Stream ecosystem responses to spatially variable land cover: an empirically based model for developing riparian restoration strategies

1. The restoration of native, forested riparian habitats is a widely accepted method for improving degraded streams. Little is known, however, about how the width, extent and continuity of forested vegetation along stream networks affect stream ecosystems. 2. To increase the likelihood of achieving restoration goals, restoration practitioners require quantitative tools to guide the development of restoration strategies in different catchment settings. We present an empirically based model that establishes a relationship between a ‘stress’ imposed at different locations along a stream by the spatial pattern of land cover within catchments, and the response of biologically determined ecosystem characteristics to this stress. The model provides a spatially explicit, quantitative framework for predicting the effects of changes in catchment land cover composition and spatial configuration on specific characteristics of stream ecosystems. 3. We used geospatial datasets and biological data for attached algae and benthic macroinvertebrates in streams to estimate model parameters for 40 sites in 33 distinct catchments within the mid‐Atlantic Piedmont region of the eastern U.S. Model parameters were estimated using a genetic optimisation algorithm. R² values for the resulting relationships between catchment land cover and biological characteristics of streams were substantially improved over R² values for spatially aggregated regression models based on whole‐catchment land cover. 4. Using model parameters estimated for the mid‐Atlantic Piedmont, we show how the model can be used to guide restoration planning in a case study of a small catchment. The model predicts the quantitative change in biological characteristics of the stream, such as indices of species diversity and species composition, that would occur with the implementation of a hypothetical restoration project.     

High resolution land cover data improve understanding of mechanistic linkages with stream integrity

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Effect of Native Vegetation Loss on Stream Ecosystem Processes: Dissolved Organic Matter Composition and Export in Agricultural Landscapes

Stream and river ecosystems are dependent on energetic inputs from their watersheds and thus shifts in land use from forest cover to agriculture will affect stream community composition and function. The disruption of forest-aquatic linkages alters the organic matter resources in agricultural streams. Dissolved organic matter (DOM) is the dominant form of organic matter in aquatic ecosystems, and a microbial energy source that is important for stream respiration. The concentrations and characteristics of DOM are regulated by both terrestrial (for example, terrestrial organic matter supply) and in-stream processes (for example, microbial respiration and periphyton production) that are influenced by land management. The effects of watershed land use and topographic, soil and climatic variables on DOM quantity (dissolved organic carbon concentration and load), source (terrestrial or in-stream) and quality (composition and lability) were measured in 14 streams across an agricultural land-use gradient. DOC concentration was positively correlated with watershed pasture cover and negatively correlated with watershed relief. No watershed variables were important correlates of DOC load. Stream DOM was primarily of terrestrial origin, but DOM in agricultural streams had a greater proportion of sources from in-stream sources. This may be due to reduced connection with riparian vegetation and increased in-stream primary production. We suggest that maintaining watershed tree cover greater than 52% and ensuring less than 10% of the length of riparian corridor is cleared for pasture could minimize changes to DOM composition. This is important to avoid flow-on effects for stream ecosystem processes that are mediated by DOM. Long-term DOM monitoring will be valuable for assessing the functional impacts of land-use change.     

Whole‐landscape modelling of compositional turnover in aquatic invertebrates informs conservation gap analysis: An example from south‐western Australia

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A multi-modeling approach to evaluating climate and land use change impacts in a Great Lakes River Basin

River ecosystems are driven by linked physical, chemical, and biological subsystems, which operate over different temporal and spatial domains. This complexity increases uncertainty in ecological forecasts, and impedes preparation for the ecological consequences of climate change. We describe a recently developed “multi-modeling” system for ecological forecasting in a 7600 km² watershed in the North American Great Lakes Basin. Using a series of linked land cover, climate, hydrologic, hydraulic, thermal, loading, and biological response models, we examined how changes in both land cover and climate may interact to shape the habitat suitability of river segments for common sport fishes and alter patterns of biological integrity. In scenario-based modeling, both climate and land use change altered multiple ecosystem properties. Because water temperature has a controlling influence on species distributions, sport fishes were overall more sensitive to climate change than to land cover change. However, community-based biological integrity metrics were more sensitive to land use change than climate change; as were nutrient export rates. We discuss the implications of this result for regional preparations for climate change adaptation, and the extent to which the result may be constrained by our modeling methodology.     

Stream macroinvertebrate response to catchment urbanisation (Georgia, U.S.A.)

