A ridge-to-reef ecosystem microbial census reveals environmental reservoirs for animal and plant microbiomes.

Microbes are found in nearly every habitat and organism on the planet, where they are critical to host health, fitness, and metabolism. In most organisms, few microbes are inherited at birth; instead, acquiring microbiomes generally involves complicated interactions between the environment, hosts, and symbionts. Despite the criticality of microbiome acquisition, we know little about where hosts' microbes reside when not in or on hosts of interest. Because microbes span a continuum ranging from generalists associating with multiple hosts and habitats to specialists with narrower host ranges, identifying potential sources of microbial diversity that can contribute to the microbiomes of unrelated hosts is a gap in our understanding of microbiome assembly. Microbial dispersal attenuates with distance, so identifying sources and sinks requires data from microbiomes that are contemporary and near enough for potential microbial transmission. Here, we characterize microbiomes across adjacent terrestrial and aquatic hosts and habitats throughout an entire watershed, showing that the most species-poor microbiomes are partial subsets of the most species-rich and that microbiomes of plants and animals are nested within those of their environments. Furthermore, we show that the host and habitat range of a microbe within a single ecosystem predicts its global distribution, a relationship with implications for global microbial assembly processes. Thus, the tendency for microbes to occupy multiple habitats and unrelated hosts enables persistent microbiomes, even when host populations are disjunct. Our whole-watershed census demonstrates how a nested distribution of microbes, following the trophic hierarchies of hosts, can shape microbial acquisition.

Pathogenicity assessment of Arcobacter butzleri isolated from Canadian agricultural surface water.

BACKGROUND: Water is considered a source for the transmission of Arcobacter species to both humans and animals. This study was conducted to assess the prevalence, distribution, and pathogenicity of A. butzleri strains, which can potentially pose health risks to humans and animals. Cultures were isolated from surface waters of a mixed-use but predominately agricultural watershed in eastern Ontario, Canada. The detection of antimicrobial resistance (AMR) and virulence-associated genes (VAGs), as well as enterobacterial repetitive intergenic consensus-polymerase chain reaction (ERIC-PCR) assays were performed on 913 A. butzleri strains isolated from 11 agricultural sampling sites. RESULTS: All strains were resistant to one or more antimicrobial agents, with a high rate of resistance to clindamycin (99%) and chloramphenicol (77%), followed by azithromycin (48%) and nalidixic acid (49%). However, isolates showed a significantly (p < 0.05) high rate of susceptibility to tetracycline (1%), gentamycin (2%), ciprofloxacin (4%), and erythromycin (5%). Of the eight VAGs tested, ciaB, mviN, tlyA, and pldA were detected at high frequency (> 85%) compared to irgA (25%), hecB (19%), hecA (15%), and cj1349 (12%) genes. Co-occurrence analysis showed A. butzleri strains resistant to clindamycin, chloramphenicol, nalidixic acid, and azithromycin were positive for ciaB, tlyA, mviN and pldA VAGs. ERIC-PCR fingerprint analysis revealed high genetic similarity among strains isolated from three sites, and the genotypes were significantly associated with AMR and VAGs results, which highlight their potential environmental ubiquity and potential as pathogenic. CONCLUSIONS: The study results show that agricultural activities likely contribute to the contamination of A. butzleri in surface water. The findings underscore the importance of farm management practices in controlling the potential spread of A. butzleri and its associated health risks to humans and animals through contaminated water.

MRI in LARS1 deficiency-Spectrum, patterns, and correlation with acute neurological deterioration.

Leucine aminoacyl tRNA-synthetase 1 (LARS1)-deficiency (infantile liver failure syndrome type 1 (ILFS1)) has a multisystemic phenotype including fever-associated acute liver failure (ALF), chronic neurologic abnormalities, and encephalopathic episodes. In order to better characterize encephalopathic episodes and MRI changes, 35 cranial MRIs from 13 individuals with LARS1 deficiency were systematically assessed and neurological phenotype was analyzed. All individuals had developmental delay and 10/13 had seizures. Encephalopathic episodes in 8/13 were typically associated with infections, presented with seizures and reduced consciousness, mostly accompanied by hepatic dysfunction, and recovery in 17/19 episodes. Encephalopathy without hepatic dysfunction occurred in one individual after liver transplantation. On MRI, 5/7 individuals with MRI during acute encephalopathy had deep gray matter and brainstem changes. Supratentorial cortex involvement (6/13) and cerebellar watershed injury (4/13) occurred with seizures and/or encephalopathy. Abnormal brainstem contour on sagittal images (8/13), atrophy (8/13), and myelination delay (8/13) were not clearly associated with encephalopathy. The pattern of deep gray matter and brainstem changes are apparently characteristic of encephalopathy in LARS1-deficiency, differing from patterns of hepatic encephalopathy or metabolic stroke in organic acidurias and mitochondrial diseases. While the pathomechanism remains unclear, fever and energy deficit during infections might be causative; thus, sufficient glucose and protein intake along with pro-active fever management is suggested. As severe episodes were observed during influenza infections, we strongly recommend seasonal vaccination.

