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Ongoing declines in production of the world's fisheries may have serious ecological and socioeconomic consequences. As a result, a number of international efforts have sought to improve management and prevent overexploitation, while helping to maintain biodiversity and a sustainable food supply. Although these initiatives have received broad acceptance, the extent to which corrective measures have been implemented and are effective remains largely unknown. We used a survey approach, validated with empirical data, and enquiries to over 13,000 fisheries experts (of which 1,188 responded) to assess the current effectiveness of fisheries management regimes worldwide; for each of those regimes, we also calculated the probable sustainability of reported catches to determine how management affects fisheries sustainability. Our survey shows that 7% of all coastal states undergo rigorous scientific assessment for the generation of management policies, 1.4% also have a participatory and transparent processes to convert scientific recommendations into policy, and 0.95% also provide for robust mechanisms to ensure the compliance with regulations; none is also free of the effects of excess fishing capacity, subsidies, or access to foreign fishing. A comparison of fisheries management attributes with the sustainability of reported fisheries catches indicated that the conversion of scientific advice into policy, through a participatory and transparent process, is at the core of achieving fisheries sustainability, regardless of other attributes of the fisheries. Our results illustrate the great vulnerability of the world's fisheries and the urgent need to meet well-identified guidelines for sustainable management; they also provide a baseline against which future changes can be quantified.
Effective C And More Effective C By Myers Pdf Download
Global fisheries are in crisis: marine fisheries provide 15% of the animal protein consumed by humans, yet 80% of the world's fish stocks are either fully exploited, overexploited or have collapsed. Several international initiatives have sought to improve the management of marine fisheries, hoping to reduce the deleterious ecological and socioeconomic consequence of the crisis. Unfortunately, the extent to which countries are improving their management and whether such intervention ensures the sustainability of the fisheries remain unknown. Here, we surveyed 1,188 fisheries experts from every coastal country in the world for information about the effectiveness with which fisheries are being managed, and related those results to an index of the probable sustainability of reported catches. We show that the management of fisheries worldwide is lagging far behind international guidelines recommended to minimize the effects of overexploitation. Only a handful of countries have a robust scientific basis for management recommendations, and transparent and participatory processes to convert those recommendations into policy while also ensuring compliance with regulations. Our study also shows that the conversion of scientific advice into policy, through a participatory and transparent process, is at the core of achieving fisheries sustainability, regardless of other attributes of the fisheries. These results illustrate the benefits of participatory, transparent, and science-based management while highlighting the great vulnerability of the world's fisheries services. The data for each country can be viewed at _assessment.
Effectiveness is defined in terms of scientific robustness, policymaking transparency, implementation capability, and extent of fishing capacity, subsidies, and access to foreign fishing. Each attribute was quantified with a set of questions, whose answers were summarized into a single scale using multidimensional scaling (see Materials and Methods). For display purposes, each scale was divided into four quarters aligned from worst- to best-case scenarios (each quarter is color coded as indicated at the bottom of the figure). Our assessment of fishery management effectiveness started with the classification of all analyzed EEZs among the four quarters on the scale of scientific robustness. The EEZs within each of those quarters were then classified among the four quarters on the scale of policymaking transparency, and then those EEZs classified among the quarter of the next attribute, with the subdivision continuing until all EEZs were classified in all attributes. The size of the bubbles is proportional to the number of EEZs classified in each quarter. For purposes of display, subsidies, overcapacity, and fishery access agreements were summarized in a single scale with multidimensional scaling; full results are provided in the Figure S1.
