Ecosystem-based management (EBM) of the ocean considers all impacts on and uses of marine and coastal systems. In recent years, there has been a heightened interest in EBM tools that allow testing of alternative management options and help identify tradeoffs among human uses. End-to-end ecosystem modeling frameworks that consider a wide range of management options are a means to provide integrated solutions to the complex ocean management problems encountered in EBM. Here, we leverage the global advances in ecosystem modeling to explore common opportunities and challenges for ecosystem-based management, including changes in ocean acidification, spatial management, and fishing pressure across eight Atlantis (atlantis.cmar.csiro.au) end-toend ecosystem models. These models represent marine ecosystems from the tropics to the arctic, varying in size, ecology, and management regimes, using a three-dimensional, spatially-explicit structure parametrized for each system. Results suggest stronger impacts from ocean acidification and marine protected areas than from altering fishing pressure, both in terms of guild-level (i.e., aggregations of similar species or groups) biomass and in terms of indicators of ecological and fishery structure. Effects of ocean acidification were typically negative (reducing biomass), while marine protected areas led to both "winners" and "losers" at the level of particular species (or functional groups). Changing fishing pressure (doubling or halving) had smaller effects on the species guilds Olsen et al. Ocean Futures Explored Using Models or ecosystem indicators than either ocean acidification or marine protected areas. Compensatory effects within guilds led to weaker average effects at the guild level than the species or group level. The impacts and tradeoffs implied by these future scenarios are highly relevant as ocean governance shifts focus from single-sector objectives (e.g., sustainable levels of individual fished stocks) to taking into account competing industrial sectors' objectives (e.g., simultaneous spatial management of energy, shipping, and fishing) while at the same time grappling with compounded impacts of global climate change (e.g., ocean acidification and warming).

The move toward an ecosystem-based fisheries management (EBFM) requires new operational tools in order to support management decisions. Among them, ecosystem-and fisheries-based models are critical to quantitatively predict the consequences of future scenarios by integrating available knowledge about the ecosystem across different scales. Despite increasing development of these complex system models in the last decades, their operational use is still currently limited in Europe. Many guidelines are already available to help the development of complex system models for advice yet they are often ignored. We identified three main impediments to the use of complex system models for decision support: (1) their very complexity which is a source of uncertainty; (2) their lack of credibility, (3) and the challenge of communicating/transferring complex results to decision makers not accustomed to deal with multivariate uncertain results. In this paper, we illustrate these somehow theoretical "best practices" with tangible successful examples, which can help the transfer of complex system models from academic science to operational advice. We first focus on handling uncertainty by optimizing model complexity with regards to management objectives and technical issues. We then list up methods, such as transparent documentation and performance evaluation, to increase confidence in complex system models. Finally, we review how and where complex system models could fit within existing institutional and legal settings of the current European fisheries decision framework. We highlight where changes are required to allow for the operational use of complex system models. All methods and approaches proposed are illustrated with successful examples from fisheries science or other disciplines. This paper demonstrates that all relevant ingredients are readily available to make complex system models operational for advice.

Anticipating fisher behaviour is necessary for successful fisheries management. Of the different concepts that have been developed to understand individual fisher behaviour, random utility models (RUMs) have attracted considerable attention in the past three decades, and more particularly so since the 2000s. This study aimed at summarizing and analysing the information gathered from RUMs used during the last three decades around the globe. A methodology has been developed to standardize information across different studies and compare RUM results. The studies selected focused on fishing effort allocation. Six types of fisher behaviour drivers were considered: the presence of other vessels in the same fishing area, tradition, expected revenue, species targeting, costs, and risk‐taking. Analyses were performed using three separate linear modelling approaches to assess the extent to which these different drivers impacted fisher behaviour in three fleet types: fleets fishing for demersal species using active gears, fleets fishing for demersal species using passive gears and fleets fishing for pelagic species. Fishers are attracted by higher expected revenue, tradition, species targeting and presence of others, but avoid choices involving large costs. Results also suggest that fishers fishing for demersal species using active gears are generally more influenced by past seasonal (long‐term) patterns than by the most recent (short‐term) information. Finally, the comparison of expected revenue with other fisher behaviour drivers highlights that demersal fishing vessels are risk‐averse and that tradition and species targeting influence fisher decisions more than expected revenue.

The ecosystem model Atlantis was used to investigate the key dynamics and processes that structure the Eastern English Channel ecosystem, with a particular focus on two commercial flatfish species, sole (Solea solea) and plaice (Pleuronectes platessa). This complex model was parameterized with data collected from diverse sources (a literature review, survey data, as well as landings and stock assessment information) and tuned so both simulated biomass and catch fit 2002-2011 observations. Here, the outputs are mainly presented for the two focus species and for some other vertebrates found to be important in the trophic network. The calibration process revealed the importance of coastal areas in the Eastern English Channel and of nutrient inputs from estuaries: a lack of river nutrients decreases the productivity of nursery grounds and adversely affects the production of sole and plaice. The role of discards in the trophic network is also highlighted. While sole and plaice did not have a strong influence on the trophic network of vertebrates, they are important predators for benthic invertebrates and compete for food with crustaceans, whiting (Merlangius merlangus) and other demersal fish. We also found that two key species, cod (Gadus morhua) and whiting, thoroughly structured the Eastern English Channel trophic network.

