Fisheries Resource Analysis and Monitoring Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Boulevard East, Seattle, WA 98112, USA
Fish Ecology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Boulevard East, Seattle, WA 98112, USA.
Proc Biol Sci. 2018 Oct 3;285(1888):20180915. doi: 10.1098/rspb.2018.0915.
Variance of community abundance will be reduced relative to its theoretical maximum whenever population densities fluctuate asynchronously. Fishing communities and mobile predators can switch among fish species and/or fishing locations with asynchronous dynamics, thereby buffering against variable resource densities (termed 'portfolio effects', PEs). However, whether variation among species or locations represent the dominant contributor to PE remains relatively unexplored. Here, we apply a spatio-temporal model to multidecadal time series (1982-2015) for 20 bottom-associated fishes in seven marine ecosystems. For each ecosystem, we compute the reduction in variance over time in total biomass relative to its theoretical maximum if species and locations were perfectly correlated (total PE). We also compute the reduction in variance due to asynchrony among species at each location (species PE) or the reduction due to asynchrony among locations for each species (spatial PE). We specifically compute total, species and spatial PE in 10-year moving windows to detect changes over time. Our analyses revealed that spatial PE are stronger than species PE in six of seven ecosystems, and that ecosystems where species PE is constant over time can exhibit shifts in locations that strongly contribute to PE. We therefore recommend that spatial and total PE be monitored as ecosystem indicators representing risk exposure for human and natural consumers.
只要种群密度不同步波动,群落丰度的方差就会相对于其理论最大值减小。渔业社区和移动捕食者可以在具有不同步动态的鱼类物种和/或捕鱼地点之间切换,从而缓冲可变资源密度(称为“投资组合效应”,PE)。然而,物种或地点之间的差异是否代表 PE 的主要贡献仍然相对未知。在这里,我们应用时空模型来分析七个海洋生态系统中 20 种底栖鱼类的多十年时间序列(1982-2015 年)。对于每个生态系统,我们计算了如果物种和地点完全相关(总 PE),总生物量的方差相对于其理论最大值随时间的减少。我们还计算了每个地点的物种间异步(物种 PE)或每个物种的地点间异步(空间 PE)引起的方差减少。我们特别在 10 年移动窗口中计算总、物种和空间 PE,以检测随时间的变化。我们的分析表明,在七个生态系统中有六个生态系统中的空间 PE 强于物种 PE,而在时间上物种 PE 保持不变的生态系统可能会发生位置变化,这些变化对 PE 有很大贡献。因此,我们建议将空间和总 PE 作为代表人类和自然消费者风险暴露的生态系统指标进行监测。