Assessing the Potential of Catch-Only Models to Inform on the State of Global Fisheries and the UN’s SDGs

Catch-only models (COMs) have been the focus of ongoing research into data-poor stock assessment methods. Two of the most recent models that are especially promising are (i) CMSY+, the latest refined version of CMSY that has progressed from Catch-MSY, and (ii) SRA+ (Stock Reduction Analysis Plus) a recent developments in field. Comparing COMs and evaluating their relative performance is essential for determining the state of regional and global fisheries that may be lacking necessary data that would be required to run traditional assessment models. In this paper we interrogate how performance of COMs can be improved by incorporating additional sources of information. We evaluate the performance of COMs on a dataset of 48 data-rich ICES (International Council for the Exploration of Seas) stock assessments. As one measure of performance, we consider the ability of the model to correctly classify stock status using FAO’s 3-tier classification that is also used for reporting on sustainable development goals to the UN. Both COMs showed notable bias when run with their inbuilt default heuristics, but as the quality of prior information increased, classification rates for the terminal year improved substantially. We conclude that although further COM refinements show some potential, most promising is the ongoing research into developing biomass or fishing effort priors for COMs in order to be able to reliably track stock status for the majority of the world’s fisheries currently lacking stock assessments.

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Precisely wrong or vaguely right: simulations of noisy discard data and trends in fishing effort being included in the stock assessment of North Sea plaice

ICES Journal of Marine Science ◽

10.1093/icesjms/fsm155 ◽

2007 ◽

Vol 64 (9) ◽

pp. 1641-1649 ◽

Cited By ~ 22

Author(s):

Mark Dickey-Collas ◽

Martin A. Pastoors ◽

Olvin A. van Keeken

Keyword(s):

North Sea ◽

Recent Trend ◽

Stock Assessment ◽

Target Population ◽

Fishing Effort ◽

Fishing Mortality ◽

Recent Past ◽

Clear Trend ◽

The Past ◽

Stock Assessments

Abstract Dickey-Collas, M., Pastoors, M. A, and van Keeken, O. A. 2007. Precisely wrong or vaguely right: simulations of noisy discard data and trends in fishing effort being included in the stock assessment of North Sea plaice. – ICES Journal of Marine Science, 64: 000–000. ICES stock assessments of North Sea plaice are routinely carried out with eXtended Survivors Analysis (XSA), based on landings and survey data. Recently, the assessments included data on discarded young fish, sampled with high variance. Fishing effort has been declining since the mid-1990s, so conditioning the estimated fishing mortality (F) on the recent past could introduce bias into the perceived stock size. Simulated populations with North Sea plaice-like characteristics are used to explore the dependence of the perceived stock dynamics on the inclusion of discards data at different sampling noise, using the same methods and XSA settings as ICES. The sensitivities of the results were tested against different trends in fishing effort and recruitment, and different scenarios for “shrinkage” (i.e. the way in which the past is used to estimate the most recent fishing mortality). Within the bounds of the simulation assumptions, the perception of population trends from an XSA stock assessment can be biased when there are trends in fishing effort: decreasing effort leads to underestimating SSB and overestimating F. When discards are not included, bias in SSB is greatest when effort decreases, and bias in F is greatest when effort increases. Bias in SSB and F were removed by including discard data, but at substantial loss of precision. If effort shows a clear trend and discards are substantial and estimated noisily, the recent trend in the target population may be hard to track with an XSA-type assessment methodology.

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Long-term fishing impact on the Senegalese coastal demersal resources: diagnosing from stock assessment models

Aquatic Living Resources ◽

10.1051/alr/2017046 ◽

2018 ◽

Vol 31 ◽

pp. 8 ◽

Cited By ~ 2

Author(s):

Kamarel Ba ◽

Modou Thiaw ◽

Massal Fall ◽

Ndiaga Thiam ◽

Beyah Meissa ◽

...

