BULLETIN OF MARINE SCIENCE, 70(2): 749–761, 2002

HARVEST CONTROL IN OPEN-ACCESS SPORT : HOT ROD OR ASLEEP AT THE REEL?

Sean P. Cox, T. Doug Beard and Carl Walters

ABSTRACT As sport- pressures increase in coastal marine waters, management agencies are expected to lose direct control over fishing effort, total harvest, and -based information for stock assessment. Harvest control will be difficult because most sport fisheries remain open to unlimited public use without direct license or effort limitation. Without effort control, management tactics such as bag limits aimed at controlling total harvest typically fail because they regulate individual anglers. We develop a simple model of recreational fishery dynamics to show that current harvest-control methods should not be expected to control or reduce exploitation rates in open-access sport fisheries. The model predictions are (1) linear effort response to changes in fish abundance, (2) fish abundance limit below which effort is not attracted, and (3) rapidly increasing exploita- tion at low effort. Also, exploitation is expected to be insensitive to effort over a rela- tively wide range. Empirical data show that harvest restrictions tend to reduce participa- tion by consumptive anglers, and we incorporate this effect into the effort-response model. We conclude that typical regulations such as bag limits and seasonal closures are not drastic enough to affect total exploitation. Although bag limits are usually ineffective for their intended purpose (direct harvest reduction), they probably act as an indirect means of effort control, but only temporarily. We suggest that managers of sport fisheries should consider direct license limitation or harvest permits where control of exploitation is needed.

Over the past three decades, has become an increasingly important sector of coastal marine fisheries because of increases in wealth, leisure time, and tour- ism (National Research Council, 1998). Total fishing effort in U.S. mid-Atlantic coastal waters has more than doubled since 1981, and total recreational harvest exceeds commer- cial catches for many of the most popular species (ASMFC, 1998; NMFS, 1998b), in- cluding bluefish, dolphin, and striped bass (Fig. 1). Such increases in fishing effort and harvest are often viewed as examples of successful management because of increases in total economic benefits derived from sport fishing activity, but recent evidence shows that many coastal recreational species are overfished by recreational fishing fleets (ASMFC, 1998; Love et al., 1998; NMFS, 1999). Further development of inshore recreational fish- eries is likely to cause even more damage unless we begin to develop new methods for controlling total exploitation by an expanding population of recreational anglers. In the present paper, we show two ways in which typical harvest-control measures are likely to fail: first, attempts at reducing per-angler harvest impacts by means of bag and gear restrictions are not severe enough to reduce exploitation substantially, and second, the open- access nature of sport fisheries will ensure that fish populations are exploited to the point where anglers are satisfied that no truly good opportunities remain. Both of these cases may or may not lead to severe overexploitation, but they do show quite clearly that our current methods of exploitation control are not adequate to ensure quality angling and sus- tainable exploitation of fish stocks in the future. On the basis of our results, we conclude that regulation of individual anglers cannot protect populations from and that effort and total-harvest-limitation programs should be considered as important in recreational fish- eries as they are in the commercial fisheries and wildlife management.

749 750 BULLETIN OF MARINE SCIENCE, VOL. 70, NO. 2, 2002

Figure 1. Total recreational angler trips (top, open circles) and harvest (top, closed circles) taken between 1981 and 1998 in U.S. coastal inland waters. Bottom panel shows distribution of total harvest of top 10 recreational species between recreational and commercial fisheries. Data source: National Marine Fisheries Service, Marine Recreational Fisheries Survey Statistics website (NMFS, 1998a,b).

A MODEL OF FISHING MORTALITY IN SPORT FISHERIES

Harvest by sport can be viewed as being less efficient than commercial meth- ods because angler catches are taken from a limited pool of vulnerable/reactive fish (Fig. 2; Cox, 2000). Exchange of fish between feeding locations, feeding rhythms, and reactiv- ity to fishing baits can be represented by the simple rate equation

dV dt=- v12() N V-- v V qeV where V represents the density of vulnerable/reactive fish, N is total fish density, e is the fishing effort, q is a catchability coefficient, and v1,v2 are exchange rates between vulner- ability states (per year). Fish exchanging between vulnerability states and removals by COX ET AL.: HARVEST CONTROL IN SPORT FISHERIES 751

Figure 2. Schematic representation of harvest by sport anglers. Total stock size N is divided into an available/reactive component V and an unavailable/unreactive component N - V. Catch by anglers involves removal from a small limited stock of reactive fish that is typically smaller than measure in sampling.

