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首页> 外文期刊>Ecology and Evolution >Modeling and predicting the growth of the mussel, Mytilus edulis: implications for planning of aquaculture and eutrophication mitigation
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Modeling and predicting the growth of the mussel, Mytilus edulis: implications for planning of aquaculture and eutrophication mitigation

机译:贻贝,贻贝的生长的建模和预测:对水产养殖和富营养化规划的影响

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AbstractThe increased pressure on the marine ecosystems highlights the need for policies and integrated approaches for sustainable management of coastal areas. Spatial planning based on geographic information of human activities, ecological structures and functions, and their associated goods and services is a fundamental component in this context. Here, we evaluate the potential of predictive modeling to provide spatial data on one ecosystem function, mussel growth for use in such processes. We developed a methodology based on statistical modeling, spatial prediction, and mapping for the relative growth of the blue mussel, Mytilus edulis. We evaluated the performance of different modeling techniques and classification schemes using empirical measurements of growth from 144 sampling sites and data on biological, chemical, and physical predictors. Following comparisons of the different techniques and schemes, we developed random forest models to predict growth along the Swedish west coast. Implemented into GIS the best model produced in this study predicts that low, intermediate, and high growth rates can be expected in 53%, 32%, and 15% of modeled area, respectively. The results of this study also suggest that the nature and quality of predictor data hold the key to improving the predictive power of models. On a more general note, this study exemplifies a feasible approach based on measuring, modeling, and mapping for obtaining scientifically based spatial information on ecosystem functions and services affected by a complex set of factors. Such information is fundamental for maritime spatial planning and ecosystem-based management and its importance is likely to increase in the future. Because of its close link to nutrient assimilation and production yield, site-specific information of soft tissue growth such as the map of predicted growth rate developed in this study can be used as a tool for optimizing actions aimed at mitigating eutrophication and aquaculture operations and in maritime spatial planning processes of coastal areas.
机译:摘要对海洋生态系统的压力越来越大,凸显了对沿海地区可持续管理的政策和综合方法的需求。在这种情况下,基于人类活动,生态结构和功能及其相关的商品和服务的地理信息的空间规划是基本要素。在这里,我们评估了预测建模的潜力,以提供有关一种生态系统功能(贻贝生长)的空间数据以用于此类过程。我们开发了一种基于统计建模,空间预测和绘图的方法,用于蓝贻贝(Mytilus edulis)的相对生长。我们使用来自144个采样点的增长的经验测量以及有关生物学,化学和物理预测因子的数据,评估了不同建模技术和分类方案的性能。在比较了不同的技术和方案之后,我们开发了随机森林模型来预测瑞典西海岸的生长。将这项研究中产生的最佳模型实施到GIS中,可以预测分别在模型面积的53%,32%和15%处实现低,中和高增长率。这项研究的结果还表明,预测数据的性质和质量是提高模型预测能力的关键。总的来说,这项研究举例说明了一种基于测量,建模和制图的可行方法,用于获得有关受一系列复杂因素影响的生态系统功能和服务的科学依据的空间信息。此类信息对于海洋空间规划和基于生态系统的管理至关重要,并且其重要性在未来可能会增加。由于它与养分吸收和产量密切相关,因此本研究中开发的特定位置的软组织生长信息(例如预测的生长速率图)可以用作优化旨在减轻富营养化和水产养殖操作的措施的工具。沿海地区的海洋空间规划过程。

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