Theoretical Ecology

Squid abundance has been reported to increase globally between 1970 and 2010. This increase has been hypothesized to result from two primary factors: the loss of top predators due to overfishing and rising ocean temperatures. The decline in apex predators may lead to the expansion of squid populations either through reduced predation pressure or diminished competition with juvenile predators. Concurrently, increased temperatures could enhance the somatic growth rates of squid, thereby accelerating their population growth. However, empirically disentangling the impacts of predator loss and temperature on squid biomass remains challenging, especially in a food-web context. In this study, we used a size- and trait-based model of upper trophic levels that resolves the ecosystem structure -- biomass and trophic interactions of fish and squid -- for varying depth, temperature, and secondary production, to investigate two hypotheses of the historical expansion of squid, i.e., the effects of predator depletion from fishing and rising temperatures on squid biomass. Our model reveals that intensified fishing of squid predators -- specifically large demersal fish in shelf systems and large pelagic fish in open oceans -- leads to a slight increase in squid biomass. Conversely, elevated temperatures are associated with a decline in squid biomass. This temperature-driven reduction in biomass is attributed to an increased metabolism of squids beyond the available food supply. If historic overfishing on large marine predators continues to be curtailed, we expect a corresponding reduction in global squid biomass and fisheries potential, which could be further exacerbated by rising temperatures.

Spatial population structure and seasonality are both central to the spread of many infectious diseases of plants, animals and humans. While seasonal forcing in transmission often plays an important role in epidemiological models of a wide range of infectious disease, and we now have some theoretical understanding of the dynamical impacts of spatial structure, the combined effects of these two ubiquitous processes has not been examined in detail. Here, we develop a novel model to explore the combined influence of spatial structure and temporal variability on disease dynamics. Spatial structure is represented using a lattice-based approach with near-neighbour interactions, while temporal variability is included through regular, seasonal, variation of the transmission rate. We use bifurcation analysis of a pair approximation of the full spatial model to identify the parameter regimes associated with qualitatively distinct dynamical behaviours. The model exhibits a remarkably wide range of complex dynamics, including limit cycles, quasi-periodic cycles, multi-year cycles, chaotic dynamics and bistability between these different states. In particular, complex dynamics occur when reproduction is predominantly local, with the dynamics depending critically on the amplitude of the seasonal transmission rate. We show how high transmission rates, high birth rates and in particular low recovery rates are requirements for complex dynamics. We predict that SI-type disease interactions in plant pathogen systems will show complex dynamics even with relatively global transmission dynamics.

Despite the impacts of within-host disease dynamics on disease outcomes in individual hosts and disease spread among-hosts, generic models of within-host population dynamics have received far less attention than their among-host counterparts. While a number of models have been proposed to explore theoretical eco-evolutionary dynamics, they have yet to be evaluated for estimability, raising questions about their ability to provide reliable inference when confronted with data. We evaluated the estimability of two generic within-host population dynamics models by assessing: (1) parameter estimation, our ability to recover correct values of model parameters from data, (2) the consequences of mis-assigning the underlying mechanistic model on parameter estimation, and (3) the reproduction of qualitative dynamics, or, our ability to use parameter estimates to reproduce observed dynamical behaviours. In some cases, fitting a mis-matched mechanistic model to time series data produced reasonable parameter estimates that were able to reproduce system dynamics, and that when provided the data-generating model, parameter uncertainty can produce substantial behavioural uncertainty. Our findings highlight the impacts of structural, parametric, and behavioural uncertainty on inference, and demonstrate the value of improving system-specific knowledge to prevent the use of incorrect functional forms and of measuring consequential parameters to improve estimability.

