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Resilience was compared for alternate states of phytoplankton pigment concentration in two multiyear whole-lake experiments designed to shift the manipulated ecosystem between alternate states. Mean exit time, the average time between threshold crossings, was calculated from automated measurements every 5 min during summer stratification. Alternate states were clearly identified, and equilibria showed narrow variation in bootstrap analysis of uncertainty. Mean exit times ranged from 13 to 290 h. In the reference ecosystem, Paul Lake, mean exit time of the low-pigment state was about 100 h longer than mean exit time of the high-pigment state. In the manipulated ecosystem, Peter Lake, mean exit time of the high-pigment state exceeded that of the low-pigment state by 30 h in the cascade experiment. In the enrichment experiment mean exit time of the low-pigment state was longer than that of the high-pigment state by about 100 h. Mean exit time is a useful measure of resilience for stochastic ecosystems where high-frequency measurements are made by consistent methods over the full range of ecosystem states.

Concentrations of phycocyanin, a pigment of Cyanobacteria, were measured at 1‐min intervals during the ice‐free seasons of 2008–2018 by automated sensors suspended from a buoy at a central station in Lake Mendota, Wisconsin, U.S.A. In each year, stochastic‐dynamic models fitted to time series of log‐transformed phycocyanin concentration revealed two alternative stable states and random factors that were much larger than the difference between the alternate stable states. Transitions between low and high states were abrupt and apparently driven by stochasticity. Variation in annual magnitudes of the alternate states and the stochastic factors were not correlated with annual phosphorus input to the lake. At daily time scales, however, phycocyanin concentration was correlated with phosphorus input, precipitation, and wind velocity for time lags of 1–15 d. Multiple years of high‐frequency data were needed to discern these patterns in the noise‐dominated dynamics of Cyanobacteria.

We conducted a 33‐yr series of whole‐lake experiments to measure ecosystem responses to food web structure and nutrient load, compare aquatic and terrestrial carbon flows to consumers, and evaluate indicators of ecosystem resilience. These manipulations showed that chlorophyll responded to nutrient loading and to grazing controlled by a trophic cascade. In this article, we synthesized experimental results using a new analysis of heretofore unrecognized variation in water color, measured as light absorbance at 440 nm. Long‐term data revealed fluctuations in precipitation that drive water color variation. We compared effects of nutrient loading, zooplankton biomass, zooplankton body size, and water color on chlorophyll. Water color was an important factor in the chlorophyll response. This driver of the chlorophyll response to manipulation was not resolved until decades of data were available. A long‐term context enriched insights from ecosystem experiments and exemplified the complementarity of experimental and long‐term approaches in limnology.

Predicting algal blooms both within and among aquatic ecosystems is important yet difficult because multiple factors promote and suppress blooms. Statistical indicators (e.g., variance and autocorrelation) based on time series can provide warning of transitions in diverse complex systems, including shifts from clear water to algal blooms. Analogous spatial indicators have been demonstrated with models and empirical data from vegetated terrestrial ecosystems. Here, we test the applicability of spatial indicators to algal blooms using a nutrient‐phytoplankton spatial model. We found that standard deviation and autocorrelation successfully distinguished bloom state and proximity to transitions, while skewness and kurtosis were more ambiguous. Our findings suggest certain spatial indicators are applicable to aquatic ecosystems despite dynamic physical–biological interactions that could reduce detectable signals. The growing capacity to collect spatial data on algal biomass presents an exciting opportunity for application and testing of spatial indicators to the study and management of blooms.

Understanding the combined and separate effects of climate and land use change on the water cycle is necessary to mitigate negative impacts. However, existing methodologies typically divide data into discrete (before and after) periods, implicitly representing climate and land use as step changes when in reality these changes are often gradual. Here, we introduce a new regression-based methodological framework designed to separate climate and land use effects on any hydrological flux of interest continuously through time, and estimate uncertainty in the contribution of these two drivers. We present two applications in the Yahara River Watershed (Wisconsin, USA) demonstrating how our approach can be used to understand synergistic or antagonistic relationships between land use and climate in either the past or the future: (1) historical streamflow, baseflow, and quickflow in an urbanizing subwatershed; and (2) simulated future evapotranspiration, drainage, and direct runoff from a suite of contrasting climate and land use scenarios for the entire watershed. In the historical analysis, we show that ∼60% of recent streamflow changes can be attributed to climate, with approximately equal contributions from quickflow and baseflow. However, our continuous method reveals that baseflow is significantly increasing through time, primarily due to land use change and potentially influenced by long-term increases in groundwater storage. In the simulation of future changes, we show that all components of the future water balance will respond more strongly to changes in climate than land use, with the largest potential land use effects on drainage. These results indicate that diverse land use change trajectories may counteract each other while the effects of climate are more homogeneous at watershed scales. Therefore, management opportunities to counteract climate change effects will likely be more effective at smaller spatial scales, where land use trajectories are unidirectional.

