A test of balanced fitness limitations theory: Pollen limitation in plants.

When reproductive success is determined by the relative availabilities of a series of essential, non-substitutable resources, the theory of balanced fitness limitations predicts that the cost of harvesting a particular resource shapes the likelihood that a shortfall of that resource will constrain realized fitness. Plant reproduction through female function offers a special opportunity to test this theory; essential resources in this context include, first, the pollen received from pollinators or abiotic vectors that is used to fertilize ovules, and, second, the resources needed to provision the developing seeds and fruit. For many plants realized reproductive success through female function can be readily quantified in the field, and one key potential constraint on fitness, pollen limitation, can be assessed experimentally by manually supplementing pollen receipt. We assembled a comparative dataset of pollen limitation using only studies that supplement pollen to all flowers produced over the plant's reproductive lifespan. Pre- and post-pollination costs were estimated using the weight of flowers and fruits and estimates of fruit set. Consistent with expectations, we find self-incompatible plants make greater pre-pollination investments and experience greater pollen limitation. However, contrary to theoretical expectations, when variation due to self-compatibility is accounted for by including self-compatibility in the statistical model as a covariate, we find no support for the prediction that plants that invest more heavily in pre-pollination costs are subject to greater pollen limitation. Strong within-species, between-population variation in the expression of pollen limitation makes the quantification of mean pollen limitation difficult. We urge plant ecologists to conduct more studies of pollen limitation using whole-plant pollen supplementation to produce a richer comparative dataset that would support a more robust test of the balanced limitations hypothesis.

Granivore abundance shapes mutualism quality in plant-scatterhoarder interactions.

Conditional mutualisms involve costs and benefits that vary with environmental factors, but mechanisms driving these dynamics remain poorly understood. Scatterhoarder-plant interactions are a prime example of this phenomenon, as scatterhoarders can either increase or reduce plant recruitment depending on the balance between seed dispersal and predation. We explored factors that drive the magnitude of net benefits for plants in this interaction using a mathematical model, with parameter values based on European beech (Fagus sylvatica) and yellow-necked mice (Apodemus flavicollis). We measured benefits as the percentage of germinating seeds, and examined how varying rodent survival (reflecting, e.g. changes in predation pressure), the rate of seed loss to other granivores, the abundance of alternative food resources, and changes in masting patterns affect the quality of mutualism. We found that increasing granivore abundance can degrade the quality of plant-scatterhoarder mutualism due to increased cache pilferage. Scatterhoarders are predicted to respond by increasing immediate consumption of gathered seeds, leading to higher costs and reduced benefits for plants. Thus, biotic changes that are detrimental to rodent populations can be beneficial for tree recruitment due to adaptive behavior of rodents. When scatterhoarder populations decline too drastically (< 5 individuals ha-1 ); however, tree recruitment may also suffer.

Eco-evolutionary maintenance of diversity in fluctuating environments.

Growing evidence suggests that temporally fluctuating environments are important in maintaining variation both within and between species. To date, however, studies of genetic variation within a population have been largely conducted by evolutionary biologists (particularly population geneticists), while population and community ecologists have concentrated more on diversity at the species level. Despite considerable conceptual overlap, the commonalities and differences of these two alternative paradigms have yet to come under close scrutiny. Here, we review theoretical and empirical studies in population genetics and community ecology focusing on the 'temporal storage effect' and synthesise theories of diversity maintenance across different levels of biological organisation. Drawing on Chesson's coexistence theory, we explain how temporally fluctuating environments promote the maintenance of genetic variation and species diversity. We propose a further synthesis of the two disciplines by comparing models employing traditional frequency-dependent dynamics and those adopting density-dependent dynamics. We then address how temporal fluctuations promote genetic and species diversity simultaneously via rapid evolution and eco-evolutionary dynamics. Comparing and synthesising ecological and evolutionary approaches will accelerate our understanding of diversity maintenance in nature.

Stage-mediated priority effects and season lengths shape long-term competition dynamics.

The relative arrival time of species can affect their interactions and thus determine which species persist in a community. Although this phenomenon, called priority effect, is widespread in natural communities, it is unclear how it depends on the length of growing season. Using a seasonal stage-structured model, we show that differences in stages of interacting species could generate priority effects by altering the strength of stabilizing and equalizing coexistence mechanisms, changing outcomes between exclusion, coexistence and positive frequency dependence. However, these priority effects are strongest in systems with just one or a few generations per season and diminish in systems where many overlapping generations per season dilute the importance of stage-specific interactions. Our model reveals a novel link between the number of generations in a season and the consequences of priority effects, suggesting that consequences of phenological shifts driven by climate change should depend on specific life histories of organisms.

