Groundfish Fleet Restructuring Information and Analysis Project

3. Results of Numerical Scenarios

In this chapter, we consider four hypothetical ways of reducing the groundfish fleet. These scenarios all follow the same, numerical, logic: various proportions of vessels in excess of those "needed" according to the capacity utilization estimates derived in chapter 2 above are eliminated from the distribution. Landings, ex vessel revenues, incomes, and fleet composition after each such reduction is then compared to the 2000 base year. The analysis is a static comparison of the 2000 "before" and the post-reduction "after" status of the fleet. It is important to note that these scenarios do not reflect any actual policy choices-we deliberately chose numerical ways of "slicing and dicing" the fleet to illustrate the GFR framework. Other scenarios could be developed for the purpose of evaluating different fleet reduction options, for example the proposed trawl buyback. Several important caveats apply. Firstly, the analysis is static; in the absence of detailed behavioral models of how the fishing fleet reacts to fleet changes-or, for that matter, other determinants like weather, environmental change or the normal suite of regulations-it is impossible to predict any adaptive response. Secondly, therefore, these numerical scenarios are not intended as viable policy alternatives per se. Rather, they illustrate the kinds of questions that can be examined in the GFR framework. To the extent that stakeholders in the fishery can agree on first order approximations of their adaptive behavior, even the static model can be used to assess policy options. We illustrate this in the next chapter, where we simulate the effects of the 2002 in-season shelf closure and of a permit stacking scheme in the LE trawl fleet based on certain assumptions. By contrast, the numerical reductions do not hinge on any assumptions about behavior. They are properly interpreted as approximations of the effects of removing varying types and numbers of vessels from the fleet and illustrate the relative distributional effect from exiting vessels to those remaining. The coast-wide summary results we present indicate the order of magnitude of income foregone by vessels leaving the fleet, which is what would presumably serve as the basis for a policy debate about compensatory or mitigation measures. Given that the total allowable catch would not necessarily change, it-and the associated income-accrues to fewer vessels remaining after a reduction. In the following section we describe the four numerical scenarios. In section 3.2 we discuss the framework we used for the economic analysis of the reduction scenarios, and describe how we integrate it with other considerations of community impacts. Section 3.3 contains the results from the four numerical scenarios, summarized for the entire coast; the final section, 3.4., illustrates the different effects these scenarios have on different communities, using the examples of Newport and Port Orford. Information on additional communities can be found in Appendix C, or can be requested from the principal investigator.

3.1 Description

Using the capacity estimates from chapter 2 above, we consider four numerical scenarios for reducing the 2000 fleet capacity:

1. by the total number of vessels in excess of those needed to harvest the 2000 allowable catch,
2. by 50% in each sector at random,
3. by 50% in each sector while preserving fleet diversity, and
4. by selecting vessels to remain in the fleet that meet minimum ex vessel revenue levels in each sector, respectively.

It is important to note that these numerical manipulations of the data are blind to the political and practical exigencies that would influence a capacity reduction measure in reality. Identifying vessels purely by the capacity estimates derived for each fleet sector is, in all likelihood, not how participants in the fishery and decision-makers would want to go about reducing the fleet, nor should the SSC capacity analysis be construed as suggesting such a course of action. We merely use the existing capacity analysis, adapted to the data available to our project, as a point of departure for our fleet reduction inquiry and to illustrate the GFR framework, which we submit may be useful for assessing any restructuring of the groundfish fleet and indeed other marine management measures.

What these "unrealistic" numerical scenarios illustrate, however, is that different reduction schemes have substantially different effects on different parts of the coast and on fleet diversity (defined here in terms of gear types and vessel size). The scenarios also have different implications for the overall amount of income that is effectively redistributed from those vessels exiting the fleet to those remaining in it, and thus may be useful for considering mitigation and compensatory measures to facilitate the transition of coastal communities. More realistic reduction scenarios would consider other criteria for identifying boats to leave the fleet, notably their willingness and readiness to exit, past landings and/or revenues, the number and diversity of fisheries in which vessels participate, or some set of optimal characteristics desired for the remaining fleet-size, profitability, habitat impacts, and so on.

Using the SSC estimates of the number of vessels needed, we asked the question "given the number of vessels needed, what might a capacity reduction look like?" The four scenarios are our answers to that question, and are intended to illustrate the kinds of effects on the different fleet sectors one might expect under various management objectives. Given the number-of-vessels-needed benchmark, we devised four different ways of reducing capacity by selecting the vessels from the corresponding number of vessels not needed in each fleet sector and analyzing the effects of their removal. Again, the overall coast-wide effect of a capacity reduction is that the harvest targets are now caught by fewer boats, whose owners are presumably better off. This entails a redistribution of income along the coast, between vessels that exit and those that stay in the fishery. In other words, landings and ex vessel revenues decline initially by the amounts associated with the eliminated vessels. This has income impacts on each port affected, and also indicates the magnitude of the redistributive effect of a fleet restructuring. Other effects include changes in the fleet composition and the types of fishing gears used to target groundfish. There are also other effects that can only be intimated with the present analysis. For example, depending on the size of and gear types used by the remaining fishing vessels, fishing activity may center on different areas on the fishing grounds than before a reduction. These dynamic and adaptive effects are beyond the scope of the GFR project. Nonetheless, the comparative statics of the scenarios presented here may suggest useful avenues for further inquiry.

