Early warning of critical transitions in biodiversity from compositional disorder

Exploring the Interface Between Planetary Boundaries and Palaeoecology

The concepts of planetary boundaries are influential in the sustainability literature and assist in delineating the 'safe operating spaces' beyond which critical Earth system processes could collapse. Moving away from our current trajectory towards 'hothouse Earth' will require knowledge of how Earth systems have varied throughout the Holocene, and whether and how far we have deviated from past ranges of variability. Such information can inform decisions about where change could be resisted, accepted or where adaptation is inevitable. The need for information on long-term (Holocene) change provides an interface for palaeoecology and sustainability that remains underexploited. In this position paper, we explore this interface, first discussing the need for long-term perspectives and introducing examples where palaeoecology has been used in defining safe operating spaces and constraining limits of acceptable change. We describe advances in quantitative methods for analysis of time-series data that strengthen the contribution of palaeoecology to the concepts of planetary boundaries and safe operating spaces. We consider the importance of issues of scaling from landscape to regional and global scales in operationalising planetary boundaries concepts. We distil principles for this field of research going forward and introduce three case studies which will form the basis of research on these topics.

Sediment DNA Records the Critical Transition of Bacterial Communities in the Arid Lake

It is necessary to predict the critical transition of lake ecosystems due to their abrupt, non-linear effects on social-economic systems. Given the promising application of paleolimnological archives to tracking the historical changes of lake ecosystems, it is speculated that they can also record the lake's critical transition. We studied Lake Dali-Nor in the arid region of Inner Mongolia because of the profound shrinking the lake experienced between the 1300 s and the 1600 s. We reconstructed the succession of bacterial communities from a 140-cm-long sediment core at 4-cm intervals and detected the critical transition. Our results showed that the historical trajectory of bacterial communities from the 1200 s to the 2010s was divided into two alternative states: state1 from 1200 to 1300 s and state2 from 1400 to 2010s. Furthermore, in the late 1300 s, the appearance of a tipping point and critical slowing down implied the existence of a critical transition. By using a multi-decadal time series from the sedimentary core, with general Lotka-Volterra model simulations, local stability analysis found that bacterial communities were the most unstable as they approached the critical transition, suggesting that the collapse of stability triggers the community shift from an equilibrium state to another state. Furthermore, the most unstable community harbored the strongest antagonistic and mutualistic interactions, which may imply the detrimental role of interaction strength on community stability. Collectively, our study showed that sediment DNA can be used to detect the critical transition of lake ecosystems.

Systematic loss in biotic heterogeneity but not biodiversity across multiple trophic levels in Erhai lake, China

Anthropogenic disturbances and climate change have significantly altered the biotic composition across many ecosystems, leading to changes in biodiversity and even ecological collapse. An ecosystem comprises multiple trophic levels, and the issue how these disturbances affect their assembly processes remains unclear. Ecological stability of assemblages was maintained by their structure, and thus, revealing structure changes across trophic levels could improve our understanding of how ecosystems response to disturbances as a whole. In this study, we combined methods from palaeolimnology, ecology and network analysis, and observed the changes of biodiversity and network structure of two trophic levels (algae - diatoms and zoobenthos - chironomids) in Erhai lake, Southwest China over the last century. Results showed nutrient enrichment induced shifts in diatom and chironomid assemblages at ∼2001 CE, suggesting that the shift in Erhai lake may have occurred at multiple trophic levels. We found biodiversity exhibit different trends across trophic levels as it decreased in diatoms but increased in chironomids. However, network skewness declined in both trophic levels, indicating the common loss of biotic heterogeneity. The consistent decline of skewness among trophic levels long before the compositional shift is a potential parameter to warn of the shifts in lake ecosystems.