Investigating the factors that stabilize biological communities is a central topic in ecology. Response diversity, defined as variation in species responses to environmental change, has been proposed as a key mechanism underlying the biodiversity-ecosystem functional stability (BEFS) relationship, whereby greater species diversity enhances ecological stability. Previous studies have shown that response diversity promotes ecological stability by generating asynchronous population fluctuations and the resulting compensatory dynamics. Although several metrics have been proposed to quantify response diversity, they do not explicitly consider the presence of insensitive species whose performance is unaffected by current environmental conditions. To examine how insensitive species influence response diversity, species persistence, and ecological stability, we conducted numerical simulations of a generalized Lotka-Volterra model under environmental forcing. We first confirmed that increasing variation among sensitive species increased the response diversity index and stabilized community dynamics. We then examined a scenario in which response diversity depended solely on the proportion of sensitive and insensitive species, assuming that all sensitive species responded identically to environmental change. Under this assumption, the response diversity index was maximized when sensitive and insensitive species occurred in equal proportions, whereas increasing the number of sensitive species monotonically destabilized community dynamics. Consequently, the relationship between response diversity and community stability depended on how response diversity was generated, such that higher response diversity could even be associated with lower community stability. These findings demonstrate that overlooking environmentally insensitive species can obscure the mechanisms linking response diversity and ecological stability. More broadly, our results reveal that response diversity comprises at least two distinct biological components--species sensitivity and response variation among sensitive species--that can have contrasting consequences for community stability. We therefore highlight the need to quantify sensitive species empirically and to develop response diversity metrics that distinguish these components. Author SummaryUnderstanding why some communities remain stable despite environmental change is a longstanding goal in ecology. Response diversity, which refers to differences in how species respond to environmental change, has been proposed as a key mechanism explaining why greater biodiversity (species richness) can promote ecological stability. Because species respond differently to changing environments, declines in some species can be compensated by increases in others, helping to stabilize community dynamics. However, previous studies have rarely considered species that are insensitive to current environmental changes. Using a mathematical model, we show that response diversity can arise from two distinct biological components--the number of sensitive species and variation in their responses--and that these components can have contrasting effects on ecological stability. When response diversity reflects variation among sensitive species, greater response diversity stabilizes community dynamics, as expected. In contrast, when response diversity changes only because of the proportions of sensitive and insensitive species, higher response diversity can be associated with lower community stability. Our findings highlight the importance of quantifying the number of sensitive species and developing response diversity metrics that distinguish species sensitivity from variation in responses among sensitive species.

After introduction, many non-native marine species are dispersed planktonically. Secondary spread within the non-native range has been shown to prevent the establishment of the introduced species if the advection of larvae prevents sufficient return of larvae to maintain the population in the face of competition with native species. However, those studies have largely neglected the effects of spatial variation in alongshore larval transport. We examine the introduction of a novel species with planktonic dispersal into a more realistic coastal environment which includes spatial variation in larval transport estimated from the Mercator Ocean 1/12th degree global circulation model. The introduction may either be from a distant habitat, or through range expansion. We find that there are locations in the global coastal ocean where introduced species are more likely to persist because of spatial variation of coastal currents. These include regions where alongshore larval transport diverges, such as estuaries. The location where a non-native species is introduced may not be where it flourishes - it cannot be assumed that the region where invading species are first noticed to be abundant is the region where it was introduced. We extend closed-population theory to open coastal systems to estimate persistence as a function of local circulation, habitat extent, and the competitive advantage of the introduced species. Software is provided which allows the estimations of regions where introduced species are more likely to persist and flourish as a function of larval depth behavior, planktonic duration and release timing.

For organisms with biparental care, successful reproduction hinges on coordination between partners. Seabirds face an extreme coordination challenge because parents must schedule nest attendance on land with long-distance foraging trips at sea. We present a computational model of incubation schedules for a vulnerable seabird, the Leachs Storm-Petrel (Hydrobates leucorhous). Using only simple energetic rules and parameters, the model recapitulates natural incubation rhythms, exposes a tradeoff between parent energy and egg attendance, and predicts severe reproductive failure in harsh environments. Incubation primarily fails through "schedule breakdown" -- a single point in the season when both parents spend too long foraging and the egg dies from cold. The resilience of the developing offspring to neglect is thus a fundamental adaptation to the uncertainties of biparental care. These results raise new alarms about the indirect causes of reproductive failure in sensitive marine species and provide theoretical foundations for the evolutionary ecology of scheduling behaviors.

