DISSERTATION RESEARCH: Theoretical and Empirical Studies of State-Dependent Variation in Maternal Investment

要预测未来生物的丰度，我们需要了解个体的繁殖模式如何对环境变化做出反应。母体生殖投资（例如第一次生殖的年龄或所生后代的大小和数量）影响人口增长，因此可以决定人口的持续或灭绝。最近的实证研究表明，雌性产生的后代的大小和数量因个体而异，并同时受到多种因素的影响，包括个体状况，资源可用性和配偶质量。拟议的研究将包括理论和实证工作，以解决产妇投资。该理论将被开发来预测上面列出的因素如何共同影响后代的产生。该理论的预测将在墨西哥的剑尾鱼物种中进行测试，已知雌性之间的母性投资各不相同。剑尾鱼是测试这一新理论的理想选择，因为它们在自然界中数量众多，而且它们的生殖生物学也得到了很好的研究。PI将与来自美国，墨西哥和英国的研究人员合作，解决种群生态学和性选择如何相互作用，以塑造剑尾鱼自然种群中的雌性繁殖。PI将让当地的高中生参与研究，他们主要来自学术界传统上代表性不足的群体。他们还将为本科生提供研究机会。最后，通过将理论和数据联系起来，以提高对个体生殖模式的理解，拟议的研究将改进用于管理和保护野生种群的预测模型。

Predicting the future abundance of organisms requires that we understand how individual reproductive patterns respond to environmental change. Maternal reproductive investment (e.g. the age at first reproduction or the size and number of offspring produced) affects population growth and can thus determine the persistence or extinction of a population. Recent empirical studies suggest that the size and number of offspring produced by females varies among individuals and is shaped simultaneously by multiple factors, including individual condition, resource availability and mate quality. The proposed research will include both theory and empirical work to address maternal investment. The theory will be developed to predict how the factors listed above jointly influence the production of offspring. The predictions from the theory will be tested in a Mexican species of swordtail fish where maternal investment is known to vary among females. Swordtails are ideal for testing this novel theory because they are naturally abundant and their reproductive biology is well studied. The PIs will collaborate with researchers from the US, Mexico, and the UK to address how population ecology and sexual selection interact to shape female reproduction in natural populations of swordtails. The PIs will involve local high-school students, largely from groups traditionally underrepresented in academia, in the research. They will also provide research opportunities for undergraduates. Finally, by linking theory and data to improve the understanding of individual reproductive patterns, the proposed research will improve predictive models used in the management and conservation of wild populations.