Molecular characteristics of dissolved organic phosphorus in watershed runoff: Coupled influences of land use and precipitation.

Land use and precipitation are two major factors affecting phosphorus (P) pollution of watershed runoff. However, molecular characterization of dissolved organic phosphorus (DOP) in runoff under the joint influences of land use and precipitation remains limited. This study used Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) to study the molecular characteristics of DOP in a typical P-polluted watershed with spatially variable land use and precipitation. The results showed that low precipitation and intense human activity, including phosphate mining and associated industries, resulted in the accumulation of aliphatic DOP compounds in the upper reaches, characterized by low aromaticity and low biological stability. Higher precipitation and widespread agriculture in the middle and lower reaches resulted in highly unsaturated DOP compounds with high biological stability constituting a higher proportion, compared to in the upper reaches. While, under similar precipitation, more aliphatic DOP compounds characterized by lower aromaticity and higher saturation were enriched in the lower reaches due to more influence from urban runoff relative to the middle reaches. Photochemical and/or microbial processes did result in changes in the characteristics of DOP compounds during runoff processes due to the prevalence of low molecular weight and low O/C bioavailable aliphatic DOP molecules in the upper reaches, which were increasingly transformed into refractory compounds from the upper to middle reaches. The results of this study can increase the understanding of the joint impacts of land use and precipitation on DOP compounds in watershed runoff.

Modelling Alternative Economic Incentive Schemes for Semi-Natural Grassland Conservation in Estonia.

Semi-natural grasslands (SNGLs) in Estonia are threatened by abandonment. This threat is leading to concerns about the degradation of biodiversity within grassland communities. Despite the high relevance of economic incentives in this context, how such incentives influence land managers' decision-making regarding the agricultural use of SNGLs has not been investigated. To obtain its socio-ecological implications for policy-making, we developed regionally specific agricultural scenarios (compensation payments, livestock capacity, hey export, and bioenergy production) and an interdisciplinary modelling approach that made it possible to simulate agricultural land use changes through land managers' responses to varied economic conditions. Through this approach, we found that some economic factors hampered the use of SNGLs: the moderate profitability of beef production, labour shortages, and the relatively high profitability of mulching. We observed a positive relationship between SNGLs and habitat suitability for breeding and feeding birds. However, due to the high maintenance costs of SNGLs, the modelling results indicated that increasing the use of SNGLs through public budgets caused crowding-out effects, i.e., the deteriorating market integration of regional agriculture. This study emphasises the need for policy measures aimed at cost-effective, labour-efficient management practices for SNGLs.

A social-ecological approach to support equitable land use decision-making.

Human-driven land use change can result in unequitable outcomes in the provision and appropriation of ecosystem services (ES). To better address equity-related effects of land use change in decision-making, analyses of land use and ES changes under different land use management alternatives should incorporate ecological and social information and take a disaggregated approach to ES analysis. Because such approaches are still scarce in the literature, we present a generalized social-ecological approach to support equitable land use decision-making (in terms of process and outcomes) and an example of its application to a case study in southwestern Ethiopia. We propose a six-step approach that combines scenario planning with equity-focused, disaggregated analyses of ES. Its application in our study area made equity-related effects of land use change explicit through the recognition of different beneficiary groups, value types, and spatial locations. We recommend the application of our approach in other contexts, especially in the Global South.

From chocolate to palm oil: The future of Indonesia's cocoa plantations.

Indonesia is the world's third largest cocoa producer, but production is decreasing since 2011. We revisited cocoa farmers for an environmental assessment in Luwu Timur, Sulawesi, 7 months after a socio-economic survey on cocoa certification outcomes and observed many cocoa plantations being converted into oil palm and maize. Including our field data as well as secondary data on commodity prices and yields, we outline reasons for cocoa conversion, potential consequences for biodiversity, and assess the future outlook for the Indonesian cocoa sector. Low cocoa productivity, volatile cocoa prices and higher revenue for oil palm, among others, drive land-use change. If shade trees are cut during cocoa conversion, it may have negative implications for biodiversity. Solutions to low soil fertility, omnipresent pests and diseases, and stable producer prices are needed to increase profitability of cocoa and prevent conversion of cocoa agroforests to oil palm monocultures.