Scenario 1: Removing all excess capacity

The first is the most extreme scenario, and captures what would happen if all the unneeded vessels were removed from the fishery and capacity was perfectly matched to the harvest targets at year 2000 levels. In other words, only exactly as many boats remain in the fishery as the SSC analysis found necessary. This obviously exceeds the 50% capacity reduction targets adopted by the PFMC's Strategic Plan, and would entail substantially larger reductions in some fleet sectors. While perhaps not politically desirable, we thought it useful to depict this capacity benchmark. Depending on what causes are attributed to the present state of over-capacity in the fleet, the coast-wide effects of this scenario can be thought of an indication of what it would take to rectify past decisions that led to the status quo. We eliminated all but the highest producers up to the number of vessels needed in each fleet sector in order to achieve the reduction goal with the minimum number of vessels necessary, given the 2000 harvest levels. In case of the open access (OA) fishery, we follow the SSC report in considering a high and low case with 100 or 50 vessels remaining, respectively (SSC Economics Subcommittee 2000). Based on the overlap of vessels in the LE non-trawl sectors that target sablefish and/or rockfish, we identified 16 vessels that had both sablefish endorsements and appeared to be targeting sablefish exclusively. We assumed that these 16 vessels would fulfill the capacity needs for harvesting sablefish, and thus did not reduce this subsector of the fleet. In the other fishery sectors, this scenario required reductions between 55% (LE trawl) and 93% (OA, low capacity utilization case).

Scenario 2: Reducing capacity by 50% at random in each fleet sector

This scenario is an apolitical version of the PFMC goal articulated in the Strategic Plan. Since the PFMC has yet to identify the mechanism for removing 50% of the capacity in each sector, we picked vessels at random. Clearly the method for identifying vessels has repercussions on the composition of the remaining fleet, which the random choice ignores. Given the considerably different capacity utilization rates across the fleet, this has the effect of pegging the reduction to current capacity rather than to what is needed for harvesting the allowed catch. In the sablefish-exclusive subsector that we identified, for example, this scenario results in removing half of the vessels deemed needed. In this scenario, we assigned numbers to vessels and picked them at random (using computer software designed for this purpose) until the halfway mark in each sector was achieved.

Scenario 3: Removing 50% of vessels in each size class within each fleet sector

With this scenario we tried to approximate the goal articulated in the Strategic Plan of preserving fleet diversity. The idea is to have vessels of all sizes and gear types remain in the fishery in order to maintain a varied production base and different kinds of fishing activities along the coast. It is not clear how this will be accomplished in practice. As a first approximation to maintaining fleet diversity, we used vessel length as an indicator of diversity, since this seems to fit at least the colloquial interpretation of fleet diversity and the distinction people along the coast make between "big" and "small" boats. To the extent that the fleet sectors are characterized by different gear types, it would be equally possible to distinguish between the kinds of gears used, or a combination of factors. In this scenario, we removed 50% of all vessels in each fleet sector by removing the low producers in each size class up to half of that class. The remainder of the fleet thus represents the high producers in each vessel size class, and each fleet sector has the same proportion of large and small vessels as before the reduction exercise.

Scenario 4: Reducing capacity in each sector while preserving economic viability

In the fourth and final scenario, we consider a different kind of capacity reduction logic. Rather than using the capacity estimates for determining how many vessels exit the fleet, we explored another often-cited goal for capacity reductions: to make the remainder of the fleet more economically viable. This would suggest that vessels that currently manage to make a living in the fishery stay in, irrespective of whether they are needed or not in numerical terms. Essentially this presumes that people can make a living in the fishery regardless of whether capacity is matched to the harvest targets.

Arguably this is the most subjective of our scenarios, since the definition of "making a living" differs from person to person, and from vessel to vessel. From conversations with fishermen, however, it seems that there are shared notions about the level of landings or revenues that distinguishes fulltime fishermen from those making a part time or occasional effort. Certainly the adequate maintenance and upkeep of vessels requires a certain level of income. Lacking comprehensive cost-earnings data, it was not feasible to determine the appropriate levels of revenues for each fleet sector statistically. Instead, we made some educated guesses based on marked "kinks" in the distribution of ex vessel revenues in each fleet sector. The analysis could easily be rerun using other specifications.

We eliminated from the fleet all vessels that did not achieve a minimum level of revenues. These cut-off points were, respectively,

• Ex vessel revenues greater than $50,000 for vessels in the LE trawl sector;
• Greater than $10,000 in the LE non-trawl/non-sablefish sector;
• Greater than $20,000 in the sablefish-exclusive sector;
• And greater than $5,000 in the open access fishery.

In other words, for a vessel to remain in, e.g. the LE trawl sector, it had to have recorded at least $50,000 in groundfish ex vessel revenues in 2000. It is important to note that our data only contain groundfish landings, so we are not considering revenues generated from participating in other fisheries, e.g. crab or salmon. We are only considering groundfish-related revenues and use these four figures as benchmarks for "making a living" in each sector. Again, these values are ad hoc and could be changed to reflect other assumptions about the economic realities of the various fishery sectors. Before presenting the results from these four numerical scenarios, we turn to the economic and community analysis we conducted in the GFR project.

 

3.2 Assessing Impacts

Whether planned or by attrition, any rationalization of the fleet will have both immediate and less immediate impacts on coastal communities. The Oregon Coastal Zone Management Association likens the groundfish transition to the structural changes affecting the logging industry since the late 1980s in the wake of environmental legislation and market forces (Oregon Coastal Zone Management Association 2002). While the transition will no doubt be painful, recent fishery management measures can lead towards recovery of depleted species, and deliberate planning may help mitigate the adverse effects of the fleet rationalization on communities. As a first step in anticipating the likely changes, we have compiled economic, demographic and other information about coastal communities that we hope will be useful in planning for the transition.