Phosphorus runoff from agricultural land is a major cause of eutrophication in lakes and reservoirs. Frequency and intensity of extreme precipitation events are increasing in agricultural regions of the Upper Midwestern U.S., and these increases are projected to continue as climate warms. We quantified the linkage between extreme daily precipitation and extreme daily discharge, phosphorus (P) load, and P concentration for Pheasant Branch and the Yahara River, two tributaries of Lake Mendota, Wisconsin, U.S.A. using the generalized Pareto distribution. Although precipitation extremes have increased since 1940, over the shorter period of stream monitoring (1994–2015 for Pheasant Branch and 1991–2015 for Yahara) there is no significant trend in extreme precipitation. Nonetheless a disproportionate number of extreme precipitation events (for example seven of the 11 largest 24-h events since 1901) occurred during the period of stream monitoring. Daily precipitation extremes were associated with extremes in daily discharge and P load. P load return levels increased steeply and almost linearly with precipitation on log-log axes. The trend toward more frequent and intense precipitation extremes will increase P loading and intensify the eutrophication of the lake, unless the excessive P enrichment of the watershed is reversed.

The Safe Operating Space (SOS) of a recreational fishery is the multidimensional region defined by levels of harvest, angler effort, habitat, predation and other factors in which the fishery is sustainable into the future. SOS boundaries exhibit trade-offs such that decreases in harvest can compensate to some degree for losses of habitat, increases in predation and increasing value of fishing time to anglers. Conversely, high levels of harvest can be sustained if habitat is intact, predation is low, and value of fishing effort is moderate. The SOS approach recognizes limits in several dimensions: at overly high levels of harvest, habitat loss, predation, or value of fishing effort, the stock falls to a low equilibrium biomass. Recreational fisheries managers can influence harvest and perhaps predation, but they must cope with trends that are beyond their control such as changes in climate, loss of aquatic habitat or social factors that affect the value of fishing effort for anglers. The SOS illustrates opportunities to manage harvest or predation to maintain quality fisheries in the presence of trends in climate, social preferences or other factors that are not manageable.

Climate change has generated growing interest in extreme events, and extremes are known to have important consequences for ecosystems. Theoretical mechanisms generating frequent extremes apply to both environmental and biological processes, yet past studies of ecological extremes have focused primarily on the abiotic environment. The rarity or commonness of extremes in biological time series is unknown. We evaluated the statistical tendency to produce extreme events in 595 biological, chemical, physical, and meteorological time series taken from 11 lakes. We found that extreme events were much more likely to occur for biological variables than for other categories. Additional analysis revealed that the tendency to produce extremes was driven primarily by within‐year dynamics, suggesting that processes occurring at short time scales underlie the high frequency of extremes in biological variables. These results should lead us to expect surprises in long‐term observations of biological populations.

Decades of fertilizer and manure applications have led to a buildup of phosphorus (P) in agricultural soils and sediments, commonly referred to as legacy P. Legacy P can provide a long-term source of P to surface waters where it causes eutrophication. Using a suite of numerical models, we investigated the influence of legacy P on water quality in the Yahara Watershed of southern Wisconsin, USA. The suite included Agro-IBIS, a terrestrial ecosystem model; THMB, a hydrologic and nutrient routing model; and the Yahara Water Quality Model which estimates water quality indicators in the Yahara chain of lakes. Using five alternative scenarios of antecedent P storage (legacy P) in soils and channels under historical climate conditions, we simulated outcomes of P yield from the landscape, lake P loading, and three lake water quality indicators. Legacy P had a significant effect on lake loads and water quality. Across the five scenarios for Lake Mendota, the largest and most upstream lake, average P yield (kg ha−1) varied by −41 to +22%, P load (kg y−1) by −35 to +14%, summer total P (TP) concentration (mg l−1) by −25 to +12%, Secchi depth (m) by −7 to +3%, and the probability of hypereutrophy by −67 to +34%, relative to baseline conditions. The minimum storage scenario showed that a 35% reduction in present-day loads to Lake Mendota corresponded with a 25% reduction in summer TP and smaller reductions in the downstream lakes. Water quality was more vulnerable to heavy rainfall events at higher amounts of P storage and less so at lower amounts. Increases in heavy precipitation are expected with climate change; therefore, water quality could be protected by decreasing P reserves.

We examined horizontal spatial patterns of fish densities and zooplankton biomass at a fine spatial scale of 50 m across seasons before, during, and after an experimental lake destratification to determine how interacting trophic levels may respond to alteration of thermal stratification. We used semivariogram analysis to calculate maximum distances of autocorrelation for fish and zooplankton separately, and cross variograms to determine whether relationships between fish and zooplankton are positive or negative. Fish became more dispersed during the manipulation, likely due to a flight response with the loss of preferred cold water habitat. There were no changes in zooplankton horizontal distributions with mixing, but we detected seasonal trends in distribution and biomass. We detected positive relationships between fish densities and zooplankton biomass for portions of the year, but did not detect any negative relationships. There was no effect of lake mixing on spatial interactions between fish and zooplankton. Our results indicate that external factors, such as seasonal wind patterns, may drive whole-lake zooplankton distributions, and that fish respond horizontally to change in vertically structured processes, especially when reliant on depth-dependent variables such as cold water.

The planetary boundary framework presents a ‘planetary dashboard’ of humanity’s globally aggregated performance on a set of environmental issues that endanger the Earth system’s capacity to support humanity. While this framework has been highly influential, a critical shortcoming for its application in sustainability governance is that it currently fails to represent how impacts related to one of the planetary boundaries affect the status of other planetary boundaries. Here, we surveyed and provisionally quantified interactions between the Earth system processes represented by the planetary boundaries and investigated their consequences for sustainability governance. We identified a dense network of interactions between the planetary boundaries. The resulting cascades and feedbacks predominantly amplify human impacts on the Earth system and thereby shrink the safe operating space for future human impacts on the Earth system. Our results show that an integrated understanding of Earth system dynamics is critical to navigating towards a sustainable future.

