Multiple configurations and fluctuating trophic control in the Barents Sea food-web

The Barents Sea is a subarctic shelf sea which has experienced major changes during the past decades. From ecological time-series, three different food-web configurations, reflecting successive shifts of dominance of pelagic fish, demersal fish, and zooplankton, as well as varying trophic control have been identified in the last decades. This covers a relatively short time-period as available ecological time-series are often relatively short. As we lack information for prior time-periods, we use a chance and necessity model to investigate if there are other possible configurations of the Barents Sea food-web than those observed in the ecological time-series, and if this food-web is characterized by a persistent trophic control. We perform food-web simulations using the Non-Deterministic Network Dynamic model (NDND) for the Barents Sea, identify food-web configurations and compare those to historical reconstructions of food-web dynamics. Biomass configurations fall into four major types and three trophic pathways. Reconstructed data match one of the major biomass configurations but is characterized by a different trophic pathway than most of the simulated configurations. The simulated biomass displays fluctuations between bottom-up and top-down trophic control over time rather than persistent trophic control. Our results show that the configurations we have reconstructed are strongly overlapping with our simulated configurations, though they represent only a subset of the possible configurations of the Barents Sea food-web.

HYDROTHERMAL-VENT ALVINELLID POLYCHAETE DISPERSAL IN THE EASTERN PACIFIC. 2. A METAPOPULATION MODEL BASED ON HABITAT SHIFTS

Marine organisms typically fall into two main categories: those with a high level of population structuring and those with a low one. The first are often found to be poor dispersers, following isolation by distance or stepping-stone theoretical predictions. The second are commonly associated with high-dispersal taxa and are best described by the island model. Deep-sea hydrothermal vent systems represent a good model for studying one-dimensional metapopulations. Whereas isolation by distance might be expected to be the rule in such a system for species with limited dispersal capabilities, a biological paradox can be observed: an apparent genetic homogeneity in some vent species with short-scale dispersal potential, in a one-dimensional fragmented habitat. This can be explained if one key assumption of the existing models is not met: gene flow between populations and genetic drift may not have the time to equilibrate. Geophysical models revealed that hydrothermal convection is intrinsically unstable, inducing processes of coalescence or splitting of venting areas in a chaotic manner. This is likely to generate frequent extinctions and recolonizations. Theoretical genetic predictions derived from extinctions/recolonizations cannot satisfactorily model a situation where habitat shifts are frequent and constantly affect the metapopulation equilibrium. Because neither the island and the stepping-stone models nor the classical metapopulation models resemble the hydrothermal vent reality, we present here a realistic model developed to provide a compromise between existing conceptual models and what is currently known of the biology and ecology of one of the most peculiar and best-studied vent species, the polychaete Alvinella pompejana. This model allows us to define the boundaries between which the metapopulation is evolutionary stable in an unstable context. Simulations show different patterns in which metapopulation size and recolonization vary but reach an equilibrium despite chaotic vent extinctions. In contrast, the model also shows that displacing habitat continuously affects the equilibrium between gene flow and drift. As a consequence, the time required to balance these evolutionary forces can never be attained, leading to chaotic fluctuations in F-statistics. Those fluctuations are mainly due to stochastic changes of the interpatch distance which affect migration rates. The shifting of active zones of venting can episodically counterbalance differentiation and allow a long-term genetic homogenization at the ridge scale. These findings lead to a new concept in which the exchanges between populations would mainly depend on the habitat's movements along the ridge axis rather than the organim's dispersal. We therefore propose a new model based on patch-network displacements in which transient contact zones allow low levels of gene flow throughout the metapopulation.

Geographic extent of introgression in Sebastes mentella and its effect on genetic population structure

Genetic population structure is often used to identify management units in exploited species, but the extent of genetic differentiation may be inflated by geographic variation in the level of hybridization between species. We identify the genetic population structure of Sebastes mentella and investigate possible introgression within the genus by analyzing 13 microsatellites in 2,562 redfish specimens sampled throughout the North Atlantic. The data support an historical divergence between the "shallow" and "deep" groups, beyond the Irminger Sea where they were described previously. A third group, "slope," has an extended distribution on the East Greenland Shelf, in addition to earlier findings on the Icelandic slope. Furthermore, S. mentella from the Northeast Arctic and Northwest Atlantic waters are genetically different populations. In both areas, interspecific introgression may influence allele frequency differences among populations. Evidence of introgression was found for almost all the identified Sebastes gene pools, but to a much lower extent than suggested earlier. Greenland waters appear to be a sympatric zone for many of the genetically independent Sebastes groups. This study illustrates that the identified groups maintain their genetic integrity in this region despite introgression.

Non-deterministic modelling of food-web dynamics

A novel approach to model food-web dynamics, based on a combination of chance (randomness) and necessity (system constraints), was presented by Mullon et al. in 2009. Based on simulations for the Benguela ecosystem, they concluded that observed patterns of ecosystem variability may simply result from basic structural constraints within which the ecosystem functions. To date, and despite the importance of these conclusions, this work has received little attention. The objective of the present paper is to replicate this original model and evaluate the conclusions that were derived from its simulations. For this purpose, we revisit the equations and input parameters that form the structure of the original model and implement a comparable simulation model. We restate the model principles and provide a detailed account of the model structure, equations, and parameters. Our model can reproduce several ecosystem dynamic patterns: pseudo-cycles, variation and volatility, diet, stock-recruitment relationships, and correlations between species biomass series. The original conclusions are supported to a large extent by the current replication of the model. Model parameterisation and computational aspects remain difficult and these need to be investigated further. Hopefully, the present contribution will make this approach available to a larger research community and will promote the use of non-deterministic-network-dynamics models as ‘null models of food-webs’ as originally advocated.

Ecosystem oceanography for global change in fisheries

Overexploitation and climate change are increasingly causing unanticipated changes in marine ecosystems, such as higher variability in fish recruitment and shifts in species dominance. An ecosystem-based approach to fisheries attempts to address these effects by integrating populations, food webs and fish habitats at different scales. Ecosystem models represent indispensable tools to achieve this objective. However, a balanced research strategy is needed to avoid overly complex models. Ecosystem oceanography represents such a balanced strategy that relates ecosystem components and their interactions to climate change and exploitation. It aims at developing realistic and robust models at different levels of organisation and addressing specific questions in a global change context while systematically exploring the ever-increasing amount of biological and environmental data.