The declines of heterogeneity and stability in diatom communities are associated with human activity

Anthropogenic forcing caused the biodiversity loss and stability decline of communities. There is still controversy over whether the decline in biodiversity will lead to a decrease in community stability. The stability of biological communities is related to both biodiversity and structure, and this paper aims to reveal the human impacts on diatom communities' biodiversity and structure. We studied the richness, β-diversity and network distance of diatom communities in Qinghai-Xizang, Yunnan-Sichuan and Lower Yangtze River Basin, China through empirical dataset and simulation method. The results showed that the diatoms richness in the Qinghai-Xizang and the Yunnan-Sichuan region was lower and the network distance was higher than that of the Lower Yangtze River Basin. β-diversity in the Lower Yangtze River Basin was the lowest and the diatom network distance responds negatively to human population densities in China. The simulation showed that the network distance kept constant during random species loss, and declined while specialist species were lost or replaced by generalist species. The results suggested diatom communities' homogeneity and stability decline were associated with human activities. Human impacts may cause biodiversity loss targeted to specialist species or no biodiversity loss while generalist species replace those specialist species. This study showed that how diversity changes determined ecological stability depends on the type of species changes.

Predicting critical transitions in assortative spin-shifting networks

Methods to forecast critical transitions, i.e. abrupt changes in systems' equilibrium states have relevance in scientific fields such as ecology, seismology, finance and medicine among others. So far, the bulk of investigations on forecasting methods builds on equation-based modeling methods, which consider system states as aggregates and thus do not account for the different connection strengths in each part of the system. This seems inadequate against the background of studies that insinuate that critical transitions can originate in sparsely connected parts of systems. Here we use agent-based spin-shifting models with assortative network representations to distinguish different interaction densities. Our investigations confirm that signals of imminent critical transitions can indeed be detected significantly earlier in network parts with low link degrees. We discuss the reason for this circumstance on the basis of the free energy principle.

Community structure determines the predictability of population collapse

Early warning signals (EWS) are phenomenological tools that have been proposed as predictors of the collapse of biological systems. Although a growing body of work has shown the utility of EWS based on either statistics derived from abundance data or shifts in phenotypic traits such as body size, so far this work has largely focused on single species populations.

However, to predict reliably the future state of ecological systems, which inherently could consist of multiple species, understanding how reliable such signals are in a community context is critical.

Here, reconciling quantitative trait evolution and Lotka–Volterra equations, which allow us to track both abundance and mean traits, we simulate the collapse of populations embedded in mutualistic and multi‐trophic predator–prey communities. Using these simulations and warning signals derived from both population‐ and community‐level data, we showed the utility of abundance‐based EWS, as well as metrics derived from stability‐landscape theory (e.g. width and depth of the basin of attraction), were fundamentally linked. Thus, the depth and width of such stability‐landscape curves could be used to identify which species should exhibit the strongest EWS of collapse.

The probability a species displays both trait and abundance‐based EWS was dependent on its position in a community, with some species able to act as indicator species. In addition, our results also demonstrated that in general trait‐based EWS were less reliable in comparison with abundance‐based EWS in forecasting species collapses in our simulated communities. Furthermore, community‐level abundance‐based EWS were fairly reliable in comparison with their species‐level counterparts in forecasting species‐level collapses.

Our study suggests a holistic framework that combines abundance‐based EWS and metrics derived from stability‐landscape theory that may help in forecasting species loss in a community context.

Reconstruction of Ecological Transitions in a Temperate Shallow Lake of the Middle Yangtze River Basin in the Last Century

Exogenous drivers may cause a gradual and reversible change in a lake equilibrium, or they may force it over a threshold to a persistent alternative stable state, described as a regime shift in the ecosystem. In the mid-and-lower Yangtze River Basin (MLYB), major environmental problems in shallow lakes have been eutrophication and abrupt algal blooms under anthropogenic disturbances for the recent century. Much value is therefore placed on understanding the changes in shallow-lake ecosystems that characteristically precede changes in the state of the lake. Here, we describe a case study of the paleolimnological signature in diatom assemblages of various types of regime shifts caused by historically documented anthropogenic drivers in a temperate shallow lake: Taibai Lake. We evaluate the effectiveness of paleolimnological data as a surrogate for long-term monitoring. Algorithms using sequential t and F statistics detected breakpoints in the time series of diatom assemblages, in 1994–1996, 1974–1977, 1952–1956, and 1931–1934, respectively. The regression statistics suggest that the hydrodynamic–ecosystem and aquacultural–ecosystem relationships fit better in the breakpoint regression model, and the relationship between nutrient loading and ecosystem state suits the linear model. Feedback loops help reconstruct dynamic changes in Taibai influenced by major stressors. Our study exemplifies the value of system approaches to identifying regime shifts and their possible causes in shallow lakes from paleolimnological records. The case study of Taibai set an example of reconstructing the ecological regime shifts in shallow lakes in the MLYB and understanding the state changes in lake ecosystems, which will benefit effective lake management.

