Watershed land use effects on lake water quality in Denmark

Geospatial analysis of toxic metal contamination in groundwater and associated health risks in the lower Himalayan industrial region

Once known for its clean and natural environment, the lower Himalayan region is now no exception to human-induced disturbances. Rapid industrial growth in Baddi-Barotiwala (BB) industrial region has led to degradation of groundwater resources in the area. Groundwater samples were collected from 37 locations to study the groundwater chemistry, geospatial variation of 15 toxic metals in groundwater, source apportionment, metals of concern and associated health risks in the region. The results showed rock dominated hydrogeology with decreasing order of anion and cation abundance as HCO3- > Cl- > SO42- > NO3- > Br- > F- and Ca+ > Na+ > Mg2+ > K+ > Li+ respectively. Concentrations of Iron (BDL-3.6 mg/l), Nickel (BDL-0.023 mg/l), Barium (0.22-0.89 mg/l), Lead (0.0001-0.085 mg/l) and Zinc (0.006-21.4 mg/l) were found above the permissible limits at few locations. Principal component analysis (PCA) and coefficient of variance (CV) showed both geogenic and anthropogenic origin of metals in groundwater of the BB industrial region. A consistent concentration of Uranium was detected at all the sampling locations with an average value of 0.0039 mg/l and poor spatial variation indicating its natural presence. Overall, non-carcinogenic (N-CR) risk in the study area via oral pathway was high for adults and children (Hazard Index > 1) with geogenic Uranium as the major contributor (Hazard Quotient > 1) followed by Zinc, Lead and Cobalt. Carcinogenic (CR) risk in the region was high for adults having mean value above the threshold (1E-04) with Nickel and Chromium as the metals of major concern. Spatial variation of health risks was overlayed on village boundaries of the region to identify the potential industrial sources of the metals of major concern. The results highlight the need for immediate remediation of groundwater resources in order to achieve a harmonious coexistence between industrialization and human well-being.

Modelling relationships between land use and water quality using statistical methods: A critical and applied review

Land use/land cover (LULC) can have significant impacts on water quality and the health of aquatic ecosystems. Consequently, understanding and quantifying the nature of these impacts is essential for the development of effective catchment management strategies. This article provides a critical review of the literature in which the use of statistical methods to model the impacts of LULC on water quality is demonstrated. A survey of these publications, which included hundreds of original research and review articles, revealed several common themes and findings. However, there are also several persistent knowledge gaps, areas of methodological uncertainty, and questions of application that require further study and clarification. These relate primarily to appropriate analytical scales, the significance of landscape configuration, the estimation and application of thresholds, as well as the potentially confounding influence of extraneous variables. Moreover, geographical bias in the published literature means that there is a need for further research in ecologically and climatically disparate regions, including in less developed countries of the Global South. The focus of this article is not to provide a technical review of statistical techniques themselves, but to examine important practical and methodological considerations in their application in modelling the impacts of LULC on water quality.

Influence of hydrological features on CO2 and CH4 concentrations in the surface water of lakes, Southwest China: A seasonal and mixing regime analysis

Due to the large spatiotemporal variability in the processes controlling carbon emissions from lakes, estimates of global lake carbon emission remain uncertain. Identifying the most reliable predictors of CO2 and CH4 concentrations across different hydrological features can enhance the accuracy of carbon emission estimates locally and globally. Here, we used data from 71 lakes in Southwest China varying in surface area (0.01‒702.4 km2), mean depth (< 1‒89.6 m), and climate to analyze differences in CO2 and CH4 concentrations and their driving mechanisms between the dry and rainy seasons and between different mixing regimes. The results showed that the average concentrations of CO2 and CH4 in the rainy season were 23.9 ± 18.8 μmol L-1 and 2.5 ± 4.9 μmol L-1, respectively, which were significantly higher than in the dry season (10.5 ± 10.3 μmol L-1 and 1.8 ± 4.2 μmol L-1, respectively). The average concentrations of CO2 and CH4 at the vertically mixed sites were 24.1 ± 21.8 μmol L-1 and 2.6 ± 5.4 μmol L-1, being higher than those at the stratified sites (14.8 ± 13.4 μmol L-1 and 1.7 ± 3.5 μmol L-1, respectively). Moreover, the environmental factors were divided into four categories, i.e., system productivity (represented by the contents of total nitrogen, total phosphorus, chlorophyll a and dissolved organic matter), physicochemical factors (water temperature, Secchi disk depth, dissolved oxygen and pH value), lake morphology (lake area, water depth and drainage ratio), and geoclimatic factors (altitude, wind speed, precipitation and land-use intensity). In addition to the regression and variance partitioning analyses between the concentrations of CO2 and CH4 and environmental factors, the cascading effects of environmental factors on CO2 and CH4 concentrations were further elucidated under four distinct hydrological scenarios, indicating the different driving mechanisms between the scenarios. Lake morphology and geoclimatic factors were the main direct drivers of the carbon concentrations during the rainy season, while they indirectly affected the carbon concentrations via influencing physicochemical factors and further system productivity during the dry season; although lake morphology and geoclimatic factors directly contributed to the carbon concentrations at the vertically mixed and stratified sites, the direct effect of system productivity was only observed at the stratified sites. Our results emphasize that, when estimating carbon emissions from lakes at broad spatial scales, it is essential to consider the influence of precipitation-related seasons and lake mixing regimes.

Relative impact of environmental variables on the lake trophic state highlights the complexity of eutrophication controls

For the effective management of lakes apart from defining and monitoring their current state it is crucial to identify environmental variables that are mostly responsible for the nutrient input. We used interpretative machine learning to investigate the environmental parameters that influence the lake's trophic state and recognize their patterns. We analysed the influence of the 25 environmental variables on the commonly used trophic state indicators values: total phosphorus (TP), Chlorophyll-a (Chl-a) and Secchi depth (SD) of 60 lakes located in the Central European Lowlands. We attempted to delineate the lakes into groups due to the influence of common prevailing environment variable/variables on the water trophic state reflected by each indicator. The results indicated that the relative impact of environmental variables on the lake trophic state has an individual hierarchy unique for each indicator. The most important are variables related to catchment impact on the lake, Ohle ratio (L. catchment area/L. area) for TP and Schindler ratio (L. area + L. catchment area)/L. volume for Chl-a and SD. There are also few variables strongly influential only for small sub-groups of lakes that stand out: lake maximum depth, catchment slope steepness expressed by the height standard deviation. The methods used in the study enabled the assessment of the character of the influence of the environmental variables on the indicator value and revealed that most essential variables (Ohle ratio for TP and Schindler ratio for Chl-a and SD) have bimodal distribution with a clear threshold value. These findings contribute to a better understanding of the drivers shaping the lake trophic status and have implication for planning effective management strategies.

Human impact on current environmental state in Chinese lakes

Anthropogenic and natural disturbance to inland aquatic ecosystems displays a notable spatial difference, yet data to measure these differences are scarce. This study encompasses 217 lakes distributed over five lake regions of China and elucidates the environmental factors determining the spatial variability of the water quality and trophic status. A significant correlation between human modification index in surrounding terrestrial systems (HMT) and trophic status of lake ecosystems (TSI) was found, and the regression slope in each region was similar except in the Qinghai-Tibet Plateau region. It was further noted that the pattern of environmental factor network (EF network) differed among freshwater and saline lakes. The EF network was complex for freshwater lakes in less human-influenced areas, but intensive man-made influence disrupted most relationships except for those between total nitrogen, total phosphorus, chlorophyll-a, and water turbidity. As for regions including saline lakes, correlations among water salinity and organic forms of carbon and nitrogen were apparent. Our results suggest that HMT and EF network can be useful indicators of the ecological integrity of local lake ecosystems, and integrating spatial information on a large scale provides conservation planners the option for evaluating the potential risk on inland aquatic systems.