Characterizing Spatiotemporal Variability in Phosphorus Export across the United States through Bayesian Hierarchical Modeling.

Phosphorus inputs from anthropogenic activities are subject to hydrologic (riverine) export, causing water quality problems in downstream lakes and coastal systems. Nutrient budgets have been developed to quantify the amount of nutrients imported to and exported from various watersheds. However, at large spatial scales, estimates of hydrologic phosphorus export are usually unavailable. This study develops a Bayesian hierarchical model to estimate annual phosphorus export across the contiguous United States, considering agricultural inputs, urban inputs, and geogenic sources under varying precipitation conditions. The Bayesian framework allows for a systematic updating of prior information on export rates using an extensive calibration data set of riverine loadings. Furthermore, the hierarchical approach allows for spatial variation in export rates across major watersheds and ecoregions. Applying the model, we map hotspots of phosphorus loss across the United States and characterize the primary factors driving these losses. Results emphasize the importance of precipitation in determining hydrologic export rates for various anthropogenic inputs, especially agriculture. Our findings also emphasize the importance of phosphorus from geogenic sources in overall river export.

Wildfires Influence Mercury Transport, Methylation, and Bioaccumulation in Headwater Streams of the Pacific Northwest.

The increasing frequency and severity of wildfires are among the most visible impacts of climate change. However, the effects of wildfires on mercury (Hg) transformations and bioaccumulation in stream ecosystems are poorly understood. We sampled soils, water, sediment, in-stream leaf litter, periphyton, and aquatic invertebrates in 36 burned (one-year post fire) and 21 reference headwater streams across the northwestern U.S. to evaluate the effects of wildfire occurrence and severity on total Hg (THg) and methylmercury (MeHg) transport and bioaccumulation. Suspended particulate THg and MeHg concentrations were 89 and 178% greater in burned watersheds compared to unburned watersheds and increased with burn severity, likely associated with increased soil erosion. Concentrations of filter-passing THg were similar in burned and unburned watersheds, but filter-passing MeHg was 51% greater in burned watersheds, and suspended particles in burned watersheds were enriched in MeHg but not THg, suggesting higher MeHg production in burned watersheds. Among invertebrates, MeHg in grazers, filter-feeders, and collectors was 33, 48, and 251% greater in burned watersheds, respectively, but did not differ in shredders or predators. Thus, increasing wildfire frequency and severity may yield increased MeHg production, mobilization, and bioaccumulation in headwaters and increased transport of particulate THg and MeHg to downstream environments.

Cervical anterior spinal artery infarction associated with anomalous vertebral artery: a case report.

We report a unique case of cervical anterior spinal artery (ASA) infarction in a 49-year-old male with hypercholesterolemia and sleep apnea. The patient experienced sudden cervical pain, quadriparesis, areflexia, and urinary incontinence after swallowing a large food bolus. Imaging revealed an infarction at the C3-C5 levels and an anomalous right vertebral artery (VA) originating from the thoracic aorta, tightly enclosed between the aorta and a vertebral column with an anterior osteophyte. This aberrant VA was the primary vascular supply to the ASA, with no contribution from the left VA or supreme intercostal arteries. We propose that transient injury to the right VA, induced by compression between the aortic arch, the food bolus, and the osteophyte, led to temporary hypoperfusion of the ASA, causing a watershed ischemic injury in the mid cervical cord's anterior gray matter. The article also provides an in-depth discussion of the developmental and clinical characteristics associated with this rare vascular anomaly.

Groundwater potential delineation using geodetector based convolutional neural network in the Gunabay watershed of Ethiopia.

