Protecting local water quality has global benefits.

Surface water is among Earth's most important resources. Yet, benefit-cost studies often report that the costs of water quality protection exceed its benefits. One possible reason for this seeming paradox is that often only a narrow range of local water quality benefits are considered. In particular, the climate damages from water pollution have rarely been quantified. Recent advances in global water science allow the computation of the global methane emission from lakes caused by human nutrient enrichment (eutrophication). Here, we estimate the present value of the global social cost of eutrophication-driven methane emissions from lakes between 2015 and 2050 to be $7.5-$81 trillion (2015 $US), and in a case-study for one well-studied lake (Lake Erie) we find the global value of avoiding eutrophication exceeds local values of either beach use or sport fishing by 10-fold.

Eutrophication will increase methane emissions from lakes and impoundments during the 21st century.

Lakes and impoundments are an important source of methane (CH4), a potent greenhouse gas, to the atmosphere. A recent analysis shows aquatic productivity (i.e., eutrophication) is an important driver of CH4 emissions from lentic waters. Considering that aquatic productivity will increase over the next century due to climate change and a growing human population, a concomitant increase in aquatic CH4 emissions may occur. We simulate the eutrophication of lentic waters under scenarios of future nutrient loading to inland waters and show that enhanced eutrophication of lakes and impoundments will substantially increase CH4 emissions from these systems (+30-90%) over the next century. This increased CH4 emission has an atmospheric impact of 1.7-2.6 Pg C-CO2-eq y-1, which is equivalent to 18-33% of annual CO2 emissions from burning fossil fuels. Thus, it is not only important to limit eutrophication to preserve fragile water supplies, but also to avoid acceleration of climate change.

Greenhouse gas emissions from lakes and impoundments: upscaling in the face of global change.

Lakes and impoundments are important sources of greenhouse gases (GHG: i.e., CO2, CH4, N2O), yet global emission estimates are based on regionally-biased averages and elementary upscaling. We assembled the largest global dataset to date on emission rates of all three GHGs and found they covary with lake size and trophic state. Fitted models were upscaled to estimate global emission using global lake size inventories and a remotely-sensed global lake productivity distribution. Traditional upscaling approaches overestimated CO2 and N2O emission but underestimated CH4 by half. Our upscaled size-productivity weighted estimates (1.25-2.30 Pg of CO2-equivalents annually) are nearly 20% of global CO2 fossil fuel emission with ~75% of the climate impact due to CH4. Moderate global increases in eutrophication could translate to 5-40% increases in the GHG effects in the atmosphere, adding the equivalent effect of another 13% of fossil fuel combustion or an effect equal to GHG emissions from current land use change.

LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes.

Understanding the factors that affect water quality and the ecological services provided by freshwater ecosystems is an urgent global environmental issue. Predicting how water quality will respond to global changes not only requires water quality data, but also information about the ecological context of individual water bodies across broad spatial extents. Because lake water quality is usually sampled in limited geographic regions, often for limited time periods, assessing the environmental controls of water quality requires compilation of many data sets across broad regions and across time into an integrated database. LAGOS-NE accomplishes this goal for lakes in the northeastern-most 17 US states.LAGOS-NE contains data for 51 101 lakes and reservoirs larger than 4 ha in 17 lake-rich US states. The database includes 3 data modules for: lake location and physical characteristics for all lakes; ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes; and in situ measurements of lake water quality for a subset of the lakes from the past 3 decades for approximately 2600-12 000 lakes depending on the variable. The database contains approximately 150 000 measures of total phosphorus, 200 000 measures of chlorophyll, and 900 000 measures of Secchi depth. The water quality data were compiled from 87 lake water quality data sets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This database is one of the largest and most comprehensive databases of its type because it includes both in situ measurements and ecological context data. Because ecological context can be used to study a variety of other questions about lakes, streams, and wetlands, this database can also be used as the foundation for other studies of freshwaters at broad spatial and ecological scales.

Low ratios of silica to dissolved nitrogen supplied to rivers arise from agriculture not reservoirs.

