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Fish catch data: Less than what meets the eye
Marine Policy 42 (2013) 268–269
Contents lists available at SciVerse ScienceDirect
Marine Policy journal homepage: www.elsevier.com/locate/marpol
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 b c
Marine Stewardship Council, 1-3 Snow Hill, London EC1A 2DH, United Kingdom Imperial College London, South Kensington, London SW7 2AZ, United Kingdom Department of Mathematics and Applied Mathematics, University of Cape Town, Rondebosch 7701, South Africa
art ic l e i nf o
a b s t r a c t
Article history: Received 12 March 2013 Received in revised form 21 March 2013 Accepted 21 March 2013
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.
Keywords: Fish stocks Stock assessment Developing countries
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 n
Corresponding author. Tel.: +44 20 7246 8938. E-mail addresses: [email protected] (D.J. Agnew), [email protected] (N.L. Gutiérrez), [email protected] (D.S. Butterworth). 0308-597X/$ - see front matter & 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.marpol.2013.03.020
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 assessment 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 unreliable 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 fisheryindependent 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
D.J. Agnew et al. / Marine Policy 42 (2013) 268–269
stewardship about the health of fisheries [17]. Thus, in developing countries, the issue is not Pauly's concern [1] of devoting fewer resources to collecting catch data, but rather of how to use available resources more efficiently to obtain more reliable information. Thus, increased efforts in developing faster, cheaper and less data demanding stock assessment approaches, as well as promoting communitybased data collection programs, can contribute to our knowledge of the status of world fisheries, particularly for the developing world. The current picture of global fishery stock status demonstrates that across much of the developed world, stock status has been improving since 2000 in response to direct management intervention, while the situation is not as clear for developing world and data-poor fisheries [3,18]. This rather complex message of the success and failure of fishery management is more difficult to communicate, but that does not mean that this should not be attempted. It is owed to those fishers and managers who have reacted positively to generate recovery and sustainability in their fish stocks and fishery ecosystems, to recognize their success; and to work with those fisheries that are really in poor shape to accurately determine their status and map a path to sustainability.
Referenecs [1] Myers RA, Worm B. Rapid worldwide depletion of predatory fish communities. Nature 2003;423:280–3. [2] Worm B, Hilborn R, et al. Rebuilding global fisheries. Science 2009;325:578–85. [3] Costello C, Ovando D, Hilborn R, Gaines SD, Deschenes O, et al. Status and solutions for the world's unassessed fisheries. Science 2012;338:517–20. [4] Pauly D, Hilborn R, Branch T. Fisheries: does catch reflect abundance? Nature 2013;494:303–6.
269
[5] Grainger RJR, Garcia SM. Chronicles of marine fisheries landings (1950–1994): trend analysis and fisheries potential. Technical Paper No. 3590429-9345 Rome, Italy: Food and Agriculture Organisation 1996. [6] Branch TA, Jensen OP, Ricard D, Ye Y, Hilborn R. Contrasting global trends in marine fishery status obtained from catches and from stock assessments. Conservation Biology 2011;25:777–86. [7] Carruthers TR, Walters CJ, McAllister MK. Evaluating methods that classify fisheries stock status using only catch data. Fisheries Research 2012;120: 66–79. [8] Daan N, Gislason H, Pope JG, Rice JC. Apocalypse in world fisheries? The reports of their death are greatly exaggerated ICES Journal of Marine Sciences 2011;68:1375–8. [9] Cook RM. A comment on “what catch data can tell us about the status of global fisheries (Froese et al., 2012)”. Marine Biology 2013. http://dx.doi.org/10.1007/ s00227-013-2183-y. [10] Kleisner K, Froese R, Zeller D, Pauly D. Using global catch data for inferences on the world's marine fisheries. Fish and Fisheries 2012. http://dx.doi.org/10.1111/ j.1467-2979.2012.00469.x. [11] Nokome B, Stokes S. Fisheries management procedures: a potential decision making tool for fisheries management in California. California USA: Trophia Ltd., Canterbury New Zealand and Quantitative Resource Assessment LLC La Jolla; 2011. [12] MacCall AD. Depletion-corrected average catch: a simple formula for estimating sustainable yields in data-poor situations. ICES Journal of Marine Sciences 2009;66:2267–71. [13] Punt AE, Smith DC. Smith ADM. Among-stock comparisons for improving stock assessments of data-poor stocks: the Robin Hood approach. ICES Journal of Marine Sciences 2011;68:972–81. [14] Castilla JC, Defeo O. Paradigm shifts needed for world fisheries. Science 2005;309:1324–5. [15] Prince JD. The barefoot ecologist goes fishing. Fish and Fisheries 2003;4:359–71. [16] Schroeter SC, Gutiérrez NL, Robinson M, Hilborn R, Halmay P. Moving from data poor to data rich: a case study of community-based data collection for the San Diego red sea urchin (Strongylocentrotus franciscanus) fishery. Marine and Coastal Fisheries 2009;1:230–43. [17] Gutiérrez NL, Hilborn R, Defeo O. Leadership, social capital and incentives promote successful fisheries. Nature 2011;470:386–9. [18] Worm B, Branch TA. The future of fish. Trends in Ecology and Evolution 2012;27:594–9.
