Fishery Discards: Factors Affecting Their Variability within a Demersal Trawl Fishery

Discards represent one of the most important issues within current commercial fishing. It occurs for a range of reasons and is influenced by an even more complex array of factors. We address this issue by examining the data collected within the Danish discard observer program and describe the factors that influence discarding within the Danish Kattegat demersal fleet over the period 1997 to 2008. Generalised additive models were used to assess how discards of the 3 main target species, Norway lobster, cod and plaice, and their subcomponents (under and over minimum landings size) are influenced by important factors and their potential relevance to management. Our results show that discards are influenced by a range of different factors that are different for each species and portion of discards. We argue that knowledge about the factors influential to discarding and their use in relation to potential mitigation measures are essential for future fisheries management strategies

Dissecting the illegal ivory trade: an analysis of ivory seizures data

Reliable evidence of trends in the illegal ivory trade is important for informing decision making for elephants but it is difficult to obtain due to the covert nature of the trade. The Elephant Trade Information System, a global database of reported seizures of illegal ivory, holds the only extensive information on illicit trade available. However inherent biases in seizure data make it difficult to infer trends; countries differ in their ability to make and report seizures and these differences cannot be directly measured. We developed a new modelling framework to provide quantitative evidence on trends in the illegal ivory trade from seizures data. The framework used Bayesian hierarchical latent variable models to reduce bias in seizures data by identifying proxy variables that describe the variability in seizure and reporting rates between countries and over time. Models produced bias-adjusted smoothed estimates of relative trends in illegal ivory activity for raw and worked ivory in three weight classes. Activity is represented by two indicators describing the number of illegal ivory transactions--Transactions Index--and the total weight of illegal ivory transactions--Weights Index--at global, regional or national levels. Globally, activity was found to be rapidly increasing and at its highest level for 16 years, more than doubling from 2007 to 2011 and tripling from 1998 to 2011. Over 70% of the Transactions Index is from shipments of worked ivory weighing less than 10 kg and the rapid increase since 2007 is mainly due to increased consumption in China. Over 70% of the Weights Index is from shipments of raw ivory weighing at least 100 kg mainly moving from Central and East Africa to Southeast and East Asia. The results tie together recent findings on trends in poaching rates, declining populations and consumption and provide detailed evidence to inform international decision making on elephants

A multidisciplinary study of discarding in North Sea fisheries

A multidisciplinary approach combining natural and social scientific data was used to provide a holistic view of the practice of discarding in the North Sea fisheries. The research comprised (a) a documentary analysis of discarding in the North Sea; and (b) a case study of one fishery, the English Nephrops fishery. The study aimed to identify the fundamental causes of discarding, the consequences of discarding, the factors that prevent discard reduction and the best means of effectively managing discarding.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Socio-economic and institutional incentives influencing fishers’ behaviour in relation to fishing practices and discard

Abstract Discard of unwanted catches are common in European fisheries, but reducing or banning this has been given high priority in the proposal for the reform of the Common Fisheries Policy. Although many technical regulations have been introduced to limit unwanted catches, there is little understanding of the underlying socio-economic and institutional incentives causing discard at the fisher level. The paper presents an approach which views discards as a result of decisions made both on deck and at earlier stages of the fishing planning and implementation process. Decisions made by fishers resulting in a more selective fishery are considered “selective behaviour”. It is argued that fishing practices are institutionally embedded within three institutional spheres: “state”, “market”, and “community”, which together with “natural conditions” create incentives and frameworks for discard and selective behaviour. A comprehensive list of factors which may influence discards and selective behaviour is developed and applied to three case studies—all trawl fisheries—in Denmark, Greece, and England. The paper discusses cross-case findings of how the identified factors may create drivers for discard. Finally, a refined list of factors is presented in a tree structure and the usefulness of the list as a tool for analysing drivers for discard and selective behaviour, in a context of developing mitigating measures, is discussed.</jats:p

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico evaluation, but few have yet demonstrated real benefit to patient care. Early-stage clinical evaluation is important to assess an AI system's actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use and pave the way to further large-scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multi-stakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two-round, modified Delphi process to collect and analyze expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 pre-defined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. In total, 123 experts participated in the first round of Delphi, 138 in the second round, 16 in the consensus meeting and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI-specific reporting items (made of 28 subitems) and ten generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we developed a guideline comprising key items that should be reported in early-stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings