Search Results (316)

Water level prediction for the backwater reaches of large reservoirs is a critical step for many tasks of reservoir operation and flood control, directly affecting the sustainability of water–energy–ecosystem balance. The problem is very challenging due to arbitrarily complicated hydrodynamic mechanisms and various types of influencing factors. This paper proposes a method based on time series decomposition for feature extraction from data samples by a novel neural architecture. To accurately quantify the complex hydraulic conditions of large reservoirs, we investigate a type of neural basis expansion to incorporate exogenous variables (e.g., reservoir regulation and storage, upstream confluence, and flow travel time). Unlike the traditional LSTM-based methods, our method is free from recurrent architecture. It can exploit backward and forward residual links as a backbone to ensure the validity and structural distribution of the information during the model training. Extensive experiments on real data of the Three Gorges Reservoir are implemented to evaluate the performance of the proposed method. The results show that the proposed method shows state-of-the-art performance on all evaluation metrics and can provide reliable technical support for the refined and sustainable operation of large reservoirs. Full article

Seasonal snowpack and snowmelt are critical regulators of forest ecosystem functioning in temperate, boreal, montane, and alpine regions. Snowpack acts as a temporary water and energy reservoir, while snowmelt determines the seasonal availability of water and influences ecosystem processes during the growing season. Climate change is altering snowfall patterns, snow accumulation, and melt timing, with consequences for forest productivity, resilience, and disturbance dynamics. This review synthesizes current knowledge on snow–forest interactions and identifies major research trends, methodological approaches, and remaining knowledge gaps. The study combines a bibliometric analysis and a qualitative literature review based on publications indexed in the Scopus and Web of Science databases. A total of 695 publications were included in the bibliometric dataset and analyzed to assess temporal trends, geographical patterns, research themes, and the ecological consequences of changing snow dynamics in forests. Representative studies from this dataset were subsequently synthesized to evaluate the influence of snowpack and snowmelt on forest ecosystem functioning, resilience, and sustainability. The reviewed literature shows that snowpack and snowmelt strongly regulate forest water availability, soil thermal conditions, nutrient cycling, vegetation responses, and carbon dynamics. Changes in snow regimes, particularly reduced snow accumulation and earlier melt, can increase the risk of soil freezing, modify moisture conditions, intensify water stress, and affect ecosystem carbon balance. However, the magnitude and direction of these effects depend on forest type, species composition, climate, and landscape characteristics. Forest structure also plays an important role in controlling snow interception, accumulation, persistence, and melt processes. The bibliometric analysis indicates a rapid increase in research interest in snow–forest interactions over the last two decades, with major contributions from the United States, Canada, China, and Northern Europe. Environmental sciences, hydrology, and ecology were the dominant research areas. Despite substantial progress, uncertainties remain regarding long-term ecosystem responses, species-specific vulnerabilities, and the interactions between declining snow cover and other climate-driven disturbances. This review emphasizes that understanding snowpack and snowmelt dynamics is essential for predicting forest ecosystem responses to climate change and for improving sustainable forest management and watershed conservation strategies in snow-dependent regions. Full article

