Watershed land use effects on lake water quality in Denmark

Mitigating nutrient losses from anthropogenic nonpoint sources is today of particular importance for improving the water quality of numerous freshwater lakes worldwide. Several empirical relationships between land use and in-lake water quality variables have been developed, but they are often weak, which can in part be attributed to lack of detailed information about land use activities or point sources. We examined a comprehensive data set comprising land use data, point-source information, and in-lake water quality for 414 Danish lakes. By excluding point-source-influenced lakes (n = 210), the strength in relationship (R2) between in-lake total nitrogen (TN) and total phosphorus (TP) concentrations and the proportion of agricultural land use in the watershed increased markedly, from 10-12% to 39-42% for deep lakes and from 10-12% to 21-23% for shallow lakes, with the highest increase for TN. Relationships between TP and agricultural land use were even stronger for lakes with rivers in their watershed (55%) compared to lakes without (28%), indicating that rivers mediate a stronger linkage between landscape activity and lake water quality by providing a "delivery" mechanism for excess nutrients in the watershed. When examining the effect of different near-freshwater land zones in contrast to the entire watershed, relationships generally improved with size of zone (25, 50, 100, 200, and 400 m from the edge of lake and streams) but were by far strongest using the entire watershed. The proportion of agricultural land use in the entire watershed was best in explaining lake water quality, both relative to estimated nutrient surplus at agricultural field level and near-lake land use, which somewhat contrasts typical strategies of management policies that mainly target agricultural nutrient applications and implementation of near-water buffer zones. This study suggests that transport mechanisms within the whole catchment are important for the nutrient export to lakes. Hence, the whole watershed should be considered when managing nutrient loadings to lakes, and future policies should ideally target measures that reduce the proportion of cultivated land in the watershed to successfully improve lake water quality.     

Is catchment productivity a useful predictor of taxa richness in lake plankton communities?

The influence of catchment variables on lake organisms is understudied. The terrestrial zone in the vicinity of lakes is, however, probably highly important for biota due to the effects on water chemistry and to various processes operating across ecosystem boundaries. We examined the relative importance of lake and catchment variables, as well as large-scale geographical factors, on the taxa richness of phyto- and zooplankton in 100 small lakes in Finland. In variation partitioning, the variability of phytoplankton richness was most strongly related to the effects of lake variables, the joint effects of lake and catchment variables, and the joint effects of all three groups of variables. Zooplankton richness, in turn, was most strongly related to the effects of lake and catchment variables and the joint effect of lake and catchment variables. The exact results of the variation partitioning depended on the catchment sizes considered in the regression models. Among lake variables, planktonic richness was strongly related to variables indicating productivity. Among catchment variables, the normalized difference vegetation index (NDVI), indicating catchment productivity, showed a relatively strong association with planktonic richness. These results provide evidence that catchment variables such as the NDVI may be efficient predictors of planktonic richness in small lakes. It is possible that individual lakes embedded in a highly productive landscape have higher taxa richness than solitary, potentially productive lakes because of the high influx of dispersing propagules from the regional pool. We also suggest that catchment variables may respond to environmental changes at different scales than the lake variables, and explicit consideration of catchment productivity would therefore be useful when planning research and monitoring programs for freshwater organisms.     

Exploring the influence of lake water chemistry on chlorophyll a: A multivariate statistical model analysis

A multivariate statistical approach integrating the absolute principal components score (APCS) and multivariate linear regression (APCS-MLR), along with structural equation modeling (SEM), was used to model the influence of water chemistry variables on chlorophyll a (Chl a) in Lake Qilu, a severely polluted lake in southwestern China. Water quality was surveyed monthly from 2000 to 2005. APCS-MLR was used to identify key water chemistry variables, mine data for SEM, and predict Chl a. Seven principal components (PCs) were determined as eigenvalues >1, which explained 68.67% of the original variance. Four PCs were selected to predict Chl a using APCS-MLR. The results showed a good fit between the observed data and modeled values, with R² = 0.80. For SEM, Chl a and eight variables were used: NH₄-N (ammonia-nitrogen), total phosphorus (TP), Secchi disc depth (SD), cyanide (CN), arsenic (As), cadmium (Cd), fluoride (F), and temperature (T). A conceptual model was established to describe the relationships among the water chemistry variables and Chl a. Four latent variables were also introduced: physical factors, nutrients, toxic substances, and phytoplankton. In general, the SEM demonstrated good agreement between the sample covariance matrix of observed variables and the model-implied covariance matrix. Among the water chemistry factors, T and TP had the greatest positive influence on Chl a, whereas SD had the largest negative influence. These results will help researchers and decision-makers to better understand the influence of water chemistry on phytoplankton and to manage eutrophication adaptively in Lake Qilu.     

