scholarly journals Indicators of the health of the North Sea fish community: identifying reference levels for an ecosystem approach to management

2006 ◽  
Vol 63 (4) ◽  
pp. 573-593 ◽  
Author(s):  
Simon P.R. Greenstreet ◽  
Stuart I. Rogers
Keyword(s):  
North Sea ◽  
Time Series Data ◽  
Size Structure ◽  
Single Species ◽  
Ecosystem Approach ◽  
Reference Points ◽  
Series Data ◽  
Anthropogenic Activity ◽  
Data Sets ◽  
The North

Abstract The shift in emphasis away from the single-species focus of traditional fisheries management towards an ecosystem approach to management requires application of indicators of ecosystem state. Further, an ecosystem approach to management requires the identification of ecological reference points against which management objectives might be set. In applying indicators, identifying reference points, and setting objectives, an obvious requirement is that the indicators respond primarily to the anthropogenic activity being managed and are sufficiently sensitive that impacts of the activity and the responses to management action are clearly demonstrable. Here we apply a suite of 12 indicators to Scottish August groundfish survey data collected in the northern North Sea over the period 1925–1997. These include indicators of size structure, life-history character composition, species diversity, and trophic structure within the community. Our choice of analytical design has two purposes; first to show that fishing has unequivocally affected these various aspects of the structure of the groundfish community, and second to illustrate an approach by which long time-series data sets might be used to identify possible management reference points. The results are discussed in the context of selecting ecological indicators in support of an ecosystem approach to management and determining appropriate reference points for objective-setting.

scholarly journals Parameter uncertainty of a dynamic multispecies size spectrum model

2016 ◽  
Vol 73 (4) ◽  
pp. 589-597 ◽  
Author(s):  
Michael A. Spence ◽  
Paul G. Blackwell ◽  
Julia L. Blanchard
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Size Structure ◽  
Management Strategies ◽  
Optimization Methods ◽  
Series Data ◽  
Size Spectrum ◽  
Aquatic Communities ◽  
The North ◽  
Spectrum Model

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.

scholarly journals Assessing the state of pelagic fish communities within an ecosystem approach and the European Marine Strategy Framework Directive

2014 ◽  
Vol 71 (7) ◽  
pp. 1572-1585 ◽  
Author(s):  
Samuel Shephard ◽  
Anna Rindorf ◽  
Mark Dickey-Collas ◽  
Niels T. Hintzen ◽  
Keith Farnsworth ◽  
...  
Keyword(s):  
North Sea ◽  
Reference Point ◽  
Fish Community ◽  
Fish Communities ◽  
Ecosystem Approach ◽  
Pelagic Fish ◽  
Reference Points ◽  
Marine Strategy Framework Directive ◽  
The North ◽  
Pelagic Fish Community

Abstract Pelagic fish are key elements in marine foodwebs and thus comprise an important part of overall ecosystem health. We develop a suite of ecological indicators that track pelagic fish community state and evaluate state of specific objectives against Good Environmental Status (GES) criteria. Indicator time-series are calculated for the EU Marine Strategy Framework Directive “Celtic Seas” (CS) and “Greater North Sea” subregions. Precautionary reference points are proposed for each indicator and a simple decision process is then used to aggregate indicators into a GES assessment for each subregion. The pelagic fish communities of both subregions currently appear to be close to GES, but each remains vulnerable. In the CS subregion, fishing mortality is close to the precautionary reference point, although the unknown dynamics of sandeel, sprat, and sardine in the subregion may reduce the robustness of this evaluation. In the North Sea, sandeel stocks have been in poor state until very recently. Pelagic fish community biomass is slightly below the precautionary reference point in both subregions.

