Biology subjects

O'Dwyer, J.

Publications and source records attributed to O'Dwyer, J..

3 recordsLinked to original sources

bioRxiv2018

Whence Lotka-Volterra? Conservation Laws and Integrable Systems in Ecology.

Competition in ecology is often modeled in terms of direct, negative effects of one individual on another. An example is logistic growth, modeling the effects of intraspecific competition, while the Lotka-Volterra equations for competition extend this to systems of multiple species, with varying strengths of intra- and inter-specific competition. These equations are a classic and well-used staple of quantitative ecology, providing a framework to understand species interactions, species coexistence, and community assembly. They can be derived from an assumption of random mixing of organisms, and an outcome of each interaction that removes one or more individuals. However, this framing is some-what unsatisfactory, and ecologists may prefer to think of phenomenological equations for competition as deriving from competition for a set of resources required for growth, which in turn may undergo their own complex dynamics. While it is intuitive that these frameworks are connected, and the connection is well-understood near to equilibria, here we ask the question: when can consumer dynamics alone become an exact description of a full system of consumers and resources? We identify that consumer-resource systems with this property must have some kind of redundancy in the original description, or equivalently there is one or more conservation laws for quantities that do not change with time. Such systems are known in mathematics as integrable systems. We suggest that integrability in consumer-resource dynamics can only arise in cases where each species in an assemblage requires a distinct and unique combination of resources, and even in these cases it is not clear that the resulting dynamics will lead to Lotka-Volterra competition.\n\nI acknowledge the Simons Foundation Grant #376199 and the McDonnell Foundation Grant #220020439.

ecology↗

bioRxiv2018

Born to run? Quantifying the balance of prior bias and new information in prey escape decisions

Animal behaviors can often be challenging to model and predict, though optimality theory has improved our ability to do so. While many qualitative predictions of behavior exist, accurate quantitative models, tested by empirical data, are often lacking. This is likely due to variation in biases across individuals and variation in the way new information is gathered and used. We propose a modeling framework based on a novel interpretation of Bayes theorem to integrate optimization of energetic constraints with both prior biases and specific sources of new information gathered by individuals. We present methods for inferring distributions of prior biases within populations rather than assuming known priors, as is common in Bayesian approaches to modelling behavior, and for evaluating the goodness of fit of overall model descriptions. We apply this framework to predict optimal escape during predator-prey encounters, based on prior biases and variation in what information prey use. Using this approach we collected and analyzed data characterizing white-tailed deer (Odocoileus virginianus) escape behavior in response to human approaches. We found that distance to predator alone was not sufficient for predicting deer flight response, and have shown that the inclusion of additional information is necessary. Additionally, we compared differences in the inferred distributions of prior biases across different populations and discuss the possible role of human activity in influencing these distributions.

ecology↗

bioRxiv2018

Stability Criteria for Complex Microbial Communities

Competition and mutualism are inevitable processes in microbial ecology, and a central question is which and how many taxa will persist in the face of these interactions. Ecological theory has demonstrated that when direct, pairwise interactions among a group of species are too numerous, or too strong, then the coexistence of these species will be unstable to any slight perturbation. This instability worsens when mutualistic interactions complement competition. Here, we refine and to some extent overturn that understanding, by considering explicitly the resources that microbes consume and produce. In contrast to more complex organisms, microbial cells consume primarily abiotic resources, and mutualistic interactions are often mediated by these same abiotic resources through the mechanism of cross-feeding. Our model therefore considers the consumption and production of a set of abiotic resources by a group of microbial species. We show that if microbes consume, but do not produce resources, then any positive equilibrium will always be stable to small perturbations. We go on to show that in the presence of crossfeeding, stability is no longer guaranteed. However, stability still holds when mutualistic interations are either symmetric, or sufficiently weak.

ecology↗