Benjamin Planque

Ecological effects of the North Atlantic Oscillation

Climatic oscillations as reflected in atmospheric modes such as the North Atlantic Oscillation (NAO) may be seen as a proxy for regulating forces in aquatic and terrestrial ecosystems. Our review highlights the variety of climate processes related to the NAO and the diversity in the type of ecological responses that different biological groups can display. Available evidence suggests that the NAO influences ecological dynamics in both marine and terrestrial systems, and its effects may be seen in variation at the individual, population and community levels. The ecological responses to the NAO encompass changes in timing of reproduction, population dynamics, abundance, spatial distribution and interspecific relationships such as competition and predator-prey relationships. This indicates that local responses to large-scale changes may be more subtle than previously suggested. We propose that the NAO effects may be classified as three types: direct, indirect and integrated. Such a classification will help the design and interpretation of analyses attempting to relate ecological changes to the NAO and, possibly, to climate in general.

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.

Climate variability and north sea cod

The stock of North Sea cod is under pressure because of overfishing, and we show here that it is also threatened by a decline in the production of young cod that has paralleled warming of the North Sea over the past ten years. The combination of a diminished stock and the possible persistence of adverse warm conditions is endangering the long-term sustainability of cod in the North Sea. To decrease the risk of collapse, fishing pressure must be reduced.

Fisheries: Climate variability and North Sea cod

The stock of North Sea cod is under pressure because of overfishing, and we show here that it is also threatened by a decline in the production of young cod that has paralleled warming of the North Sea over the past ten years. The combination of a diminished stock and the possible persistence of adverse warm conditions is endangering the long-term sustainability of cod in the North Sea. To decrease the risk of collapse, fishing pressure must be reduced.

Synchrony in the recruitment time-series of plaice (Pleuronectes platessa L) around the United Kingdom and the influence of sea temperature

Abstract Historical time-series of recruitment to plaice stocks around the United Kingdom were examined for evidence of synchrony. Correlations were significant for most pair-wise comparisons and a meta-analysis test over all the stocks was highly significant. Previous studies on plaice recruitment in the North Sea have suggested that a negative relationship exists between sea temperature, during the first few months of the year, and subsequent year-class strength. When we examined the correlations between sea surface temperature and plaice recruitment, we found statistically significant negative relationships for most areas. These were strongest for the period February–June. Our results are consistent with the hypothesis that the temperature effect on recruitment of North Sea plaice is due to changes in predation pressure on the planktonic stages. However, western (North Sea and Channel) and eastern (Irish Sea and Celtic Sea) stocks appeared to respond to different time-scales of temperature variability which may imply that different mechanisms could be operating in these stocks. Management of plaice is based upon projections of future stock dynamics. Compared with fisheries on some other species, those on plaice are less dependent on the in-coming year-class. Therefore, the incorporation of sea temperature data into plaice stock dynamic models will probably not have a large impact on short-term projections. However, incorporation of a temperature relationship will allow medium to long-term forecasts to be made under varying environmental scenarios. These may provide a more realistic range of projections of future stock trends than is currently achieved.

Who eats whom in the Barents Sea: a food web topology from plankton to whales

A food web is an ecological network and its topological description consists of the list of nodes, i.e., trophospecies, the list of links, i.e., trophic interactions, and the direction of interactions (who is the prey and who is the predator). Food web topologies are widely used in ecology to describe structural properties of communities or ecosystems. The selection of trophospecies and trophic interactions can be realized in different manners so that many different food webs may be constructed for the same community. In the Barents Sea, many simple food webs have been constructed. We present a comprehensive food web topology for the Barents Sea ecosystem, from plankton to marine mammals. The protocol used to compile the data set includes rules for the selection of taxa and for the selection and documentation of the trophic links. The resulting topology, which includes 244 taxa and 1589 trophic links, can serve as a basis for topological analyses, comparison with other marine ecosystems, or as a basis to ...

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.

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.

Cryptic Sebastes norvegicus species in Greenland waters revealed by microsatellites

Cryptic Sebastes norvegicus species in Greenland waters revealed by microsatellites Atal Saha*, Lorenz Hauser, Rasmus Hedeholm, Benjamin Planque, Svein-Erik Fevolden, Jesper Boje, and Torild Johansen Institute of Marine Research, Tromsø Department, PO Box 6404, Tromsø 9294, Norway School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195-5020, USA Greenland Institute of Natural Resources, Kivioq 2, PO Box 570, Nuuk 3900, Greenland Hjort Centre for Marine Ecosystem Dynamics, Bergen 5817, Norway Department of Arctic and Marine Biology, UiT The Arctic University of Norway, Tromsø 9037, Norway DTU Aqua – National Institute of Aquatic Resources, Charlottenlund DK 2920, Denmark *Corresponding author: tel: þ47 97959302; fax: þ47 55238531; e-mail: atal.saha@imr.no

Exploring stochasticity and imprecise knowledge based on linear inequality constraints

This paper explores the stochastic dynamics of a simple foodweb system using a network model that mimics interacting species in a biosystem. It is shown that the system can be described by a set of ordinary differential equations with real-valued uncertain parameters, which satisfy a set of linear inequality constraints. The constraints restrict the solution space to a bounded convex polytope. We present results from numerical experiments to show how the stochasticity and uncertainty characterizing the system can be captured by sampling the interior of the polytope with a prescribed probability rule, using the Hit-and-Run algorithm. The examples illustrate a parsimonious approach to modeling complex biosystems under vague knowledge.