Building modern coexistence theory from the ground up: The role of community assembly.

Modern coexistence theory (MCT) is one of the leading methods to understand species coexistence. It uses invasion growth rates-the average, per-capita growth rate of a rare species-to identify when and why species coexist. Despite significant advances in dissecting coexistence mechanisms when coexistence occurs, MCT relies on a 'mutual invasibility' condition designed for two-species communities but poorly defined for species-rich communities. Here, we review well-known issues with this component of MCT and propose a solution based on recent mathematical advances. We propose a clear framework for expanding MCT to species-rich communities and for understanding invasion resistance as well as coexistence, especially for communities that could not be analysed with MCT so far. Using two data-driven community models from the literature, we illustrate the utility of our framework and highlight the opportunities for bridging the fields of community assembly and species coexistence.

Coevolution of Patch Selection in Stochastic Environments.

AbstractSpecies interact in landscapes where environmental conditions vary in time and space. This variability impacts how species select habitat patches. Under equilibrium conditions, evolution of this patch selection can result in ideal free distributions where per capita growth rates are zero in occupied patches and negative in unoccupied patches. These ideal free distributions, however, do not explain why species occupy sink patches, why competitors have overlapping spatial ranges, or why predators avoid highly productive patches. To understand these patterns, we solve for coevolutionarily stable strategies (coESSs) of patch selection for multispecies stochastic Lotka-Volterra models accounting for spatial and temporal heterogeneity. In occupied patches at the coESS, we show that the differences between the local contributions to the mean and the variance of the long-term population growth rate are equalized. Applying this characterization to models of antagonistic interactions reveals that environmental stochasticity can partially exorcize the ghost of competition past, select for new forms of enemy-free and victimless space, and generate hydra effects over evolutionary timescales. Viewing our results through the economic lens of modern portfolio theory highlights why the coESS for patch selection is often a bet-hedging strategy coupling stochastic sink populations. Our results highlight how environmental stochasticity can reverse or amplify evolutionary outcomes as a result of species interactions or spatial heterogeneity.

Evolutionary History Mediates Population Response to Rapid Environmental Change through Within-Generational and Transgenerational Plasticity.

AbstractRapid environmental change is affecting many organisms; some are coping well, but many species are in decline. A key mechanism for facilitating success following environmental change is phenotypic plasticity. Organisms use cues to respond phenotypically to environmental conditions; many incorporate recent information (within-generation plasticity) and information from previous generations (transgenerational plasticity). We extend an existing evolutionary model where organisms utilize within-generational plasticity, transgenerational plasticity, and bet hedging to include changes in environmental regime. We show how when rapid evolution of plasticity is not possible, the effect of environmental change (altering the environment mean, variance, or autocorrelation or cue reliability) on population growth rate depends on the population's evolutionary history and past evolutionary responses to historical environmental conditions. We then evaluate the predictions that populations adapted to highly variable environments or with greater within-generational plasticity are more likely to successfully respond to environmental change. We identify when these predictions fail and show that environmental change is most detrimental when previously reliable cues become unreliable. When multiple cues become unreliable, environmental change can cause deleterious effects regardless of the population's evolutionary history. Overall, this work provides a general framework for understanding the role of plasticity in population responses to rapid environmental change.

Does deterministic coexistence theory matter in a finite world?

Contemporary studies of species coexistence are underpinned by deterministic models that assume that competing species have continuous (i.e., noninteger) densities, live in infinitely large landscapes, and coexist over infinite time horizons. By contrast, in nature, species are composed of discrete individuals subject to demographic stochasticity and occur in habitats of finite size where extinctions occur in finite time. One consequence of these discrepancies is that metrics of species' coexistence derived from deterministic theory may be unreliable predictors of the duration of species coexistence in nature. These coexistence metrics include invasion growth rates and niche and fitness differences, which are now commonly applied in theoretical and empirical studies of species coexistence. In this study, we tested the efficacy of deterministic coexistence metrics on the duration of species coexistence in a finite world. We introduce new theoretical and computational methods to estimate coexistence times in stochastic counterparts of classic deterministic models of competition. Importantly, we parameterized this model using experimental field data for 90 pairwise combinations of 18 species of annual plants, allowing us to derive biologically informed estimates of coexistence times for a natural system. Strikingly, we found that for species expected to deterministically coexist, community sizes containing only 10 individuals had predicted coexistence times of more than 1000 years. We also found that invasion growth rates explained 60% of the variation in intrinsic coexistence times, reinforcing their general usefulness in studies of coexistence. However, only by integrating information on both invasion growth rates and species' equilibrium population sizes could most (>99%) of the variation in species coexistence times be explained. This integration was achieved with demographically uncoupled single-species models solely determined by the invasion growth rates and equilibrium population sizes. Moreover, because of a complex relationship between niche overlap/fitness differences and equilibrium population sizes, increasing niche overlap and increasing fitness differences did not always result in decreasing coexistence times, as deterministic theory would predict. Nevertheless, our results tend to support the informed use of deterministic theory for understanding the duration of species' coexistence while highlighting the need to incorporate information on species' equilibrium population sizes in addition to invasion growth rates.