Comparison of Wind and Wave Extremes in Very Long-Term Climatic Scales

2018 ◽  
Author(s):  
Christos N. Stefanakos ◽  
Erik Vanem
Keyword(s):  
Time Series Data ◽  
North Atlantic Ocean ◽  
Wave Climate ◽  
Series Data ◽  
Data Sets ◽  
Ocean Climate ◽  
The North ◽  
Block Maxima ◽  
Return Value

The study of very long-term ocean climate is of great interest in a number of different applications. In a climate change perspective, estimations of return values of wind and wave parameters to a future climate are of great importance for risk management and adaptation purposes. However, there are various ways of estimating the required return values, which introduce additional uncertainties in extreme weather and climate variables pertaining to both current and future climates. The different approaches that are considered in the present work include the annual maxima approach, the block maxima approach, and the MENU method which is based on the calculation of return periods of various level values from nonstationary time series data. Furthermore, the effect of different modelling choices within each of the approaches will be explored. Thus, a range of different return value estimates for the different data sets is obtained for a field of datapoints. Long-term datasets for an area in the North Atlantic Ocean are used in the present study, derived for project ExWaCli, comprising of 30 years in the present (historic period) and two sets of 30 years in the future (future projections). The comparison between the results of the various approaches reveals a variability of the return period estimates, and an assessment of this is given. Moreover, it seems that a slight shift towards higher extremes in a future wave climate might be possible based on the particular datasets that have been analysed.

Mixed-fishery or ecosystem conundrum? Multispecies considerations inform thinking on long-term management of North Sea demersal stocks

2009 ◽  
Vol 66 (7) ◽  
pp. 1107-1129 ◽  
Author(s):  
Steven Mackinson ◽  
Barrie Deas ◽  
Doug Beveridge ◽  
John Casey
Keyword(s):  
North Sea ◽  
Single Species ◽  
Ecosystem Model ◽  
Ecosystem Approach ◽  
Maximum Sustainable Yield ◽  
The North ◽  
Trade Offs ◽  
Management Plans ◽  
Term Management

Signatories of the 2002 World Summit on Sustainable Development declaration committed to maintain or restore fish stocks to levels that can produce the maximum sustainable yield (MSY), a goal that has been challenged on a number of grounds. The European Commission has stated an objective to manage fisheries (independently) to achieve MSY by 2015, which has catalysed the Regional Advisory Councils’ (RACs) thinking on MSY and how it relates to their goal of developing long-term management plans. This study uses an ecosystem model of the North Sea to investigate questions relating to MSY in the context of mixed demersal fisheries for cod, haddock, and whiting. Results suggest that it is not possible to simultaneously achieve yields corresponding to MSYs predicted from single-species assessments and that the contradictory response of whiting is central to the trade-offs in yield and value for mixed demersal fisheries. Incompatibility between mixed-fishery and ecosystem-scale considerations exemplifies the difficult conceptual and practical challenges faced when moving toward an ecosystem approach.

scholarly journals Lessons learned from stock collapse and recovery of North Sea herring: a review

2010 ◽  
Vol 67 (9) ◽  
pp. 1875-1886 ◽  
Author(s):  
Mark Dickey-Collas ◽  
Richard D. M. Nash ◽  
Thomas Brunel ◽  
Cindy J. G. van Damme ◽  
C. Tara Marshall ◽  
...  
Keyword(s):  
North Sea ◽  
Time Management ◽  
Single Species ◽  
Time Frame ◽  
Maximum Sustainable Yield ◽  
Lessons Learned ◽  
Reference Points ◽  
Ecosystem Change ◽  
The North ◽  
Stock Collapse

