Multiscale landscape and wetland drivers of lake total phosphorus and water color (original) (raw)
Related papers
Effects of Land Use on Lake Nutrients: The Importance of Scale, Hydrologic Connectivity, and Region
PLOS ONE, 2015
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.
Multi-scaled drivers of ecosystem state: quantifying the importance of the regional spatial scale
Ecological Applications, 2013
The regional spatial scale is a vital linkage for the informed extrapolation of results from local to continental scales to address broad-scale environmental problems. Among-region variation in ecosystem state is commonly accounted for by using a regionalization framework, such as an ecoregion classification. Rarely have alternative regionalization frameworks been tested for variables measuring ecosystem state, nor have the underlying relationships with the variables that are used to define them been assessed. In this study, we asked two questions: (1) How much among-region variation is there for ecosystems and does it differ by regionalization framework? (2) What are the likely causes of this amongregion variation? We present a case study using a large data set of lake water chemistry, uni-and multi-scaled hydrogeomorphic and anthropogenic driver variables that likely influence lake chemistry at the subcontinental scale, and seven existing regionalization frameworks. We used multilevel models to quantify and explain within-and among-region variation in lake water chemistry. Our models account for local driver variables of ecosystem variation within regions, differences in regional mean ecosystem state (i.e., random intercepts in multilevel models), and differences in relationships between local drivers and ecosystem state by region (i.e., random slopes in multilevel models). Using one of the best performing regionalization frameworks (Ecological Drainage Units), we found that for lake phosphorus and alkalinity: (1) a majority of all the variation in water chemistry among the studied lakes occurred among regions, (2) very few regional-scale landscape driver variables were required to explain among-region variation in lake water chemistry, (3) a much higher proportion of the total variation among lakes was explained at the regional scale than at the local scale, and (4) some relationships between local-scale driver variables and lake water chemistry varied by region. Our results demonstrate the importance of considering the regional spatial scale for broad-scale research and ecosystem management and conservation. Our quantitative approach can be easily applied to other response variables, ecosystem types, geographic areas, and spatial extents to inform ecosystem responses to global environmental stressors.
Quantifying Relationships Among Phosphorus, Agriculture, and Lake Depth at an Inter-Regional Scale
Ecosystems, 2008
To date, studies examining the impact of agriculture on freshwater systems have been spatially confined (that is, single drainage basin or regional level). Across regions, there are considerable differences in a number of factors, including geology, catchment morphometry, and hydrology that affect water quality. Given this heterogeneity, it is unknown whether agricultural activities have a pervasive impact on lake trophic state across large spatial scales. To address this issue, we tested whether the proportion of agricultural land in a catchment (% Agr) could explain a significant portion of the variation in lake water quality at a broad inter-regional scale. As shallow, productive systems have been shown to be particularly susceptible to eutrophication, we further investigated how lake mean depth modulates the relationship between % Agr and lake total phosphorus (TP) concentration. We applied both traditional metaanalytic techniques and more sophisticated linear mixed-effects models to a dataset of 358 temperate lakes that spanned an extensive spatial gradient (5°E to 73°W) to address these issues. With metaanalytical techniques we detected an across-study correlation between TP and % Agr of 0.53 (onetailed P-value = 0.021). The across-study correlation coefficient between TP and mean depth was substantially lower (r = )0.38; P = 0.057). With linear mixed-effects modeling, we detected amongstudy variability, which arises from differences in pre-impact (background) lake trophic state and in the relationship between lake mean depth and lake TP. To our knowledge, this is the first quantitative synthesis that defines the influence of agriculture on lake water quality at such a broad spatial scale. Syntheses such as these are required to define the global relationship between agricultural land-use and water quality.
2012
Lake phosphorus concentrations are strongly influenced by the surrounding landscape that generates phosphorus loads and water inflow to lakes, and the physical characteristics of the lake that determine the fate of these inputs. In addition, the presence, connectivity, and configuration of upstream lakes and wetlands likely affect downstream lake phosphorus concentrations. These freshwater landscape features have only sometimes been incorporated of inflows to lakes. Our results suggest that when modeling lake phosphorus concentrations, freshwater features of the landscape and their spatial arrangement should be taken into account.
Wetland effects on lake water quality in the Minneapolis/St. Paul metropolitan area
Landscape Ecology, 1993
A method developed to evaluate the cumulative effect of wetland mosaics on water quality was applied to 33 lake watersheds in the seven-county region surrounding Minneapolis-St. Paul, Minnesota. A geographic information system (GIS) was used to record and measure landscape variables derived from aerial photos. Twenty-seven watershed land-use and land-cover variables were reduced to eight principal components which described 85% of the variance among watersheds. Relationships between lake water quality variables and the first six principal components plus an index of lake mixis were analyzed through stepwise multiple regression analysis. A combination of three landscape components (wetland/watershed area, agriculture/wetlands, and forest/soils components) explained 49~ of the variance in atrophic state index, even though most of the lakes examined were already highly eutrophic, and thus were influenced by internal loading. The regression equations explained a range of 14 to 76% of the variation in individual water quality variables. Forested land-use was associated with lower lake trophic state, chloride, and lead. High lake trophic state was associated with agricultural land-use and with wetland distance from the lake of interest. The extent of wetlands was associated with low total lead and high color in lakes downstream. Wet meadows or herbaceous, seasonallyflooded wetlands contributed more to lake water color than did cattail marshes.