Calibration of complex, process-based ecosystem models is a timely task with modellers challenged by many parameters, multiple outputs of interest and often a scarcity of empirical data. Incorrect calibration can lead to unrealistic ecological and socio-economic predictions with the modeller's experience and available knowledge of the modelled system largely determining the success of model calibration. Here we provide an overview of best practices when calibrating an Atlantis marine ecosystem model, a widely adopted framework that includes the parameters and processes comprised in many different ecosystem models. We highlight the importance of understanding the model structure and data sources of the modelled system. We then focus on several model outputs (biomass trajectories, age distributions, condition at age, realised diet proportions, and spatial maps) and describe diagnostic routines that can assist modellers to identify likely erroneous parameter values. We detail strategies to fine tune values of four groups of core parameters: growth, predator-prey interactions, recruitment and mortality. Additionally, we provide a pedigree routine to evaluate the uncertainty of an Atlantis ecosystem model based on data sources used. Describing best and current practices will better equip future modellers of complex, processed-based ecosystem models to provide a more reliable means of explaining and predicting the dynamics of marine ecosystems. Moreover, it promotes greater transparency between modellers and end-users, including resource managers.Please note that this is an author-produced PDF of an article accepted for publication following peer review. The definitive publisher-authenticated version is available on the publisher Web site. Highlights► Best practices for calibrating complex process-based ecosystem models are described. ► We emphasize the importance of understanding the model structure and data sources. ► Strategies to estimate core parameters for an Atlantis ecosystem model are defined. ► Key diagnostic routines to help modelers identify erroneous parameters are outlined. ► A pedigree to evaluate ecosystem model confidence and data quality is proposed.

Coastal bays provide habitats for juveniles and adults of many marine species. Mont Saint-Michel Bay (MSMB, France) hosts a highly diversified fish community and constitutes one of the most important nursery grounds for many commercially exploited marine species, such as sea bass, flatfish, clupeids and rays in the English Channel. Besides, MSMB also suffers from the massive invasion of an exotic mollusc, the American slipper-limpet (Crepidula fornicata, L). This species arrived four decades ago and now represents the main filter-feeder biomass in the bay (150 Mt), an order of magnitude larger than local farmed and natural shellfishes. Recent analyses underlined the impact of this small gastropod on the trophic structure of this bay and its negative influence on juvenile sole densities in the nursery grounds. The present study uses a geostatistical approach to explore the effect of the extension of the slipper-limpet on flatfish (common sole Solea solea, L plaice Pleuronectes platessa, L brill Scophthalmus rhombus, L and flounder Platichthys flesus, L) spatial distribution. Data collected during survey of the MSMB at the end of the 1970s and three decades later have been used to build interpolated maps of (1) slipper-limpet and (2) flatfish spatial distributions. Slipper-limpets were concentrated in a small area, in the western part of the MSMB, in the 1970s while today they occupy half of the bay. This rapid proliferation led to the decrease of available surface for flatfishes, which previously occupied the whole bay and are now restricted to its eastern part. The present study highlighted that the negative influence on fish habitat in MSMB is apparently more related to changes in the substratum than to trophic interactions. This invasion has possible consequences on flatfish population renewal at a large scale and may also damage other benthic or demersal species, such as rays

In recent years, RNA interference has been exploited as a tool for investigating gene function in plants. We tested the potential of double-stranded RNA interference technology for silencing a transgene in the actinorhizal tree Allocasuarina verticillata. The approach was undertaken using stably transformed shoots expressing the beta-glucuronidase (GUS) gene under the control of the constitutive promoter 35S; the shoots were further transformed with the Agrobacterium rhizogenes A4RS containing hairpin RNA (hpRNA) directed toward the GUS gene, and driven by the 35S promoter. The silencing and control vectors contained the reporter gene of the green fluorescent protein (GFP), thus allowing a screening of GUS-silenced composite plantlets for autofluorescence. With this rapid procedure, histochemical data established that the reporter gene was strongly silenced in both fluorescent roots and actinorhizal nodules. Fluorometric data further established that the level of GUS silencing was usually greater than 90% in the hairy roots containing the hairpin GUS sequences. We found that the silencing process of the reporter gene did not spread to the aerial part of the composite A. verticillata plants. Real-time quantitative polymerase chain reaction showed that GUS mRNAs were substantially reduced in roots and, thereby, confirmed the knock-down of the GUS transgene in the GFP(+) hairy roots. The approach described here will provide a versatile tool for the rapid assessment of symbiotically related host genes in actinorhizal plants of the Casuarinaceae family.

a b s t r a c tUnderstanding and modelling fleet dynamics and their response to spatial constraints is a prerequisite to anticipating the performance of marine ecosystem management plans. A major challenge for fisheries managers is to be able to anticipate how fishing effort is re-allocated following any permanent or seasonal closure of fishing grounds, given the competition for space with other active maritime sectors. In this study, a Random Utility Model (RUM) was applied to determine how fishing effort is allocated spatially and temporally by the French demersal mixed fleet fishing in the Eastern English Channel. The explanatory variables chosen were past effort i.e. experience or habit, previous catch to represent previous success, % of area occupied by spatial regulation, and by other competing maritime sectors. Results showed that fishers tended to adhere to past annual fishing practices, except the fleet targeting molluscs which exhibited within year behaviour influenced by seasonality. Furthermore, results indicated French and English scallop fishers share the same fishing grounds, and maritime traffic may impact on fishing decision. Finally, the model was validated by comparing predicted re-allocation of effort against observed effort, for which there was a close correlation.