Successful management of natural resources requires local action that adapts to larger‐scale environmental changes in order to maintain populations within the safe operating space (SOS) of acceptable conditions. Here, we identify the boundaries of the SOS for a managed freshwater fishery in the first empirical test of the SOS concept applied to management of harvested resources. Walleye (Sander vitreus) are popular sport fish with declining populations in many North American lakes, and understanding the causes of and responding to these changes is a high priority for fisheries management. We evaluated the role of changing water clarity and temperature in the decline of a high‐profile walleye population in Mille Lacs, Minnesota, USA, and estimated safe harvest under changing conditions from 1987 to 2017. Thermal–optical habitat area (TOHA)—the proportion of lake area in which the optimal thermal and optical conditions for walleye overlap—was estimated using a thermodynamic simulation model of daily water temperatures and light conditions. We then used a SOS model to analyze how walleye carrying capacity and safe harvest relate to walleye thermal–optical habitat. Thermal–optical habitat area varied annually and declined over time due to increased water clarity, and maximum safe harvest estimated by the SOS model varied by nearly an order of magnitude. Maximum safe harvest levels of walleye declined with declining TOHA. Walleye harvest exceeded safe harvest estimated by the SOS model in 16 out of the 30 yr of our dataset, and walleye abundance declined following 14 of those years, suggesting that walleye harvest should be managed to accommodate changing habitat conditions. By quantifying harvest trade‐offs associated with loss of walleye habitat, this study provides a framework for managing walleye in the context of ecosystem change.

Eutrophication of freshwaters occurs in watersheds with excessive pollution of phosphorus (P). Factors that affect P cycling and transport, including climate and land use, are changing rapidly and can have legacy effects, making future freshwater quality uncertain. Focusing on the Yahara Watershed (YW) of southern Wisconsin, USA, an intensive agricultural landscape, we explored the relative influence of land use and climate on three indicators of water quality over a span of 57 years (2014–2070). The indicators included watershed-averaged P yield from the land surface, direct drainage P loads to a lake, and average summertime lake P concentration. Using biophysical model simulations of future watershed scenarios, we found that climate exerted a stronger influence than land use on all three indicators, yet land use had an important role in influencing long term outcomes for each. Variations in P yield due to land use exceeded those due to climate in 36 of 57 years, whereas variations in load and lake total P concentration due to climate exceeded those due to land use in 54 of 57 years, and 52 of 57 years, respectively. The effect of land use was thus strongest for P yield off the landscape and attenuated in the stream and lake aquatic systems where the influence of weather variability was greater. Overall these findings underscore the dominant role of climate in driving inter-annual nutrient fluxes within the hydrologic network and suggest a challenge for land use to influence water quality within streams and lakes over timescales less than a decade. Over longer timescales, reducing applications of P throughout the watershed was an effective management strategy under all four climates investigated, even during decades with wetter conditions and more frequent extreme precipitation events.

Scenarios are increasingly used for envisioning future social-ecological changes and consequences for human well-being. One approach integrates qualitative storylines and biophysical models to explore potential futures quantitatively and maximize public engagement. However, this integration process is challenging and sometimes oversimplified. Using the Yahara Watershed (Wisconsin, USA) as a case study, we present a transparent and reproducible roadmap to develop spatiotemporally explicit biophysical inputs climate, land use/cover (LULC), and nutrients that are consistent with scenario narratives and can be linked to a process-based biophysical modeling suite to simulate long-term dynamics of a watershed and a range of ecosystem services. Our transferrable approach produces daily weather inputs by combining climate model projections and a stochastic weather generator, annual narrative-based watershed-scale LULC distributed spatially using transition rules, and annual manure and fertilizer (nitrogen and phosphorus) inputs based on current farm and livestock data that are consistent with each scenario narrative. Novel approach to determine spatiotemporally explicit biophysical model inputs.Inputs include climate, land use/land cover, and land nutrient applications.Communication between scenario narrative writers and modeling team is critical.

As human populations increase and land-use intensifies, toxic and unsightly nuisance blooms of algae are becoming larger and more frequent in freshwater lakes. In most cases, the blooms are predominantly blue-green algae (Cyanobacteria), which are favored by low ratios of nitrogen to phosphorus. In the past half century, aquatic scientists have devoted much effort to understanding the causes of such blooms and how they can be prevented or reduced. Here we review the evidence, finding that numerous long-term studies of lake ecosystems in Europe and North America show that controlling algal blooms and other symptoms of eutrophication depends on reducing inputs of a single nutrient: phosphorus. In contrast, small-scale experiments of short duration, where nutrients are added rather than removed, often give spurious and confusing results that bear little relevance to solving the problem of cyanobacteria blooms in lakes.

Variable flows of food, water, or other ecosystem services complicate planning. Management strategies that decrease variability and increase predictability may therefore be preferred. However, actions to decrease variance over short timescales (2-4 y), when applied continuously, may lead to long-term ecosystem changes with adverse consequences. We investigated the effects of managing short-term variance in three well-understood models of ecosystem services: lake eutrophication, harvest of a wild population, and yield of domestic herbivores on a rangeland. In all cases, actions to decrease variance can increase the risk of crossing critical ecosystem thresholds, resulting in less desirable ecosystem states. Managing to decrease short-term variance creates ecosystem fragility by changing the boundaries of safe operating spaces, suppressing information needed for adaptive management, cancelling signals of declining resilience, and removing pressures that may build tolerance of stress. Thus, the management of variance interacts strongly and inseparably with the management of resilience. By allowing for variation, learning, and flexibility while observing change, managers can detect opportunities and problems as they develop while sustaining the capacity to deal with them.

