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

预测未来生物的丰富程度需要我们了解个体的繁殖模式如何对环境变化做出反应。产妇生殖投资(如第一次生育的年龄或所生后代的大小和数量)影响人口增长，从而可决定人口的存续或灭绝。最近的经验研究表明，雌性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，包括个体条件、资源可获得性和配偶质量。拟议的研究将包括解决产妇投资问题的理论和实证工作。这一理论将被用来预测上述因素如何共同影响后代的生产。这一理论的预测将在一种墨西哥剑尾鱼身上得到验证，众所周知，这种鱼的母性投资在雌性之间存在差异。剑尾是检验这一新理论的理想选择，因为它们自然资源丰富，其生殖生物学也得到了很好的研究。PIS将与来自美国、墨西哥和英国的研究人员合作，研究种群生态和性选择如何相互作用，在自然剑尾种群中塑造雌性生殖。PIs将让当地的高中生参与研究，这些学生大多来自传统上在学术界代表性较低的群体。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繁殖模式的理解，拟议的研究将改进用于野生种群管理和保护的预测模型。

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.