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Deriving nutrient criteria to support ʽgoodʼ ecological status in European lakes: An empirically based approach to linking ecology and management

机译:得出支持欧洲湖泊良好生态状况的营养标准:将生态学与管理联系起来的基于经验的方法

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摘要

European water policy has identified eutrophication as a priority issue for water management. Substantial progress has been made in combating eutrophication but open issues remain, including setting reliable and meaningful nutrient criteria supporting ʽgoodʼ ecological status of the Water Framework Directive.The paper introduces a novel methodological approach - a set of four different methods - that can be applied to different ecosystems and stressors to derive empirically-based management targets. The methods include Ranged Major Axis (RMA) regression, multivariate Ordinary Least Squares (OLS) regression, logistic regression, and minimising the mismatch of classifications. We apply these approaches to establish nutrient (nitrogen and phosphorus) criteria for the major productive shallow lake types of Europe: high alkalinity shallow (LCB1; mean depth 3–15 m) and very shallow (LCB2; mean depth < 3 m) lakes.Univariate relationships between nutrients and macrophyte assessments explained 29–46% of the variation. Multivariate models with both total phosphorus (TP) and total nitrogen (TN) as predictors had higher R2 values (0.50 for LCB1 and 0.49 for LCB2) relative to the use of TN or TP singly. We estimated nutrient concentrations at the boundary where lake vegetation changes from ʽgoodʼ to ‘moderate’ ecological status. LCB1 lakes achieved ʽgoodʼ macrophyte status at concentrations below 48–53 μg/l TP and 1.1–1.2 mg/l TN, compared to LCB2 lakes below 58–78 μg/l TP and 1.0–1.4 mg/l TN. Where strong regression relationships exist, regression approaches offer a reliable basis for deriving nutrient criteria and their uncertainty, while categorical approaches offer advantages for risk assessment and communication, or where analysis is constrained by discontinuous measures of status or short stressor gradients.We link ecological status of macrophyte communities to nutrient criteria in a user-friendly and transparent way. Such analyses underpin the practical actions and policy needed to achieve ʽgoodʼ ecological status in the lakes of Europe.
机译:欧洲水政策已将富营养化确定为水管理的优先事项。在防治富营养化方面取得了实质性进展,但仍存在未解决的问题,包括制定可靠且有意义的营养标准,以支持《水框架指令》的“良好”生态状况。本文介绍了一种新颖的方法论方法-四种不同的方法集-可应用于不同的生态系统和压力源,以得出基于经验的管理目标。这些方法包括远程长轴(RMA)回归,多元普通最小二乘(OLS)回归,逻辑回归和最小化分类的不匹配。我们采用这些方法为欧洲主要的生产性浅湖类型建立了营养(氮和磷)标准:高碱度浅湖(LCB1;平均深度3-15 m)和非常浅湖(LCB2;平均深度<3 m)。营养素和大型植物评估之间的单变量关系解释了29–46%的变化。相对于单独使用TN或TP,以总磷(TP)和总氮(TN)为预测指标的多元模型具有更高的R 2 值(LCB1为0.50,LCB2为0.49)。我们估算了湖泊植被从“好”状态变为“中等”生态状态的边界处的养分浓度。与低于58-78μg/ l TP和1.0-1.4μmg/ l TN的LCB2湖泊相比,LCB1湖泊在48-53μg/ l TP和1.1-1.2μmg/ l TN浓度下获得了良好的大型植物状态。在存在强回归关系的地方,回归方法为得出养分标准及其不确定性提供了可靠的基础,而分类方法为风险评估和交流提供了优势,或者在状态的不连续测量或短压力胁迫梯度限制了分析的情况下,我们将生态状态联系在一起。以一种易于使用且透明的方式将大型植物群落的养分标准纳入营养标准。这些分析为在欧洲湖泊中实现“良好”生态状况所需的实际行动和政策奠定了基础。

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