Before outlining the economic model used for assessing immediate income impacts of the fleet reduction scenarios considered in the GFR project, as well as the components of a broader community analysis, it is important to consider the context for community analysis. The law requires that the people and places that stand to be affected by policy measures be considered. In the case of fishery management, National Standard 8 of the Magnuson Stevens Fishery Conservation and Management Act of 1996 (a.k.a. The Sustainable Fisheries Act) requires that

"Conservation and management measures shall, consistent with the conservation requirements of this Act (including the prevention of overfishing and rebuilding of overfished stocks), take into account the importance of fishery resources to fishing communities in order to (A) provide for the sustained participation of such communities, and (B) to the extent practicable, minimize adverse economic impacts on such communities" (Sec. 301, Magnuson Stevens Act 1996).

Typically, community impacts enter into the regulatory process in the form of environmental impact statements, regulatory impact analysis and other assessments required under the Magnuson Stevens Act and other legislation. Various forms of quantitative and qualitative analysis are routinely used in this stage of policy making, ranging from a full-fledged cost-benefit analysis of policy alternatives to qualitative statements about expected effects (Pautzke 2000). A review of recent groundfish regulations suggests that the accepted format of community analysis mainly entails comparisons of gross ex vessel revenues and landings, occasionally augmented by considerations of income impacts using a regional economic impact model developed for the fishery management council (described in SSC Economics Subcommittee 1994).

We use the current version of PFMC's Fishery Economic Assessment Model (FEAM), to derive income impacts of our reduction scenarios. The FEAM is described in more detail in the next section. Essentially it translates changes in landings due to regulatory measures into the concomitant changes in income for the various communities along the coast. Changes in harvesters' and processors' incomes, however, are only part of the picture of the impacts on coastal communities. In section 3.2.2. below, therefore, we describe some additional metrics of change in communities that we adapted for the purposes of the GFR project.

3.2.1. Economic impacts

The effect of fleet reductions is effectively a zero-sum game: the declines in landings and revenues in some ports are matched by increases in landings and revenues in other ports, depending on the distribution of the remaining fleet. In the GFR analysis, however, we focus our attention on an earlier stage-right after the removal of the excess vessels, before the remaining vessels have the opportunity to harvest the freed up allocation. Effectively, our scenarios consider the impacts on landing ports of a number of vessels disappearing, as if they had sunk: the initial, local effect is a loss in landings and concomitant revenues. These declines will translate in reduced fish sales to processors, and result in lower incomes for fishing families and processors, as well as -in a derivative effect- for marine suppliers and other fishing-related businesses. In addition to landings and ex vessel revenues, we focus on the income impacts in the presentation of the scenario results, since these give a first order estimate of the effects likely to be felt along the coast.

The FEAM provides a mechanism for estimating some of the income impacts associated with changes in groundfish landings. The FEAM belongs to a class of regional input-output models that treat the economic activity in a region as a set of interconnected sectors. It is routinely used on the coast to describe the income generated from various fishing activities (see for example the recent report by the Oregon Coastal Zone Management Association 2002). Each dollar generated in one sector has a "multiplier effect" because it generates economic activity in other sectors. For example, fish are landed and the vessel is paid a price per pound for its catch, generating the ex vessel revenue. Out of this revenue, crew shares, maintenance and moorage costs and other expenses are paid, which in turn generates personal income, and revenues for the port district and other marine-related businesses. The FEAM estimates these effects for the two primary sectors affected by fishing activity, i.e. harvesters (fishermen and their families) and processors. The currently available version of FEAM is based on a 1996 version of a national input-output model that generates lists of coefficients describing the relationships between various economic sectors. These have been adapted to a regional, fisheries-specific model, i.e. the FEAM, which is then used to generate a set of multipliers for various fisheries and their harvesting and processing sectors. These model outputs have been summarized in a set of spreadsheets available from the PFMC (Davis 1998), which can readily be integrated into the GFR framework.

We consider the economic impacts of each scenario for communities and the entire coast. Typically, for each pound in landings there are between $1 and $4 in income impacts (Davis 1998), depending on the value of species and the kind of processing they undergo. For example, higher value species like sablefish have a proportionately larger impact than low-value, high-volume species like whiting. The FEAM only considers a fraction of all groundfish species targeted and some regionally important market sectors, such as live rockfish, are not modeled at all. Since the FEAM only considers a subset of groundfish species ("sablefish", "thornyheads", "soles/flounders", "other rockfish and perch" and "whiting"), we reassigned the species contained in our landings data into the appropriate FEAM groups before applying the local impact multipliers derived in FEAM. We then estimated the impacts of each reduction scenario on each port (by port group). The port impacts are then converted into statewide impacts, which in turn are converted into coast-wide impacts. In other words, each pound of groundfish landed in a port has local and coast-wide income impacts. Detailed results for all coastal communities can be found in Appendix C. In the interest of brevity, we only report the coast-wide results in section 3.3 below.

