Metapopulations with habitat modification

Ecosystem engineering and food web stability

Ecosystem engineering, which involves organism-triggered physical modification of the environment, is a widespread phenomenon. Despite this, the role of engineering in ecological communities remains poorly understood. This study employs a food web model to uncover the key roles of ecosystem engineering in maintaining food webs. While engineers facilitating population growth and suppressing consumers' foraging activity can help maintain complex communities with diverse species, engineering effects that suppress population growth and facilitate consumers' foraging activity can largely destabilize community dynamics. Furthermore, in the middle levels of engineering-related species within a community, an increase in species richness can increase community stability, contrary to classical ecological prediction. The study findings suggest that ecosystem engineering can explain biodiversity persistence in nature, but it depends on the proportion of engineering-related species and how engineering affects organisms.

Temporal variability can promote migration between habitats

Understanding the conditions that promote the evolution of migration is important in ecology and evolution. When environments are fixed and there is one most favorable site, migration to other sites lowers overall growth rate and is not favored. Here we ask, can environmental variability favor migration when there is one best site on average? Previous work suggests that the answer is yes, but a general and precise answer remained elusive. Here we establish new, rigorous inequalities to show (and use simulations to illustrate) how stochastic growth rate can increase with migration when fitness (dis)advantages fluctuate over time across sites. The effect of migration between sites on the overall stochastic growth rate depends on the difference in expected growth rates and the variance of the fluctuating difference in growth rates. When fluctuations (variance) are large, a population can benefit from bursts of higher growth in sites that are worse on average. Such bursts become more probable as the between-site variance increases. Our results apply to many (≥ 2) sites, and reveal an interplay between the length of paths between sites, the average differences in site-specific growth rates, and the size of fluctuations. Our findings have implications for evolutionary biology as they provide conditions for departure from the reduction principle, and for ecological dynamics: even when there are superior sites in a sea of poor habitats, variability and habitat quality across space determine the importance of migration.

Punctuated virus-driven succession generates dynamical alternations in CRISPR-mediated microbe-virus coevolution

The coevolutionary dynamics of lytic viruses and microbes with CRISPR-Cas immunity exhibit alternations between sustained host control of viral proliferation and major viral epidemics in previous computational models. These alternating dynamics have yet to be observed in other host-pathogen systems. Here, we address the breakdown of control and transition to large outbreaks with a stochastic eco-evolutionary model. We establish the role of host density-dependent competition in punctuated virus-driven succession and associated diversity trends that concentrate escape pathways during control phases. Using infection and escape networks, we derive the viral emergence probability whose fluctuations of increasing size and frequency characterize the approach to large outbreaks. We explore alternation probabilities as a function of non-dimensional parameters related to the probability of viral escape and host competition. Our results demonstrate how emergent feedbacks between host competition and viral diversification render the host immune structure fragile, potentiating a dynamical transition to large epidemics.

The unexpected influence of legacy conspecific density dependence

When plants die, neighbours escape competition. Living conspecifics could disproportionately benefit because they are freed from negative intraspecific processes; however, if the negative effects of past conspecific neighbours persist, other species might be advantaged, and diversity might be maintained through legacy effects. We examined legacy effects in a mapped forest by modelling the survival of 37,212 trees of 23 species using four neighbourhood properties: living conspecific, living heterospecific, legacy conspecific (dead conspecifics) and legacy heterospecific densities. Legacy conspecific effects proved nearly four times stronger than living conspecific effects; changes in annual survival associated with legacy conspecific density were 1.5% greater than living conspecific effects. Over 90% of species were negatively impacted by legacy conspecific density, compared to 47% by living conspecific density. Our results emphasize that legacies of trees alter community dynamics, revealing that prior research may have underestimated the strength of density dependent interactions by not considering legacy effects.

Tipping points emerge from weak mutualism in metacommunities

The coexistence of obligate mutualists is often precariously close to tipping points where small environmental changes can drive catastrophic shifts in species composition. For example, microbial ecosystems can collapse by the decline of a strain that provides an essential resource on which other strains cross-feed. Here, we show that tipping points, ecosystem collapse, bistability and hysteresis arise even with very weak (non-obligate) mutualism provided the population is spatially structured. Based on numeric solutions of a metacommunity model and mean-field analyses, we demonstrate that weak mutualism lowers the minimal dispersal rate necessary to avoid stochastic extinction, while species need to overcome a mean threshold density to survive in this low dispersal rate regime. Our results allow us to make numerous predictions for mutualistic metacommunities regarding tipping points, hysteresis effects, and recovery from external perturbations, and let us draw general conclusions for ecosystems even with random, not necessarily mutualistic, interactions and systems with density-dependent dispersal rather than direct mutualistic interactions.