SUMMARY 1. The effects of catchment urbanisation on water quality were examined for 30 streams (stratified into 15, 50 and 100 km² ± 25% catchments) in the Etowah River basin, Georgia, U.S.A. We examined relationships between land cover (implying cover and use) in these catchments (e.g. urban, forest and agriculture) and macroinvertebrate assemblage attributes using several previously published indices to summarise macroinvertebrate response. Based on a priori predictions as to mechanisms of biotic impairment under changing land cover, additional measurements were made to assess geomorphology, hydrology and chemistry in each stream. 2. We found strong relationships between catchment land cover and stream biota. Taxon richness and other biotic indices that reflected good water quality were negatively related to urban land cover and positively related to forest land cover. Urban land cover alone explained 29–38% of the variation in some macroinvertebrate indices. Reduced water quality was detectable at c. >15% urban land cover. 3. Urban land cover correlated with a number of geomorphic variables such as stream bed sediment size (–) and total suspended solids (+) as well as a number of water chemistry variables including nitrogen and phosphorus concentrations (+), specific conductance (+) and turbidity (+). Biotic indices were better predicted by these reach scale variables than single, catchment scale land cover variables. Multiple regression models explained 69% of variation in total taxon richness and 78% of the variation in the Invertebrate Community Index (ICI) using phi variability, specific conductance and depth, and riffle phi, specific conductance and phi variability, respectively. 4. Indirect ordination analysis was used to describe assemblage and functional group changes among sites and corroborate which environmental variables were most important in driving differences in macroinvertebrate assemblages. The first axis in a non‐metric multidimensional scaling ordination was highly related to environmental variables (slope, specific conductance, phi variability; adj. R²=0.83) that were also important in our multiple regression models. 5. Catchment urbanisation resulted in less diverse and more tolerant stream macroinvertebrate assemblages via increased sediment transport, reduced stream bed sediment size and increased solutes. The biotic indices that were most sensitive to environmental variation were taxon richness, EPT richness and the ICI. Our results were largely consistent over the range in basin size we tested.     

Relationship of fish and macroinvertebrate communities in the mid-Atlantic uplands: Implications for integrated assessments

Indices developed for stream bioassessment are typically based on either fish or macroinvertebrate assemblages. These indices consist of metrics which subsume attributes of various species into aggregate measures reflecting community-level ecological responses to disturbance. However, little is known about the relationship between fish and macroinvertebrate metrics, or about how ecological health assessments are affected by assemblage-specific responses to disturbance. We used principal component analysis (PCA) and regression analysis of existing fish (n = 371) and macroinvertebrate (n = 442) stream bioassessment data from a multi-source dataset to determine broad scale, within-assemblage metric patterns, and to examine the intercorrelation of fish and macroinvertebrate metrics (n = 246) and their response to watershed area and land use/land cover gradients. Fish and macroinvertebrate metrics expressed as principal components (PCs) accounted for 72.4 and 85.4% of dataset variance, respectively, with PC-metric patterns reflecting aspects of stream impairment including water and habitat quality. Model components predicting fish metric response differed among fish PCs, with watershed area and macroinvertebrate metric response strongly correlated with the first fish PC, and remaining fish PC models consisting of watershed area, land use, and macroinvertebrate PCs. Correlation between fish and macroinvertebrate PCs, and models relating fish and macroinvertebrate PCs generally explained less variation (13–27%) than metric response models of fish (25–34%) and macroinvertebrates (8–38%) to watershed area and land use/land cover variables. Best-response models integrating fish and macroinvertebrate PCs, watershed area, and land use/land cover variables accounted for the greatest variation in fish PCs (32–50%) across sites. Because fish and macroinvertebrate metrics provide different information on ecological condition, integrated use of information from multiple groups may be appropriate when developing monitoring programs.     

Relating land cover to stream properties in southern Chilean watersheds: trade-off between geographic scale, sample size, and explicative power