O_LISeasonal forcing is a dominant factor shaping host-pathogen interactions and disease dynamics across many wildlife systems, including species impacted by environmentally transmitted parasites. How seasonality in parasite dynamics translates to the host when the infection and disease impacts operate at different timescales, however, remains poorly understood. C_LIO_LIWe investigate how seasonality shapes sarcoptic mange in bare-nosed wombats, Vombatus ursinus, a disease caused by the environmentally transmitted parasitic mite Sarcoptes scabiei, causing a protracted clinical time-course in the host. Using an empirically informed state-based deterministic model we explore how wombat population trajectories are influenced by (i) seasonal constraints to mite survival and (ii) in context of host-pathogen encounter rates, as measured by the ratio of burrows to wombats. C_LIO_LIWe demonstrate three long-term outcomes of wombat-mange: host and parasite extinction, endemic disease, and disease-free. We find seasonal environments narrow the range of host-pathogen encounter rates that support S. scabiei persistence relative to stable environments, and prevalence and population sizes vary more in seasonal compared to stable environments except under moderate host-pathogen encounter rates when seasonal effects are less apparent. We also find that a protracted infectious period is essential for host-parasite coexistence in the wombat-mange system. C_LIO_LIOur seasonal model results are consistent with field observations, such that mange prevalence in natural populations increases during seasons of longer off-host mite survival. Application of these findings suggest management efforts could reduce host population impacts through disease management in seasons with longer off-host parasite survival or reduce the environmental reservoir through disease management in seasons with shorter off-host survival. C_LIO_LIWe provide novel, mechanistic explanations for distinctive population trajectories that arise from a seasonally forced wildlife disease, including climate factors that operate independently on parasites, host demography, and disparate timescales over which seasonality affects parasites and hosts. Broadly, linking seasonality to long-term population dynamics can improve the predictability and management of wildlife diseases, but requires an understanding of how local intrinsic factors interact with seasonal pressures over time. C_LI

As ecosystems face a growing number of threats, coextinctions (resultant extinctions following a primary extinction) are expected to proliferate. However, less is known about the conditions under which coextinctions could outpace primary extinctions. Because coextinctions often occur through lost species interactions, we posit that aspects of food web structure and complexity can help predict differences in vulnerability to coextinction across ecosystems. To test this, we leverage Bayesian network models to assess the extent to which variation in ecosystem vulnerability to coextinction varies with food web structure. We find that food webs with high maximum trophic level are most vulnerable to coextinction, and that maximum trophic level is a better predictor than other aspects of food web structure, such as species richness or trophic connectance. Extending this approach, we also find that maximum trophic level uncovers the relative vulnerability of ecosystem services to species coextinction across 12 empirical food webs.

Plants competing belowground may produce extra roots, fewer roots, or no detectable change compared to plants growing alone. This inconsistency is often attributed to plants altering their root allocation in response to diverse cues, including neighbor detection and resource depletion by neighbors, but isolating these cues experimentally is challenging. Here, we hypothesize that water depletion alone can generate the range of root allocation strategies reported in the literature. We present this hypothesis as a water-explicit optimization model of root allocation that predicts a non-monotonic response. The model identified a critical depletion rate at which allocation shifted from increasing to decreasing with depletion. We tested this prediction using artificially rooted pots that imposed controlled water depletion while excluding living neighbors and their cues. A continuous artificial depletion gradient revealed the predicted hump-shaped pattern. These results reframe root overproliferation and underproliferation as positions along a single depletion-response curve.

The shape of density-dependence governs species persistence, and ecosystem stability. Yet, whether per-capita growth declines sublinearily, or superlinearily with density remains hotly debated. Growth rates across the tree of life have been shown to decline sublinearly with density, whereas theory founded on resource competition predicts the opposite. Here, we resolve this discrepancy and show that sublinearity can readily emerge from geometric constraints on consumer interactions. By linking inter individual spacing, movement and interference rates, we derive two limiting-interference regimes, one of which the well-mixed limit recovers the form of classic Beddington DeAngelis interference response. We then developed an individual-based model from first principles which reproduces the derived sublinearity response, and further use empirical data from published consumer-resource experiments that also bears the signature of sublinear density-dependence. Further, embedding the interference mechanisms underlying the emergence of sublinear density-dependence in coexistence theory opens a new regime for species coexistence where classical theory fails to predict. Our framework indicates that non-consumptive interactions are not merely a correction to resource competition but might be a distinct axis along which diverse communities may potentially coexist.

