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: Increasing anthropogenic activities on land and at sea underline the demand for easily applicable indices to effectively predict human mediated changes in ecosystem functioning. Here, we propose a novel bioirrigation index (IPc) that is based on body mass, abundance, burrow type, feeding type and injection pocket depth of bottom dwelling animals. Results from both community and single-species experimental incubations indicate that IPc is able to predict the bioirrigation rate in different sediment types (mud, fine sand, sand). Further, IPc increased the predictability of biogeochemical cycling (i.e. changing concentrations of phosphate, silicate, ammonium, nitrate and nitrite) under different environmental conditions (i.e. sediment type, temperature, faunal inventory, gradients across the sediment water interface), compared to trait based bioturbation potential (BPc). The trait-based index thus demonstrated robustness in the prediction of animal-mediated functional processes that support biogeochemical functions. Additionally our results confirm that biogeochemical cycling is more closely linked to irrigation traits than to sediment reworking traits. Based on these findings we argue that trait-based indices provide a useful tool for the prediction of ecosystem processes as effect traits provide a direct link to the behavioral mechanisms that drive ecosystem functioning.

Description: As the EU’s commitment to renewable energy is projected to grow to 20% of energy generation by 2020, the use of marine renewable energy from wind, wave and tidal resources is increasing. This literature review (233 studies) (i) summarizes knowledge on how marine renewable energy devices affect benthic environments, (ii) explains how these effects could alter ecosystem processes that support major ecosystem services and (iii) provides an approach to determine urgent research needs. Conceptual diagrams were set up to structure hypothesized cause-effect relationships (i.e. paths). Paths were scored for (i) temporal and spatial scale of the effect, (ii) benthic sensitivity to these effects,(iii) the effect consistency and iv) scoring confidence, and consecutively ranked. This approach identified prominent knowledge gaps and research needs about (a) hydrodynamic changes possibly resulting in altered primary production with potential consequences for filter feeders, (b) the introduction and range expansion of non-native species (through stepping stone effects) and, (c) noise and vibration effects on benthic organisms. Our results further provide evidence that benthic sensitivity to offshore renewable effects is higher than previously indicated. Knowledge on changes of ecological functioning through cascading effects is limited and requires distinct hypothesis-driven research combined with integrative ecological modelling.