Effects of buoyancy, transparency and zooplankton feeding on surface maxima and deep maxima: Comprehensive mathematical model for vertical distribution in cyanobacterial biomass

Inhomogeneous vertical distributions of the cyanobacterial biomass are widely observed during the summer season in stratified lake ecosystems. Among these are surface maxima characterized by surface scum formation and deep or subsurface maxima also known as deep chlorophyll maxima (DCM). The former occurs at the epilimnion in eutrophic lakes, and are usually caused by colonial cyanobacteria such as Microcystis. On the other hand, the latter occurs at the metalimnion and the upper part of the hypolimnion near the thermocline in oligotrophic lakes, and are referred to filamentous cyanobacteria such as Oscillatoria. The aim of this paper is to present a simple mathematical model that can simultaneously describe these phenomena including the annual and diurnal variations, emphasizing the roles of buoyancy regulation, transparency of the lake and zooplankton feeding on cyanobacteria. According to our computer analyses, the increased buoyancy, the low clarity of the lake and the low rate of zooplankton feeding take significant roles in formation of surface maxima, while the reversal of these factors makes deep maxima predominant. Our two-component model with nutrients and cyanobacteria can distinguish between two phenomena by changing the parameters for these factors, without altering the model itself.     

A thermodynamic model of freshwater Antarctic lake ice

Antarctic lakes with simple plankton ecosystems are believed to be sensitive biological indicators of climate change. Models of the physical environment, in particular the ice layer, support understanding of how the ecosystems respond to meteorological variables. This paper describes how data from a previously reported automatic measuring probe and meteorological data from Davis station were used to develop a detailed thermodynamic model of the ice layer on Crooked Lake, one of the largest and deepest freshwater lakes in Antarctica. The general model structure is similar to a previously reported model of sea ice but with modifications specific to the Antarctic freshwater lake case informed by the data. The model inputs are atmospheric variables as well as water temperature, ice albedo and the radiation extinction coefficient for the ice. Heat and radiation fluxes at the ice–air and ice–water boundaries are calculated using equations chosen for their suitability for the Antarctic. In the case of shortwave radiation, equations were fitted to data from the automatic probe. Using the heat fluxes to establish boundary conditions, and incorporating the known thermodynamic properties of ice, the temperature profile within the ice and the resulting growth and melt of the ice can be calculated. The model uses a largely mechanistic approach, with most equations taken from established thermodynamic theories or empirical studies and only one adjustable parameter related to the sensible heat flux from the water, which is not easily calculated from the available data. It was found to accurately reproduce ice temperature and ice thickness data for the year 2003, with r² = 0.89, n = 2005. Finally, the model was simplified to run with air temperature as the only input variable and was shown to perform well—this suggests that freshwater lake ice is affected more by air temperature than any other variable, and is therefore a useful indicator of climate change in its own right.     

Extrinsic and intrinsic controls of zooplankton diversity in lakes

Pelagic crustacean zooplankton were collected from 336 Norwegian lakes covering a wide range of latitude, altitude, lake area, mean depth, production (as chlorophyll a), and fish community structure. Mean zooplankton species richness during the ice-free season was generally low at high latitudes and altitudes. Further, lower species richness was recorded in western lakes, possibly reflecting constraints on migration and dispersal. However, despite obvious spatial limitations, geographic boundaries were only weak predictors of mean zooplankton richness. Similarly, lake surface area did not contribute positively to mean richness such as seen in other ecosystem surveys. Rather, intrinsic factors such as primary production and fish community (planktivore) structure were identified by regression analysis as the major predictors of zooplankton diversity, while a positive correlation was observed between species richness and total zooplankton biomass. However, in spite of a large number of variables included in this study, the predictive power of multiple regression models was modest (<50% variance explained), pointing to a major role for within-lake properties, as yet unidentified intrinsic forces, stochasticity, or dispersal as constraints on zooplankton diversity in these lakes.     