Sustainable agricultural development requires regional agricultural systems to balance output growth, resource efficiency, ecological protection, and long-term resilience. In mountainous and ecologically sensitive regions, identifying the development constraints and statistically derived marginal contribution thresholds of agriculture is essential for promoting green transformation and sustainable land use. Taking Yunnan Province, China, as a representative plateau mountainous agricultural region, this study uses provincial annual data from 1990 to 2023 to quantitatively identify the key drivers and threshold characteristics of agricultural development under multidimensional constraints. A multidimensional indicator system was constructed covering fiscal and investment support, agricultural production inputs, rural infrastructure, and labor and population conditions. Ridge regression was employed to address multicollinearity among explanatory variables, Bootstrap approximate inference was used to improve the robustness of coefficient estimation, and the SHAP interpretation framework was introduced to rank key driving factors and identify marginal contribution thresholds. By integrating ridge regression, Bootstrap approximate inference, SHAP-based contribution ranking, and threshold identification, the proposed framework advances prior agricultural sustainability studies by linking coefficient-based factor analysis with interpretable marginal contribution thresholds under conditions of high multicollinearity and multidimensional resource constraints. The results show that agricultural development in Yunnan is characterized by multidimensional resource and infrastructure constraints. Rural electricity consumption, total reservoir storage capacity, fixed asset investment in agriculture, forestry, animal husbandry and fisheries, local public fiscal budget expenditure, and agricultural population generally act as positive supporting factors. Rural electricity consumption is the most stable and core driver across the aggregate and three sectoral models. In contrast, pesticide and fertilizer inputs show significant negative associations in most models, suggesting that future agricultural development in Yunnan is unlikely to be sustainably supported by continued expansion of high-intensity chemical inputs. Sectoral heterogeneity is also evident: agriculture and animal husbandry are more dependent on energy, water resources, and mechanization, whereas forestry shows a more distinct operational structure. The SHAP dependence analysis identifies several statistically derived marginal contribution thresholds, including rural electricity consumption of approximately 6.055 billion kWh, total reservoir storage capacity of approximately 10.395 billion m³, total agricultural machinery power of approximately 19.8324 million kW, pesticide use of approximately 37,500 tons, and fertilizer application of approximately 1.5238 million tons. These values should be interpreted as empirical transition points in the modeled marginal contributions rather than definitive biophysical ecological limits. They indicate that the sustainability-related constraint structure of agricultural development in Yunnan is not a single output ceiling but a composite interval shaped by infrastructure support capacity, factor allocation conditions, and the declining marginal contribution of high-intensity chemical inputs. The findings provide directional quantitative evidence for sustainable agricultural governance, agricultural green transformation, and differentiated policy discussion in mountainous agricultural regions and offer reference implications for advancing SDG 2 and SDG 15 through the coordination of food-related production, resource use efficiency, and ecosystem conservation. The identified thresholds should be interpreted as model-derived marginal contribution transition points rather than operational policy cutoffs or directly enforceable ecological standards. Full article

Habitats are fundamental for maintaining biodiversity, supporting ecological processes, and delivering essential ecosystem services such as carbon sequestration, water regulation, and soil conservation. Habitat degradation has become an increasingly critical environmental concern, particularly in coastal regions where anthropogenic pressures intersect with natural dynamics under the accelerating impacts of climate change. (1) This study explores the spatially stratified heterogeneity and underlying driving factors of habitat quality and degradation in Çeşme, a rapidly developing coastal district in western Türkiye. (2) The InVEST Habitat Quality model was applied to assess both habitat quality and habitat degradation across the study area for the years 2017 and 2024. The GeoDetector method was applied to analyze the spatial heterogeneity in habitat quality and degradation, enabling the assessment of dominant environmental and anthropogenic drivers, including urban development pressure, tourism activities, energy-related infrastructure, road density, and vegetation conditions. (3) Night-time light intensity showed the highest explanatory power among the tested variables, although its absolute explanatory power for habitat degradation remained limited, while protection status represented a contrasting human-related factor associated with higher habitat quality. (4) These findings underscore the importance of carefully directing human interventions to balance development pressures with effective conservation strategies. Full article

The rapid proliferation of electric vehicles (EVs) has positioned Vehicle-to-Grid (V2G) technology as an important enabler for mitigating grid congestion, accelerating the energy transition, and supporting the sustainable transition of regional energy systems. However, recent incentive mechanisms often fail to balance EV users’ willingness to participate with the economic viability of intermediary operators, thereby hindering effective multi-party collaboration in Regional Integrated Energy System (RIES). To address this challenge, this paper proposes a novel commission-based service fee mechanism for V2G incentive mechanisms to dynamically regulate revenue distribution among Integrated Energy System Operator (IESO), Energy Supplier (ES), Charging Station Operator (CSO), and Electric Vehicle Aggregator (EVA). The study further examines how different incentive strategies affect V2G market liquidity. Case studies indicate that the proposed strategy significantly increases effective V2G transaction power while preserving CSO profit margins and encouraging EV participation. The results also indicate that the reward rate, commission rate, and subsidy have nonlinear effects on V2G transaction performance and should be set within reasonable ranges. The proposed model also exhibits superior performance in enhancing system economic benefits and promoting multi-agent coordination. It provides an actionable framework for sustaining CSO participation under upper-level subsidy mechanisms while improving the long-term commercial viability and ecological sustainability of smart-grid ecosystems. These findings provide practical guidance for designing incentive policies that facilitate the low-carbon energy transition and sustainable smart-grid development. Full article

