Temporal correlations among demographic parameters are ubiquitous but highly variable across species

Population Dynamic Consequences of Context-Dependent Trade-Offs across Life Histories

AbstractTrade-offs are central to life history theory and play a role in driving life history diversity. They arise from a finite amount of resources that need to be allocated among different functions by an organism. Yet covariation of demographic rates among individuals frequently do not reflect allocation trade-offs because of variation in resource acquisition. The covariation of traits among individuals can thus vary with the environment and often increases in benign environments. Surprisingly, little is known about how such context-dependent expression of trade-offs among individuals affect population dynamics across species with different life histories. To study their influence on population stability, we develop an individual-based simulation where covariation in demographic rates varies with the environment. We use it to simulate population dynamics for various life histories across the slow-fast pace-of-life continuum. We found that the population dynamics of slower life histories are relatively more sensitive to changes in covariation, regardless of the trade-off considered. Additionally, we found that the impact on population stability depends on which trade-off is considered, with opposite effects of intraindividual and intergenerational trade-offs. Last, the expression of different trade-offs can feed back to influence generation time through selection acting on individual heterogeneity within cohorts, ultimately affecting population dynamics.

Consequences of cross-season demographic correlations for population viability

Demographic correlations are pervasive in wildlife populations and can represent important secondary drivers of population growth. Empirical evidence suggests that correlations are in general positive for long-lived species, but little is known about the degree of variation among spatially segregated populations of the same species in relation to environmental conditions. We assessed the relative importance of two cross-season correlations in survival and productivity, for three Atlantic puffin (Fratercula arctica) populations with contrasting population trajectories and non-overlapping year-round distributions. The two correlations reflected either a relationship between adult survival prior to breeding on productivity, or a relationship between productivity and adult survival the subsequent year. Demographic rates and their correlations were estimated with an integrated population model, and their respective contributions to variation in population growth were calculated using a transient-life table response experiment. For all three populations, demographic correlations were positive at both time lags, although their strength differed. Given the different year-round distributions of these populations, this variation in the strength population-level demographic correlations points to environmental conditions as an important driver of demographic variation through life-history constraints. Consequently, the contributions of variances and correlations in demographic rates to population growth rates differed among puffin populations, which has implications for-particularly small-populations' viability under environmental change as positive correlations tend to reduce the stochastic population growth rate.

Conservation implications of a mismatch between data availability and demographic impact

Cost-effective use of limited conservation resources requires understanding which data most contribute to alleviating biodiversity declines. Interventions might reasonably prioritise life-cycle transitions with the greatest influence on population dynamics, yet some contributing vital rates are particularly challenging to document. This risks managers making decisions without sufficient empirical coverage of the spatiotemporal variation experienced by the species. Here, we aimed to explore whether the number of studies contributing estimates for a given life-stage transition aligns with that transition's demographic impact on population growth rate, λ. We parameterised a matrix population model using meta-analysis of vital rates for the common eider (Somateria mollissima), an increasingly threatened yet comparatively data-rich species of seaduck, for which some life stages are particularly problematic to study. Female common eiders exhibit intermittent breeding, with some established breeders skipping one or more years between breeding attempts. Our meta-analysis yielded a breeding propensity of 0.72, which we incorporated into our model with a discrete and reversible 'nonbreeder' stage (to which surviving adults transition with a probability of 0.28). The transitions between breeding and nonbreeding states had twice the influence on λ than fertility (summed matrix-element elasticities of 24% and 11%, respectively), whereas almost 15 times as many studies document components of fertility than breeding propensity (n = 103 and n = 7, respectively). The implications of such mismatches are complex because the motivations for feasible on-the-ground conservation actions may be different from what is needed to reduce uncertainty in population projections. Our workflow could form an early part of the toolkit informing future investment of finite resources, to avoid repeated disconnects between data needs and availability thwarting evidence-led conservation.