Lake morphological characteristics and climatic factors affect long-term trends of phytoplankton community in the Rotorua Te Arawa lakes, New Zealand during 23 years observation

Monitoring the long-term dynamics of lake phytoplankton can help understand their natural temporal variability, as well as assess potential impacts of interventions aimed at improving lake ecological condition. However, investigating long-term changes in lake ecosystems has received scant attention. In the present study, we analyzed a long-term dataset of phytoplankton communities collected from 1990 to 2013 from eleven of the 12 Rotorua Te Arawa lakes in New Zealand, to explore their responses to changing abiotic conditions. We used a sequential algorithm to examine the likelihood of regime shifts in abiotic and biotic factors during the study period that could be attributable to lake interventions. Our analysis suggests that lake interventions have improved the abiotic factors, whereas the response of biotic factors was less clear. Total phosphorus levels were implicated in the decline in lake condition, including in two lakes subject to lake interventions, and in four control lakes. Both abiotic and biotic factors showed diverse trends (e.g., increase, decrease or no change), and abiotic factors had more regime shifts than biotic factors. Shifts in biotic indices also displayed time lags to shifts in abiotic factors. Long-term responses of abiotic and biotic factors were also influenced by lake morphological characteristics and climatic variables. This latter finding underscores the importance of considering lake morphological characteristics and climate changes when planning management practices. A sound understanding of resilience and threshold of phytoplankton shifts to environmental changes are needed to assess the effectiveness of previous management strategies and prioritize the future conservation efforts toward water quality goals.

Human health risk assessment and pollution index of groundwater in Jammu plains of India: A geospatial approach

To examine the drinking water suitability as well as to study the influence of local lithology in controlling groundwater chemistry a study has been carried out in the Jammu plains of India by using 50 groundwater samples during the post-monsoon (POM) and pre-monsoon (PRM) seasons. The groundwater samples are found to be dominated by Mg-Ca-HCO₃, and Ca-Mg-HCO_3, types. Besides this, the Pollution Index of Groundwater (PIG) was also calculated to assess the overall groundwater quality of the study area. As per the PIG, the groundwater quality of the study is suitable for domestic utilization except for a few samples (2%) which need conventional treatment in order to make the groundwater resources potable. Based on rock water interaction, there is a considerable variation in the POM and PRM seasons, which indicates the role of weathering and dissolution of rock minerals. The multivariate statistical analysis reveals that the lithogenic factors, such as rock-water interactions and weathering of carbonate-bearing rocks, are predominantly controlling groundwater chemistry. Further, trace elements such as As, Cu, Cd, Fe, Mn, and Zn were also analyzed to determine the Human Health Risk Assessment (HHRA) in order to know about the carcinogenic risk in adults and children in the study area.

Joint role of land cover types and microbial processing on molecular composition of dissolved organic matter in inland lakes

Anthropogenic activities have greatly changed the land use and land cover (LULC) and further influenced the chemical properties and amount of DOM transported into aquatic systems, meanwhile, microbial processing is also critical to DOM molecular composition in freshwaters. However, how they jointly shape DOM's chemical composition and chemodiversity in lakes is poorly understood. Here we examined DOM characteristics for seven inland lakes with three different land cover conditions (forest-dominated, cropland-dominated, and urban-dominated). Results indicated that DOM in cropland-dominated and forest-dominated lakes exhibited more characteristics of terrestrial organic matter, while urban-dominated lakes had more allochthonous organic matter driven by relatively high nutrient input. Human activities extended terrestrial DOM input to lakes and intensified the amount of heteroatomic organic molecules containing nitrogen and sulfur in lakes, with cropland contributing more N-containing compounds and urban contributing more S-containing compounds. Differential bacterial community composition appeared in the three types of land cover lakes, while strong co-occurrence/exclusion patterns between specific microbes and molecular formula groups revealed the key DOM metabolism functions of these bacteria. Matrix correlations based on Mantel tests confirmed that watershed landcover status was a dominating factor for DOM sources and molecular composition in mountainous lakes through direct input of terrestrial organic matter, and microbial processing was not the key factor for DOM molecular formula. Our findings help to assess the influence of human activities and microbial processing in the transfer and transformation of DOM in environmental waters.

Predicting water quality from geospatial lake, catchment, and buffer zone characteristics in temperate lowland lakes

Lakes provide essential ecosystem services and strongly influence landscape nutrient and carbon cycling. Therefore, monitoring water quality is essential for the management of element transport, biodiversity, and public goods in lakes. We investigated the ability of machine learning models to predict eight important water quality variables (alkalinity, pH, total phosphorus, total nitrogen, chlorophyll a, Secchi depth, color, and pCO₂) using monitoring data from 924 to 1054 lakes. The geospatial predictor variables comprise a wide range of potential drivers at the lake, buffer zone, and catchment level. We compared the performance of nine predictive models of varying complexity for each of the eight water quality variables. The best models (Random Forest and Support Vector Machine in six and two cases, respectively) generally performed well on the test set (R² = 0.28-0.60). Models were then used to predict water quality for all 180,377 mapped Danish lakes. Additionally, we trained models to predict each water quality variable by using the predictions we had generated for the remaining seven variables. This improved model performance (R² = 0.45-0.78). Overall, the uncovered relationships were in line with the findings of previous studies, e.g., total nitrogen was positively related to catchment agriculture and chlorophyll a, Secchi depth, and alkalinity were influenced by soil type and landscape history. Remarkably, buffer zone geomorphology (curvature, ruggedness, and elevation) had a strong influence on nutrients, chlorophyll a, and Secchi depth, e.g., curvature was positively related to nutrients and chlorophyll a and negatively to Secchi depth. Lake area was a strong predictor of multiple variables, especially its relationship with pH (positive), pCO₂ (negative), and color (negative). Our analysis shows that the combination of machine learning methods and geospatial data can be used to predict lake water quality and improve national upscaling of predictions related to nutrient and carbon cycling.

Estimating the pollutant loss rate based on the concentration process and landscape unit interactions: a case study of the Dianchi Lake Basin, Yunnan Province, China

The landscape analysis model establishes a quantitative relationship between landscape patterns and pollution processes. The spatial heterogeneity within and between landscapes affects the pollutant transmission process and originates from the superposition effect of terrestrial geographical and morphological characteristics. This study aimed to develop a new method to estimate the pollutant loss rate. From the perspective of the flow process of pollutants entering a water body, the interaction between each landscape unit and adjacent unit during pollutant migration was simulated along the pollutant migration flow path. The role of pollutants affected by external forces in the process of migration could be divided into "promoting" and "hindering." Four indices were proposed to simulate the pollutant loads entering the lake. The linear coefficients between the load of the pollutants chemical oxygen demand (COD_Cr), ammoniacal nitrogen (NH₃-N), total nitrogen (TN), and total phosphorus (TP) entering the lake and the pollutant load emission weighted by the upstream and downstream confluence ratio index were 0.930, 0.835, 0.925, and 0.795, respectively, and the non-linear variance explanation coefficients were 87.70%, 87.50%, 87.60%, and 84.70%, respectively. When the surface resistance was integrated into the index as a parameter, the linear and nonlinear correlation coefficients were significantly improved. The linear coefficients were 0.952, 0.897, 0.919, and 0.939, respectively, and the non-linear variance explanations were 99.00%, 97.30%, 95.10%, and 97.30%, respectively. The spatial distribution of landscape surface resistance reflects the spatial movement trend of pollutants from different sources. The indices characterizing the promoting and hindering effects could be integrated to calculate the loss rate of pollutant load entering the lake from landscape units at different locations in the basin space.