Does habitat modification impact morphology, performance, and inflammatory responses in an amphibian with limited dispersal capacity (Lisssotriton helveticus)?

The environment of an organism exerts selective pressures that affect mobility, feeding, reproduction as well as predator-prey and conspecific interactions. Land use changes induced by human activities modify these selective pressures and may result in the adaptation of organisms. Amphibians are ectotherms that typically show a biphasic life cycle with an aquatic and terrestrial phase, which makes them particularly sensitive to environmental change. We studied the impact of habitat modifications on palmate newt populations in the Ile de France region across four types of habitats: urban, mixed, agricultural, and natural with at least two replicates for each habitat type. We measured the morphology of newts using callipers, quantified maximal running and swimming speed and acceleration using high-speed video recordings, and quantified the swelling of the hind limb linked to an inflammatory reaction. Our results show that in urban habitats, newts are larger and heavier and have a better body condition. Females, moreover, have a larger head in natural habitats, possibly due to diet specialisation of females during the breeding season. In mixed and agricultural habitats, newts have longer limbs and show a tendency to run faster, possibly associated with the selective pressures on movement in mixed habitats. Differences in inflammatory responses were observed between sexes but not habitat types. Overall, our results show differences in morphology and trends for differences in performance in newts living in different habitats suggesting that animals are adapting to human-induced changes in their environment.

Rethinking Urban Water Management Through Drivers-Pressures-States-Impacts-Responses Framework Application in Chennai, India.

Cities suffering water scarcity are projected to increase in the following decades. However, the application of standardized indicator frameworks for assessing urban water resource management problems is on an early stage. India is expected to have the highest urban population facing water scarcity in the world by 2050. In this study, the authors assess how the Drivers-Pressures-States-Impacts-Responses framework, a causal framework adopted by the European Environment Agency, can contribute to evaluate water management challenges in cities and apply it to Chennai, India´s fourth-largest urban agglomeration. The framework proved to be a helpful tool for the evaluation of water management challenges in cities by disentangling relationships between environmental indicators and structuring dispersed data that allows a better understanding for policymakers. The main drivers identified in Chennai were population growth and economic development which generated impacts such as loss of aquatic ecosystems, low water table, low water quality, and reduction of biodiversity and human health. As a response, better urban planning, projects for new water infrastructure, and water bodies restoration have been implemented. Nevertheless, Chennai keeps facing difficulties to achieve proper water management. The severe hit of the COVID-19 pandemic on the Indian economy and its future management will be key for achievements related to water management.

Improving the identification of pollution source areas with catchment-resolution sensitivity analysis.

The significant impacts of total nitrogen (TN) and total phosphorus (TP) on riverine ecosystems underscores the critical need to identify the primary nutrient source areas in watersheds. This study aims to unravel the influences of terrain and land use types on mean monthly TN (TNM) and mean monthly TP (TPM) export across varying catchment resolutions in the Qiantang River Watershed of China. The findings of this study illuminated the critical role of topography in understanding nutrient dynamics, wielding a profound influence over water flow patterns and nutrient dispersion. Both land slope and Stream Power Index (SPI) displayed substantial negative correlations (r < -0.6) with TNM and TPM concentrations, whereas the Topographic Wetness Index (TWI) showed positive correlations with the nutrient indexes. In addition to terrain characteristics, impervious land surfaces had a positive correlation with nutrient concentrations, while grassland and forest areas exhibited negative correlations. Results further underscored the substantial influence of catchment resolution on correlations between watershed properties and riverine nutrient concentrations. It was imperative to choose an effective catchment resolution in watershed delineation - not too coarse, nor too fine - to accurately capture the topographic and land use impacts on nutrient dynamics. With the most appropriate catchment size (Catchment 700 km2), the critical pollution source areas for TN and TP pollution were identified, and thus could be used to guide future pollution reduction efforts. The study not only highlights the importance of identifying an appropriate catchment size for water pollution, but also emphasizes the necessity of effectively extracting critical pollution source areas to mitigate water nutrient pollution and increase the ecological integrity of the Qiantang River Watershed.

Derivation of ecotoxicologically acceptable Cu concentrations in soil from different land uses in South Korea.

