Recent data suggest no further recovery in North Sea Large Fish Indicator

Fung, Tak; Farnsworth, Keith D.; Reid, David G.; Rossberg, Axel G.

doi:10.1093/icesjms/fsr206

Cited by 32 publications

(30 citation statements)

References 11 publications

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“…Secondly, the spatial distribution of trawling is also very heterogeneous (see also Rijnsdorp et al 1998;Jennings et al 1999) and has changed recently, with areas trawled more intensively in the 1990s coinciding with greater reductions in the LFI from 1983-1999; areas where trawling has been reduced since then, have shown better recoveries in the LFI from 2000-2012 than other areas. Thirdly, although the LFI has significantly improved since 2000 in especially the western North Sea, it is not yet at levels comparable to the 1980s (in line with Greenstreet et al 2011;Fung et al 2012Fung et al , 2013and see Shephard et al 2013 on lack of recovery in the Celtic Sea LFI). The uneven distribution of the LFI is unsurprising and partly reflects the distribution patterns of the two predominant species in the 'large fish component' of the LFI: cod and saithe (Greenstreet et al 2011).…”

Section: Discussionmentioning

confidence: 92%

“…This paper uses the revised definition of the LFI (Greenstreet et al 2011) Fung et al (2012). To determine yearly LFI values, the equation is as follows:…”

Section: Survey Data and Indicator Calculationmentioning

confidence: 99%

“…Following computation of the LFI scores by rectangle, the time-series of the LFI index for the entire North Sea was correlated with the values reported by Fung et al (2012) as a validation of the coding exercise.…”

Section: Survey Data and Indicator Calculationmentioning

confidence: 99%

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Effort reduction and the large fish indicator: spatial trends reveal positive impacts of recent European fleet reduction schemes

et al. 2015

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Environmental Conservation (2015) 42 (3): 227-236 C Foundation for Environmental Conservation 2015. The online version of this article is published within an Open Access environment subject to the conditions of the Creative Commons Attribution licence http://creativecommons.org/licenses/by/3.0/ doi:10.1017/S0376892915000077 Effort reduction and the large fish indicator: spatial trends reveal positive impacts of recent European fleet reduction schemes

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Section: Discussionmentioning

confidence: 92%

“…This paper uses the revised definition of the LFI (Greenstreet et al 2011) Fung et al (2012). To determine yearly LFI values, the equation is as follows:…”

Section: Survey Data and Indicator Calculationmentioning

confidence: 99%

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Effort reduction and the large fish indicator: spatial trends reveal positive impacts of recent European fleet reduction schemes

et al. 2015

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“…Second, the species composition between models and inclusion in the calculation of the community metrics differed. Here, demersal species only were used to calculate community metrics (in keeping with empirical analyses; Fung et al (2012)), and from further experiments, we found that the LFI is more sensitive to species subsetting than the slope of the community size spectrum.…”

Section: Discussionmentioning

confidence: 76%

Parameter uncertainty of a dynamic multispecies size spectrum model

Spence

Blackwell

Blanchard

2016

Can. J. Fish. Aquat. Sci.