Spatiotemporal variations of water quality and their driving forces in the Yangtze River Basin, China, from 2008 to 2020 based on multi-statistical analyses

Water quality deterioration is a prominent issue threatening water security worldwide. As the largest river in China, the Yangtze River Basin is facing severe water pollution due to intense human activities. Analyzing water quality trends and identifying the corresponding driver factors are important components of sustainable water quality management. Thus, spatiotemporal characteristics of the water quality from 2008 to 2020 were analyzed by using a Mann-Kendall test and rescaled range analysis (R/S). In addition, multi-statistical analyses were used to determine the main driving factors of variation in the permanganate index (COD_Mn), ammonia nitrogen (NH₃-N) concentration, and total phosphorus (TP) concentration. The results showed that the mean concentrations of NH₃-N and TP decreased from 0.31 to 0.16 mg/L and 0.16 to 0.07 mg/L, respectively, from 2008 to 2020, indicating that the water quality improved during this period. However, the concentration of COD_Mn did not reduce remarkably. Based on R/S analysis, the NH₃-N concentration was predicted to continue to decrease from 2020 to 2033, whereas the COD_Mn concentration was forecast to increase, highlighting an issue of great concern. In terms of spatial distribution, water quality in the upstream was better than that of the mid-downstream. Multi-statistical analyses revealed that the temporal variation in water quality was predominantly influenced by tertiary industry (TI), the nitrogen fertilizer application rate (N-FAR), the phosphate fertilizer application rate (P-FAR), and the irrigation area of arable land (IAAL), with contribution rates of 15.92%, 14.65%, 3.46%, and 2.84%, respectively. The spatial distribution of COD_Mn was mainly influenced by TI, whereas that of TP was primarily determined by anthropogenic activity factors (e.g., N-FAR, P-FAR). This study provides deep insight into water quality evolution in the Yangtze River Basin that can guide water quality management in this region.

Anthropogenic eutrophication of shallow lakes: Is it occasional?

Understanding and managing the susceptibility of lakes to anthropogenic eutrophication has been a primary goal of limnological research for decades. To achieve United Nations' Sustainable Development Goals, scientists have attempted to understand why shallow lakes appear to be prone to eutrophication and resistant to restoration. A rich data base of 1151 lakes (each ≥ 0.5 km²) located within the Europe and the United States of America offers a rare opportunity to explore potential answers. Analysis of sites showed that lake depth integrated socio-ecological systems and reflected potential susceptibility to anthropogenic stressors, as well as lake productivity. In this study, lakes distributed in agricultural plain and densely populated lowland areas were generally shallow and subjected to intense human activities with high external nutrient inputs. In contrast, deep lakes frequently occurred in upland regions, dominated by natural landscapes with little anthropogenic nutrient input. Lake depth appeared to not only reflect external nutrient load to the lake, but also acted as an amplifier that increased shallow lake susceptibility to anthropogenic disturbance. Our findings suggest that shallow lakes are more susceptible to human forcing and their eutrophication may be not an occasional occurrence, and that societal expectations, policy goals, and management plans should reflect this observation.

Exploring watershed effects on nutrient concentrations in shallow lakes through stable isotope analysis

Biogeochemistry patterns in shallow lakes are influenced by both in-lake factors such as ecosystem state as well as watershed-level factors such as land use, but the relative importance of in-lake versus watershed factors is poorly known. This knowledge gap makes it difficult for lake mangers to prioritize efforts on watershed versus in-lake strategies for stabilizing the clear-water state. We studied 48 shallow lakes in Minnesota, USA to assess the relative influence of lake size, land use in watersheds, and ecosystem state (turbid versus clear) on water column total nitrogen (TN) and total phosphorus (TP), as well as δ¹⁵N and δ¹³C in three species of fish. Our land use categories included natural areas, row crop agriculture, and all agriculture (row crops plus alfalfa). A model selection approach revealed different control mechanisms on the behavior of stable isotopes and nutrients. δ¹³C ratios in fish were most strongly influenced by lake size, while δ¹⁵N ratios were influenced by all agriculture in watersheds. In contrast, water column TN and TP concentrations were influenced by the in-lake factor of ecosystem state, with both nutrients lower in the clear state. We detected no effects of land use on TN or TP concentrations, likely due to strong effects of ecosystem state masking watershed effects. However, the strong relationship between agriculture and δ¹⁵N in fish indicated that watersheds did influence nutrient processing in shallow lakes, and that effects are not a legacy from past watershed events. Collectively, these observations indicate that lake managers should minimize agricultural intensity in shallow lake watersheds to facilitate the clear-water state, which will, in turn reduce water-column TN and TP relative to the turbid state.

External Phosphorus Loading in New Lakes

The water quality of lakes is highly dependent on external phosphorus (P) loading. The vast external loadings from sewage and other wastewater discharge that European lakes have historically received have been dramatically reduced today by improved wastewater treatment. Gaining knowledge of the catchment characteristics that influence external P-loading should enable predictions of the achievable water quality of lakes. In this study, we tested this proposition. Data from 90 new Danish lakes show no apparent relationship between the mean summer P-concentration and the size or land use of the catchments. The external P-loading and resulting annual P-concentration were further investigated on a representative subset of 12 of the new lakes, using six methods. Three of the methods used empirical estimates of P-transport from catchments, based on the national average P-transport, runoff-dependent P-transport, and crop-dependent P-transport, and the other three methods used different empirical models tested on the lakes. External P-loading was reliably predicted by several of the methods. The predictions of the annual P-concentration were highly dependent on the inclusion of annual runoff. However, the predicted P-concentrations were generally overestimated, most pronounced for the nutrient-poor and most recently established lakes. In these lakes, internal P-loading was found to be the most important factor in predicting achievable water quality.

Controls on the epilimnetic phosphorus concentration in small temperate lakes

Phosphorus (P) is one of the key limiting nutrients for algal growth in most fresh surface waters. Understanding the determinants of P accumulation in the water column of lakes of interest, and the prediction of its concentration is important to water quality managers and other stakeholders. We hypothesized that lake physicochemical, climate, and watershed land-use attributes control lake P concentration. We collected relevant data from 126 lakes in Maine, USA, to determine the major drivers for summer total epilimnetic P concentrations. Predictive regression-based models featured lake external and internal drivers. The most important land-use driver was the extent of agriculture in the watershed. Lake average depth was the most important physical driver, with shallow lakes being most susceptible to high P concentrations; shallow lakes often stratify weakly and are most subject to internal mixing. The sediment NaOH-extracted aluminum (Al) to bicarbonate/dithionite-extracted P molar ratio was the most important sediment chemical driver; lakes with a high hypolimnetic P release have low ratios. The dissolved organic carbon (DOC) concentration was an important water column chemical driver; lakes having a high DOC concentration generally had higher epilimnetic P concentrations. Precipitation and temperature, two important climate/weather variables, were not significant drivers of epilimnetic P in the predictive models. Because lake depth and sediment quality are fixed in the short-term, the modeling framework serves as a quantitative lake management tool for stakeholders to assess the vulnerability of individual lakes to watershed development, particularly agriculture. The model also enables decisions for sustainable development in the watershed and lake remediation if sediment quality is conducive to internal P release. The findings of this study may be applied to bloom metrics more directly to support lake and watershed management actions.

