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Plant pathogens are often hypothesized to promote species coexistence by generating conspecific negative density dependence (CNDD). However, the relative importance of fungal versus oomycete pathogens in maintaining plant species coexistence and community composition remains unresolved, despite their recognized effects on plant performance. Here, we use fungicide application to investigate how fungal versus oomycete pathogens affect plant species coexistence in an alpine meadow. We found that the severity of foliar fungal disease was density-dependent at both intra- and interspecific levels. Fungal pathogen-exclusion treatment successfully decreased the severity of foliar fungal diseases, with no detectable effects on root colonization by arbuscular mycorrhizal fungi or on soil chemical properties. Fungal pathogens were important factors shaping CNDD across 25 coexisting plant species. Exclusion of fungal pathogens significantly reduced plant species richness and Shannon’s evenness. Treatments that excluded fungal pathogens also led to significant shifts in plant community composition toward more Poaceae and Cyperaceae. These results indicate that fungal pathogens, especially those affecting aboveground plant parts, may play a larger role in maintaining species coexistence and shaping community composition than has been previously recognized.

Population dynamics models have long assumed that populations are composed of a restricted number of groups, where individuals in each group have identical demographic rates and where all groups are similarly affected by density-dependent and -independent effects. However, individuals usually vary tremendously in performance and in their sensitivity to environmental conditions or resource limitation, such that individual contributions to population growth will be highly variable. Recent efforts to integrate individual processes in population models open up new opportunities for the study of eco-evolutionary processes, such as the density-dependent influence of environmental conditions on the evolution of morphological, behavioral, and life-history traits. We review recent advances that demonstrate how including individual mechanisms in models of population dynamics contributes to a better understanding of the drivers of population dynamics within the framework of integrated population models (IPMs). IPMs allow for the integration in a single inferential framework of different data types as well as variable population structure including sex, social group, or territory, all of which can be formulated to include individual-level processes. Through a series of examples, we first show how IPMs can be beneficial for getting more accurate estimates of demographic traits than classic matrix population models by including basic population structure and their influence on population dynamics. Second, the integration of individual- and population-level data allows estimating density-dependent effects along with their inherent uncertainty by directly using the population structure and size to feedback on demography. Third, we show how IPMs can be used to study the influence of the dynamics of continuous individual traits and individual quality on population dynamics. We conclude by discussing the benefits and limitations of IPMs for integrating data at different spatial, temporal, and organismal levels to build more mechanistic models of population dynamics.

In the mid-1950s Western Desert of Australia, Aboriginal populations were in decline as families left for ration depots, cattle stations, and mission settlements. In the context of reduced population density, an ideal free-distribution model predicts landscape use should contract to the most productive habitats, and people should avoid areas that show more signs of extensive prior use. However, ecological or social facilitation due to Allee effects (positive density dependence) would predict that the intensity of past habitat use should correlate positively with habitat use. We analyzed fire footprints and fire mosaics from the accumulation of several years of landscape use visible on a 35,300-km² mosaic of aerial photographs covering much of contemporary Indigenous Martu Native Title Lands imaged between May and August 1953. Structural equation modeling revealed that, consistent with an Allee ideal free distribution, there was a positive relationship between the extent of fire mosaics and the intensity of recent use, and this was consistent across habitats regardless of their quality. Fire mosaics build up in regions with low cost of access to water, high intrinsic food availability, and good access to trade opportunities; these mosaics (constrained by water access during the winter) then draw people back in subsequent years or seasons, largely independent of intrinsic habitat quality. Our results suggest that the positive feedback effects of landscape burning can substantially change the way people value landscapes, affecting mobility and settlement by increasing sedentism and local population density.

Studies of spatial population synchrony constitute a central approach for understanding the drivers of ecological dynamics. Recently, identifying the ecological impacts of climate change has emerged as a new important focus in population synchrony studies. However, while it is well known that climatic seasonality and sequential density dependence influences local population dynamics, the role of season-specific density dependence in shaping large-scale population synchrony has not received attention. Here, we present a widely applicable analytical protocol that allows us to account for both season and geographic context-specific density dependence to better elucidate the relative roles of deterministic and stochastic sources of population synchrony, including the renowned Moran effect. We exemplify our protocol by analyzing time series of seasonal (spring and fall) abundance estimates of cyclic rodent populations, revealing that season-specific density dependence is a major component of population synchrony. By accounting for deterministic sources of synchrony (in particular season-specific density dependence), we are able to identify stochastic components. These stochastic components include mild winter weather events, which are expected to increase in frequency under climate warming in boreal and Arctic ecosystems. Interestingly, these weather effects act both directly and delayed on the vole populations, thus enhancing the Moran effect. Our study demonstrates how different drivers of population synchrony, presently altered by climate warming, can be disentangled based on seasonally sampled population time-series data and adequate population models.

