Theoretical Ecology

Jarvis-Cross, Madeline; Krkošek, Martin

doi: 10.1007/s12080-026-00634-1pmid: N/A

Gibbs, Theo L.; Dahlin, Kyle J.-M.; Brennan, Joe; Silveira, Cynthia B.; McManus, Lisa C.

doi: 10.1007/s12080-026-00637-ypmid: N/A

Many macroscopic organisms enter tightly linked symbioses with microbial communities. Although experimental work has demonstrated the importance of these symbioses, a theoretical understanding of stable, multi-scale coexistence remains underdeveloped. Here, we explored how the competition-colonization tradeoff, a classic coexistence mechanism, operates when bacterial species compete for a dynamic biological host. Specifically, we introduce a model where corals are colonized by fast-growing mutualists and slow-growing pathogens. Vital rates of the host coral influenced coexistence outcomes between bacterial types. Notably, pathogen-induced host death expanded the region of parameter space where coexistence was stable for all three species, and mutualistic bacteria enabled coexistence in systems that would have otherwise collapsed. In an explicitly spatial model, dispersal limitation favored the mutualist over the pathogen when the mutualist increased the host colonization rate. These findings provide new insights into the interplay between microbial interactions and macroscopic processes. Our work illustrates how host-microbe interactions can shape ecosystem stability, providing a theoretical framework applicable to a wide range of symbiotic systems.

Nobre, Davi Arrais; Abbott, Karen C.; Machta, Jonathan; Hastings, Alan

doi: 10.1007/s12080-025-00633-8pmid: N/A

Synchronous oscillations of spatially disjunct populations are widely observed in ecology. Even in the absence of spatially synchronized exogenous forces, metapopulations may synchronize via dispersal. For many species, most dispersal is local, but rare long-distance dispersal events also occur. While even small amounts of long-range dispersal are known to be important for processes like invasion and spatial spread rates, their potential influence on population synchrony is often overlooked, since local dispersal on its own can be strongly synchronizing. In this work, we investigate the effect of random, rare, long-range dispersal on the spatial synchrony of a metapopulation and find profound effects not only on synchrony but also on properties of the resulting spatial patterns. While controlling for the overall amount of emigration from each local subpopulation, we vary the fraction of dispersal that occurs locally (to nearest neighbors) versus globally (to random locations, irrespective of distance). Using a metric that measures the instantaneous level of global synchrony, we show that this form of long-range dispersal significantly favors the spatially synchronous state and homogenizes the population by decreasing the size of clusters of subpopulations that are out of phase with the rest of the metapopulation. Moreover, the addition of non-local dispersal significantly decreases the equilibration time of the metapopulation.

Jarvis‑Cross, Madeline; Krkošek, Martin

doi: 10.1007/s12080-026-00636-zpmid: N/A

Fog, Agner

doi: 10.1007/s12080-026-00639-wpmid: N/A

This article develops stochastic models of different ecological mechanisms of natural selection that explicitly account for the interdependence of individual fates in case of ecological competition. Competition as a zero-sum game makes the fates of individuals interdependent. Competition for a limited resource and competition to escape predators are shown to have markedly different statistical properties. The effect of selection depends not only on individual phenotypes, but also on the strength of competition. This is illustrated with simulations comparing five different selection mechanisms with and without competition. It is shown how the rate of genetic change, the probability of fixation of a mutant allele, mean fixation time, etc. depend on the strength of competition, fitness ratio between individuals with different competitive abilities, initial allele fraction, population size, and Mendelian dominance. The effect of competition is reduced when mobility is limited so that individuals can compete with conspecifics only within a limited distance. This is regarded as imperfect interdependence. A lower limit for the effect of competition under imperfect interdependence is estimated. The statistical effects of different forms of ecological competition is a previously neglected area of study where many traditional models ignore the interdependence of fates.