fishing imply a strong inverse relationship between the instantaneous equilibrium density of available fish V and fishing effort e of the form

vN1 V = Eq. 1 vvqe12++

This model implies that increasing effort will suppress instantaneous density of reac- tive/vulnerable fish even if the fishery has no short-term impact on the total stock size. If fish are only removed from the vulnerable pool, then the total fishing mortality rate taken over a season will behave as

qvE F = Eq. 2 vvqE12++

where E is total season fishing effort. The important features of this model are that: (1) fishing mortality will increase rapidly for the first few effort units because of low compe- tition among anglers for a limited stock of available fish and (2) fishing mortality will tend toward an asymptotic value that may be less than unity (Fig. 3). Classical models that relate fishing mortality to fishing effort assume that all fish are available and reactive to fishing gear. Therefore, instantaneous fishing mortality is usually calculated as F = qE. The differences in fishing mortality predictions between these two models have impor- tant implications for setting target fishing-effort levels. For example, suppose we wish to determine the optimum levels of effort (i.e., effort required to achieve some target exploi- 752 BULLETIN OF MARINE SCIENCE, VOL. 70, NO. 2, 2002

Figure 3. Relationships between fishing effort and exploitation in sport fisheries. Predictions from the best-fit limited-vulnerability model (Eq. 2; LV) are shown as solid lines and compared to the best-fit prediction of U = 1 - exp(-qE) (FV; dashed line). British Columbia salmon troll data are from (Smith et al., 1999), and rainbow-trout exploitation rates were determined from mark-recapture experiments (Cox, 2000). tation rate Uopt) for the rainbow trout (Uopt = 0.24) and salmon (Uopt = 0.45) troll data shown in Fig. 3. Using Eq. 2 results in optimum effort estimates that are 40% and 23% lower than the traditional model for rainbow trout and salmon, respectively (Fig. 4). There- fore, assessments that use only the classical model may seriously underestimate fishing- effort impacts at low effort. Although this may seem to be a trivial effect of model choice, most exploitation studies are done over too small a range in effort levels and therefore limit evidence for alternative models. However, there is evidence that nonlinear relation- ships between effort and fishing mortality may be more common (Smith et al., 1999).

DYNAMICS OF SPORT FISHING EFFORT

One of the most difficult and often ignored problems in recreational fisheries manage- ment is uncontrollable fishing effort. Effort-dynamics theory in recreational fisheries has received surprisingly little development (Hilborn, 1985; Carpenter et al., 1994), even though most biologists openly acknowledge that anglers are strongly responsive to new COX ET AL.: HARVEST CONTROL IN SPORT FISHERIES 753

Figure 4. Bayes posterior probabilities of optimum fishing effort for the limited-vulnerability model (Eq. 2; LV) and the traditional model, which assumes full vulnerability (FV).

fishing opportunities. A simple way to model such responses is to assume that anglers will distribute themselves among fishing opportunities (bays, reefs, estuaries) so that no particular fishing location stands out as having above average quality or catch rate c (Hilborn, 1985; Gillis et al., 1993; Walters and Bonfil, 1999). That is, we expect anglers to move about so that all locations with similar access display the same instantaneous

catch rate co (an ideal free distribution prediction, IFD). Substituting this IFD prediction

into Eq. 1 (where co = qV) and solving for instantaneous effort e gives

v112vv+ e =-N . co q

Integrating this equation over a fishing season of length T results in effort’s behaving as

NN0 - vT E = ()• 1- e- 1 Eq. 3 co ()

where N is the fish density at the beginning of the season and N c (1 + v /v )/q is the 0 • = o 2 1 minimum fish density below which effort will no longer be attracted. This model predicts that fishing effort will vary linearly with changes in fish abundance with a slope that is inversely proportional to the target catch rate co (Fig. 5). The observed linear effort re- sponse for lakes in British Columbia implies that anglers are able to detect changes in abundance and reduce fish stocks to the level at which all fisheries exhibit the same average angling quality. From a management perspective, the effort model suggests that any regulation aimed at limiting harvest by individual anglers will be ineffective at con- total harvest because total effort is free to increase without limit. One might ar- 754 BULLETIN OF MARINE SCIENCE, VOL. 70, NO. 2, 2002