Groundwater potential delineation is essential for efficient water resource utilization and long-term development. The scarcity of potable and irrigation water has become a critical issue due to natural and anthropogenic activities in meeting the demands of human survival and productivity. With these constraints, groundwater resource is now being used extensively in Ethiopia. Therefore, an innovative convolutional neural network (CNN) is successfully applied in the Gunabay watershed to delineate groundwater potential based on the selected major influencing factors. Groundwater recharge, lithology, drainage density, lineament density, transmissivity, and geomorphology were selected as major influencing factors during the groundwater potential of the study area. For dataset training, 70% of samples were selected and 30% were used for serving out of the total 128 samples. The spatial distribution of groundwater potential has been classified into five groups: very low (10.72%), low (25.67%), moderate (31.62%), high (19.93%), and very high (12.06%). The area obtains high rainfall but has a very low amount of recharge due to lack of proper soil and water conservation structures. The major outcome of the study showed that moderate and low potential is dominant. Geodetoctor results revealed that the magnitude influences on groundwater potential have been ranked as transmissivity (0.48), recharge (0.26), lineament density (0.26), lithology (0.13), drainage density (0.12), and geomorphology (0.06). The model results showed that using a convolutional neural network (CNN), groundwater potentiality can be delineated with higher predictive capability and accuracy. CNN based AUC validation platform showed that, 81.58% and 86.84% were accrued from the accuracy of training and testing values, respectively. Based on the findings, the local government can receive technical assistance for groundwater exploration, and sustainable water resource development in the Gunabay watershed. Finally, the use of a detector-based deep learning algorithm can provide a new platform for industrial sectors, groundwater experts, scholars, and decision-makers.

A GIS-based modified PAP/RAC model and Caesium-137 approach for water erosion assessment in the Raouz catchment, Morocco.

Water erosion poses a significant environmental threat in the Mediterranean region, with pronounced impacts observed throughout Morocco. It impairs soil quality and disrupts both sediment transport and water availability. Contributing factors range from natural (climate, topography, and geology) to anthropogenic (land use, vegetation cover, and management). This study introduces an improved Priority Actions Program/Regional Activity Centre (PAP/RAC) model, enriched with GIS and the Caesium-137 (137Cs) technique, to investigate erosion within Morocco's Raouz basin. Enhanced with additional variables including soil types, slope length, rainfall erosion potential, slope orientation, soil moisture, and land surface temperature, the model transcends the classical approach, promoting granularity and precision in predictions. In addition to the comprehensive model, the 137Cs method, which discerns long-term soil erosion and redistribution, provides a dual-faceted validation, bolstering the robustness of this project's erosion risk evaluation. This study's outcomes underscore the gravity of the erosion hazard with significant soil depletion rates ranging from 8.1 to 20 t ha-1 yr-1, demonstrating the model's alignment with empirical data, affirming its utility. The modified PAP/RAC model concurs with the 137Cs data, demonstrating its usefulness for water erosion assessment and management in similar areas.

Evaluating and diagnosing ecosystem health of the "three-lake" watershed in Yuxi, Yunnan, China from 2010 to 2020 by PSR-KDE.

To carry out the diagnosis and evaluation of the ecosystem health in Yuxi three-lake watershed, this paper presents the changing trend of its health state, and predicts the future development. This also provides ideas for maintaining the regional ecosystem health, and then gradually improves the ecological environment quality. Taking Fuxian Lake, Qilu Lake and Xingyun Lake (the three-lake watershed) in Yuxi City, Yunnan Province, Southwest China as the research object, a model combining pressure-state-response and kernel density estimation (PSR-KDE) adopts to diagnose and evaluate the ecosystem health of the "three lake" watershed from 2010 to 2020, and the distribution map of ecosystem health index has obtained by the evaluation indexes integration based on GIS spatial analysis. Hence, the evaluation results have visualized on the map. The results show that: The distribution of ecosystem health index in the study area was 0.1530-0.7045 in 2010, 0.2056-0.7512 in 2015, and 0.2248-0.7662 in 2020. 0.12% was in the pathological area in 2010. After 2015, the pathological condition of ecosystem health has completely solved, and the proportion of unhealthy ecosystems was 11.95% in 2010, 7.38% in 2015, and 5.97% in 2020. The ecosystem health index of the study region was 0.5523 in 2010, 0.5807 in 2015, and 0.5815 in 2020, it indicates that the ecosystem was in a sub-health state. From 2010 to 2020, the ecosystem health around Qilu Lake was the most worrying, followed by the northwest of Fuxian Lake and the northern and southern regions of Xingyun Lake. The ecosystem health of the three-lake watershed showed significant improvement from 2010 to 2020. The study ecosystem health assessment and early warning in the three-lake watershed is significant to the ecological environment protection and management of the plateau lake basin, the restoration of the territorial space ecology and the economic development of the surrounding area.