This study aimed to establish ecotoxicologically acceptable Cu concentrations for soil-residing species by integrating the biotic ligand model and the species sensitivity distribution. Statistical analyses were performed on 35 soil solution samples collected from four distinct land use sites: residential, agricultural, forested, and industrial regions. The environmental parameters of these samples, including pH, dissolved organic carbon (DOC), Ca2⁺, Mg2⁺, K⁺, and Na⁺ concentrations, exhibited wide variations across the four regions. Specifically, pH and the concentrations of Mg2⁺, K⁺, and Na⁺ showed significant variability. Additionally, a strong correlation was observed between pH and Ca2⁺, as well as between the DOC concentration and Mg2⁺ and Na⁺. Using the biotic ligand model, we derived the half-maximal effective activities of Cu (EC50{Cu2+}) for 10 soil organisms based on the chemical compositions of the soil solution samples. Additionally, a species sensitivity distribution approach was employed to determine the 5% hazardous concentration (HC5) for soil biota, which was closely associated with DOC and Na⁺ concentrations, with Mg2⁺ playing a secondary role. We attributed these relationships to the formation of DOC complexes that mitigate Cu toxicity, along with competitive interactions with cations. Notably, HC5 values did not differ significantly across sampling sites (p = 0.523). Clustering based on environmental factors grouped the samples into four clusters, each containing soils from different land use types. However, the third cluster included an outlier from agricultural soil due to its unusually high pH and DOC levels. These findings suggest that it is crucial to consider site-specific soil characteristics when determining ecotoxicologically acceptable Cu concentrations, and soil solution characteristics do not always align with specific land use patterns.

Identifying resource-conscious and low-carbon agricultural development pathways through land use modelling.

Increasing agricultural production with current resources and technology may lead to increased GHG emissions. Additionally, large population countries like India face substantial challenges in terms of food demand, agro-ecological heterogeneity, carbon footprint and depleting natural resources, thus increasing the decision complexities for policymakers and planners. We aim to examine the potential of producing more food from available agricultural land with low-carbon (reduced GHG emissions) and resource-conscious (optimal resource use) options. The current study develops multiple calorie production and emission-centric land use using a land use optimization model wherein the calorie production and emission objective, resource and emissions constraints, and food production targets interact across multiple spatial levels. The capabilities of the developed model are demonstrated with a case study in India targeting ten crops (grown over two seasons) covering three food groups (cereals, legumes, and oilseeds). Three hypothetical scenarios for each objective of maximizing calories production (Calories-nation, Calories-group, Calories-crop) and minimizing GHG emissions (Emissions-nation, Emissions-group, Emissions-crop) are developed concerning targets of national crop production (Calories-nation, Emissions-nation), state food groups production (Calories-group, Emissions-group), and state crop production(Calories-crop, Emissions-crop), with different spatial levels of constraints. A maximum growth of 11% in calorie production is observed in Calories-nation while mitigating 2.5% emissions. Besides, the highest emission reduction of around 30% is observed in Emissions-group but with no change in calorie production. Emission scenarios can spare up to 14.8% land and 18.2% water, while calorie production-maximization scenarios can spare a maximum of 4.7% land and 6.5% water. The optimization-based methodology identifies the regions of altered land use by proposing appropriate crop substitution strategies, such as increasing oilseeds in Rajasthan and soybean in east Maharashtra. Many states show conservative production growth and emission reduction with state-level crop production targets (Calories-crop), suggesting crop redistribution within the state alone will not be sufficient unless improved technologies are introduced. The maximum growth and mitigation potential estimated in this study may be affected by climate shocks; therefore, introducing the improved technologies needs to be coupled with a crop redistribution mechanism to design climate-resilient and futuristic land use systems. The proposed land use model can be modified to incorporate climate change effects through consideration of scenarios of changed crop yields or through direct/indirect coupling with dynamic crop simulation models.

Adrenal and metabolic hormones demonstrate risk-reward trade-offs for African elephants foraging in human-dominated landscapes.

