Simple signals indicate which period of the annual cycle drives declines in seasonal populations

Demographic consequences of changes in environmental periodicity

The fate of natural populations is mediated by complex interactions among vital rates, which can vary within and among years. Although the effects of random, among-year variation in vital rates have been studied extensively, relatively little is known about how periodic, nonrandom variation in vital rates affects populations. This knowledge gap is potentially alarming as global environmental change is projected to alter common periodic variations, such as seasonality. We investigated the effects of changes in vital-rate periodicity on populations of three species representing different forms of adaptation to periodic environments: the yellow-bellied marmot (Marmota flaviventer), adapted to strong seasonality in snowfall; the meerkat (Suricata suricatta), adapted to inter-annual stochasticity as well as seasonal patterns in rainfall; and the dewy pine (Drosophyllum lusitanicum), adapted to fire regimes and periodic post-fire habitat succession. To assess how changes in periodicity affect population growth, we parameterized periodic matrix population models and projected population dynamics under different scenarios of perturbations in the strength of vital-rate periodicity. We assessed the effects of such perturbations on various metrics describing population dynamics, including the stochastic growth rate, log λ_S . Overall, perturbing the strength of periodicity had strong effects on population dynamics in all three study species. For the marmots, log λ_S decreased with increased seasonal differences in adult survival. For the meerkats, density dependence buffered the effects of perturbations of periodicity on log λ_S . Finally, dewy pines were negatively affected by changes in natural post-fire succession under stochastic or periodic fire regimes with fires occurring every 30 years, but were buffered by density dependence from such changes under presumed more frequent fires or large-scale disturbances. We show that changes in the strength of vital-rate periodicity can have diverse but strong effects on population dynamics across different life histories. Populations buffered from inter-annual vital-rate variation can be affected substantially by changes in environmentally driven vital-rate periodic patterns; however, the effects of such changes can be masked in analyses focusing on inter-annual variation. As most ecosystems are affected by periodic variations in the environment such as seasonality, assessing their contributions to population viability for future global-change research is crucial.

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.

Early warning indicators of population collapse in a seasonal environment

Recent studies have demonstrated that generic statistical signals derived from time series of population abundance and fitness-related traits of individuals can provide reliable indicators of impending shifts in population dynamics. However, how the seasonal timing of environmental stressors influences these early warning indicators is not well understood. The goal of this study was to experimentally assess whether the timing of stressors influences the production, detection and sensitivity of abundance- and trait-based early warning indicators derived from declining populations. In a multi-generation, season-specific habitat loss experiment, we exposed replicate populations of Drosophila melanogaster to one of two rates of chronic habitat loss (10% or 20% per generation) in either the breeding or the non-breeding period. We counted population abundance at the beginning of each season, and measured body mass and activity levels in a sample of individuals at the end of each generation. When habitat was lost during the breeding period, declining populations produced signals consistent with those documented in previous studies. Inclusion of trait-based indicators generally improved the detection of impending population collapse. However, when habitat was lost during the non-breeding period, the predictive capacity of these indicators was comparatively diminished. Our results have important implications for interpreting signals in the wild because they suggest that the production and detection of early warning indicators depends on the season in which stressors occur, and that this is likely related to the capacity of populations to respond numerically the following season.

An experimental test of the ecological mechanisms driving density-mediated carry-over effects in a seasonal population

Carry-over effects occur when past experience influences current individual performance. Although variation in conspecific density in one season has been shown to carry over to influence dynamics in the following season, the proximate ecological mechanisms driving these effects are unknown. One hypothesis is that high density decreases food availability, resulting in poor physiological condition, which in turn compromises performance the next season. Alternatively, high conspecific density could also lead to a high degree of antagonistic interactions, decreasing the amount of time individuals spend foraging. To investigate these hypotheses, we applied a factorial design where both conspecific density and per capita food availability during the non-breeding period were independently manipulated in seasonal populations of common fruit flies (Drosophila melanogaster Meigen, 1830). Individual condition at the beginning of the breeding period was influenced by per capita food availability but not density during the previous non-breeding period. In contrast, reproductive output was most strongly influenced by the interaction between per capita food availability and density in the previous non-breeding period, such that populations that experienced high non-breeding densities and low food availability had the lowest reproductive output. However, the strength of this effect was relatively weak. Our results demonstrate how environmental and social conditions in one part of the annual cycle can carry over to influence individual performance in subsequent periods.