Effects of terrestrial dissolved organic matter on the growth, photosynthesis and colonial morphology of Microcystis aeruginosa at different levels of iron.

Terrestrial dissolved organic matter (tDOM) holds great promise for controlling cyanobacteria blooms through watershed management. To identify tDOM that could inhibit the growth, photosynthesis and colony formation, unicellular Microcystis aeruginosa Kützing (FACHB-469) was cultivated and treated with varying concentrations of gallic acid, proline and tea polyphenols at different levels of iron. The results indicated that gallic acid and tea polyphenols could inhibit Microcystis growth by suppressing photosynthesis and colony formation by reducing extracellular polysaccharides (EPS) secretion. However, proline had no significant effect on the growth, photosynthesis, colony size and EPS content of Microcystis. Transcriptome analysis showed Microcystis may optimize the internal energy transfer mode of photosynthesis through the change of phycobilisome at different levels of iron. In addition, Microcystis adapted to different iron concentration environments by regulating the expression of genes associated with iron uptake and transport. These findings suggest that the effects of plant species on algal blooms should be considered in reforestation of watershed. This consideration necessitates finding a balance between the costs and benefits of controlling cyanobacteria blooms using tDOM.

Bilateral watershed infarcts due to hypoperfusion in the context of drug abuse: case report.

BACKGROUND: Watershed infarcts (WIs) are a distinct type of stroke with a varying clinical presentation that affects the border areas between the territories of two cerebral arteries and are typically associated with hemodynamic impairment and internal carotid artery stenosis. However, there is a paucity of data concerning its association with the history of recreational substance and drug abuse. METHODS/CASE REPORT: This case report presents a unique instance of bilateral internal watershed infarcts in a 23-year-old male with a history of polysubstance abuse, including methadone and cocaine. The patient's presentation included confusion, lower limb weakness, and systemic complications such as acute liver injury and myonecrosis, underlying the complexity of the clinical scenario. RESULTS: The investigation revealed no evidence of arterial stenosis or thrombosis, leading to the conclusion that the infarctions were likely precipitated by a total loss of consciousness due to substance abuse-related cerebral hypoperfusion and vasoconstriction. Methadone and cocaine, both implicated in vasoconstriction, lowering the seizure threshold and contributing to QTc prolongation, thus leading to loss of consciousness, were identified as potential triggers for the episode. CONCLUSIONS: In the young adult population, it is important to consider drug abuse as an etiological trigger for watershed infarcts, whereas the multi-system involvement and atypical presentation highlight the need for a comprehensive approach.

Terrestrial vegetation carbon sink analysis and driving mechanism identification in the Qinghai-Tibet Plateau.

The estimation of terrestrial carbon sinks in the Qinghai-Tibet Plateau (QTP) still faces significant uncertainties, and the spatiotemporal dynamics of terrestrial carbon sinks along altitudinal gradients remain unexplored. Moreover, the driving mechanisms of terrestrial carbon sinks at the watershed scale in the QTP continue to be lacking. To address these research gaps, based on multi-source remote sensing data and meteorological data, this study calculated the Net Ecosystem Productivity (NEP) in the QTP from 2000 to 2020 using the Modis NPP-soil respiration model. Through the coefficient of variation (CV), the Mann-Kendall test (MK), and the spatial autocorrelation methods, the spatial distribution pattern and spatiotemporal trends of NEP were investigated. Employing a pixel accumulation method, the variation of NEP along altitudinal gradients was explored. Grey relation analysis, Pearson correlation analysis, and Geographical detector (GD) were used to investigate the driving mechanisms of NEP at the watershed scale. Results showed that: (1) the terrestrial ecosystem in the QTP served as a carbon sink, which produced a total of 2.04 Pg C from 2000 to 2020, and the multi-year average of total carbon sinks was 96.92 Tg C; (2) the spatial distribution of NEP shows a decreasing change from southeast to northwest, and the clustering characteristic of NEP is significant at the watershed scale; (3) the elevation of 4507 m we proposed is likely to be a key threshold for biophysical processes of the terrestrial ecosystems in the QTP; (4) the fluctuation and change trend of carbon sources and carbon sinks show significant differences between the East and West; (5) at the watershed scale, precipitation and temperature play a dominant role in the variation of NEP, while the impact of human activities on NEP variation is weak. Our study aims to address the existing knowledge gaps and provide valuable insights into the management of terrestrial carbon sinks in QTP.

