoration of floodplain meadows based on former locations that date back many centuries. The article summarises catchment-based studies carried out across England and Wales between 2017 and 2024. The methodology is GIS-based and uses a variety of base layers, historic landscape sources such as maps and lidar, and non-mappable documentary and published sources, all of which are readily accessible to users. In total, 373 historic floodplain meadows in seven catchments were identified, recorded, and added to a freely available online map. The results show that floodplain meadows were present in the historic landscape in many parts of England and Wales and suggest that even where meadows were situated on the riverine peripheries of manors or parishes, they were central to the structure of agricultural societies and the landscapes to which they gave rise. The approach that has been developed is relevant throughout the geographic range of floodplain meadows, reflecting at least the extent of medieval open field agriculture in Europe. However, the methodology may also be relevant to the restoration of anthropogenic habitats across the globe that are of high importance for nature conservation, climate mitigation and adaptation, where traces interpretable from the historic landscape are more extensive than the survival of the habitat itself.

Effective communication is a key instrument for managing visitor impacts in natural areas. This study examines how passive (pamphlets) and active (face-to-face) communication strategies influence campfire behavior, with a focus on reducing the use of ancient trees for firewood. While campfires are a cherished activity worldwide, they can cause severe ecological damage. Using a multi-methods approach that integrates social and natural sciences, we conducted a quasi-experimental field study combining visitor interviews, surveys, observations, and environmental assessments. Our main analysis used a multiple regression model that reflects how communication operates under real-world conditions by accounting for visitor volume, visitor characteristics, and weather. Based on registered tree damage incidents, our results show that both communication types effectively reduced the number of tree damage incidents by 57% compared to days without communication. During communication periods, visitors more often refrained from making campfires or relied on provided firewood. The two communication strategies were similarly effective, challenging the common assumption in the literature that direct interaction works best. This suggests that simple, low-cost approaches to influencing visitor behavior can be powerful tools for environmental management, particularly in settings where staff capacity is limited.

Managing water resources in water-scarce regions requires rigorous monitoring and reliable forecasting. To address this, we developed RSAI (Remote-Sensing–Artificial-Intelligence), a reproducible computational workflow that couples Google Earth Engine (GEE) scripts with deep learning models. RSAI is designed to map the spatiotemporal trends of six hydrological variables and specifically predict monthly surface-water extent. The workflow was applied to the Coastal Algiers Basin (02 A) over the 2001–2022 period. Trend analysis using the Mann-Kendall test revealed a statistically significant decline in surface-water area (Sen’s slope = −1.03 km² year⁻¹, equivalent to a 36% loss), while climatic drivers (precipitation, temperature) showed non-significant trends, suggesting a decoupling driven by anthropogenic factors. For the predictive component, three neural network architectures (ANN, DNN, and LSTM) were trained on the GEE-derived time series using a 70/30% train-test split. The Deep Neural Network (DNN) achieved the most robust performance on the independent test set (R = 0.89, MAE = 0.36 km², RMSE = 46.31 km²), outperforming the LSTM and ANN models. Sensitivity analysis further confirmed the DNN’s robustness to sensor noise (Propagation Factor = 0.26). These results validate RSAI as a practical, transferable workflow for basin-scale hydrological monitoring and forecasting in data-limited Mediterranean regions.

Monitoring biodiversity in protected areas is essential to mitigate biodiversity loss and evaluate the effectiveness of conservation policies. Integrating satellite remote sensing technologies, ecological niche models, and time-series analyses of biodiversity trends offers a fast and robust approach for assessing habitat suitability changes and species vulnerability over time. In this study, we implemented a framework combining these tools to monitor biodiversity in the Montesinho/Nogueira Special Conservation Area (Northeast Portugal). Using the MaxEnt algorithm, we generated ecological niche models for 342 species based on a time series (2001–2023) of remote sensing data from the Moderate-Resolution Imaging Spectroradiometer (MODIS) sensor. We analysed habitat suitability trends with the Mann-Kendall test to detect changes in habitat quality, as a metric of species vulnerability for individual species, five major taxonomic groups (vascular flora, amphibians, reptiles, birds, and mammals), functional groups (e.g. climate affinity, habitat type, diet, activity, reproduction), and conservation status (regional and European levels). Our study revealed a significant decline in habitat suitability over the past two decades, impacting all taxonomic groups and ecological functions. We observed a high variability in habitat suitability trends among species and taxonomic/functional groups, highlighting the complexity of biodiversity responses to environmental changes. Functional traits such as climatic affinity, trophic level or habitat specialisation were associated with variable rates of habitat decline, with species of Atlantic affinity, species associated with croplands and wetlands, and species specialised in insectivorous diets being at higher risk. Overall, these findings emphasise the need for comprehensive biodiversity monitoring programmes and demonstrate the utility of our approach to inform evidence-based conservation strategies in protected areas globally.