Figure 5. Effort responses to stocking rates in British Columbia rainbow-trout lakes (n = 68) from three management regions. Top panel shows a strong effort response on lakes that are easily accessible from Vancouver, B.C., which is the source of most fishing effort. The lower panel shows a weaker effort response in a region that requires a significantly longer mean travel time to lakes. gue, however, that, if total season harvest H = hE, where h is harvest per angler day and E is total angler days, then one can control H by limiting h or E. Indeed, this is the main logical argument used in developing bag limits in the first place. In today’s sport fisher- ies, however, average angler catch per day (h) rarely exceeds most bag limits. For ex- ample, 15 lake-yrs of creel surveys that we conducted on trout lakes in British Columbia revealed not a single case where the mean catch per angler-day exceeded the bag limit (Cox, 2000). The situation is similar to Wisconsin walleye lakes (T.D.B., unpublished data), and sport anglers in Georgia Strait, B.C., have maintained consistently high exploi- tation rates of Pacific salmon despite a suite of changes in bag, size, and season limits over the past two decades (Fig. 6). In fact, most bag limits would have to be reduced to less than one fish per day to reduce per-angler harvest. Yet, even if h could be effectively controlled, E remains unbounded, so the only theoretical bounds on total exploitation are those imposed by fish behavior effects as described in Eq. 2. We suggest that, rather than serving as a direct means of harvest control, bag limits more often serve as an indirect control by influencing effort responses as described below. COX ET AL.: HARVEST CONTROL IN SPORT FISHERIES 755

Figure 6. Exploitation of Pacific salmon in Georgia Strait, B.C., by sport anglers 1980–1991.

EFFORT RESPONSES TO MANAGEMENT ACTIONS

Clark (1985) calls for a ‘predictive’ theory of in which a full range of fish population and fishing effort dynamics could be predicted in response to management actions. In this section, we show how the above model structure predicts recreational fishery dynamics in response to management changes in season length and bag limits. Seasonal closures are most often used in sport fisheries as a means of protecting fish during spawning periods, but they are also used for harvest control (Kohler and Hubert, 1993). A simple in-season model of angler effort responses using Eq. 3 shows that there is virtually no practical limit to season length for reducing total exploitation (Fig. 7). As- suming that a full fishing season runs from 1 May to 31 October, our simulations suggest that a hypothetical goal of 30% reduction in exploitation would require delaying the fishery opening from early May to early October. No management agency is likely to be willing to endure the public outcry that would result from such an action. Failure of acceptably shorter fishing seasons (up to four weeks) in the simulation is due mainly to the form of relationship between effort and exploitation. Recall that this function in- creases sharply as the first few effort units are added and then remains rather constant despite further increases in effort. Therefore, most of the damage to the stock is done very soon after the opening, regardless of when that opening occurs. Also recall that our effort model assumes open-access adjustment of effort so as to maintain catch rates near the target co. This assumption causes very high effort early in the season followed by a gradual decline, which ensures that most exploitation will occur soon after opening. In applying our model to sport fisheries in British Columbia, the Colorado River, and Wisconsin, we have noticed that restrictive bag limits tend to reduce the slope of angler effort responses. Numerous studies in freshwater systems show that bag limits have little 756 BULLETIN OF MARINE SCIENCE, VOL. 70, NO. 2, 2002

Figure 7. Simulated changes in total season exploitation rate with later season opening dates. Markers indicate percentage change in exploitation if season is opened on the date shown. Open circles show changes where angler effort responds rapidly to changes in fish abundance, and closed circles represent a weaker effort response case. or no effect on total numbers of fish harvested (Webb and Ott, 1991; Munger and Kraai, 1997; T.D.B., unpublished data). Instead, increasingly restrictive bag limits appear to cause decreases in total angler effort (Fig. 8, top panel). We interpret this negative effect as a reduction in the attractiveness of a fishery to consumptive anglers (those anglers who seek to harvest as many fish as possible per trip). The simplest hypothesis for modeling regulation effects is to assume a linear relationship between the IFD catch rate co and regulation of the form

cBo =+ab

where a is the maximum co value possible (cmax = qN/2) and b represents a response effect (typically negative) to increasing bag limits. In other words, higher bag limits cause lower target catch rates co, which then result in a higher effort response slope (note co is in the denominator of Eq. 3). Figure 8 (bottom panel) shows the expected response of stock size, effort, and exploitation for a rather drastic bag limit change from five fish per day to two fish per day. Effort declines initially because of the co change and then increases gradually as lower exploitation causes a gradual increase in stock size. This pattern of short-term success and exploitation reduction is common in Wisconsin walleye lakes and was also observed in Lake Meredith, Texas (Munger and Kraai, 1997), but note that even this large simulated change in bag limit does not cause a substantial long-term movement toward the optimum effort and stock size. Again, this prediction is qualitatively similar to observed total effort and exploitation patterns in Wisconsin walleye lakes and Lake Meredith, as both harvest and effort returned to preregulation levels after several years. Munger and Kraai (1997) noted that had their study been ended after only 4 yrs the COX ET AL.: HARVEST CONTROL IN SPORT FISHERIES 757