Auxins are a family of plant hormones involved in various processes across plant tissues and species. The Nuclear Auxin Pathway (NAP) consists of interacting transcription factors (ARFs) and repressors (Aux/IAAs), which govern an individual cells response to changes in auxin concentration. These components are present in all land plants, and many species possess multiple copies of each signalling component. We present a general framework for ODE-based models of NAP submodules with the flexibility to model the promotion and repression of target genes by any combination of transcriptional regulators. We analyse published data and show that auxin treatment in Arabidopsis thaliana roots triggers a range of characteristically distinct temporal response profiles--for both target genes and the signalling components themselves. Using our modelling framework, we recapitulate aspects of this behaviour by presenting examples of real and theoretical NAP subnetworks, and by analysing the effect that these network dynamics have on auxin-mediated transcriptional responses. This work demonstrates the utility of our modelling framework as a general-purpose tool for understanding the function of certain protein-protein and protein-DNA interactions through their effects on the NAP. This exploration of the rich dynamics of more complex signalling pathways promises to advance our understanding of the NAP.

The study of tissue dynamics has been stimulated during the last decades thanks to the use of quantitative descriptions, with the development of several theoretical and computational frameworks, many of them revolving around the notion of reaction-diffusion systems, eventually with additional structure variables beyond time and space. The use of structure variables can accommodate phenotypic traits. In this work, we study a family of competition models, where a given population depends on a resource (e.g. oxygen) and several populations are competing for it. Our quantitative description incorporates phenotypic traits and heterogeneity at the level of cell cycle variations, which influence replication rates via oxygen consumption. This enables us to replicate the fitness of specific subpopulations to environmental conditions (e.g. oxygen shortage or external influences). Using numerical simulations, we show that such models display dynamical pattern formation in the form of coupled travelling wave profiles that expand or retreat at the same wave speed. The full theoretical analysis of such dynamics is quite involved; to circumvent this difficulty, we introduce a quasi-stationary approximation for the resource dynamics. We find that this approximation can reproduce the overall behaviour very accurately, with the additional benefit of allowing theoretical treatment of the reduced model. In this way, we provide estimates on the wave speed which are numerically shown to be robust across a wide range of macroscopic parameters of the full model. The wave speeds are thus found to depend strongly on the proliferation rate of the fittest population, resembling a winner-takes-all dynamics.

Biodiversity frequently peaks in fluctuating micro-oxic environments such as marine oxygen minimum zone interfaces, rhizospheric aggregates, sediments, microbial mats, and gut mucus layers. Yet, classical ecological theories do not adequately explain why intermediate oxygen tensions repeatedly favor coexistence and diversification. Herein, we propose a murburn ecological formalism wherein oxygen acts not merely as a metabolic substrate but as a generator of dynamic redox heterogeneity through partial reduction and diffusible reactive species (DRS) and redox-intermediates formation. Integrating empirical observations from marine, gut, soil, and aquatic-interface ecosystems with a reaction-diffusion framework, we show that intermediate oxygen tensions naturally maximize radical-field heterogeneity and produce dynamically shifting fitness landscapes. Numerical simulations demonstrate spontaneous coexistence, biodiversity maxima within micro-oxic zones, localized diversification, and coexistence stabilization without externally imposed niche partitioning. Additional simulations suggest that aquatic macrofauna indirectly enhance biodiversity by restructuring oxygen gradients and generating ecosystem-scale diffusional redox architectures (ESDRA). The framework proposes that fluctuating redox interfaces function as potential ecological zones of elevated adaptive turnover across biological scales.

