Abstract
Benthic infaunal species and communities have been extensively used to evaluate quality of the marine environment. Within the MSFD, community composition is addressed most commonly through Descriptor 6 (Seafloor integrity), criterion 6.2 (Condition of benthic communities). At the same time, the Directive has stipulations for addressing and assessing indicators linked with pressures in an explicitly spatial manner. At larger scales, achieving this through point sampling may be impractical or unfeasible; hence predictive methods are being increasingly employed to produce the large scale spatial data that are often required for marine spatial planning and management. The aim of the current work was to develop statistical and spatial modelling tools that can predict the distribution of soft-sediment benthic polychaetes in the Aegean coast of Turkey. To do that, we employed Species Archetype Models (SAMs), a novel analytical and modelling framework which uses mixture models to cluster species responses to the environment, producing a number of “archetypal” responses assumed to represent species with similar ecological/physiological tolerances. Polychaete presence/absence data were obtained from the literature and modelling was performed against environmental variables reflecting the main natural and anthropogenic gradients in the region. The resulting models are interpreted in light of the sensitivity/tolerance classification scheme for benthic invertebrates. Three Species Archetypes were identified through the analysis. In brief, Species Archetype 1 consists of the most prevalent species in the dataset and primarily follows the salinity and temperature gradients. Species Archetype 2, present in the central and southern Aegean, is dominated by sensitive and indifferent species and responds negatively to chlorophyll a, whereas Species Archetype 3 represents mostly tolerant and opportunistic polychaetes with increased probability of occurrence in eutrophic, shallow, inshore areas throughout the region. Predictive performance was constrained by the information contained in our data. These results from a limited data set show promise that SAMs as a modelling tool can offer valuable insights into patterns of benthic species distribution and coexistence and increase our capacity to provide predictive advice.
Highlights
The Marine Strategy Framework Directive is the current legal framework under which EU Member States are required to assess and protect the health of the marine environment with the ultimate target of achieving “Good Environmental Status” (EU, 2008)
Initial model selection was performed for values of G ranging from 1 to 8 and the number of Archetypes that minimized the Bayesian Information Criterion was G = 3 (BIC = 5727, Table S1)
Archetype membership for most of the species was well estimated with probability values close to 1, for Species Archetype 1 (Table S1)
Summary
The Marine Strategy Framework Directive is the current legal framework under which EU Member States are required to assess and protect the health of the marine environment with the ultimate target of achieving “Good Environmental Status” (EU, 2008). The Directive has stipulations for addressing and assessing indicators linked with pressures in an explicitly spatial manner This has a number of implications for the design of monitoring and assessment strategies, starting from defining meaningful and relevant ecological scales to demonstrate state-pressure links (Lynam et al, 2015) and establish the “naturalness” or natural background variability of the system in order to set reference conditions for assessment or environmental targets for management (Van Hoey et al, 2010).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