A key driver of the African savannah elephant population decline is the loss of habitat and associated human-elephant conflict. Elephant physiological responses to these pressures, however, are largely unknown. To address this knowledge gap, we evaluated faecal glucocorticoid metabolite (fGCM) concentrations as an indicator of adrenal activity and faecal thyroid metabolite (fT3) concentrations as an indicator of metabolic activity in relation to land use, livestock density, and human landscape modification, while controlling for the effects of seasonality and primary productivity (measured using the normalized difference vegetation index). Our best-fit model found that fGCM concentrations to be elevated during the dry season, in areas with higher human modification index values, and those with more agropastoral activities and livestock. There was also a negative relationship between primary productivity and fGCM concentrations. We found fT3 concentrations to be higher during the wet season, in agropastoral landscapes, in locations with higher human activity, and in areas with no livestock. This study highlights how elephants balance nutritional rewards and risks in foraging decisions when using human-dominated landscapes, results that can serve to better interpret elephant behaviour at the human-wildlife interface and contribute to more insightful conservation strategies.

Phenotypic and genotypic antimicrobial resistance patterns in honey bee (Apis mellifera L.) bacterial symbionts.

Antimicrobial resistance (AMR) is a major global public health problem. Nevertheless, the knowledge of the factors driving the spread of resistance among environmental microorganisms is limited, and few studies have been performed worldwide. Honey bees (Apis mellifera L.) have long been considered bioindicators of environmental pollution and more recently also of AMR. In this study, 53 bacterial strains isolated from the body surface of honey bees at three ontogenetic stages, collected from ten different geographic locations, were tested for their phenotypic and genotypic resistance to eight classes of the most widely used antimicrobials in human and veterinary medicine. Results showed that 83% of the strains were resistant to at least one antimicrobial and 62% were multidrug-resistant bacteria, with a prevalence of resistance to nalidixic acid, cefotaxime, and aztreonam. A high percentage of isolates harbouring at least one antimicrobial gene was also observed (85%). The gene encoding resistance to colistin mcr-1 was the most abundant, followed by those for tetracycline tetM and tetC. Geographical features influenced the distribution of these traits more than bacterial species or bee stage, supporting the use of honey bee colonies and their associated bacteria as indicators to monitor environmental resistance. This approach can improve the scientific understanding of this global threat by increasing data collection capacity.

Spatio-temporal analysis and prediction of land use land cover (LULC) change in Wular Lake, Jammu and Kashmir, India.

Landsat land use/land cover (LULC) data analysis to establish freshwater lakes' temporal and spatial distribution can provide a solid foundation for future ecological and environmental policy development to manage ecosystems better. Analysis of changes in LULC is a method that can be used to learn more about direct and indirect human interactions with the environment for sustainability. Neural network technology significantly facilitates mapping between asymmetric and high-dimensional data. This paper presents a methodological advancement that integrates the CA-ANN (cellular automata-artificial neural network) technique with the dynamic characteristics of the water body to forecast forthcoming water levels and their spatial distribution in "Wular Lake." We used remote sensing data from 2001 to 2021 with a 10-year interval to predict spatio-temporal change and LULC simulation. The validation of the calibration of predicted and accurate LULC maps for 2021 yielded a maximum kappa value of 0.86. Over the past three decades, the study region has seen an increase in a net change % in the impervious surface of 22.41% and in agricultural land by 52.02%, while water decreased by 14.12%, trees/forests decreased by 40.77%, shrubs decreased by 11.53%, and aquatic vegetation decreased by 4.14%. Multiple environmental challenges have arisen in the environmentally sustainable Wular Lake in the Kashmir Valley due to the vast land transformation, primarily due to human activities, and have been predominantly negative. The research acknowledges the importance of (LULC) analysis, recognizing it as a fundamental cornerstone for developing future ecological and environmental policy frameworks.

Linking sediment geochemistry with catchment processes, internal phosphorus loading and lake water quality.