Several studies relating land cover to stream properties have used sample sizes of more than 100 watersheds, but the variance that they explain is moderate to low (R ² less than 50%), limiting the predictive value of these studies when their models are applied to watersheds that were not included in the models’ development. We hypothesize that this is due to the increases in variation that occur with increases in sample size and in the geographic scales of the areas in which the watersheds are distributed. Land cover alone cannot explain all of that variation; more predictors must be considered. Conversely, models with high explicative power would require relatively small sample sizes distributed over small areas. This hypothesis was evaluated sampling 17 watersheds from southern Chile’s Lake Region, for which we developed regressive models between land cover/watershed area/precipitation/geomorphology and stream properties (i.e., conductivity, temperature). With a maximum n = 15 watersheds, on a regional scale, a poorly explained variation in hydrologic variables (mean 37–49%) was obtained. The R ² increased slightly, to 45–52%, when precipitation was included as a predictor. In half of the cases analyzed, the models improved when geomorphology was considered as an additional predictor (60–66%), supporting our hypothesis. Furthermore, when our analysis was restricted to a narrower latitudinal span (n = 9), the R ² was much stronger (68–87%) when only land cover and watershed area were included as predictors. These percentages also increased when more predictors were incorporated. Nevertheless, a portion of unexplained variance remained that would require the consideration of more predictors, such as geology and edaphology. The documented trade-off provides evidence that argues against the spatial generality of land cover/stream property models.     

Shifts in leaf litter breakdown along a forest–pasture–urban gradient in Andean streams

Tropical montane ecosystems of the Andes are critically threatened by a rapid land‐use change which can potentially affect stream variables, aquatic communities, and ecosystem processes such as leaf litter breakdown. However, these effects have not been sufficiently investigated in the Andean region and at high altitude locations in general. Here, we studied the influence of land use (forest–pasture–urban) on stream physico‐chemical variables (e.g., water temperature, nutrient concentration, and pH), aquatic communities (macroinvertebrates and aquatic fungi) and leaf litter breakdown rates in Andean streams (southern Ecuador), and how variation in those stream physico‐chemical variables affect macroinvertebrates and fungi related to leaf litter breakdown. We found that pH, water temperature, and nutrient concentration increased along the land‐use gradient. Macroinvertebrate communities were significantly different between land uses. Shredder richness and abundance were lower in pasture than forest sites and totally absent in urban sites, and fungal richness and biomass were higher in forest sites than in pasture and urban sites. Leaf litter breakdown rates became slower as riparian land use changed from natural to anthropogenically disturbed conditions and were largely determined by pH, water temperature, phosphate concentration, fungal activity, and single species of leaf‐shredding invertebrates. Our findings provide evidence that leaf litter breakdown in Andean streams is sensitive to riparian land‐use change, with urban streams being the most affected. In addition, this study highlights the role of fungal biomass and shredder species (Phylloicus; Trichoptera and Anchytarsus; Coleoptera) on leaf litter breakdown in Andean streams and the contribution of aquatic fungi in supporting this ecosystem process when shredders are absent or present low abundance in streams affected by urbanization. Finally, we summarize important implications in terms of managing of native vegetation and riparian buffers to promote ecological integrity and functioning of tropical Andean stream ecosystems.     

APPLIED ISSUES: Exploring the response of functional indicators of stream health to land‐use gradients

1. Broad‐scale assessment of stream health is often based on correlative relationships between catchment land‐use categories and measurements of stream biota or water chemistry. Few studies have attempted to characterise the response curves that describe how measures of ecosystem function change along gradients of catchment land use, or explored how these responses vary at broad spatial scales. 2. In autumn 2008, we conducted a survey of 84 streams in three bioregions of New Zealand to assess the sensitivity of functional indicators to three land‐use gradients: percentage of native vegetation cover, percentage of impervious cover (IC) and predicted nitrogen (N) concentration. We examined these relationships using general linear models and boosted regression trees to explore monotonic, non‐monotonic and potential threshold components of the response curves. 3. When viewing the responses to individual land‐use gradients, four of five functional indicators were positively correlated with the removal of native vegetation cover and N. In general, weaker and less responsive models were observed for the IC gradient. An analysis of the response to multiple stressors showed δ¹⁵N of primary consumers and gross primary productivity (GPP) to be the most responsive functional indicators to land‐use gradients. The multivariate models identified thresholds for change in the relationship between the functional indicators and all three land‐use gradients. Apparent thresholds were <10%IC, between 40 and 80% loss of native vegetation cover and at 0.5 and 3.2 mg L^?1 N. 4. The strength of regression models and the nature of the response curves suggest that measures of ecosystem function exhibit predictable relationships with land use. Furthermore, the responses of functional indicators varied little among three bioregions. This information provides a strong argument for the inclusion of functional indicators in a holistic assessment of stream health.     