Estimating the critical phosphorus loading of shallow lakes with the ecosystem model PCLake: Sensitivity, calibration and uncertainty

There is a vast body of knowledge that eutrophication of lakes may cause algal blooms. Among lakes, shallow lakes are peculiar systems in that they typically can be in one of two contrasting (equilibrium) states that are self-stabilizing: a ‘clear’ state with submerged macrophytes or a ‘turbid’ state dominated by phytoplankton. Eutrophication may cause a switch from the clear to the turbid state, if the P loading exceeds a critical value. The ecological processes governing this switch are covered by the ecosystem model PCLake, a dynamic model of nutrient cycling and the biota in shallow lakes. Here we present an extensive analysis of the model, using a three-step procedure. (1) A sensitivity analysis revealed the key parameters for the model output. (2) These parameters were calibrated on the combined data on total phosphorus, chlorophyll-a, macrophytes cover and Secchi depth in over 40 lakes. This was done by a Bayesian procedure, giving a weight to each parameter setting based on its likelihood. (3) These weights were used for an uncertainty analysis, applied to the switchpoints (critical phosphorus loading levels) calculated by the model. The model was most sensitive to changes in water depth, P and N loading, retention time and lake size as external input factors, and to zooplankton growth rate, settling rates and maximum growth rates of phytoplankton and macrophytes as process parameters. The results for the ‘best run’ showed an acceptable agreement between model and data and classified nearly all lakes to which the model was applied correctly as either ‘clear’ (macrophyte-dominated) or ‘turbid’ (phytoplankton-dominated). The critical loading levels for a standard lake showed about a factor two uncertainty due to the variation in the posterior parameter distribution. This study calculates in one coherent analysis uncertainties in critical phosphorus loading, a parameter that is of great importance to water quality managers.     

Benthic-planktonic coupling, regime shifts, and whole-lake primary production in shallow lakes

Alternative stable states in shallow lakes are typically characterized by submerged macrophyte (clear-water state) or phytoplankton (turbid state) dominance. However, a clear-water state may occur in eutrophic lakes even when macrophytes are absent. To test whether sediment algae could cause a regime shift in the absence of macrophytes, we developed a model of benthic (periphyton) and planktonic (phytoplankton) primary production using parameters derived from a shallow macrophyte-free lake that shifted from a turbid to a clear-water state following fish removal (biomanipulation). The model includes a negative feedback effect of periphyton on phosphorus (P) release from sediments. This in turn induces a positive feedback between phytoplankton production and P release. Scenarios incorporating a gradient of external P loading rates revealed that (1) periphyton and phytoplankton both contributed substantially to whole-lake production over a broad range of external P loading in a clear-water state; (2) during the clear-water state, the loss of benthic production was gradually replaced by phytoplankton production, leaving whole-lake production largely unchanged; (3) the responses of lakes to biomanipulation and increased external P loading were both dependent on lake morphometry; and (4) the capacity of periphyton to buffer the effects of increased external P loading and maintain a clear-water state was highly sensitive to relationships between light availability at the sediment surface and the of P release. Our model suggests a mechanism for the persistence of alternative states in shallow macrophyte-free lakes and demonstrates that regime shifts may trigger profound changes in ecosystem structure and function.     

Invasive salmonids and lake order interact in the decline of puye grande Galaxias platei in western Patagonia lakes

Salmonid fishes, native to the northern hemisphere, have become naturalized in many austral countries and appear linked to the decline of native fishes, particularly galaxiids. However, a lack of baseline information and the potential for confounding anthropogenic stressors have led to uncertainty regarding the association between salmonid invasions and galaxiid declines, especially in lakes, as these have been much less studied than streams. We surveyed 25 lakes in the Aysén region of Chilean Patagonia, including both uninvaded and salmonid-invaded lakes. Abundance indices (AI) of Galaxias platei and salmonids (Salmo trutta and Oncorhynchus mykiss) were calculated using capture-per-unit-effort data from gillnets, minnow traps, and electrofishing. We also measured additional environmental variables, including deforestation, lake morphometrics, altitude, and hydrological position (i.e., lake order). An information-theoretic approach to explaining the AI of G. platei revealed that by far the strongest effect was a negative association with the AI of salmonids. Lake order was also important, and using structural equation modeling, we show that this is an indirect effect naturally constraining the salmonid invasion success in Patagonia. Supporting this conclusion, an analysis of an independent data set from 106 mountain lakes in western Canada showed that introduced salmonids are indeed less successful in low-order lakes. Reproductive failure due to insufficient spawning habitat and harsh environmental conditions could be the cause of these limits to salmonid success. The existence of this effect in Chilean Patagonia suggests that low-order lakes are likely to provide natural ecological refugia for G. platei. Finally, pristine, high-order lakes should be actively protected as these have become rare and irreplaceable unspoiled references of the most diverse, natural lake ecosystems in Patagonia.     