Research in the field of sediment geochemistry suggests potential linkages between catchment processes (land use), internal phosphorus (P) loading and lake water quality, but evidence is still poorly quantified due to a limited amount of data. Here we address the issues based on a comprehensive data set from 27 lakes in southern Finland. Specifically, we aimed at: 1) elucidating factors behind spatial variations in sediment geochemistry; 2) assessing the impact of diagenetic transformation on sediment P regeneration across lakes based on the changes in the vertical distribution of sediment components; 3) exploring the role of the sediment P forms in internal P loading (IL), and 4) determining the impact of IL on lake water quality. The relationship between sediment P concentration and field area percentage (FA%) was statistically significant in (mainly eutrophic) lakes with catchments that included more than 10 % of fields. We found that sediment iron-bound P (Fe-P) increased with increasing FA%, which agrees with the high expected losses from the cultivated areas. Additionally, populated areas increased the pool of sediment Fe-P. Internal P loading was significantly positively related to both sediment Fe-P and sediment organic P (Org-P). However, Org-P was not significant (as the third predictor) in models that had a trophic state variable as the first predictor and Fe-P as the second predictor. Further, the vertical profiles of sediment components indicated a role of diagenetic transformations in the long-term sediment P release, especially in lakes with deeper maximum depth and longer water residence time. Finally, IL was significantly positively correlated to water quality variables including phytoplankton biomass, its proportion of cyanobacteria, chlorophyll a concentration and trophic state index. Our findings suggest that reduction of P losses from the field and populated areas will decrease internal P loads and increase water quality through a reduced pool of Fe-P.

Examining the Effects of Land Use, Salinity Gradient, and Water Pollution on Greenhouse Gas Emissions in Urbanized Estuaries.

Estuaries are significant contributors to greenhouse gases (GHGs) in waterways. However, the effects of human activities and ecological variables on GHG emissions in estuaries remain poorly understood. This study examines the patterns and causes of GHG emissions in the Scheldt Estuary, focusing on the roles of salinity, water contamination, and land use. The findings indicate that salinity negatively impacts the release of carbon dioxide (CO2) and nitrous oxide (N2O), likely due to reduced salt levels and cleaner water upstream. Water contamination's influence on GHG emissions was more pronounced in cleaner, upriver sites compared to saltier downstream locations. Specifically, CO2 emissions quadrupled, and N2O emissions tripled as water conditions worsened from healthy (near the mouth, bordered by agricultural land) to polluted (farther downstream, bordered by urban areas). Methane (CH4) emissions were significantly higher in aquatic locations than in salty sites. The reduced impact of contamination from downstream to the river mouth may be due to increasing population density. Urban sites emitted about twice as much CO2 and N2O as those in natural and industrial areas. Machine learning analysis also showed that fertilizers and organic enrichment, along with salinity, significantly increased GHG emissions. These results highlight the importance of understanding the interplay of salinity, water contamination, and land use in influencing GHG emissions in coastal ecosystems.

Isotopic and trace element record of changing metal source contributions to tropical freshwater Lake Naivasha (Kenya).

Lake Naivasha, Kenya's second-largest freshwater body is a wetland of international ecological importance and currently subjected to unprecedented anthropogenic influence. The study aims to chronologically reconstruct the main human activities and background weathering reactions that govern metal mobilizations into the lake and their potentially adverse effects on its ecological status. We combine extensive geochemical analyses (major, trace elements, Zn-Pb isotope ratios) in a dated lake sediment record and catchment rocks with remote sensing techniques. Downcore geochemical variations reflect natural ecosystem destabilizations occurring as early as the first half of the 20th century. These coincide with changes towards less radiogenic Pb-isotope values which persist towards the top of the core (206Pb/207Pb = 1.243 at core base ~1843, to 206Pb/207Pb = 1.225 at ~1978). We interpret the land-clearance for agricultural purposes on the Aberdare Range and documented early aviation activities as vectors of this early Pb-isotope excursion. The overlapping Pb-isotope signatures between sediment sources and anthropogenic contributions challenges a straightforward deconvolution of the two. Our conservative model calculations suggest, nevertheless, that an addition of up to ~1.8 % Pb-gasoline influx to the total Pb flux, peaking in the 1980s is able to explain the Pb distribution trend. Homogeneous Zn-isotope compositions in sediments deposited until ~1970s (δ66/64Zn = 0.216-0.225 ‰) do not follow major hydro-climatic events or anthropogenic forcing but reflect lake-specific natural cycling. Subsequent higher variations to both heavier (up to δ66/64Zn = 0.242 ±â€¯0.005 ‰) and lighter (down to δ66/64Zn = 0.184 ±â€¯0.003 ‰) Zn-isotope values are contemporaneous with intensification of large-scale horticultural industry in the catchment. Together with supporting indicators, the lighter Zn-isotope compositions in youngest analysed sediments (21st century) are attributable to increased biological productivity (algal blooms) and ongoing lake eutrophication. Our study demonstrates the applicability of the heavy metal isotope tool to reconstruct human influences on lake environments with complex geological settings such as the East African Rift System.

