Food web structure and interaction strength pave the way for vulnerability to extinction

Processes governing species richness in communities exposed to temporal environmental stochasticity: A review and synthesis of modelling approaches

Research into the processes governing species richness has often assumed that the environment is fixed, whereas realistic environments are often characterised by random fluctuations over time. This temporal environmental stochasticity (TES) changes the demographic rates of species populations, with cascading effects on community dynamics and species richness. Theoretical and applied studies have used process-based mathematical models to determine how TES affects species richness, but under a variety of frameworks. Here, we critically review such studies to synthesise their findings and draw general conclusions. We first provide a broad mathematical framework encompassing the different ways in which TES has been modelled. We then review studies that have analysed models with TES under the assumption of negligible interspecific interactions, such that a community is conceptualised as the sum of independent species populations. These analyses have highlighted how TES can reduce species richness by increasing the frequency at which a species becomes rare and therefore prone to extinction. Next, we review studies that have relaxed the assumption of negligible interspecific interactions. To simplify the corresponding models and make them analytically tractable, such studies have used mean-field theory to derive fixed parameters representing the typical strength of interspecific interactions under TES. The resulting analyses have highlighted community-level effects that determine how TES affects species richness, for species that compete for a common limiting resource. With short temporal correlations of environmental conditions, a non-linear averaging effect of interspecific competition strength over time gives an increase in species richness. In contrast, with long temporal correlations of environmental conditions, strong selection favouring the fittest species between changes in environmental conditions results in a decrease in species richness. We compare such results with those from invasion analysis, which examines invasion growth rates (IGRs) instead of species richness directly. Qualitative differences sometimes arise because the IGR is the expected growth rate of a species when it is rare, which does not capture the variation around this mean or the probability of the species becoming rare. Our review elucidates key processes that have been found to mediate the negative and positive effects of TES on species richness, and by doing so highlights key areas for future research.

Community ecological response to polycyclic aromatic hydrocarbons in Baiyangdian Lake based on an ecological model

The dynamic response of a single population to chemicals can be represented by a Weibull function. However, it is unclear whether the overall response can still be represented in this manner when scaled up to the community level. In this study, we investigated the responses of biological communities to polycyclic aromatic hydrocarbons by using an ecological model of Baiyangdian Lake in northern China. The community dynamics process was divided into the following three stages. In the first stage, toxicity, played a dominant role and strong, medium, and weak species responses were observed according to the toxicity sensitivity. In the second stage, the dynamic process was dominated by the interaction strength with three alternative dynamic pathways comprising of direct response, no response, or inverse response. In the third stage, the toxicity was again dominant, and the biomasses of all species decreased to extinction. The toxicological dynamics were far more complex at the community level than those at the single species level and they were also influenced by the interaction strength as well as toxicity. The toxicological dynamic process in the community was constantly driven by the competing effects of these two forces. In addition to the total biomass, the interaction strength was identified as a suitable community-level signal because it exhibited good indicator properties regarding ecosystem steady-state transitions. However, we found that food web stability indicators were not suitable for use as community-level signals because they were not sensitive to changes in the ecosystem state. Some ecological management suggestions have been proposed, including medium to long-term monitoring, and reduction of external pollution loads and bioindicators. The results obtained in this study increase our understanding of how chemicals interfere with community dynamics, and the interaction strength and total biomass were identified as useful holistic indicators.

Trait-based approaches to global change ecology: moving from description to prediction

Trait-based approaches are increasingly recognized as a tool for understanding ecosystem re-assembly and function under intensifying global change. Here we synthesize trait-based research globally (n = 865 studies) to examine the contexts in which traits may be used for global change prediction. We find that exponential growth in the field over the last decade remains dominated by descriptive studies of terrestrial plant morphology, highlighting significant opportunities to expand trait-based thinking across systems and taxa. Very few studies (less than 3%) focus on predicting ecological effects of global change, mostly in the past 5 years and via singular traits that mediate abiotic limits on species distribution. Beyond organism size (the most examined trait), we identify over 2500 other morphological, physiological, behavioural and life-history traits known to mediate environmental filters of species' range and abundance as candidates for future predictive global change work. Though uncommon, spatially explicit process models—which mechanistically link traits to changes in organism distributions and abundance—are among the most promising frameworks for holistic global change prediction at scales relevant for conservation decision-making. Further progress towards trait-based forecasting requires addressing persistent barriers including (1) matching scales of multivariate trait and environment data to focal processes disrupted by global change, and (2) propagating variation in trait and environmental parameters throughout process model functions using simulation.

Conditions for Eltonian Pyramids in Lotka-Volterra Food Chains

In ecological communities consumers (excluding parasites and parasitoids) are in general larger and less numerous than their resource. This results in a well-known observation known as 'Eltonian pyramids' or the 'pyramid of numbers', and metabolic arguments suggest that this pattern is independent of the number of trophic levels in a system. At the same time, Lotka-Volterra (LV) consumer-resource models are a frequently used tool to study many questions in community ecology, but their capacity to produce Eltonian pyramids has not been formally analysed. Here, I address this knowledge gap by investigating if and when LV food chain models give rise to Eltonian pyramids. I show that Eltonian pyramids are difficult to reproduce without density-dependent mortality in the consumers, unless biologically plausible relationships between mortality rate and interaction strength are taken into account.