Description: Marine benthic ecosystems are difficult to monitor and assess, which is in contrast to modern ecosystem-based management requiring detailed information at all important ecological and anthropogenic impact levels. Ecosystem management needs to ensure a sustainable exploitation of marine resources as well as the protection of sensitive habitats, taking account of potential multiple-use conflicts and impacts over large spatial scales. The urgent need for large-scale spatial data on benthic species and communities resulted in an increasing application of distribution modelling (DM). The use of DM techniques enables to employ full spatial coverage data of environmental variables to predict benthic spatial distribution patterns. Especially, statistical DMs have opened new possibilities for ecosystem management applications, since they are straightforward and the outputs are easy to interpret and communicate. Mechanistic modelling techniques, targeting the fundamental niche of species, and Bayesian belief networks are the most promising to further improve DM performance in the marine realm. There are many actual and potential management applications ofDMsin the marine benthic environment, these are (i) earlywarning systems for species invasion and pest control, (ii) to assess distribution probabilities of species to be protected, (iii) uses in monitoring design and spatial management frameworks (e.g. MPA designations), and (iv) establishing long-term ecosystem management measures (accounting for future climate-driven changes in the ecosystem). It is important to acknowledge also the limitations associated with DM applications in a marine management context as well as considering new areas for futureDMdevelopments. The knowledge of explanatory variables, for example, setting the basis for DM, will continue to be further developed: this includes both the abiotic (natural and anthropogenic) and the more pressing biotic (e.g. species interactions) aspects of the ecosystem.

Description: Understanding the distribution and structure of biotopes is essential for marine conservation according to international legislation, such as the European Marine Strategy Framework Directive (MSFD). The biotope ‘Sea Pen and Burrowing Megafuna Communities’ is included in the OSPAR list of threatened and/or declining habitats. Accordingly, the MSFD prescribes a monitoring of this biotope by the member states of the EU. In the German North Sea, however, the distribution and spatial extent of this biotope as well as the structuring of its benthic species inventory is unknown. We used an extensive geo-referenced dataset on occurrence, abundance and biomass of the benthic infauna of the south-eastern North Sea to estimate the distribution of the biotope and to characterize the associated infauna assemblages. Sediment preferences of the burrowing megafauna, comprising decapod crustaceans and echiurids, were identified and the core distribution areas of the burrowing megafauna were modelled using Random Forests. Clusters of benthic infauna inside the core distribution areas were identified by fuzzy clustering. The burrowing megafauna occurred on a wide range of sediments with varying mud contents. The core distribution area of the burrowing megafauna was characterized by elevated mud content and a water depth of 25–55 m. The analysis of the benthic communities and their relation to sedimentological conditions identified four infauna clusters of slightly varying species composition. The biotope type ‘Sea Pen and Burrowing Megafuna Communities’ is primarily located inside the paleo valley of the river Elbe and covers an area of 4980 km2. Dedicated monitoring will have to take into account the spatial extent and the structural variability of the biotope. Our results can provide a baseline for the evaluation of the future development of the environmental status of the biotope. The maps generated herein will facilitate the communication of information relevant for environmental management to authorities and policy makers.