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Using ecological models to assess ecosystem status in support of the European Marine Strategy Framework Directive

Piroddi, Chiara; Teixeira, Heliana; Lynam, Christopher P.; Smith, Chris; Alvarez, Maria C.; Mazik, Krysia; Andonegi, Eider; Churilova, Tanya; Tedesco, Letizia; Chifflet, Marina; Chust, Guillem; Galparsoro, Ibon; Garcia, Ana Carla; Kämäri, Maria; Kryvenko, Olga; Lassalle, Geraldine; Neville, Suzanna; Niquil, Nathalie; Papadopoulou, Nadia; Rossberg, Axel G.; Suslin, Vjacheslav; Uyarra, Maria C.

Authors

Chiara Piroddi

Heliana Teixeira

Christopher P. Lynam

Chris Smith

Maria C. Alvarez

Eider Andonegi

Tanya Churilova

Letizia Tedesco

Marina Chifflet

Guillem Chust

Ibon Galparsoro

Ana Carla Garcia

Maria Kämäri

Olga Kryvenko

Geraldine Lassalle

Suzanna Neville

Nathalie Niquil

Nadia Papadopoulou

Axel G. Rossberg

Vjacheslav Suslin

Maria C. Uyarra



Abstract

© 2015 The Authors. Published by Elsevier Ltd. The European Union's Marine Strategy Framework Directive (MSFD) seeks to achieve, for all European seas, "Good Environmental Status" (GEnS), by 2020. Ecological models are currently one of the strongest approaches used to predicting and understanding the consequences of anthropogenic and climate-driven changes in the natural environment. We assess the most commonly used capabilities of the modelling community to provide information about indicators outlined in the MSFD, particularly on biodiversity, food webs, non-indigenous species and seafloor integrity descriptors. We built a catalogue of models and their derived indicators to assess which models were able to demonstrate: (1) the linkages between indicators and ecosystem structure and function and (2) the impact of pressures on ecosystem state through indicators. Our survey identified 44 ecological models being implemented in Europe, with a high prevalence of those that focus on links between hydrodynamics and biogeochemistry, followed by end-to-end, species distribution/habitat suitability, bio-opt ical (remote sensing) and multispecies models. Approximately 200 indicators could be derived from these models, the majority of which were biomass and physical/hydrological/chemical indicators. Biodiversity and food webs descriptors, with ∼49% and ∼43% respectively, were better addressed in the reviewed modelling approaches than the non-indigenous species (0.3%) and sea floor integrity (∼8%) descriptors. Out of 12 criteria and 21 MSFD indicators relevant to the abovementioned descriptors, currently only three indicators were not addressed by the 44 models reviewed. Modelling approaches showed also the potential to inform on the complex, integrative ecosystem dimensions while addressing ecosystem fundamental properties, such as interactions between structural components and ecosystems services provided, despite the fact that they are not part of the MSFD indicators set. The cataloguing of models and their derived indicators presented in this study, aim at helping the planning and integration of policies like the MSFD which require the assessment of all European Seas in relation to their ecosystem status and pressures associated and the establishment of environmental targets (through the use of indicators) to achieve GEnS by 2020.

Citation

Piroddi, C., Teixeira, H., Lynam, C. P., Smith, C., Alvarez, M. C., Mazik, K., …Uyarra, M. C. (2015). Using ecological models to assess ecosystem status in support of the European Marine Strategy Framework Directive. Ecological Indicators, 58, 175-191. https://doi.org/10.1016/j.ecolind.2015.05.037

Journal Article Type Article
Acceptance Date May 19, 2015
Online Publication Date Jun 17, 2015
Publication Date 2015-11
Deposit Date Jul 9, 2018
Publicly Available Date Jul 13, 2018
Journal Ecological Indicators
Print ISSN 1470-160x
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 58
Pages 175-191
DOI https://doi.org/10.1016/j.ecolind.2015.05.037
Keywords MSFD; Marine ecosystems; Ecological models; Model-derived indicators; Pressures; Habitats; Biodiversity descriptors
Public URL https://hull-repository.worktribe.com/output/544693
Publisher URL https://www.sciencedirect.com/science/article/pii/S1470160X1500285X?via%3Dihub

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Copyright Statement
© 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).





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