Environmental gradients associated with continentality shape terrestrial ecosystems by modifying biodiversity patterns, community structure, and ecosystem functioning. In arid ecosystems, where water and thermal constraints are pronounced, soil organisms represent sensitive indicators of environmental change. Soil nematodes, due to their functional diversity encompassing bacterivores, fungivores, herbivores, omnivores, and predators, constitute effective bioindicators of soil health. We hypothesized that increasing continentality (thermal amplitude) would progressively reduce nematode diversity and functional complexity while altering CUE and metabolic footprints through community compositional shifts. A total of 130 soil samples were collected across three bioclimatic zones (island, coastal, and semi-continental) within the Arganeraie Biosphere Reserve, Morocco, and analyzed for nematode abundance, diversity, trophic structure, ecological indices, and functional traits. Nematode abundance and richness were significantly higher in the island zone compared to the coastal and semi-continental zones, while Shannon diversity did not differ significantly. The island zone exhibited a balanced trophic structure with higher proportions of bacteribores, fungivores, herbivores, and omnivores–predators, than the coastal and semi-continental zones. CUE values were consistently low (<0.5) across all zones, with the widest distribution in the island zone. Thermal amplitude was negatively associated with nematode biomass (R = −0.36), production (R = −0.27), and all trophic footprints, with herbivores showing the steepest decline (R = −0.51). Notably, total energy flux remained relatively stable despite reductions in diversity and trophic complexity, suggesting functional redundancy within dominant bacterivore guilds. These findings support the hypothesis that increasing continentality is associated with reduced nematode diversity and functional complexity, alongside altered carbon processing efficiency. This study underscores the value of integrating trophic, metabolic, and energetic approaches for assessing soil health vulnerability in Mediterranean agroecosystems under climate change. Full article

Vegetation is an important component of ecosystems and plays an important role in carbon balance, water balance, and energy conversion. The spatial and temporal changes in the normalized difference vegetation index (NDVI), water resources, and hydrometeorological factors in southwest China between 2003 and 2020 were investigated using multisource remote sensing data. Correlation analyses were performed to assess the correlation among NDVI, water resource changes, and hydrometeorological factors with different time lags. A stepwise regression model with different lag times was constructed to clarify the effects of four topographic factors and eight climatic factors on NDVI, and the following conclusions were obtained: (1) NDVI increased from 2003 to 2020, and the increase became obvious after 2012. (2) NDVI was considerably affected by alterations in the soil water content caused by natural changes. The correlation of NDVI with evapotranspiration and precipitation was high, followed by NDVI’s correlation with surface temperature. The spatial distribution of the positive correlation between NDVI and evapotranspiration and NDVI and precipitation was relatively consistent, and a positive correlation was observed in most parts of Southwest China. (3) The hydrometeorological factors mainly affected NDVI with a lag of 0–1 month, and the correlation was high in western Sichuan and most of Yunnan. In Yunnan, Available Water Capacity (AWC) affected NDVI with a lag of 0–2 months; the lag was 0–1 month in western Yunnan and 1–2 months in eastern Yunnan. (4) In terms of different vertical heights, the NDVI in the regions with altitudes higher than 3000 m was affected by climate change, especially evapotranspiration and precipitation. (5) Digital Elevation Model (DEM), Latitude (Lat), Evapotranspiration (ET), Precipitation (PRCP), Land Surface Temperature (LST), and NDVI were closely related in the construction of stepwise regression models with different lag times. Full article

