Variability and the Population Biology of Marine Organisms

许多海洋生物物种的特点是个体大小差异很大，特别是在早期生活史期间。 拟议研究的目标是：1）量化自然种群中的这种变异，2）确定变异是否通过时间传递，3）评估大小和生长变化是否有人口统计学后果，以及4）量化大小和生长变化对种群模型的影响。 解决这个问题的方法将是多元化的，包括在该领域的个人观察，易处理的人口的实验操作，以及包括个人特征的人口建模。将从分类和生活史不同的几个物种收集观察和实验数据，包括一种鱼、一种帽贝和一种近岸鱼。 实验将通过操纵种群中变异的数量和类型来确定变异是否会单独影响未来的种群轨迹。 在整个研究过程中，将通过跟踪被标记个体的命运来收集个体层面的信息。 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，生长率是否与时间相关，存活率以及所有这些特征在个体之间变化的倾向。 分析将对比包括个体间变异性的模型（基于个体的模型）与使用微生物属性平均值的模型（基质群体模型）的结果。 这项工作的重要性源于这样一种认识，即要理解海洋生物的补充为何不同，可能需要包括个体属性。

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.