Functional Responses of Phytoplankton Assemblages to Watershed Land Use and Environmental Gradients

Watershed land-use changes have been identified as major threats to lake fauna, subsequently affecting ecosystem functioning. In this study, the functional-based approach was used to examine the effects of land use and environmental changes on phytoplankton communities in four selected lakes in Northeast China. We also identified the sensitive functional traits as indicators of environmental stressors. The integration of RLQ analysis with the fourth-corner approach significantly identified five of 18 functional trait categories, including flagella, filamentous, unicellular, mixotrophic, and chlorophyll c, as potential indicators to changes in watershed land-use intensity and environmental gradients. Significant relationships between traits and land use and water quality highlighted the consequential indirect impact of extensive agricultural and urban development on phytoplankton via allochthonous nutrient inputs and various contaminants. In addition, the functional richness of phytoplankton assemblages generally increased along with surface area and forests, but decreased along with intensive agricultural and urban land use, implying that functional homogenization may cause a reduction in ecosystem productivity and reliability to land-use intensity. Given the superior performance of the functional-based approach, our findings also highlighted the importance of the application of both the biological traits and functional diversity index in monitoring programs for lake ecosystems.

Land-use and agriculture in Denmark around year 1900 and the quest for EU Water Framework Directive reference conditions in coastal waters

The EU Water Framework Directive (WFD) aims to protect the ecological status of coastal waters. To establish acceptable boundaries between good and moderate ecological status, the WFD calls for reference conditions practically undisturbed by human impact. For Denmark, the nitrogen (N) concentrations present around year 1900 have been suggested to represent reference conditions. As the N load of coastal waters relates closely to runoff from land, any reduction in load links to agricultural activity. We challenge the current use of historical N balances to establish WFD reference conditions and initiate an alternative approach based on parish-level land-use statistics collected 1896/1900 and N concentrations in root zone percolates from experiments with year 1900-relevant management. This approach may be more widely applicable for landscapes with detailed historic information on agricultural activity. Using this approach, we find an average N concentration in root zone percolates that is close to that of current agriculture. Thus, considering Danish coastal waters to be practically unaffected by human activity around year 1900 remains futile as 75% of the land area was subject to agricultural activity with a substantial potential for N loss to the environment. It appears unlikely that the ecological state of coastal waters around year 1900 may serve as WFD reference condition.

Spatiotemporal variation of nitrogen and phosphorus and its main influencing factors in Huangshui River basin

The foundation of managing excess nutrients in river is the identification of key physical processes and the control of decisive influencing factors. The existing studies seldom consider the influence of rainfall-runoff relationship and only focus on a few anthropogenic activities and natural attributes factors. To address this issue, a comprehensive set of influencing factors including rainfall-runoff relationship (represented by runoff coefficient), basic physical and chemical parameters of water quality, land use types, landscape patterns, topography, and socioeconomic development was constructed in this study. M-K test and cluster analysis were conducted to identify the temporal mutation and spatial clustering characteristics of NH₃-N and TP in Huangshui River basin, respectively. Partial least squares regression was used to elucidate the linkages between water contaminants and the factors. As shown in the results, the temporal mutations of NH₃-N and TP were obvious in the middle reaches, with 4 out of 7 catchments in the middle reaches have a larger number of mutations of NH₃-N than other catchments. The cluster analysis results of NH₃-N and TP among catchments were similar. This study also indicated that although the Huangshui River basin was located in the upper reaches of the Yellow River, the influences of rainfall-runoff relationship on spatiotemporal changes of NH₃-N and TP in its sub-basins were limited. Only the temporal change of NH₃-N in Jintan catchment in the upstream area was significantly affected by runoff coefficient. The indexes of proportion of water area (PWA), proportion of impervious area (PIA), and proportion of primary industry (PPI) were the top three influencing factors of temporal variation of NH₃-N and TP for most catchments in the middle reaches. The temporal change of NH₃-N in Jintan catchment in the upstream area was obviously affected by runoff coefficient. The spatial variation of NH₃-N and TP were all affected by PWA and proportion of secondary industry significantly. The results of this study can provide theoretical basis and technical support for the control and management of nitrogen and phosphorus pollution in upper reaches of rivers.

Response of macroinvertebrate communities to land use and water quality in Wudalianchi Lake

Macroinvertebrate assemblages are structured by a number of abiotic and biotic factors interacting simultaneously. We investigated macroinvertebrate assemblages along gradients of human disturbance and morphometric characteristics in five lakes connected by the same stream. We aimed to assess the relative effects of environmental gradients on macroinvertebrate assemblages and to investigate whether water quality effects on the assemblages were correlated with buffer land use. There were significant differences in macroinvertebrate community compositions among lakes, and our results indicated that oligochaetes (mainly Limnodrilus) and insects (mainly Chironomus) contributed highly to the differences. We used redundancy analysis with variation partitioning to quantify the independent and combined anthropogenic effects of water quality and land use gradients on the macroinvertebrate community. The independent effect of water quality was responsible for 17% of the total variance in macroinvertebrate community composition, the independent effect of buffer land use accounted for 6% of variation, and the combined variation between land use change and water quality accounted for 12%. Our study indicated that both the independent effects of land use and within-lake water quality can explain the influence in macroinvertebrate assemblages, with significant interactions between the two. This is rather important to notice that changes in buffer land use generally may alter nutrient inputs and thus severely affect abiotic conditions encountered by macroinvertebrate. Our study demonstrates that considering buffer zone effects explicitly may be significant in the selection and application of conservation and management strategies.

Identifying the Influence of Land Cover and Human Population on Chlorophyll a Concentrations Using a Pseudo-Watershed Analytical Framework

Increasing agricultural development and urbanization exacerbates the degradation of water quality in vulnerable freshwater systems around the world. Advances in remote sensing and greater availability of open-access data provides a valuable resource for monitoring water quality but harmonizing between databases remains a challenge. Here, we: (i) developed a pseudo-watershed analytical framework to associate freshwater lakes with adjacent land cover and human population data and (ii) applied the framework to quantify the relative influence of land cover and human population on primary production for 9313 lakes from 72 countries. We found that land cover and human population explained 30.2% of the variation in chlorophyll a concentrations worldwide. Chlorophyll a concentrations were highest in regions with higher agricultural activities and human populations. While anthropogenic land cover categories equated to only 4 of the 18 categories, they accounted for 41.5% of the relative explained variation. Applying our pseudo-watershed analytical framework allowed us to quantify the importance of land cover and human population on chlorophyll concentration for over 9000 lakes. However, this framework has broader applicability for any study or monitoring program that requires quantification of lake watersheds.