Our assessment of the extent of fishing capacity, subsidies, and access to foreign fishing fleets yielded the following results. We found that fleet sizes are quantified and regulated in 20% of the world's EEZs (Figure S1N), although in 93% of EEZs, fishing fleets face some level of modernization to catch fish more efficiently or cheaply (Figure S1O). Thus, although fishing capacity may be reduced in terms of fleet size, fishing power may remain constant or even increase due to technological improvements (i.e., fewer improved boats being more effective at catching fish). Effective controls on fleet size were more common among high-income than low-income EEZs (p
To provide a general overview of fisheries management effectiveness, we averaged all scores on the scales of scientific robustness, policymaking transparency, implementation capability, fishing capacity, subsidies, and access to foreign fishing. We excluded the effects of small-scale and recreational fisheries, recognizing that their lack of management would extensively reduce the scores. Only 5% of all EEZs were in the top quarter of this scale (Figure S1S, countries depicted in Figure 4), with high-income EEZs having significantly better overall management effectiveness than low-income ones (p
We focused our assessment on fishery management conditions for all ocean realms under the sovereignty of a defined coastal territory. Under the United Nations Convention on the Law of the Sea [39], the protection and harvesting of coastal resources rest within the 200-nautical mile EEZ of each coastal state. There are, however, exceptions, such as the European Union, whose fisheries regulations are mandated by the Common Fisheries Policy but whose enforcement is the responsibility of the member states; member states also differ in their fishing capability and possibly in their compliance with regulations. Similarly, many countries have overseas territories, which may or may not have autonomous control of the regulation of their fisheries, and consequently, there may be variations in the effectiveness of their management regimes. For instance, Saint Pierre and Miquelon, French Guiana, French Polynesia, French Southern and Antarctic lands, New Caledonia, Saint Martin, Reunion, Guadeloupe, and Martinique all are under the sovereignty of France, which furthermore has direct control over its own Atlantic and Mediterranean coast; yet all of these zones have different management conditions. To consider these differences in fishery management regimes, zones managed under the same entity (e.g., the European Union) or zones in different parts of the world belonging to the same sovereignty (e.g., overseas territories of France, United Kingdom, and United States) were analyzed separately. We also included zones that may not be technically defined or recognized as EEZs under the United Nations (e.g., division among coastal states of the Baltic Sea and Black Sea). In total, 245 such zones exist in the world (see Figure 3), which excludes conflict zones (e.g., the Paracel Islands, Spratly Islands, and Southern Kuriles). Out of those 245 zones, we were unable to gather data for isolated islands under the sovereignty of the United Kingdom (i.e., Ascension, Pitcairn, Saint Helena, South Georgia, and the South Sandwich Islands and Tristan da Cunha) and France (Clipperton Atoll) for which neither contacts nor information was available. We also excluded Monaco and Singapore; interviewees at local authorities (Coopération Internationale pour l'Environnement et de Développement in Monaco and the Agri-Food and Veterinary Authority in Singapore) in both of these countries claimed that although marine fishing occurs, it was minimal and considered insufficient to motivate governmental regulation. The final database contained complete data for 236 zones. Although all data are reported in Figures 3 and 4, the statistics reported in the text were based on 209 inhabited zones for which per capita Gross Domestic Product data exist; that excluded uninhabited and isolated atolls to prevent biases due to the fact that we could not get data for all such areas (i.e., United Kingdom and France, see above).
Data on fisheries sustainability was quantified for the year 2004 and linked to the effectiveness of fisheries management using a classification/regression tree. A classification tree tests for significant differences in fisheries sustainability among the quarters of each attribute (note that the first and fourth quarters are the extremes of a scale from worst- to best-case scenarios for each attribute; see Figure 2). The attribute that maximizes differences among quarters (i.e., smallest p-value) is placed at the root of the tree and the EEZs in each of those quarters separated in different branches. Subsequently, the EEZs in each branch are tested for significant differences among quarters of the remaining attributes. The attribute that maximizes differences among quarters is placed at the base of the branch and the EEZs in each of those quarters separated in upper branches. The process is repeated until no differences are found within each branch in any remaining attribute. This analysis included all attributes considered in this study: scientific robustness, policymaking transparency, implementation capability, fishing capacity, subsidies, access to foreign fishing, and country wealth (i.e., 2007 per capita Gross Domestic Product larger or smaller than US$10,000, respectively). Given the inflation of Type I errors due to multiple comparisons, significance was set at p 2ff7e9595c
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