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Foreseeing population collapse is an on-going target in ecology, and this has led to the development of early warning signals based on expected changes in leading indicators before a bifurcation. Such signals have been sought for in abundance time-series data on a population of interest, with varying degrees of success. Here we move beyond these established methods by including parallel time-series data of abundance and fitness-related trait dynamics. Using data from a microcosm experiment, we show that including information on the dynamics of phenotypic traits such as body size into composite early warning indices can produce more accurate inferences of whether a population is approaching a critical transition than using abundance time-series alone. By including fitness-related trait information alongside traditional abundance-based early warning signals in a single metric of risk, our generalizable approach provides a powerful new way to assess what populations may be on the verge of collapse. Predicting population collapse by monitoring key early warning signals in time-series data may highlight when interventions are needed. Here, the authors show that including information on phenotypic traits like body size can more accurately predict critical transitions than abundance data alone.

Early warning signals (EWSs) offer the hope that patterns observed in data can predict the future states of ecological systems. While a large body of research identifies such signals prior to the collapse of populations, the prediction that such signals should also be present before a system’s recovery has thus far been overlooked. We assess whether EWSs are present prior to the recovery of overexploited marine systems using a trait-based ecological model and analysis of real-world fisheries data. We show that both abundance and trait-based signals are independently detectable prior to the recovery of stocks, but that combining these two signals provides the best predictions of recovery. This work suggests that the efficacy of conservation interventions aimed at restoring systems which have collapsed may be predicted prior to the recovery of the system, with direct relevance for conservation planning and policy. While several studies have documented early warning signals of population collapse, the use of such signals as indicators of population recovery has not been investigated. Here the authors use models and empirical fisheries data to show that there are statistical indicators preceding recovery of cod populations.

Carcharocles megalodon (\"Megalodon\") is the largest shark that ever lived. Based on its distribution, dental morphology, and associated fauna, it has been suggested that this species was a cosmopolitan apex predator that fed on marine mammals from the middle Miocene to the Pliocene (15.9-2.6 Ma). Prevailing theory suggests that the extinction of apex predators affects ecosystem dynamics. Accordingly, knowing the time of extinction of C. megalodon is a fundamental step towards understanding the effects of such an event in ancient communities. However, the time of extinction of this important species has never been quantitatively assessed. Here, we synthesize the most recent records of C. megalodon from the literature and scientific collections and infer the date of its extinction by making a novel use of the Optimal Linear Estimation (OLE) model. Our results suggest that C. megalodon went extinct around 2.6 Ma. Furthermore, when contrasting our results with known ecological and macroevolutionary trends in marine mammals, it became evident that the modern composition and function of modern gigantic filter-feeding whales was established after the extinction of C. megalodon. Consequently, the study of the time of extinction of C. megalodon provides the basis to improve our understanding of the responses of marine species to the removal of apex predators, presenting a deep-time perspective for the conservation of modern ecosystems.

The term ‘sixth mass extinction’ has become synonymous with the current biodiversity crisis. However, despite a general agreement that current biodiversity declines are severe, no consensus has been reached on whether this constitutes a ‘mass extinction event’, and thus, whether our current situation is comparable to the catastrophic extinction events of deep time. Here, we suggest that our inability to gauge whether the current biodiversity crisis is a mass extinction event may lie less in quantifiable evidence and more in the language used to define such events. We highlight areas of linguistic contention, vagueness and epistemic dispute, and discuss the role of post hoc decision‐making and language in shaping our understanding and communication of biodiversity loss. Our discussion raises larger questions about how we communicate science to the public, funders and other scientists, and how we use language to both shape awareness and leverage action. The term ‘sixth mass extinction’ used for the current biodiversity crisis lacks consensus on its accuracy. The epistemic dispute stemming from this ambiguity underscores the importance of clear communication in shaping public awareness and spurring action regarding biodiversity loss.

Research aimed at identifying indicators of persistent abrupt shifts in ecological communities, a.k.a regime shifts, has led to the development of a suite of early warning signals (EWSs). As these often perform inaccurately when applied to real-world observational data, it remains unclear whether critical transitions are the dominant mechanism of regime shifts and, if so, which EWS methods can predict them. Here, using multi-trophic planktonic data on multiple lakes from around the world, we classify both lake dynamics and the reliability of classic and second generation EWSs methods to predict whole-ecosystem change. We find few instances of critical transitions, with different trophic levels often expressing different forms of abrupt change. The ability to predict this change is highly processing dependant, with most indicators not performing better than chance, multivariate EWSs being weakly superior to univariate, and a recent machine learning model performing poorly. Our results suggest that predictive ecology should start to move away from the concept of critical transitions, developing methods suitable for predicting resilience loss not limited to the strict bounds of bifurcation theory. Abrupt regime shifts could in theory be predicted from early warning signals. Here, the authors show that true critical transitions are challenging to classify in lake planktonic systems, due to mismatches between trophic levels, and reveal uneven performance of early warning signal detection methods.

The extinction of a species is an event that often captures the public’s imagination. Indeed, declaring a species as extinct is typically though of as a way of raising awareness of the impacts humanity is having on the global biosphere. However, thus far there is little evidence to suggest whether declaring a species as extinct leads to increased public concern, and whether this concern may in turn lead to support to slow future biodiversity loss. To assess this, I look to see whether there is any increase in the number of donations made to a large conservation charity after five recent, well-publicised extinction events that have generated public interest. I find that peaks in public interest in a species that has been reported as extinct may correspond to an increase in the number of donations made, but that other conservation related events may also affect month–month variation in the number of pledges made.