Knowledge of the density-dependent processes that regulate animal populations is key to understanding, predicting, and conserving populations. In migratory birds, density-dependence is most often studied during the breeding season, yet we still lack a robust understanding of the reproductive traits through which density influences individual reproductive success. We used 27-yr of detailed, individual-level productivity data from an island-breeding population of Savannah sparrows Passerculus sandwichensis to evaluate effects of local and total annual population density on female reproductive success. Local density (number of neighbors within 50 m of a female's nest) had stronger effects on the number of young fledged than did total annual population density. Females nesting in areas of high local density were more likely to suffer nest predation and less likely to initiate and fledge a second clutch, which led to fewer young fledged in a season. Fledging fewer young subsequently decreased the likelihood of a female recruiting offspring into the breeding population in a subsequent year. Collectively, these results provide insight into the scale and reproductive mechanisms mediating density-dependent reproductive success and fitness in songbirds.

Mechanisms such as conspecific negative density dependence (CNDD) and niche partitioning have been proposed to explain species coexistence and community diversity. However, as a potentially important axis of niche partitioning, the role of interannual climate variability in driving local community dynamics remains largely unknown. Here we used a 15-year monitoring data set of more than 53,000 seedlings in a temperate forest to examine (1) what are the relative effects of interannual climate variability, biotic interactions, and habitat conditions on seedling survival; (2) how the effects of biotic interactions change with interannual climate variability, and habitat conditions; and (3) whether the impacts of interannual climate variability, biotic interactions, and habitat conditions differ with plant traits. Interannual climate variability accounted for the most variation in seedling survival at the community level, followed by biotic interactions, and habitat conditions. Increased snowpack and decreased minimum temperature during the nongrowing season had positive effects on seedling survival. Effects of conspecific neighbor density were weakened in higher snowpack, effective accumulated temperature, elevation, and soil-resource gradient, but were intensified with increased ultraviolet radiation, maximum precipitation, minimum temperature, and soil moisture. In addition, the relative importance of interannual climate variability versus biotic interactions differed depending on species-trait groups. Specifically, biotic interactions for gravity-dispersed species had a larger effect size in affecting seedling survival than other trait groups. Also, gravity-dispersed species experienced a stronger CNDD than wind-dispersed, probably because wind-dispersed seedlings rarely had adult conspecifics nearby. We found that interannual climate variability was most strongly associated with seedling survival, but the magnitude of climatic effects varied among species-trait groups. Interannual climate variability may act as an inhibitor or accelerator to density-dependent interactions and should be accounted for in future studies, as both a potential direct and indirect factor in understanding the diversity of forest communities.

Interactions among multiple resources and consumers involve two indirect interactions: resource competition among consumers and apparent competition among resources. However, competition among multiple consumers is typically viewed through the lens of direct interactions embodied in the Lotka-Volterra competition model, which fails to capture the mechanisms of these indirect interactions. In this paper, I analyze various elaborations of MacArthur's and Tilman's original consumer–resource models including more than two species per trophic level, saturating functional responses, and direct intraspecific density dependence within the consumers. First, the simplest model with two resources and two consumers with linear functional responses is analyzed via the structure of the resulting isoclines, and this is reconciled with Tilman's graphical ZNGI/consumption vector approach. With three species at each trophic level even in this simple model, each consumer is not required to have the largest impact on the resource that most limits its growth for multiple consumers to coexist. In fact, a consumer that is an inferior competitor on each resource in isolation may still coexist with superior competitors, and conversely a consumer that is an inferior competitor on each available resource may still be able to drive all other consumers extinct. However, the maximum number of coexisting consumers is set by the number of available resources. Saturating functional responses do not qualitatively alter the conditions for multiple consumers and resources to coexist at a stable point equilibrium but do increase the range of apparent competitive abilities for resources that can invade and coexist. Saturating functional responses also increase the range of dynamics that the community may display (i.e., limit cycles and chaos), which previous analyses have shown can permit more consumer species than resources to coexist. Adding direct intraspecific density dependence in the consumers, either in the form of feeding interference or density-dependent demographic rates, permit more consumers to coexist than available resources, even at stable point equilibria. Understanding the indirect effects that cascade through a community is essential to predicting community changes and understanding how species at multiple trophic levels coexist, and these indirect effects should not be shrouded behind the curtain of Lotka-Volterra competition.