Nonpoint source pollution is the runoff of pollutants (including soil and nutrients) from agricultural, urban, and other lands (as opposed to point source pollution, which comes directly from one outlet). Many efforts have been made to combat both types of pollution, so why are we making so little progress in improving water quality by reducing runoff of soil and nutrients into lakes and rivers? This essay examines the challenges inherent in: 1) producing science to predict and assess nonpoint management and policy effectiveness; and 2) using science for management and policy-making. Barriers to demonstrating causality include few experimental designs, different spatial scales for behaviors and measured outcomes, and lags between when policies are enacted and when their effects are seen. Primary obstacles to using science as evidence in nonpoint policy include disagreements about values and preferences, disputes over validity of assumptions, and institutional barriers to reconciling the supply and demand for science. We will illustrate some of these challenges and present possible solutions using examples from the Yahara Watershed in Wisconsin. Overcoming the barriers to nonpoint-pollution prevention may require policy-makers to gain a better understanding of existing scientific knowledge and act to protect public values in the face of remaining scientific uncertainty.

Species’ thermal limits play a key role in determining spatial distributions and understanding their response to changing environments. Manipulation of thermal habitat is a potential avenue of exploration for management of invasive species such as the cold-water rainbow smelt (Osmerus mordax), which has adverse effects on native fish communities in central North American inland lakes. In an effort to test the thermal limits and selectively eradicate rainbow smelt, we experimentally mixed Crystal Lake, Wisconsin, USA, during summer of 2012 and 2013 to warm the hypolimnion and eliminate cold-water habitat. This whole-ecosystem manipulation allowed for field testing of published thermal thresholds reported for rainbow smelt. The rainbow smelt population responded to the thermal manipulation by exhibiting unexpected shifts in behavior, intrapopulation divergence in body condition, and significant population declines. Small individuals of each adult age-class tended to survive the manipulation, and the population persisted despite high mortality rates. Our results indicate a high degree of size-based intrapopulation variation in thermal sensitivity for this species. Our findings also raise questions regarding applicability of lab- and model-derived thermal limits to field scenarios, highlighting a need for further field evaluations of species’ thermal limits.

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.

Rapid changes in state have been documented for many of Earth's ecosystems. Despite a growing toolbox of methods for detecting declining resilience or early warning indicators (EWIs) of ecosystem transitions, these methods have rarely been evaluated in whole-ecosystem trials using reference ecosystems. In this study, we experimentally tested EWIs of cyanobacteria blooms based on changes in the spatial structure of a lake. We induced a cyanobacteria bloom by adding nutrients to an experimental lake and mapped fine-resolution spatial patterning of cyanobacteria using a mobile sensor platform. Prior to the bloom, we detected theoretically predicted spatial EWIs based on variance and spatial autocorrelation, as well as a new index based on the extreme values. Changes in EWIs were not discernible in an unenriched reference lake. Despite the fluid environment of a lake where spatial heterogeneity driven by biological processes may be overwhelmed by physical mixing, spatial EWIs detected an approaching bloom suggesting the utility of spatial metrics for signaling ecological thresholds.

Based on empirical and synthetic research, lakes make, store, and mineralize organic carbon (OC) at rates that are significant and relevant to regional and global carbon budgets. Although some global-scale studies have examined specific processes such as carbon burial and CO2 exchange with the atmosphere, most studies of lake carbon cycling are from single systems, focus only on a specific habitat, and do not account for all of the major terms in OC budgets. Hence, most lake OC budgets are incomplete, leaving some key processes highly uncertain. To advance the analysis of the role of the inland waters in C-cycling, ecosystem science needs a new generation of studies that confront these shortcomings. Here we address research needs and priorities for improving OC budgets. We present ten key research questions and recommend a framework for essential ecosystem-scale studies of lake OC cycling. Answers to these ten questions will not only improve carbon budgets but also provide robust estimates of lake contributions to global and regional carbon cycling. In addition, studies of lake carbon budgets will provide relative autochthonous and allochthonous carbon fluxes, indicate sources and rates of carbon burial, improve quantification of lake-atmosphere carbon exchanges, better integrate lakes with terrestrial and lotic carbon dynamics, promote understanding of how climate and land-use change will impact lakes, and enable tests of ecological theory related to subsidies and food web stability.

Changes in fertilizer use, manure management or precipitation may alter the frequency of episodes of high nutrient runoff and thereby affect annual nutrient loads and total nutrient concentrations of lakes. We developed an empirical, stochastic model for daily P loads and used the model to project annual P loads and summer total P concentrations in Lake Mendota, Wisconsin, USA. Daily P loads (8,250 daily observations) were fit closely by a three-part gamma distribution composed of days with low, intermediate, and high P loads. High P load days happen when heavy rains or snowmelt occur on soil with abundant P, often as a result of manure or inorganic fertilizer application. In Lake Mendota, on average 29 days per year accounted for 74 % of the annual load. Simulations showed that median annual P loads increased linearly with the frequency of high P load days. However, the upper quantiles of the annual P load distribution increased more steeply than the median. Increases in the number of high P load days per year also increased summer concentrations of P in the lake. Thus increases in the frequency of high P load days due to larger precipitation events or increased application of fertilizers and manure may worsen widespread problems caused by P pollution of lakes in this agricultural watershed.

