Evaluating the performance of temporal and spatial early warning statistics of algal blooms.

Regime shifts have large consequences for ecosystems and the services they provide. However, understanding the potential for, causes of, proximity to, and thresholds for regime shifts in nearly all settings is difficult. Generic statistical indicators of resilience have been proposed and studied in a wide range of ecosystems as a method to detect when regime shifts are becoming more likely without direct knowledge of underlying system dynamics or thresholds. These early warning statistics (EWS) have been studied separately but there have been few examples that directly compare temporal and spatial EWS in ecosystem-scale empirical data. To test these methods, we collected high-frequency time series and high-resolution spatial data during a whole-lake fertilization experiment while also monitoring an adjacent reference lake. We calculated two common EWS, standard deviation and autocorrelation, in both time series and spatial data to evaluate their performance prior to the resulting algal bloom. We also applied the quickest detection method to generate binary alarms of resilience change from temporal EWS. One temporal EWS, rolling window standard deviation, provided advanced warning in most variables prior to the bloom, showing trends and between-lake patterns consistent with theory. In contrast, temporal autocorrelation and both measures of spatial EWS (spatial SD, Moran's I) provided little or no warning. By compiling time series data from this and past experiments with and without nutrient additions, we were able to evaluate temporal EWS performance for both constant and changing resilience conditions. True positive alarm rates were 2.5-8.3 times higher for rolling window standard deviation when a lake was being pushed towards a bloom than the rate of false positives when it was not. For rolling window autocorrelation, alarm rates were much lower and no variable had a higher true positive than false positive alarm rate. Our findings suggest temporal EWS provide advanced warning of algal blooms and that this approach could help managers prepare for and/or minimize negative bloom impacts.

Anatomy and resilience of the global production ecosystem.

Much of the Earth's biosphere has been appropriated for the production of harvestable biomass in the form of food, fuel and fibre. Here we show that the simplification and intensification of these systems and their growing connection to international markets has yielded a global production ecosystem that is homogenous, highly connected and characterized by weakened internal feedbacks. We argue that these features converge to yield high and predictable supplies of biomass in the short term, but create conditions for novel and pervasive risks to emerge and interact in the longer term. Steering the global production ecosystem towards a sustainable trajectory will require the redirection of finance, increased transparency and traceability in supply chains, and the participation of a multitude of players, including integrated 'keystone actors' such as multinational corporations.

Early warnings of regime shifts: a whole-ecosystem experiment.

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.

Early warnings of unknown nonlinear shifts: a nonparametric approach.

Early warning signals (EWS) of regime shifts are challenging in cases where the true natural data-generating process is uncertain. Nonparametric drift-diffusion-jump models address this problem by fitting a general model that can approximate a wide range of data-generating processes. Drift measures the local rate of change. Diffusion measures relatively small shocks that occur at each time step. Jumps are large intermittent shocks. Total variance combines the contributions of diffusion and jumps. Nonparametric methods are well suited to emerging technology for automated, high-frequency sensors. Total variance is the most precisely measured indicator. Jump intensity appears to be a useful EWS. Estimates of the drift are highly uncertain unless long time series with many regime shifts are available. EWS computed from drift estimates (such as autocorrelation coefficients or return rates) have low precision and should be used with caution. Nonetheless, in the current state of knowledge, it is premature to disregard any potential EWS.

Leading indicators of trophic cascades.

Regime shifts are large, long-lasting changes in ecosystems. They are often hard to predict but may have leading indicators which are detectable in advance. Potential leading indicators include wider swings in dynamics of key ecosystem variables, slower return rates after perturbation and shift of variance towards lower frequencies. We evaluated these indicators using a food web model calibrated to long-term whole-lake experiments. We investigated whether impending regime shifts driven by gradual increase in exploitation of the top predator can create signals that cascade through food webs and be discerned in phytoplankton. Substantial changes in standard deviations, return rates and spectra occurred near the switch point, even two trophic levels removed from the regime shift in fishes. Signals of regime shift can be detected well in advance, if the driver of the regime shift changes much more slowly than the dynamics of key ecosystem variables which can be sampled frequently enough to measure the indicators. However, the regime shift may occur long after the driver has passed the critical point, because of very slow transient dynamics near the critical point. Thus, the ecosystem can be poised for regime shift by the time the signal is discernible. Field tests are needed to evaluate these indicators.

Rising variance: a leading indicator of ecological transition.

Regime shifts are substantial, long-lasting reorganizations of complex systems, such as ecosystems. Large ecosystem changes such as eutrophication, shifts among vegetation types, degradation of coral reefs and regional climate change often come as surprises because we lack leading indicators for regime shifts. Increases in variability of ecosystems have been suggested to foreshadow ecological regime shifts. However, it may be difficult to discern variability due to impending regime shift from that of exogenous drivers that affect the ecosystem. We addressed this problem using a model of lake eutrophication. Lakes are subject to fluctuations in recycling associated with regime shifts, as well as fluctuating nutrient inputs. Despite the complications of noisy inputs, increasing variability of lake-water phosphorus was discernible prior to the shift to eutrophic conditions. Simulations show that rising standard deviation (SD) could signal impending shifts about a decade in advance. The rising SD was detected by studying variability around predictions of a simple time-series model, and did not depend on detailed knowledge of the actual ecosystem dynamics.