Regression Techniques for Examining Land Use/Cover Change: A Case Study of a Mediterranean Landscape

In many areas of the northern Mediterranean Basin the abundance of forest and scrubland vegetation is increasing, commensurate with decreases in agricultural land use(s). Much of the land use/cover change (LUCC) in this region is associated with the marginalization of traditional agricultural practices due to ongoing socioeconomic shifts and subsequent ecological change. Regression-based models of LUCC have two purposes: (i) to aid explanation of the processes driving change and/or (ii) spatial projection of the changes themselves. The independent variables contained in the single ‘best’ regression model (that is, that which minimizes variation in the dependent variable) cannot be inferred as providing the strongest causal relationship with the dependent variable. Here, we examine the utility of hierarchical partitioning and multinomial regression models for, respectively, explanation and prediction of LUCC in EU Special Protection Area 56, ‘Encinares del río Alberche y Cofio’ (SPA 56) near Madrid, Spain. Hierarchical partitioning estimates the contribution of regression model variables, both independently and in conjunction with other variables in a model, to the total variance explained by that model and is a tool to isolate important causal variables. By using hierarchical partitioning we find that the combined effects of factors driving land cover transitions varies with land cover classification, with a coarser classification reducing explained variance in LUCC. We use multinomial logistic regression models solely for projecting change, finding that accuracies of maps produced vary by land cover classification and are influenced by differing spatial resolutions of socioeconomic and biophysical data. When examining LUCC in human-dominated landscapes such as those of the Mediterranean Basin, the availability and analysis of spatial data at scales that match causal processes is vital to the performance of the statistical modelling techniques used here.     

Quantifying relationships between land‐use gradients and structural and functional indicators of stream ecological integrity

1. Modification of natural landscapes and land‐use intensification are global phenomena that can result in a range of differing pressures on lotic ecosystems. We analysed national‐scale databases to quantify the relationship between three land uses (indigenous vegetation, urbanisation and agriculture) and indicators of stream ecological integrity. Boosted regression tree modelling was used to test the response of 14 indicators belonging to four groups – water quality (at 578 sites), benthic invertebrates (at 2666 sites), fish (at 6858 sites) and ecosystem processes (at 156 sites). Our aims were to characterise the ecological response curves of selected functional and structural metrics in relation to three land uses, examine the environmental moderators of these relationships and quantify the relative utility of metrics as indicators of stream ecological integrity. 2. The strongest indicators of land‐use effects were nitrate + nitrite, delta‐15 nitrogen value (δ¹⁵N) of primary consumers and the Macroinvertebrate Community Index (a biotic index of organic pollution), while the weakest overall indicators were gross primary productivity, benthic invertebrate richness and fish richness. All indicators declined in response to removal of indigenous vegetation and urbanisation, while variable responses to agricultural intensity were observed for some indicators. 3. The response curves for several indicators suggested distinct thresholds in response to urbanisation and agriculture, specifically at 10% impervious cover and at 0.1 g m^?3 nitrogen concentration, respectively. 4. Water quality and ecosystem process indicators were influenced by a combination of temperature, slope and flow variables, whereas for macroinvertebrate indicators, catchment rainfall, segment slope and temperature were significant environmental predictor variables. Downstream variables (e.g. distance to the coast) were significant in explaining residual variation in fish indicators, not surprisingly given the preponderance of diadromous fish species in New Zealand waterways. The inclusion of continuous environmental variables used to develop a stream typology improved model performance more than the inclusion of stream type alone. 5. Our results reaffirm the importance of accounting for underlying spatial variation in the environment when quantifying relationships between land use and the ecological integrity of streams. Of distinctive interest, however, were the contrasting and complementary responses of different indicators of stream integrity to land use, suggesting that multiple indicators are required to identify land‐use impact thresholds, develop environmental standards and assign ecological scores for reporting purposes.     

Impact of short-term rainfall fluctuation on interannual land cover change in sub-Saharan Africa