Permanence via invasion graphs: incorporating community assembly into modern coexistence theory.

To understand the mechanisms underlying species coexistence, ecologists often study invasion growth rates of theoretical and data-driven models. These growth rates correspond to average per-capita growth rates of one species with respect to an ergodic measure supporting other species. In the ecological literature, coexistence often is equated with the invasion growth rates being positive. Intuitively, positive invasion growth rates ensure that species recover from being rare. To provide a mathematically rigorous framework for this approach, we prove theorems that answer two questions: (i) When do the signs of the invasion growth rates determine coexistence? (ii) When signs are sufficient, which invasion growth rates need to be positive? We focus on deterministic models and equate coexistence with permanence, i.e., a global attractor bounded away from extinction. For models satisfying certain technical assumptions, we introduce invasion graphs where vertices correspond to proper subsets of species (communities) supporting an ergodic measure and directed edges correspond to potential transitions between communities due to invasions by missing species. These directed edges are determined by the signs of invasion growth rates. When the invasion graph is acyclic (i.e. there is no sequence of invasions starting and ending at the same community), we show that permanence is determined by the signs of the invasion growth rates. In this case, permanence is characterized by the invasibility of all [Formula: see text] communities, i.e., communities without species i where all other missing species have negative invasion growth rates. To illustrate the applicability of the results, we show that dissipative Lotka-Volterra models generically satisfy our technical assumptions and computing their invasion graphs reduces to solving systems of linear equations. We also apply our results to models of competing species with pulsed resources or sharing a predator that exhibits switching behavior. Open problems for both deterministic and stochastic models are discussed. Our results highlight the importance of using concepts about community assembly to study coexistence.

Pathways to the density-dependent expression of cannibalism, and consequences for regulated population dynamics.

Cannibalism, once viewed as a rare or aberrant behavior, is now recognized to be widespread and to contribute broadly to the self-regulation of many populations. Cannibalism can produce endogenous negative feedback on population growth because it is expressed as a conditional behavior, responding to the deteriorating ecological conditions that flow, directly or indirectly, from increasing densities of conspecifics. Thus, cannibalism emerges as a strongly density-dependent source of mortality. In this synthesis, we review recent research that has revealed a rich diversity of pathways through which rising density elicits increased cannibalism, including both factors that (a) elevate the rate of dangerous encounters between conspecifics and (b) enhance the likelihood that such encounters will lead to successful cannibalistic attacks. These pathways include both features of the autecology of cannibal populations and features of interactions with other species, including food resources and pathogens. Using mathematical models, we explore the consequences of including density-dependent cannibal attack rates on population dynamics. The conditional expression of cannibalism generally enhances stability and population regulation in single-species models but also may increase opportunities for alternative states and prey population escape from control by cannibalistic predators.

Temporally auto-correlated predator attacks structure ecological communities.

For species primarily regulated by a common predator, the P* rule of Holt & Lawton (Holt & Lawton, 1993. Am. Nat.142, 623-645. (doi:10.1086/285561)) predicts that the prey species that supports the highest mean predator density (P*) excludes the other prey species. This prediction is re-examined in the presence of temporal fluctuations in the vital rates of the interacting species including predator attack rates. When the fluctuations in predator attack rates are temporally uncorrelated, the P* rule still holds even when the other vital rates are temporally auto-correlated. However, when temporal auto-correlations in attack rates are positive but not too strong, the prey species can coexist due to the emergence of a positive covariance between predator density and prey vulnerability. This coexistence mechanism is similar to the storage effect for species regulated by a common resource. Negative or strongly positive auto-correlations in attack rates generate a negative covariance between predator density and prey vulnerability and a stochastic priority effect can emerge: with non-zero probability either prey species is excluded. These results highlight how temporally auto-correlated species' interaction rates impact the structure and dynamics of ecological communities.

Mast seeding promotes evolution of scatter-hoarding.

