The role of macrozoobenthos for Arctic production and energy flow - The pan-Arctic database project

• Main Authors: Degen, Renate, Jørgensen, Lis L, Dannheim, Jennifer, Boetius, Antje, Brey, Thomas
• Format: Conference Object
• Language: unknown
• Published: 2013
• Subjects: Arctic; Barents Sea; Climate change; Sea ice
• Online Access: https://epic.awi.de/id/eprint/32101/; https://epic.awi.de/id/eprint/32101/1/AF_poster_Degen.pdf; https://hdl.handle.net/10013/epic.40762; https://hdl.handle.net/10013/epic.40762.d001

The Arctic is a hotspot of climate change and shifting parameters like rising seawater temperature or reduction in sea ice extent affect the whole ecosystem. Currently our knowledge of large-scale Arctic ecosystem structure and functioning is insufficient to predict forthcoming changes. The integration of existing biological and ecological data on an Arctic-wide scale would be a major step towards a better view on the whole Arctic biosphere and its dynamics. Within this context, we intend to create a pan-Arctic macro-benthic database that will combine data from many studies in one massive geo-referenced data management system. This system will allow for the identification and analysis of benthic structures (e.g. biodiversity) and processes (e.g. production, metabolism) on large scales and to model the impact of environmental drivers on the benthic system. The inclusion of historical data from the 1930s onwards will add a temporal dimension to all analyses, which may allow for the identification of past trends and shifts in Arctic benthic ecosystems. Building such a database is a long-term task that comprises the following steps:  Data mining: Identify and consolidate all available data (published and unpublished) on Arctic benthic macro-and megafauna in one georeferenced data management system  Quality control: cross-calibrate and standardize taxonomic, geographical and sampling methodology  Create a searchable metadata inventory  Make the database available to the scientific community  Install a continuous data bank update process Here we use a Barents Sea data set (bycatch data from 900 trawl sampling stations, Lis L. Jørgenson, IMR-PINRO Project) to demonstrate how such a database can be applied. We show the spatial distribution of basic benthic community parameters (biomass, biodiversity), of community production and the relationship between community parameters and the environment.