Figure 8. Observed relationship between bag limit, mean fishing effort (solid line), and mean catch rate (dashed line) (top panel; n lakes = 250) used to estimate bag-limit effect on the effort response parameter co. Bottom panel shows resulting simulated effect of a bag-limit reduction from five to two fish per day on total effort, exploitation, and stock size. All values are shown relative to the optimum values (dashed line) for the population. Stock dynamics are predicted from an age-structured model and a Ricker recruitment function with typical parameter values for Wisconsin walleye. Effort model parameters are inferred from empirical data on the basis of equilibrium assumptions (Cox, 2000). 758 BULLETIN OF MARINE SCIENCE, VOL. 70, NO. 2, 2002 central conclusions would have been that bag limits were effective for reducing walleye harvest. Although many other factors might affect long-term changes in effort, the simple assumption of effort adjustment in response to changes in stock size and regulation sug- gests that bag-limit policies should be viewed with some skepticism.

DISCUSSION

Management of exploitation is an important issue to sport-fishery managers in North America mainly because of increasing demand (Mather et al., 1995), yet few published results show successful long-term exploitation control using traditional tactics (Wilde, 1997). From high-profile marine systems to small lakes, streams, and ponds, our experi- ences tend to be the same; fish population sizes and angling quality are low in easily accessible areas and higher where accessibility (i.e., travel cost, privatization, access lim- its) or extreme regulation policies (i.e., catch-and-release) reduce angler numbers (Cox, 2000). Although angling quality means different things to different people, catch rates appear to influence angler satisfaction strongly (Holland and Ditton, 1992). Regardless of how angling quality is measured, we contend that, given freedom of movement through open access, anglers will be attracted to high-quality opportunities until they no longer see any. Bag limits and seasonal closures might serve as temporary indirect effort-control measures (i.e., by excluding certain subsets of the angler population), but their long-term effectiveness is weakened substantially where total effort remains unbounded. In the marine environment, both opportunities and risks are associated with sport fish- eries. Most fishery-management plans refer in one form or another to the economic value generated by recreational fisheries (Edwards, 1990). Indeed, recreational fishing advo- cates use these arguments to support demands for higher proportions of mixed sport/ commercial fishery quotas, but the risk in transferring fishing rights from commercial to sport fisheries may be large if sport fisheries remain open to unlimited access without license limitation and reliable effort and catch reporting (National Research Council, 1998). Harvest statistics for marine fisheries remain highly uncertain because of sam- pling difficulties (National Reserach Council, 1998; Parma, this issue). In contrast to commercial fishery data collections, where relatively few boats participate and landings are reported at known locations, the estimated 195 million pounds of fish harvested by sport anglers in U.S. coastal inland waters in 1998 were spread over an estimated 60.5 million angler trips (NMFS, 1998a). In the U.S. mid-Atlantic region, over 3 million trips were made from shore, 6.5 million were on privately owned or rented fishing boats, and only 0.4 million were made on party or charter vessels subject to mandatory reporting (NMFS, 1998b). To yield reasonably precise estimates from such situations, survey data must be aggregated over broad temporal and spatial scales, so in-season harvest monitor- ing and detection of important changes in substock/spatial structure of fish populations are precluded. Further, telephone, mail, and creel-census sampling methods used to gen- erate harvest estimates are typically suspect because of inherent reporting biases and the ease with which anglers can lie or cheat on regulations (Sullivan, 1999). From this per- spective, the problems associated with detailed harvest sampling (i.e., for changes in substock/spatial structure), enforcement, and stock assessment of commercial fisheries seem only minor. Even if we could accurately measure recreational catches and enforce regulations, the potential for overexploitation undoubtedly remains as it has in open- access commercial fisheries. Rather than seeking to develop and promote access to coastal COX ET AL.: HARVEST CONTROL IN SPORT FISHERIES 759

