Assessment of Alternative Harvest Regulations for Sustaining ...

North American Journal of Fisheries Management 23:22–34, 2003 q Copyright by the American Fisheries Society 2003

Assessment of Alternative Harvest Regulations for Sustaining Recreational Fisheries: Model Development and Application to Bull Trout JOHN R. POST,* CRAIG MUSHENS, ANDREW PAUL, MICHAEL SULLIVAN1

AND

Division of Ecology, Department of Biological Sciences, University of Calgary, Calgary, Alberta T2N 1N4, Canada Abstract.—Regulations designed to protect recreational fisheries from overexploitation can fail. Regulations such as size and bag limits restrict harvest by individual anglers but not angler effort and therefore not total harvest. Even when individual harvest limits are set to zero (i.e., catch and release), a combination of hooking mortality and noncompliance may lead to fishing mortality rates that are not sustainable if angling effort is sufficiently high. These assertions were tested and quantified by using simulation experiments on a size- and age-structured model developed for a fishery on an adfluvial bull trout population. The functions and rates describing the biology and fishery were derived from a variety of sources, including published and unpublished information on bull trout and, where such sources were unavailable, from other salmonid species. The model predicts that a 40-cm minimum size limit for harvest would maintain viable populations at an annual effort up to 4 angler-hours · ha21 · year21, a 65-cm minimum size limit up to 10 anglerhours · ha21 · year21, and a catch-and-release fishery up to 18 angler-hours · ha21 · year21. The quality of the fisheries that developed under these three alternative regulations varied substantially with the amount of angler effort imposed. Uncertainty in the minimum population size necessary to ensure sustainability, recruits per unit stock, catchability, hooking mortality rate, and noncompliance rate modifies quantitative predictions, but the qualitative patterns are general. If anglers respond dynamically to variation in the quality of fishing, then the ability of size limit regulations to sustain fisheries is further compromised. The combination of life history and fishery traits such as slow growth, late age at maturity, low fecundity, longevity, and high catchability render adfluvial bull trout particularly susceptible to overfishing, even within relatively narrow bounds of angler effort.

A common management response to reduced quality of recreational fisheries is the imposition of regulations to limit the number or size of fish harvested by individual anglers (hereafter termed harvest regulations). The intent is usually to reduce the overall rate of fishing mortality, thereby allowing growth of overexploited populations or increased abundance of the larger fish that are typically sought by anglers. Yet these regulations restrict only the harvest by individual anglers and not the overall rate of harvest, which is the product of individual angler harvest and numbers of anglers. Several field assessments have examined the effects of harvest regulations on the abundance and size structure of fish populations and fish harvested, but results are equivocal (see reviews by Lyons et al. 1996; Power and Power 1996; Munger

and Kraai 1997; Maceina et al. 1998b; Slipke et al. 1998; Hale et al. 1999; Newman and Hoff 2000). Unfortunately, none of these studies measured the numerical response of anglers when calculating total population exploitation. In fact, the imposition of harvest regulations may have its greatest impact not through restricting individual anglers but by altering the number of anglers. For example, the imposition of more restrictive minimum size regulations on the walleye Stizostedion vitreum fishery of Lake Mendota, Wisconsin, resulted in a substantial increase in the number of anglers and an increase in the exploitation rate of walleye (Johnson and Carpenter 1994). In contrast, imposition of a minimum length regulation for white bass Morone chrysops in a lake and river fishery in Texas reduced overall fishing effort (Muoneke 1994). Therefore, equivocal results from field studies may simply represent unknown angler responses to fishing quality under harvest regulations. Population models have been used to predict the effects of harvest regulations on various measures of fishing quality across a range of exploitation

* Corresponding author: [email protected] 1 Present address: Natural Resources Service, Fish and Wildlife Division, Alberta Sustainable Resource Development, Edmonton, Alberta T5L 2W4, Canada. Received June 28, 2000; accepted May 23, 2002

