了解招聘,将个人添加到种群或渔业中的过程,对于了解人口动态和促进可持续渔业管理至关重要。在人群中观察到招募动态的重要变化,其中一些种群表现出渐近生产力,而另一些种群表现出过度补偿(即,补偿性密度依赖性招聘)。我们理解招募模式中这种种群间差异的能力受到对潜在机制理解不足的限制,例如密度依赖性之间的复杂相互作用,招募,和环境。此外,大多数关于招募的研究都是使用观察性设计进行的,该设计具有长时间序列,很少以实验控制的方式在人群中复制。没有适当的复制,人群之间的推断是脆弱的,潜在的环境趋势难以量化。为了解决这些问题,我们进行了一项田间试验,操纵了三个野生种群中幼鱼鳟鱼Salvelinusfontinalis的放养密度,以表明这些相邻种群-由于环境条件而表现出不同的密度依赖性模式-在招募动态上也具有重要差异。针对四种股票招募模型进行测试(密度无关,线性,Beverton-Holt,和Ricker),种群在渐近生产力上表现出~两倍的变化,按照贝弗顿-霍尔特模型没有超额补偿。虽然环境变量(例如,温度,pH值,深度,底物)与招募中的人口差异相关,它们并没有提高个体人群的预测能力.将我们的招募模式与经典的鲑鱼案例研究进行比较,发现尽管曲线的形状和参数存在差异(即,Rickervs.Beverton-Holt),出现了约5条YOY鱼/m2的最大放养密度。较高的密度导致招聘的边际增加(Beverton-Holt)或由于过度补偿而减少招聘(Ricker)。
Understanding recruitment, the process by which individuals are added to a population or to a fishery, is critical for understanding population dynamics and facilitating sustainable fisheries management. Important variation in recruitment dynamics is observed among populations, wherein some populations exhibit asymptotic productivity and others exhibit overcompensation (i.e., compensatory density-dependence in recruitment). Our ability to understand this interpopulation variability in recruitment patterns is limited by a poor understanding of the underlying mechanisms, such as the complex interactions between density dependence, recruitment, and environment. Furthermore, most studies on recruitment are conducted using an observational design with long time series that are seldom replicated across populations in an experimentally controlled fashion. Without proper replication, extrapolations between populations are tenuous, and the underlying environmental trends are challenging to quantify. To address these issues, we conducted a field experiment manipulating stocking densities of juvenile brook trout Salvelinus fontinalis in three wild populations to show that these neighboring populations-which exhibit divergent patterns of density dependence due to environmental conditions-also have important differences in recruitment dynamics. Testing against four stock-recruitment models (density independent, linear, Beverton-Holt, and Ricker), populations exhibited ~twofold variation in asymptotic productivity, with no overcompensation following a Beverton-Holt model. Although environmental variables (e.g., temperature, pH, depth, substrate) correlated with population differences in recruitment, they did not improve the predictive power in individual populations. Comparing our patterns of recruitment with classic salmonid
case studies revealed that despite differences in the shape and parameters of the curves (i.e., Ricker vs. Beverton-Holt), a maximum stocking density of about five YOY fish/m2 emerged. Higher densities resulted in very marginal increases in recruitment (Beverton-Holt) or reduced recruitment due to overcompensation (Ricker).