The water–energy–food (WEF) system acts as a critical nexus of social–ecological systems. However, rapid urbanization has intensified the regional imbalance in the supply and demand of ecosystem services (ESs). Clarifying the spatiotemporal matching of ecosystem services supply and demand (ESSD) within the WEF framework and revealing the driving mechanisms behind such imbalances are essential to formulating reasonable zoning schemes and targeted optimization strategies for the coordinated development of the regional WEF system. Taking Zhejiang Province as a case study, this research uses water yield (WY), carbon sequestration (CS), and grain production (GP) to characterize the WEF nexus system. It uses the InVEST model to assess WY and CS, applies spatial allocation methods to characterize GP, and integrates socioeconomic data to quantify the demand for the above three ESs. All indicators were standardized and integrated with equal weights to further clarify the comprehensive levels of ESSD. By integrating the Geodetector and K-Means clustering methods, the study analyzes the supply–demand matching of ecosystem services and its driving mechanisms in Zhejiang Province during this period, thereby exploring ecological management zoning and optimization strategies within the WEF system. The study findings indicate that: (1) From the supply perspective, Zhejiang Province’s WY services demonstrate a trend of elevated activity in the southwest and diminished presence in the northeast; high values for CS services are predominantly found in the vegetation-rich areas of the northwest, while high values for GP services are clustered in the northern Zhejiang Plain; from the demand perspective, high values for all three ESs in Zhejiang Province are primarily located in economically active, densely populated urban areas. (2) The correlation between ESSD within Zhejiang Province’s WEF system exhibits significant spatial heterogeneity and is driven by the combined effects of natural and socioeconomic factors, with the interaction between these two factors often producing a synergistic effect. Specifically, annual average precipitation and population density are the dominant factors influencing WY services, NDVI and human footprint are the dominant factors influencing CS services, and population density and GDP are the dominant factors influencing GP services. (3) From 2000 to 2020, the supply–demand ratio for comprehensive ESs in Zhejiang Province generally followed a pattern of being lower in the east and higher in the west. The supply–demand imbalance of ESs intensified in the core areas of eastern cities, whereas the western regions maintained a relatively sound supply–demand balance. (4) The study classifies the counties in Zhejiang Province into four ecological management zones—ecological stable zones, ecological conservation zones, ecological control zones, and ecological restoration zones—and explores differentiated approaches to optimizing these zones and implementing control strategies. Full article

Urban carbon neutrality is increasingly shaped by cross-regional interactions rather than a closed balance between local emissions and sequestration. From an open-system perspective, this study conceptualizes urban carbon neutrality as the outcome of interactions between embodied carbon transfer (ECT) and carbon sequestration service flows (CSSFs). Using panel data for 297 Chinese cities in 2012, 2017, and 2022, an integrated measurement framework is developed to examine spatiotemporal patterns, typological heterogeneity, and driving mechanisms. The results reveal significant disparities in emission responsibility and ecological support across city types. Ecological conservation-oriented cities act as major carbon sequestration providers, while industrial- and service-oriented cities face higher emission pressures and weaker local sequestration capacity. The joint effects of ECT and CSSF reshape urban carbon neutrality through responsibility reallocation and ecological support transfer, enhancing overall performance while intensifying inter-city differentiation. Spatial Durbin model results indicate that carbon neutrality is jointly influenced by socioeconomic development, energy structure, factor mobility, ecological conditions, and institutional regulation, with both local and spillover effects. These findings suggest that urban carbon neutrality is a relational process embedded in production–consumption linkages and ecosystem service networks, highlighting the need for differentiated governance pathways to support coordinated mitigation and ecological compensation. Full article

There is a strong global increase in the installation of renewable energy power plants, due to increasing energy demand in the electricity generation sector and fast cost reduction. Recent studies indicate that the installation and operation of photovoltaic (PV) power plants have negligible microclimatic effects, although there are minor effects on night temperature in some cases, which, however, do not justify climate or environmental change. The development of solar energy and the installation and operation of PV power plants serve as a key solution for the energy transition to reduce carbon emissions and to address global warming. Despite the benefit of emission reduction, the deployment of solar energy through the installation of solar power plants causes land cover changes and may have minor effects on the surface energy balance by modifying roughness and albedo, biodiversity by disturbing habitats, and water resources by requiring water for cooling and cleaning. These changes may also lead to minor climatic, ecological, and social impacts. The objective of the paper consists of assessing the potential microclimatic effects of photovoltaic power plants based on satellite-based land surface temperature (LST) analyses. Specifically, the potential change in the land surface temperature, both under photovoltaic panels and on the panels, in relation to the temperature of the surrounding area is being examined in this study. The implementation is conducted in Mediterranean ecosystems, which are considered vulnerable agroecosystems due to increased climate variability. The final Landsat-based time series analysis further supports this synthesis, reporting that monthly LST differences between the PV Park and surrounding area are negligible and do not indicate a meaningful microclimate alteration attributable to PV operations. Accordingly, the evidence supports the core conclusion: utility-scale PV deployment does not constitute a driver of climate change, and the documented effects are best understood as localized surface–atmosphere energy-balance perturbations whose sign and magnitude depend on land cover, seasonality, and operation. Full article