Abstract Dickey-Collas, M., Nash, R. D. M., Brunel, T., van Damme, C. J. G., Marshall, C. T., Payne, M. R., Corten, A., Geffen, A. J., Peck, M. A., Hatfield, E. M. C., Hintzen, N. T., Enberg, K., Kell, L. T., and Simmonds, E. J. 2010. Lessons learned from stock collapse and recovery of North Sea herring: a review. – ICES Journal of Marine Science, 67: 1875–1886. The collapse and recovery of North Sea herring in the latter half of the 20th century had both ecological and economic consequences. We review the effect of the collapse and investigate whether the increased understanding about the biology, ecology, and stock dynamics gained in the past three decades can aid management to prevent further collapses and improve projections of recovery. Recruitment adds the most uncertainty to estimates of future yield and the potential to reach biomass reference points within a specified time-frame. Stock–recruitment relationships must be viewed as being fluid and dependent on ecosystem change. Likewise, predation mortality changes over time. Management aimed at maximum sustainable yield (MSY) fishing mortality targets implies interannual variation in TACs, and variability in supply is therefore unavoidable. Harvest control rules, when adhered to, aid management greatly. We advocate that well-founded science can substantially contribute to management through improved confidence and increased transparency. At present, we cannot predict the effects of collapse or recovery of a single stock on the ecosystem as a whole. Moreover, as managers try to reconcile commitments to single-species MSY targets with the ecosystem-based approach, they must consider the appropriate management objectives for the North Sea ecosystem as a whole.

scholarly journals Redundancy in metrics describing the composition, structure, and functioning of the North Sea demersal fish community

2012 ◽  
Vol 69 (1) ◽  
pp. 8-22 ◽  
Author(s):  
Simon P. R. Greenstreet ◽  
Helen M. Fraser ◽  
Stuart I. Rogers ◽  
Verena M. Trenkel ◽  
Stephen D. Simpson ◽  
...  
Keyword(s):  
North Sea ◽  
Fish Community ◽  
Size Structure ◽  
Demersal Fish ◽  
Community Size ◽  
The North ◽  
Management Objectives ◽  
The North Sea ◽  
Composition Structure ◽  
And Function

Abstract Greenstreet, S. P. R., Fraser, H. M., Rogers, S. I., Trenkel, V. M., Simpson, S. D., and Pinnegar, J. K. 2012. Redundancy in metrics describing the composition, structure, and functioning of the North Sea demersal fish community. – ICES Journal of Marine Science, 69: 8–22. Broader ecosystem management objectives for North Sea demersal fish currently focus on restoring community size structure. However, most policy drivers explicitly concentrate on restoring and conserving biodiversity, and it has not yet been established that simply restoring demersal fish size composition will be sufficient to reverse declines in biodiversity and ensure a generally healthy community. If different aspects of community composition, structure, and function vary independently, then to monitor all aspects of community general health will require application of a suite of metrics. This assumes low redundancy among the metrics used in any such suite and implies that addressing biodiversity issues specifically will require explicit management objectives for particular biodiversity metrics. This issue of metric redundancy is addressed, and 15 metrics covering five main attributes of community composition, structure, and function are applied to groundfish survey data. Factor analysis suggested a new interpretation of the metric information and indicated that a minimum suite of seven metrics was necessary to ensure that all changes in the general health of the North Sea demersal fish community were monitored properly. Covariance among size-based and species-diversity metrics was low, implying that restoration of community size structure would not necessarily reverse declines in species diversity.

From single-species advice to mixed-species management: taking the next step

2004 ◽  
Vol 61 (8) ◽  
pp. 1398-1409 ◽  
Author(s):  
Morten Vinther ◽  
Stuart A. Reeves ◽  
Kenneth R. Patterson
Keyword(s):  
North Sea ◽  
Fishery Management ◽  
Single Species ◽  
Mixed Species ◽  
The North ◽  
Recent Approach ◽  
Starting Point ◽  
The North Sea ◽  
Management Advice ◽  
Management Priorities