Noise pollution assessment and management in rare earth mining areas: a case study of Kollam, Kerala, India.

Noise pollution is an unintentional consequence of mining activities, needing rigorous assessment, monitoring, and mitigation techniques to reduce its impact on local residents and ecosystems. The study specifically examines the noise pollution from rare earth mining activities in the Neendakara-Kayamkulam (NK) coastal belt, Kollam, Kerala, India, a region rich in ilmenite, rutile, sillimanite, zircon, and monazite. Despite the known environmental and health impacts of noise pollution, there is limited specific data on its magnitude and sources in this region, as well as a lack of effective mitigation strategies tailored to rare earth mining operations. Studies have indicated that mining operations, such as the movement of heavy mineral sands, considerably elevate noise levels, which have an effect on the environment's quality and public health. This study seeks to fill the gap by geospatial mapping and assessing the noise levels and recommend measures to effectively mitigate noise pollution. Systematic noise measurements were conducted at 48 suitable locations within the NK coastal belt, including residential, commercial, industrial, coastal, and silence zones. The noise levels vary from 49.1 dB(A) near a religious place to 82.4 dB(A) near the local industry. The study employs geospatial noise mapping and land cover superimposition to implement class-specific mitigation measures for noise pollution in a coastal vicinity mixed land use area, including natural and vegetative barriers, operational scheduling, zoning, and land use planning.

Regional ecological risk assessment through the application of production-living-ecology land use function indicators: a case study of the eco-economic zone of Yellow River Delta.

To date, land use structure information has been employed extensively for ecological risk assessment (ERA) purpose in regional/landscape scales; in contrast, land use function (LUF) information-based ERA research is still scarce. Therefore, it is necessary to carry out more ERA case studies in macroscale with the help of pertinent LUF indicators. As an important way to construct production-living-ecology LUF indexes, this study employs the weighted stacking method and related economic statistical data for regional ecological risk assessment (RERA) purpose within Yellow River Delta High-efficiency Eco-economic Zone (YRDHEZ), China. This YRDHEZ-RERA research pointed out that (1) it was rational to use a series of economic statistical data to more comprehensively and precisely characterize regional production and living function grades in YRDHEZ. (2) The Yellow River Delta had lower agriculture and non-agriculture production functions, whereas the rest of the zone had higher production functions. (3) Most people lived in the south part, whereas north coastal zone had very low population density; the east part had higher per capita disposable income of urban/rural households than that of west. (4) The south part of the zone had higher production/living functions and integrated ecological risk source intensity than those of north coastal zone, whereas the coastal zone had higher ecology function, eco-environmental vulnerability, and final integrated ecological risk than those of inland region. As for regional ecological risk management, establishing nature reserve with strict spatial governance for coastal/estuarine wetlands and coordinating production/ecology functions of coastal salterns/breeding ponds are relevant feasible measures.

Effects of mixed land use on urban stormwater quality under different rainfall event types.

The joint effect of mixed land uses and rainfall event types was studied using a two-year field monitoring program in four urban catchments in Calgary, Alberta, Canada. Event mean concentration (EMC) and event pollutant load (EPL) were employed to evaluate the total suspended sediment (TSS), nitrogen and phosphorus. The correlation analysis showed that most nitrogen and phosphorus components (except for NO2-/NO3- and TDP) predominantly exist in particulate form in the study areas. The correlation for EPL was notably stronger than EMC, which can be attributed to varying rainfall characteristics. The differences in EMCs and EPLs of TSS, nitrogen and phosphorus across catchments indicated that the complexity and spatial distribution of mixed land use can influence the generation and transportation of pollutants in urban runoff. The impacts of rainfall characteristics on stormwater quality are integrated rather than driven by a single rainfall characteristic. Brief but intense events tended to elevate TSS, nitrogen and phosphorus concentrations, especially in complex land-use catchments. Events with long antecedent dry days and short duration also resulted in increased pollutant concentrations, while events with long duration and low intensity could result in higher EPLs. The effect of mixed land use on water quality can vary depending on rainfall event types. Seasonal variations were found in EMC and EPL of TSS, nitrogen and phosphorus, with higher values in the spring and summer than the fall. Seasonal variations are mainly influenced by rainfall conditions, temperature and anthropogenic activities (e.g. lawn fertilization and de-icing with sands). MLR considering rainfall characteristics is an effective method for predicting stormwater quality within a single catchment. Considering complexity and spatial distribution of mixed land use can improve the accuracy of the harmonized MLR model. This research provided insights into understanding the complexities introduced by mixed land use and rainfall event types in urban stormwater quality.