Compensatory responses of vital rates attenuate impacts of competition on population growth and promote coexistence

Competition is among the most important factors regulating plant population and community dynamics, but we know little about how different vital rates respond to competition and jointly determine population growth and species coexistence. We conducted a field experiment and parameterised integral projection models to model the population growth of 14 herbaceous plant species in the absence and presence of neighbours across an elevation gradient (284 interspecific pairs). We found that suppressed individual growth and seedling establishment contributed the most to competition-induced declines in population growth, although vital rate contributions varied greatly between species and with elevation. In contrast, size-specific survival and flowering probability and seed production were frequently enhanced under competition. These compensatory vital rate responses were nearly ubiquitous (occurred in 92% of species pairs) and significantly reduced niche overlap and stabilised coexistence. Our study highlights the importance of demographic processes for regulating population and community dynamics, which has often been neglected by classic coexistence theories.

Pathways to global-change effects on biodiversity: new opportunities for dynamically forecasting demography and species interactions

In structured populations, persistence under environmental change may be particularly threatened when abiotic factors simultaneously negatively affect survival and reproduction of several life cycle stages, as opposed to a single stage. Such effects can then be exacerbated when species interactions generate reciprocal feedbacks between the demographic rates of the different species. Despite the importance of such demographic feedbacks, forecasts that account for them are limited as individual-based data on interacting species are perceived to be essential for such mechanistic forecasting-but are rarely available. Here, we first review the current shortcomings in assessing demographic feedbacks in population and community dynamics. We then present an overview of advances in statistical tools that provide an opportunity to leverage population-level data on abundances of multiple species to infer stage-specific demography. Lastly, we showcase a state-of-the-art Bayesian method to infer and project stage-specific survival and reproduction for several interacting species in a Mediterranean shrub community. This case study shows that climate change threatens populations most strongly by changing the interaction effects of conspecific and heterospecific neighbours on both juvenile and adult survival. Thus, the repurposing of multi-species abundance data for mechanistic forecasting can substantially improve our understanding of emerging threats on biodiversity.

The shifting importance of abiotic and biotic factors across the life cycles of wild pollinators

Organisms living in seasonal environments are exposed to different environmental conditions as they transition from one life stage to the next across their life cycle. How different life stages respond to these varying conditions, and the extent to which different life stages are linked, are fundamental components of the ecology of an organism. Nevertheless, the influence of abiotic and biotic factors on different parts of an organism's life cycle is often not accounted for, which limits our understanding of the ecological consequences of environmental change. We investigated the relative importance of climate conditions, food availability, and previous life-stage abundance in an assemblage of seven wild bumble bee species, asking: how do these three factors directly influence bee abundance at each life stage? To do so, we used a 7-year dataset where we monitored climate conditions, floral resources, and abundances of bees in each life stage across the active colony life cycle in a highly seasonal subalpine ecosystem in the Colorado Rocky Mountains, USA. Bee abundance at different life stages responded to abiotic and biotic conditions in a broadly consistent manner across the seven species: the survival and recruitment stage of the life cycle (overwintered queens) responded negatively to longer winters; the growth stage (workers) responded positively to floral resource availability; and the reproductive stage (males) was positively related to the abundance of the previous life stage (workers). Most species also exhibited some idiosyncratic responses. Our long-term examination of annual bumble bees reveals a general set of responses in the abundance of each life stage to climate conditions, floral resource availability, and previous life stage. Across species, these three factors each directly influenced a distinct life stage, illustrating how their relative importance can shift throughout the life cycle. The life-cycle approach that we have taken highlights that important details about demography can be overlooked without considering life-stage-specific responses. Ultimately, it is these life-stage-specific responses that shape population outcomes, not only for animal pollinators but also for many organisms living in seasonal environments.

Life history adaptations to fluctuating environments: Combined effects of demographic buffering and lability

Demographic buffering and lability have been identified as adaptive strategies to optimise fitness in a fluctuating environment. These are not mutually exclusive, however, we lack efficient methods to measure their relative importance for a given life history. Here, we decompose the stochastic growth rate (fitness) into components arising from nonlinear responses and variance-covariance of demographic parameters to an environmental driver, which allows studying joint effects of buffering and lability. We apply this decomposition for 154 animal matrix population models under different scenarios to explore how these main fitness components vary across life histories. Faster-living species appear more responsive to environmental fluctuations, either positively or negatively. They have the highest potential for strong adaptive demographic lability, while demographic buffering is a main strategy in slow-living species. Our decomposition provides a comprehensive framework to study how organisms adapt to variability through buffering and lability, and to predict species responses to climate change.