Climate and landscape conditions indirectly affect fish mercury levels by altering lake water chemistry and fish size

Mercury pollution is a global environmental problem that threatens ecosystems, and negatively impacts human health and well-being. Mercury accumulation in fish within freshwater lakes is a complex process that appears to be driven by factors such as individual fish biology and water chemistry at the lake-scale, whereas, climate, and land-use/land-cover conditions within lake catchments can be influential at relatively larger scales. Nevertheless, unravelling the intricate network of pathways that govern how lake-scale and large-scale factors interact to affect mercury levels in fish remains an important scientific challenge. Using structural equation models (SEMs) and multiple long-term databases we identified direct and indirect effects of lake-scale and larger-scale factors on mercury levels in Walleye and Northern Pike - two species that are valued in inland fisheries. At the lake-level, the most parsimonious path models contained direct effects of fish weight, DOC, and pH, as well as an indirect effect of DOC on fish mercury levels via fish weight. Interestingly, lakeshed-, climate-, and full-path models that combine the effects of both lakeshed and climate revealed indirect effects of surrounding landscape conditions and latitude via DOC, pH, and fish weight but no direct effects on fish mercury levels. These results are generally consistent across species and lakes, except for some differences between stratified and non-stratified lakes. Our findings imply that understanding climate and land-use driven alterations of water chemistry and fish biology will be critical to predicting and mitigating fish mercury bioaccumulation in the future.

Small Reservoirs, Landscape Changes and Water Quality in Sub-Saharan West Africa

Small reservoirs (SRs) are essential water storage infrastructures for rural populations of Sub-Saharan West Africa. In recent years, rapid population increase has resulted in unprecedented land use and land cover (LULC) changes. Our study documents the impacts of such changes on the water quality of SRs in Burkina Faso. Multi-temporal Landsat images were analyzed to determine LULC evolutions at various scales between 2002 and 2014. Population densities were calculated from downloaded 2014 population data. In situ water samples collected in 2004/5 and 2014 from selected SRs were analyzed for Suspended Particulate Matter (SPM) loads, an integrative proxy for water quality. The expansion of crop and artificial areas at the expense of natural covers controlled LULC changes over the period. We found a very significant correlation between SPM loads and population densities calculated at a watershed scale. A general increase between the two sampling dates in the inorganic component of SPM loads, concomitant with a clear expansion of cropland areas at a local scale, was evidenced. Results of the study suggest that two complementary but independent indicators (i.e., LULC changes within 5-km buffer areas around SRs and demographic changes at watershed scale), relevantly reflected the nature and intensity of overall pressures exerted by humans on their environment, and locally on aquatic ecosystems. Recommendations related to the re-greening of peripheral areas around SRs in order to protect water bodies are suggested.

Precipitation, landscape properties and land use interactively affect water quality of tropical freshwaters

Globally, conversion of pristine areas to anthropogenic landscapes is one of the main causes of ecosystem service losses. Land uses associated with urbanization and farming can be major sources of pollution to freshwaters promoting artificial inputs of several elements, leading to impaired water quality. However, how the effects of land use on freshwater quality are contingent on properties of the local landscape and climate is still poorly understood. The aim of this study was to evaluate the effects of landscape properties (morphometric measurements of lakes and their catchments), precipitation patterns, and land use properties (extent and proximity of the land use to freshwaters) on water quality of 98 natural lakes and reservoirs in northeast Brazil. Water quality impairment (WQI) was expressed as a composite variable incorporating parameters correlated with eutrophication including nitrogen (N), phosphorus (P) and Chlorophyll-a concentration. Regression tree analysis showed that WQI is mainly related to highly impacted "buffer areas". However, the effects of land use in these adjacent lands were contingent on precipitation variability for 13% of waterbodies and on surface area of the buffer in relation to the volume of waterbody (BA:Vol) for 87% of waterbodies. Overall, effects on WQI originating from the land use in the adjacent portion of the lake were amplified by high precipitation variability for ecosystems with highly impacted buffer areas and by high BA:Vol for ecosystems with less impacted buffer areas, indicating that ecosystems subjected to intense episodic rainfall events (e.g. storms) and higher buffer areas relative to aquatic ecosystem size (i.e. small waterbodies) are more susceptible to impacts of land use. Land use at the catchment scale was important for the largest ecosystems. Thus, our findings point toward the need for considering a holistic approach to managing water quality, which includes watershed management within the context of climate change.

Water Depth Underpins the Relative Roles and Fates of Nitrogen and Phosphorus in Lakes

Eutrophication mitigation is an ongoing priority for aquatic ecosystems. However, the current eutrophication control strategies (phosphorus (P) and/or nitrogen (N)) are guided mainly by nutrient addition experiments in small waters without encompassing all in-lake biogeochemical processes that are associated largely with lake morphological characteristics. Here, we use a global lake data set (573 lakes) to show that the relative roles of N vs P in affecting eutrophication are underpinned by water depth. Mean depth and maximum depth relative to mixing depth were used to distinguish shallow (mixing depth > maximum depth), deep (mixing depth < mean depth), and transitional (mean depth ≤ mixing depth ≤ maximum depth) lakes in this study. TN/TP ratio (by mass) was used as an indicator of potential lake nutrient limitation, i.e., N only limitation if N/P < 9, N + P colimitation if 9 ≤ N/P < 22.6, and P only limitation if N/P ≥ 22.6. The results show that eutrophication is favored in shallow lakes, frequently (66.2%) with N limitation while P limitation predominated (94.4%) in most lakes but especially in deep ones. The importance of N limitation increases but P limitation decreases with lake trophic status while N and P colimitation occurs primarily (59.4%) in eutrophic lakes. These results demonstrate that phosphorus reduction can mitigate eutrophication in most large lakes but a dual N and P reduction may be needed in eutrophic lakes, especially in shallow ones (or bays). Our analysis helps clarify the long debate over whether N, P, or both control primary production. While these results imply that more resources be invested in nitrogen management, given the high costs of nitrogen pollution reduction, more comprehensive results from carefully designed experiments at different scales are needed to further verify this modification of the existing eutrophication mitigation paradigm.

Spatially Varying and Scale-Dependent Relationships of Land Use Types with Stream Water Quality

Understanding the complex relationships between land use and stream water quality is critical for water pollution control and watershed management. This study aimed to investigate the relationship between land use types and water quality indicators at multiple spatial scales, namely, the watershed and riparian scales, using the ordinary least squares (OLS) and geographically weighted regression (GWR) models. GWR extended traditional regression models, such as OLS to address the spatial variations among variables. Our results indicated that the water quality indicators were significantly affected by agricultural and forested areas at both scales. We found that extensive agricultural land use had negative effects on water quality indicators, whereas, forested areas had positive effects on these indicators. The results also indicated that the watershed scale is effective for management and regulation of watershed land use, as the predictive power of the models is much greater at the watershed scale. The maps of estimated local parameters and local R² in GWR models showcased the spatially varying relationships and indicated that the effects of land use on water quality varied over space. The results of this study reinforced the importance of watershed management in the planning, restoration, and management of stream water quality. It is also suggested that planners and managers may need to adopt different strategies, considering watershed characteristics—such as topographic features and meteorological conditions—and the source of pollutants, in managing stream water quality.

