Using ecological models to assess ecosystem status in support of the European Marine Strategy Framework Directive. (November 2015)

• Record Type: Journal Article
• Authors: 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.
• Is Part Of: Ecological indicators. Volume 58(2015)
• Page Start: 175
• Page End: 191
• Publication Date: 2015-11
• Subjects: MSFD -- Marine ecosystems -- Ecological models -- Model-derived indicators -- Pressures -- Habitats -- Biodiversity descriptors; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2015.05.037
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: We review the current capabilities of the modelling community to provide information about indicators outlined in the Marine Strategy Framework Directive (MSFD). We identified 44 ecological models with a high prevalence of hydrodynamics–biogeochemistry, species distribution/habitat suitability and bio-optical models. ∼200 indicators were assessed, the majority of which were biomass and physical/hydrological/chemical indicators. Biodiversity and food webs MSFD descriptors were better addressed than the non-indigenous species and sea floor integrity descriptors. Out of 12 criteria and 21 MSFD indicators only three indicators were not addressed by the models reviewed. Abstract: 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-optical (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.