The black-legged tick (Ixodes scapularis), a key vector of Lyme disease, anaplasmosis, and babesiosis, exhibits regionally distinct patterns of seasonal activity driven by climate. Consequently, the relative timing of larval and nymphal activity varies across geographic locations, influencing pathogen transmission dynamics. Early-emerging nymphs may increase pathogen transmission, whereas early-emerging larvae may reduce transmission. In addition, synchrony between the two life-stages facilitates co-feeding transmission, which contributes to pathogen maintenance and coinfection risk. Temperature is thought to be an important driver of tick phenology, but existing mechanistic models that incorporate temperature fail to accurately capture the timing of larval and nymphal tick activity. To address this limitation, we developed a mechanistic model that includes two additional factors: humidity-dependent questing and low rates of overwinter development. To assess the value of these factors for explaining real-world patterns, we fitted alternative models to tick collection data from the National Ecological Observatory Network. In doing so, we found that explicitly incorporating humidity is necessary to reproduce observed tick phenology, with larval ticks being especially sensitive to relative humidity compared to other life stages. In addition, we found that accounting for humidity had a larger effect at Mid-Atlantic sites than at Northeastern sites, underscoring the importance of region-specific interactions between temperature and humidity in shaping I. scapularis phenology. By more accurately capturing tick seasonality compared to existing mechanistic models, our model illustrates the importance of accounting for factors beyond temperature for investigating how climate variability influences seasonal tick activity and pathogen transmission.

Focal adhesions maintain force-bearing attachment between cells and the extracellular matrix but can also undergo dynamic remodeling. Their assembly and actomyosin tension are coupled through mechanochemical feedback. The processes underlying this feedback are not instantaneous and therefore involve a time delay. However, how this delayed feedback gives rise to stable adhesion maintenance or dynamic remodeling remains unclear. Here, paired time-lapse measurements of vinculin fluorescence and traction stress revealed distinct local adhesion-force dynamics, including low-fluctuation and recurrent fluctuation patterns. To examine how these patterns could arise, we formulated a minimal mechanochemical model coupling focal adhesion assembly and actomyosin force through delayed reciprocal feedback. The model exhibited stable and oscillatory modes depending on feedback strength, the balance of opposing feedback effects, and the effective feedback delay. Bistability and hysteretic switching also occurred in a subset of parameter space, and the oscillation period followed a power-law relation with the delay. These results suggest that stable adhesion maintenance and dynamic remodeling can emerge from a common mechanochemical feedback architecture.

As anthropogenic threats have intensified over the past 500 years, we find ourselves in the midst of a sixth mass extinction, with continued losses of biodiversity threatening ecosystem stability. This biodiversity loss has caused species extinctions across taxa, and placed several others at high risk of functional extinction. These disturbance-driven impacts represent one of the most acute biodiversity crises facing global marine systems. Species exhibiting slow life histories characteristically have low resilience to disturbance. Here, we assess the risk of functional extinction and identify policy pathways for population recovery of the slow-living, Critically Endangered elasmobranch, the spinetail devil ray (Mobula mobular). We develop a stochastic, state-structured Integral Projection Model (IPM) parameterised with demographic data collected from fishery landings data in India, the world's largest mobulid fishery, and supplemented with data on vital rates from published literature. Using the IPM, we estimate that the population is declining at approximately 12% annually, experiencing substantial limiting pressure from fisheries overexploitation and failing to approach its biological maximum growth potential. Our results indicate that populations of M. mobular will be at high risk of functional extinction if 'business as usual' harvest scenario persists for another decade. We further show that long-term population recovery is only possible if survival increases significantly across all size classes, especially among large reproductive females, alongside a concurrent increase in fecundity. We conclude that no single policy measure is sufficient to recover population of M. mobular along the southeastern coast of India. Instead, combined protection through maximum bycatch mitigation and protection of nursery areas in no-take zones will be required for population recovery. This research demonstrates that recovery of overexploited populations often requires integrated resource management across life stages, and that the Critically Endangered M. mobular warrants urgent conservation action to avoid functional extinction.

