Chapter 7

An ecological-economic model for spatial management in support of Infinity Fish

“Identifying areas (in the marine ecosystem) where stocks are more likely to be over-​exploited without effective fisheries management measures”.

Fishing is an important economic, social and cultural activity for many communities in the world. Global marine fisheries currently directly and indirectly support 35 million jobs, generating US$ 35 billion in fishing household income and US$ 8 billion in profits a year (World Bank & Food and Agriculture Organization, 2009). It provides employment in fishing, processing, and ancillary services, as well as through subsistence-​based activities at the community level (Roy et al., 2009) (Teh et al., 2011) (L. S. Teh et al., 2011). The economic impact of marine fisheries to the world economy is estimated at US$ 220 to 235 billion in 2003 (Dyck & Sumaila, 2010). Nearly one billion people worldwide, or about 20% of the global population, rely on fish as a primary source of animal protein (FAO, 2011). In many cases, fishing is undertaken for economic and/or social benefits such as revenues and livelihoods. But there are increasing focus on the impacts of over-​exploitation on the conservation of marine species (Dulvy et al., 2003) (Sadovy de Mitcheson et al., 2013), and the need to shift to ecosystem-​based fisheries management (Pitcher & Lam, 2010). This means that fisheries management needs to achieve a more balanced portfolio of objectives.5 The trade-​offs between economic and conservation objectives become severe when the vulnerability of exploited species to fishing and the incentive for overfishing are both high (Norse et al., 2012). In some extreme cases, fishing can drive species or stocks to local or near global extinction. For example, the Chinese Bahaba (Bahaba taipengensis) in the South and East China Seas is inherently highly vulnerable to fishing because of its large body size and the tendency to form spawning aggregations. The species has become Critically Endangered under the IUCN Red List of Endangered Species ( www​.redlist​.org ) primarily because of its extremely valuable swimbladder as a traditional Chinese medicine (Sadovy de Mitcheson & Cheung, 2003). Another example is the sea otter (Enhydra lutris), which was hunted to near extinction along the North American coast for the fur trade (Doroff et al., 2003).

Life history and population dynamic theories predict that fish populations with low reproductive rate are intrinsically more vulnerable to over-​ exploitation (Reynolds et al., 2005). Particularly, fishes that are large, slow growing and late-​maturing are particularly vulnerable to fishing (Cheung et al., 2005). When subjected to similar fishing mortality rate, abundance of species with higher intrinsic vulnerability decrease faster than species with lower vulnerability, all else being equal (Cheung & Pitcher, 2008). This systematic difference in sensitivity to fishing between fish species is partly the reason behind the increasing dominance of less vulnerable fish species in global fish catches (Cheung et al., 2007). However, such intrinsic vulnerability does not account for non-​biological factors, such as intensity of fishing, which ultimately determine the level of fishing mortality and exploitation status of the populations.

Bioeconomic theory predicts that optimal fishing strategy is a function of the productivity of the exploited population (represented by the intrinsic rate of population increase), cost of fishing, price of the catch and discount rate (Clark, 1973). A common driver of overfishing is the open access nature of fisheries resources, under which each fishing unit seeks to maximize its own benefits from fishing, leading to over-​exploitation of the resources. Moreover, the discount rate determines how much the flow of future costs and benefits is discounted to obtain the net present value. Thus, a high discount rate means that we value current benefits much more than those we can get (or lose) in the future (Sumaila, 2004). Given this situation, it would be economically reasonable to increase the current exploitation of the resource, particularly if we will only incur the costs associated with such an action in the distant future (Ussif Rashid Sumaila, 2004). In fisheries, fishers are considered to have their own private discount rate that is based on the intuitive discounting they apply in their decision-​making processes. However, the private discount rate of fishers has only been estimated in a few cases (e.g. (Fehr & Leibbrandt, 2008) (L. C. L. Teh et al., 2009)). According to (Clark, 1973), when the discount rate is higher than the intrinsic rate of population increase, and all else being equal, the economically optimal fishing strategy would be to overfish the stocks. When the discount rate is much higher than the fishes’ population growth rate, the theory predicts that it is economically rational to drive fish stocks to extinction (Clark, 1973). Thus, we can expect that fish stocks in regions where discount rates are high while population growth rate is low would have a relatively higher vulnerability to overfishing.

A range of fisheries management strategies and tactics have been proposed to ensure the sustainability of fisheries (Walters & Martell, 2004). Some are ‘command-​and-​control’ type management measures that manage fisheries through limiting fishing or other activities, e.g. marine protected areas, while others are ‘incentive’-​based measures that use economic or other incentives to encourage sustainable fishing practices, e.g. transferrable quotas. However, these measures have their pros and cons. Understanding the key drivers and vulnerability to overfishing provides useful information for identifying suitable strategies and tactics to effectively manage the fisheries.

In the present study, we aimed to identify, on a global scale, the bioeconomic vulnerability of fishes to overfishing. We derived an index to evaluate the vulnerability resulting from both the intrinsic biological characteristics and the economic factors that may lead to overfishing. We collected published discount rates of countries that are reported to fish in the ocean. We estimated the intrinsic population growth rate for major exploited fish species in the world. Finally, using these estimates, we calculated the bioeconomic vulnerability index on a 0.5° latitude × 0.5° longitude grid for each taxon and fishing country from the ‘Sea Around Us’ project and identified areas where the potential for overfishing is most severe. We discuss the potential application of such an index to the evaluation of fisheries management options.

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