Targeted set-aside: Benefits from reduced nitrogen loading in Danish aquatic environments

Nitrogen (N) leaching from agricultural areas in the form of nitrate (NO₃^-) is one of the most dominant sources of eutrophication in coastal waters. This environmental pressure is expected to intensify with the predicted increase in food demand, highlighting the need for developing novel ways to reduce N loads from agriculture. This may be achieved by exploiting the spatial variation in N removal through denitrification in groundwater and surface water systems. Thus, agricultural intensification should occur in areas characterized by high N removal potential, whereas effective N-reduction measures such as setting aside agricultural land (set-aside) should be targeted towards areas characterized by low N removal. Simultaneously, setting aside agricultural land can potentially strengthen local nature areas. To reach the water quality targets defined by the EU Water Framework Directive (WFD), the Danish region has defined individual coastal N reduction goals for each of the existing Danish water catchments. With set-aside as an effective N-reduction measure the study aims were to: 1) evaluate the effect of targeting areas to set aside versus using no targeting and 2) evaluate whether different prioritization for targeting set-aside areas enhances multi-functionality of the landscape, while efficiently achieving the required N load reduction. Areas were selected according to three priority values: 1) high contribution to coastal N loads, 2) high nature value, and 3) low agricultural land rent. The combination of these three values per area defined three multifunctional scenarios: (GreenEnvi - N load dominates, TerreEco - nature dominates, AgroEcon - land rent dominates). Results indicate, that targeting areas with high N loads for set-aside is more beneficial (effective) for achieving multiple goals than blanket policies for entire countries (no targeting). Targeting requires only 23% of agricultural land compared to 35% when not targeting, leaving more land available for satisfying food demand. Moreover, multiple benefits can be achieved in surrounding environments by increasing set-aside to 25% according to the GreenEnvi scenario. The GreenEnvi scenario is also cheaper compared to targeting for only land rent.

Ecological networks reveal contrasting patterns of bacterial and fungal communities in glacier-fed streams in Central Asia

Bacterial and fungal communities in biofilms are important components in driving biogeochemical processes in stream ecosystems. Previous studies have well documented the patterns of bacterial alpha diversity in stream biofilms in glacier-fed streams, where, however, beta diversity of the microbial communities has received much less attention especially considering both bacterial and fungal communities. A focus on beta diversity can provide insights into the mechanisms driving community changes associated to large environmental fluctuations and disturbances, such as in glacier-fed streams. Moreover, modularity of co-occurrence networks can reveal more ecological and evolutionary properties of microbial communities beyond taxonomic groups. Here, integrating beta diversity and co-occurrence approach, we explored the network topology and modularity of the bacterial and fungal communities with consideration of environmental variation in glacier-fed streams in Central Asia. Combining results from hydrological modeling and normalized difference of vegetation index, this study highlighted that hydrological variables and vegetation status are major variables determining the environmental heterogeneity of glacier-fed streams. Bacterial communities formed a more complex and connected network, while the fungal communities formed a more clustered network. Moreover, the strong interrelations among the taxonomic dissimilarities of bacterial community (BC) and modules suggest they had common processes in driving diversity and taxonomic compositions across the heterogeneous environment. In contrast, fungal community (FC) and modules generally showed distinct driving processes to each other. Moreover, bacterial and fungal communities also had different driving processes. Furthermore, the variation of BC and modules were strongly correlated with hydrological properties and vegetation status but not with nutrients, while FC and modules (except one module) were not associated with environmental variation. Our results suggest that bacterial and fungal communities had distinct mechanisms in structuring microbial networks, and environmental variation had strong influences on bacterial communities but not on fungal communities. The fungal communities have unique assembly mechanisms and physiological properties which might lead to their insensitive responses to environmental variations compared to bacterial communities. Overall, beyond alpha diversity in previous studies, these results add our knowledge that bacterial and fungal communities have contrasting assembly mechanisms and respond differently to environmental variation in glacier-fed streams.

Effects of land use, topography, climate and socio-economic factors on geographical variation pattern of inland surface water quality in China

The deterioration of water quality has become a primary environmental concern worldwide. Understanding the status of water quality and identifying the influencing factors are important for water resources management. However, reported analyses have mostly been conducted in small and focused areas. It is still unclear if factors driving spatial variation in water quality would be different in extended spatial scales. In this paper, we analyzed spatial pattern of inland surface water quality in China using a dataset with four water quality parameters (i.e., pH, DO, NH₄⁺-N and COD_Mn) and the water quality level. We tested the effects of anthropogenic (i.e., land use and socio-economic) and natural (i.e., climatic and topographic) factors on spatial variation in water quality. The study concluded that the overall inland surface water quality in China was at level III (fair). Water quality level was strongly correlated with COD_Mn and NH₄⁺-N concentration. In contrast to reported studies that suggested land use patterns were the determinants of inland surface water quality, this study revealed that both anthropogenic and natural factors played important roles in explaining spatial variation of inland surface water quality in China. Among the tested explanatory variables, mean elevation within watershed appeared as the best predictor for pH, while annual precipitation and mean air temperature were the most important explanatory variables for COD_Mn and DO, respectively. NH₄⁺-N concentration and water quality level were most strongly correlated with the percent of forest cover in watershed. Compared to studies at smaller spatial scales, this study found different influencing factors of surface water quality, suggesting that factors may play different roles at different spatial scales of consideration. Therefore management policies and measures in water quality control must be established and implemented accordingly. Since currently adopted parameters for monitoring of inland surface water quality in China are largely influenced by natural variables, additional physicochemical and biological indicators are needed for a robust assessment of human impacts on water quality.

Cascading influences of grassland degradation on nutrient limitation in a high mountain lake and its inflow streams

Nitrogen (N) and phosphorus (P) are key growth-limiting nutrients for organisms and their absolute and relative supplies regulate the structure and function of ecosystems. Landcover changes lead to modifications of terrestrial biogeochemistry, consequently influencing aquatic nutrient conditions. This study sought to evaluate the potential impacts of grassland degradation on nutrient availability and nutrient limitation in the Qinghai Lake (China) and its inflow streams. We sampled nutrient concentrations and tested stream nutrient limitation by conducting nutrient diffusing substrata (NDS) bioassays in streams flowing through subbasins with different grassland status. To test nutrient limitation and the responses of lake phytoplankton to stream inflows, bioassays were conducted by adding different nutrients (N, P, and joint NP) as well as water from different streams to lake water with phytoplankton, respectively. In general, N concentrations as well as N:P ratios decreased while P concentrations increased with decreased normalized difference vegetation index (NDVI, an index of vegetation status), especially in September, suggesting that grassland degradation (low NDVI) has the potential to differentially decrease N availability and increase P availability in streams. Consistent with this, relative responses (RR) of stream periphyton to P and combined NP enrichments in the NDS bioassays decreased with stream P concentrations while increased with stream water N:P ratios. Lake phytoplankton responded strongly to P and combined NP addition indicating strong P-limitation of lake phytoplankton. RR of lake phytoplankton to stream water decreased with nitrate concentration and N:P ratios in stream water and increased with the concentrations of ammonium, total phosphorus, and soluble reactive phosphorus, indicating that stream water with higher P but lower N and N:P from degraded subcatchments is associated with increased impact on P-limited Lake phytoplankton. Overall, this study suggests that grassland degradation has the potential to differentially influence the nutrients delivered to streams with substantial increases in P but decreases in N and N:P, alleviating P limitation of stream periphyton and, ultimately, stimulating P-limited phytoplankton growth in the lake.