marine fisheries further, management agencies should attempt to find more robust meth- ods for controlling harvest in the face of increasing demand. Wildlife managers have addressed overexploitation issues by implementing limited- entry draws for North American game animals, despite strong initial opposition from the hunting community. The success of such programs demonstrates the need to establish direct control over harvest in fisheries. Direct harvest-control programs for sport fisher- ies could be more flexible than those used in game or commercial-fishery management because anglers usually have the option of releasing fish. We envision three general strat- egies for recreational harvest-control programs. First, a limited-entry harvest-permit sys- tem, in which the total allowable harvest is allocated to permit holders by means of a lottery, would allow the greatest control of harvest while retaining open access to fishing opportunities provided anglers release fish for which they do not have permits. This sys- tem would have the least impact (although certainly not a negligible one) on angler par- ticipation and could be particularly attractive for multispecies fisheries. Where hook- and-release mortality is substantial, however, such a program could not guarantee that harvest goals would be met because even a small hooking mortality can generate high total fishing mortality rates if effort is large. For example, in 1998, estimated total hook- ing-mortality losses of Atlantic striped bass (Morone saxatilis) were 1.2 million fish, compared to total recreational landings of 1.4 million fish (NMFS, 1999). This level of mortality, when combined with total commercial fishery losses, has led to an overfishing declaration on striped bass (NMFS, 1999). Second, a limited-entry effort program (again using a lottery system to assign fishing rights) combined with a bag limit would be an effective harvest-control option if the relationship among total exploitation (including nonlanded losses), effort, and the bag limit were known. Given a total allowable harvest and a known maximum level of effort, bag limits would be much more effective in an effort-managed fishery because the uncer- tainty associated with effort responses would be reduced. However, effort-limitation poli- cies would certainly involve great political risk by limiting anglers’ rights to fishing op- portunities. Further, the optimum level of effort may change over time because of changes in fishing technology or spatial distributions of fish (Martell and Walters, this issue). The third option, which combines effort limitation and harvest-permit systems, would control for hook-and-release mortality through the effort limit and possible changes in catchability through limits on the total number of fish harvested. Such a system would represent the most drastic form of access control but would probably be the only way to gain substantial control of total landing and nonlanding losses in recreational fisheries. In the present paper, we have outlined some potential mechanisms by which our cur- rent methods of exploitation control fail in sport fisheries. First, we typically underesti- mate the small amount of effort that is required to cause relatively high exploitation. The result may be overly optimistic expectations for the effectiveness of minor changes in bag or season limits. Second, we have showed that, under open-access conditions, an- glers adjust fishing effort in response to changing levels of fish abundance, access, and regulation, and the expected result is an equilibrium level of quality or exploitation that is largely outside of management control. The resulting implication is that the equilibrium level of exploitation depends only on the target catch rates that anglers seek. That is, if anglers are willing to fish at very low catch rates, fish stocks could be pushed into a state of severe overexploitation despite all but the most severe bag or season limits. This situ- ation, along with our proposal for tighter effort and harvest limits, is strikingly similar to 760 BULLETIN OF MARINE SCIENCE, VOL. 70, NO. 2, 2002 that of commercial fisheries (Ludwig et al., 1993), but the success of limited-entry pro- grams in commercial fisheries remains questionable (Clark and Munro, this issue). Ulti- mately, control of our recreational fisheries will depend on the willingness of regulators and politicians to put sustainable fisheries ahead of short-term political concerns. To date, the desire for sustainable fisheries is questionable, as evidenced by the rather liberal bag and seasonal limits, which rarely prove to be effective in the long-term.

ACKNOWLEDGMENTS

We thank F. C. Coleman for providing us with the opportunity to contribute to the Third Mote Symposium. We also thank J. Kitchell, S. Martell, and T. Essington for helpful suggestions with earlier drafts. The comments of two anonymous reviewers greatly improved this manuscript. Fund- ing for S.P.C. was provided by the Natural Sciences and Engineering Research Council of Canada and Wisconsin Sea Grant.

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ADDRESSES: (S.P.C., T.D.B.) Center for Limnology, University of Wisconsin, Madison, 680 N. Park Street, Madison, Wisconsin 53706. E-mail: , ; (C.W.) Fisheries Centre, University of British Columbia, 2204 Main Mall, Vancouver, B.C. V6T 1Z4, Canada. E-mail: .