Towards an integrated forecasting system for fisheries on habitat-bound stocks

Christensen, Asbjørn; Butenschön, Momme; Gürkan, Zeren; Allen, Icarus

doi:10.5194/os-9-261-2013

Cited by 9 publications

(12 citation statements)

References 50 publications

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“…Sandeels are forage fish, described as major food‐web energy conveyers (Christensen et al. ) and as such are important high‐energy mid‐trophic prey for piscivorous fish, such as gadoids, that are also porpoise prey.…”

Section: Discussionmentioning

confidence: 99%

Seasonal habitat‐based density models for a marine top predator, the harbor porpoise, in a dynamic environment

et al. 2016

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. 2016. Seasonal habitat-based density models for a marine top predator, the harbor porpoise, in a dynamic environment. Ecosphere 7(6):e01367. 10. 1002/ecs2.1367 Abstract. Effective species conservation and management requires information on species distribution patterns, which is challenging for highly mobile and cryptic species that may be subject to multiple anthropogenic stressors across international boundaries. Understanding species-habitat relationships can improve the assessment of trends and distribution by explicitly allowing high-resolution data on habitats to inform abundance estimation and the identification of protected areas. In this study, we aggregated an unprecedented set of survey data of a marine top predator, the harbor porpoise (Phocoena phocoena), collected in the UK (SCANS II, Dogger Bank), Belgium, the Netherlands, Germany, and Denmark, to develop seasonal habitat-based density models for the central and southern North Sea. Visual survey data were collected over 9 yr (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) by means of dedicated line-transect surveys, taking into account the proportion of missed sightings. Generalized additive models of porpoise density were fitted to 156,630 km of on-effort survey data with 14,356 sightings of porpoise groups. Selected predictors included static and dynamic variables, such as depth, distance to shore and to sandeel (Ammodytes spp.) grounds, sea surface temperature (SST), proxies for fronts, and day length. Day length and the spatial distribution of daily SST proved to be good proxies for "season," allowing predictions in both space and time. The density models captured seasonal distribution shifts of porpoises across international boundaries. By combining the large-scale international SCANS II survey with the more frequent, small-scale national surveys, it has been possible to provide seasonal maps that will be used to assist the EU Habitats and Marine Strategy Framework Directives in effectively assessing the conservation status of harbor porpoises. Moreover, our results can facilitate the identification of regions where human activities and disturbances are likely to impact the population and are especially relevant for marine spatial planning, which requires accurate fine-scale maps of species distribution to assess risks of increasing human activities at sea.

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Section: Discussionmentioning

confidence: 99%

Seasonal habitat‐based density models for a marine top predator, the harbor porpoise, in a dynamic environment

et al. 2016

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“…Daewel et al, 2011) or is one-way coupling sufficient (e.g. Christensen et al, 2013)? Similarly, inputs of physical parameters need to be matched to the temporal and spatial scales on which biological models (e.g.…”

Section: Discussionmentioning

confidence: 99%

Uncertainties in projecting climate-change impacts in marine ecosystems

Payne

Barangé

Cheung

et al. 2015

ICES Journal of Marine Science

140

112

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Projections of the impacts of climate change on marine ecosystems are a key prerequisite for the planning of adaptation strategies, yet they are inevitably associated with uncertainty. Identifying, quantifying, and communicating this uncertainty is key to both evaluating the risk associated with a projection and building confidence in its robustness. We review how uncertainties in such projections are handled in marine science. We employ an approach developed in climate modelling by breaking uncertainty down into (i) structural (model) uncertainty, (ii) initialization and internal variability uncertainty, (iii) parametric uncertainty, and (iv) scenario uncertainty. For each uncertainty type, we then examine the current state-of-the-art in assessing and quantifying its relative importance. We consider whether the marine scientific community has addressed these types of uncertainty sufficiently and highlight the opportunities and challenges associated with doing a better job. We find that even within a relatively small field such as marine science, there are substantial differences between subdisciplines in the degree of attention given to each type of uncertainty. We find that initialization uncertainty is rarely treated explicitly and reducing this type of uncertainty may deliver gains on the seasonal-to-decadal time-scale. We conclude that all parts of marine science could benefit from a greater exchange of ideas, particularly concerning such a universal problem such as the treatment of uncertainty. Finally, marine science should strive to reach the point where scenario uncertainty is the dominant uncertainty in our projections.

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“…While new biological findings are leading to further revisions of the input data for stock assessments, it is clear that sustainable levels of fishing mortality differ considerably among the new sandeel stocks (Christensen et al, 2013;ICES, 2017), so highlighting the importance of incorporating population structure into fisheries management advice.…”

Section: Comparison Of Population and Stock Structure Used In Managementmentioning

confidence: 99%

Integrating the scale of population processes into fisheries management, as illustrated in the sandeel, Ammodytes marinus

Wright

Christensen

Regnier

et al. 2019

ICES Journal of Marine Science

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Aggregations of site-attached populations can show marked differences in density due to variation in local productivity and mortality processes. Matching management actions to the scale of biological processes is therefore important for sustainable fisheries management. This study examined the adequacy and appropriate scale of a spatially explicit management regime for sandeel, Ammodytes marinus, in the North Sea. Information from biophysical model simulations of larval transport and otolith chemistry was used to estimate the scale of mixing among aggregations. Together, these approaches indicated that there was negligible exchange of pre-settled sandeel among aggregations >200 km apart. Additionally, a re-analysis of tag-recapture experiments and distribution data indicated that the dispersive range decreased further after settlement. Significant differences in length at maturity and year-class strength not only reflect the limited mixing across the North Sea, but also point to regional differences in productivity and thereby vulnerability to fishing pressure. We conclude that the current management regime comprised of multiple assessment areas enable these differences to be considered in advice on annual fishing quotas.

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Towards an integrated forecasting system for fisheries on habitat-bound stocks

Cited by 9 publications

References 50 publications

Seasonal habitat‐based density models for a marine top predator, the harbor porpoise, in a dynamic environment

Seasonal habitat‐based density models for a marine top predator, the harbor porpoise, in a dynamic environment

Uncertainties in projecting climate-change impacts in marine ecosystems

Integrating the scale of population processes into fisheries management, as illustrated in the sandeel, Ammodytes marinus

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