Microbial populations generally evolve in fluctuating environments under time-varying conditions. These are often described by binary switching models, sometimes seen as coarse-grained feast-famine cycles, in which resource availability switches abruptly between abundant and scarce conditions. However, experimental studies suggest that feast-famine environments actually exhibit more complex temporal dynamics. Here, we study how two strains, one growing slightly slower than the other, compete for the same resources in fluctuating environments comprising a finite number of intermediate states, each having its own carrying capacity. Environmental switching between these states and their carrying capacities represents gradual changes in nutrient availability. This class of multi-state stochastic switching models can be interpreted as a coarse-grained description of feast-famine cycles and allows us to investigate strain competition under the gradual recovery and depletion of resources. By computational and analytical means, we characterise the population dynamics in these multi-state fluctuating environments. In particular, we study how the switching rates and distribution of carrying capacities affect the population-size statistics, fixation probability, and mean fixation time. By comparing these results with their counterparts in binary environments, we clarify how the frequency and amplitude of environmental fluctuations influence population dynamics in coarse-grained feast-famine cycles.

Resource fluctuations can facilitate microbial coexistence when species are sufficiently differentiated in their resource uptake strategies. However, past emphasis on the binary classification of species into equilibrium versus non-equilibrium resource specialists has obscured the potential range of temporal niches available to competitors. Here, we investigate whether microbes that switch between respiratory and fermentative metabolism can coexist with specialist competitors under fluctuations in a single resource. Based on simulations of consumer-resource models, we show that metabolic switching generates distinct growth responses to resource availability, allowing metabolically flexible organisms to exploit temporal variation in ways that differ from specialist strategies. As a result, metabolic switchers can coexist with both respiratory and fermentative specialists under intermediate regimes of resource fluctuation. The competitive ability of metabolic switchers is enhanced when transitions between metabolic states are faster and more responsive to changes in resource availability. Rather than constituting physiological constraints, our results suggest that the metabolic flexibility afforded by overflow metabolism may enable organisms to better exploit fluctuating resources environments.

Cross-feeding mutualisms, in which partner species exchange essential metabolites, are ubiquitous in microbial communities. In spatially structured environments, motility can improve access to partner-produced resources but also impose metabolic costs and displace cells from nutrient-rich regions, so its net benefit depends on the spatial dynamics of the interaction. Here, we combine competition experiments in a cross-feeding mutualism between Escherichia coli and Salmonella enterica with a spatially explicit consumer-resource model to determine what drives selection on motility. Spatial structure imposes asymmetric selection between partners i.e. S. enterica benefits from motility regardless of partner motility, whereas selection on E. coli switches from favourable to unfavourable depending on whether its partner can move. Competition in well-mixed culture suggests that this reversal reflects the loss of a spatial benefit rather than an increased cost. Our model attributes the asymmetry to three interacting factors: the ratio of metabolite production to consumption which sets whether the cross-fed resource is scarce or abundant; the number of growth-limiting resources which determines whether an alternative gradient can rescue the benefit of motility; and partner motility and growth rate, which shape where metabolites are produced. When a metabolite is scarce, motile cells gain by dispersing into regions it has reached but not yet been depleted from. When it accumulates, this gradient is eroded, and the motility costs offset any benefit it provides. Selection on motility therefore depends on the metabolic structure of the interaction and the spatial behaviour of partners.

Population dynamics and their component vital rates may be driven by weather, climate teleconnections between sea and air (e.g. ENSO), or biotic interactions. These drivers operate directly or indirectly and on different temporal scales. We used a Bayesian structural equation model to characterize effects among weather, climate, and incidental intraguild predation (IGP) on the butterfly Euphydryas gillettii's vital rate of pre-diapause survival, using an 18 year dataset. IGP was a major determinant of pre-diapause survival, along with direct and indirect effects of weather and spring climate teleconnections. The direction of climate effects was reversed when mediated through IGP. Our analysis illustrates the need for sequential hypotheses to capture the cascading effects of abiotic factors via biotic interactions. Using sequential hypotheses addresses the debate on weather -- climate teleconnection roles by disentangling their contributions from one another. Finally, vital rates must be decomposed to component rates in order to detect their drivers.