Resources in lakes are vertically partitioned due to stratification and trophic interactions. Metalimnetic phytoplankton could be an important resource for zooplankton that either reside in the metalimnion or migrate through this layer. However, it is difficult to estimate metalimnetic resource use, especially using isotope approaches, because surface and deep phytoplankton often have similar isotopic compositions. To overcome this limitation, we experimentally enriched the metalimnetic dissolved inorganic carbon (DIC) 13C pool in Peter Lake to enhance the isotopic separation between metalimnetic phytoplankton and other resources. Metalimnetic d13CDIC peaked at 73.2% after the isotope addition and maintained an average enrichment of 34.5% above epilimnetic d13C-DIC for 62 d. Combining hydrogen and carbon stable isotope values, we estimated the epilimnetic, metalimnetic, and terrestrial resource use by zooplankton, using a Bayesian mixing model that accounted for uncertainties in both consumers and sources. We also measured diel vertical migration and net ecosystem production with in situ bottle incubations over the course of the experiment. Metalimnetic resource use was minor (0–8%) for zooplankton that either resided in the epilimnion of the lake during the day or migrated there at night. For consumers that resided in the metalimnion, metalimnetic phytoplankton accounted for 18– 21% of zooplankton isotope composition. The most important resource for all zooplankton was terrestrial organic matter (56–73% of consumer mass), regardless of habitat. This experiment indicates that, in lakes like Peter Lake, metalimnetic autochthonous resources are of minor importance to zooplankton relative to epilimnetic autochthonous and allochthonous resources.

Trophic responses to phosphorus (P) loads spanning 29–33 years were assessed for the eutrophic Yahara chain of lakes: Mendota (area = 39.6 km 2 , mean depth = 12.7 m, flushing rate = 0.23 yr −1 ); Monona (13.7 km 2 , 8.3 m, 1.3 yr −1 ); Waubesa (8.5 km 2 , 4.7 m, 4.3 yr −1 ); and Kegonsa (13.0 km 2 , 5.1 m, 3.0 yr −1 ). During extended drought periods with low P loads, summer (Jul–Aug) total P (TP) concentrations declined substantially in all 4 lakes, with Mendota achieving mesotrophic conditions (

Environmental sensor networks are developing rapidly to assess changes in ecosystems and their services. Some ecosystem changes involve thresholds, and theory suggests that statistical indicators of changing resilience can be detected near thresholds. We examined the capacity of environmental sensors to assess resilience during an experimentally induced transition in a whole-lake manipulation. A trophic cascade was induced in a planktivore-dominated lake by slowly adding piscivorous bass, whereas a nearby bass-dominated lake remained unmanipulated and served as a reference ecosystem during the 4-y experiment. In both the manipulated and reference lakes, automated sensors were used to measure variables related to ecosystem metabolism (dissolved oxygen, pH, and chlorophyll-a concentration) and to estimate gross primary production, respiration, and net ecosystem production. Thresholds were detected in some automated measurements more than a year before the completion of the transition to piscivore dominance. Directly measured variables (dissolved oxygen, pH, and chlorophyll-a concentration) related to ecosystem metabolism were better indicators of the approaching threshold than were the estimates of rates (gross primary production, respiration, and net ecosystem production); this difference was likely a result of the larger uncertainties in the derived rate estimates. Thus, relatively simple characteristics of ecosystems that were observed directly by the sensors were superior indicators of changing resilience. Models linked to thresholds in variables that are directly observed by sensor networks may provide unique opportunities for evaluating resilience in complex ecosystems.

SUMMARY 1. Lake food webs can be supported by primary production from within the lake, organic matter imported from the catchment or some mixture of these two sources. Generalisations about food-web subsidies to lake ecosystems are often based on data from only a few ecosystems and therefore do not consider the potential variability of subsidies among diverse ecosystems in a landscape. 2. We measured the variation among lake ecosystems in terrestrial (allochthonous) utilisation by pelagic consumers and developed models to describe the variability. Stable isotope ratios of hydrogen and carbon were measured for Chaoborus spp. and crustacean zooplankton taxa in 40 lakes to quantify consumer allochthonous resource use (allochthony). 3. The median fraction of consumer allochthony estimated using a two-source Bayesian mixing model varied between 4 and 82% (mean among all lakes = 36%) for Chaoborus sp. among lakes and between 1 and 76% in a more limited sample of crustacean zooplankton consumers. The degree of allochthonous resource use increased linearly with the availability of allochthonous resources. 4. Terrestrial support of Chaoborus was correlated (using best fitting relationships) with covariates for lake organic matter sources including dissolved inorganic carbon, total phosphorus, chlorophyll a, colour and catchment area. However, the most parsimonious model was an inverse relationship between lake surface area and consumer allochthony, indicating that allochthonous subsidies are more important in smaller than larger systems. Given the preponderance of small waterbodies, allochthonous subsidies are important in a large number of lake ecosystems.