Distributional effects. Again, it is important to note that these immediate income impacts are not permanent but have differential effects, depending on whether the vessels in a port are among those removed or remaining in the fleet. In section 3.3 we compare the four scenarios in terms of their coast-wide economic impacts. Since the overall landings and associated income does not change under our assumption of constant harvest targets, the difference between the base and each scenario essentially constitutes the amount of income that will be reallocated from the vessels departing the fishery to those remaining in it. Each scenario is associated with a change in landings, and so applying the relevant multipliers to the amount of the change generates an initial estimate of the income impact. It is important to note that this impact analysis is static in nature, i.e. it compares a "before" state with an "after" state under the assumption that everything else remains equal, notably that fishing behavior does not change in response to regulatory changes. Clearly that assumption is only realistic in the very short term, before fishermen and processors adapt to management measures. In terms of the fleet restructuring precipitated by capacity reductions, the major response is that vessels remaining in the fleet harvest the allocations formerly harvested by the vessels exiting, up to the level of the coast-wide total. So in this sense, the income impacts give an initial indication of the order of magnitude of the groundfish related income that will be redistributed along the coast.

The dynamics of fleet restructuring over time are not modeled in this project. How individuals or businesses, communities and the whole coast will adjust to profound structural changes is as important to the sustainable transition of the fishery as it is elusive. Typically, these responses are approximated by postulating some likely responses and estimating their impacts. This method is routinely used in council processes, drawing upon the expertise of fishing industry representatives and aided by regional input-output models such as the FEAM, which in turn are widely used in regulatory analyses for natural resources management to gauge the immediate impact of a proposed policy measure. A longer-term research need is to improve our dynamic understanding of the fishery and how it relates to ecological, social and economic systems. One plausible direction might be to develop dynamic models for considering alternatives about the fleet size under a set of constraints such as maximizing income, minimizing habitat effects, or increasing ecological and social resilience (Lawson and Gooday 2001; Walker, Carpenter et al. 2002).

3.2.2. Community analysis

There is, of course, more to fishing communities than landings, revenues, and the associated income. The culture of fishing, for example, is clearly important to the social cohesion of coastal communities (The H. John Heinz III Center for Science Economics and the Environment 2000). Therefore a central aspect of the GFR project was the collection and integration of other socioeconomic data into the analysis. The ultimate goal is to develop a measure of community health and resilience in the face of changes in the fishery, potentially in a joint ecological-socioeconomic model we are exploring with academic partners. For the purposes of this project, however, we focused on identifying and integrating a variety of community-relevant data into the GFR framework. We approach this both through harvesting the fishery-dependent data in ways that we think are relevant for understanding how communities will make the transition, and through a range of other data from sources like the United States Census Bureau.

In terms of the fishery-dependent data, we are using length as an indicator of vessel size and, together with gear types used, of fleet diversity-the preservation of which is important to many people and organizations on the coast. Thus we consider the "before" and "after" make-up of the groundfish fleet in each port as well as coast-wide. Clearly, different reduction scenarios will have very different effects on the composition of the fleet, and this may be an important consideration in the design and implementation of fleet reduction measures. The GFR framework makes visible these effects on fleet diversity of different scenarios, and allows communities and sectors of the fleet to evaluate how they will likely be affected.

Ideally, we would consider the fleet not in terms of its landings and ex vessel revenues, but in terms of the income net of operating costs and other outlays to gain a measure of the profitability of the fleet or individual vessels. The FEAM estimates are based on fairly old cost-earnings information, which has furthermore not been replicated systematically along the entire coast. A recent cost-earnings survey of the groundfish fleet was completed by the PSMFC (2001), but it suffers from low return rates. This lack of up-to-date information on costs and earnings is one of the socioeconomic data shortfalls diagnosed by the PFMC in its West Coast Economic Data Plan (2000). Over the course of the GFR project, we collected a small, non-representative sample of cost, earnings, and operational information on different kinds of fishing vessels to gain a better understanding of the fishery, which we present in the community case studies in section 3.4 below. This remains an area for further research.

There are a number of efforts under way to assemble more comprehensive community information for the coast, notably the communities documents under preparation at the PFMC and PSMFC (PFMC 1999; Langdon-Pollock 2002), as well as the more comprehensive analysis made necessary by the EIS for the 2003 harvest measures (PFMC 2002). The GFR project database contains a literature section that catalogues these and other publications (for example, Gilden 1999; Radtke and Davis 2000; Gilden and Conway 2002; Oregon Coastal Zone Management Association 2002), which we cross-referenced with the ports and regions to which they pertain. Using a port ID, the GFR database can then be queried to generate all the literature linked to a particular port. We have also mined some of this information directly, adding it to the description of ports. Since this is again linked through data categories, it is possible to relate published information about ports with new information we have collected, and with the rest of the GFR database. This makes it convenient and, as we hope, useful to communities and others on the coast to tap into the collective research that has been conducted along the coast without having to undertake the literature review anew each time.

We also augmented the GFR framework with census and regional economic statistics available from federal agencies. These provide information on the demographic make-up of communities, and contain metrics of important community aspects such as educational attainment, county income, home ownership and so on. While it is at this stage not possible to link this information directly to the fishing fleet, it does allow comparisons, e.g. of the groundfish-related income in a port or group of ports to the overall income in the county where they are located. Similarly, while changes in census statistics cannot be linked to changes in the fishery, comparing data on, e.g. poverty, across different ports provides important context for considering fishery management measures. For example, reducing the fleet in a port with a higher rate of poverty or unemployment may have disproportionately larger effects than reducing the fleet in a well-diversified community. The GFR project barely begins to consider all the possible socioeconomic factors, but does combine and present them in one integrated framework that we hope will be of use for future analyses.

Ultimately the goal is to develop measures of community health and adaptability to change, such as an index of community resilience outlined in the PSMFC's community analysis (Langdon-Pollock 2002). Measurable aspects of location, demographics and economy such as commercial and marine infrastructure, distance from major cities or from other ports, number and diversity of local businesses could conceivably be constructed into one or more indices, appropriate levels of which may suggest communities more or less resilient to change. This remains an area for further research, and the community analysis presented here remains largely descriptive.

