Variability and the Population Biology of Marine Organisms

许多海洋生物物种的特点是个体大小变化很大，特别是在早期生命历史期间。拟议研究的目标是：1)量化自然种群中的这种变异性，2)确定变异性是否随时间传递，3)评估是否存在大小和生长变化的人口后果，以及4)量化大小和生长变化对种群模型的影响。解决这一问题的方法将是多元化的，包括实地观察个体，对可驯化的种群进行实验操作，以及包括个体特征的种群建模。观测和实验数据将来自几个在分类和生活史上不同的物种，包括一种藻类、一种帽贝和一种近岸鱼类。实验将通过操纵种群中变异的数量和类型来确定变异本身是否可以影响未来的种群轨迹。在整个研究过程中，将通过跟踪被标记的个人的命运来收集个人层面的信息。在观察和实验中，将被量化的关键生物学特征包括个体生长，生长速度是否随时间相关，存活率，以及所有这些特征在个体之间变化的倾向。这些分析将对比包括个体间变异性的模型(基于个体的模型)和使用有机体属性平均值的模型(矩阵种群模型)的结果。这项工作的重要性源于这样一种认识，即理解海洋生物的招募为什么不同，可能需要纳入个别属性。

Many species of marine organisms are characterized by high variation in the size of individuals, especially during the early life history. The objectives of the proposed research are to: 1) quantify this variability in natural populations, 2) determine whether variability is transmitted through time, 3) assess if there are demographic consequences of size and growth variation, and 4) quantify the effects of size and growth variation on population models. The approach to the problem will be pluralistic, including observations of individuals in the field, experimental manipulation of tractable populations, and population modeling where individual traits are included. Observational and experimental data will be gathered from several species that differ in their taxonomy and life history, including an alga, a limpet and a nearshore fish. Experiments will determine if variation alone can affect future population trajectories by manipulating the quantity and type of variability in a population. Throughout the study, information will be gathered at the level of the individual by following the fate of marked individuals. In both observations and experiments, the key biological features that will be quantified include individual growth, whether growth rates are correlated through time, survivorship, and the propensity for all these traits to vary among individuals. The analyses will contrast the outcome of models which include variability among individuals (individual based models) versus those that use a mean value for organism attributes (matrix population models). The importance of this work draws from a recognition that understanding why recruitment varies in marine organisms may require the inclusion of individual attributes.