We investigate the temporal patterns in inter-annual variability in ice breakup dates for Lakes Mendota and Monona, Wisconsin, between 1905 and 2004. We analyze the contributions of long-term trends attributed to climate change, local weather, indices of sunspots, and large-scale climatic drivers, such as the North Atlantic Oscillation (NAO) and El Niňo Southern Ocean Index (ENSO) on time series of lake-ice breakup. The relative importance of the aforementioned explanatory variables was assessed using linear regression and variation partitioning models accounting for cyclic temporal dynamics as represented by Moran Eigenvector Maps (MEM). Model results explain an average of 58 % of the variation in ice breakup dates. A combination of the long-term linear trends, rain and snowfall in the month prior to breakup, air temperature in the winter prior to breakup, cyclic dynamics associated with sunspot numbers, ENSO, and for Lake Mendota, NAO, all significantly influence the timing of ice breakup. Significant cycle lengths were 3.5, 9, 11, and 50 years. Despite their proximity, Lakes Mendota and Monona exhibit differences in how and which explanatory variables were incorporated into the models. Our results indicate that lake ice dynamics are complex in both lakes and multiple interacting processes explain the residuals around the linear warming trends that characterize lake ice records.

Directional change in environmental drivers sometimes triggers regime shifts in ecosystems. Theory and experiments suggest that regime shifts can be detected in advance, and perhaps averted, by monitoring resilience indicators such as variance and autocorrelation of key ecosystem variables. However, it is uncertain whether management action prompted by a change in resilience indicators can prevent an impending regime shift. We caused a cyanobacterial bloom by gradually enriching an experimental lake while monitoring an unenriched reference lake and a continuously enriched reference lake. When resilience indicators exceeded preset boundaries, nutrient enrichment was stopped in the experimental lake. Concentrations of algal pigments, dissolved oxygen saturation, and pH rapidly declined following cessation of nutrient enrichment and became similar to the unenriched lake, whereas a large bloom occurred in the continuously enriched lake. This outcome suggests that resilience indicators may be useful in management to prevent unwanted regime shifts, at least in some situations. Nonetheless, a safer approach to ecosystem management would build and maintain the resilience of desirable ecosystem conditions, for example, by preventing excessive nutrient input to lakes and reservoirs.

It is virtually impossible to quantify the limnological characteristics of every aquatic ecosystem all the time. The goal of this study was to assess the capacity of lake-monitoring data to predict annually resolved characteristics in systems where measurements are not always made. To address this, we provide an analysis of interpolation (i.e., predicting a current lake characteristic based on current characteristics of other lakes) and forecasting (i.e., predicting a current lake characteristic based on historical trends and characteristics of a set of study lakes) in seven lakes over a 28yr time frame. Themosteffective interpolations aregenerated using12–15yr of training data. Interpolation modelsare 29%more effective, on average, when historical trends (forecasting) are also incorporated into the models. Forecasting models that predict lake characteristics using long-term trends in the focal lake were improved by including historical observations from other lakes. Direct comparisons of different prediction models further demonstrated that it is sometimes more effective to generate predictions based on a set of previously measured conditions (forecasts) rather than a set of knownregional conditions that have been recentlyquantified (interpolations). Basic monitoring data have the potential to be upscaled to generate predictions of lake characteristics, but the effectiveness of predictions depend on the training data characteristics and prediction approaches employed.

Whole-ecosystem metabolism is often estimated in lakes using high frequency free-water measurements of dissolved oxygen (DO) taken in the upper mixed layer. DO dynamics in the metalimnion are not adequately captured by measurements made in the upper mixed layer, which could reduce the accuracy of whole-lake metabolism estimates made from such data. However, estimating metabolism from metalimnetic DO time series can be challenging because of high variability (noise). This study used simulated and field data to determine if metabolism estimates from metalimnetic data containing noise can be improved by accounting for both process and observation error in models. When DO time series exhibited high variability, free-water metabolism estimates obtained using a Kalman filter (which accounts for both process and observation error) were substantially more accurate than estimates obtained from models that did not account for error or accounted for process error only.

Surface freshwaters—lakes, reservoirs, and rivers—are among the most extensively altered ecosystems on Earth. Transformations include changes in the morphology of rivers and lakes, hydrology, biogeochemistry of nutrients and toxic substances, ecosystem metabolism and the storage of carbon (C), loss of native species, expansion of invasive species, and disease emergence. Drivers are climate change, hydrologic flow modification, land-use change, chemical inputs, aquatic invasive species, and harvest. Drivers and responses interact, and their relationships must be disentangled to understand the causes and consequences of change as well as the correctives for adverse change in any given watershed. Beyond its importance in terms of drinking water, freshwater supports human well-being in many ways related to food and fiber production, hydration of other ecosystems used by humans, dilution and degradation of pollutants, and cultural values. A natural capital framework can be used to assess freshwater ecosystem services, competing uses for freshwaters, and the processes that underpin the long-term maintenance of freshwaters. Upper limits for human consumption of freshwaters have been proposed, and consumptive use may approach these limits by the mid-century.

Lakeshore residential development (LRD) is associated with both low riparian tree density and reduced structural complexity of the littoral zone. Fallen trees from riparian zones (coarse woody habitat [CWH]) provide littoral structure for fish refuge, substrate for invertebrate production, and habitat for nesting fish. We performed a subsurface viewing and snorkel survey comparing the spawning behavior of largemouth bass Micropterus salmoides in six lakes that span the known regional gradients of CWH and LRD in Wisconsin's Northern Highlands Lake District. We tested for differences in the water depth at nest sites and the nest distance to littoral structures (including every dock encountered) among lakes with contrasting CWH or LRD density. Largemouth bass nested under or near CWH in lakes with high CWH density. In lakes with low CWH, many males nested near CWH; however, nests contained smaller pieces of wood and were established in deeper water within low-CWH lakes than within high-CWH lakes. No...