Land use and urbanization indirectly control riverine CH4 and CO2 emissions by altering nutrient input.

Urban rivers are recognized as significant sources of methane (CH4) and carbon dioxide (CO2) emissions. Despite this, the influence of land use and urbanization on carbon emissions across rural-urban rivers at the watershed scale has been insufficiently explored. This study utilized in-situ surveys of the Liao River in northern China to investigate the spatial and temporal variations of CH4 and CO2 emissions and their relationship with urbanization and its potential controlling factors. The findings revealed that CH4 emissions peaked in fall, whereas CO2 emissions were highest in summer. The average fluxes of CH4 and CO2 at the water-gas interface were 1387.22 ± 2474.98 µmol·m-2·d-1 and 52.78 ± 54.44 mmol·m-2·d-1, respectively. Water quality parameters accounted for 80.49 % of the total variation in CH4 and CO2 concentrations and fluxes. Structural equation modeling indicated that TN, TP, DTC, and conductivity had direct effects on riverine CH4 and CO2 emissions, with standardized direct effects of 0.50 and 0.49, respectively. Nutrient input emerged as the primary driver, increasing CH4 and CO2 concentrations and fluxes, particularly in urban-adjacent river sections likely receiving higher nutrient loads. This study underscores that land use and urbanization indirectly influence riverine CH4 and CO2 emissions by modifying nutrient inputs. Effective land use management and nutrient input control are recommended strategies to mitigate riverine CH4 and CO2 emissions.

The past and future dynamics of ecological resilience and its spatial response analysis to natural and anthropogenic factors in Southwest China with typical Karst.

With the global land use/land cover (LULC) and climate change, the ecological resilience (ER) in typical Karst areas has become the focus of attention. Its future development trend and its spatial response to natural and anthropogenic factors are crucial for understanding the changes of ecologically fragile areas to human behavior. However, there is still a lack of relevant quantitative research. The study systematically analyzed the characteristics of LULC changes in Southwest China with typical Karst over the past 20 years. Drawing on the landscape ecology research paradigm, a potential-elasticity-stability ER assessment model was constructed. Revealing the characteristics and heterogeneity of the spatial distribution, annual evolution, and development trend of ER in the past and under different scenarios of shared socioeconomic pathways and representative concentration pathways (SSP-RCP) in the future. In addition, the spatial econometric model was utilized to reveal the spatial effect response mechanism of ER, and adaptive development strategies were proposed to promote the sustainable development of Southwest China. The study found that : (1) In the past 20 years, the LULC in Southwest China showed an accelerated change trend, the ER decreased declined in general, and there was significant spatial heterogeneity, showing the spatial distribution pattern of "west is larger than east, south is larger than north, and reduction in the west was slower than that in the east." (2) Under the same SSP scenario, with the increase of RCP emission concentration, the area of the lowest-resilience increased significantly, and the area of the highest-resilience decreased. (3) The woodland was the largest contributor to ER per unit area in the Southwest China, and grassland was the main LULC type, which had a prominent impact on the ER of the study area. (4) The average precipitation and the normalized difference vegetation index (NDVI) were significant natural drivers of ER in the study area, and the economic growth, innovation, and optimization of industrial structure contributed to the ER of Southwest China. Overall, the integration of quantitative assessment and multi-scenario-based modeling not only provides new perspectives for understanding the pattern of change and response mechanisms, but also provides valuable references for other typical Karst regions around the world to achieve sustainable development.