Evolutionary responses to limiting factors in heterogeneous environments

所有生物都有可能产生数量呈指数增长的后代，但最终由于限制繁殖成功的各种因素的作用而无法这样做。生态学领域主要致力于研究这些限制因素。关于不同的潜在限制因素对特定微生物、植物和动物类群的相对重要性的争论遍及进化生态学文献；突出的例子包括外在与内在的死亡来源，生物体生长所需的不同宏量和微量营养素，生物体不同关键结构特征的物理磨损或破坏，种群调节中的资源与捕食者，植物中的花粉与资源限制，昆虫中的卵与宿主限制。虽然在特定背景下解决这些争论的理论发展取得了重要进展，但这些理论治疗方法的发展是彼此孤立的。然而，许多这些争论都有一个共同的逻辑结构：病灶生物生活在异质环境中，具有有限的代谢资源池来改善多种限制因素，并且不能立即调整代谢分配以完美匹配环境。本项目将开发一个通用的数学框架来分析具有这种逻辑结构的进化问题，将该框架应用于进化生态学中几个主要限制因素的争论，并用经验数据面对建模预测。数学框架将为随机过程和动力系统的界面提供广泛适用的方法。这些方法将用于了解(i)昆虫是否受到卵供应有限或寄主寿命短的限制，以及（ii）植物是否受到其吸引传粉者的能力或繁殖的其他方面的限制。为了建立理论与自然世界之间的对话，将收集和分析卵子限制和花粉限制的数据，以评估理论。保护和恢复生态学家感兴趣的是预测动物和植物对不断变化的环境的反应，并能够操纵这些反应以达到有益的目的。该项目将通过提供对生物如何进化以应对可能限制繁殖成功的不同因素的更深入了解，为实现这些目标做出贡献。如果一个种群的适合度一直受到某一特定因素的限制，那么它对该因素的扰动会做出可预测的反应。另一方面，如果一个种群的适应性在不同的时间或地点受到不同因素的限制，那么它对扰动的反应就不那么可预测。该项目的一个关键主题，花粉限制，直接关系到传粉昆虫（如蜜蜂）数量的全球下降。这些人口的减少威胁着全世界的植物群落和作物生产力。本计画的成果将纳入传粉生态学的新课程、两本应用于生命科学的微积分与建模教材，以及生物学学生的入门课程。此外，本科生、研究生和博士后将以垂直整合的方式培养。

All organisms have the potential to produce descendants whose numbers grow exponentially, but are eventually prevented from doing so by the action of various factors that limit reproductive success. The field of ecology is largely devoted to the study of these limiting factors. Debates concerning the relative importance of different potentially limiting factors for particular microbe, plant, and animal taxa pervade the evolutionary ecology literature; prominent examples include extrinsic versus intrinsic sources of mortality, different macro- and micronutrients required for organismal growth, physical wear or breakage of different key structural features of an organism, resources versus predators in population regulation, pollen versus resource limitation in plants, and egg versus host limitation in insects. While important progress has been made developing theory to resolve these debates in particular contexts, these theoretical treatments have been developed in isolation from one another. Many of these debates, however, share a common logical structure: the focal organism lives in a heterogeneous environment, has a finite pool of metabolic resources to ameliorate multiple limiting factors, and can not instantaneously adjust metabolic allocations to perfectly match the environment. This project will develop a general mathematical framework for analyzing evolutionary problems with this logical structure, apply this framework to several major limiting factor debates in evolutionary ecology, and confront the modeling predictions with empirical data. The mathematical framework will provide broadly applicable methods at the interface of stochastic processes and dynamical systems. These methods will be used to understand (i) whether insects are limited by a finite supply of eggs or a short lifespan to locate hosts and (ii) whether plants are limited by their ability to attract pollinators or by other aspects of reproduction. To establish a dialogue between the theory and the natural world, data on egg limitation and pollen limitation will be collected and analyzed to evaluate the theory. Conservation and restoration ecologists are interested in anticipating the responses of animals and plants to changing environments and in being able to manipulate those responses to beneficial ends. This project will contribute to these goals by providing a deeper understanding of how organisms evolve in response to different factors that may limit reproductive success. A population of organisms whose fitness is consistently limited by one particular factor will respond predictably to perturbations of that factor. On the other hand, a population of organisms whose fitness is limited by different factors at different times or places will respond to perturbations less predictably. A key topic of this project, pollen limitation, has direct bearing on documented global declines in the populations of pollinating insects such as bees. These population declines threaten plant communities and crop productivity world wide. Results from this project will be incorporated into a new course on pollination ecology, into two textbooks dealing with calculus and modeling as applied to the life sciences, and into entry-level courses for biology students. Moreover, undergraduates, graduate students, and post-doctoral associates will be trained in a vertically integrated manner.