Implementation of ecological modeling as an effective management and investigation tool: Lake Kinneret as a case study

The need for scientifically based management of lakes, as key water resources, requires the establishment of quantitative relationships between in-lake processes responsible for water quality (WQ) and the intensity of major management measures (MM, e.g. nutrient loading). In this paper, we estimate the impact of potential changes in nutrient loading on the Lake Kinneret ecosystem. Following validation of the model against a comprehensive dataset, we applied an approach that goes beyond scenario testing by linking the lake ecosystem model DYRESM–CAEDYM with a set of ecosystem variables included in a pre-assessed system of water quality indices. The emergent properties of the ecosystem predicted from the model simulations were also compared with lake data as a form of indirect validation of the model. Model output, in good agreement with lake data, indicated differential effects of nitrogen and phosphorus nutrient loading on concentrations, and major in-lake fluxes, of TN and TP, and dynamics and algal community structure. Both model output and lake data indicated a strong relationship between nitrogen loading and in-lake TN values. This relationship is not apparent for phosphorus and only a weak relationship exists between phosphorus loading and in-lake TP. The modeling results, expressed in terms of water quality, allowed establishment of critical/threshold values for the nutrient loads. Implementation of the ecological modeling supplemented with the quantified set of WQ indices allowed us to take a step towards establishment of the association between permissible ranges for water quality and major management measures, i.e. towards sustainable management.     

基于RS与GIS的武汉城市湖泊演化研究

以武汉市主城区为例,利用1995和2005年Landsat5两期TM影像与2000和2010年Landset7两期ETM＋影像的解译结果,基于景观分形理论与GIS的空间分析功能相结合的研究方法,分别构建湖泊变化强度指数和湖泊分形维数变化指数。从湖泊面积变化和湖泊形态变化,以及湖泊水域和其他土地利用类型的转移变化特点与影响进行综合分析。来丰富湖泊演化的分析方法,并总结高速城市化背景下湖泊的变化规律,从而更深入地了解和认识人类活动因素与湖泊水域动态变化之间的响应关系,同时提出若干城市湖泊治理与管理的方式。研究结果表明,（1）15年间的湖泊水域面积总量的变化呈现萎缩的趋势,年变化量在逐渐减小,湖泊萎缩的速度得到了一定的控制。（2）1995-2010年湖泊分形维数也呈逐期较小趋势,说明湖泊几何形状趋于简单化,人为活动对湖泊的影响加大。（3）15年来主城区28个主要湖泊的变化强度指数均为负值,呈萎缩趋势。但从2000年开始,少数湖泊变化强度指数为正值,萎缩趋势得到初步的控制。（4）1995-2010年间湖泊的水域面积主要转移成为建设用地和耕地。其转移面积占转移总面积的87．02％。围湖造田和城市化率的迅速提高对城市湖泊的演化影响深刻。（5）城市化背景下湖泊面积与形态变化的规律并非完全与城市化发展速率呈正比的关系,当城市化率上升到一定的阶段后,城市内部对生态环境的保护与要求也不断提高。为改善城市环境和城市内部的生态用地,湖泊应得到立法等强制性保护。     

Biogeography of bacterioplankton in lakes and streams of an Arctic tundra catchment

Bacterioplankton community composition was compared across 10 lakes and 14 streams within the catchment of Toolik Lake, a tundra lake in Arctic Alaska, during seven surveys conducted over three years using denaturing gradient gel electrophoresis (DGGE) of PCR-amplified rDNA. Bacterioplankton communities in streams draining tundra were very different than those in streams draining lakes. Communities in streams draining lakes were similar to communities in lakes. In a connected series of lakes and streams, the stream communities changed with distance from the upstream lake and with changes in water chemistry, suggesting inoculation and dilution with bacteria from soil waters or hyporheic zones. In the same system, lakes shared similar bacterioplankton communities (78% similar) that shifted gradually down the catchment. In contrast, unconnected lakes contained somewhat different communities (67% similar). We found evidence that dispersal influences bacterioplankton communities via advection and dilution (mass effects) in streams, and via inoculation and subsequent growth in lakes. The spatial pattern of bacterioplankton community composition was strongly influenced by interactions among soil water, stream, and lake environments. Our results reveal large differences in lake-specific and stream-specific bacterial community composition over restricted spatial scales (<10 km) and suggest that geographic distance and connectivity influence the distribution of bacterioplankton communities across a landscape.     

