ICES CM 2012/A:06 Ecological resilience research in practice: the experience of the Barents Sea Ecosystem Resilience project (BarEcoRe) Benjamin Planque, Grégoire Certain, Kathrine Michalsen, Magnus Wiedmann, Susanne Kortsch, Lis Lindal Jørgensen, Raul Primicerio, Michaela Aschan, Padmini Dalpadado, Mette Skern-Mauritzen, Edda Johannesen The BarEcoRe project investigates the resilience of the Barents Sea Ecosystem under global environmental changes. Studying resilience of marine ecosystems is fundamental in the current context of climate change and intense fishing pressure, but the theoretical framework and the practical tools to define, quantify and monitor resilience are still being developed. So far, the BarEcoRe project has studied several aspects of the Barents Sea ecosystem structure and function with a view to contribute to a better understanding, monitoring and projection of the resilience of this system. In this presentation, we report on the aspects of resilience that are specifically addressed during the BarEcoRe project. We present how some of the results of the BarEcoRe project can contribute to resilience research through either dynamical or structural approaches. This collection of research topics reveals the diversity of aspects that need to be considered for resilience studies conducted at the ecosystem level. Keywords: ecosystem resilience, taxonomic diversity, functional diversity, food-web topology, community structure, macro-ecological models, spatial distribution models Contact author: Benjamin Planque, Institute of Marine Research, POSTBOKS 6404, 9294 Tromsø, Norway. E- mail: [email protected], Phone: +47 77609721, Fax: +47 77609001 1 Aim anD scope of BarEcoRe What controls the resilience of the Barents Sea ecosystem? How does it vary with time and space? Can we anticipate possible future changes in the resilience of the Barents Sea? These were the general questions which motivated the BarEcoRe project which began in June 2010 and will terminate in May 2013. BarEcoRe, which stands for Barents Sea Ecosystem resilience under global environmental change, is a research project in applied ecology with the initial goal to evaluate the effects of global environmental change on the future structure and resilience of the Barents Sea ecosystem. BarEcoRe was initially structured around five questions: • What are the key characteristics of past temporal and spatial variations in fish and benthos communities and how are these related to past climate variability and fishing pressure? • How does climate variability and change propagate through the Barents Sea ecosystem and influences species interactions? • How can the combined effects of fisheries and climate modify the spatial distribution of plankton, benthos and fish species in the Barents Sea? • What determines vulnerability or resilience of the Barents Sea ecosystem and how will these be affected by possible future changes in climate and fisheries regimes? • Can we detect early warning signals and can we evaluate management strategies with regards to ecosystem resilience? Addressing these questions requires an appropriate combination of theoretical framework, numerical tools and field data. On the basis of the experience acquired during the BarEcoRe project, we report below what we have identified as the key fundamentals to study ecosystem resilience in practice. Ecosystem monitoring Monitoring multiple components of the ecosystem is paramount to investigations of ecosystem resilience. The Barents Sea benefits from a long history of monitoring, from physics to whales. During the last two decades the development of the ‘ecosystem approach to fisheries management’ led to an evolution in the recommendation for collection of oceanic data (FAO, 2003). In the Barents Sea, this resulted in the establishment of a dedicated ecosystem surveys in the early 2000’s (Olsen et al., 2011). The Barents Sea ecosystem survey turned out to be the essential primary data source for this project. The key elements of the data collection include: • Simultaneous collection of data across many trophic levels, including phytoplankton, zooplankton, benthos, fish, mammals and birds, • Collection of physical and chemical data, • taxonomic identification at a high resolution and with quality check, • large spatial coverage (>1 million square nautical miles), • Annual repetition over multi-decadal periods Practical approaches to resilience The literature on resilience is rich, spans a wide range of disciplines sometimes far away from ecology, and may not always be consistent with the way resilience is understood, defined and eventually quantified (Strunz, 2012). In ecological studies, resilience is usually broadly defined as ‘the ability of a system to absorb disturbances and still maintain structure and functions’. But such definition is too vague to be practical for applied quantitative ecological research in the Barents Sea. 2 In the BarEcoRe project, we attempted to classify concepts and metrics related to resilience according to their applicability in quantitative ecology (Planque et al., poster A:20, this conference). We identify a first class of resilience-related concepts that are often conceptually vague but useful to promote creative thinking, transdisciplinary exchanges, and participative processes for complex problem solving. These include for example terms such as identity, adaptability and transformability. On the other side, precision is necessary to ensure scientific rather than faith based thinking, to set the limits of validity of particular concepts and to ensure testability of concepts against empirical evidence. These criteria are used to define a second class of concepts of direct relevance to quantitative ecology. These can be further divided into structural and dynamic approaches to resilience. The structural approach to resilience relies on a couple of paradigms borrowed from the literature on diversity-stability relationships, functional diversity and trophic network structure. It is currently the only available framework allowing the use of the resilience concept in large ecosystems composed of hundreds or thousands of species. Structural studies of resilience are typically concerned with the measurement of diversity, redundancy and modularity of ecosystem components (Levin and Lubchenco, 2008). The dynamic approach to resilience comprises temporal analysis of systems close to equilibrium (as is the case for return rate and elasticity) or in transition between multiple stable states (e.g. tipping points, hysteresis and regime shifts). In practice dynamic studies are most conducted on small, closed systems which dynamics is well known and for which equilibrium points can be defined, usually on the basis of simple mathematical models (Scheffer et al., 2001). Examples of results Spatial patterns of biodiversity How to choose a proper set of metrics to describe the structural properties of the Barents Sea biodiversity, how to compute and aggregate them at a spatial scale consistent with management needs, and how to interpret them in the context of resilience? To address these questions, we analysed the spatial patterns of biodiversity across trophic levels and within and across benthic, demersal and pelagic communities, based on the Barents Sea ecosystem survey data from 2004 – 2008. The Barents Sea was geographically divided in several polygons, taken as homogeneous ecosystem sub-units. For each sub-unit, environmental and biological data were aggregated, and structural properties of resilience, i.e. biodiversity metrics, were computed. In addition, environmental descriptors including physico-chemical descriptors, productivity, zooplankton biomass, and fishing pressure where aggregated in the same geographical sub-units in order to provide the context within which biodiversity metrics can be interpreted. The use of several taxonomic, phylogenetic and functional biodiversity metrics was considered for 4 major communities: benthic, demersal, pelagic, and top predators. For each metric/community combination, total (γ) diversity within a polygon can be partitioned between α- (intra-site) and β- (inter-site) component, which can be interpreted as local and spatial measures of diversity, respectively (Figure 1). Additionally, topological properties of the food web were investigated, offering measures of the food web organisation within each polygons at the ecosystem scale. 3 Figure 1. Spatial distribution of Hill’s alpha and beta taxonomic diversity in the sub-regions of the Barents Sea for the demersal fish community (2004-2009). The preliminary, methodological results indicate that: i) Although there is a large range of diversity metrics available on taxonomic, phylogenetic and functional diversity, many where highly correlated. Multivariate statistics suggested that most information was retained by using a couple of metrics, one for the α-diversity and one for the β-diversity; ii) presence – absence data clearly lacked sensitivity in comparison to abundance data; iii) numbers of individuals and biomass data gave different biodiversity patterns. From a functional point of view, it can be argued that biomass is more important than numbers, and biomass is also more frequently measured than numbers during the survey. Hence, final analyses will preferably be based on biomass-data. iv) The use of polygons, identified to enclose relatively homogenous areas, provided a useful framework for aggregating the data across communities. Multivariate analyses demonstrated that