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Dynamic size spectrum models have been recognized as an effective way of describing how size-based interactions can give rise to the size structure of aquatic communities. They are intermediate-complexity ecological models that are solutions to partial differential equations driven by the size-dependent processes of predation, growth, mortality, and reproduction in a community of interacting species and sizes. To be useful for quantitative fisheries management these models need to be developed further in a formal statistical framework. Previous work has used time-averaged data to "calibrate" the model using optimization methods with the disadvantage of losing detailed time-series information. Using a published multispecies size spectrum model parameterized for the North Sea comprising 12 interacting fish species and a background resource, we fit the model to time-series data using a Bayesian framework for the first time. We capture the 1967-2010 period using annual estimates of fishing mortality rates as input to the model and time series of fisheries landings data to fit the model to output. We estimate 38 key parameters representing the carrying capacity of each species and background resource, as well as initial inputs of the dynamical system and errors on the model output. We then forecast the model forward to evaluate how uncertainty propagates through to population-and community-level indicators under alternative management strategies.Résumé : Les modèles de spectres de tailles dynamiques sont reconnus comme offrant une approche efficace pour décrire comment les interactions basées sur la taille peuvent donner lieu à une structure de taille dans les communautés aquatiques. Ce sont des modèles écologiques de complexité moyenne représentant des solutions à des équations différentielles partielles déterminées par les processus dépendant de la taille que sont la prédation, la croissance, la mortalité et la reproduction dans une communauté d'espèces et de tailles interagissant entre elles. Pour être utiles dans la gestion quantitative des pêches, ces modèles doivent être approfondis dans un cadre statistique formel. Des travaux antérieurs ont fait appel à des valeurs moyennes de séries temporelles pour « étalonner » le modèle en utilisant des méthodes d'optimisation, ce qui a le désavantage d'occulter de l'information détaillée contenue dans les séries chronologiques. En utilisant un modèle publié de spectre de tailles multi-espèce paramétré pour la mer du Nord et comptant 12 espèces de poissons interagissant entre elles et les ressources de référence, nous avons calé le modèle sur des données de séries chronologiques en utilisant un cadre bayésien pour la première fois. Nous capturons la période de 1967 à 2010 en employant des estimations annuelles des taux de mortalité par pêche comme entrées au modèle et des séries chronologiques de données de débarquement de pêche pour caler le modèle sur les données de sortie. Nous estimons 38 paramètres clés représentant la capacité de charge de chaque espèce et...

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“…; Fung et al . ), it may or may not be specified which grid cells are included in an analysis, making it more difficult to compare studies. Our decomposition by both species and space further demonstrated that changes in abundance of a relatively non‐abundant species, the lesser spotted dogfish, in just one grid cell, contributed greatly to overall trends.…”

Section: Discussionmentioning

confidence: 99%

Community management indicators can conflate divergent phenomena: two challenges and a decomposition‐based solution

Adams

Reuman

2016

Journal of Applied Ecology

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Summary1. Community indicators are used to assess the state of ecological communities and to guide management. They are usually calculated from monitoring data, often collected annually. Since any given community indicator provides a univariate summary of complex multivariate phenomena, different changes in the community may lead to the same response in the indicator. Sampling variation can also mask ecologically important trends. 2. This study addresses these challenges for community indicators, with a focus on the large fish indicator (LFI), internationally used to report status of marine fish communities. The LFI expresses 'large' fish biomass as a proportion of total fish biomass and is calculated from species-size-abundance data collected on trawl surveys. We develop new methods to decompose the contributions of species, sampling locations and season to trends over time in the LFI, and highlight consequences for assessment and management. 3. Our results showed that both species and locations made divergent contributions to overall trends in the LFI indicator, with contributions differing by several orders of magnitude and in sign. Only small proportions of species and locations drove overall LFI trends, and their contributions changed with season (spring and autumn surveys). To assess significance of component trends, a resampling method was developed. Our method can be generalized and applied to many other community indicators based on survey data. 4. Synthesis and applications. Our new method for decomposing community indicators and generating confidence intervals makes it possible to extract much more information on what drives a 'headline' indicator, providing a solution to challenges arising from multiple possible interpretations of changes in the indicator and from sampling variation. Analysis of the effects of indicator components on headline indicator values is recommended, because the results allow assessors and managers to identify and interpret how divergent factors (e.g. species, sampling locations and seasons) contribute to the headline indicator value.

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Recent data suggest no further recovery in North Sea Large Fish Indicator

Cited by 32 publications

References 11 publications

Effort reduction and the large fish indicator: spatial trends reveal positive impacts of recent European fleet reduction schemes

Effort reduction and the large fish indicator: spatial trends reveal positive impacts of recent European fleet reduction schemes

Parameter uncertainty of a dynamic multispecies size spectrum model

Community management indicators can conflate divergent phenomena: two challenges and a decomposition‐based solution

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