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework integrating quantile regression with interpretable machine learning

● A novel framework integrating quantile regression with machine learning is proposed. ● It aims to identify factors driving observations to upper boundary of relationship. ● Increasing N:P and TN concentration help fulfill the effect of TP on CHL. ● Wetter and warmer decrease potential and increase eutrophication control difficulty. ● The framework advances applications of quantile regression and machine learning. The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.     

Presentation and analysis of a model simulating epilimnetic and hypolimnetic temperatures in lakes

An important factor in aquatic modelling is water temperature. This is especially true for dimictic lakes where stratification and mixing influence many processes and variables, such as oxygen conditions, lake water retention time, etc. This paper evaluates and improves an existing method to predict water temperatures developed by Håkanson ,1996 (Ecol. Model., 88:157–181). The method is incorporated in a model simulating water temperatures in epilimnion and hypolimnion. The model is calibrated and validated against an extensive set of empirical data. It is driven by readily available parameters, e.g. latitude, continentality and altitude. The predictive power, especially for the epilimnetic temperature, is such that the model could be used as a sub-model in many models concerning lake ecosystems. However, the model has only been tested for Swedish lakes covering a relatively narrow range in terms of latitude, longitude and altitude and it would be interesting to investigate if this approach also holds for other parts of the world. As an example of how the model can be used in practise, a simulation of retention of caesium in lake water, using the temperature model as a sub-model, is presented.     

湖泊营养物基准的候选变量和指标

湖泊营养物基准指标变量是可用于衡量水质、评价或预测水体的营养状态或富营养化程度的变量,是构成建立区域和湖泊营养物基准的基础。详细介绍和分析了氮、磷两个营养物变量和有机碳、叶绿素、透明度、溶解氧、大型植物、生物群落结构等生物学指标,以及营养状态指标、自养指数、温度、pH值、电导率以及土地利用等一系列相关变量（度量或指标）,并总结了当前美国各州在湖泊营养物基准指标选取方面的基本情况。归纳出选择营养物基准指标时应遵循的若干原则,即综合考虑富营养化控制关键因子和区域差异性,所选指标应具有相对稳定、早期预警和易于监测等特点。最后针对我国湖泊营养物基准指标的选取提出了几点建议。     

Macrozoobenthic assemblages in relation to environments of the Yangtze-isolated lakes

Eutrophication can shift lakes from a clear, macrophyte-dominated state to a turbid, algae-dominated state, and different habitat condition supports different fauna. Macrozoobenthos are good indicators of water environment, and studies on macrozoobenthic assemblage characteristics can help us to know which state a lake is in, thus provide the basis for its eutrophication control. In this study, a systematic investigation on macrozoobenthos was conducted in 17 Yangtze-isolated lakes to explore the macroecological laws of macrozoobenthic assemblages. Detrended correspondence analysis (DCA) revealed that variance of benthic assemblage structure occurred in two types of lakes. In macrophytic lakes, altogether 51 taxa of macrozoobenthos were identified. The average density and biomass of total macrozoobenthos were 2231 individuals·m^?2 and 1.69 g dry weight·m^?2, respectively. Macrozoobenthic assemblage was characterized by dominance of scrapers (i.e. gastropods). In algal lakes, altogether 20 taxa of macrozoobenthos were identified. The average density and biomass of total macrozoobenthos were 2814 individuals·m^?2 and 1.38 g dry weight·m^?2, respectively. Macrozoobenthic assemblage was characterized by dominance of collector-gatherers (i.e. oligochaetes). Wet biomass of submersed macrophytes (B _Mac) and phytoplankton chlorophyll a concentration (Chl a) were demonstrated as the key factor structuring macrozoobenthic assemblages in macrophytic and algal lakes, respectively.     