Aim Interannual land cover change plays a significant role in food security, ecosystem processes, and regional and global climate modelling. Measuring the magnitude and location and understanding the driving factors of interannual land cover change are therefore of utmost importance to improve our understanding and prediction of these impacts and to better differentiate between natural and human causes of land cover change. Despite advances in quantifying the magnitude of land cover change, the interpretation of the observed land cover change in terms of climatic, ecological and anthropogenic processes still remains a complex issue. In this paper, we map land cover change across sub‐Saharan Africa and examine the influences of rainfall fluctuations on interannual change. Location The analysis was applied to sub‐Saharan Africa. Methods Ten‐day rainfall estimates (RFE) obtained from National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Center (CPC) were used to extract information on inter and intra‐annual rainfall fluctuations. The magnitude of land cover change was quantified based on the multitemporal change vector method measuring year‐to‐year differences in bidirectional reflectance distribution function (BRDF) corrected 16‐day enhanced vegetation index (EVI) data from the Moderate Resolution Imaging Spectro‐radiometer (MODIS). Statistical models were used to estimate the relationship between short‐term rainfall variability and the magnitude of land cover change. The analysis was stratified first by physiognomic vegetation type and second by chorological data on species distribution to gain insights into spatial variations in response to short‐term rainfall fluctuations. Results The magnitude of land cover change was significantly related to rainfall variability at the 5% level. Stratification considerably strengthened the relationship between the magnitude of change and rainfall variability. Explanatory power of the models ranged from R² = 0.22 for the unstratified model to 0.40–0.96 for the individual models stratified by patterns of species distribution. The total variability explained by the combined models including the influence of rainfall and differences in vegetation response ranged from 22% for the model not stratified by vegetation to 76% when stratified by chorological data. Main conclusions Using this methodology, we were able to measure the contribution of natural variation in precipitation to land cover change. Several ecosystems across sub‐Saharan Africa are highly sensitive to short‐term rainfall variability.     

The influence of watershed land use cover on stream fish diversity and size-at-age of a generalist fish

Changes in land use have manifold effects on stream ecosystems. Consequently, the degradation of watersheds can cause extreme responses if the resilience of the stream is exceeded, triggering changes in fish communities and a reorganization of the ecosystem. Fish community surveys are frequently used to evaluate the impact of anthropogenic pressures on freshwater streams. Dynamic indices such as individual growth are also interesting because they integrate the effects of environmental conditions through time, providing an assessment in the long term. In this study we have investigated the ecological implications of watershed land use cover on fish diversity and growth of the generalist species Umbra limi (central mudminnow) in six streams in Southern Ontario (Canada). In detail, the growth of U. limi has been explored using a Dynamic Energy Budget (DEB) model, which pursues a mechanistic explanation of the bioenergetics of an individual under different environmental conditions. Given the mechanistic approach, the outcomes of the DEB model can provide a solid foundation for extrapolating the conclusions of this study to a broader spatial scale. The results of this study reveal that the proportion of modified land use of the watershed (agricultural and urban land) can reach a tipping point beyond which the functioning of the stream abruptly changes. Consequently, land use cover may be used as a precautionary indicator for watershed management. The results also demonstrate that U. limi could be used as a sentinel species to identify potential impacts on fish diversity and size-at-age as a cost-effective indicator for stream monitoring programs.     

Relationships Between Land Cover and Dissolved Organic Matter Change Along the River to Lake Transition

Dissolved organic matter (DOM) influences the physical, chemical, and biological properties of aquatic ecosystems. We hypothesized that controls over spatial variation in DOM quantity and composition (measured with DOM optical properties) differ based on the source of DOM to aquatic ecosystems. DOM quantity and composition should be better predicted by land cover in aquatic habitats with allochthonous DOM and related more strongly to nutrients in aquatic habitats with autochthonous DOM. Three habitat types [rivers (R), rivermouths (RM), and the nearshore zone (L)] associated with 23 tributaries of the Laurentian Great Lakes were sampled to test this prediction. Evidence from optical indices suggests that DOM in these habitats generally ranged from allochthonous (R sites) to a mix of allochthonous-like and autochthonous-like (L sites). Contrary to expectations, DOM properties such as the fluorescence index, humification index, and spectral slope ratio were only weakly related to land cover or nutrient data (Bayesian R ² values were indistinguishable from zero). Strongly supported models in all habitat types linked DOM quantity (that is, dissolved organic carbon concentration [DOC]) to both land cover and nutrients (Bayesian R ² values ranging from 0.55 to 0.72). Strongly supported models predicting DOC changed with habitat type: The most important predictor in R sites was wetlands whereas the most important predictor at L sites was croplands. These results suggest that as the DOM pool becomes more autochthonous-like, croplands become a more important driver of spatial variation in DOC and wetlands become less important.     