Intransitivity in plant-soil feedbacks is rare but is associated with multispecies coexistence

Although plant-soil feedback (PSF) is being recognized as an important driver of plant recruitment, our understanding of its role in species coexistence in natural communities remains limited by the scarcity of experimental studies on multispecies assemblages. Here, we experimentally estimated PSFs affecting seedling recruitment in 10 co-occurring Mediterranean woody species. We estimated weak but significant species-specific feedback. Pairwise PSFs impose similarly strong fitness differences and stabilizing-destabilizing forces, most often impeding species coexistence. Moreover, a model of community dynamics driven exclusively by PSFs suggests that few species would coexist stably, the largest assemblage with no more than six species. Thus, PSFs alone do not suffice to explain coexistence in the studied community. A topological analysis of all subcommunities in the interaction network shows that full intransitivity (with all species involved in an intransitive loop) would be rare but it would lead to species coexistence through either stable or cyclic dynamics.

On the limits to invasion prediction using coexistence outcomes

The dynamics of ecological communities in nature are typically characterized by probabilistic processes involving invasion dynamics. Because of technical challenges, however, the majority of theoretical and experimental studies have focused on coexistence dynamics. Therefore, it has become central to understand the extent to which coexistence outcomes can be used to predict analogous invasion outcomes relevant to systems in nature. Here, we study the limits to this predictability under a geometric and probabilistic Lotka-Volterra framework. We show that while individual survival probability in coexistence dynamics can be fairly closely translated into invader colonization probability in invasion dynamics, the translation is less precise between community persistence and community augmentation, and worse between exclusion probability and replacement probability. These results provide a guiding and testable theoretical framework regarding the translatability of outcomes between coexistence and invasion outcomes when communities are represented by Lotka-Volterra dynamics under environmental uncertainty.

An immune memory-structured SIS epidemiological model for hyperdiverse pathogens

A hyperdiverse class of pathogens of humans and wildlife, including the malaria parasite Plasmodium falciparum, relies on multigene families to encode antigenic variation. As a result, high (asymptomatic) prevalence is observed despite high immunity in local populations under high-transmission settings. The vast diversity of "strains" and genes encoding this variation challenges the application of established models for the population dynamics of such infectious diseases. Agent-based models have been formulated to address theory on strain coexistence and structure, but their complexity can limit application to gain insights into population dynamics. Motivated by P. falciparum malaria, we develop an alternative formulation in the form of a structured susceptible-infected-susceptible population model in continuous time, where individuals are classified not only by age, as is standard, but also by the diversity of parasites they have been exposed to and retain in their specific immune memory. We analyze the population dynamics and bifurcation structure of this system of partial-differential equations, showing the existence of alternative steady states and an associated tipping point with transmission intensity. We attribute the critical transition to the positive feedback between parasite genetic diversity and force of infection. Basins of attraction show that intervention must drastically reduce diversity to prevent a rebound to high infection levels. Results emphasize the importance of explicitly considering pathogen diversity and associated specific immune memory in the population dynamics of hyperdiverse epidemiological systems. This statement is discussed in a more general context for ecological competition systems with hyperdiverse trait spaces.

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.

Priority Effects Determine How Dispersal Affects Biodiversity in Seasonal Metacommunities

AbstractThe arrival order of species frequently determines the outcome of their interactions. This phenomenon, called the priority effect, is ubiquitous in nature and determines local community structure, but we know surprisingly little about how it influences biodiversity across different spatial scales. Here, we use a seasonal metacommunity model to show that biodiversity patterns and the homogenizing effect of high dispersal depend on the specific mechanisms underlying priority effects. When priority effects are driven only by positive frequency dependence, dispersal-diversity relationships are sensitive to initial conditions but generally show a hump-shaped relationship: biodiversity declines when dispersal rates become high and allow the dominant competitor to exclude other species across patches. When spatiotemporal variation in phenological differences alters species' interaction strengths (trait-dependent priority effects), local, regional, and temporal diversity are surprisingly insensitive to variation in dispersal, regardless of the initial numeric advantage. Thus, trait-dependent priority effects can strongly reduce the effect of dispersal on biodiversity, preventing the homogenization of metacommunities. Our results suggest an alternative mechanism that maintains local and regional diversity without environmental heterogeneity, highlighting that accounting for the mechanisms underlying priority effects is fundamental to understanding patterns of biodiversity.

Habitat Heterogeneity, Environmental Feedbacks, and Species Coexistence across Timescales

AbstractClassic ecological theory explains species coexistence in variable environments. While spatial variation is often treated as an intrinsic feature of a landscape, it may be shaped and even generated by the resident community. All species modify their local environment to some extent, driving changes that can feed back to affect the composition and coexistence of the community, potentially over timescales very different from population dynamics. We introduce a simple nested modeling framework for community dynamics in heterogeneous environments, including the possible evolution of heterogeneity over time due to community-environment feedbacks. We use this model to derive analytical conditions for species coexistence in environments where heterogeneity is either fixed or shaped by feedbacks. Among other results, our approach reveals how dispersal and environmental specialization interact to shape realized patterns of habitat association and demonstrates that environmental feedbacks can tune landscape conditions to allow the stable coexistence of any number of species. Our flexible modeling framework helps explain feedback dynamics that arise in a wide range of ecosystems and offers a generic platform for exploring the interplay between species and landscape diversity.