Denitrification mitigates N flux through the stream-floodplain complex of a desert city

The Indian Bend Wash (IBW) flood-control project relies on a greenbelt to carry floods through Scottsdale, Arizona, USA. The greenbelt is characterized by a chain of shallow artificial lakes in a larger floodplain of irrigated turf, which has been protected from encroaching urban development. As such, this urban stream-floodplain complex can be divided into three subsystems: artificial lakes, channelized stream segments, and floodplain. We conducted experiments to evaluate which, if any, of these subsystems were important sites of denitrification, and to explore factors controlling denitrification rates. Denitrification enzyme activity (DEA) bioassays were conducted on sediments from eight lake and six stream segments as well as soil samples from eight floodplain transects. Mass-specific potential denitrification rates were significantly higher in lakes than in streams or floodplains. Nutrient limitation bioassays revealed that nitrate (NO3-) limited denitrification in lake sediments, a surprising finding given that NO3(-)-rich groundwater additions frequently raised lake NO3(-) concentration above 1 mg N/L. Experiments on intact lake cores suggested that denitrification was limited by the rate NO3(-) diffused into sediments, rather than its availability in overlying water. Floodplain denitrification was limited by water content, not NO3(-) or C, and irrigation of soils stimulated denitrification. We constructed a N budget for the IBW stream-floodplain complex based on our experimental results. We found that both lakes and floodplains removed large quantities of N, with denitrification removing 261 and 133 kg N ha(-1) yr(-1) from lake sediments and floodplain soils, respectively, indicating that lakes are hotspots for denitrification. Nevertheless, because floodplain area was >4.5 times that of lakes, floodplain soils removed nearly 2.5 times as much N as lake sediments. Given the desert's low annual precipitation, a finding that floodplain soils are active sites of denitrification might seem implausible; however, irrigation is common in urban landscapes, and it elevated annual denitrification in IBW. Based on our results, we conclude that construction of artificial lakes created hotspots while application of irrigation water created hot moments for denitrification in the stream-floodplain complex, demonstrating that management decisions can improve the ability of urban streams to provide critical ecosystem services like N retention.     

The role of environmental and spatial processes in structuring lake communities from bacteria to fish

We assessed the relative roles of local environmental conditions and dispersal on community structure in a landscape of lakes for the major trophic groups. We use taxonomic presence-absence and abundance data for bacteria, phytoplankton, zooplankton, and fish from 18 lakes in southern Quebec, Canada. The question of interest was whether communities composed of organisms with more limited dispersal abilities, because of size and life history (zooplankton and fish) would show a different effect of lake distribution than communities composed of good dispersers (bacteria and phytoplankton). We examine the variation in structure attributable to local environmental (i.e., lake chemical and physical variables) vs. dispersal predictors (i.e., overland and watercourse distances between lakes) using variation partitioning techniques. Overall, we show that less motile species (crustacean zooplankton and fish) are better predicted by spatial factors than by local environmental ones. Furthermore, we show that for zooplankton abundances, both overland and watercourse dispersal pathways are equally strong, though they may select for different components of the community, while for fish, only watercourses are relevant dispersal pathways. These results suggest that crustacean zooplankton and fish are more constrained by dispersal and therefore more likely to operate as a metacommunity than are bacteria and phytoplankton within this studied landscape.     

中国湖泊富营养化影响因素研究——基于中国22个湖泊实证分析

基于1：25万河流水系和数字高程（DEM）数据制备了选取湖泊的流域边界,据其集成了流域社会经济数据,并据中国科学院资源环境数据中心提供的1990、1995、2000、2005年4个时段土地利用数据形成了流域反映人类活动强度的表征指标,选取了全国湖泊富营养化区域差异性调查课题获取的案例湖泊的水质数据,集成了中国湖泊富营养化影响因素计量分析的面板数据集,研究了1990-2005年间中国湖泊营养状态的发展趋势与差异特征,探讨了湖泊富营养化的自然气候与社会经济影响机制,构建了中国湖泊富营养化影响因素分析的计量模型,厘定了1990-2005年间影响湖泊营养状态变化的重要因素,测度了其对湖泊富营养化的影响方向和作用强度。基于面板数据的计量分析结果表明,近15年人类活动强度对湖泊营养状态呈显著的正影响,其表征指标人均GDP与建设用地所占流域面积比均具有较强的显著性,而在人类扰动较小的情况下,湖泊的营养状态与湖泊补给系数成正比,与湖泊蓄容量成反比,补给系数较小且其他因素也相同时,水体营养状态应与流域土壤本底值相关;以林、草地的面积比重所测度的流域自然生态系统发育程度与湖泊营养状态呈显著负相关关系,表明林地与草地生态系统对流域的氮、磷营养物的人湖量具有一定的削减作用,论文研究结果将为流域管理措施方案制订提供科技支撑。