Porter Hoagland and Di Jin, Marine Policy Center, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02543 USA

Abstract

During the past several decades, harmful algal bloom (HAB) events have occurred in more locations than ever before throughout the United States and the world. Marine scientists continue to identify ever larger numbers of algal species involved in such events. There are now more known toxins, and fisheries have been affected more widely. Whether this global increase in HABs is taking place because of enhanced nutrient and pollutant loadings from anthropogenic sources is a topic of continuing debate within the marine scientific community. Whatever the reasons, virtually all coastal regions of the United States are now subject to an unprecedented variety and frequency of HAB events. In many places, these events have resulted in measurable economic damages. When such damages are likely to be significant, it is sensible to estimate their size. If the economic damages of HAB events are large enough, then it may be appropriate to take actions to mitigate their effects. We suggest an economic decision framework for determining the appropriateness of such actions.

In earlier work, we have developed an estimate of the "economic impacts" of HABs for events in the United States where such impacts were measurable with a fair degree of confidence during the six-year period from 1987 to 1992 (Anderson et al. 2001). We define the term economic impact broadly to mean either lost gross revenues in the relevant product or factor markets, expenditures for medical treatments, environmental monitoring, and management, or other costs that would not have been incurred in the absence of HABs. Although estimates of economic impacts are not always useful in a normative sense (i.e., they may involve only a crude estimate of true economic losses), they may help to guide our thinking about the identification and implementation of appropriate policy responses. Our study considered impacts of four basic types: (1) public health; (2) commercial fisheries; (3) recreation and tourism; and (4) monitoring and management. In the United States, a conservative estimate of total economic impacts due to HABs is on the order of $50 million per year. More importantly, however, the historical record reveals the occurrence of individual HAB events with economic damages that have met or exceeded our average annual estimate.

HABs can result in negative economic impacts, but management measures undertaken to reduce or eliminate the economic damages of HABs can be costly too. In the United States, we estimate that HAB monitoring and management costs amount to approximately $2 million each year. A wide range of potential policy responses exist (see Table 1), although only a subset may be appropriate for any particular location, type of affected resource, or type of bloom. As we increase the level of any particular policy response (or set of complementary responses), we expect to see the economic damages from a HAB event decline. At the same time, we expect that the costs of the response may increase. The economically efficient level of response is found at that point where the sum of both economic damages and response costs are minimized. In some cases, private financial resources or public budgets may limit the level of response, thereby constraining mitigation to a suboptimal level.

We are in the process of developing a framework for the economically efficient control of HABs. The base of the framework is a theoretical model that allows decisionmakers to choose the optimal level of a policy response to a HAB event. However, before applying the theoretical model, several steps must be taken. It is important first to tailor the set of feasible responses to the type of HAB. Next, we need to characterize the extent to which economic damages may be reduced or eliminated through the implementation of each response (or through the implementation of a set of complementary responses). Third, we should estimate the costs associated with adopting each response (or combination of responses). Finally, we should evaluate the net benefits of implementing the response (or combination).