Many plant species worldwide are dispersed by scatter-hoarding granivores: animals that hide seeds in numerous, small caches for future consumption. Yet, the evolution of scatter-hoarding is difficult to explain because undefended caches are at high risk of pilferage. Previous models have attempted to solve this problem by giving cache owners large advantages in cache recovery, by kin selection, or by introducing reciprocal pilferage of 'shared' seed resources. However, the role of environmental variability has been so far overlooked in this context. One important form of such variability is masting, which is displayed by many plant species dispersed by scatterhoarders. We use a mathematical model to investigate the influence of masting on the evolution of scatter-hoarding. The model accounts for periodically varying annual seed fall, caching and pilfering behaviour, and the demography of scatterhoarders. The parameter values are based mostly on research on European beech (Fagus sylvatica) and yellow-necked mice (Apodemus flavicollis). Starvation of scatterhoarders between mast years decreases the population density that enters masting events, which leads to reduced seed pilferage. Satiation of scatterhoarders during mast events lowers the reproductive cost of caching (i.e. the cost of caching for the future rather than using seeds for current reproduction). These reductions promote the evolution of scatter-hoarding behaviour especially when interannual variation in seed fall and the period between masting events are large. This article is part of the theme issue 'The ecology and evolution of synchronized seed production in plants'.

Sick of eating: Eco-evo-immuno dynamics of predators and their trophically acquired parasites.

When predators consume prey, they risk becoming infected with their prey's parasites, which can then establish the predator as a secondary host. A predator population's diet therefore influences what parasites it is exposed to, as has been repeatedly shown in many species such as threespine stickleback (Gasterosteus aculeatus) (more benthic-feeding individuals obtain nematodes from oligocheate prey, whereas limnetic-feeding individuals catch cestodes from copepod prey). These differing parasite encounters, in turn, determine how natural selection acts on the predator's immune system. We might therefore expect that ecoevolutionary dynamics of a predator's diet (as determined by its ecomorphology) should drive correlated evolution of its immune traits. Conversely, the predator's immunity to certain parasites might alter the relative costs and benefits of different prey, driving evolution of its ecomorphology. To evaluate the potential for ecological morphology to drive evolution of immunity, and vice versa, we use a quantitative genetics framework coupled with an ecological model of a predator and two prey species (the diet options). Our analysis reveals fundamental asymmetries in the evolution of ecomorphology and immunity. When ecomorphology rapidly evolves, it determines how immunity evolves, but not vice versa. Weak trade-offs in ecological morphology select for diet generalists despite strong immunological trade-offs, but not vice versa. Only weak immunological trade-offs can explain negative diet-infection correlations across populations. The analysis also reveals that eco-evo-immuno feedbacks destabilize population dynamics when trade-offs are sufficiently weak and heritability is sufficiently high. Collectively, these results highlight the delicate interplay between multivariate trait evolution and the dynamics of ecological communities.

Is Evolution in Response to Extreme Events Good for Population Persistence?

AbstractClimate change is predicted to increase the severity of environmental perturbations, including storms and droughts, which act as strong selective agents. These extreme events are often of finite duration (pulse disturbances). Hence, while evolution during an extreme event may be adaptive, the resulting phenotypic changes may become maladaptive when the event ends. Using individual-based models and analytic approximations that fuse quantitative genetics and demography, we explore how heritability and phenotypic variance affect population size and extinction risk in finite populations under an extreme event of fixed duration. Since more evolution leads to greater maladaptation and slower population recovery following an extreme event, greater heritability can increase extinction risk when the extreme event is short. Alternatively, when an extreme event is sufficiently long, heritability often helps a population persist. We also find that when events are severe, the buffering effect of phenotypic variance can outweigh the increased load it causes.

Effects of size selection versus density dependence on life histories: A first experimental probe.

When prey experience size-based harvesting by predators, they are not only subject to selection due to larger individuals being preferentially harvested but also selection due to reductions in population density. Density-dependent selection represents one of the most basic interactions between ecology and evolution. Yet, the reduction in density associated with exploitation has not been tested as a possible driving force of observed evolutionary changes in populations harvested size-dependently. Using an artificial selection experiment with a mixture of Daphnia clones, we partition the evolutionary effects of size-based harvesting into the effects of removing large individuals and the effects of lowering the population density. We show that both size selection and density-dependent selection are significant drivers of life-history evolution. Importantly, these drivers affected different life-history traits with size-selective harvesting selecting for slower juvenile growth rates and a larger size at maturity, and low-density selecting for reduced reproductive output.

Positively and Negatively Autocorrelated Environmental Fluctuations Have Opposing Effects on Species Coexistence.