Eco-evolutionary dynamics in microbial interactions

Microbes play an important role in ecosystem functioning and human health. A key feature of microbial interactions is a feedback system in which they modify the physical environment and react to it. Recently, it has been shown that the ecological consequences of microbial interactions driven by the modification of their surrounding pH environment can be predicted from the effects of their metabolic properties on pH. The optimum environmental pH for a given species can adaptively change in response to the changes in environmental pH that are induced by them. However, the mechanisms underlying the effect of these adaptive changes in pH niche on microbial coexistence are yet to be explored. In this study, I theoretically demonstrate that ecological theory can only accurately predict the qualitative ecological consequences if the growth and pH change rates are the same for each species, which suggests that adaptive pH niche changes can generally make ecological consequence predictions based on ecological theory difficult.

The temporal and spatial dimensions of plant-soil feedbacks

Feedbacks between plants and soil microbes form a keystone to terrestrial community and ecosystem dynamics. Recent advances in dissecting the spatial and temporal dynamics of plant-soil feedbacks (PSFs) have challenged longstanding assumptions of spatially well-mixed microbial communities and exceedingly fast microbial assembly dynamics relative to plant lifespans. Instead, PSFs emerge from interactions that are inherently mismatched in spatial and temporal scales, and explicitly considering these spatial and temporal dynamics is crucial to understanding the contribution of PSFs to foundational ecological patterns. I propose a synthetic spatiotemporal framework for future research that pairs experimental and modeling approaches grounded in mechanism to improve predictability and generalizability of PSFs.

Metapopulation persistence can be inferred from incomplete surveys

Habitat destruction and fragmentation are principal causes of species loss. While a local population might go extinct, a metapopulation-populations inhabiting habitat patches connected by dispersal-can persist regionally by recolonizing empty patches. To assess metapopulation persistence, two widely adopted indicators in conservation management are metapopulation capacity and patch importance. However, we face a fundamental limitation in that assessing metapopulation persistence requires that we survey or sample all the patches in a landscape: often these surveys are logistically challenging to conduct and repeat, which raises the question whether we can learn enough about the metapopulation persistence from an incomplete survey. Here, we provide a robust statistical approach to infer metapopulation capacity and patch importance by sampling a portion of all patches. We provided analytic arguments on why the metapopulation capacity and patch importance can be well predicted from sub-samples of habitat patches. Full-factorial simulations with more complex models corroborate our analytic predictions. We applied our model to an empirical metapopulation of mangrove hummingbirds (Amazilia boucardi). On the basis of our statistical framework, we provide some sampling suggestion for monitoring metapopulation persistence. Our approach allows for rapid and effective inference of metapopulation persistence from incomplete patch surveys.

No robust multispecies coexistence in a canonical model of plant-soil feedbacks

Plant–soil feedbacks (PSFs) are considered a key mechanism generating frequency‐dependent dynamics in plant communities. Negative feedbacks, in particular, are often invoked to explain coexistence and the maintenance of diversity in species‐rich communities. However, the primary modelling framework used to study PSFs considers only two plant species, and we lack clear theoretical expectations for how these complex interactions play out in communities with natural levels of diversity. Here, we extend this canonical model of PSFs to include an arbitrary number of plant species and analyse the dynamics. Surprisingly, we find that coexistence of more than two species is virtually impossible, suggesting that alternative theoretical frameworks are needed to describe feedbacks observed in diverse natural communities. Drawing on our analysis, we discuss future directions for PSF models and implications for experimental study of PSF‐mediated coexistence in the field.

Metapopulations with habitat modification

Across the tree of life, organisms modify their local environment, rendering it more or less hospitable for other species. Despite the ubiquity of these processes, simple models that can be used to develop intuitions about the consequences of widespread habitat modification are lacking. Here, we extend the classic Levins metapopulation model to a setting where each of n species can colonize patches connected by dispersal, and when patches are vacated via local extinction, they retain a "memory" of the previous occupant-modeling habitat modification. While this model can exhibit a wide range of dynamics, we draw several overarching conclusions about the effects of modification and memory. In particular, we find that any number of species may potentially coexist, provided that each is at a disadvantage when colonizing patches vacated by a conspecific. This notion is made precise through a quantitative stability condition, which provides a way to unify and formalize existing conceptual models. We also show that when patch memory facilitates coexistence, it generically induces a positive relationship between diversity and robustness (tolerance of disturbance). Our simple model provides a portable, tractable framework for studying systems where species modify and react to a shared landscape.