Keyword(s):

Linear Models ◽

Stock Assessment ◽

Ecosystem Approach ◽

Fishing Effort ◽

Production Model ◽

Commercial Catch ◽

Worst Case ◽

Fishing Impact ◽

Stock Assessments ◽

Abundance Indices

For the first time in Senegal, assessments based on both stochastic and deterministic production models were used to draw a global diagnosis of the fishing impact on coastal demersal stocks. Based one national fisheries databases and scientific trawl surveys data: (i) trends in landings since 1971 were examined, (ii) abundance indices of 10 stocks were estimated using linear models fitted to surveys data and commercial catch per unit efforts, and (iii) stock assessments were carried out using pseudo-equilibrium Fox and Pella-Tomlinson models and a Biomass dynamic production model fitted in a Bayesian framework to abundance indices. Most stocks have seen their abundance sharply declining over time. All stocks combined, results of stock assessments suggest a 63% reduction compared to virgin state. Three fifth of demersal stocks are overexploited and excess in fishing effort was estimated until 75% for the worst case. We conclude by suggesting that the fishing of such species must be regulated and an ecosystem approach to fisheries management should be implemented in order to monitor the whole ecosystem.

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Estimating uncertainty of data limited stock assessments

ICES Journal of Marine Science ◽

10.1093/icesjms/fsw145 ◽

2016 ◽

Vol 74 (1) ◽

pp. 69-77 ◽

Cited By ~ 15

Author(s):

Alexandros Kokkalis ◽

Anne Maria Eikeset ◽

Uffe H. Thygesen ◽

Petur Steingrund ◽

Ken H. Andersen

Keyword(s):

Stock Assessment ◽

Assessment Method ◽

Fish Stocks ◽

Stock Status ◽

North East ◽

The North ◽

Stock Biomass ◽

Uncertainty Estimates ◽

Stock Assessments ◽

Spawning Stock

Many methods exist to assess the fishing status of data-limited stocks; however, little is known about the accuracy or the uncertainty of such assessments. Here we evaluate a new size-based data-limited stock assessment method by applying it to well-assessed, data-rich fish stocks treated as data-limited. Particular emphasis is put on providing uncertainty estimates of the data-limited assessment. We assess four cod stocks in the North-East Atlantic and compare our estimates of stock status (F/Fmsy) with the official assessments. The estimated stock status of all four cod stocks followed the established stock assessments remarkably well and the official assessments fell well within the uncertainty bounds. The estimation of spawning stock biomass followed the same trends as the official assessment, but not the same levels. We conclude that the data-limited assessment method can be used for stock assessment and that the uncertainty estimates are reliable. Further work is needed to quantify the spawning biomass of the stock.

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Eastern Baltic cod in distress: biological changes and challenges for stock assessment

ICES Journal of Marine Science ◽

10.1093/icesjms/fsv109 ◽

2015 ◽

Vol 72 (8) ◽

pp. 2180-2186 ◽

Cited By ~ 77

Author(s):

Margit Eero ◽

Joakim Hjelm ◽

Jane Behrens ◽

Kurt Buchmann ◽

Massimiliano Cardinale ◽

...

Keyword(s):

Baltic Sea ◽

Gadus Morhua ◽

Stock Assessment ◽

The Baltic Sea ◽

Stock Status ◽

Management Measures ◽

Stock Assessments ◽

Management Advice ◽

The Baltic ◽

Eastern Baltic

Abstract The eastern Baltic (EB) cod (Gadus morhua) stock was depleted and overexploited for decades until the mid-2000s, when fishing mortality rapidly declined and biomass started to increase, as shown by stock assessments. These positive developments were partly assigned to effective management measures, and the EB cod was considered one of the most successful stock recoveries in recent times. In contrast to this optimistic view, the analytical stock assessment failed in 2014, leaving the present stock status unclear. Deteriorated quality of some basic input data for stock assessment in combination with changes in environmental and ecological conditions has led to an unusual situation for cod in the Baltic Sea, which poses new challenges for stock assessment and management advice. A number of adverse developments such as low nutritional condition and disappearance of larger individuals indicate that the stock is in distress. In this study, we (i) summarize the knowledge of recent changes in cod biology and ecosystem conditions, (ii) describe the subsequent challenges for stock assessment, and (iii) highlight the key questions where answers are urgently needed to understand the present stock status and provide scientifically solid support for cod management in the Baltic Sea.

