Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/27940
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Deriving nutrient criteria to support 'good' ecological status in European lakes: An empirically based approach to linking ecology and management
Author(s): Poikane, Sandra
Phillips, Geoff
Birk, Sebastian
Free, Gary
Kelly, Martyn G
Willby, Nigel J
Keywords: Environmental Engineering
Waste Management and Disposal
Pollution
Environmental Chemistry
Issue Date: 10-Feb-2019
Date Deposited: 9-Oct-2018
Citation: Poikane S, Phillips G, Birk S, Free G, Kelly MG & Willby NJ (2019) Deriving nutrient criteria to support 'good' ecological status in European lakes: An empirically based approach to linking ecology and management. Science of The Total Environment, 650 (Part 2), pp. 2074-2084. https://doi.org/10.1016/j.scitotenv.2018.09.350
Abstract: 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 
DOI Link: 10.1016/j.scitotenv.2018.09.350
Rights: This article is available under the terms of the Creative Commons Attribution License (CC BY). You may copy and distribute the article, create extracts, abstracts and new works from the article, alter and revise the article, text or data mine the article and otherwise reuse the article commercially (including reuse and/or resale of the article) without permission from Elsevier. You must give appropriate credit to the original work, together with a link to the formal publication through the relevant DOI and a link to the Creative Commons user license above. You must indicate if any changes are made but not in any way that suggests the licensor endorses you or your use of the work.
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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