3.3 Summary

We now turn to the presentation of the results from the four numerical fleet reduction scenarios. To recapitulate, the four scenarios were:

1. Reducing all excess capacity-given the estimates of how many vessels are needed to harvest the 2000 harvest targets, we consider what the fishery would look like if only the highest producing vessels up to the level needed were harvesting;
2. Reducing capacity by 50% in each sector-this is the PFMC priority articulated in the Strategic Plan. Since there was no particular mechanism identified, we randomly selected half of the vessels in each sector;
3. Reducing capacity by 50% in each sector while preserving fleet diversity-this takes into consideration the Strategic Plan goal to preserve fleet diversity, which we interpret here as preserving the proportions of different vessel lengths present in each fleet sector in the base year, 2000; and
4. Reducing capacity in each sector while preserving economic viability-defined by the following minimum groundfish-related ex vessel revenue levels: LE trawl > $50,000; LE non-trawl/non-sable > $10,000; LE non-trawl/sable > $20,000; and OA > $5,000. In other words, for a vessel to remain in, e.g. the LE trawl sector, it had to have recorded at least $50,000 groundfish ex vessel revenues in the base year 2000.

The results of the four numeric reduction scenarios are summarized in Table 2 below. We focus on two central aspects of fleet reductions: 1) the landings, ex vessel revenues and associated income that are redistributed from the vessels exiting the fishery to the remainder of the fleet, and 2) the effects on overall size and composition of the fleet. Obviously there are many other issues that can be explored with the GFR framework, which we reserve for future research and presentation in order to keep this report to a manageable size. In particular, we only compare the coast-wide results of the scenarios. It is possible to explore the effects down to the level of individual ports with the GFR framework in Appendix C.

It is apparent that even at the coast-wide scale, different reduction schemes have substantially different effects on the fleet. There are three notable results. Firstly, the effects of removing all excess capacity and removing 50% of capacity are remarkably similar. Recall that scenario 1 removes the entire excess capacity, and only the numbers of vessels per fleet sector needed to harvest the 2000 targets remain in the fleet. The overall effect is comparable to that of a 50% capacity reduction, in terms of the initial reductions landings and revenues and the amount of income effectively redistributed from the exiting vessels to those remaining. Indeed, since scenario 1 selected for the highest producers, this occurs at a smaller initial decline in ex vessel revenues than in the random selection process of scenario 2. To the extent that income impacts can be thought of as the "cost" of capacity reduction, a coast-wide reduction of fleet capacity can thus be achieved for between $70 and 75 million. Coast-wide, the effect on fleet composition is most pronounced when removing all excess capacity to the low level of only 50 distinct open access vessels. Not surprisingly, the share of the smallest vessels, i.e. those less than 35 feet in length (VS1) drops.

Secondly, selecting for a diverse remainder of the fleet imposes significantly lower costs (in terms of the income redistributed) on the coast. In other words, reducing fleet capacity by 50% in each vessel size class in each sector achieves the same reduction of vessels, but at a smaller redistributive effect. Also, consider the meaning of the multiplier: each pound landed has an income "footprint". The fleet remaining after scenario 3 has a larger income footprint than the other scenarios. In other words, each pound caught generates more income than the same pound caught in a differently configured fleet. The total amount of income redistributed from the vessels exiting to those remaining is around $50 million. Since the number and sizes of vessels remaining in the fleet have a different geographic distribution than in scenarios 1 and 2, the effects of this scenario are also distributed differently. In comparison to the random reduction of 50% in each fleet sector, the overall fleet composition remains the same, but with more vessel instances (1464 versus 1212) and thus with more associated income and jobs.

Finally, scenario 4 suggests that economic viability may be a useful consideration in designing capacity reduction measures. Recall that this scenario is based on some explicit and not entirely realistic assumptions about levels of ex vessel revenues derived from groundfish needed to "make a living". Since these economic constraints can be translated into vessels to select for removal from the fleet, there are clear effects on the size, composition and distribution of the remaining fleet. It would be interesting to examine the economic viability criterion in conjunction with numeric reduction targets. Interestingly, the particular set of economic viability criteria we chose had the effect of increasing the share of vessels in the 60–80-foot range (VS 3). This further illustrates the fleet composition effects of fleet reductions, which can be explicitly considered in the GFR framework.

TABLE 2: Summary of Fleet Reduction Scenarios
		initial value of fleet remaining after capacity reduction
	base (2000)	scenario 1 (with 50 OA remaining)	scenario 1 (with 100 OA remaining)	scenario 2 (random)	scenario 3 (diversity)	scenario 4 (viability)
coastwide landings (pounds)	272,390,187	123,131,582	123,772,655	132,480,150	153,934,597	181,145,380
change from base		–55%	–55%	–51%	–43%	–33%

The local implications of these scenarios differ along the coast. Figure 5 shows the amount of income generated by fishing in 2000 and in each of the four reduction scenarios, aggregated by port group from South to North. To the right of the base column for each port group are the income impacts of each scenario, i.e. the amount of harvester and processor income generated by the vessels remaining after the reduction. As is evident from the graph, some scenarios (notably the economic viability one) result in some ports maintaining income levels at pre-reduction levels, e.g. the Monterey Bay area or ports in the Eureka area. Also, the aggregate income effects suggest that economic viability concerns may be more important in some ports than others. For example, Eureka, Coos Bay and Newport areas fare better in terms of income associated from landings by the remainder of the fleet under the economic viability scenario than the fleet diversity one, whereas there is little difference for Astoria or the Northern Puget Sound area. Recall, however, that the economic viability criteria were set rather lower than realistic and are thus likely to retain too many vessels in the fleet.

