Benthic Ecosystem Functioning across Arctic Shelves, Slopes and Basins

Arctic shelves like the southern Chukchi Sea, the Bering Shelf and the Barents Sea exhibit some of the highest densities of benthic (i.e. seafloor associated) invertebrate fauna in the worlds Oceans. This high benthic production supports a variety of upper trophic level consumers, ranging from commercially important fish stocks up to marine mammals. The fuel of this prosperity is the episodic flux of organic matter linked to the brief passage of ice-edge blooms during the seasonal ice melt. Today, the Arctic sea ice cover is decreasing in an unprecedented rate, and an ice free Arctic Ocean in summer is predicted before mid of this century. As sea ice is the main structuring factor of the Arctic environment, these changes will affect the entire Arctic ecosystem. Currently, however, we understand neither the direction nor the mode of these ecological developments sufficiently to predict forthcoming changes in Arctic marine ecosystems functions, goods and services. One obstacle is that we are lacking baseline information about benthic community patterns, from which change can be identified. While in recent years some information was gathered about the structural variability of Arctic benthos, information on the functional variability is lacking almost completely so far. We aim at filling these knowledge gaps by means of a pan-Arctic, integrated approach. The first phase includes the consolidation of all available Arctic macrobenthos (animals >1 mm) and megabenthos (animals >2 cm) data in one data management system. Based on this initial, structural data base we aim at building a functional trait data base, i.e. a collection of the functional characteristics of all species present, comprising information about life history, morphology and behavior. This trait database will be designed as a dynamic tool, accessible for designated experts of Arctic functional ecology and linked to other Arctic specific platforms (e.g. PANABIO project, WoRMS). The second phase of this study focuses on the evaluation of the consolidated data by means of a biological trait approach (BTA). The BTA is a suitable method for describing the ecological functioning of benthic communities and detecting changes in functioning related to changes or gradients in the environment. Degen (2015) applied the BTA for the first time on macrofauna datasets from the Eurasian Arctic deep sea and could show that since 1991 functional changes already happened. The main objectives of this study are to i) analyze benthic functioning on Arctic shelves and basins and along a shelf-slope-basin gradient in the Eurasian and the Amerasian part of the Arctic, to ii) to identify functions and regions most susceptible to changes, and iii) to predict benthic ecosystem functioning in a future, seasonally ice free Arctic Ocean.

An extensive ecological trait database for life on the arctic seafloor improves our understanding of this fascinating ecosystem and the rapid changes it is facing. Arctic shelf seas such as the northern Bering Sea, the Chukchi Sea, and the Barents Sea are among the most productive marine regions of the world's Oceans. The density and diversity of life on the seafloor supports a great variety of consumers on the upper end of the marine food web, including commercially relevant fish stock and marine mammals such as walrus or grey whale. But this food chain is changing rapidly. The Arctic is warming at twice the rate than the global average, und a summer ice-free Arctic Ocean is predicted before the mid of this century. So far we were not able to understand the ecological developments in a way that would allow us to make sound predictions regarding changing ecosystem functions and services. One reason is the lack of ecological baseline data, from which change (current or predicted) can be identified. Our project could fill this knowledge gap for one important component of marine life, the organisms on the seafloor (or zoobenthos). In the first working step a dataset of about 1000 sampling stations and associated metadata was compiled vie the collaboration with international experts, covering large parts of the atlantic and the pacific side of the Arctic Ocean. In the next working step ecological information of all taxa occurring at these stations was compiled via literature research and communication with experts. An interactive, web-based trait database was developed (The Arctic Traits Database: www.univie.ac.at/arctictraits) in order to make this vast amount of ecological information freely accessible to the scientific community. This database enables the rapid download of ecological information, but also the interactive exchange and communication among users. Another feature is the use of a coding system, that allows to download trait information also in form of a numerical code that can be directly incorporated into statistical software. The underlying code of the database itself was also published in order to foster the development of trait databases in other working groups or fields of research. In the third working step the station data and the ecological data are combined and analyzed via trait-based approaches. In doing so we can get insight in how similar or different the ecological patterns are between the pacific and the atlantic side of the Arctic, or between shallow and deeper regions. Also we can find out which regions are robust and which are more sensitive to the ongoing changes we observe in the Arctic. This last working step is currently still in progress.