Critical Transitions in Lake Ecosystem State May Be Driven by Coupled Feedback Mechanisms: A Case Study from Lake Erhai, China

Critical transitions between ecosystem states can be triggered by relatively small external forces or internal perturbations and may show time-lagged or hysteretic recovery. Understanding the precise mechanisms of a transition is important for ecosystem management, but it is hampered by a lack of information about the preceding interactions and associated feedback between different components in an ecosystem. This paper employs a range of data, including paleolimnological, environmental monitoring and documentary sources from lake Erhai and its catchment, to investigate the ecosystem structure and dynamics across multiple trophic levels through the process of eutrophication. A long-term perspective shows the growth and decline of two distinct, but coupled, positive feedback loops: a macrophyte-loop and a phosphorus-recycling-loop. The macrophyte-loop became weaker, and the phosphorus-recycling-loop became stronger during the process of lake eutrophication, indicating that the critical transition was propelled by the interaction of two positive feedback loops with different strengths. For lake restoration, future weakening of the phosphorus-recycling loop or a reduction in external pressures is expected to trigger macrophyte growth and eventually produce clear water conditions, but the speed of recovery will probably depend on the rates of feedback loops and the strength of their coupling.

Future phytoplankton diversity in a changing climate

The future response of marine ecosystem diversity to continued anthropogenic forcing is poorly constrained. Phytoplankton are a diverse set of organisms that form the base of the marine ecosystem. Currently, ocean biogeochemistry and ecosystem models used for climate change projections typically include only 2-3 phytoplankton types and are, therefore, too simple to adequately assess the potential for changes in plankton community structure. Here, we analyse a complex ecosystem model with 35 phytoplankton types to evaluate the changes in phytoplankton community composition, turnover and size structure over the 21st century. We find that the rate of turnover in the phytoplankton community becomes faster during this century, that is, the community structure becomes increasingly unstable in response to climate change. Combined with alterations to phytoplankton diversity, our results imply a loss of ecological resilience with likely knock-on effects on the productivity and functioning of the marine environment.

Spatial early warning signals of social and epidemiological tipping points in a coupled behaviour-disease network

The resurgence of infectious diseases due to vaccine refusal has highlighted the role of interactions between disease dynamics and the spread of vaccine opinion on social networks. Shifts between disease elimination and outbreak regimes often occur through tipping points. It is known that tipping points can be predicted by early warning signals (EWS) based on characteristic dynamics near the critical transition, but the study of EWS in coupled behaviour-disease networks has received little attention. Here, we test several EWS indicators measuring spatial coherence and autocorrelation for their ability to predict a critical transition corresponding to disease outbreaks and vaccine refusal in a multiplex network model. The model couples paediatric infectious disease spread through a contact network to binary opinion dynamics of vaccine opinion on a social network. Through change point detection, we find that mutual information and join count indicators provided the best EWS. We also show the paediatric infectious disease natural history generates a discrepancy between population-level vaccine opinions and vaccine immunity status, such that transitions in the social network may occur before epidemiological transitions. These results suggest that monitoring social media for EWS of paediatric infectious disease outbreaks using these spatial indicators could be successful.