* Note: Revenue, landings and income estimates are based on the unique vessels identified in the capacity calculation. Each vessel, however, has multiple instances as a function of making landings in multiple ports and using multiple gears over the course of a year. The numbers reported in this table report these per port "vessel-gear instances". So in the base year, there were, for example, 642 gear-port combinations of the 244 vessels in the LE trawl sector.

It is also important to notice that our analysis assumes that the total possible harvest remains unchanged, i.e. that there is no net reduction in the harvest allocations in conjunction with a fleet reduction. Specifically, for our 2000 baseline this means that the remainder of the fleet is catching the same total poundage as the fleet prior to the reductions. In light of the increasingly more stringent measures made necessary by rebuilding plans and other considerations, there may be a concomitant reduction of the overall harvest. In that case, there would be income impacts in addition to the redistribution effect between exiting and remaining vessels we consider here.

FIGURE 5: Summary of Scenario Income Impacts Along the Coast

Figure 5 is properly interpreted as the level of income generated in each port group immediately after each reduction scenario is implemented, by the vessels that were making landings in those ports before. The dynamic response of the fishery to each scenario cannot be inferred. In particular, it is not clear how the landings formerly accruing to the vessels exiting the fishery would be allocated among the remainder of the fleet. This offsetting effect on port-reduction income levels could be approximated by making some assumptions about the remainder of the fleet. For example, one could reasonably assume that vessels remaining in the fleet would harvest the now "surplus" allocation according to the same proportions as they did before. Alternatively, one could impose some new allocation rules such as gear requirement on the remainder of the fleet.

It is also important to note that our analysis assumes that processors and prices would remain at 2000 levels. Both the processing sector's internal dynamics and its likely response to a fleet rationalization make it likely, however, that there would be changes that may offset some of the income effects observed in our scenarios.

The fleet composition effects summarized for the entire coast in Table 3 are considerably more pronounced at the local level, where some scenarios eliminate entire vessel size and gear classes in some ports. Results for individual ports are listed in Appendix C.

 

3.4 Effects on Communities

In order to illustrate the effects of fleet reductions on different communities, we discuss in this section the outcome of the four numeric scenarios on Newport and Port Orford. In subsequent chapters, we will also frequently refer to these communities to illustrate additional results and applications of the GFR framework. Both are fishing communities located in Oregon, and illustrate some of the differential effects of fleet restructuring on different kinds of communities. Although both have prominent fishing fleets, neither relies on fishing for a significant share of income generated-at least not at the county level considered here. Newport is a larger city with a diversified economic base. Its fishing fleet includes all kinds of gear-types and vessel sizes, targets groundfish and the full complement of other commercially significant species on the West Coast. Furthermore, the fleet operates both in Oregon waters and as far away as Southern California, and a significant number of boats are part of the distant water fleet that operates seasonally in Alaska. By contrast, Port Orford is a small community with greater relative dependence on fishing. Its fleet is comparatively homogenous and consists of a moderate number of medium-sized vessels that mostly target rockfish and operate in day trips from port.

Not surprisingly, the different reduction scenarios we analyzed in the GFR project have markedly different effects on Newport and Port Orford. This illustrates the case for considering the effects of fleet reductions from different communities' perspectives, and for taking regional and community differences into account in the design of any fleet restructuring. In the following two sections, we discuss both the numerical results for the two ports, and give a synopsis of other statistics and qualitative information contained in the GFR database. While the scenario summaries for the remainder of West Coast ports are listed in Appendix C, similar narrative profiles for communities can be requested from the principal investigator.

Below we discuss some, but by no means all, of the fisheries and other features of both communities. In general, the data coverage is too thin to infer causal relationships between changes in the fishery and any of the social and economic characteristics. Considerably more research would be needed to address such linkages.

 

3.4.1. Newport

Newport is located in Lincoln County, and is one of the biggest fishing ports on the West Coast. It houses a large, diverse fleet comprising trawlers, shrimpers, salmon trollers and longliners. The fleet, especially larger vessels, operates both off the coast and in distant waters (Alaska). The distant water fleet is of considerable importance to the port, accounting for 10–15% of vessels and concomitant shares of moorage revenues, marine supplier business, and boat work (interview 45). Groundfish accounted for 9% of all fish landed in 2000 (Oregon Coastal Zone Management Association 2002, p. IV–9), or approximately 85 million pounds that generated $24 million in income for local harvesters and processors. Groundfish-related income accounted for almost 50% of total fishery income generated in the Newport area, and most of this was due to whiting (Stoebig and Carter 2001, p. 10). Total fishery income in Newport, in turn, was estimated at $45 million for the 2000-2001 fishing season (PFMC 2003, table 3.3-48, p. 3–160).

There is a significant amount of fishing-related infrastructure and businesses in Newport, including net makers, marine suppliers, boat yards, and cold storage. Many of these businesses have experienced considerable declines in revenues in recent years, or closed entirely (interviews 117, 126). A local net maker, for example, has experienced a drop decline in business and noted that 20% of clients are behind in their payments (interview 23). As of summer 2002, there were two full-time processors in town, with several other fish buyers operating seasonally (or focusing on other species, notably crab). A recent report by the OZCMA concluded that Newport appears well poised to weather the transition of the groundfish fishery (Oregon Coastal Zone Management Association 2002, p. IV–10), the recent experience of harvesters and processors notwithstanding.