22

ALTERNATIVE HARVEST REGULATIONS FOR BULL TROUT

rates (Gerhardt and Hubert 1991; Luecke et al. 1994; Quinn et al. 1994; Beamesderfer and North 1995; Bulak et al. 1995; Power and Power 1996; Maceina et al. 1998a, 1998b). These models provide useful tools for examining the tradeoffs among catch rate, harvest rate, and fish size across a range of size regulations and exploitation rates. Direct application of these model predictions to assessment of alternative management strategies requires knowledge of current and future rates of exploitation, which are the product of angler efficiency (measured as fish catchability) and angler behavior. This allows translation of exploitation rate into the more commonly measured fishery characteristic, angler effort. The interactions between regulations and angler effort have not been assessed on recreational fisheries (Cook et al. 2001; Radomski et al. 2001). In this paper, we develop a model that allows us to examine the tradeoffs among catch rate, harvest rate, and fish size across a range of minimum size limits for harvest, including catch-and-release (CR), and to contrast the effects of static and dynamic responses in angler effort to changes in fishing quality. This model allows us to delimit combinations of regulations and effort that lead to sustainability or collapse of fisheries. The quantitative results we present are specific to the life history, population, and fishery characteristics of the species we modeled. However, the qualitative patterns presented should apply across recreational fisheries. We developed this model for bull trout Salvelinus confluentus, many populations of which have been negatively impacted throughout their range by a combination of habitat deterioration and overexploitation (Donald and Alger 1993; Rieman and McIntyre 1996; references in Mackay et al. 1997; Post and Johnston 2002). As a consequence, bull trout have been designated in various jurisdictions as ‘‘species of special concern,’’ ‘‘endangered,’’ or ‘‘vulnerable.’’ This species appears to be particularly vulnerable to overfishing because of its life history traits, the low-productivity and lowtemperature environment it occupies, and vulnerability to anglers. Bull trout spawn in highelevation, cold, unproductive streams, mature at age 5–7, and are long lived. Relative to nonsalmonid fishes, females produce few eggs. Juvenile bull trout are vulnerable to angling several years before maturity and appear to be more vulnerable to angling than are many other species of salmonids (Paul 2000; Paul et al. 2003, this issue). This combination of environment, demography, and

23

vulnerability to anglers implies that bull trout is a species with low potential intrinsic rate of increase and a high potential for overexploitation (Post and Johnston 2002). Among various management policies applied to ensure the sustainability of bull trout fisheries are such restrictions on harvest as localized closures to fishing, CR, and size limits. The purpose of this paper is to develop an analytical framework to assess the ability of harvest regulations to sustain recreational fisheries and to apply the framework to management of bull trout. Model Development and Parameterization Baseline functions and parameter set.—The functions and parameter set we used for assessing harvest policy options was developed to represent an adfluvial population of bull trout. The parameter set (Table 1) is a combination of direct estimates from field data accumulated during an intensive field study of the adfluvial bull trout population of Lower Kananaskis Lake, Alberta (Mushens and Post 2000; C. Mushens and J. R. Post, unpublished data), information from other studies on bull trout (reviewed in Paul 2000; Post and Johnston 2002; Thera et al. 2001) and related species, and expert opinion. In this manuscript we deal with the implications of uncertainty of several key parameters; a more formal uncertainty analysis of the full parameter set is presented elsewhere (Thera et al. 2001). Biological processes.—Bull trout tend to be long-lived fish that are relatively slow growing and late to mature and attain large sizes late in life, although this general pattern varies considerably (Post and Johnston 2002). Bull trout populations express four life history strategies—stream resident, fluvial, adfluvial, and anadromous—strategies that differ in growth rates and age at maturity. In our analyses, we characterize the life history of adfluvial bull trout, which tend to be the fastest growing and have the largest size at maturity and asymptotic length. For these reasons, adfluvial bull trout are sought by recreational anglers as trophy fish. We developed an age-structured population model with a maximum age of 15 years and an age at maturity of 6 years, which is typical of this life history type (Post and Johnston 2002). All processes modeled are based on an annual time step from spawning in the fall to the next fall. At each time step, individuals of the maximum age spawn and die, whereas individuals of all other ages, if mature, spawn and then experience a constant per capita mortality rate (see description be-

24

POST ET AL.