AbstractEnvironmental fluctuations can mediate coexistence between competing species via the storage effect. This fluctuation-dependent coexistence mechanism requires three conditions: (i) there is a positive covariance between species responses to environmental conditions and the strength of competition, (ii) there are species-specific environmental responses, and (iii) species are less sensitive to competition in environmentally unfavorable years. In serially uncorrelated environments, condition (i) occurs only if favorable environmental conditions immediately and directly increase the strength of competition. For many demographic parameters, this direct link between favorable years and competition may not exist. Moreover, many environmental variables are temporal autocorrelated, but theory has largely focused on serially uncorrelated environments. To address this gap, a model of competing species in autocorrelated environments is analyzed. This analysis shows that positive autocorrelations in demographic rates that increase fitness (e.g., maximal fecundity or adult survival) produce the positive environment-competition covariance in condition (i). Hence, when these demographic rates contribute to buffered population growth, positive temporal autocorrelations generate a storage effect; otherwise, they destabilize competitive interactions. For negatively autocorrelated environments, this theory highlights an alternative stabilizing mechanism that requires three conditions: (i') there is a negative environment-competition covariance, (ii) there are species-specific environmental responses, and (iii') species are less sensitive to competition in more favorable years. When the conditions for either of these stabilizing mechanisms are violated, temporal autocorrelations can generate stochastic priority effects or hasten competitive exclusion. Collectively, these results highlight that temporal autocorrelations in environmental conditions can play a fundamental role in determining ecological outcomes of competing species.

Cross-scale dynamics and the evolutionary emergence of infectious diseases.

When emerging pathogens encounter new host species for which they are poorly adapted, they must evolve to escape extinction. Pathogens experience selection on traits at multiple scales, including replication rates within host individuals and transmissibility between hosts. We analyze a stochastic model linking pathogen growth and competition within individuals to transmission between individuals. Our analysis reveals a new factor, the cross-scale reproductive number of a mutant virion, that quantifies how quickly mutant strains increase in frequency when they initially appear in the infected host population. This cross-scale reproductive number combines with viral mutation rates, single-strain reproductive numbers, and transmission bottleneck width to determine the likelihood of evolutionary emergence, and whether evolution occurs swiftly or gradually within chains of transmission. We find that wider transmission bottlenecks facilitate emergence of pathogens with short-term infections, but hinder emergence of pathogens exhibiting cross-scale selective conflict and long-term infections. Our results provide a framework to advance the integration of laboratory, clinical, and field data in the context of evolutionary theory, laying the foundation for a new generation of evidence-based risk assessment of emergence threats.

Technical Comment on Pande et al. (2020): Why invasion analysis is important for understanding coexistence.

Pande et al. (2020) point out that persistence time can decrease even as invader growth rates (IGRs) increase, which potentially undermines modern coexistence theory. However, because persistence time increases rapidly with system size only when IGR > 0, to understand how any real community persists, we should first identify the mechanisms producing positive IGR.

Individual variation in dispersal and fecundity increases rates of spatial spread.

Dispersal and fecundity are two fundamental traits underlying the spread of populations. Using integral difference equation models, we examine how individual variation in these fundamental traits and the heritability of these traits influence rates of spatial spread of populations along a one-dimensional transect. Using a mixture of analytic and numerical methods, we show that individual variation in dispersal rates increases spread rates and the more heritable this variation, the greater the increase. In contrast, individual variation in lifetime fecundity only increases spread rates when some of this variation is heritable. The highest increases in spread rates occur when variation in dispersal positively co-varies with fecundity. Our results highlight the importance of estimating individual variation in dispersal rates, dispersal syndromes in which fecundity and dispersal co-vary positively and heritability of these traits to predict population rates of spatial spread.

Multiple Attractors and Long Transients in Spatially Structured Populations with an Allee Effect.

We present a discrete-time model of a spatially structured population and explore the effects of coupling when the local dynamics contain a strong Allee effect and overcompensation. While an isolated population can exhibit only bistability and essential extinction, a spatially structured population can exhibit numerous coexisting attractors. We identify mechanisms and parameter ranges that can protect the spatially structured population from essential extinction, whereas it is inevitable in the local system. In the case of weak coupling, a state where one subpopulation density lies above and the other one below the Allee threshold can prevent essential extinction. Strong coupling, on the other hand, enables both populations to persist above the Allee threshold when dynamics are (approximately) out of phase. In both cases, attractors have fractal basin boundaries. Outside of these parameter ranges, dispersal was not found to prevent essential extinction. We also demonstrate how spatial structure can lead to long transients of persistence before the population goes extinct.