Biogenic elements-informed assessment of the impact of human activities on river ecosystems.

River ecosystems, acting as pivotal conduits linking terrestrial, marine, and atmospheric realms, have faced significant disturbances due to human exploitation of their resources. Recent years have witnessed a heightened intensification of human activities, adversely affecting the equilibrium of water ecosystems. To systematically study the various factors that affect river ecosystems under human activities, we introduce a universally applicable approach that considers the diversity of watersheds, biogenic elements, and human activities. Using this method, this application uncovers the sensitive human activity types, biogenic factors, and species significantly influencing river biodiversity within the study area. Incorporating statistical modelling, sensitivity screening, and advanced correlation analyses within a random forest regression framework, Sensitive biogenic elements and biological types affected by human activities were identified in typical watersheds, and the stability of different aquatic ecosystems was evaluated. Suggestions for watershed management measures were proposed When human activities affect the degree of water resource development and utilization, the forms of sensitive biogenic elements include DIC and Tsi; When human activities affect the discharge of pollutants into rivers, the forms of sensitive biogenic elements include TP, PP, and DEP, and the ratio composition includes TC: TN, TC: TP, TP: TSi, and TN: TP, This study pioneers a novel method for assessing human impacts on river ecosystems and successfully applies this approach to inform management decisions for river segments and tributaries in the middle and upper reaches of the Yangtze River basin. thereby enhancing our understanding of the consequences of human-induced impacts on biodiversity.

Dual stable isotopes to rethink the watershed-scale spatiotemporal interaction between surface water and groundwater.

The interaction between groundwater and surface water, including their recharge relationship and ratio, is crucial for water cycling, management, and pollution control. However, accurately estimating their spatiotemporal interaction at the watershed scale remains challenging. In this study, we used dual stable isotopes (δ18O, δ2H, d-excess, and lc-excess) and hydrochemistry methods to rethink spatiotemporal interaction at the Yiluo River watershed in central China. We collected 20 groundwater and 40 surface water samples over four periods in two seasons (dry and wet). Our results showed that in the downstream region, groundwater recharged surface water in the dry season while surface water recharged groundwater in the wet season, with average recharge ratios of 89.82% and 90.02%, respectively. In the midstream region, surface water recharged groundwater in both seasons with average ratios of 93.79% and 91.35%. In contrast, in the upstream region, groundwater recharged surface water in both seasons with ratios of 67.35% and 76.89%. Seasonal changes in the recharge relationship between surface water and groundwater in the downstream region also been found. Our findings provide valuable insights for watershed-scale water resource and pollution management.

How much nutrient reaches a stream: Insights from a hybrid model and implications for watershed nitrogen export and removal.

Excess nitrogen (N) discharged into streams and rivers degrades freshwater quality and threatens ecosystems worldwide. Land use patterns may influence riverine N export, yet the effect of location on N export and removal is not fully understood. We proposed a hybrid model to analyze N export and removal within the watersheds. The proposed model is satisfied for the riverine N modelling. The KGE and R2 are 0.75 and 0.72 in the calibration period which are 0.76 and 0.61 in the validation period. Human-impacted land use may modify the N yield in the watershed, and the net N export from built-up to the in-stream system was highest in the urbanized sub-watersheds (0.81), followed by the agricultural sub-watersheds (0.88), and forested sub-watersheds (0.96). Agricultural activities make a large contribution to the N exports in the watersheds, and the mean N input from the agricultural land use to in-stream were 2069-4353 kg km-2 yr-1. Besides, the excess inputs of N by overapplication of fertilizer and manure during the agricultural activities may increase legacy N in soil and groundwater. Biological processes for the riverine N removal may be controlled by the available substrate in the freshwater system, and temperature sensitivity of denitrification is highest in the flood seasons, especially for the human-impacted sub-watersheds. The riverine biological processes may be limited by other competitions. Our model results provide evidence that quantity and location of specific land use may control biogeochemistry within watersheds. We demonstrate the need to understand nutrient export and removal within watersheds by improving the representation of spatial patterns in existing watershed models, and we consider this study to be a new effort for the spatially explicit modeling to support land-use based N management in watersheds.