Effects of Vegetation Pattern and Spontaneous Succession on Remediation of Potential Toxic Metal-Polluted Soil in Mine Dumps

The ecological rehabilitation of potential toxic metal-contaminated soils in sites disturbed by mining has been a great challenge in recent decades. Phytoremediation is one of the most widely promoted renovation methods due to its environmental friendliness and low cost. However, there is a lack of in situ investigation on the influence of vegetation pattern and spontaneous succession on the rehabilitation of potential toxic metal-polluted soil. To clarify how the vegetation pattern in the early stage of restoration and the spontaneous succession influence the remediation of the soil, we investigated a metal mining dump in Sichuan, China, by field investigation and laboratory analysis. We determined the plant growth, soil fertility, and the capacity of potential toxic metals (PTMs) in metal mining soil under different initial vegetation patterns for different years to understand the role of vegetation pattern and spontaneous succession in PTM pollution phytoremediation projects. The results show that: (1) Phytoremediation with a simple initial vegetation pattern (RP rehabilitative plant pattern) which involves two rehabilitation plants, Agave sisalana and Neyraudia reynaudiana, achieves a PTM pollution index that is 9.28% lower than that obtained with the complex vegetation pattern (RP&LP rehabilitation plants mixed with local plants pattern), 21.86% lower in the soil fertility index, and 73.69% lower in the biodiversity index; (2) The phytoremediation with the 10-year RP&LP pattern was associated with a PTM pollution index that was 4.04% higher than that for the 17-year RP&LP pattern, a soil fertility index that was 4.48% lower, and a biodiversity index that was 12.49% lower. During the process of vegetation succession, if accumulator plants face inhibition of growth or retreat, the reclamation rate will decrease. The vegetation patterns influence the effect of phytoremediation. Spontaneous vegetation succession will cause the phytoremediation process to deviate from the intended target. Therefore, according to the goal of vegetation restoration, choosing a suitable vegetation pattern is the main premise to ensure the effect of phytoremediation. The indispensable manipulation of succession is significant during the succession series, and more attention should be paid to the rehabilitative plants to ensure the stable effect of reclamation. The results obtained in this study could provide a guideline for the in situ remediation of PTM-polluted soil in China.

Modeling the effects of climatic and land use changes on phytoplankton and water quality of the largest Turkish freshwater lake: Lake Beyşehir

Climate change and intense land use practices are the main threats to ecosystem structure and services of Mediterranean lakes. Therefore, it is essential to predict the future changes and develop mitigation measures to combat such pressures. In this study, Lake Beyşehir, the largest freshwater lake in the Mediterranean basin, was selected to study the impacts of climate change and various land use scenarios on the ecosystem dynamics of Mediterranean freshwater ecosystems and the services that they provide. For this purpose, we linked catchment model outputs to the two different processed-based lake models: PCLake and GLM-AED, and tested the scenarios of five General Circulation Models, two Representation Concentration Pathways and three different land use scenarios, which enable us to consider the various sources of uncertainty. Climate change and land use scenarios generally predicted strong future decreases in hydraulic and nutrient loads from the catchment to the lake. These changes in loads translated into alterations in water level as well as minor changes in chlorophyll a (Chl-a) concentrations. We also observed an increased abundance of cyanobacteria in both lake models. Total phosphorus, temperature and hydraulic loading were found to be the most important variables determining cyanobacteria biomass. As the future scenarios revealed only minor changes in Chl-a due to the significant decrease in nutrient loads, our results highlight that reduced nutrient loading in a warming world may play a crucial role in offsetting the effects of temperature on phytoplankton growth. However, our results also showed increased abundance of cyanobacteria in the future may threaten ecosystem integrity and may limit drinking water ecosystem services. In addition, extended periods of decreased hydraulic loads from the catchment and increased evaporation may lead to water level reductions and may diminish the ecosystem services of the lake as a water supply for irrigation and drinking water.

Influence of Land Use and Point Source Pollution on Water Quality in a Developed Region: A Case Study in Shunde, China

To design and implement policy to manage water quality, it is important to investigate land use and possible sources of pollution. In this study, using Pearson regression analysis, redundancy analysis and multiple regression analysis, we assess the influence of land use and point sources on water quality in the river system in Shunde district in 2000 and 2010. The results show that water quality was related positively with water surface but negatively with impervious and urban greening area. Additionally, water quality was related negatively to point source emissions of chemical oxygen demand (COD) and ammonium-nitrogen (NH₄-N). The total explanatory power of spatial variation of water quality was improved from 43.4% to 60.0% in 2000 and from 31.3% to 57.8% in 2010, respectively, when the influence of point sources was added into redundancy analysis between water quality and land use. Thus, both land use management and point source pollution control should be considered for improving river water quality.

Tracing sources of nitrate using water chemistry, land use and nitrogen isotopes in the Ganjiang River, China

In this work, we traced sources of nitrate in the Ganjiang River, a major tributary of Yangtze River, China, by analysing the water chemistry, nitrogen isotopes and land use. Water samples from 20 sites in the main stream and tributaries were collected in the dry and wet seasons. The [Formula: see text] ranged from 0.97 to 8.60 ‰, and was significantly higher in the wet season than in the dry season, and significantly higher in tributaries than in the main stream. In the dry season, [Formula: see text] concentrations and [Formula: see text] were significantly negatively correlated with forest and grassland areas, and positively correlated with paddy field and residential area. However, most of the correlations were not significant in the wet season. The results showed that fertilizer was the main source of nitrate in the Ganjiang River, and domestic sewage was important in the dry season, but its contribution was lower than that in other rivers in the Yangtze Basin. In the wet season, the intensified nitrogen cycle caused by high temperature and the mixing effect caused by rainfall made it difficult to trace nitrate sources using [Formula: see text] and land use.

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression

As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R² values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R² ~59.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use conditions within each watershed to optimize mitigation strategies for contrasting land-use characteristics and seasonal variations.

Variation partitioning of diatom species data matrices: Understanding the influence of multiple factors on benthic diatom communities in tropical streams

Elucidating the confounding influence of multiple environmental factors on benthic diatom communities is important in developing water quality predictive models for better guidance of stream management efforts. The objective of this study was to explore the relative impact of metal pollution and hydromorphological alterations in, addition to nutrient enrichment and organic pollution, on diatom taxonomic composition with the view to improve stream diatom-based water quality inference models. Samples were collected twice at 20 sampling stations in the tropical Manyame Catchment, Zimbabwe. Diatom, macroinvertebrate communities and environmental factors were sampled and analysed. The variations in diatom community composition explained by different categories of environmental factors were analysed using canonical correspondence analysis using variance partitioning (partial CCA). The following variations were explained by the different predictor matrices: nutrient levels and organic pollution - 10.4%, metal pollution - 8.3% and hydromorphological factors - 7.9%. Thus, factors other than nutrient levels and organic pollution explain additional significant variation in these diatom communities. Development of diatom-based stream water quality inference models that incorporate metal pollution and hydromorphological alterations, where these are key issues, is thus deemed necessary.

Macroinvertebrate assemblages in agricultural, mining, and urban tropical streams: implications for conservation and management

The study evaluated the response of macroinvertebrate assemblages to changes in water quality in different land-use settings in Manyame catchment, Zimbabwe. Four land-use categories were identified: forested commercial farming, communal farming, Great Dyke mining (GDM) and urban areas. Macroinvertebrate community structure and physicochemical variables data were collected in two seasons from 41 sites following standard methods. Although not environmentally threatening, urban and GDM areas were characterised by higher conductivity, total dissolved solids, salinity, magnesium and hardness. Chlorides, total phosphates, total nitrogen, calcium, potassium and sodium were significantly highest in urban sites whilst dissolved oxygen (DO) was significantly higher in the forested commercial faming and GDM sites. Macroinvertebrate communities followed the observed changes in water quality. Macroinvertebrates in urban sites indicated severe pollution (e.g. Chironomidae) whilst those in forested commercial farming sites and GDM sites indicated relatively clean water (e.g. Notonemouridae). Forested watersheds together with good farm management practices are important in mitigating impacts of urbanisation and agriculture. Strategies that reduce oxygen-depleting substances must be devised to protect the health of Zimbabwean streams. The study affirms the wider applicability of the South African Scoring System in different land uses.