Ecological Indicators, 2007
Developing effective indicators of ecological condition requires calibration to determine the geographic range and ecosystem type appropriate for each indicator. Here, we demonstrate an approach for evaluating the relative influence of geography, geomorphology and human disturbance on patterns of variation in biotic indicators derived from multiple assemblages for ecosystems that span broad spatial scales. To accomplish this, we collected abundance information on six biotic assemblages (birds, fish, amphibians, aquatic macroinvertebrates, wetland vegetation, and diatoms) from over 450 locations along U.S. shorelines throughout each of the Great Lakes during 2002-2004. Sixty-six candidate taxon-and function-based indicators analyzed using hierarchical variance partitioning revealed that geographic (lake) rather than geomorphic factors (wetland type) had the greatest influence on the proportion of variance explained across all indicators, and that a significant portion of the variance was also related to response to human disturbance. Wetland vegetation, fish and bird indicators were the most, and macroinvertebrates the least, responsive to human disturbance. Proportion of rock bass, Carex lasiocarpa, and stephanodiscoid diatoms, as well as the presence of spring peepers and the number of insectivorous birds were among the indicators that responded most strongly to a human disturbance index, suggesting they have good potential as indicators of Great Lakes coastal wetland condition. Ecoprovince, wetland type, and indicator type (taxa vs function based) explained relatively little variance. Variance patterns for macroinvertebrates and birds were least concordant with those of other assemblages, while diatoms and amphibians, and fish and wetland vegetation were the most concordant assemblage pairs. Our results strongly suggest it will not be possible to develop effective indicators of Great Lakes coastal wetland condition without accounting for differences among A u t h o r ' s p e r s o n a l c o p y lakes and their important interactions. This is one of the first attempts to show how ecological indicators of human disturbance vary over a broad spatial scale in wetlands. #
Landscape heterogeneity and the effect of environmental conditions on prairie wetlands
Landscape Ecology, 2012
Populations can vary considerably in their response to environmental fluctuations, and understanding the mechanisms behind this variation is vital for predicting effects of environmental variation and change on population dynamics. Such variation can be caused by spatial differences in how environmental conditions influence key parameters for the species, such as availability of food or breeding grounds. Knowing how these differences are distributed in the landscape allows us to identify areas that we can expect the highest impact of environmental change, and where predictions on population dynamical effects will be most precise. We evaluated how wetland dynamics in the North-American prairies (pond counts; a key parameter for several waterfowl populations) were related to spatial and temporal variation in the environment, as measured by weather variables, primary productivity and phenology derived from annual normalized difference vegetation index (NDVI) curves, and agricultural composition of the landscape. Spatial and temporal variation in pond counts were closely related to these environmental variables. However, correlation strength and predictive ability of these environmental variables on wetland dynamics varied considerably across the study area. This variation was related to landscape characteristics and to the spatial scaling of the wetland dynamics, such that areas with late onset of spring, low spring temperature, high primary productivity, and high proportion of cropland had more predictable and spatially-homogenous dynamics. The success of predicting environmental influences on wetlands from NDVI measures derived from satellite images indicates they will be useful tools for assessing effects of changing landscape and climatic conditions on wetland ecosystems and their wildlife populations. Keywords Agricultural influence Á Climate effect Á Environmental phenology Á NDVI Á North American prairie Á Landscape variation Á Spatial heterogeneity Á Waterfowl Á Wetland ecology Electronic supplementary material The online version of this article (
Journal of Great Lakes Research, 2007
Lakes, but little is known about appropriate spatial scales to characterize disturbance or response for most indicators. We surveyed birds, fish, amphibians, aquatic macroinvertebrates, wetland vegetation, and diatoms at 276 coastal wetland locations throughout the U.S. Great Lakes coastal region during 2002-2004. We assessed the responsiveness of 66 candidate indicators to human disturbance (agriculture, urban development, and point source contaminants) characterized at multiple spatial scales (100, 500, 1,000, and 5,000 m buffers and whole watersheds) using classification and regression tree analysis (CART). Nonstressor covariables (lake, ecosection, watershed, and wetland area) accounted for a greater proportion of variance than disturbance variables. Row-crop agriculture and urban development, especially at J. Great Lakes Res. 33 (Special Issue 3):42-66 Internat. Assoc. Great Lakes Res.