A phosphorus (P) budget was estimated for the watershed of Lake Mendota, Wisconsin, to assess the effects of nutrient management on P accumulation in the watershed soils. We estimated how nutrient management programs and legislation have affected the budget by comparing the budget for 2007 to a budget calculated for 1995, prior to implementation of the programs. Since 1995, inputs decreased from 1,310,000 to 853,000 kg P/yr (35% reduction) and accumulation decreased from 575,000 to 279,000 kg P/yr (51% reduction). Changes in P input and accumulation were attributed primarily to enhanced agricultural nutrient management, reduction in dairy cattle feed supplements and an urban P fertilizer ban. Four scenarios were investigated to determine potential impacts of additional nutrient management tactics on the watershed P budget and P loading to Lake Mendota. Elimination of chemical P fertilizer input has the greatest potential to reduce watershed P accumulation and establishment of riparian buffers has the greatest potential to prevent P loading to Lake Mendota.

Catastrophic ecological regime shifts may be announced in advance by statistical early warning signals such as slowing return rates from perturbation and rising variance. The theoretical background for these indicators is rich, but real-world tests are rare, especially for whole ecosystems. We tested the hypothesis that these statistics would be early warning signals for an experimentally induced regime shift in an aquatic food web. We gradually added top predators to a lake over 3 years to destabilize its food web. An adjacent lake was monitored simultaneously as a reference ecosystem. Warning signals of a regime shift were evident in the manipulated lake during reorganization of the food web more than a year before the food web transition was complete, corroborating theory for leading indicators of ecological regime shifts.

The development of complete regional carbon (C) budgets for different biomes is an integral step in the effort to predict global response and potential feedbacks to a changing climate regime. Wetland and lake contributions to regional C cycling remain relatively uncertain despite recent research highlighting their importance. Using a combination of field surveys and tower-based carbon dioxide (CO 2 ) flux measurements, modeling, and published literature, we constructed a complete C budget for the Northern Highlands Lake District in northern Wisconsin/ Michigan, a ~6400km 2 region rich in lakes and wetlands. This is one of the first regional C budgets to incorporate aquatic and terrestrial C cycling under the same framework. We divided the landscape into three major compartments (forests, wetlands, and surface waters) and quantified all major C fluxes into and out of those compartments, with a particular focus on atmospheric exchange but also including sedimentation in lakes and hydrologic fluxes. Landscape C storage was dominated by peat-containing wetlands and lake sediments, which make up only 20% and 13% of the landscape area, respectively, but contain > 80% of the total fixed C pool (ca. 400 Tg). We estimated a current regional C accumulation of 1.1 ± 0.1 Tg yr -1 , and the largest regional flux was forest net ecosystem exchange (NEE) into aggrading forests for a total of 1.0 ± 0.1 Tg yr -1 . Mean wetland NEE (0.12 ± 0.06Tg yr -1 into wetlands), lake CO 2 emissions and riverine efflux (each ca. 0.03 ± 0.01 Tg yr -1 ) were smaller but of consequence to the overall budget. Hydrologic transport from uplands/wetlands to surface waters within the region was an important vector of terrestrial C. Regional C fluxes and pools would be misrepresented without inclusion of surface waters and wetlands, and C budgets in heterogeneous landscapes open opportunities to examine the sensitivities of important fluxes to changes in climate and land use/land cover.

Entrainment of phosphorus across the thermocline can be an important nutrient source for phytoplankton in stratified lakes. In eutrophic stratified lakes, seasonal entrainment can be responsible for delayed recovery following a decrease in external phosphorus load. We compared seasonal estimates of entrainment derived from single- and multilocation thermocline migration approaches. Entrainment estimates from these methods were similar. A sampling approach based on a single centralized location produced whole-lake entrainment estimates in general agreement with the mean value from the multilocation approach (the single-location approach reasonably reproduced patterns at a weekly and seasonal time scale). In this study, it was not essential to account for spatial variation in estimating annual rates of entrainment. We also estimated entrainment based on a three-dimensional (3-D) hydrodynamic model over a short period of significant thermocline migration. The 3-D model was most useful in exposing spatial and temporal variation in temperature and phosphorus profiles that are otherwise difficult to observe. Spatial variation in phosphorus profiles was associated with upwelling of metalimnetic water represented by the 3-D model. These transient dynamics, though a relatively small portion of an annual phosphorus budget, may supply nutrients to epilimnetic phytoplankton during periods of nutrient limitation. There is a need for further research that combines 3-D hydrodynamic modeling with field collection of biological and chemical data.

In pelagic systems, phytoplankton biomass may remain abundant or near equilibrium while concentrations of the limiting nutrient are below detection. In eutrophic lakes, it has been thought that episodic algal blooms are due to mixing events that break down this equilibrium by adding nutrients to the mixed layer. Alternatively, rapid rates of biotic recycling among primary producers and heterotrophic consumers could maintain high phytoplankton biomass, yet the recycling process has been difficult to observe in situ. Here we use free-water oxygen measurements and an associated metabolic model to infer rates of phosphorus (P) uptake and biotic mineralization in the epilimnion of a eutrophic lake. The rates of uptake and mineralization were compared to “external” sources of P such as loading and entrainment. Also, model results were assessed using sensitivity analysis. We found that the majority of phytoplankton P demand during the period of low P availability could be accounted for by biotic mineralization, but that it was important to consider the effects of entrainment in order to account fully for P uptake. These general results were relatively insensitive to model parameterization, though the relative C:P ratio of material taken up versus mineralized was an important consideration. This study integrates modeling and measurement tools that monitor ecosystem processes at finer temporal resolution than has previously been possible, complementing other studies that use experimental incubation and elemental tracers. Extension of this approach could enhance models that aim to integrate biological and physical processes in assessment of water quality and prediction of phytoplankton biomass.