A novel approach to identify priority areas for optimal nutrient management in mixed land-use watersheds through nutrient budget assessment.

Excessive nutrient supply in agricultural regions has led to various environmental issues, thereby requiring concentrated management owing to its persistent upward trend. Nutrient budgets (NBs), a vital agricultural environmental indicator, are employed for nutrient management in agricultural areas, using data surveyed by administrative agencies. However, the spatial extent of nutrient data for nutrient budgeting is limited by administrative boundaries according to the surveying organization, posing challenges in interpreting spatial patterns at the watershed level. In this study, a novel approach was developed to identify priority nutrient management areas by applying hot spot spatial analysis to watershed-level NBs, considering hydrological characteristics. This method was applied to approximately 850 subwatersheds across the Republic of Korea, where land cover characteristics are complex. Reassessing nutrient budgets at the watershed scale, accounting for overlapping administrative boundary areas and crop cultivation ratios, indicated similar levels between the two methods. Hot spot analysis revealed that watersheds with elevated NBs mirrored the spatial patterns of livestock excreta and cropland. The spatial distribution characteristics of watersheds with high nutrient levels in rivers corresponded with the concentration characteristics of industrial and commercial areas. Therefore, applying watershed-level NBs based on land cover ratios that consider nutrient input characteristics in agricultural regions is deemed appropriate for selecting priority nutrient management areas. Collectively, this study presents a method for selecting nutrient management priority areas by simultaneously considering the spatial characteristics of various environmental factors, such as land cover, livestock excreta, river water quality, and land area-based watershed-specific NBs. The proposed approach, considering mixed land cover characteristics, is anticipated to be valuable for selecting priority management areas in watersheds with diverse pollution sources. Future research is needed to explore nutrient budgets within watersheds, the influence of land use on pollution sources, and their correlation with water quality.

Sediment source fingerprints of natural processes and anthropogenic pressures: A contribution to manage the Paraopeba River basin impacted by the B1 tailings dam collapse.

Understanding the origins of sediment transport in river systems is crucial for effective watershed management, especially after catastrophic events. This information is essential for the development of integrated strategies that guarantee water security in river basins. The present study aimed to investigate the rupture of the B1 tailings dam of the Córrego do Feijão mine, which drastically affected the Brumadinho region (Minas Gerais, Brazil). To address this issue, a confluence-based sediment fingerprinting approach was developed through the SedSAT model. Uncertainty was assessed through Monte Carlo simulations and Mean Absolute Error (MAE). Estimates of the overall average contributions of each tributary were quantified for each station and annually during the period 2019-2021. It was observed that the sampling point PT-09, closest to the dam breach, contributed to almost 80% of the Paraopeba River in 2019. Despite the dredging efforts, this percentage increased to 90% in 2020 due to the need to restore the highly degraded area. Additionally, the main tributaries contributing to sediment increase in the river are Manso River "TT-03" (almost 36%), associated with an area with a high percentage of urban land use, and Cedro stream "TT-07" (almost 71%), whose geology promotes erosion, leading to higher sediment concentration. Uncertainties arise from the limited number of available tracers, variations caused by dredging activities, and reduced data in 2020 due to the pandemic. Parameters such as land use, riparian vegetation degradation, downstream basin geology, and increased precipitation are key factors for successfully assessing tributary contributions to the Paraopeba River. The obtained results are promising for a preliminary analysis, allowing the quantification of key areas due to higher erosion and studying how this disaster affected the watershed. This information is crucial for improving decision-making, environmental governance, and the development of mitigating measures to ensure water security. This study is pioneering in evaluating this methodology in watersheds affected by environmental disasters, where restoration efforts are ongoing.

Synergies and trade-offs of ecosystem services affected by land use structures of small watershed in the Loess Plateau.

