Beschreibung: Marine benthic organisms living in shelf seas of the Siberian Arctic are impacted severely by the pronounced consequences of climate change. Polar ecosystems are used to stable conditions and even small changes could influence benthic communities, food webs, and ecosystem functions. Regional patterns in community composition result from the interaction between marine organisms and their local environment. In this study, these relationships are investigated in order to understand how climate change affect Arctic biodiversity in particular.

Beschreibung: Marine benthic organisms living in shelf seas of the Siberian Arctic are impacted severely by the pronounced consequences of climate change. Polar ecosystems are used to stable conditions and even small changes could influence benthic communities, food webs, and ecosystem functions. Regional patterns in community composition result from the interaction between marine organisms and their local environment. In this study, these relationships are investigated in order to understand how climate change affect Arctic biodiversity in particular.

Beschreibung: Climate change and its consequences pressure the Arctic Siberian shelf region and impact marine benthic organisms severely. Polar ecosystems are used to long-term stable conditions and even small changes could have wide-ranging effects on benthic communities, food webs, and ecosystem functions. The interaction between marine organisms and their local environment generate different regional patterns in community composition. Analysing these relationships and identifying their spatial scales is an essential step in understanding how climate change affects marine biodiversity and in guiding future conservation and management strategies. To achieve this purpose, we combine benthic community data (412 species in 228 samples) from 10 different regions within the Siberian Arctic and selected environmental parameters (e.g. bathymetry, sea-ice cover and temperature) and employ recent multivariate spatial modelling techniques to study the composition and distributional patterns of the Artic Siberian macrobenthos. The ecological community data necessary for this investigation originate from several “TRANSDRIFT” expeditions in various seas in the Arctic Siberian shelf from 1992 until 2014. The abiotic data is provided by public online databases. We then employ Moran’s eigenvector mapping (MEM), which is a multivariate modelling framework, to model the spatial structure of our benthic and environmental data. MEM detects the different broad, meso and fine spatial scales within a community, it describes the relationship between spatial structure and abiotic factors and identifies which species are associated with which spatial scale. This analysis reveals that mainly environmental variables from the water column (e.g. water depths, sea-ice cover, temperature) describe the composition of macrobenthic communities on broader scales (〉50 kilometres). Environmental factors describing the seafloor (e.g. sediment type) are more responsible for structuring the community on smaller scales (metres up to a few kilometres).

Beschreibung: Multiple environmental factors control benthic community patterns, and their relative importance varies with spatial scale. Since this variation is difficult to evaluate quantitatively, extensive sampling across a broad range of spatial scales is required. Here, we present a first case study on Southern Ocean shelf benthos, in which mega-epibenthic communities and biota-environment relationships have been explored at multiple spatial scales. The analyses encompassed 20 seafloor, water-column, and sea-ice parameters, as well as abundances of 18 mega-epibenthic taxa in a total of 2799 high-resolution seabed images taken at 28 stations at 32–786 m depth off the northern Antarctic Peninsula. Based on a priori nesting of sampling stations into ecoregions, subregions, and habitats, analyses indicated most pronounced patchiness levels at finest (within transects among adjacent seabed photos) and largest (among ecoregions) spatial scale considered. Using an alternative approach, explicitly involving the spatial distances between the geo-referenced data, Moran’s Eigenvector mapping (MEM) classified the continuum of spatial scales into four categories: broad (〉 60 km), meso (10–60 km), small (2–10 km), and fine (〈 2 km). MEM analyses generally indicated an increase in mega-epibenthic community complexity with increasing spatial scale. Moreover, strong relationships between biota and environmental drivers were found at scales of 〉 2 km. In contrast, few environmental variables contributed to explaining biotic structures at finer scales. These are likely rather determined by nonmeasured environmental variables, as well as biological traits and interactions that are assumed to be most effective at small spatial scales.

Beschreibung: Adding fertiliser to sediments is an established way of studying the effects of eutrophication but a lack of consistent methodology, reporting on enrichment levels, or guidance on application rates precludes rigorous synthesis and meta-analysis. We developed a simple enrichment technique then applied it to 28 sites across an intertidal sandflat. Fertiliser application rates of 150 and 600 g N m−2 resulted in pore water ammonium concentrations respectively 1–110 and 4–580 × ambient, with greater elevations observed in deeper (5–7 cm) than surface (0–2 cm) sediments. These enrichment levels were similar to eutrophic estuaries and were maintained for at least seven weeks. The high between-site variability could be partially explained by the sedimentary environment and macrofaunal community (42%), but only at the high application rate. We suggest future enrichment studies should be conducted in situ across large environmental gradients to incorporate real world complexity and increase generality of conclusions.

Beschreibung: This was the first workshop on traits of Arctic benthic fauna. An international group of participants discussed how to use species traits in Arctic benthic sciences. It is intended that a review-paper will be published soon.

Beschreibung: The degradation of ecosystems is often associated with losses of large organisms and the concomitant losses of the ecological functions they mediate. Conversely, the resilience of ecosystems to stress is strongly influenced by faunal communities and their impacts on processes. Denitrification in coastal sediments is a process that may provide ecosystem resilience to eutrophication by removing excess bioavailable nitrogen. Here, we conducted a large-scale field experiment to test the effect of macrofaunal community composition on denitrification in response to two levels of nutrient enrichment at 28 sites across a biologically heterogeneous sandflat. After 7 weeks of enrichment, we measured denitrification enzyme activity (DEA) along with benthic macrofaunal community composition and environmental variables. We normalised treatment site specific DEA values by those in ambient sediments (DEACN) to reveal the underlying response across the heterogeneous landscape. Nutrient enrichment caused reductions in DEACN as well as functional changes in the community; these were both more pronounced under the highest level of nutrient loading (on average DEACN was reduced by 34%). The degree of suppression of DEACN following moderate nitrogen loading was mitigated by a key bioturbating species, but following high nitrogen loading (which reduced the key species density) the abundance and diversity of other nutrient processing species were the most important factors alleviating negative effects. This study provides a prime example of the context-dependent role of biodiversity in maintaining ecosystem functioning, underlining that different elements of biodiversity can become important as stress levels increase. Our results emphasise that management and conservation strategies require a real-world understanding of the community attributes that facilitate nutrient processing and maintain resilience in coastal ecosystems.