Many important transitions in phytoplankton composition of lakes and oceans are related to shifts in nutrient supply ratios. Some phytoplankton transitions, such as cyanobacteria blooms in freshwater supplies and red tides in coastal oceans, are important for aquatic resource management. Therefore, it would be useful to have leading indicators which precede phytoplankton shifts and could be readily monitored in the field. We investigated potential indicators using a well-understood model of phytoplankton dynamics parameterized to mimic the transition toward cyanobacteria blooms in freshwater lakes. In stationary distributions, performance of the indicators depends on whether the species are capable of stable coexistence over a certain range of nutrient inputs. In transient simulations, however, indicators show consistent responses regardless of the possibility of stable coexistence. Leading indicators occurring 10 to 40 days prior to species shift include shift of lag-1 autoregression coefficient toward 0, low standard deviation, fluctuating skewness, and high kurtosis. These responses are different from those reported for critical transitions such as fold bifurcations. Thus, the indicators reveal clues to the mechanisms of important ecosystem transitions. In practice, indicators should be measured for multiple ecosystem variables, and interpretation of the indicators should be guided by experiments and mechanistic site-specific models to help resolve potential ambiguities.

Carbon and nitrogen stable isotope ratios are increasingly used to study long-term food web change. Temporal variation at the base of the food web may impact the accuracy of trophic niche estimates, but data describing interannual baseline variation are limited. We quantified baseline variation over a 23-year period in a north-temperate lake and used a simulation model to examine how this variation might affect consumer trophic niche estimates. Interannual variation in C and N stable isotope ratios was significant for both benthic and pelagic primary consumer baselines. Long-term linear trends and shorter-term autoregressive patterns were apparent in the data. There were no correlations among benthic and pelagic C and N baselines. Simulations demonstrated that error in estimated fish trophic niches, but not bias, increased substantially when sampling of baselines was incomplete. Accurate trophic niche estimates depended more on accurate estimation of baseline time series than on accurate estimation of growth and turnover rates. These results highlight the importance of previous and continued efforts to constrain bias and error in long-term stable isotope food web studies.

Airborne inputs of terrestrial particulate organic carbon (TPOC) were measured during summ- er stratification for an oligotrophic north temperate lake located in a forested watershed. These inputs were episodic and associated with wind and rain events. The rate of deposition decreased exponentially with distance from shore. Yet, about 55 % of the total airborne TPOC input occurred more than 12 m from shore on this 25.8 ha lake. Of total deposition, 39 % was less than 153 mm in diameter - a size fraction not commonly measured in prior studies. Average air- borne deposition was 5 mg C m -2 d -1 , which is consistent with measurements from other lakes and equivalent to about 1.1 % of daily net primary production in our study lake. C:N ratios of TPOC were between 6:1 and 22:1 (molar), much lower than the values for terrestrial leaves which were between 39:1 and 48:1 (molar). These low C:N ratios suggest that TPOC may be a useful substrate for aquatic consumers and may supplement in-lake primary production as a food source, especially after wind and rain events when airborne TPOC inputs are high.

Regime shifts, or massive changes in ecosystems, are often associated with thresholds in drivers such as climate, land-use change, nutrient fluxes, or other factors. A frequently studied example is eutrophication, which is a serious environmental problem of lakes and reservoirs associated with phosphorus (P) enrichment above a threshold. We estimated probability distributions of thresholds for eutrophication of Lake Mendota, Wisconsin, USA using 30 years of annual P budgets. Although thresholds were likely to influence eutrophication of the lake (probability 96.6%), the probability distributions of thresholds spanned a wide range of P loading rates. Management recommendations are consistent with simpler models that recommend P load targets near or below the lowest P loads observed in the past 30 years. If loads increase, there is considerable risk of crossing a threshold to sustained eutrophication with high in-lake P concentrations and poor water quality. On the other hand, if loads decrease there is a chance of crossing a mitigation threshold, causing substantial reductions in P concentrations and improvements in water quality. Consideration of these risks will increase estimates of the net economic benefits of lower P loading. Our analysis illustrates a process for estimating probability distributions for thresholds of ecosystem regime shifts. Even though threshold probability distributions may be wide with thick tails, they provide crucial information about potential consequences of alternative policy choices.

Environmental regulations often rely on limits or thresholds to indicate an acceptable pollutant load. Estimates of the Risk of Exceeding such Thresholds (RET) are often based on a single model deemed to be the best for the particular pollutant or particular case. However, if many models make different predictions but explain the data almost equally well, predictions based on a single model may omit important information contained in other models that fit almost as well as the “best” single model. More accurate assessments of RET may result if multiple models are considered. We compared performance of the single best model relative to that of an ensemble of models estimated by bagging (Bootstrap AGGregatING) using the example of soil P concentrations and the risk of exceeding environmental limits of soil P concentrations in the watershed of Lake Mendota, Wisconsin, USA. Bagging yielded significantly better predictions of the risk of exceeding a threshold level of soil P (99.6% accuracy versus 74% for single-model prediction at a 20 mg kg−1 threshold). Use of multiple model techniques can improve estimates of RET over a range of realistic thresholds in other management situations where thresholds are important including eutrophication, desertification, fisheries, and many types of pollution control.