Call for special issue: “Assessing the Data Poor Stocks”

The ever-increasing human population as oppose to dwindling food resources, increases the reliance on the seas. For this very reason, the United Nations, among 17 sustainable development goals, stipulates conservation and sustainable use of the oceans, seas, and marine resources.  With this goal, the responsibility is placed on the shoulders of the coastal states whether or not their economies can afford the necessities entailed. Sustainability necessitates good management practices, and good management demands reliable data that can help assess the production capacity and status of the resources. However, fisheries data is costly to come by, and the cost is particularly challenging for nations with limited resources and where the fishery is practiced dispersedly. The scientific skills needed to collect some primary data that are commonly used in the management of the stocks, such as age, entail costly investments in terms of time and expertise. Hence, data-demanding advanced stock assessment methods can hardly be applied in the management of small-scale fisheries or fisheries in developing countries.

This bottleneck standing in front of UN's SDG accelerates the development of fish stock assessment models that can be applied in data-poor situations. Such models prepared for this purpose, which runs with some primary data, such as catch statistics, are easy to use and have impressive outputs, have started to become widespread. Considering the increase in the number of data-poor assessment models developed worldwide, it seems certain that they will be widely used in the future, too.

The main challenge in these type of models are, the weakness of the data is largely compensated by expert knowledge. Therefore, those who use these models are expected to have sufficient information about the stock, biology of the species, and fishery they are working with and be able to quantify and incorporate this information in the model. It is also underlined that if these conditions are not met, the results to be obtained can be highly misleading. Thus, the assessment results produced by data-poor models are considered only within the context of precautionary management by most of the regional fisheries management organizations.

The main theme of this special issue is data-poor fish stock assessment models, and it aims to publish articles addressing the correct use of these models. With that regard, this special issue invites,

- studies comparing the results of the full analytical models with that of data-poor models;

- examples highlighting the pros, as well as the cons of data-poor stock assessment models;

- studies addressing the pitfalls that should be avoided when using such models,

as well as case studies assessing the status of data-poor (not poor data) fish stocks.

It is hoped that the articles to be published in this issue will not only guide future users of data-poor assessment models,  but also, the problems to be underlined will guide those who will further improve such models.

Key Dates

Papers submission opening: March 16, 2022
Submission deadline: October 16, 2022

Specal Issue Editors

Manuscript Submission Information
Manuscripts should be submitted online at:

https://www.trjfas.org/submit/login.php

Manuscripts can be submitted until the deadline. At the beginning of submission, "Special Issue" should be selected from the “Manuscript Type” section.

Research and review papers are invited. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). Submitted papers should be well formatted and use good English. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page.

Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue section of journal website.