Spatial heterogeneity of climate and land-cover constraints on distributions of tick-borne pathogens

Aim To compare the geographical distributions of two tick‐borne pathogens vectored by different tick species, to examine the relative importance of climate, land cover and host density in structuring these distributions, and to assess the spatial variability of these environmental constraints across the species ranges. Location South‐central and south‐eastern North America. Methods Presence/absence data for two tick‐borne pathogens, Ehrlichia chaffeensis and Anaplasma phagocytophilum, were obtained for 567 counties from a regional data base based on white‐tailed deer (Odocoileus virginianus) serology. Environmental variables describing climate, land cover and deer density were calculated for these counties. Global logistic regression analysis was used to screen the environmental variables and select a parsimonious subset of predictors. Local analysis was carried out using geographically weighted regression (GWR) to explore spatial variability in the parameters of the regression models. Cluster analysis was applied to the GWR output to identify zones with distinctive species–habitat relationships. Results Global habitat models for E. chaffeensis and A. phagocytophilum included temperature, humidity, precipitation and forest cover as explanatory variables. The E. chaffeensis model also included forest fragmentation, whereas the A. phagocytophilum model included deer density. Local analyses revealed that climate was the primary correlate of pathogen presence in the eastern portion of the study area, whereas forest cover and fragmentation constrained the western range boundaries. Habitat relationships for all variables were weak in and around the Mississippi Delta. Main conclusions Efforts to model pathogen and disease ranges, and to predict shifts in response to global change should consider future scenarios of land‐cover change as well as climate change, and should address the possibility of spatial heterogeneity in species–habitat relationships. The methods presented here outline an approach for objectively delineating geographical zones with similar species–environment relationships, which can then be used to stratify landscapes for the purposes of further explanatory and predictive modelling.     

Spatial-temporal character of vegetation cover and its influence factors in the Shule River Basin China,during 1985–2011

Abstract

Vegetation coverage is an important indicator of the terrestrial ecosystems, and it provides crucial significance for evaluation and analysis of vegetation change. The Shule River Basin is a typical ecological fragile region in the inland of Northwest China. We used vegetation coverage index as given in Technical Specifications for Assessment of Ecological Environment. Geographic information system (GIS) spatial analysis was used to analyze the temporal and spatial features of vegetation cover in the Shule River Basin and its influencing factors from 1986 to 2011. The results showed that vegetable cover is very low in most areas of Shule River Basin with only the upstream parts of the oasis and watershed haven high vegetation cover. The average vegetation coverage index increased from 6.78 to 8.31 during 1986–2011. An area of 59,998?km² in the Shule River Basin has unchanged vegetation coverage index and this account for 51.7% of watershed areas for the period of the study. Also, an area of 31,721?km² recorded an increased vegetable cover, accounting for 27.3% while an area of 24,372?km² decreased vegetation cover which accounts for 21.0%. There was different correlation between vegetation cover and annual precipitation in the Shule River Basin.     

Human activities cause distinct dissolved organic matter composition across freshwater ecosystems

Dissolved organic matter (DOM) composition in freshwater ecosystems is influenced by the interactions among physical, chemical, and biological processes that are controlled, at one level, by watershed landscape, hydrology, and their connections. Against this environmental template, humans may strongly influence DOM composition. Yet, we lack a comprehensive understanding of DOM composition variation across freshwater ecosystems differentially affected by human activity. Using optical properties, we described DOM variation across five ecosystem groups of the Laurentian Great Lakes region: large lakes, Kawartha Lakes, Experimental Lakes Area, urban stormwater ponds, and rivers (n = 184 sites). We determined how between ecosystem variation in DOM composition related to watershed size, land use and cover, water quality measures (conductivity, dissolved organic carbon (DOC), nutrient concentration, chlorophyll a), and human population density. The five freshwater ecosystem groups had distinctive DOM composition from each other. These significant differences were not explained completely through differences in watershed size nor spatial autocorrelation. Instead, multivariate partial least squares regression showed that DOM composition was related to differences in human impact across freshwater ecosystems. In particular, urban/developed watersheds with higher human population densities had a unique DOM composition with a clear anthropogenic influence that was distinct from DOM composition in natural land cover and/or agricultural watersheds. This nonagricultural, human developed impact on aquatic DOM was most evident through increased levels of a microbial, humic‐like parallel factor analysis component (C6). Lotic and lentic ecosystems with low human population densities had DOM compositions more typical of clear water to humic‐rich freshwater ecosystems but C6 was only present at trace to background levels. Consequently, humans are strongly altering the quality of DOM in waters nearby or flowing through highly populated areas, which may alter carbon cycles in anthropogenically disturbed ecosystems at broad scales.