Ryan D. Batt

Early Warnings of Regime Shifts: A Whole-Ecosystem Experiment

High-frequency monitoring of manipulated and reference lakes enabled early detection of subsequent catastrophic regime shift. 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.

Changes in ecosystem resilience detected in automated measures of ecosystem metabolism during a whole-lake manipulation

Significance Large changes can occur when ecosystems cross certain thresholds. Crossing such thresholds poses a challenge to ecosystem management because the positions of the threshold are uncertain and change over time. However, as an ecosystem approaches a threshold its resilience declines, resulting in changes in system dynamics that increase variance and autocorrelation. Calculating these statistics requires frequent and sustained sampling efforts. Our study detected an approaching threshold by computing the statistical indicators from data collected by automated sensors, which are far less labor-intensive than comparable manual methods. Thus it may be feasible to monitor for approaching ecosystem thresholds using automated methods. This finding highlights a powerful use of modern sensor technology. 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.

Asymmetric response of early warning indicators of phytoplankton transition to and from cycles

Phytoplankton populations often exhibit cycles associated with nuisance blooms of cyanobacteria and other algae that cause toxicity, odor problems, oxygen depletion, and fish kills. Models of phytoplankton blooms used for management and basic research often contain critical transitions from stable points to cycles, or vice-versa. It would be useful to know whether aquatic systems, especially water supplies, are close to a critical threshold for cycling blooms. Recent studies of resilience indicators have focused on alternate stable points, although theory suggests that indicators such as variance and autocorrelation should also rise prior to a transition from stable point to stable cycle. We investigated changes in variance and autocorrelation associated with transitions involving cycles using two models. Variance rose prior to the transition from a small-radius cycle (or point) to a larger radius cycle in all cases. In many but not all cases, autocorrelation increased prior to the transition. However, the transition from large-radius to small-radius cycles was not associated with discernible increases in variance or autocorrelation. Thus, indicators of changing resilience can be measured prior to the transition from stable to cyclic plankton dynamics. Such indicators are potentially useful in management. However, these same indicators do not provide useful signals of the reverse transition, which is often a goal of aquatic ecosystem restoration. Thus, the availability of resilience indicators for phytoplankton cycles is asymmetric: the indicators are seen for the transition to bloom–bust cycles but not for the reverse transition to a phytoplankton stable point.

Reversal of a cyanobacterial bloom in response to early warnings

Significance Blooms of cyanobacteria in lakes and reservoirs cause fish kills and pose toxicity risk for humans, livestock, and wildlife. Theory suggests that blooms may be anticipated in advance by calculating resilience indicators using high-frequency observations of pigments in lake water. However, it is not known whether management can prevent blooms once indicators are detected. We measured these indicators while gradually enriching a lake until a bloom was triggered. When indicators passed a preset threshold, nutrient input was stopped. This action reversed the bloom, showing that monitoring of resilience indicators followed by prompt action when limits are exceeded can be useful in management. However, in practice, the risk of blooms may best be prevented by reducing inputs of nutrients. 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.

Direct observations of ice seasonality reveal changes in climate over the past 320–570 years

Lake and river ice seasonality (dates of ice freeze and breakup) responds sensitively to climatic change and variability. We analyzed climate-related changes using direct human observations of ice freeze dates (1443–2014) for Lake Suwa, Japan, and of ice breakup dates (1693–2013) for Torne River, Finland. We found a rich array of changes in ice seasonality of two inland waters from geographically distant regions: namely a shift towards later ice formation for Suwa and earlier spring melt for Torne, increasing frequencies of years with warm extremes, changing inter-annual variability, waning of dominant inter-decadal quasi-periodic dynamics, and stronger correlations of ice seasonality with atmospheric CO2 concentration and air temperature after the start of the Industrial Revolution. Although local factors, including human population growth, land use change, and water management influence Suwa and Torne, the general patterns of ice seasonality are similar for both systems, suggesting that global processes including climate change and variability are driving the long-term changes in ice seasonality.

Altered energy flow in the food web of an experimentally darkened lake

Theory suggests that alternative resources may begin to support a food web when highly used resources become less available relative to alternatives. To test the potential for alternative resources to support consumers, we experimentally darkened a lake whose consumers had relied heavily on algal resources (phytoplankton and benthic algae). We estimated the support consumers received from resources before and after darkening using a Bayesian mixing model and stables isotopes of carbon, nitrogen, and hydrogen. Between a prior year and the darkened year, phytoplankton biomass diminished by 60%, and surface dissolved oxygen saturation, pCO2, and net ecosystem production indicated a shift from autotrophy to heterotrophy. Although a specialist copepod maintained a high reliance on phytoplankton after darkening, a generalist zooplankton predator (Chaoborus spp.) derived more support from terrestrial sources. Fishes received less support from benthic algae after darkening, and received greater support from float...

Observed and modeled presence 1968-2014

NMFS Trawl Survey data used to fit species distribution models and the resulting modeled predictions for presence/absence (preds1) and abundance (preds).