Tipping positive change

Tipping points exist in social, ecological and climate systems and those systems are increasingly causally intertwined in the Anthropocene. Climate change and biosphere degradation have advanced to the point where we are already triggering damaging environmental tipping points, and to avoid worse ones ahead will require finding and triggering positive tipping points towards sustainability in coupled social, ecological and technological systems. To help with that I outline how tipping points can occur in continuous dynamical systems and in networks, the causal interactions that can occur between tipping events across different types and scales of system-including the conditions required to trigger tipping cascades, the potential for early warning signals of tipping points, and how they could inform deliberate tipping of positive change. In particular, the same methods that can provide early warning of damaging environmental tipping points can be used to detect when a socio-technical or socio-ecological system is most sensitive to being deliberately tipped in a desirable direction. I provide some example targets for such deliberate tipping of positive change. This article is part of the theme issue 'Climate change and ecosystems: threats, opportunities and solutions'.

Temperature change as a driver of spatial patterns and long-term trends in chironomid (Insecta: Diptera) diversity

Anthropogenic activities have led to a global decline in biodiversity, and monitoring studies indicate that both insect communities and wetland ecosystems are particularly affected. However, there is a need for long-term data (over centennial or millennial timescales) to better understand natural community dynamics and the processes that govern the observed trends. Chironomids (Insecta: Diptera: Chironomidae) are often the most abundant insects in lake ecosystems, sensitive to environmental change, and, because their larval exoskeleton head capsules preserve well in lake sediments, they provide a unique record of insect community dynamics through time. Here, we provide the results of a metadata analysis of chironomid diversity across a range of spatial and temporal scales. First, we analyse spatial trends in chironomid diversity using Northern Hemispheric data sets overall consisting of 837 lakes. Our results indicate that in most of our data sets, summer temperature (T_jul ) is strongly associated with spatial trends in modern-day chironomid diversity. We observe a strong increase in chironomid alpha diversity with increasing T_jul in regions with present-day T_jul between 2.5 and 14°C. In some areas with T_jul  > 14°C, chironomid diversity stabilizes or declines. Second, we demonstrate that the direction and amplitude of change in alpha diversity in a compilation of subfossil chironomid records spanning the last glacial-interglacial transition (~15,000-11,000 years ago) are similar to those observed in our modern data. A compilation of Holocene records shows that during phases when the amplitude of temperature change was small, site-specific factors had a greater influence on the chironomid fauna obscuring the chironomid diversity-temperature relationship. Our results imply expected overall chironomid diversity increases in colder regions such as the Arctic under sustained global warming, but with complex and not necessarily predictable responses for individual sites.

Network parameters quantify loss of assemblage structure in human-impacted lake ecosystems

Lake biodiversity is an incomplete indicator of exogenous forcing insofar as it ignores underlying deformations of community structure. Here, we seek a proxy for deformation in a network of diatom assemblages comprising 452 species in 273 lakes across China. We test predictions from network theory that nodes of similar type will tend to self-organize in an unstressed system to a positively skewed frequency distribution of nodal degree. The empirical data reveal shifts in the frequency distributions of species associations across regions, from positive skew in lakes in west China with a history of low human impacts, to predominantly negative skew amongst lakes in highly disturbed regions in east China. Skew values relate strongly to nutrient loading from agricultural activity and urbanization, as measured by total phosphorus in lake water. Reconstructions through time show that positive skew reduces with temporal intensification of human impacts in the lake and surrounding catchments, and rises as lakes recover from disturbance. Our study illustrates how network parameters can track the loss of aquatic assemblage structure in lakes associated with human pressures.

Complex relationship between the diversity and stability of chironomid assemblages in the recent sediments of two large alpine lakes in SW China

There is no doubt that the diversity and stability of freshwater ecosystems have suffered dramatic changes as a result of intensified human activities. However, the relationship between community diversity and stability is still debated. In this study, we used biological and geochemical records from the recent sediments of two lakes to test the hypothesis that different aspects of the diversity of the chironomid community have different relationships with community stability. Yangzong Lake (YZ) and Chenghai Lake (CH) are large and deep alpine lakes in SW China. We conducted a multi-proxy study of the sedimentary records spanning the last 200 years from the two lakes. Our focus was on subfossil chironomid remains, but analyses of chemical elements, total organic carbon (TOC) and total nitrogen (TN) were also conducted. The principal results are as follows: 1) Both nutrient and chironomid assemblages underwent a critical transition in 1990 at YZ and in 1998 at CH. 2) The response of species richness varied between the two lakes, but the trends of their respective β diversity indices are consistent, despite the fact that the contributors to β diversity are different. 3) The stability of the chironomid communities has decreased in both lakes since the mid-20th century. 4) The relationship between diversity and stability varies in relation to the type of diversity. Overall, our results emphasize the importance of considering the complex nature of diversity and stability when studying community assemblages.

