Dunlop Erin S, Heino Mikko, Dieckmann Ulf
Evolution and Ecology Program, International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria.
Ecol Appl. 2009 Oct;19(7):1815-34. doi: 10.1890/08-1404.1.
We present eco-genetic modeling as a flexible tool for exploring the course and rates of multi-trait life-history evolution in natural populations. We build on existing modeling approaches by combining features that facilitate studying the ecological and evolutionary dynamics of realistically structured populations. In particular, the joint consideration of age and size structure enables the analysis of phenotypically plastic populations with more than a single growth trajectory, and ecological feedback is readily included in the form of density dependence and frequency dependence. Stochasticity and life-history trade-offs can also be implemented. Critically, eco-genetic models permit the incorporation of salient genetic detail such as a population's genetic variances and covariances and the corresponding heritabilities, as well as the probabilistic inheritance and phenotypic expression of quantitative traits. These inclusions are crucial for predicting rates of evolutionary change on both contemporary and longer timescales. An eco-genetic model can be tightly coupled with empirical data and therefore may have considerable practical relevance, in terms of generating testable predictions and evaluating alternative management measures. To illustrate the utility of these models, we present as an example an eco-genetic model used to study harvest-induced evolution of multiple traits in Atlantic cod. The predictions of our model (most notably that harvesting induces a genetic reduction in age and size at maturation, an increase or decrease in growth capacity depending on the minimum-length limit, and an increase in reproductive investment) are corroborated by patterns observed in wild populations. The predicted genetic changes occur together with plastic changes that could phenotypically mask the former. Importantly, our analysis predicts that evolutionary changes show little signs of reversal following a harvest moratorium. This illustrates how predictions offered by eco-genetic models can enable and guide evolutionarily sustainable resource management.
我们提出生态遗传建模，将其作为一种灵活的工具，用于探索自然种群中多性状生活史进化的过程和速率。我们在现有建模方法的基础上，结合有助于研究实际结构化种群的生态和进化动态的特征。特别是，年龄和大小结构的联合考虑能够分析具有多条生长轨迹的表型可塑性种群，并且生态反馈可以很容易地以密度依赖和频率依赖的形式纳入。随机性和生活史权衡也可以实现。至关重要的是，生态遗传模型允许纳入显著的遗传细节，如种群的遗传方差和协方差以及相应的遗传力，以及数量性状的概率遗传和表型表达。这些纳入对于预测当代和更长时间尺度上的进化变化速率至关重要。生态遗传模型可以与经验数据紧密耦合，因此在生成可检验的预测和评估替代管理措施方面可能具有相当大的实际相关性。为了说明这些模型的实用性，我们举一个生态遗传模型的例子，该模型用于研究捕捞诱导的大西洋鳕鱼多性状进化。我们模型的预测（最显著的是，捕捞会导致成熟年龄和大小的遗传减少，生长能力根据最小长度限制增加或减少，以及繁殖投资增加）得到了野生种群中观察到的模式的证实。预测的遗传变化与可能在表型上掩盖前者的可塑性变化同时发生。重要的是，我们的分析预测，在捕捞暂停后，进化变化几乎没有逆转的迹象。这说明了生态遗传模型提供的预测如何能够实现并指导可持续的资源管理。
