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Development of a mechanistic eutrophication model for wetland management: Sensitivity analysis of the interplay among phytoplankton, macrophytes, and sediment nutrient release

机译:湿地管理机制富营养化模型的发展:植物植物,宏粒和沉积物营养释放相互作用的敏感性分析

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Wetlands are important ecosystems that play a key role in flood control, nutrient sink, shoreline stability, and biodiversity conservation. Considerable attention has been placed globally on the assessment and restoration of degraded wetlands. Of particular concern is the Cootes Paradise marsh, one of the most degraded Great Lakes wetlands in Southern Ontario, which has experienced a 90% decline in macrophyte coverage over the past 50 years. In this study, we present a wetland eutrophication model that explicitly accounts for the ecological interplay among phytoplankton, macrophytes, and nutrient release from the sediments. We first reviewed the pertinent literature to compile the most commonly used macrophyte mathematical formulations and plausible parameter ranges of their major ecophysiological processes, adaptive strategies, and ecosystem functional roles, such as resource (nutrient, light, and oxygen) limitation, refuge effects, and allelopathic interactions. We then used two sensitivity analysis methods: conventional multiple-linear regression and Self-Organizing Maps (SOM) to evaluate the ability of our mechanistic model to capture different facets of the wetland functioning, including a potential non-linear shift from a turbid phytoplankton-dominated to a clear macrophyte-dominated state. Our analysis showed that the residual variability of the linear models varied from 7% to 37%, when ecological parameters are considered in the sensitivity analysis, and thus SOM analysis is more suitable to elucidate complex non-linear patterns and identify model sensitivity. Parameters related to the characterization of sediment processes (sediment porosity and vertical diffusivity) appear to be influential in shaping model predictions for variables of management interest, such as ambient total phosphorus (Tau Rho) or chlorophyll a (Chia) concentrations, and macrophyte abundance. Our study also showed that the ability of submerged macrophytes to exploit the available under
机译:湿地是在防洪,营养水槽,海岸线稳定和生物多样性保护中发挥关键作用的重要生态系统。在全球范围内,在降级和恢复退化湿地的评估和恢复方面已经得到了相当大的关注。特别关注的是Cootes Paradise Marsh是安大略省南部最劣化的大湖泊湿地之一,在过去50年中经历了90%的宏粒覆盖率下降。在这项研究中,我们提出了一种湿地富营养化模型,明确地占浮游植物,宏粒和盐酸植物中的生态相互作用。我们首先审查了相关的文献,编制了其主要生态学过程,适应性策略和生态系统功能作用的最常用的宏观物流数学制剂和合理的参数范围,例如资源(营养,光和氧气)限制,避难效果和化感互动。然后我们使用了两个灵敏度分析方法:传统的多线性回归和自组织地图(SOM)来评估机械模型捕获湿地运作的不同方面的能力,包括来自浑浊浮游植物的潜在非线性偏移 - 占据澄清的宏观物质主导的状态。我们的分析表明,当在敏感性分析中考虑生态参数时,线性模型的残余变化从7%变化到37%,因此SOM分析更适合于阐明复杂的非线性模式并识别模型敏感性。与沉积物过程的表征相关的参数(沉积物孔隙率和垂直扩散率)似乎在成型模型预测中有影响力,用于管理兴趣的变量,例如环境总磷(TAU RHO)或叶绿素A(Chia)浓度,以及宏观物质丰富。我们的研究还表明,淹没宏观物质剥削可用的能力

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