Ecohydrology最新文献

Algae-based diets offer a sustainable approach to enhancing mussel aquaculture, with potential benefits for ecohydrological systems through improved biofiltration and nutrient cycling. This study evaluates the effects of three algal feed types—powdered Spirulina platensis, freeze-dried Ulva rigida and frozen Nannochloropsis sp.—on the growth performance and fatty acid composition of Mediterranean mussels (Mytilus galloprovincialis Lamarck 1819) across three size classes (small, medium, large) under controlled conditions. A total of 810 mussels were fed for 28 days, and biometric and lipid parameters were measured. Mussels fed with Spirulina exhibited the highest growth rates and docosahexaenoic acid (DHA) levels, with small individuals increasing by 14.7% in shell length and 25% in body weight. Nannochloropsis led to significant enrichment of eicosapentaenoic acid (EPA), particularly in medium mussels, while Ulva resulted in lower growth and higher saturated and omega-6 fatty acids. The results demonstrate clear size-dependent responses to algal diets and emphasize the nutritional and ecological advantages of Spirulina and Nannochloropsis. It is well established that mussels respond to algal diets in terms of growth and lipid composition, and the present findings confirm these diet-dependent differences. These algae-based feeds not only improve mussel quality but also support the development of sustainable aquaculture systems by enhancing filter-feeding efficiency and reducing the environmental footprint of bivalve farming. The study provides evidence that algae-integrated diets can play a key role in sustainable water quality management and the design of multifunctional aquaculture systems aligned with ecosystem-based approaches. These findings not only enhance mussel quality but also contribute to water quality regulation through improved particle clearance and filtration, reinforcing the role of algae-based diets in the design of ecohydrological aquaculture systems that integrate biological processes with hydrological functions. These improvements in growth and lipid profile also support enhanced filtration activity and nutrient assimilation, indicating that algae-based diets may strengthen the ecohydrological functionality of mussels in integrated aquaculture systems.

The plant communities of Poyang Lake, constituting the foundational element of the wetland ecosystem, are integral to crucial ecological processes including energy flow, biodiversity sustenance, water purification and hydrological regulation. Consequently, they serve an irreplaceable function in preserving the stability and ecosystem services of the region. This study uses Landsat 8, Sentinel-2 optical images and Sentinel-1 SAR images as data sources to extract spectral reflectance, index features and texture features from optical images as well as radar backscattering features from SAR images, constructing a multidimensional feature dataset. The Recursive Feature Elimination algorithm is employed to perform feature optimization on the dataset. Three classification schemes with different feature combinations are designed, and based on the random forest classifier, the impacts of multisource data fusion and feature optimization on the accuracy of plant community identification are investigated. The results demonstrate that the feature optimization-based classification scheme attains the highest accuracy, reaching 93.42% overall accuracy with a Kappa coefficient of 0.93. Meanwhile, the optical-SAR data fusion scheme shows significantly superior performance compared with the optical-only scheme, delivering a 13.04% enhancement in overall classification accuracy. This study provides a scientific reference for remote sensing classification of wetland plant communities and supports biodiversity conservation and ecological management in the Poyang Lake wetland.

Hydropower development significantly impacts the fragile fish habitats in river reaches of the Tibetan Plateau. To support the conservation of fish resources in these reaches, this study developed a physical habitat evaluation model for spawning grounds based on the ecological requirements of key fish species. An artificial neural network (ANN) model was employed to fit the response relationships between spawning ground indicators and environmental factors. Results indicate that water temperature is a critical factor influencing spawning grounds. In natural river reaches, suitable spawning periods occur primarily in the afternoon. In contrast, water temperature in dam-downstream reaches is significantly affected by hydropower operations, leading to distinct differences in spawning rhythms compared to natural reaches. The Weighted Usable Area (WUA) and Patch Number (PN) of spawning grounds initially increase and then decrease with rising flow. The ANN model effectively fits the response relationships between environmental factors and WUA and PN (R² > 0.87). Water temperature exhibits a stronger influence, while flow primarily affects WUA and PN by altering suitable substrate area. This study presents the development and application of physical and ANN models for fish spawning grounds in hydropower-affected river reaches of the Tibetan Plateau. The findings reveal the distribution patterns of spawning grounds and identify key environmental factors. These results provide methodological references and scientific evidence for the evaluation and conservation of fish resources, supporting the sustainable management of native fish populations in plateau rivers.

Snowmelt from montane forests is a critical water resource in the western United States. Forest managers use treatments like selective thinning to encourage resilient ecosystems for wildfire mitigation and wildlife habitat. There is also interest in managing forests to optimize snowpack retention to improve water resources in a changing climate, but detailed studies and management recommendations are limited. We explore the controls on snowpack accumulation using a newly developed light detection and ranging (lidar) point-cloud filtering method and a local open-reference area approach using data collected over gradients in forest structure across multiple snow seasons in the Sagehen Creek Basin (SCB) in the central Sierra Nevada, California, USA. Consistent with previous studies with much more limited snow and vegetation measurements, we show there is ~25% more snow accumulation in open areas relative to forested areas. Random forest (RF) outputs indicate that forest structure metrics explain a greater amount of accumulation variance than terrain metrics, and the greatest potential to increase snow accumulation via thinning occurs when the fraction of vegetation (fVEG) is > 30%. Our results suggest that considering both coarse (e.g., fVEG) and fine-scale (e.g., the arrangement of canopy) canopy information is integral to predict snowpack response to canopy disturbance at many relevant management scales (i.e., 100 m² to 100 km²). The corresponding simple decision support tool, developed with data from SCB, can assess the utility of completed and planned forest restoration over a larger spatial extent to strategically target areas with the highest potential snowpack response. Our new lidar processing methods are easily transferrable to other areas where they could improve snowpack management from forest restoration.