According to census data, the population of Lincoln County increased from 38,889 to 44,479 between 1990 and 2000. During this time, the poverty rate has remained at around 14%, but at least one informant observed that the fishery as at the forefront of a local economic decline that is beginning to affect school services (interview 117). An often-cited study by Oregon Sea Grant found that 23 out of 81 groundfish vessels in Newport were at high risk of failure (Stoebig and Carter 2001, p.12), mostly due to limited opportunities for diversifying into other fisheries (as assessed by the number and types of permits associated with Oregon vessels).

In Newport, one common type of vessels used in the groundfish fishery are trawlers in the 60–80-foot range (see Figure 6). In addition to capital costs, operating costs are a key factor in determining the viability of a particular fishing business. Put simply, the amount of fish a vessel is allowed to land each year-as extrapolated from the trip limits set by the council and the average number of trips a vessel is likely to make-translates into revenues that at the least have to cover the costs of fishing before generating income for fishing families. Not surprisingly, these costs can be quite large for larger boats. For example, a 70+-foot trawler might require $25-50,000 in annual maintenance-repairs to the hull and other structures, gear repairs or replacement, engine and electronic maintenance. In addition, moorage, taxes, insurance and licenses may cost another $30,000 per year, and fuel, ice and provisions each cost $18–25,000/year. In recent years, due to decreasing trip and cumulative limits trawlers have spent considerably fewer days at sea (approximately 120 compared to 165 in 1990), resulting in fewer days in which to catch enough to cover these costs and generate income for crew and skipper. A common coping strategy is to defer maintenance, and-as in the case of the $45,000 trawl nets that used to be replaced every 2–3 year-delay gear replacement (interview 23). Over the same time period, many trawlers have seen the value of their boats and permits decline by 50–80% (interview 11).

 

3.4.2. Port Orford

Port Orford is located in Curry County, on the Southern coast of Oregon. It is unique among ports on the Oregon coast in that it is not located on a river channel, but rather on an open bay. Vessels homeported there are limited in size, since they have to be hoisted in out of the water by two cranes located on the pier, the bigger of which has a capacity of 50,000 pounds (interview 121). Consequently, the majority of vessels are 36 feet or smaller-34 (77%) out of a 44 total making landings there in our base year, 2000. Groundfish accounted for 40% of total landings in 2000 (Oregon Coastal Zone Management Association 2002, p. IV-18), or approximately 550,000 pounds; other species include (roughly in order of importance) urchin, crab, tuna, and salmon. These groundfish landings generated approximately $670,000 in harvester and processor incomes-illustrating the higher per-pound value of the groundfish species landed here than in Newport. Most of the groundfish landed are sablefish and live rockfish. According to one interviewee, Port Orford accounted for 50% of the state urchin and 80% of live rockfish harvest (interview 41). There were three fish buyers in Port Orford, all of whom transport groundfish to Charleston for processing (interview 121).

There is little fishing related infrastructure in Port Orford. Apart from the pier and the two cranes, there is cold storage and ice to be had at one of the fish plants, and the port sells fuel (interview 41). Vessels tend to go to Brookings or Gold Beach for repairs. Other marine businesses include a tackle store, and there is interest from a dive operator to open a shop at the port (interview 121). The same nearshore reef complex that makes Port Orford a center for the live fish fishery (Oregon Coastal Zone Management Association 2002, p. IV-19), also attracts recreational fishermen and divers (interview 121). Prospects for fishing related tourism may improve with the passing of an ordinance that would allow overnight camping (interview 121).

Between 1990 and 2000, the population of Curry County increased from 19,327 to 21,137, and the poverty level stayed at 12%. Estimates of fishery-related employment vary considerable. According to a port official, there are approximately 325 fishing related jobs in Port Orford alone, or 30% of the population in the voting district (interview 121). By contrast, a recent PFMC document estimates the number of fishery-related jobs in the entire Brookings port group (which includes the larger ports of Brookings, as well as Gold Beach) as 400, with 171 of these dedicated to groundfish. Both the local and the PFMC estimate are considerably higher than comparable statistics from the Regional Economic Information System (Bureau of Economic Analysis (BEA) 2002), and illustrate the relative importance of the fishing for the economic base in Port Orford. Discrepancies such as the employment figures for Port Orford underscore the need for better, locally validated information on key socioeconomic parameters.

The smaller, fixed gear vessels characteristic Port Orford are cheaper to maintain and tend to be well diversified-in addition to groundfish, many vessels also target crab, salmon and/or tuna (see Figure 7). For a 32' fixed gear boat, annual maintenance costs may run to almost $30,000. Moorage, taxes, insurance, and license fees may run to an additional $20,000. Fuel costs are approximately $9,000/year, and ice and bait may be close to $7,000 for a fishing season that might be as short as 90 days at sea. Most of those, due to the relatively small range of the Port Orford fleet, are day trips, and highly dependent on weather and current conditions. Recent declines of trip limits, coupled with the bad 2002 crab season, have led to declines of up to 40% in boat income (interview 40).

 

3.4.3. Comparing baseline information and scenario effects

The four reduction scenarios have somewhat different effects on Newport and Port Orford. This is not least a function of the considerable size difference of the groundfish fishery in both communities-Newport's landings are two orders of magnitude greater than landings made in Port Orford, and in absolute terms, the impacts from the various reduction scenarios are larger, too. Recall the four ways to reduce fleet capacity that we are considering so far:

1. removing all vessels in excess of those needed to harvest the 2000 allowable catch (with 50 and 100 OA vessels remaining, respectively);
2. removing 50% at random in each sector;
3. removing 50% in each sector while preserving fleet diversity, i.e. removing 50% of each size class; and
4. selecting vessels to remain in the fleet that meet minimum ex vessel revenue levels in each sector.

The results are summarized in Table 3 below, and reflect the different natures of the groundfish fishery in the two communities.

TABLE 3: Scenario Summaries for Newport and Port Orford
		initial value of fleet remaining after capacity reduction
	base (2000)	scenario 1 (with 50 OA remaining)	scenario 1 (with 100 OA remaining)	scenario 2 (random)	scenario 3 (diversity)	scenario 4 (viability)
coastwide landings (pounds)	272,390,187	123,131,582	123,772,655	132,480,150	153,934,597	181,145,380
change from base		–55%	–55%	–51%	–43%	–33%
coastwide revenues	$62,141,810	$36,1127,210	$37,274,029	$30,509,611	$43,644,904	$47,744,959
change from base		–42%	–40%	–51%	–30%	–23%
coastwide income impacts income redistributed	$138,961,151	$63,9832,802	$65,180,144	$68,244,427	$90,997,105	$101,667,573
(change from base)	$0	$75,128,349	$73,781,007	$70,716,723	$47,964,046	$37,293,578
income change	0%	–54%	–53%	–51%	–35%	–27%
implied multiplier ($/pound)	0.51	0.52	0.53	0.52	0.59	0.56
number of vessels*	2,427	986	1,011	1,212	1,464	1,499
LE trawl	642	344	344	311	378	553
LE non-trawl, non-sablefish	422	143	143	210	255	152
LE sablefish exclusive	25	25	25	11	17	21
Open Access	1,339	174	499	680	814	773
fleet diversity (%) of total fleet
VS1	39%	26%	37%	40%	39%	38%
VS2	37%	29%	27%	37%	36%	32%
VS3	18%	35%	28%	17%	17%	23%
VS4	5%	9%	7%	3%	6%	6%
VS5	0%	0%	0%	0%	0%	0%
VS6	1%	1%	1%	3%	2%	1%

It is interesting to note that the scenario effects vary significantly depending on whether landings, revenues, or income are considered. For example, in Newport both variations of scenario 1 (the removal of all excess capacity) and the diversity scenario lead to 50% reductions in landings. Yet, despite impacting revenues more (41% as opposed to 31%), the diversity scenario results in higher post-reduction incomes to harvesters and processors. This is likely a function of more vessels targeting higher-value species remaining in the fleet in scenario 3. Designing fleet reductions to maintain diversity can therefore mitigate the income impacts. Another important consideration is the question of fleet viability. Even with our simplistic assumptions, treating viability as a fixed minimum level of ex vessel revenues, such considerations may well help identify a strategy that maintains-in this case the highest-pre-reduction levels of income in the community.

As in Newport, the most severe effects in Port Orford take place under the full-removal scenario, which may be an indication of things to come if the restructuring continues by attrition. The fleet does surprisingly well under the random scenario, in which 50% of each fleet sector are removed at random. This may be an artifact of having picked high-value vessels for remaining in the fleet. The next best scenario, in terms of having the least adverse effects on the community, is the diversity scenario, in which the fleet composition in the port is maintained to reflect pre-reduction levels of diversity.

Fleet restructuring is a coast-wide undertaking, and the decision-making process will likely entail balancing the interests of many different communities and local fleets. It is therefore instructive to compare the relative impacts of the reduction scenarios on landings, revenues and income in Newport and Port Orford. What is good for one may not be good for the other, and expectations of relative community wealth post-reduction may be grounds for contention in the fleet restructuring process.

Figure 8 compares relative impacts for each of the three "community wealth" parameters-landings, revenues, and income-for Newport and Port Orford. The x-axis depicts the percentage change from the baseline figures, as summarized in Table 3 above. The closer the "spike" is to the outside of the graph, the smaller the change from the baseline, i.e. the lesser the adverse impacts, and the "better" the scenario.

As should be apparent from these graphs, whether fishery participants from Newport and Port Orford can agree on a fleet restructuring scheme that benefits both of them, or at least mitigates impacts on both communities somewhat equitable, will depend on which of the three parameters is considered. For example, in terms of ex vessel revenues, the scenarios that are good for Port Orford (2 and 3) are not as good for Newport, which would tend to do better under the full-excess-capacity removal (scenario 1). If, however, landings are considered, the two ports are much more closely aligned, and scenarios 1 and 4 would appear to be likely candidates for mutual ground. The match is closed in terms of income, where scenario 1 is equally bad for both ports-while the scenario that is best for Port Orford (2) is one of the worst for Newport. If all of the scenarios were to be considered, e.g. in the context of an assessment of different policy alternatives for realizing fleet reductions on the West Coast, then something like the diversity scenario may be a compromise between what is best for Newport, in terms of income, (4) and for Port Orford (2).

FIGURE 8: Comparative Effects in Newport and Port Orford

 

It is important to note that the policy discussions around fleet restructuring have not progressed to the point of considering different alternatives. Instead, proposals such as the trawl buyback target one fishery sector in isolation. The framework developed here could be used to compare the effects of such a buyback on different parts of the coast, and to estimate the effects on various communities. To the extent that there are multiple design options for the buyback, which at least in its initial form focuses on an auction design that selects for viability (Leipzig 2001), parameters such as fleet diversity could be factored into any analysis.

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