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A modelling approach to evaluate the impact of fish spatial behavioural types on fisheries stock assessment

ICES Journal of Marine Science ◽

10.1093/icesjms/fsy172 ◽

2018 ◽

Vol 76 (2) ◽

pp. 489-500 ◽

Cited By ~ 8

Author(s):

Josep Alós ◽

Andrea Campos-Candela ◽

Robert Arlinghaus

Keyword(s):

Stock Assessment ◽

Fishing Effort ◽

Fish Stock ◽

Catch Per Unit Effort ◽

Wide Range ◽

Stock Assessments ◽

Theoretical Predictions ◽

Behavioural Types ◽

Catch Rates ◽

The Impact

Abstract Spatial behavioural types (SBTs) arise from between-individual differences in behavioural traits that foster spatial behavioural patterns that are consistent over time and ecological contexts. Fish stocks are regularly assessed using catch per unit effort (CPUE) as input data that may non-linearly co-vary with the underlying abundance (N) of the exploited stock when SBT affect catchability. We hypothesized that SBT promote characteristic changes in catchability within harvesting seasons that affect catch rates and in turn catch-based fish stock assessments. To test this hypothesis, we developed a spatially explicit agent-based simulation where we measured encounters between fish and fishers and estimated the shape of the CPUE–N relationship. We ran the simulation in a prototypical fish–fisher encounter-leads-to-catch-type fishery and systematically studied outcomes in the presence or absence of SBTs. It was revealed that the existence of SBTs leads to CPUE inevitably declining faster than N (a process known as hyperdepletion) when compared with a simulation lacking SBTs. This finding was consistent in a wide range of fishing effort scenarios. The emergent hyperdepletion of catch rates was caused by fast and behavioural-selective exploitation of vulnerable SBT that encompassed the mobile component of the fish stock. The theoretical predictions received support from field data from a coastal recreational fishery. Our work suggests that the consideration of SBT when interpreting trends in CPUE data may notably improve stock assessments by providing a more reliable CPUE–N relationship.

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Introduction: Exploring Russian nationalisms

10.3366/edinburgh/9781474433853.003.0001 ◽

2018 ◽

Author(s):

Pål Kolstø ◽

Helge Blakkisrud

Keyword(s):

The State ◽

Complex Interplay ◽

Recent Developments ◽

Part Structure

Russian societal nationalism comes in various guises, both ethnic and imperialist. Also Putin’s rhetoric is marked by the tensions between ethnic and state-focused, imperialist thinking. Noting the complex interplay of state nationalism and societal nationalism, this introductory chapter examines the mental framework within which Russian politicians were acting prior to the decision to annex Crimea. The chapter develops a typology of Russian nationalisms, surveys recent developments, and presents the three-part structure of this book: official nationalism, radical and other societal nationalisms, and identities/otherings. It concludes that after the annexation of Crimea, when the state took over the agenda of both ethnic and imperialist nationalists in Russia, societal nationalism finds itself at low ebb.

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Japanese-language videos on YouTube as a source of public health information for COVID-19 (Preprint)

10.2196/preprints.24655 ◽

2020 ◽

Author(s):

Takeo Yasu

Keyword(s):

Public Health ◽

Health Information ◽

Scientific Evidence ◽

The State ◽

Video Content ◽

Sources Of Information ◽

State Of Emergency ◽

Public Health Information ◽

Youtube Videos ◽

Spread Of Infection

BACKGROUND Serious public health problems, such as the COVID-19 pandemic, can cause an infodemic. Sources of information that may cause an infodemic include social networking services; YouTube, which consists of content created and uploaded by individuals, is one such source. OBJECTIVE To survey the content and changes in YouTube videos that present public health information about COVID-19 in Japan. METHODS We surveyed YouTube content regarding public health information pertaining to COVID-19 in Japan. YouTube searches were performed on March 6, 2020 (before the state of emergency), April 14 (during the state of emergency), and May 27 (after the state of emergency was lifted), with 136, 113, and 140 sample videos evaluated, respectively. The main outcome measures were: (1) The total number of views for each video, (2) video content, and (3) the usefulness of the video. RESULTS In the 100 most viewed YouTube videos during the three periods, the number of videos on public health information in March was significantly higher than in May (p = .02). Of the 331 unique videos, 9.1% (n = 30) were released by healthcare professionals. Useful videos providing public health information about the prevention of the spread of infection comprised only 13.0% of the sample but were viewed significantly more often than not useful videos (p = .006). CONCLUSIONS Individuals need to take care when obtaining information from YouTube before or early in a pandemic, during which time scientific evidence is scarce.

