Methods For Detecting Early Warnings Of Critical Transitions In Time Series Illustrated Using Simulated Ecological Data

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called ‘early warning signals’, and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.Organismic and Evolutionary Biolog

Early Warning Signals of Ecological Transitions: Methods for Spatial Patterns

A number of ecosystems can exhibit abrupt shifts between alternative stable states. Because of their important ecological and economic consequences, recent research has focused on devising early warning signals for anticipating such abrupt ecological transitions. In particular, theoretical studies show that changes in spatial characteristics of the system could provide early warnings of approaching transitions. However, the empirical validation of these indicators lag behind their theoretical developments. Here, we summarize a range of currently available spatial early warning signals, suggest potential null models to interpret their trends, and apply them to three simulated spatial data sets of systems undergoing an abrupt transition. In addition to providing a step-by-step methodology for applying these signals to spatial data sets, we propose a statistical toolbox that may be used to help detect approaching transitions in a wide range of spatial data. We hope that our methodology together with the computer codes will stimulate the application and testing of spatial early warning signals on real spatial data

Reserves and trade jointly determine exposure to food supply shocks

While a growing proportion of global food consumption is obtained through international trade, there is an ongoing debate on whether this increased reliance on trade benefits or hinders food security, and specifically, the ability of global food systems to absorb shocks due to local or regional losses of production. This paper introduces a model that simulates the short-term response to a food supply shock originating in a single country, which is partly absorbed through decreases in domestic reserves and consumption, and partly transmitted through the adjustment of trade flows. By applying the model to publicly-available data for the cereals commodity group over a 17 year period, we find that differential outcomes of supply shocks simulated through this time period are driven not only by the intensification of trade, but as importantly by changes in the distribution of reserves. Our analysis also identifies countries where trade dependency may accentuate the risk of food shortages from foreign production shocks; such risk could be reduced by increasing domestic reserves or importing food from a diversity of suppliers that possess their own reserves. This simulation-based model provides a framework to study the short-term, nonlinear and out-of-equilibrium response of trade networks to supply shocks, and could be applied to specific scenarios of environmental or economic perturbations

Wind and trophic status explain within and among-lake variability of algal biomass

Phytoplankton biomass and production regulates key aspects of freshwater ecosystems yet its variability and subsequent predictability is poorly understood. We estimated within-lake variation in biomass using high-frequency chlorophyll fluorescence data from 18 globally distributed lakes. We tested how variation in fluorescence at monthly, daily, and hourly scales was related to high-frequency variability of wind, water temperature, and radiation within lakes as well as productivity and physical attributes among lakes. Within lakes, monthly variation dominated, but combined daily and hourly variation were equivalent to that expressed monthly. Among lakes, biomass variability increased with trophic status while, within-lake biomass variation increased with increasing variability in wind speed. Our results highlight the benefits of high-frequency chlorophyll monitoring and suggest that predicted changes associated with climate, as well as ongoing cultural eutrophication, are likely to substantially increase the temporal variability of algal biomass and thus the predictability of the services it provides.Peer reviewe

Environmental controls on benthic food web functions and carbon resource use in subarctic lakes

Climate warming and consequent greening of subarctic landscapes increase the availability of organic carbon to the detrital food webs in aquatic ecosystems. This may cause important shifts in ecosystem functioning through the functional feeding patterns of benthic organisms that rely differently on climatically altered carbon resources. Twenty-five subarctic lakes in Finnish Lapland across a tree line ecotone were analysed for limnological and optical variables, carbon (delta C-13) and nitrogen (delta N-15) stable isotope (SI) composition of surface sediment organic matter (OM) and fossil Chironomidae (Diptera) remains to examine environmental controls behind chironomid functional feeding group (FFG) structure and their isotopic associations for assessing ecosystem functioning and carbon utilisation. We hypothesise that the chironomid SI signatures reflect increased allochthony with increasing allochthonous input, but the resource use may be altered by the functional characteristics of the assemblage. Multivariate analyses indicated that carbon geochemistry in the sediments (delta C-13, delta N-15, C/N), nutrients, indices of productivity (chlorophyll-a) and lake water optical properties, related to increasing presence of OM, played a key role in defining the chironomid FFG composition and isotopic signatures. Response modelling was used to examine how individual FFGs respond to environmental gradients. They showed divergent responses for OM quantity, dissolved organic carbon and nutrients between feeding strategies, suggesting that detritivores and filter feeders prefer contrasting carbon and nutrient conditions, and may thus hold paleoecological indicator potential to identify changes between different carbon fluxes. Benthic production was the primary carbon source for the chironomid assemblages according to a three-source SI mixing model, whereas pelagic and terrestrial components contributed less. Between-lake variability in source utilisation was high and controlled primarily by allochthonous OM inputs. Combination of biogeochemical modelling and functional classification is useful to widen our understanding of subarctic lake ecosystem functions and responses to climate-driven changes in limnology and catchment characteristics for long-term environmental change assessments and functional paleoecology.Peer reviewe

Assessing ecological resilience to human induced environmental change in shallow lakes