Climate and land use interactively affect lake phytoplankton nutrient limitation status

Climate-change models predict more frequent and intense summer droughts for many areas, including the midwestern United States. Precipitation quantity and intensity in turn drive the rates and ratios at which nitrogen (N) and phosphorus (P) are exported from watersheds into lakes, but these rates and ratios are also modulated by watershed land use. This led us to ask the question, is the effect of precipitation on phytoplankton nutrient limitation dependent on watershed land use? Across 42 lakes, we found that phytoplankton in lakes in agricultural landscapes were usually P limited but shifted to strong N limitation under increased drought intensity, and that droughts promoted N-fixing cyanobacteria. In contrast, phytoplankton in lakes with forested watersheds were consistently N limited, regardless of drought status. This climate-land use interaction suggests that droughts may increase the incidence of N limitation in agriculturally impacted lakes. N limitation would likely impair valuable ecosystem services such as drinking water, fisheries, and recreation by promoting the occurrence and severity of cyanobacterial blooms.

Effects of Land Use on Lake Nutrients: The Importance of Scale, Hydrologic Connectivity, and Region

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales.

The importance of lake-specific characteristics for water quality across the continental United States

Lake water quality is affected by local and regional drivers, including lake physical characteristics, hydrology, landscape position, land cover, land use, geology, and climate. Here, we demonstrate the utility of hypothesis testing within the landscape limnology framework using a random forest algorithm on a national-scale, spatially explicit data set, the United States Environmental Protection Agency's 2007 National Lakes Assessment. For 1026 lakes, we tested the relative importance of water quality drivers across spatial scales, the importance of hydrologic connectivity in mediating water quality drivers, and how the importance of both spatial scale and connectivity differ across response variables for five important in-lake water quality metrics (total phosphorus, total nitrogen, dissolved organic carbon, turbidity, and conductivity). By modeling the effect of water quality predictors at different spatial scales, we found that lake-specific characteristics (e.g., depth, sediment area-to-volume ratio) were important for explaining water quality (54-60% variance explained), and that regionalization schemes were much less effective than lake specific metrics (28-39% variance explained). Basin-scale land use and land cover explained between 45-62% of variance, and forest cover and agricultural land uses were among the most important basin-scale predictors. Water quality drivers did not operate independently; in some cases, hydrologic connectivity (the presence of upstream surface water features) mediated the effect of regional-scale drivers. For example, for water quality in lakes with upstream lakes, regional classification schemes were much less effective predictors than lake-specific variables, in contrast to lakes with no upstream lakes or with no surface inflows. At the scale of the continental United States, conductivity was explained by drivers operating at larger spatial scales than for other water quality responses. The current regulatory practice of using regionalization schemes to guide water quality criteria could be improved by consideration of lake-specific characteristics, which were the most important predictors of water quality at the scale of the continental United States. The spatial extent and high quality of contextual data available for this analysis makes this work an unprecedented application of landscape limnology theory to water quality data. Further, the demonstrated importance of lake morphology over other controls on water quality is relevant to both aquatic scientists and managers.

Detection of critical LUCC indices and sensitive watershed regions related to lake algal blooms: a case study of Taihu Lake

Taihu Lake in China has suffered from severe eutrophication over the past 20 years which is partly due to significant land use/cover change (LUCC). There is an increasing need to detect the critical watershed region that significantly affects lake water degradation, which has great significance for environmental protection. However, previous studies have obtained conflicting results because of non–uniform lake indicators and inadequate time periods. To identify the sensitive LUCC indices and buffer distance regions, three lake divisions (Meiliang Lake, Zhushan Lake and Western Coastal region) and their watershed region within the Taihu Lake basin were chosen as study sites, the algal area was used as a uniform lake quality indicator and modeled with LUCC indices over the whole time series. Results showed that wetland (WL) and landscape index such as Shannon diversity index (SHDI) appeared to be sensitive LUCC indices when the buffer distance was less than 5 km, while agricultural land (AL) and landscape fragmentation (Ci) gradually became sensitive indices as buffer distances increased to more than 5 km. For the relationship between LUCC and lake algal area, LUCC of the WC region seems to have no significant effect on lake water quality. Conversely, LUCC within ML and ZS region influenced algal area of corresponding lake divisions greatly, while the most sensitive regions were found in 3 km to 5 km, rather than the whole catchment. These results will be beneficial for the further understanding of the relationship between LUCC and lake water quality, and will provide a practical basis for the identification of critical regions for lake.

Nutrient and sediment losses in snowmelt runoff from perennial forage and annual cropland in the canadian prairies

An 8-yr field-scale study, 2005 to 2012, investigated effects of agricultural land use on nutrient and sediment losses during snowmelt runoff from four treatment fields in southern Manitoba. In 2005, two fields with a long-term history of annual crop (AC) production were planted to perennial forage (PF), while two other fields were left in AC production. In 2009, the AC fields were converted to PF, while the PF fields were returned to AC. Runoff flow rates were monitored at the lower edge of the fields, and nutrient concentrations of runoff water were determined. The effects of AC and PF on selected variables were similar for the spatial (between-fields) and temporal (within-field) comparisons. The flow-weighted mean concentrations (FWMCs) and loads of particulate N, P, and sediment were not affected by treatment. Soil test N and the FWMC and load of NO (NO + NO) were significantly greater in the AC treatment, but the FWMC and load of NH were greater in the PF treatment. Loads of total dissolved N (TDN) and total N (TN) were not affected by treatment, although the concentrations of TDN and TN were greater in the AC treatment. The PF treatment significantly increased FWMCs and loads of total dissolved P (TDP) and total P (TP). On an annual snowmelt runoff basis, the PF treatment increased the FWMC of TDP by 53% and TP by 52% and increased the load of TDP by 221% and TP by 160% compared with the AC treatment. The greater P and NH losses in the PF treatment were attributed mainly to nutrient release from forage residue due to freezing.

Scale effects on spatially varying relationships between urban landscape patterns and water quality

Scientific interpretation of the relationships between urban landscape patterns and water quality is important for sustainable urban planning and watershed environmental protection. This study applied the ordinary least squares regression model and the geographically weighted regression model to examine the spatially varying relationships between 12 explanatory variables (including three topographical factors, four land use parameters, and five landscape metrics) and 15 water quality indicators in watersheds of Yundang Lake, Maluan Bay, and Xinglin Bay with varying levels of urbanization in Xiamen City, China. A local and global investigation was carried out at the watershed-level, with 50 and 200 m riparian buffer scales. This study found that topographical features and landscape metrics are the dominant factors of water quality, while land uses are too weak to be considered as a strong influential factor on water quality. Such statistical results may be related with the characteristics of land use compositions in our study area. Water quality variations in the 50 m buffer were dominated by topographical variables. The impact of landscape metrics on water quality gradually strengthen with expanding buffer zones. The strongest relationships are obtained in entire watersheds, rather than in 50 and 200 m buffer zones. Spatially varying relationships and effective buffer zones were verified in this study. Spatially varying relationships between explanatory variables and water quality parameters are more diversified and complex in less urbanized areas than in highly urbanized areas. This study hypothesizes that all these varying relationships may be attributed to the heterogeneity of landscape patterns in different urban regions. Adjustment of landscape patterns in an entire watershed should be the key measure to successfully improving urban lake water quality.