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Qualitative network models in support of ecosystem approaches to bivalve aquaculture

机译:支持双壳类水产养殖生态系统方法的定性网络模型

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Predicting the effects of aquaculture development for coastal ecosystems remains challenging, particularly for data-limited systems, and tools that account for complex ecological interactions are needed to support ecosystem approaches to aquaculture. Here, we used qualitative network models (QNMs) to examine the potential community effects of increasing bivalve aquaculture in South Puget Sound, a large estuarine system in Washington, United States. QNMs are formalized conceptual models that require only a qualitative understanding of how variables composing a system interact (that is, the sign of interactions: +, -, and 0) and are therefore well-suited to data-limited systems. Specifically, we examined community-wide responses to scenarios in which bivalve cultivation effort increased for three different bivalve species (Manila clam Venerupis philippinarum, Pacific oyster Crassostrea gigas, and geoduck Panopea generosa). Further, we evaluated community-wide responses to the removal of benthic bivalve predators, a future increase in nutrient loadings, and combinations of these scenarios acting simultaneously. The scenarios enabled identification of potential trade-offs between increased aquaculture and shifts in the abundance of community members and assessment of the possible effects of different management actions. We also analysed the QNM to identify key interactions that influence the sign outcome of community responses to press perturbations, highlighting potential points for management intervention and linkages deserving of more focused quantitative study. QNMs are mathematically robust and highly flexible, but remain underutilized. We suggest that they may serve as valuable tools for supporting ecosystem approaches to aquaculture.
机译:预测水产养殖发展对沿海生态系统的影响仍然具有挑战性,特别是对于数据有限的系统而言,并且需要用于解释复杂生态相互作用的工具来支持水产养殖的生态系统方法。在这里,我们使用定性网络模型(QNMs)来研究南普吉特海湾(South Puget Sound)(美国华盛顿的一个大型河口系统)增加双壳类水产养殖的潜在社区影响。 QNM是形式化的概念模型,只需要对组成系统的变量如何相互作用(即相互作用的符号:+,-和0)进行定性了解,因此非常适合于数据受限的系统。具体来说,我们研究了社区对三种不同双壳类物种(马尼拉蛤仔Venerupis philippinarum,太平洋牡蛎Crassostrea gigas和象拔蚌Panopea属)的双壳类栽培努力增加的情景的反应。此外,我们评估了社区范围内对底栖双壳类捕食者被捕食的反应,未来养分含量的增加以及这些情景同时起作用的组合。这些方案使人们能够确定水产养殖增加与社区成员数量变化之间的潜在权衡,并评估不同管理行动的可能影响。我们还分析了QNM,以识别影响社区对新闻界反应的反应结果的关键相互作用,强调管理干预和联系的潜在要点,值得重点研究。 QNM具有强大的数学功能和高度的灵活性,但仍未得到充分利用。我们建议它们可以作为支持水产养殖生态系统方法的宝贵工具。

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