The demography and dynamics of heterogeneous populations

预测植物和动物种群的丰度将如何随着时间的推移而变化取决于认识到个体之间的差异，例如，年轻与年老，成熟与不成熟，以及这些差异如何影响个体的生存，生长，发育和繁殖，统称为生命率。 基于这些生命率的数学模型在基础和应用种群生态学中起着重要的作用。 例如，它们可以衡量环境因素对种群动态的影响，评估自然资源管理战略，并预测全球变化对物种丰度的影响。 然而，除了个体之间的明显差异外，所有种群都包含某种程度的个体间异质性，这种异质性无法测量。这种异质性可能是由食物供应、遗传变异、个体历史或环境影响驱动的生理过程造成的。 该项目将开发包括此类异质性的新数学模型。 将分析种群人口统计模型，以量化异质性对种群增长和敏感性模式的影响，并将其应用于南极海鸟种群的长期数据。教育推广是生态学数学研究的一个重要方面。 为了使其他研究人员更广泛地获得研究结果，将在美国生态学会全国年会上组织一个教育讲习班。 从这项工作中产生的模型也将在野生动物种群管理和保护生物学中有实际应用。

Predicting how the abundance of populations of plants and animals will change through time depends on recognizing differences among individuals, e.g., young vs. old, mature vs. immature, and on how those differences affect individual survival, growth, development, and reproduction, collectively known as the vital rates. Mathematical models based on these vital rates play an important role in both basic and applied population ecology. For example, they can measure the impact of environmental factors on population dynamics, evaluate strategies for the management of natural resources, and project the consequences of global change on species abundance. However, in addition to obvious differences among individuals, all populations contain some level of heterogeneity among individuals that cannot be measured. This heterogeneity may result from physiological processes driven by food availability, genetic variation, individual history, or environmental effects. This project will develop new mathematical models that include such types of heterogeneity. The population demographic models will be analyzed to quantify the effects of heterogeneity on population growth and sensitivity patterns, and applied to long-term data on Antarctic seabird populations. Educational outreach is a critical aspect of mathematical research in ecology. With the goal of making the results of the research more widely accessible to other researchers, an educational workshop will be organized at the national Annual Meeting of the Ecological Society of America. The models that result from this work will also have practical application in the management of wildlife populations, and in conservation biology.