The Chinese government has implemented a series of ecological restoration projects in the Loess Plateau (LP), and the surface cover changed dramatically, impacting the ecosystem services (ESs) greatly. In this study, we used K-means clustering to classify the land use structures (LUSs) of the LP from 1990 to 2015 at the small watershed scale, and investigated the effects of LUS on water supply (WS), soil conservation (SC), and carbon sequestration (CS, expressed as NPP) with constraint lines. The values of WS and SC were obtained from the InVEST simulation, validated by the hydrographic station data. The results showed that the LUSs in LP were cropland structure (CLS, distinguished with CS), forest structure (FS), grassland structure (GS), crop-grassland structure (CGS), crop-forest-grassland structure (CFGS) and a very few areas of barren structure (BS). The proportion of dominant land use in those LUSs with a balance of WS, SC, and CS was 0.6-0.7 (cropland in CLS), 0.5 (forest in FS), 0.45/0.4 (cropland/grassland in CGS), 0.75 to 0.85 (grassland in GS), and 0.15/0.4/0.25 to 0.35 (cropland/forest/grassland in CFGS), respectively. The types of constraint curves of ESs for those LUSs involves hump-shaped curve, negative convex, half-concave-waved curve and concave-waved curve. This study proposed a method to objectively delineate LUS and improved the constraint line method to make it suitable for cases with less data, innovatively presenting the variation of ESs inside LUSs, which may provide a reference for optimal land planning and sustainable development of social-ecological systems.

Use of one-dimensional CNN for input data size reduction in LSTM for improved computational efficiency and accuracy in hourly rainfall-runoff modeling.

A deep learning architecture, denoted as CNNsLSTM, is proposed for hourly rainfall-runoff modeling in this study. The architecture involves a serial coupling of the one-dimensional convolutional neural network (1D-CNN) and the long short-term memory (LSTM) network. In the proposed framework, multiple layers of the CNN component process long-term hourly meteorological time series data, while the LSTM component handles short-term meteorological time series data and utilizes the extracted features from the 1D-CNN. In order to demonstrate the effectiveness of the proposed approach, it was implemented for hourly rainfall-runoff modeling in the Ishikari River watershed, Japan. A meteorological dataset, including precipitation, air temperature, evapotranspiration, longwave radiation, and shortwave radiation, was utilized as input. The results of the proposed approach (CNNsLSTM) were compared with those of previously proposed deep learning approaches used in hydrologic modeling, such as 1D-CNN, LSTM with only hourly inputs (LSTMwHour), a parallel architecture of 1D-CNN and LSTM (CNNpLSTM), and the LSTM architecture, which uses both daily and hourly input data (LSTMwDpH). Meteorological and runoff datasets were separated into training, validation, and test periods to train the deep learning model without overfitting, and evaluate the model with an independent dataset. The proposed approach clearly improved estimation accuracy compared to previously utilized deep learning approaches in rainfall = runoff modeling. In comparison with the observed flows, the median values of the Nash-Sutcliffe efficiency for the test period were 0.455-0.469 for 1D-CNN, 0.639-0.656 for CNNpLSTM, 0.745 for LSTMwHour, 0.831 for LSTMwDpH, and 0.865-0.873 for the proposed CNNsLSTM. Furthermore, the proposed CNNsLSTM reduced the median root mean square error (RMSE) of 1D-CNN by 50.2%-51.4%, CNNpLSTM by 37.4%-40.8%, LSTMwHour by 27.3%-29.5%, and LSTMwDpH by 10.6%-13.4%. Particularly, the proposed CNNsLSTM improved the estimations for high flows (≧75th percentile) and peak flows (≧95th percentile). The computational speed of LSTMwDpH is the fastest among the five architectures. Although the computation speed of CNNsLSTM is slower than LSTMwDpH's, it is still 6.9-7.9 times faster than that of LSTMwHour. Therefore, the proposed CNNsLSTM would be an effective approach for flood management and hydraulic structure design, mainly under climate change conditions that require estimating hourly river flows using meteorological datasets.

How does payment for watershed ecosystem services alleviate farmer poverty in conservation intervention areas? Evidence from China.

Payment for watershed ecosystem services (PES) has been applied to water conservation and poverty reduction in an increasing number of developing countries. This study evaluates the effect of payment for watershed ecosystem services on farmers' income in conservation intervention areas using a difference-in-differences model and a panel dataset that covers 18 countries in the Xin'an River Basin in China for fourteen consecutive years (2006-2019). The results show that PES programs increase farmers' income and that the poverty reduction effect is sustainable. The PES programs mainly increase the farmers' income in conservation intervention areas through two paths: triggering the transfer of agricultural labor and promoting agricultural restructuring. PES programs are pro-poor and more conducive to increasing the income of farmers in upstream regions and counties with lower levels of economic development. This paper reveals the specific role played by PES in promoting rural poverty reduction in developing countries, providing insights into alleviating the contradiction between poverty and watershed ecosystem protection.