Burger, Isabella J.; Olugbusi, Rachel; Riddell, Eric A.

doi: 10.1007/s12080-026-00638-xpmid: N/A

Population growth models are essential tools for predicting population demographic trends and assessing population viability over time. Population growth models are often parameterized using demographic data that account for imperfect detection; however, historical datasets—collected prior to the widespread incorporation of imperfect detection—may still yield valuable insights into long-term population dynamics. Here, we used a deterministic age structured model and a stochastic individual based model, which were both parameterized with age-specific vital rates, to estimate population growth in a woodland salamander (Plethodon metcalfi). To parameterize our model, we used long-term historical demographic data collected by Hairston (1983) to estimate population growth. Our objectives were to evaluate differences between the population growth models and assess whether historical demographic data can produce realistic estimates of population dynamics. We found that the individual based model predicted a declining population size, whereas the age structured model predicted an increasing population size. However, sensitivity analyses revealed that minimal changes to survival or fecundity were sufficient to produce stable populations in both models, reflecting observations of these populations in the wild. Therefore, our results suggest that historical data can be informative even in the absence of detection-corrected estimates in cryptic species. We also found that both models were capable of predicting age distributions similar to those observed in nature. Together, these results emphasize the importance of model selection and utility of historical datasets in forecasting population resilience under variable environmental conditions.

Marcinko, Kelsey

doi: 10.1007/s12080-025-00630-xpmid: N/A

Climate change has created new and evolving environmental conditions, impacting all species, including hosts and parasitoids. In that context, we present integrodifference equation (IDE) models of host–parasitoid systems to model population dynamics in the context of climate-driven shifts in habitats. In this paper, we describe and analyze two IDE models of host–parasitoid systems to determine criteria for coexistence of the host and parasitoid. Specifically, we determine the critical habitat speed, beyond which the parasitoid cannot survive. By comparing the results from two IDE models, we investigate the impacts of assumptions that reduce the system to a single-species model. We also compare critical speeds predicted by a spatially-implicit difference-equation model with critical speeds determined from numerical simulations of the IDE system. The spatially-implicit model uses approximations for the dominant eigenvalue of an integral operator. The classic methods to approximate the dominant eigenvalue for IDE systems do not perform well for asymmetric kernels, including those that are present in shifting-habitat IDE models. Therefore, we compare several methods for approximating dominant eigenvalues that have not previously been compared in two-species IDE moving-habitat models. Ultimately, geometric symmetrization and iterated geometric symmetrization approximations give the best estimates of the parasitoid critical speed, which extends the superiority of these approximations into the two-species context.

MacQueen, Sarah A.; Hardy, Clara F.; Braun, W. John; Tyson, Rebecca C.

doi: 10.1007/s12080-026-00635-0pmid: N/A

Foraging site constancy, or repeated return to the same foraging location, is a foraging strategy used by many species to decrease uncertainty and risks. It is often unclear, however, exactly how organisms identify the foraging site. Here we are interested in the context where the actual harvesting of food is first preceded by a separate exploration period. In this context, foraging consists of three distinct steps: (1) exploration of the landscape (site-generation), (2) selection of a foraging site (site-selection), and (3) exploitation (harvesting) through repeated trips between the foraging site and "home base". This type of foraging has received scant attention in the modelling literature, leading to two main knowledge gaps. First, there is very little known about how organisms implement steps (1) and (2). Second, it is not known how the choice of implementation method affects the outcomes of step (3). Typical outcomes include the foragers’ rate of energy return, and the distribution of foragers on the landscape. We investigate these two gaps, using an agent-based model with bumble bees as our model organism foraging in a patchy resource landscape of crop, wildflower, and empty cells. We tested two different site-generation methods (random and circular foray exploration behaviour) and four different site-selection methods (random and optimizing based on distance from the nest, local wildflower density, or net rate of energy return) on a variety of outcomes from the site-constant harvesting step. We find that site-selection method has a high impact on crop pollination services as well as the percent of crop resources collected, while site-generation method has a high impact on the percent of time spent harvesting and the total trip time. We also find that some of the patterns we identify can be used to infer how a given real organism is identifying a foraging site. Our results underscore the importance of explicitly considering exploratory behaviour to better understand the ecological consequences of foraging dynamics.

Ducrot, Arnaud; Seydi, Ousmane

doi: 10.1007/s12080-025-00629-4pmid: N/A

We develop a spatially explicit age-structured model to study the invasion dynamics of plant species, integrating habitat quality, demographic structure, and seed dispersal. Our approach incorporates continuous age structuring and explicitly derives a habitat-quality-dependent invasion threshold, \documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\mathcal {T}_0(q)$$\end{document}, which determines whether a species can establish (\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\mathcal {T}_0(q)> 1$$\end{document}) or extinct (\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\mathcal {T}_0(q)\le 1$$\end{document}). This threshold encapsulates three fundamental components of biological invasions: (i) biotic factors, (ii) abiotic conditions, and (iii) dispersal capacity. Our model is applied to the invasion of black cherry (Prunus serotina) in France, using empirical data to simulate spatio-temporal invasion dynamics.