Biology subjects

Holt, R. D.

Publications and source records attributed to Holt, R. D..

4 recordsLinked to original sources

bioRxiv2026

Host behavioral responses to perceived risk shape spatial disease dynamics

There is growing recognition that host behavioral responses to disease risk are critical factors driving disease dynamics, but understanding how behavioral responses influence dynamics remains a major challenge. Coupled behavioral and epidemiological models commonly assume that hosts use population prevalence as an indicator of disease risk. However, real-world estimates of prevalence come from data aggregated over coarse spatial scales, while transmission occurs through fine-scale contacts. Fine-scale changes in movement behavior represent an important type of risk response because individuals must use proxies for infection risk, such as host density or environmental factors, whose relationship with actual transmission risk may vary across contexts. In this study, we examine the consequences of using diierent risk proxies to inform fine-scale movement and determine when and if relying on imperfect proxies can cause risk-averse behaviors to increase, rather than decrease, disease transmission relative to no behavioral change. We examine the effect of three risk proxies - local prevalence, local host density, and local transmission coefficient (i.e., "place") - in the context of "simple trips", where individuals may respond to disease risk by altering rates of travel from home to "away" locations and back. In one case, individuals stay home more frequently (an absolute risk response) and in the other case, individuals shift their travel to less risky, away locations (a relative risk response). Absolute responses were far more effective in reducing prevalence than relative responses, which were detrimental in some parameter regimes. Detrimental responses occurred when information used to perceive risk was mismatched with the mode of transmission (either density-dependent or frequency-dependent), such that individuals either failed to use pertinent information or used irrelevant information. Imperfect information thus plays a critical role in determining whether behavioral response reduces or elevates disease risk.

ecology↗

bioRxiv2025

Modeling and Inferring Metacommunity Dynamics with Maximum Caliber

A major challenge for community ecology is using spatio-temporal data to infer parameters of dynamical models without conducting laborious experiments. We present a novel framework from statistical physics - Maximum Caliber - to characterize the temporal dynamics of complex ecological systems in spatially extended landscapes and infer parameters from empirical data. As an extension of Maximum Entropy modeling, Maximum Caliber aims at modeling the probability of possible trajectories of a stochastic system, rather than focusing on system states. We demonstrate the ability of the Maximum Caliber framework to capture ecological processes ranging from near-to far from-equilibrium, using an array of species interaction motifs including random interactions, apparent competition, intraguild predation, and non-transitive competition, along with dispersal among multiple patches. For spatio-temporal data of species occupancy in a metacommunity, the parameters of a Maximum Caliber model can be estimated through a simple logistic regression to reveal migration rates between patches, interactions between species, and local environmental suitabilities. We test the accuracy of the method over a range of system sizes and time periods, and find that these parameters can be estimated without bias. We introduce "entropy production" as a measure of irreversibility in system dynamics, and use "pseudo-R2" to characterize predictability of future states. We show that our model can predict the dynamics of metacommunities that are far from equilibrium. The capacity to estimate basic parameters of dynamical metacommunity models from spatio-temporal data represents an important breakthrough for the study of metacommunities with application to practical problems in conservation and restoration ecology.

ecology↗

bioRxiv2023

Neglected consequences of spatio-temporal heterogeneity and dispersal: Metapopulations, the inflationary effect, and real-world consequences for public health

The metapopulation perspective is an important conceptual framework in ecology and evolutionary ecology. Metapopulations are spatially distributed populations linked by dispersal. Both metapopulation models and their community and ecosystem level analogues, metacommunity and meta-ecosystem models, tend to be more stable regionally than locally and display enhanced abundance because of the interplay of spatiotemporal heterogeneity and dispersal (an effect that has been called the "inflationary effect"). We highlight the essential role of spatiotemporal heterogeneity in metapopulation biology, sketch empirical demonstrations of the inflationary effect, and provide a mechanistic interpretation of how the inflationary effect arises and impacts population growth and abundance. We illustrate the effect with examples from the spread of infectious disease. Namely, failure to recognize the full possible effects of spatiotemporal heterogeneity likely enhanced the spread of COVID-19, a failure based on lack of understanding of emergent population processes at large scales which may hamper control and eradication of other infectious diseases. We finish by noting how the effects of spatiotemporal heterogeneity have implicitly played roles in the history of ecology, ranging across subdisciplines as diverse as natural enemy-victim dynamics, species coexistence, and conservation biology. Seriously confronting the complexity of spatiotemporal heterogeneity could push many of these subdisciplines forward.

ecology↗

bioRxiv2022

Effects of disease emergence on invasive grass impacts

Invasive species impact ecosystems through their large abundances and strong per capita effects. Enemies can regulate abundances and per capita effects, but are notably absent for many new invaders. However, invaders acquire enemies over time and as they spread; processes hypothesized to mitigate negative invader impacts by reducing abundance or per capita effects. Alternatively, properties of invaders or acquired enemies, such as an enemys ability to attack multiple species, may hinder enemy mitigation of invader impacts. We used field experiments to evaluate disease mitigation of invader impacts using the invasive grass Microstegium vimineum, which hosts an emerging fungal disease, and a native grass competitor, Elymus virginicus. We manipulated competition through density gradients of each plant species, and we reduced ambient foliar diseases with fungicide and autoclaving. We then modeled long-term population dynamics with field-estimated parameters. In the field, disease did not reduce invader abundance or per capita effects. The invader amplified disease on itself and the competitor, and disease reduced invader and competitor fitness components (e.g., germination). The dynamical model predicted that disease impacts on the competitor are greater than on the invader, such that disease will reduce invader abundance by 18%, and competitor abundance by 88%, over time. Our study suggests that enemies acquired by invaders will not necessarily mitigate invader impacts if the invader amplifies the enemy and the enemy attacks and suppresses competitor species.

ecology↗