A fundamental challenge in developing IEAs that reliably inform EBM is to provide assessment tools that are process‐oriented and address whole ecosystem properties, such as biodiversity, that closely relate to ecosystem vulnerability. The above challenge will require an integration of information on demographic characteristics, ecological interactions and ecosystem functions of component species. Trait-based approaches and foodweb analysis can provide the required information, which, if properly
integrated and communicated, will inform EBM on fundamental aspects of ecosystem vulnerability (Levin and Lubchenco, 2008).
The vulnerability of an ecosystem to environmental stress is a function of the sensitivity and adaptive capacity of its components, i.e. species, and of the whole. Among the properties that stand out as core components of ecosystem robustness are functional diversity, functional redundancy and foodweb modularity (Levin and Lubchenco, 2008). To address the areal based Ecosystem Vulnerability Assessment of the Barents Sea demersal resources, we relied on the integration of trait-based approaches and foodweb analysis to assess species and ecosystem properties affecting ecosystem vulnerability. Trait-based approaches break down information on life history, behaviour, and other relevant phenotypic characteristics into response traits and effect (or functional) traits. Response traits determine the vulnerability of a species to a specific environmental stressor like fishing, whereas effect traits provide information on ecosystem functions of species (Lavorel and Garnier, 2002). Response traits data allow to rank species according to their vulnerability, an approach that has been particularly fruitful in the context of assessment of vulnerability to fishing (Le Quesne and Jennings, 2012). Rank data can be averaged across species present in a given area or location to provide a measure of community vulnerability (Wiedmann et al., 2014a). Effect traits data allow to classify species according to their ecosystem functions and provide the basis for the assessment of collective properties of ecosystems such as functional diversity, which affects the adaptive capacity of ecosystems, and functional redundancy, which affects the sensitivity of ecosystems (Wiedmann et al., 2014b). Finally, foodweb data allow to measure species properties, such as centrality, and ecosystem properties, such as foodweb modularity, that depend on the configuration of ecological interactions connecting ecosystem components.
In 2015, the project VULRES performed a vulnerability analysis of the benthos, demersal fish and pelagic fish of the Barents Sea ecosystem. Three prominent properties of Barents Sea demersal fish communities influencing ecosystem vulnerability to trawling all displayed substantial spatial variability with clear geographical patterns (Figure 2.3.1). Through time (2004–2012), the spatial patterns changed, displaying trends associated with increasing water temperatures and decreasing sea ice coverage. Fish sensitivity to trawling, assessed on the basis of life-history characteristics of fish that affect demographic growth rates, showed a sharp gradient, with average fish sensitivity (averaged ranks) at stations falling rapidly in a Northeast direction (Figure 2.3.1). Fish functional diversity, estimated on the basis of a functional traits dendrogram, displayed a clear gradient with diversity dropping towards the East (Figure 2.3.1). Finally, the average number of fish feeding links (degree centrality) showed a strong reduction towards the North indicating that there is a lower foodweb connectivity in the Arctic reaches of the Barents Sea (Figure 2.3.1).
Figure 2.3.1. Barents Sea demersal fish community in 2004. Fish sensitivity to trawling (left panel), functional diversity (mid panel) and foodweb degree centrality (right panel). Highest values in red, lowest values in blue (circle size is proportional to measured value at a station).
The temporal trends showed a systematic increase in sensitivity, functional diversity and degree centrality towards the North, with the Arctic reaches of the Barents Sea experiencing the most rapid and extensive changes in ecosystem vulnerability (Figure 2.3.2).
Figure 2.3.2. Barents Sea demersal fish community in 2012. Fish sensitivity to trawling (left panel), functional diversity (mid panel) and foodweb degree centrality (right panel). Highest values in red, lowest values in blue (circle size is proportional to measured value at a station).
The pelagic fish community (pelagic trawl catches) also displayed extensive spatial variation with regard to the above three properties, with patterns partly resembling those observed for demersal fish (Figure 2.3.3). The temporal changes in spatial patterns were also substantial, and apparently related to the climatic variability and to the fluctuating abundances of some of the dominant pelagic fish species.
Figure 2.3.3. Barents Sea pelagic fish community in 2004. Fish sensitivity to trawling (left panel), functional diversity (mid panel) and foodweb degree centrality (right panel). Highest values in red, lowest values in blue (circle size is proportional to measured value at a station).
The VULRES findings on Barents Sea ecosystem vulnerability assessment highlight strong spatial heterogeneity in vulnerability of all functional groups currently included in the analyses. Further, the temporal trends show a strong influence of climate variability resulting in systematic change in spatial patterns of vulnerability. The findings have clear implications for an ecosystem approach to spatial management of the Barents Sea.