Biology subjects

Duthie, A. B.

Publications and source records attributed to Duthie, A. B..

10 recordsLinked to original sources

bioRxiv2025

Persistence and near persistence via trait evolution: pathways to coexistence

Modern coexistence theory relies on the invasion criterion: each species must be able to increase when rare in a resident community at ecological equilibrium. However, when considering trait evolution, for example of competing species, this concept must be refined to account for evolution potentially feeding back on population dynamics. We analyze a model of two competing species whose quantitative traits evolve under stabilizing selection, assuming fixed but potentially unequal intraspecific trait variances. Using persistence theory, we derive conditions under which both species persist for all initial trait values, and we introduce the concept of near persistence, in which coexistence holds for a specific, biologically relevant, subset of initial trait configurations. Our analysis reveals that equal trait variances between species, which is commonly assumed in previous work, yield highly specific outcomes and obscure a broader set of coexistence scenarios that emerge under asymmetric trait variation. We identify fifteen distinct qualitative dynamical regimes as a function of initial conditions and trait variances. Moreover, we show that invasion analysis must often be performed at multiple eco-evolutionary equilibria, as invader dynamics may converge to different trait values depending on the ecological and evolutionary context. We discuss the biological implications of these results and perspectives for future work.

ecology↗

bioRxiv2024

A Habitat Selection Multiverse Reveals Largely Consistent Results Despite a Multitude of Analysis Options

Researchers are intrinsically part of the research process. While we may strive for objectivity, there are always judgement calls required during research. When you ask ten researchers to answer the same question with the same dataset, you will likely receive ten different answers. This variation in answers has been linked to several disciplines replication crises. Here, we explore whether answers from movement ecology, specifically habitat selection, vary as a result of differing analytical choices. We conducted a multiverse analysis on around 400 synthetic animal movement datasets, exploring a multitude of analysis pathways to determine habitat selection, resulting in approximately half a million unique estimates of selection. By using simulated virtual animals with a known preference, we were able to show which decisions during analysis could lead to more variable estimates of habitat selection. The multiverse revealed that data quantity (i.e., tracking frequency and duration) was more important to obtaining consistent answers than any analysis choice. Overall, the pattern of estimates shows the majority of analysis pathways provide similar final results, particularly for modern analysis methods. The pattern reflects findings from other disciplines, indicating that while movement ecology is not immune to issues of non-replicability stemming from researcher choice, it is also not at any greater risk than other disciplines.

ecology↗

bioRxiv2024

The effect of host population genetic diversity on variation in metrics of parasite success

According to conventional wisdom, disease transmission rate is usually higher in more genetically homogenous host populations. Previous studies have principally considered how host population genetic diversity impacts the mean of parasite infection performance. However, when considering risks from epidemics and the emergence of novel infectious diseases, variability in parasite success may be just as important as the mean. Here we propose an Epidemic Diversity Model for how host-parasite population genetic diversity influences both the mean and variability in parasite success. We evaluate this conceptual model by re-analysing effect size data from two meta-analyses, including 211 comparisons of high versus low genetic diversity host populations from 48 studies. Our analysis challenges previous understanding by demonstrating that high host population genetic diversity only reduces mean parasite success for specialist parasites with narrow host range, but not for generalist multi-host parasites. We also find that the combination of host range and parasite population genetic diversity determine the effect of host population genetic diversity on the variability in parasite success. These results have important implications for the management of host population genetic diversity for natural populations.

ecology↗

bioRxiv2023

Exponential diversity-dependent diversification emerges from an individual-based model with Lotka-Volterra competition

AbstractA long-standing question in macroevolution is whether diversification is governed by the same processes that structure diversity at ecological scales, particularly competition. This competition has led to the development of a model where diversification rates depend on diversity, analogous to density-dependence in population growth models. Various versions of this model have been widely used for inference, where the rate of speciation and/or extinction can be either a linear or a power function of species number. It is, however, unknown if either approximates the diversification process that arises from the general ecological setting proposed to lead to diversity-dependence. This is of concern for inference, as failure to include a model that appropriately represents the hypothesized scenario is likely to lead to erroneous inference. Here we use an individual-based model adapted from adaptive dynamics, where fitness is governed by resource availability and the density of competitors, to determine the shape of the diversity-dependence functions. We find that the diversity-dependent rate of speciation produced by the individual-based model is best approximated by an exponential function of species diversity, consistent with a view of macroevolution where diversity increases rapidly after mass extinctions or when new adaptive space becomes available. Although we do find diversity-dependence in the extinction rate, it remains low over the entire process and erases its own signal, so it cannot be recovered from reconstructed phylogenies. The support for a linear relationship for diversity-dependent diversification found in many empirical phylogenies suggests that either our adaptive dynamics model of speciation is inadequate or there is too little information contained in reconstructed phylogenies. We indeed find evidence for the latter when pruning extinct species from our simulated phylogenies, but this does not rule out the former.