Despite having important implications for water resources, the climatic dependence of forest thinning impacts on snowpack is poorly quantified. In this study, we used a high-resolution snow model to understand the impact of forest thinning on snowpack in Arizona under contrasting climate conditions, leading to ephemeral vs. seasonal snowpack conditions. The model is evaluated using a spatiotemporally extensive set of snowpack measurements and is run for the same set of pre- and post-thinning forest patch geometry using two meteorological forcing datasets representing locally mid- and high-elevation climate conditions. Although the high-elevation climate is only 1°C cooler and has 20% more winter precipitation, it leads to markedly different snowpack conditions, i.e., twice as long-lasting snowpack, less mid-winter ablation events and ~60% larger at its peak. For both climates, forest thinning increased peak snow water equivalent (SWE) and liquid water input (LWI), but it decreased snow cover duration (SCD) only for the high-elevation climate. Total sublimation losses decreased from ~35% of wintertime precipitation pre-thinning to ~25% post-thinning for the high-elevation climate and from ~25% to ~15% for the mid-elevation climate. Generally, a 10% reduction in canopy cover resulted in ~4.5% more snowfall reaching the ground, and a 10-day decrease in SCD reduced the fraction of winter precipitation lost to snowpack sublimation by ~2%. Post-thinning changes in forest patch geometry were also important as larger canopy gaps had more LWI, and areas with warmer canopy edges had lower peak SWE and SCD.

The lack of information on what constitutes suitable habitat for native freshwater mussels can limit restoration efforts. While many species reside in silt–sand–gravel substrates, species such as the Spectaclecase (Cumberlandia monodonta) and Salamander (Simpsonaias ambigua) mussels are thought to be associated with rock structures (e.g., wing dams and rock outcrops) in rivers. Our objective was to assess if hydroacoustic technology could be used to quantify physical habitat features for C. monodonta and S. ambigua. Multibeam echosounder, acoustic Doppler current profiler, sidescan sonar and underwater videography were used to quantify water depth, substrate hardness, bed roughness and bed slope of the riverbed, water velocity, shear velocity and the degree of rock clustering at six sites in the Saint Croix River, Minnesota. The sites varied in type of rock structures and relative abundances of both species. The strength of the associations among physical habitat features and mussel abundance was weak; R² values were typically < 0.5. However, species-specific differences in microhabitat were observed. For example, C. monodonta was typically observed at sites with higher velocity and shear velocity compared to S. ambigua. Mussel abundance was greatest at sites that contained crevices of sand surrounded by boulders and bedrock. Future refinements in hydroacoustic methods and post-processing computations could improve predictions. Information on habitat features from occupied and unoccupied sites could help resource managers characterize existing occupied habitats, identify potential reintroduction areas and implement restoration programmes.

Understanding the disasters that arise from climate change in advance and developing necessary adaptation plans are crucial to mitigate their impacts. Drought progresses slowly but can profoundly impact entire ecosystems and human livelihoods. Many indices are introduced to analyse drought. This study aims to quantify the spatiotemporal response of groundwater systems to long-term meteorological and hydrological trends in the Seyhan Basin using the Groundwater Drought Index (GWI). It tests the hypothesis that groundwater drought exhibits a lagged but regionally distinct response to climatic drivers, especially in semiarid regions where topography, distance to the sea and anthropogenic withdrawals vary significantly. The years 1970–2016 were selected for analysing meteorological data and 1970–2015 for analysing hydrological data. Fifteen measurements from 24 meteorological observation stations (15 within the basin and 9 in neighbouring basins), 5 evaporation observation stations, 20 stream-gauging stations and 9 groundwater observation wells were utilised. The effects of analysed trends on GWI were examined, and climate change has been observed to impact drought parameters from a holistic perspective. Selecting an index appropriate to regional characteristics should be considered, and updating measurements is crucial for accurate predictions.

Pinus ponderosa is a widespread conifer species across western North America, yet its intraspecific variability in drought response remains understudied, particularly at subseasonal time scales. We investigated how intraspecific tree dominance influences physiological and anatomical growth responses to warm-season precipitation pulses in a semi-arid montane forest in southern Nevada, USA. Using high-resolution dendrochronology, quantitative wood anatomy and dual-isotope (δ¹⁸O, δ¹³C) analysis of tree-ring cellulose, we compared dominant (old-growth) and codominant (mature) trees during two growing seasons: one impacted by a remnant tropical storm that provided an uncharacteristic pulse of precipitation to southern Nevada during the monsoon season (2015) and one with drier conditions with little monsoonal precipitation (2016). Codominant trees exhibited stronger and more immediate growth responses to warm-season precipitation, characterized by increased tracheid production and cellulose δ¹⁸O values that matched those of warm-season precipitation δ¹⁸O values, indicating shallow soil water use. In contrast, dominant trees relied more on deeper soil moisture and showed more conservative growth strategies. These divergent strategies suggest that intraspecific dominance mediates access to water and controls the sensitivity of growth to seasonal precipitation variability, highlighting the importance of intraspecific variation in shaping forest resilience and climate adaptation strategies under increasing drought and climate extremes.