Data to investigate the role of Pomatoschistus microps in intertidal food webs, sampled off the island of Sylt

Ecological network analysis (ENA) was used to study the effects of Pomatoschistus microps on energy transport through the food web, its impact on other compartments and its possible role as a keystone species in the trophic webs of an Arenicola tidal flat ecosystem and a sparse Zostera noltii bed ecosystem. Three ENA models were constructed: (a) model 1 contains data of the original food web from prior research in the investigated area by Baird et al. (2007), (b) an updated model 2 which included biomass and diet data of P. microps from recent sampling, and (c) model 3 simulating a food web without P. microps. A comparison of energy transport between the different models revealed that more energy is transported from lower trophic levels up the food chain, in the presence of P. microps (models 1 and 2) than in its absence (model 3). Calculations of the keystone index (KSi) revealed the high overall impact (measured as eps_i) of this fish species on food webs. In model 1, P. microps was assigned a low KSi in the Arenicola flat and in the sparse Z. noltii bed. Calculations in model 2 ranked P. microps first for keystoneness and eps_i in both communities, the Arenicola flat and the sparse Z. noltii bed. Taken together, our results give insight into the role of P. microps when considering a whole food web and reveal direct and indirect trophic interactions of this small-sized fish species. These results might illustrate the impact and importance of abundant, widespread species in food webs and facilitate further investigations.

(Table A1) Species list of the high Antarctic Weddell Sea food web

Human-induced habitat destruction, overexploitation, introduction of alien species and climate change are causing species to go extinct at unprecedented rates, from local to global scales. There are growing concerns that these kinds of disturbances alter important functions of ecosystems. Our current understanding is that key parameters of a community (e.g. its functional diversity, species composition, and presence/absence of vulnerable species) reflect an ecological network's ability to resist or rebound from change in response to pressures and disturbances, such as species loss. If the food web structure is relatively simple, we can analyse the roles of different species interactions in determining how environmental impacts translate into species loss. However, when ecosystems harbour species-rich communities, as is the case in most natural systems, then the complex network of ecological interactions makes it a far more challenging task to perceive how species' functional roles influence the consequences of species loss. One approach to deal with such complexity is to focus on the functional traits of species in order to identify their respective roles: for instance, large species seem to be more susceptible to extinction than smaller species. Here, we introduce and analyse the marine food web from the high Antarctic Weddell Sea Shelf to illustrate the role of species traits in relation to network robustness of this complex food web. Our approach was threefold: firstly, we applied a new classification system to all species, grouping them by traits other than body size; secondly, we tested the relationship between body size and food web parameters within and across these groups and finally, we calculated food web robustness. We addressed questions regarding (i) patterns of species functional/trophic roles, (ii) relationships between species functional roles and body size and (iii) the role of species body size in terms of network robustness. Our results show that when analyzing relationships between trophic structure, body size and network structure, the diversity of predatory species types needs to be considered in future studies.

Decision evaluation in complex risk network systems (DecernsSDSS) demo and Black River case study

The selection of metrics for ecosystem restoration programs is critical for improving the quality of monitoring programs and characterizing project success. Moreover it is oftentimes very difficult to balance the importance of multiple ecological, social, and economical metrics. Metric selection process is a complex and must simultaneously take into account monitoring data, environmental models, socio-economic considerations, and stakeholder interests. We propose multicriteria decision analysis (MCDA) methods, broadly defined, for the selection of optimal sets of metrics to enhance evaluation of ecosystem restoration alternatives. Two MCDA methods, a multiattribute utility analysis (MAUT), and a probabilistic multicriteria acceptability analysis (ProMAA), are applied and compared for a hypothetical case study of a river restoration involving multiple stakeholders. Overall, the MCDA results in a systematic, unbiased, and transparent solution, informing restoration alternatives evaluation. The two methods provide comparable results in terms of selected metrics. However, because ProMAA can consider probability distributions for weights and utility values of metrics for each criteria, it is suggested as the best option if data uncertainty is high. Despite the increase in complexity in the metric selection process, MCDA improves upon the current ad-hoc decision practice based on the consultations with stakeholders and experts, and encourages transparent and quantitative aggregation of data and judgement, increasing the transparency of decision making in restoration projects. We believe that MCDA can enhance the overall sustainability of ecosystem by enhancing both ecological and societal needs.