Sudden unpredictable changes in ecosystems are an increasing source of concern because of their inherent unpredictability and the difficulties involved in restoration. Our understanding of the changes that occur across different trophic levels and the form of this change is lacking. This is especially true of large shallow lakes, where characteristics such as fetch and depth are close to theoretical boundary values for hysteretic behaviour. The development of reliable indicators capable of predicting these changes has been the focus of much research in recent years. The success of these early warning indicators (EWIs) has so far been mixed. There remain many unknowns about how they perform under a wide variety of conditions and parameters. Future climate change is predicted to have a wide range of impacts through the interaction of combined pressures, making the understanding of EWIs and the in-lake processes that occur during regime shifts imperative. Loch Leven, Scotland, UK, is a large shallow lake with a history of eutrophication, research and management and as such is an ideal study site to better understand resilience and regime shifts under a range of interacting stressors. The objectives of this research are to: (1) analyse long term data to identify the occurrence of common tipping points within the chemical (water column nutrient concentrations) and biological (macrophytes, phytoplankton, zooplankton) components of the loch, then test these tipping points using five statistical early warning indicators (EWIs) across multiple rolling window sizes; and (2) quantify the changes in lake ecology using a before/after analysis and testing for non-linearity, combined with modelling using the aquatic ecosystem process model PCLake to determine the level of resilience following a regime shift during recovery from eutrophication; (3) using PCLake, examine the sensitivity of Loch Leven to regime shifts in the face of predicted environmental change (e.g. climate change, nutrient pollution). Statistical analysis identified tipping points across all trophic levels included, from physical and chemical variables through to apex predators. The success of EWIs in predicting the tipping points was highly dependent on the number of EWIs used, with window size having a smaller impact. The 45% window size had the highest overall accuracy across all EWIs but only detected 16.5% more tipping points than the window size with the lowest overall accuracy. Differences between individual EWI performance and usage of them as a group was substantial with a 29.7% increase between the two. In both individual and group use of EWIs, false positives (early warning without a tipping point) were more common than true positives (tipping point preceded by EWI), creating significant doubts about their reliability as management tools. Significant change was seen across multiple variables and trophic levels in the before/after analysis following sudden recovery from eutrophication, with most variables also showing evidence of non-linear change. Modelling of responses to nutrient loading for chlorophyll, zooplankton and macrophytes, under states from before and after the shift, indicate hysteresis and thus the presence of feedback mechanisms. The modelling of responses to nutrient loading and predicted climate change in temperature and precipitation demonstrated that increases in temperature and decreases in summer precipitation individually had large impacts on chlorophyll and zooplankton at medium to high phosphorus (P) loads. However, modelling of the combined effects of these changes resulted in the highest lake chlorophyll concentrations of all tested scenarios. At low P loads higher temperatures and increased winter precipitation had the greatest impact on system resilience with a lower Critical Nutrient Load (CNL). The difference between chlorophyll and zooplankton as opposed to macrophytes was in the presence of a lower CNL for the increased winter precipitation-only scenarios which was not seen in the macrophytes. This highlights the potential role of high winter inputs potentially loaded with particulate matter in reducing resilience at lower P loads. This research has highlighted the vulnerability and low resilience of Loch Leven to environmental change. The presence of multiple tipping points and high levels of EWI activity show a high level of flexibility in the system. Coupled with the occurrence of widespread trophic change during a sudden recovery and a small level of hysteresis and high levels of sensitivity to climate change, the low levels of resilience become clear. The impact of lake-specific characteristics such as moderate depth, large fetch and a heterogeneous bed morphology is particularly evident in the limitations on macrophyte cover and the reliance on zooplankton to determine the hysteresis offset (amount of phosphorus (P) loading between the two CNL). The presence of these characteristics can be used to identify other lakes vulnerable to change. Improving the predictive capabilities of resilience indicators such as EWIs, and better understanding of the ecological changes that occur during non-linear change in response to recovery and climate change, can help target relevant ecosystem components for preventative management. These actions may become necessary under even the most conservative estimates of environmental change

Effects of multiple stressors on cyanobacteria abundance vary with lake type

Blooms of cyanobacteria are a current threat to global water security that is expected to increase in the future because of increasing nutrient enrichment, increasing temperature and extreme precipitation in combination with prolonged drought. However, the responses to multiple stressors, such as those above, are often complex and there is contradictory evidence as to how they may interact. Here we used broad scale data from 494 lakes in central and northern Europe, to assess how cyanobacteria respond to nutrients (phosphorus), temperature and water retention time in different types of lakes. Eight lake types were examined based on factorial combinations of major factors that determine phytoplankton composition and sensitivity to nutrients: alkalinity (low and medium‐high), colour (clear and humic) and mixing intensity (polymictic and stratified). In line with expectations, cyanobacteria increased with temperature and retention time in five of the eight lake types. Temperature effects were greatest in lake types situated at higher latitudes, suggesting that lakes currently not at risk could be affected by warming in the future. However, the sensitivity of cyanobacteria to temperature, retention time and phosphorus varied among lake types highlighting the complex responses of lakes to multiple stressors. For example, in polymictic, medium‐high alkalinity, humic lakes cyanobacteria biovolume was positively explained by retention time and a synergy between TP and temperature while in polymictic, medium‐high alkalinity, clear lakes only retention time was identified as an explanatory variable. These results show that, although climate change will need to be accounted for when managing the risk of cyanobacteria in lakes, a ‘one‐size fits‐all’ approach is not appropriate. When forecasting the response of cyanobacteria to future environmental change, including changes caused by climate and local management, it will be important to take this differential sensitivity of lakes into account