Anadromous salmonid recovery faces major challenges at high-head dams where volitional passage is limited. For obsolete structures, dam removal may be the only sustainable long-term solution, but at active hydroelectric dams, trap-and-haul facilities remain one of the few viable options for restoring fish passage connectivity. These facilities provide an assisted migration strategy, enabling juvenile transport downstream and adult transport upstream, and thus serve as a two-way conservation tool. Despite their increasing use, there remains considerable uncertainty about what “trap-and-haul” entails. Facilities range from simple, seasonal barriers and traps used to estimate run size, migration rates, behavioral patterns, and restoration effects, to highly engineered systems incorporating technical fishways, sorting facilities, and water-to-water transfer. The latter allows programmatic review, population-specific management, and adaptive strategies. We reviewed 37 trap-and-haul facilities in the Pacific Northwest (North America) to summarize key design and operational elements, including: (1) facility information; (2) species transported and numbers; (3) attraction and fishway flow rates and water sources; (4) trapping system types; (5) hydraulic drop per pool and energy dissipation factors; (6) attraction water diffuser type and source; (7) intake screen and cleaner types; and (8) presence of water-to-water transfer. Because existing data can guide development of new facilities, this review offers valuable insights not only for the Pacific Northwest but also for European hydropower operators facing similar challenges under the European Union Restoration Law, Habitat Directive, Water Framework Directive, and Eel Regulations.

Recently, the resist–accept–direct (RAD) framework has emerged as a conceptualized tool for managing ecosystem change. Yet, its application remains limited and uneven across ecological, social, and economic dimensions. To assess how RAD has been implemented to date, we conducted a systematic literature review using a structured PI(E)CO-based search and screening process. Of 473 documents identified, 19 contained case studies and met our inclusion criteria, highlighting the still-early use of RAD in practice. Most case studies focused on resist approaches along the ecological axis, with fewer fully incorporating social or economic considerations. Climate change and biodiversity loss were the most frequently addressed stressors. From our findings and assessed case studies, we developed a RAD strategy advice checklist, designed to guide practitioners in assessing potential trade-offs and implementation constraints, illustrated by a case study from southern Ontario, Canada. Our synthesis assesses the current state of RAD application, laying the groundwork for future knowledge sharing, real-time learning, and the development of broader decision-support networks.

Ecological restoration is increasingly recognized as a key strategy to enhance ecosystem services and mitigate climate change impacts. However, there is limited understanding of whether spatially prioritized restoration areas remain effective under future climate and land-use changes. This study evaluates the combined effects of climate scenarios (RCP 4.5 and RCP 8.5 for 2040–2069 and 2070–2099) and land-use and land-cover (LULC) scenarios (economic, trend, and green) on water ecosystem services (WES) in a river basin in southeastern Brazil. Climate and biophysical models from the InVEST suite were used to simulate sediment export and retention (erosion control), total nitrogen and phosphorus export and retention (water purification), and quickflow and baseflow (water supply). The green scenario assumes the restoration of areas previously identified as spatial priorities in a published study based on a multicriteria analysis of WES, in addition to legally protected areas such as riparian buffers and legal reserves established by the Brazilian Forest Code. Results indicate that climate change primarily affected water supply services, whereas LULC changes exerted stronger effects on erosion control and water purification. Targeted restoration of priority and legally protected areas reduced sediment and nutrient exports and partially buffered climate change impacts on water supply. The novelty of this study lies in testing the robustness of restoration areas prioritized under current conditions by evaluating their effectiveness across future climate and land-use scenarios, rather than defining restoration areas directly within the scenario modeling process.

Wildfires are natural components of arid and semi-arid ecosystems, yet climate change is amplifying their intensity and frequency, posing serious threats to ecosystem services essential for human well-being. This study presents a novel approach to reduce risk and protect ecosystem services under threat from flammability and climate change. In this regard, ten ecosystem services (carbon sequestration, heritage, food crops, livestock rates, shelter function, recreation, water production, soil formation, soil conservation, and beekeeping) were mapped using field data, the InVEST model, and GIS-based spatial analysis. Flammability and climate change risk were quantified using plant functional traits and environmental indicators. The results showed that the degree of climate change risk, flammability, and vulnerability of ecosystem services differed significantly between different land covers (p < 0.05). Water production and beekeeping were most threatened by climate change, while carbon sequestration, food, and livestock rates were most affected by fire. Through simplified causal-path analysis, we identified key drivers influencing the resilience of ecosystem services, and correlation analysis revealed that local environmental conditions can enhance service stability under disturbance. Overall, our findings provide a practical and transferable framework for forecasting vulnerabilities, reducing risk, and informing preventive and adaptive strategies that support both human well-being and long-term ecosystem sustainability.

Critical infrastructure (CI)—the essential systems and facilities that support various societal functions and economic activities—is increasingly at risk from climate change. In Canada, evidence on these risks remains fragmented and uneven. This study presents a systematic review of peer-reviewed research on climate change impacts on CI in Canada, following PRISMA guidelines and a PICO-informed search strategy. Existing research is concentrated geographically in Ontario and British Columbia and focused primarily on transportation, water, wastewater, and energy systems. Flooding, extreme precipitation, temperature variability, and permafrost thaw dominate the hazards examined, while wildfires and compound climate risks receive comparatively little attention. Across sectors, studies consistently document physical damage, service disruptions, economic losses, and cascading failures arising from infrastructure interdependencies. Non-climatic factors, including asset age, geographic location, governance arrangements, and investment levels, emerge as critical determinants of vulnerability and recovery. Methodologically, the literature is dominated by engineering and hydrological modeling, with limited integration of social, institutional, and equity considerations. This review synthesizes current knowledge, identifies persistent gaps, and outlines priorities for advancing climate-resilient CI research and policy in Canada.