It is 100 years since the first paper described the multiannual cycles in Arctic rodents and lagomorphs. The mechanisms driving population cycles in animals like lemmings and voles are complex, often attributed to extrinsic factors, such as food availability and quality, pathogens, parasites and/or predators. While extrinsic factors provide insights into population cycles, none fully explain the phenomenon. We propose an underlying innate, intrinsic mechanism, based on epigenetic regulation, that drives population cycles under harsh arctic conditions. We propose that epigenetically driven phenotypic changes associated with sexual development, growth and behaviour accumulate over time in offspring, eventually producing a phase change from rising population density to eventual population collapse. Under this hypothesis, and unlike previous hypotheses, extrinsic factors modify population cycles but would not be primary drivers. The interaction between our intrinsic cycle and extrinsic factors explains established phenomena like delayed‐density dependence, whereby population growth is controlled by time‐dependent negative feedback. We advocate integrating a century of field research with the latest epigenetic analysis to better understand the drivers of population cycles. It is 100 years since the first paper described the recurring nature of Arctic population cycles, yet the mechanistic drivers of these are still not well understood. This paper challenges researchers to consider a new paradigm, with reference to the role of epigenetics in the cycling process. We provide a testable hypothesis describing a series of hormonal/epigenetic steps that form an intrinsic cycle.

The enemy‐induced Janzen–Connell (JC) effect, a classic model invoking conspecific negative density dependence (CNDD) and distance dependence, is a primary biodiversity maintenance hypothesis. Yet, conflicting evidence for the JC effect leads to disagreement about its role in maintaining forest diversity. We focus this review on soil‐borne pathogens, which are the primary agent inducing the JC effect in many forest ecosystems. Although the test of the pathogen‐induced JC effect in ecology critically rests on the seedling mortality caused by soil pathogens, what has not been explicitly explored in the early literature but has increasingly received attention is the long‐recognized fact that the environment can alter virulence of pathogens and host susceptibility (thus pathogen–host interactions), as predicted by the classic disease triangle framework enlightened by pathology research in agricultural systems. Here, following the disease triangle framework we review evidence on how the pathogen‐induced JC effect may be contingent on context (e.g. environmental conditions, pathogen inoculum load and genetic divergence in host and pathogen populations). The reviewed evidence reveals and clarifies the conditions where pathogens may or may not cause disease to hosts, thus contributing to reconciling the inconsistent results about the pathogen‐induced JC effect in the literature. The context dependence of the disease triangle predicts that the pathogen‐induced JC effect would change under global change. Gaining insights from evidence that the pathogen‐induced JC effect is context‐dependent, we suggest that future tests on the JC hypothesis be conducted under the framework of disease triangle, and we stress the necessity by controlling the effect of context factors on plant–pathogen interactions when testing for the JC effect. We conclude the review by proposing three lines of future research for testing the importance of the JC effect in maintaining global forest tree species diversity, with a particular emphasis on testing the effect of global warming on the strength of pathogen–host interactions for better predicting changes of forest biodiversity under climate change. A plain language summary is available for this article. Plain Language Summary

Mutualisms are ubiquitous in nature, provide important ecosystem services, and involve many species of interest for conservation. Theoretical progress on the population dynamics of mutualistic interactions, however, comparatively lagged behind that of trophic and competitive interactions, leading to the impression that ecologists still lack a generalized framework to investigate the population dynamics of mutualisms. Yet, over the last 90 years, abundant theoretical work has accumulated, ranging from to detailed. Here, we review and synthesize historical models of two‐species mutualisms. We find that population dynamics of mutualisms are qualitatively robust across derivations, including levels of detail, types of benefit, and inspiring systems. Specifically, mutualisms tend to exhibit stable coexistence at high density and destabilizing thresholds at low density. These dynamics emerge when benefits of mutualism saturate, whether due to intrinsic or extrinsic density dependence in intraspecific processes, interspecific processes, or both. We distinguish between thresholds resulting from Allee effects, low partner density, and high partner density, and their mathematical and conceptual causes. Our synthesis suggests that there exists a robust population dynamic theory of mutualism that can make general predictions. Theoretical progress on the ecology of mutualistic interactions comparatively lagged behind that of trophic and competitive interactions, leading to the impression that ecologists still lack a generalized framework to investigate the population dynamics of mutualisms. Yet, over the last 90 years, abundant work has accumulated, with qualitatively robust predictions across inspiring systems and levels of mechanistic detail. We review and synthesize this work, finding that mutualisms tend to exhibit stable coexistence at high density and destabilizing thresholds at low density.