Despite growing scholarly attention to electric vehicle adoption in Southeast Asia, no study has systematically compared battery electric vehicle (BEV) readiness across Thailand, Lao PDR, and Vietnam using a unified demand–supply framework. This paper develops and applies a seven-dimension BEV Country Readiness Assessment framework encompassing supply-side factors (parts and materials sourcing, manufacturing, and after-sales support), demand, and enabling environment (legal and regulatory, government support, and market development), with maturity scores (1–5) assigned across 16 sub-dimensions based on national statistics, industry reports, and primary field research conducted between August 2024 and March 2026. Thailand scores highest overall (3.43/5.0) as a regional production hub with balanced readiness; Vietnam follows (3.26/5.0) with the highest demand score driven by VinFast’s ecosystem; and Lao PDR scores lowest (1.95/5.0) yet exhibits a notably high EV/ICE registration ratio driven by fleet-led adoption in a very small absolute market. The findings reveal complementary rather than competitive roles within the regional BEV value chain, with energy security, supply chain dependency on China, and institutional capacity identified as critical determinants of long-term readiness. Full article

The growing demand for renewable energy, together with the need to mitigate climate change and promote more sustainable agriculture systems, has stimulated interest in energy crops. In this context, invasive alien plant species (IAPS), which have progressively colonized abandoned farmland, degraded ecosystems, and marginal areas, represent a key bioresource. IAPS have a dual nature combining high ecological invasiveness and fast growing rate with notable energetic potential. These aspects have generated a still ongoing debate among farm managers, ecologists, and policymakers regarding their role within the future bioeconomy. The present study provides a review of the IAPS black locust (Robinia pseudoacacia L.) on its real benefits as a source of bioenergy, ecological impact, and the management strategies adopted. We examine the trade-offs between containment efforts and use for renewable bioenergy production, particularly in marginal areas where few alternatives exist. This review highlights the need for stratified site-specific approaches that balance biodiversity conservation with bioresource exploitation. Finally, this study also contributes to the ongoing discussion on whether IAPS should be regarded primarily as a management challenge or a multifunctional bioresource, as in the production of bioenergy. Full article

Against the backdrop of urbanization and global warming, reducing carbon emissions and achieving carbon neutrality have emerged as focal points in current urban ecological research. Urban green infrastructure (UGI) serves as the primary natural carbon sink within cities; therefore, investigating and optimizing its carbon sequestration services is a crucial step toward realizing carbon neutrality and fostering sustainable urban development. As the core components of urban ecosystems, urban parks provide essential ecosystem services that play a pivotal role in expanding carbon sinks, facilitating energy conservation and emission reduction, and enhancing urban climate resilience. This paper takes 20 parks in Linyi City’s central urban area as examples, systematically quantifies the carbon sequestration effect of urban parks in the central urban area of Linyi City from 2019 to 2024 using methods such as the Carnegie–Ames–Stanford Approach (CASA) and the gravity model, and quantitatively evaluates the equity of urban residents’ access to these services. The study shows that the overall annual average carbon sequestration rate of urban parks in Linyi City’s central area over nearly six years ranges from 202.02 gC·m⁻²·a⁻¹ to 279.31 gC·m⁻²·a⁻¹, while individual park annual averages range from 171.29 to 332.76 gC·m⁻²·a⁻¹, falling within the normal range for cities at the same latitude; in terms of vegetation carbon sequestration capacity, woody plant communities dominate in this region, with annual average carbon sequestration rates approximately 10% higher than those dominated by herbaceous vegetation. In terms of intrinsic activity performance of carbon sequestration, overall, woody-dominated plant communities exhibit greater stability and resilience under extreme weather conditions, experiencing smaller impacts on ecological functions but longer recovery cycles to peak levels. Regarding equity in the supply and demand of ecosystem services, the Gini coefficient in the study area is 0.59, indicating an extremely imbalanced state; within the same park service range, up to 60% of residents do not benefit from carbon sequestration ecosystem services. The urban supply–demand mismatch reveals that approximately 20% of the population resides in high-demand–low-supply areas, experiencing extreme ecological deprivation; only about 13% of the population falls into the high-demand–high-supply category, this group being the high-benefit recipients who enjoy both spatial convenience and high-quality ecological welfare. The theoretical implications for urban green space planning: according to the results, merely expanding park green space area to increase per capita access is myopic and inadvisable in central urban park planning. Instead, greater emphasis should be placed on enhancing ecological service levels beyond basic area requirements, comprehensively improving vegetation quality and ecosystem service capacity of parks. In old urban areas constrained by land use, the hierarchical structure of vegetation should be strengthened, and micro green spaces should have enhanced ecological service capabilities to improve residents’ access rights through higher service quality. In newly developed urban areas, planning should balance quantity and quality to serve more people and alleviate urban ecological pressures. Overall, by quantitatively assessing the carbon sequestration capacity and the socio-spatial equity of ecosystem services provided by urban parks in Linyi City, this study offers robust empirical evidence and methodological tools for sustainable urban planning, ultimately fostering the sustainable development of urban ecosystems. Full article