Contents lists available at SciVerse ScienceDirect
Marine Policy journal homepage: www.elsevier.com/locate/marpol
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 b c
Marine Stewardship Council, 1-3 Snow Hill, London EC1A 2DH, United Kingdom Imperial College London, South Kensington, London SW7 2AZ, United Kingdom Department of Mathematics and Applied Mathematics, University of Cape Town, Rondebosch 7701, South Africa
art ic l e i nf o
a b s t r a c t
Article history: Received 12 March 2013 Received in revised form 21 March 2013 Accepted 21 March 2013
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.
Keywords: Fish stocks Stock assessment Developing countries
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 n
Corresponding author. Tel.: +44 20 7246 8938. E-mail addresses: [email protected] (D.J. Agnew), [email protected] (N.L. Gutiérrez), [email protected] (D.S. Butterworth). 0308-597X/$ - see front matter & 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.marpol.2013.03.020
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 assessment 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 unreliable 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 fisheryindependent 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
D.J. Agnew et al. / Marine Policy 42 (2013) 268–269
stewardship about the health of fisheries [17]. Thus, in developing countries, the issue is not Pauly's concern [1] of devoting fewer resources to collecting catch data, but rather of how to use available resources more efficiently to obtain more reliable information. Thus, increased efforts in developing faster, cheaper and less data demanding stock assessment approaches, as well as promoting communitybased data collection programs, can contribute to our knowledge of the status of world fisheries, particularly for the developing world. The current picture of global fishery stock status demonstrates that across much of the developed world, stock status has been improving since 2000 in response to direct management intervention, while the situation is not as clear for developing world and data-poor fisheries [3,18]. This rather complex message of the success and failure of fishery management is more difficult to communicate, but that does not mean that this should not be attempted. It is owed to those fishers and managers who have reacted positively to generate recovery and sustainability in their fish stocks and fishery ecosystems, to recognize their success; and to work with those fisheries that are really in poor shape to accurately determine their status and map a path to sustainability.
Referenecs [1] Myers RA, Worm B. Rapid worldwide depletion of predatory fish communities. Nature 2003;423:280–3. [2] Worm B, Hilborn R, et al. Rebuilding global fisheries. Science 2009;325:578–85. [3] Costello C, Ovando D, Hilborn R, Gaines SD, Deschenes O, et al. Status and solutions for the world's unassessed fisheries. Science 2012;338:517–20. [4] Pauly D, Hilborn R, Branch T. Fisheries: does catch reflect abundance? Nature 2013;494:303–6.
269
[5] Grainger RJR, Garcia SM. Chronicles of marine fisheries landings (1950–1994): trend analysis and fisheries potential. Technical Paper No. 3590429-9345 Rome, Italy: Food and Agriculture Organisation 1996. [6] Branch TA, Jensen OP, Ricard D, Ye Y, Hilborn R. Contrasting global trends in marine fishery status obtained from catches and from stock assessments. Conservation Biology 2011;25:777–86. [7] Carruthers TR, Walters CJ, McAllister MK. Evaluating methods that classify fisheries stock status using only catch data. Fisheries Research 2012;120: 66–79. [8] Daan N, Gislason H, Pope JG, Rice JC. Apocalypse in world fisheries? The reports of their death are greatly exaggerated ICES Journal of Marine Sciences 2011;68:1375–8. [9] Cook RM. A comment on “what catch data can tell us about the status of global fisheries (Froese et al., 2012)”. Marine Biology 2013. http://dx.doi.org/10.1007/ s00227-013-2183-y. [10] Kleisner K, Froese R, Zeller D, Pauly D. Using global catch data for inferences on the world's marine fisheries. Fish and Fisheries 2012. http://dx.doi.org/10.1111/ j.1467-2979.2012.00469.x. [11] Nokome B, Stokes S. Fisheries management procedures: a potential decision making tool for fisheries management in California. California USA: Trophia Ltd., Canterbury New Zealand and Quantitative Resource Assessment LLC La Jolla; 2011. [12] MacCall AD. Depletion-corrected average catch: a simple formula for estimating sustainable yields in data-poor situations. ICES Journal of Marine Sciences 2009;66:2267–71. [13] Punt AE, Smith DC. Smith ADM. Among-stock comparisons for improving stock assessments of data-poor stocks: the Robin Hood approach. ICES Journal of Marine Sciences 2011;68:972–81. [14] Castilla JC, Defeo O. Paradigm shifts needed for world fisheries. Science 2005;309:1324–5. [15] Prince JD. The barefoot ecologist goes fishing. Fish and Fisheries 2003;4:359–71. [16] Schroeter SC, Gutiérrez NL, Robinson M, Hilborn R, Halmay P. Moving from data poor to data rich: a case study of community-based data collection for the San Diego red sea urchin (Strongylocentrotus franciscanus) fishery. Marine and Coastal Fisheries 2009;1:230–43. [17] Gutiérrez NL, Hilborn R, Defeo O. Leadership, social capital and incentives promote successful fisheries. Nature 2011;470:386–9. [18] Worm B, Branch TA. The future of fish. Trends in Ecology and Evolution 2012;27:594–9.