TABLE 1.—Parameter set for an age-structured fishery model representing an adfluvial bull trout population. See text for definitions. Parameter

Value

Source

Biology von Bertalanffy growth L` k t0 Length to mass c d Fecundity e f Recruitment g h Natural mortality (m)

80 cm 0.32 2.2 years

a

0.01 g 3.0

a

261.3 eggs 1.48 eggs/kg

a

0.00332 2.075 3 1026 0.2

a

a a

a

a

a b

Fishery Size-dependent vulnerability p b Catchability (q) Hooking mortality (r ) Noncompliance mortality (s) Fixed angler effort (E) Dynamic angler effort response t u w y (weak, medium, strong)

0.3 1200 0.07 (0.14, 0.035) fish caught·vulnerable fish21·anglerhour 21·year 21 0.1 (0.02, 0.25) 0.1 (0.02, 0.25) 0–30 angler-hours·ha 21·year 21 16 angler-hours·ha 21·year 21 0.1 3 1000, 600, 200 vulnerable fish

c c d e f g h h h h

a

Parameters developed to approximate observations of the adfluvial bull trout population of Lower Kananaskis Lake, Alberta (Mushens and Post 2000; Paul 2000; Post et al. 2001). b Natural mortality rates have not been reported for bull trout in the published literature, so we assumed that observations from Lower Kananaskis Lake are representative and that estimates for the lake trout are similar (Shuter et al. 1998). c Parameter value was chosen to reflect the observations that 20-cm bull trout are invulnerable and 40-cm bull trout are completely vulnerable in the Lower Kananaskis Lake bull trout fishery. d Estimated from creel data from Lower Kananaskis Lake and experimental fishery data from Marie Lake and Quirk Creek (Mushens and Post 2000; Paul 2000; Sullivan 2001). We also explored the effects of 2q and 0.5q on model predictions (in parentheses). e We have no direct estimate of hook-and-release mortality for bull trout but presume that in the mixed-gear Lower Kananaskis Lake fishery it is between the rate reported in the literature for the single-hook artificial and multihook bait fisheries. We used 10% for the nominal runs and explored the effects of 2% and 25% (in parentheses). f We have no direct estimate of the noncompliance mortality for bull trout. Sullivan (in press) reports noncompliance rates in Alberta walleye fisheries ranging from 2% to 60%. We chose a 10% mortality rate for nominal runs and explored the effects of 2% and 25% (in parentheses). g We varied angler effort over the range of 0–30 angler-hours·ha 21·year 21 , which is the range observed in walleye fisheries in Alberta. h There is no quantitative information available to model the responsiveness of angling effort to variation in fishing quality for bull trout or any other recreational species. We therefore bracket the possibilities from totally unresponsive (which is the assumption inherent in most empirical studies) to a weak response (which approaches a linear response) to a strong response (where there is a narrow range of fishing quality over which effort increases from low to maximal). The coefficients were chosen to produce these qualitative patterns in effort response, all constrained to the same maximum effort level (see Figure 5a).

low). Age-0 individuals recruit into the population annually as detailed later. The annual rate of growth in length was modeled by using a von Bertalanffy growth curve,

where La is length in cm at age a, and L`, k, and t0 are parameters defining growth. For conversions from length to mass, we used an empirical exponential relationship

L a 5 L ` [1 2 e2k(a2t 0 ) ],

Wa 5 cLad ,


where Wa is mass at age a and c and d are parameters defining the relationship. We did not incorporate density-dependent growth into this agestructured model. The growth parameters we used here reproduce the size at age we observed in the heavily exploited bull trout population from Lower Kananaskis Lake (Mushens and Post 2000). Clearly, if populations rebuild under harvest restrictions and low angler effort, we would expect to see reductions in growth rates and size at age and possibly increases in age at maturity. Because the focus of this analysis is on regulations imposed on populations under exploitation, however, densitydependent reductions in growth rate at high density are not considered. Population fecundity was calculated by assuming that one-half (i.e., females) of the mature age6 and older fish would spawn annually:

O [N (e 1 f W ) · 0.5], 15

E5

a5 6

a

in a recruits per female of 2.4 at age at first maturity. This is very similar to the empirical estimate of annual reproductive rate of lake trout S. namaycush and within the range derived for salmonids in general (Myers et al. 1995). We also assessed the effect of a doubling and halving of this recruits-per-female assumption. Natural mortality is represented as a constant instantaneous rate for ages 0–15 of 0.20. This is in accord with observed mortality of mature bull trout in Lower Kananaskis Lake (Mushens and Post 2000) and with empirical estimates of lake trout mortality, which overlap substantially in life history characteristics (Shuter et al. 1998; Post and Johnston 2002). The total number of mortalities for age a over the course of a year is determined from the sum of the instantaneous natural and fishing mortality rates as D a 5 N a [1 2 e2(m1 f a ) ],

a

where E is egg number calculated by summing over all mature ages, e and f are coefficients describing the fecundity of an individual of mass Wa at age a, and Na is the total number of age-a fish. Recruitment from population fecundity to age0 juveniles is modeled by using a Beverton–Holt stock–recruitment, R5

25

gE , 1 1 hE

where R is recruitment of age-0 fish, and g and h are parameters determining the shape of the stock and recruitment relationship. Parameters for an asymptotic stock–recruitment curve were estimated from data available for the Lower Kananaskis Lake adfluvial bull trout population. The maximum number of recruits to the mature stock has been approximately 450–500 over several years, despite substantial increases in adult numbers over this period (Mushens and Post 2000). Therefore, we calculated the number of age-0 fish necessary to produce 450–500 age-6 fish, given a per capita natural mortality of 0.2 (see below) from age 0 to age 6 in the absence of fishing mortality. This value was set as the asymptotic recruitment of age-0 fish for the stock–recruitment relationship. The stock–recruit relationship also required that we define the maximum number of recruits per unit stock as stock approaches zero. If adfluvial bull trout are of a size that produces 4,000 eggs · female21 (Post and Johnston 2002), then using g 5 0.00332 results

where Da is the total number of deaths at age a, m is the instantaneous mortality rate, and fa is the instantaneous fishing mortality rate at age a (as described below). Fishery processes.—The vulnerability of individual age-classes to the fishery (Va) is represented as a sigmoid relationship with length and scaled from 0 (completely invulnerable) to 1.0 (completely vulnerable) following the methods of Cox (2000) and Paul (2000): Va 5 (1 2 e2pL a ) b, where Va is the vulnerability of fish of age a with length La and p and b describe the shape of the relationship. Data from Lower Kananaskis Lake suggest that individuals about 20 cm long are not caught in the fishery; those 40 cm and longer form the majority of the catch (Mushens, unpublished data). Assessment of size-vulnerability to angling in a resident population of bull trout from Quirk Creek, Alberta, showed a similar pattern (Paul 2000; Paul et al. 2003). The two parameters for this sigmoid function were chosen to capture this general pattern. The choice of a sigmoid function rather than linear or exponential with an asymptote was based on an extensive size-vulnerability data set for lentic rainbow trout Oncorhynchus mykiss (Cox 2000). The total number of vulnerable fish in the population is the sum across all ages of the product of age-specific abundance and vulnerability by age, that is,

26

POST ET AL.