evolutionary biology↗

bioRxiv2023

A general time-in, time-out model for the evolution of nuptial gift-giving

Nuptial gift-giving occurs in several taxonomic groups including insects, snails, birds, squid, arachnids and humans. Although this trait has evolved many times independently, no general framework has been developed to predict the conditions necessary for nuptial gift-giving to evolve. We use a time-in time-out model to derive analytical results describing the requirements necessary for selection to favour nuptial gift-giving. Specifically, selection will favour nuptial gift-giving if the fitness increase caused by gift-giving exceeds the product of expected gift search time and encounter rate of the opposite sex. Selection will favour choosiness in the opposite sex if the value of a nuptial gift exceeds the inverse of the time taken to produce offspring multiplied by the rate at which mates with nuptial gifts are encountered. Selection can differ between the sexes, potentially causing sexual conflict. We further investigate these results using an individual-based model inspired by a system of nuptial gift-giving spiders, Pisaura mirabilis, by estimating the fitness benefit of nuptial gift-giving using experimental data from several studies. Our results provide a general framework for understanding when the evolution of nuptial gift-giving can occur and provide novel insight into the evolution of worthless nuptial gifts, occurring in multiple taxonomic groups with implications for understanding parental investment.

evolutionary biology↗

bioRxiv2022

resevol: an R package for spatially explicit models of pesticide resistance given evolving pest genomes

The evolution of pesticide resistance is a widespread problem with potentially severe consequences for global food security. We introduce the resevol R package, which simulates individual-based models of pests with evolving genomes that produce complex, polygenic, and covarying traits affecting pest life history and pesticide resistance. Simulations are modelled on a spatially-explicit and highly customisable landscape in which crop and pesticide application and rotation can vary, making the package a highly flexible tool for both general and tactical models of pest management and resistance evolution. We present the key features of the resevol package and demonstrate its use for a simple example simulating pests with two covarying traits. The resevol R package is open source under GNU Public License. All source code and documentation are available on GitHub.

evolutionary biology↗

bioRxiv2021

Models as games: a novel approach for 'gamesourcing' parameter data and communicating complex models

1O_LIModels have become indispensable tools in conservation science in the face of increasingly rapid loss of biodiversity through anthropogenic habitat loss and natural resource exploitation. In addition to their ecological components, accurately representing human decision-making processes in such models is vital to maximise their utility. This can be problematic as modelling complexity increases, making them challenging to communicate and parameterise. C_LIO_LIGames have a long history of being used as science communication tools, but are less widely used as data collection tools, particularly in videogame form. We propose a novel approach to (1) aid communication of complex social-ecological models, and (2) "gamesource" human decision-making data, by explicitly casting an existing modelling framework as an interactive videogame. C_LIO_LIWe present players with a natural resource management game as a front-end to a social-ecological modelling framework (Generalised Management Strategy Evaluation, GMSE). Players actions replace a model algorithm making management decisions about a population of wild animals, which graze on crops and can thus lower agricultural yield. A number of non-player agents (farmers) respond through modelled algorithms to the players management, taking actions that may affect their crop yield as well as the animal population. Players are asked to set their own management goal (e.g. maintain the animal population at a certain level or improve yield) and make decisions accordingly. Trial players were also asked to provide any feedback on both gameplay and purpose. C_LIO_LIWe demonstrate the utility of this approach by collecting and analysing game play data from a sample of trial plays, in which we systematically vary two model parameters, and allowing trial players to interact with the model through the game interface. As an illustration, we show how variations in land ownership and the number of farmers in the system affects decision-making patterns as well as population trajectories (extinction probabilities). C_LIO_LIWe discuss the potential and limitations of this model-game approach in the light of trial player feedback received. In particular, we highlight how a common concern about the game framework (perceived lack of "realism" or relevance to a specific context) are actually criticisms of the underlying model, as opposed to the game itself. This further highlights both the parallels between games and models, as well as the utility of model-games to aid in communicating complex models. We conclude that videogames may be an effective tool for conservation and natural resource management, and that although they provide a promising means to collect data on human decision-making, it is vital to carefully consider both external validity and potential biases when doing so. C_LI

scientific communication and education↗

bioRxiv2021

Intervene or wait? Modelling the timing of intervention in conservation conflicts adaptive management under uncertainty.