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Silencing and Oblivion of Psychological Trauma, Its Unconscious Aspects, and Their Impact on the Inflation of Vajrayāna. An Analysis of Cross-Group Dynamics and Recent Developments in Buddhist Groups Based on Qualitative Data

Religions ◽

10.3390/rel10110622 ◽

2019 ◽

Vol 10 (11) ◽

pp. 622 ◽

Cited By ~ 2

Author(s):

Anders

Keyword(s):

Group Dynamics ◽

Interdisciplinary Approach ◽

Psychological Trauma ◽

Ongoing Research ◽

Psychological Mechanisms ◽

Teacher Student ◽

New Concepts ◽

Recent Developments ◽

Student Relationship ◽

The Impact

The commercialization of Buddhist philosophy has led to decontextualization and indoctrinating issues across groups, as well as abuse and trauma in that context. Methodologically, from an interdisciplinary approach, based on the current situation in international Buddhist groups and citations of victims from the ongoing research, the psychological mechanisms of rationalizing and silencing trauma were analyzed. The results show how supposedly Buddhist terminology and concepts are used to rationalize and justify economic, psychological and physical abuse. This is discussed against the background of psychological mechanisms of silencing trauma and the impact of ignoring the unconscious in that particular context. Inadequate consideration regarding the teacher–student relationship, combined with an unreflective use of Tibetan honorary titles and distorted conceptualizations of methods, such as the constant merging prescribed in so-called 'guru yoga', resulted in giving up self-responsibility and enhanced dependency. These new concepts, commercialized as 'karma purification' and 'pure view', have served to rationalize and conceal abuse, as well as to isolate the victims. Therefore, we are facing societal challenges, in terms of providing health and economic care to the victims and implementing preventive measures. This use of language also impacts on scientific discourse and Vajrayāna itself, and will affect many future generations.

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Securitisation gaps: Towards ideational understandings of state weakness

European Journal of International Security ◽

10.1017/eis.2021.13 ◽

2021 ◽

pp. 1-20

Author(s):

Kevork Oskanian

Keyword(s):

The State ◽

Collective Knowledge ◽

State Action ◽

Role Of The State ◽

Wide Range ◽

State And Society ◽

Interpretive Approach ◽

Recent Developments ◽

The Republic

Abstract This article contributes a securitisation-based, interpretive approach to state weakness. The long-dominant positivist approaches to the phenomenon have been extensively criticised for a wide range of deficiencies. Responding to Lemay-Hébert's suggestion of a ‘Durkheimian’, ideational-interpretive approach as a possible alternative, I base my conceptualisation on Migdal's view of state weakness as emerging from a ‘state-in-society's’ contested ‘strategies of survival’. I argue that several recent developments in Securitisation Theory enable it to capture this contested ‘collective knowledge’ on the state: a move away from state-centrism, the development of a contextualised ‘sociological’ version, linkages made between securitisation and legitimacy, and the acknowledgment of ‘securitisations’ as a contested Bourdieusian field. I introduce the concept of ‘securitisation gaps’ – divergences in the security discourses and practices of state and society – as a concept aimed at capturing this contested role of the state, operationalised along two logics (reactive/substitutive) – depending on whether they emerge from securitisations of the state action or inaction – and three intensities (latent, manifest, and violent), depending on the extent to which they involve challenges to state authority. The approach is briefly illustrated through the changing securitisation gaps in the Republic of Lebanon during the 2019–20 ‘October Uprising’.

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Empowering Advanced Driver-Assistance Systems from Topological Data Analysis

Mathematics ◽

10.3390/math9060634 ◽

2021 ◽

Vol 9 (6) ◽

pp. 634

Author(s):

Tarek Frahi ◽

Francisco Chinesta ◽

Antonio Falcó ◽

Alberto Badias ◽

Elias Cueto ◽

...

Keyword(s):

Data Analysis ◽

The State ◽

Sensor Data ◽

Topological Data Analysis ◽

Motion Sensors ◽

Driver Assistance Systems ◽

The Road ◽

Topological Features ◽

Recent Developments ◽

Topological Data

We are interested in evaluating the state of drivers to determine whether they are attentive to the road or not by using motion sensor data collected from car driving experiments. That is, our goal is to design a predictive model that can estimate the state of drivers given the data collected from motion sensors. For that purpose, we leverage recent developments in topological data analysis (TDA) to analyze and transform the data coming from sensor time series and build a machine learning model based on the topological features extracted with the TDA. We provide some experiments showing that our model proves to be accurate in the identification of the state of the user, predicting whether they are relaxed or tense.

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