Abstract Fishery management advice has traditionally been given on a stock-by-stock basis. Recent problems in implementing this advice, particularly for the demersal fisheries of the North Sea, have highlighted the limitations of the approach. In the long term, it would be desirable to give advice that accounts for mixed-fishery effects, but in the short term there is a need for approaches to resolve the conflicting management advice for different species within the same fishery, and to generate catch or effort advice that accounts for the mixed-species nature of the fishery. This paper documents a recent approach used to address these problems. The approach takes the single-species advice for each species in the fishery as a starting point, then attempts to resolve it into consistent catch or effort advice using fleet-disaggregated catch forecasts in combination with explicitly stated management priorities for each stock. Results are presented for the groundfish fisheries of the North Sea, and these show that the development of such approaches will also require development of the ways in which catch data are collected and compiled.

scholarly journals Cell cycle time series gene expression data encoded as cyclic attractors in Hopfield systems

2017 ◽  
Author(s):  
Anthony Szedlak ◽  
Spencer Sims ◽  
Nicholas Smith ◽  
Giovanni Paternostro ◽  
Carlo Piermarocchi
Keyword(s):  
Neural Network ◽  
Gene Expression ◽  
Cell Cycle ◽  
Time Series ◽  
Time Series Data ◽  
Series Data ◽  
Data Sets ◽  
Expression Data ◽  
Time Series Gene Expression ◽  
Human Cervical Cancer

AbstractModern time series gene expression and other omics data sets have enabled unprecedented resolution of the dynamics of cellular processes such as cell cycle and response to pharmaceutical compounds. In anticipation of the proliferation of time series data sets in the near future, we use the Hopfield model, a recurrent neural network based on spin glasses, to model the dynamics of cell cycle in HeLa (human cervical cancer) and S. cerevisiae cells. We study some of the rich dynamical properties of these cyclic Hopfield systems, including the ability of populations of simulated cells to recreate experimental expression data and the effects of noise on the dynamics. Next, we use a genetic algorithm to identify sets of genes which, when selectively inhibited by local external fields representing gene silencing compounds such as kinase inhibitors, disrupt the encoded cell cycle. We find, for example, that inhibiting the set of four kinases BRD4, MAPK1, NEK7, and YES1 in HeLa cells causes simulated cells to accumulate in the M phase. Finally, we suggest possible improvements and extensions to our model.Author SummaryCell cycle – the process in which a parent cell replicates its DNA and divides into two daughter cells – is an upregulated process in many forms of cancer. Identifying gene inhibition targets to regulate cell cycle is important to the development of effective therapies. Although modern high throughput techniques offer unprecedented resolution of the molecular details of biological processes like cell cycle, analyzing the vast quantities of the resulting experimental data and extracting actionable information remains a formidable task. Here, we create a dynamical model of the process of cell cycle using the Hopfield model (a type of recurrent neural network) and gene expression data from human cervical cancer cells and yeast cells. We find that the model recreates the oscillations observed in experimental data. Tuning the level of noise (representing the inherent randomness in gene expression and regulation) to the “edge of chaos” is crucial for the proper behavior of the system. We then use this model to identify potential gene targets for disrupting the process of cell cycle. This method could be applied to other time series data sets and used to predict the effects of untested targeted perturbations.

An Efficient Method for Forecasting Using Fuzzy Time Series

2017 ◽  
pp. 287-304 ◽  
Author(s):  
Pritpal Singh
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Weather Forecasting ◽  
Small Error ◽  
Fuzzy Time Series ◽  
Series Data ◽  
Data Sets ◽  
Proposed Model ◽  
Temperature Forecasting ◽  
The University

Forecasting using fuzzy time series has been applied in several areas including forecasting university enrollments, sales, road accidents, financial forecasting, weather forecasting, etc. Recently, many researchers have paid attention to apply fuzzy time series in time series forecasting problems. In this paper, we present a new model to forecast the enrollments in the University of Alabama and the daily average temperature in Taipei, based on one-factor fuzzy time series. In this model, a new frequency based clustering technique is employed for partitioning the time series data sets into different intervals. For defuzzification function, two new principles are also incorporated in this model. In case of enrollments as well daily temperature forecasting, proposed model exhibits very small error rate.

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