Coastal marine systems are greatly altered by toxic marine algae, eutrophication and hypoxia. These problems have been linked to decreased ratios of dissolved silica to inorganic nitrogen (Si : DIN) delivered from land. Two mechanisms for this decline under consideration are enhanced nitrogen (N) fertiliser losses from agricultural lands or Si sequestration in reservoirs. Here we examine these mechanisms via nutrient concentrations in impoundments receiving water from 130 watersheds in a landscape representative of the agriculture that often dominates coastal nutrient inputs. Decreased Si : DIN was correlated with agriculture, not impoundment. Watersheds with > 60% agricultural land yielded highest DIN, whereas Si was uncorrelated with agricultural intensity. Furthermore, eutrophic lakes were dominated by Cyanobacteria that use little Si, so reservoirs did not diminish Si : DIN. Instead, Si : DIN increased slightly as reservoir residence time increased. These data suggest that impoundments in agricultural watersheds may enhance the water quality of coastal ecosystems, whereas fertiliser losses are detrimental.

Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse.

Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000 km(2)). LAGOS includes two modules: LAGOSGEO, with geospatial data on every lake with surface area larger than 4 ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOSLIMNO, with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated database reproducible and extensible, allowing users to ask new research questions with the existing database or through the addition of new data. The largest challenge of this task was the heterogeneity of the data, formats, and metadata. Many steps of data integration need manual input from experts in diverse fields, requiring close collaboration.

Long-term citizen-collected data reveal geographical patterns and temporal trends in lake water clarity.

We compiled a lake-water clarity database using publically available, citizen volunteer observations made between 1938 and 2012 across eight states in the Upper Midwest, USA. Our objectives were to determine (1) whether temporal trends in lake-water clarity existed across this large geographic area and (2) whether trends were related to the lake-specific characteristics of latitude, lake size, or time period the lake was monitored. Our database consisted of >140,000 individual Secchi observations from 3,251 lakes that we summarized per lake-year, resulting in 21,020 summer averages. Using Bayesian hierarchical modeling, we found approximately a 1% per year increase in water clarity (quantified as Secchi depth) for the entire population of lakes. On an individual lake basis, 7% of lakes showed increased water clarity and 4% showed decreased clarity. Trend direction and strength were related to latitude and median sample date. Lakes in the southern part of our study-region had lower average annual summer water clarity, more negative long-term trends, and greater inter-annual variability in water clarity compared to northern lakes. Increasing trends were strongest for lakes with median sample dates earlier in the period of record (1938-2012). Our ability to identify specific mechanisms for these trends is currently hampered by the lack of a large, multi-thematic database of variables that drive water clarity (e.g., climate, land use/cover). Our results demonstrate, however, that citizen science can provide the critical monitoring data needed to address environmental questions at large spatial and long temporal scales. Collaborations among citizens, research scientists, and government agencies may be important for developing the data sources and analytical tools necessary to move toward an understanding of the factors influencing macro-scale patterns such as those shown here for lake water clarity.

Cyanobacteria dominance influences resource use efficiency and community turnover in phytoplankton and zooplankton communities.

Freshwater biodiversity loss potentially disrupts ecosystem services related to water quality and may negatively impact ecosystem functioning and temporal community turnover. We analysed a data set containing phytoplankton and zooplankton community data from 131 lakes through 9 years in an agricultural region to test predictions that plankton communities with low biodiversity are less efficient in their use of limiting resources and display greater community turnover (measured as community dissimilarity). Phytoplankton resource use efficiency (RUE = biomass per unit resource) was negatively related to phytoplankton evenness (measured as Pielou's evenness), whereas zooplankton RUE was positively related to phytoplankton evenness. Phytoplankton and zooplankton RUE were high and low, respectively, when Cyanobacteria, especially Microcystis sp., dominated. Phytoplankton communities displayed slower community turnover rates when dominated by few genera. Our findings, which counter findings of many terrestrial studies, suggest that Cyanobacteria dominance may play important roles in ecosystem functioning and community turnover in nutrient-enriched lakes.

Watershed sediment losses to lakes accelerating despite agricultural soil conservation efforts.

