Wildlife Ecology and Conservation Group, Wageningen University and Research Centre, Droevendaalsesteeg 3a, 6708 PB, Wageningen, The Netherlands.
Forest Ecology and Forest Management Group, Wageningen University and Research Centre, Droevendaalsesteeg 3a, 6708 PB, Wageningen, The Netherlands.
Commun Biol. 2022 Jan 11;5(1):28. doi: 10.1038/s42003-021-02960-y.
Marine fish populations commonly exhibit low-frequency fluctuations in biomass that can cause catch volatility and thus endanger the food and economic security of dependent coastal societies. Such variability has been linked to fishing intensity, demographic processes and environmental variability, but our understanding of the underlying drivers remains poor for most fish stocks. Our study departs from previous findings showing that sea surface temperature (SST) is a significant driver of fish somatic growth variability and that life-history characteristics mediate population-level responses to environmental variability. We use autoregressive models to simulate how fish populations integrate SST variability over multiple years depending on fish life span and trophic position. We find that simulated SST-driven population dynamics can explain a significant portion of observed low-frequency variability in independent observations of fisheries landings around the globe. Predictive skill, however, decreases with increasing fishing pressure, likely due to demographic truncation. Using our modelling approach, we also show that increases in the mean and variance of SST could amplify biomass volatility and lessen its predictability in the future. Overall, biological integration of high-frequency SST variability represents a null hypothesis with which to explore the drivers of low-frequency population change across upper-trophic marine species.
海洋鱼类种群的生物量通常会出现低频波动，这可能导致捕捞量不稳定，从而危及依赖沿海地区的社会的粮食和经济安全。这种可变性与捕捞强度、人口过程和环境可变性有关，但我们对大多数鱼类种群的潜在驱动因素的了解仍然很差。我们的研究偏离了先前的发现，即海表温度 (SST) 是鱼类体生长变异性的重要驱动因素，并且生活史特征介导了种群对环境变异性的反应。我们使用自回归模型来模拟鱼类种群如何根据鱼类的寿命和营养位置，在多年内整合 SST 变异性。我们发现，模拟的 SST 驱动的种群动态可以解释全球渔业捕捞量独立观测中观察到的低频变化的很大一部分。然而，随着捕捞压力的增加，预测能力会下降，这可能是由于人口截断造成的。使用我们的建模方法，我们还表明，SST 的均值和方差增加可能会放大生物量的波动性，并降低其未来的可预测性。总的来说，高频 SST 变异性的生物综合代表了一个零假设，可以用来探索上层海洋物种低频种群变化的驱动因素。