Temperature change affects biological systems in multifaceted ways, including the alteration of species interaction strengths, with implications for the stability of populations and communities. Temperature‐dependent changes to antipredatory responses are an emerging mechanism of destabilization and thus there is a need to understand how prey species respond to predation pressures in the face of changing temperatures. Here, using ciliate protozoans, we assess whether temperature can alter the strength of phenotypic antipredator responses in a prey species and whether this relationship depends on the predator's hunting behavior. We exposed populations of the ciliate Paramecium caudatum to either (i) a sit‐and‐wait generalist predator (Homalozoon vermiculare) or (ii) a specialized active swimmer predator (Didinium nasutum) across two different temperature regimes (15 and 25°C) to quantify the temperature dependence of antipredator responses over a 24‐h period. We utilized a novel high‐throughput automated robotic monitoring system to track changes in the behavior (swimming speed) and morphology (cell size) of P. caudatum at frequencies and resolutions previously unachievable by manual sampling. The change in swimming speed through the 24 h differed between the two temperatures but was not altered by the presence of the predators. In contrast, P. caudatum showed a substantial temperature‐dependent morphological response to the presence of D. nasutum (but not H. vermiculare), changing cell shape toward a more elongated morph at 15°C (but not at 25°C). Our findings suggest that temperature can have strong effects on prey morphological responses to predator presence, but that this response is potentially dependent on the predator's feeding strategy. This suggests that greater consideration of synergistic antipredator behavioral and physiological responses is required in species and communities subject to environmental changes. Paramecium caudatum shows a substantial temperature‐dependent morphological response to the presence of Didinium nasutum (but not Homalozoon vermiculare), changing cell shape toward a more elongated morph at 15°C (but not at 25°C). This suggests that temperature can have strong effects on prey morphological responses to predator presence, but that this response is potentially dependent on the predator's feeding strategy.

Critical transitions are qualitative changes of state that occur when a stochastic dynamical system is forced through a critical point. Many critical transitions are preceded by characteristic fluctuations that may serve as model‐independent early warning signals, implying that these events may be predictable in applications ranging from physics to biology. In nonbiological systems, the strength of such early warning signals has been shown partly to be determined by the speed at which the transition occurs. It is currently unknown whether biological systems, which are inherently high dimensional and typically display low signal‐to‐noise ratios, also exhibit this property, which would have important implications for how ecosystems are managed, particularly where the forces exerted on a system are anthropogenic. We examine whether the rate of forcing can alter the strength of early warning signals in (1) a model exhibiting a fold bifurcation where a state shift is driven by the harvesting of individuals, and (2) a model exhibiting a transcritical bifurcation where a state shift is driven by increased grazing pressure. These models predict that the rate of forcing can alter the detectability of early warning signals regardless of the underlying bifurcation the system exhibits, but that this result may be more pronounced in fold bifurcations. These findings have important implications for the management of biological populations, particularly harvested systems such as fisheries, and suggest that knowing the class of bifurcations a system will manifest may help discriminate between true‐positive and false‐positive signals. Predicting population collapse is a major goal in conservation biology and ecology and has led to the development of so‐called early warning signals, which can be used to predict whether a population is approaching a critical transition. In nonbiological systems, the strength of such early warning signals has been shown to be partly determined by the speed at which the transition occurs. We show, using a combination of modeling and experimental approaches, that the rate of forcing of a biological system has the potential to alter the strength of early warning signals, but that this result is contingent upon the underlying nature of the bifurcation manifested by the system.

Aim: Given its catastrophic consequences, the extinction of apex predators has long been of interest to modern ecology. Despite major declines, no presentday species of marine apex predator has yet become extinct. Because of their vulnerability, understanding the mechanisms leading to their extinction in the past could provide insight into the natural factors that interact with human threats to drive their loss. We studied the geographical distribution patterns of the extinct macro-predatory shark Carcharocles megalodon in order to elucidate its pathway to extinction. Location: World-wide from the Miocene to the Pliocene (c. 23-2.6 Ma). Methods: A meta-analysis of C. megalodon occurrence records was performed using the Paleobiology Database as a platform. The data were binned into geological time slices, and the circular home range around each data point was mapped in reconstructions made in GPlates. We then quantitatively assessed the species' geographical range and global abundance over time, and the relationship between distribution and climate. Results: The pathway to extinction of C. megalodon probably started in the late Miocene with a decrease in its global abundance. This decrease was then followed by a decline in its geographical range during the Pliocene. Although the extinction of C. megalodon has been attributed to climate change, we found no evidence of direct effects of global temperature. Instead, we found that the collapse in geographical distribution coincided mainly with a drop in the diversity of filter-feeding whales and the appearance of new competitors (large predatory whales and the great white shark). Main conclusions: This research represents the first study of the distributional trends of an extinct, cosmopolitan apex predator in deep-time. Our results suggest that biotic factors, and not direct temperature limitations, were probably the primary drivers of the extinction of the largest marine apex predators that ever lived.

As we enter the next phase of international policy commitments to halt biodiversity loss (e.g., Kunming-Montreal Global Biodiversity Framework), biodiversity indicators will play an important role in forming the robust basis upon which targeted, and time sensitive conservation actions are developed. Population trend indicators are one of the most powerful tools in biodiversity monitoring due to their responsiveness to changes over short timescales and their ability to aggregate species trends from global down to sub-national or even local scale. We consider how the project behind one of the foremost population level indicators - the Living Planet Index - has evolved over the last 25 years, its value to the field of biodiversity monitoring, and how its components have portrayed a compelling account of the changing status of global biodiversity through its application at policy, research and practice levels. We explore ways the project can develop to enhance our understanding of the state of biodiversity and share lessons learned to inform indicator development and mobilise action.