The timing of biodiversity managers interventions can be critical to the success of conservation, especially in situations of conflict between conservation objectives and human livelihood, i.e., conservation conflicts. Given the uncertainty associated with complex social-ecological systems and the potentially irreversible consequences of delayed action for biodiversity and livelihoods, managers tend to simply intervene as soon as possible by precaution. However, refraining from intervening when the situation allows it can be beneficial, notably by saving critical management resources. Here, we introduce a strategy for managers to decide, based on monitoring, whether intervention is required or if waiting is possible. This study evaluates the performance of this waiting strategy compared to a strategy of unconditional intervention at every opportunity. We built an individual-based model of conservation conflict between a manager aiming to conserve an animal population and farmers aiming to maximize yield by protecting their crop from wildlife damage. We then simulated a budget-constrained adaptive management over time applying each strategy, while accounting for uncertainty around population dynamics and around decision-making of managers and farmers. Our results showed that when the decision for the manager to intervene was based on a prediction of population size trajectory, the waiting strategy performed at least as well as unconditional intervention while also allowing managers to save resources by avoiding unnecessary interventions. Under difficult budgetary constraints on managers, this waiting strategy ensured as high yields as unconditional intervention while significantly improving conservation outcomes by compensating managers lack of resources with the benefits accrued over waiting periods. This suggests that waiting strategies are worth considering in conservation conflicts, as they can facilitate equitable management with a more efficient use of management resources, which are often limiting in biodiversity conservation.

ecology↗

bioRxiv2017

GMSE: an R package for generalised management strategy evaluation

O_LIManagement strategy evaluation (MSE) is a powerful tool for simulating all key aspects of natural resource management under conditions of uncertainty.\nC_LIO_LIWe present the R package GMSE, which applies genetic algorithms to provide a generalised tool for simulating adaptive decision-making management scenarios between stakeholders with competing objectives under complex social-ecological interactions and uncertainty.\nC_LIO_LIGMSE models can be agent-based and spatially explicit, incorporating a high degree of realism through mechanistic modelling of links and feedbacks among stakeholders and with the ecosystem; additionally, user-defined sub-models can also be incorporated as functions into the broader GMSE framework.\nC_LIO_LIWe show how GMSE simulates a social-ecological system using the example of an adaptively managed waterfowl population on an agricultural landscape; simulated waterfowl exploit agricultural land, causing conflict between conservation interests and the interest of food producers maximising their crop yield.\nC_LIO_LIThe R package GMSE is open source under GNU Public License; source code and documents are freely available on GitHub.\nC_LI

ecology↗

bioRxiv2017

Evolution Of Pre-Copulatory And Post-Copulatory Strategies Of Inbreeding Avoidance And Associated Polyandry

Inbreeding depression is widely hypothesised to drive adaptive evolution of pre-copulatory and post-copulatory mechanisms of inbreeding avoidance, which in turn are hypothesised to affect evolution of polyandry (i.e., female multiple mating). However, surprisingly little theory or modelling critically examines selection for pre-copulatory or post-copulatory inbreeding avoidance, or both strategies, given evolutionary constraints and direct costs, or examines how evolution of inbreeding avoidance strategies might feed back to affect evolution of polyandry. Selection for post-copulatory inbreeding avoidance, but not for pre-copulatory inbreeding avoidance, requires polyandry, while interactions between pre-copulatory and post-copulatory inbreeding avoidance might cause functional redundancy (i.e., degeneracy) potentially generating complex evolutionary dynamics among inbreeding strategies and polyandry. We used individual-based modelling to quantify evolution of interacting pre-copulatory and post-copulatory inbreeding avoidance and associated polyandry given strong inbreeding depression and different evolutionary constraints and direct costs. We found that evolution of post-copulatory inbreeding avoidance increased selection for initially rare polyandry, and that evolution of a costly inbreeding avoidance strategy became negligible over time given a lower cost alternative strategy. Further, fixed pre-copulatory inbreeding avoidance often completely precluded evolution of polyandry and hence post-copulatory inbreeding avoidance, but fixed post-copulatory inbreeding avoidance did not preclude evolution of pre-copulatory inbreeding avoidance. Evolution of inbreeding avoidance phenotypes and associated polyandry are therefore affected by evolutionary feedbacks and degeneracy. All else being equal, evolution of pre-copulatory inbreeding avoidance and resulting low polyandry is more likely when post-copulatory inbreeding avoidance is precluded or costly, and evolution of post-copulatory inbreeding avoidance greatly facilitates evolution of costly polyandry.

evolutionary biology↗