Short communication Fish catch data: Less than what meets the eye David J. Agnew a,b , Nicolas L. Gutiérrez a,n , Doug S. Butterworth c a Marine Stewardship Council, 1-3 Snow Hill, London EC1A 2DH, United Kingdom b Imperial College London, South Kensington, London SW7 2AZ, United Kingdom c Department of Mathematics and Applied Mathematics, University of Cape Town, Rondebosch 7701, South Africa article info Article history: Received 12 March 2013 Received in revised form 21 March 2013 Accepted 21 March 2013 Keywords: Fish stocks Stock assessment Developing countries abstract A recent opinion piece published in Nature summarises the differing views held by Pauly on the one hand, and by Hilborn and Branch on the other, regarding the challenge faced by fishery scientists in accurately determining the status of the world's fisheries. Both commentaries discuss whether the fisheries catch data published by FAO can by themselves be used to infer fishery status. The purpose of this short communication is to examine both views and to propose additional solutions to contribute to the understanding of fishery status globally. These may include expanding data-poor stock assessment methods as well as community-based data collection and monitoring programs, particularly in developing countries. & 2013 Elsevier Ltd. All rights reserved. Interest in the state of the world's fishery resources has been increasing dramatically in the last few years [1–3]. The recent opinion piece in the journal Nature by Pauly from one perspective, by Hilborn and Branch from another [4], captures very well the issues facing fishery scientists as they grapple with the challenge of determining stock status and sustainable management approaches for the world's fisheries. However, the particular point at issue is not whether catch data are unimportant; rather it is that on their own, catch data are not a reliable indicator of stock status. To understand why this is so one must first examine under what circumstances catch data are ever likely, on their own, to be a useful indicator of stock status. This is the case where fishing activity is unconstrained by management, where this activity is unaffected by dynamic fishery economics (the cost of extraction and the value of fish) and particularly the world trade in fish, and where fish population dynamics can be expected to be more or less predictable. Whilst these may have been appropriate simplifying assumptions when FAO scientists developed the approach which they used in 1996 to infer stock status [5], this is no longer so given the further information available now almost 20 years later. The failure of stock status determination methods based solely on catch data has been repeatedly demonstrated ([6–9] and figure 2 in Ref. [4]), but still some scientists seek to continue to promulgate their use [4,5]. Even when corrected for recent management intervention [10], such methods cannot accurately determine stock recovery and rarely predict anything other than a continuing decline in world fish stock status that leads to a conveniently simple (see figure 1 in Ref. [4]) but misleading message. The inconvenient truth is that determining stock status is not simple, and requires the use of multiple data sources in addition to catch data to avoid misinterpretations and confusion within managers, policy makers and the general public. While Hilborn and Branch [4] suggest use of data from surveys conducted from research vessels, age and size distributions of fish, and catch per unit of effort, Pauly [4] argues that this information is not readily available in developing countries nor there is the capacity to build such databases. However, none of the authors proceeds to suggest alternative solutions to this problem. Traditional stock assessment methods are costly and demand large quantities of time and information. However, simple assess- ment methods that use historical catches and size-composition information could potentially be applied to many data-poor stocks. Although important advances have been made in the last decade to develop both fishery evaluation and decision making methods (including simple generic management procedures [11]) that are amenable to data-limited situations [12,13], the ability of such models to assess the status of fish stock reliably still depends on the quality of the information [7]. In most developing countries and small-scale fisheries, information is indeed scarce and unreli- able due to limited resources to conduct surveys and fieldwork by management agencies [14]. A promising solution is when fishers are trained to collect both fishery-dependent and fishery- independent information at relevant temporal and spatial scales [15,16]. These community-based data collection and monitoring programs provide an alternative and cost-effective way of expanding fisheries information while raising community awareness and Contents lists available at SciVerse ScienceDirect journal homepage: www.elsevier.com/locate/marpol Marine Policy 0308-597X/$ - see front matter & 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.marpol.2013.03.020 n Corresponding author. Tel.: +44 20 7246 8938. E-mail addresses: David.agnew@msc.org (D.J. Agnew), Nicolas.gutierrez@msc.org (N.L. Gutiérrez), Doug.Butterworth@uct.ac.za (D.S. Butterworth). Marine Policy 42 (2013) 268–269