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一种用于研究种群动态的新颖、无偏分析方法:以挪威哲水蚤及其在北海的数量减少为例的研究

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

作者信息

Papworth Danny J, Marini Simone, Conversi Alessandra

机构信息

Faculty of Science and Technology, School of Marine Science and Engineering, Plymouth University, Plymouth, Devon, PL4 8AA, United Kingdom.

ISMAR-Marine Sciences Institute in La Spezia, CNR-National Research Council of Italy, Forte Santa Teresa, Loc. Pozzuolo, 19032, Lerici, SP, Italy.

出版信息

PLoS One. 2016 Jul 1;11(7):e0158230. doi: 10.1371/journal.pone.0158230. eCollection 2016.

Abstract

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.

摘要

海洋生物种群受一系列驱动因素的控制,这些因素与物理环境和生物环境(营养捕食者 - 猎物相互作用)都有关。关于驱动因素存在激烈的争论,尤其是在试图理解被称为 regime shifts 的重大生态系统事件的原因时。在这项工作中,我们研究并开发了一种基于遗传编程(GP)的新方法,用于区分哪些驱动因素会影响物种丰度。这种方法的优点是对所使用的生态参数或它们之间潜在的数学关系都没有先验假设。我们通过将其应用于北海浮游生态系统来验证了这种方法。我们使用目标物种哲水蚤(Calanus finmarchicus),它是温带和亚北极生态系统中的一种关键桡足类动物,以及86个生物、水文和气候时间序列,范围从当地水体营养物质和鱼类捕食到大规模气候压力模式。选定的研究区域是北海中部,时间跨度为从年,在此期间发生了一次生态 regime shift。基于遗传编程的分析确定了哲水蚤丰度的3个可能驱动因素,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)和捕食(鲱鱼)。没有选择大规模气候模式,这表明当两种数据类型都可用时,局部驱动因素更为重要。基于遗传编程的程序产生的结果与迄今为止发表的文献一致,并验证了遗传编程在解释物种动态方面的应用。我们认为这种方法在高度非线性的生态学领域具有前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/902c/4930201/49d504c790f9/pone.0158230.g001.jpg

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