Molly Creagar , Richard Rebarber , Brigitte Tenhumberg
{"title":"Spatial evolutionary public goods game theory applied to optimal resource allocation and defense strategies in herbaceous plants","authors":"Molly Creagar , Richard Rebarber , Brigitte Tenhumberg","doi":"10.1016/j.tpb.2025.02.003","DOIUrl":null,"url":null,"abstract":"<div><div>Empirical evidence suggests that the attractiveness of a plant to herbivores can be affected by the investment in defense by neighboring plants, as well as investment in defense by the focal plant. Thus, the payoff for allocating to defense may not only be influenced by the frequency and intensity of herbivory but also by defense strategies employed by other plants in the environment. We use a combination of spatial evolutionary game theory and stochastic dynamic programming to predict the proportion of plants in the population investing in defense (cooperators) and the proportion of plants that do not (defectors). Our model accounts for metabolic costs of maintenance of stored resources when predicting optimal resource allocation to growth, reproduction, and storage; this cost is not commonly accounted for in previous models. For both annual and perennial plants, our model predicts an evolutionarily stable proportion of cooperators and defectors (mixed stable strategy), but the proportion of cooperators is higher in a population of perennial plants than in a population of annual plants. We also show that including a metabolic cost of maintaining stored resources does not change the proportion of cooperators but does decrease plant fitness and allocation to overwinter storage.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"163 ","pages":"Pages 36-49"},"PeriodicalIF":1.2000,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theoretical Population Biology","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0040580925000115","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECOLOGY","Score":null,"Total":0}
Spatial evolutionary public goods game theory applied to optimal resource allocation and defense strategies in herbaceous plants
Empirical evidence suggests that the attractiveness of a plant to herbivores can be affected by the investment in defense by neighboring plants, as well as investment in defense by the focal plant. Thus, the payoff for allocating to defense may not only be influenced by the frequency and intensity of herbivory but also by defense strategies employed by other plants in the environment. We use a combination of spatial evolutionary game theory and stochastic dynamic programming to predict the proportion of plants in the population investing in defense (cooperators) and the proportion of plants that do not (defectors). Our model accounts for metabolic costs of maintenance of stored resources when predicting optimal resource allocation to growth, reproduction, and storage; this cost is not commonly accounted for in previous models. For both annual and perennial plants, our model predicts an evolutionarily stable proportion of cooperators and defectors (mixed stable strategy), but the proportion of cooperators is higher in a population of perennial plants than in a population of annual plants. We also show that including a metabolic cost of maintaining stored resources does not change the proportion of cooperators but does decrease plant fitness and allocation to overwinter storage.
期刊介绍:
An interdisciplinary journal, Theoretical Population Biology presents articles on theoretical aspects of the biology of populations, particularly in the areas of demography, ecology, epidemiology, evolution, and genetics. Emphasis is on the development of mathematical theory and models that enhance the understanding of biological phenomena.
Articles highlight the motivation and significance of the work for advancing progress in biology, relying on a substantial mathematical effort to obtain biological insight. The journal also presents empirical results and computational and statistical methods directly impinging on theoretical problems in population biology.