Agricultural soil loss and deposition in aquatic ecosystems is a problem that impairs water quality worldwide and is costly to agriculture and food supplies. In the US, for example, billions of dollars have subsidized soil and water conservation practices in agricultural landscapes over the past decades. We used paleolimnological methods to reconstruct trends in sedimentation related to human-induced landscape change in 32 lakes in the intensively agricultural region of the Midwestern United States. Despite erosion control efforts, we found accelerating increases in sediment deposition from erosion; median erosion loss since 1800 has been 15.4 tons ha(-1). Sediment deposition from erosion increased >6-fold, from 149 g m(-2) yr(-1) in 1850 to 986 g m(-2) yr(-1) by 2010. Average time to accumulate one mm of sediment decreased from 631 days before European settlement (ca. 1850) to 59 days mm(-1) at present. Most of this sediment was deposited in the last 50 years and is related to agricultural intensification rather than land clearance or predominance of agricultural lands. In the face of these intensive agricultural practices, traditional soil conservation programs have not decelerated downstream losses. Despite large erosion control subsidies, erosion and declining water quality continue, thus new approaches are needed to mitigate erosion and water degradation.

Effects of watershed configuration and composition on downstream lake water quality.

We evaluated the relationships between landscape characteristics and lake water quality in receiving waters by regressing four water quality responses on landscape variables that were measured for whole watersheds and three different buffer distances (30, 60, and 120 m). Classical percolation theory was used to conceptualize nutrient pathways and to explain nonlinear responses. The response variables were total nitrogen (TN), total phosphorus (TP), chlorophyll-a (Chl-a), and Secchi transparency (SD). Landscape data were obtained from satellite image-derived maps of 130 watersheds in Iowa using geographic information systems software. We developed regression models with a stepwise protocol selecting the optimal number of significant explanatory variables. Configuration variables such as contagion, the cohesion of cropland and urban land, and the aggregation index of forest were very important and more important than variables assessing landscape composition (e.g., percentage farmland). Whole watershed models predicted between 15 and 67% of the variability in TN, TP, Chl-a, and SD. Proximity-explicit data offered only slightly improved statistical power over land cover data derived from the entire watershed for variables TN, Chl-a. and SD, but not for TP.

Freshwater methane emissions offset the continental carbon sink.

Inland waters (lakes, reservoirs, streams, and rivers) are often substantial methane (CH(4)) sources in the terrestrial landscape. They are, however, not yet well integrated in global greenhouse gas (GHG) budgets. Data from 474 freshwater ecosystems and the most recent global water area estimates indicate that freshwaters emit at least 103 teragrams of CH(4) year(-1), corresponding to 0.65 petagrams of C as carbon dioxide (CO(2)) equivalents year(-1), offsetting 25% of the estimated land carbon sink. Thus, the continental GHG sink may be considerably overestimated, and freshwaters need to be recognized as important in the global carbon cycle.

Environmental factors influencing microcystin distribution and concentration in the Midwestern United States.

During May-September 2000-2001, physicochemical data were collected from 241 lakes in Missouri, Iowa, northeastern Kansas, and southern Minnesota U.S.A., to determine the environmental variables associated with high concentrations of the cyanobacterial hepatotoxin microcystin (MC). The study region represents a south-north latitudinal gradient in increasing trophic status, with total phosphorus (TP) and total nitrogen (TN) values ranging between 2-995 and 90-15870 microg/L, respectively. Particulate MC values, measured by ELISA, ranged from undetectable to 4500 ng/L and increased with increasing latitude. Despite latitudinal trends, environmental variables explained < 50% of the variation in MC values. Inspection of MC-TN and MC-Secchi bivariate plots revealed distinctly nonlinear trends, suggesting optima for maximum MC values. Nonlinear interval maxima regression indicated that MC-TN maxima were characterized by a unimodal curve, with maximal (> 2000 ng/L) MC values occurring between 1500 and 4000 microg/L TN. Above 8000 microg/L TN all MC values were < 150 ng/L. MC-Secchi maxima were characterized by exponential decline, with maximal MC values occurring at Secchi depths < 2.5 m. The development of empirical relationships between environmental variables and MC values is critical to effective lake management and minimization of human health risks associated with the toxin. This study indicates MC values are linked to the physicochemical environment; however, the relationships are not traditional linear models.