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 'good' 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 R 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 'good' to 'moderate' ecological status. LCB1 lakes achieved 'good' 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 'good' ecological status in the lakes of Europe.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6215087PMC
http://dx.doi.org/10.1016/j.scitotenv.2018.09.350DOI Listing

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