Ecological forecasts: an emerging imperative.

Planning and decision-making can be improved by access to reliable forecasts of ecosystem state, ecosystem services, and natural capital. Availability of new data sets, together with progress in computation and statistics, will increase our ability to forecast ecosystem change. An agenda that would lead toward a capacity to produce, evaluate, and communicate forecasts of critical ecosystem services requires a process that engages scientists and decision-makers. Interdisciplinary linkages are necessary because of the climate and societal controls on ecosystems, the feedbacks involving social change, and the decision-making relevance of forecasts.

PCB congeners in Lake Michigan coho (Oncorhynchus kisutch) and chinook (Oncorhynchus tshawytscha) salmon.

We determined PCB congener concentrations in coho and chinook salmon collected in two Lake Michigan tributaries during the fall of 1996. Chinook salmon were larger than coho salmon and contained higher concentrations of the 78 PCB congeners we detected. There were no differences between male and female chinook or coho salmon in size or their PCB concentrations. Among individual fish, we found little evidence for a relationship between congener concentrations and percent lipid; however, congener concentrations did show a generally positive relationship with salmon size. Fish and macroinvertebrate congener concentrations are clearly related, and PCB congeners biomagnify approximately 20-30-fold as they flow from macroinvertebrates, two trophic levels below salmon, to the salmon. Slopes of regressions of salmonid congener concentrations on macroinvertebrate congener concentrations within homologs indicated that the degree of biomagnification generally increased with the degree of congener chlorination, although this pattern was much stronger for Mysis than for Diporeia. Log Kow and categorical variables for coplanar and "toxic" PCBs were not significant additional model terms, indicating that bioaccumulation of PCB congeners was not statistically related to these physicochemical attributes of the PCBs. The distribution of homologue PCBs shifts from a distinct predominance of hexachlorobiphenyls in macroinvertebrates to pentachlorobiphenyls and hexachlorobiphenyls in the salmon.

Ecosystem experiments.

Experimental manipulations of entire ecosystems have been conducted in lakes, catchments, streams, and open terrestrial and marine environments. Experiments have addressed applied problems of ecosystem management and complex responses of communities and ecosystems to perturbations. In the course of some experiments, environmental indicators and models have been developed and tested. Surprising results with implications for ecological understanding and management are common.

Biotic feedbacks in Lake phosphorus cycles.

Limnologists are now reconsidering the role of the biota in the phosphorus (P) cycles of lakes. Changes in lake communities can have significant consequences for ecosystem P cycles. At seasonal timescales, the relative importance of nitrogen (N) and Pas limiting factors for primary production depends in part on zooplankton species composition. Phosphorus storage and recycling by fish and zooplankton can be large components of P budgets, and mobile consumers can be important vectors in P transport. Stability, resilience and resistance of lake P cycles may depend heavily on fluxes to and from upper trophic levels.

Resilience and resistance of a lake phosphorus cycle before and after food web manipulation.

Parameters of a phosphorus cycling model were estimated for two configurations of a lake ecosystem. The piscivore-dominated configuration had one more trophic level than the planktivore-dominated configuration. We derived four main conclusions from analysis of the model. (1) Results support the argument of DeAngelis et al. that turnover rate of a limiting nutrient is directly related to ecosystem resilience. (2) Results support the hypothesis of Pimm and Lawton that longer food chains are less resilient. (3) Inputs of phosphorus to the pelagic system derived from inshore feeding by fishes were a large flux, which is comparable to inputs from physical-chemical fluxes. (4) Algal (seston) standing crops, unlike all other compartments, were less sensitive to phosphorus inputs in the piscivore-dominated system. Consistent with the trophic cascade hypothesis, the piscivore-dominated system had higher herbivore standing crops and lower algal standing crops than the planktivore-dominated system. Changes in trophic structure that derive from trophic cascades can be viewed as changes in the phosphorus cycle driven by fishes.

Regulation of Lake Primary Productivity by Food Web Structure.

We performed whole-lake manipulations of fish populations to test the hypothesis that higher trophic levels regulate zooplankton and phytoplankton community structure, biomass, and primary productivity. The study involved three lakes and spanned 2 yr. Results demonstrated hierarchical control of primary production by abiotic factors and a trophic cascade involving fish predation. In Paul Lake, the reference lake, productivity varied from year to year, illustrating the effects of climatic factors and the natural dynamics of unmanipulated food web interactions. In Tuesday Lake, piscivore addition and planktivore reduction caused an increase in zooplankton biomass, a compositional shift from a copepod/rotifer assemblage to a cladoceran assemblage, a reduction in algal biomass, and a continuous reduction in primary productivity. In Peter Lake, piscivore reduction and planktivore addition decreased zooplanktivory, because potential planktivores remained in littoral refugia to escape from remaining piscivores. Both zooplankton biomass and the dominance of large cladocerans increased. Algal biomass and primary production increased because of increased concentrations of gelatinous colonial green algae. Food web effects and abiotic factors were equally potent regulators of primary production in these experiments. Some of the unexplained variance in primary productivity of the world's lakes may be attributed to variability in fish populations and its effects on lower trophic levels.