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A Novel Unbiased Analysis Approach for Investigating Population Dynamics: A Case Study on Calanus finmarchicus and Its Decline in the North Sea

机译：一种新颖的无偏差的人口动态分析方法：以北海螯鱼及其下降为例

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Marine populations are controlled by a series of drivers, pertaining to both the physical environment and the biological environment (trophic predator-prey interactions). There is heated debate over drivers, especially when trying to understand the causes of major ecosystem events termed regime shifts. In this work, we have researched and developed a novel methodology based on Genetic Programming (GP) for distinguishing which drivers can influence species abundance. This methodology benefits of having no a priori assumptions either on the ecological parameters used or on the underlying mathematical relationships among them. We have validated this methodology applying it to the North Sea pelagic ecosystem. We use the target species Calanus finmarchicus, a key copepod in temperate and subarctic ecosystems, along with 86 biological, hydrographical and climatic time series, ranging from local water nutrients and fish predation, to large scale climate pressure patterns. The chosen study area is the central North Sea, from 1972 to 2011, during which period there was an ecological regime shift. The GP based analysis identified 3 likely drivers of C. finmarchicus abundance, which highlights the importance of considering both physical and trophic drivers: temperature, North Sea circulation (net flow into the North Atlantic), and predation (herring). No large scale climate patterns were selected, suggesting that when there is availability of both data types, local drivers are more important. The results produced by the GP based procedure are consistent with the literature published to date, and validate the use of GP for interpreting species dynamics. We propose that this methodology holds promises for the highly non-linear field of ecology.
机译：海洋人口受到一系列与自然环境和生物环境（营养性捕食者－猎物相互作用）有关的驱动因素的控制。关于驱动程序，引起了激烈的争论，尤其是在试图了解被称为政权转移的主要生态系统事件的成因时。在这项工作中，我们已经研究和开发了一种基于遗传程序设计（GP）的新颖方法，以区分哪些驱动程序可以影响物种的丰度。这种方法的优点是对使用的生态参数或它们之间的潜在数学关系都没有先验假设。我们已经验证了将该方法应用于北海中上层生态系统的有效性。我们使用目标物种Calanus finmarchicus（温带和亚北极生态系统中的重要co足类），以及86种生物，水文和气候时间序列，包括局部水养分和鱼类捕食，以及大规模的气候压力模式。选定的研究区域是1972年至2011年的北海中部，在此期间生态系统发生了变化。基于GP的分析确定了finmarchicus丰度的3种可能驱动因素，这突出了考虑物理和营养驱动因素的重要性：温度，北海环流（流入北大西洋的净流量）和掠食（鲱鱼）。没有选择大规模的气候模式，这表明当两种数据类型均可用时，本地驱动因素更为重要。基于GP的程序产生的结果与迄今为止发表的文献一致，并验证了GP在解释物种动态中的用途。我们建议这种方法学对高度非线性的生态学领域具有希望。

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