Ordered diatom species loss along a total phosphorus gradient in eutrophic lakes of the lower Yangtze River basin, China

As global changes begin to affect the biosphere profoundly, the impacts on ecosystem health will become more significant. Understanding the sequence of functional species loss along an environmental or ecological gradient remains a research priority for ecosystem conservation. In this paper, nestedness, β-diversity and its components in diatom communities are used as ecological indicators of the dynamic change in functional species along environment gradients in 76 lakes of the lower Yangtze River basin, China. The results indicate that species turnover is typically the dominant component of β-diversity and that the influence of nestedness is generally low. However, changes in nestedness denote a significant threshold of lake eutrophication at a total phosphorus (TP) level of 0.06 mg/l, which is lower than the threshold indicated by diatom diversity. This finding was coupled with theoretical predictions about the successive proportional loss of 'canary' and 'keystone' species, which are replaced by 'weedy' species. These results show that nestedness of diatom communities can provide an additional metric for evaluating lake ecosystem health in this region. As management targets for nutrient control have already been introduced in the region, a revision of the identified critical phosphorus level (i.e., TP = 0.087-0.1 mg/l) to TP = 0.06 mg/l is proposed to keep lakes under low risk.

Rate of recovery from perturbations as a means to forecast future stability of living systems

Anticipating critical transitions in complex ecological and living systems is an important need because it is often difficult to restore a system to its pre-transition state once the transition occurs. Recent studies demonstrate that several indicators based on changes in ecological time series can indicate that the system is approaching an impending transition. An exciting question is, however, whether we can predict more characteristics of the future system stability using measurements taken away from the transition. We address this question by introducing a model-less forecasting method to forecast catastrophic transition of an experimental ecological system. The experiment is based on the dynamics of a yeast population, which is known to exhibit a catastrophic transition as the environment deteriorates. By measuring the system's response to perturbations prior to transition, we forecast the distance to the upcoming transition, the type of the transition (i.e., catastrophic/non-catastrophic) and the future equilibrium points within a range near the transition. Experimental results suggest a strong potential for practical applicability of this approach for ecological systems which are at risk of catastrophic transitions, where there is a pressing need for information about upcoming thresholds.

How one might miss early warning signals of critical transitions in time series data: A systematic study of two major currency pairs

There is growing interest in the use of critical slowing down and critical fluctuations as early warning signals for critical transitions in different complex systems. However, while some studies found them effective, others found the opposite. In this paper, we investigated why this might be so, by testing three commonly used indicators: lag-1 autocorrelation, variance, and low-frequency power spectrum at anticipating critical transitions in the very-high-frequency time series data of the Australian Dollar-Japanese Yen and Swiss Franc-Japanese Yen exchange rates. Besides testing rising trends in these indicators at a strict level of confidence using the Kendall-tau test, we also required statistically significant early warning signals to be concurrent in the three indicators, which must rise to appreciable values. We then found for our data set the optimum parameters for discovering critical transitions, and showed that the set of critical transitions found is generally insensitive to variations in the parameters. Suspecting that negative results in the literature are the results of low data frequencies, we created time series with time intervals over three orders of magnitude from the raw data, and tested them for early warning signals. Early warning signals can be reliably found only if the time interval of the data is shorter than the time scale of critical transitions in our complex system of interest. Finally, we compared the set of time windows with statistically significant early warning signals with the set of time windows followed by large movements, to conclude that the early warning signals indeed provide reliable information on impending critical transitions. This reliability becomes more compelling statistically the more events we test.