Large trees are keystone ecological structures that sustain biodiversity and ecosystem services, particularly in human-altered landscapes. However, their persistence is increasingly threatened by land-use change, urban expansion, and inadequate monitoring. This study develops and validates a scalable, automated framework for monitoring the loss of large individual trees using satellite image time series and breakpoint detection. We compared four spectral indices (SIs): Enhanced Vegetation Index 2–EVI2; Normalized Burn Ratio–NBR; Normalized Difference Red Edge–NDRE, and the Normalized Difference Vegetation Index–NDVI derived from Sentinel-2 imagery (2015–2025) for 691 georeferenced trees in Lousada, northern Portugal. Data were accessed and processed in Google Earth Engine and analyzed using a custom R-based workflow, including cloud masking, gap-filling, temporal interpolation, upper-envelope smoothing, deseasonalization, and break detection. Five breakpoint detection algorithms were compared: BFAST, energy-divisive, linear regression of structural changes, wild-binary segmentation, and change point models. Detected breakpoints were subsequently post-validated to determine whether they were associated with declines in SIs, using three pre-/post-breakpoint methods: comparisons of short- and long-term medians and a randomized trend analysis. As a baseline, these algorithms/post-validation logic were compared against the Continuous Change Detection and Classification (CCDC) approach. The results indicate moderate but consistent break detection performance, with a maximum balanced accuracy of 73% (for EVI2 or NDVI and using the energy-divisive algorithm coupled with the long-term median post-validator) under conservative validation criteria and high specificity for surviving trees. CCDC ranked comparatively lower at 62%. Algorithm performance varied substantially, with the energy-divisive providing the most conservative detection and the wild-binary segmentation yielding higher sensitivity. Performance was further influenced by tree structural attributes and species identity, with larger, taller and isolated trees, as well as particular genera, showing higher detection accuracy, with genus Eucalyptus, Tilia and Celtis yielding top performance results (79–65%) and Quercus, Castanea and Platanus the lowest (62–60%). By integrating satellite observations with large-tree inventory data from the Green Giants citizen science project, this study demonstrates the potential of decentralized, Earth observation-based monitoring to support tree-level loss assessments in fragmented landscapes. The proposed framework provides a transferable foundation for wide-scale monitoring of large trees in peri-urban and mixed-use environments. Full article

The accumulation of microplastics in aquatic ecosystems poses a significant threat to fish physiology and welfare. This study investigated the impact of exposure to virgin polystyrene microplastics (15 µm) on energy balance and welfare in goldfish (Carassius auratus). Fish were exposed for 14 days, and the effects were assessed through an integrated analysis of behavioral, metabolic, neuroendocrine, and physiological parameters. Microplastic exposure significantly reduces feed intake and feed anticipatory activity, indicating a potent anorexigenic effect. This effect was driven by neuroendocrine disruption, characterized by the downregulation of orexigenic neuropeptides (npy, agrp, hcrt) and the upregulation of anorexigenic signaling (pomca, cartpt, lepa). Simultaneously, exposed fish exhibited increased oxygen consumption, suggesting elevated metabolic demands. These factors converged to impaired growth and reduced hepatosomatic index, suggesting altered energy allocation. Furthermore, microplastic exposure induced anxiety-like responses and increased plasma cortisol levels, confirming the activation of the physiological stress response. Overall, these findings demonstrate that microplastics disrupt energy homeostasis and trigger behavioral shifts that ultimately compromise fish welfare and the biological resilience of aquatic species. Full article