O (N · V ), 15

VT 5

a5 1

a

a

where VT is the total number of fish vulnerable to angling. The total annual catch by the fishery is the product of the total number of vulnerable fish, the amount of fishing effort, and the catchability of the fish: CT 5 qVTA, where CT is catch in fish/year, q is catchability expressed as the proportion of vulnerable fish in the population caught by one unit of effort (fish caught · fish21 · angler-hours21Table 2· year21), and A is angler fishing effort in anglerhours · ha21 · year21. We have 12 individual estimates of catchability (mean 5 0.07) derived from a voluntary creel program on Lower Kananaskis Lake over the four seasons and 3 years (Mushens, unpublished data). This estimate is probably biased because it comes from a voluntary reporting program. We therefore assessed the implications of uncertainty in catchability on assessments of sustainable fishing efforts by using 2q and 0.5q as reasonable bounds. Catch by age is then simply the total catch partitioned into age-classes by weighting the total catch by the vulnerability and abundance of the individual classes, that is, Ca 5 NaVaCT/VT , where Ca is the total catch partitioned among ages according to numbers caught and size- and agebased vulnerability. When unregulated, the fishing mortality by ageclass is simply the catch per age-class, Ca. With size limit regulations, anglers are required to return fish caught at lengths outside the legally specified range of lengths for harvest. We assume three sources of fishing mortality: harvest mortality, hooking mortality of fish that are returned because they are not of legal size, and noncompliance mortality from illegal harvest of fish that are outside the legal size limits. If La is within the size range for legal harvest, then Fa 5 Ca ; otherwise Fa 5 (r 1 s 2 rs)Ca , where Fa is the number of fishing-caused deaths for age-a fish, r is the proportion of those fish

outside the legal size range for harvest that are returned but die because of hooking-related mortality, and s is the proportion of harvested fish that should have been returned because they are outside the legal size range. Instantaneous fishing mortality by age is then

1

f a 5 2log e 1 2

2

Fa . Na

We have no direct information on the magnitude of hooking and noncompliance mortality specifically for bull trout populations, but studies of hooking mortality of nonanadromous salmonids have indicated a range of 2–40% (Dextrase and Ball 1991; Taylor and White 1992; Bendock and Alexandersdottir 1993). Because the artificial gears required in many bull trout fisheries tend to result in lower mortality rates, we used an intermediate value of 10% hooking mortality for baseline simulations; we also assessed implications of a lower (2%) and a higher (25%) hooking mortality rate on sustainable angling effort. Although we have no assessment of the rate of noncompliance typical of bull trout fisheries, a comprehensive study of noncompliance in recreational walleye fisheries in Alberta had a mean noncompliance across 20 lake-years of 19% (range, 0–70%; Sullivan 2002). Estimates of angler noncompliance with slot limits in Minnesota northern pike Esox lucius fisheries was 13–19% (Pierce and Tomcko 1998). In this analysis we used a baseline noncompliance rate of 10% but also assessed implications of a lower (2%) and a higher (25%) rate of noncompliance. Harvest regulations and angler behavior.—The harvest regulations considered here include size limits, CR, and angling effort limitations. Size limits can be minimum, maximum, slot limits for protection, or slot limits for harvest, but here we explore only minimum size for harvest. In the model, CR regulations can be simply implemented by setting the minimum size limit to a size that is larger than that found in the population. Fishing effort is represented in two ways. The first, and standard, approach is to assume that a constant pool of fishing effort is applied to a fishery. We explore the implications of a range of constant annual angling effort on sustainability of an adfluvial bull trout fishery. Although we have no empirical estimate of the maximum annual fishing effort that might be applied to any particular bull trout fishery, data from various recreational Esocidae and Percidae fisheries in Alberta show that lake fisheries receive


effort in proportion to their surface area; therefore, a lake of the surface area of Lower Kananaskis Lake could expect 10–20 angler-hours · ha21 · year21 (M. Sullivan, unpublished data). A second, and probably more realistic, representation of angler behavior is to assume that the total fishing effort is related to the quality of that fishery. Implicit in this is that anglers have options for applying their effort over regions and that their decisions to fish a particular population are based on knowledge of the ‘‘quality’’ of the particular angling opportunity. We model this angler decision as a sigmoid curve relating angler effort to the number of vulnerable fish in the population: A 5 tu 1 t[VwT /(yw 1 VwT )], where t is the maximum effort, u is the proportion of the maximum effort always present, y is the number of vulnerable fish that elicits one-half of the maximum effort, and w is a term that characterizes the steepness of the effort–response curve. This expression implies that the angler effort attracted to any particular system is a function only of its own fishing quality. This model of angler effort dynamics does not incorporate angler dynamics at the regional level, where decisions depend not only on local assessments of quality but also on knowledge at alternative destinations. Here we focus on the impacts of effort, and effort dynamics, at the local single fishery scale. Response variables for assessing sustainability and angling quality.—The ability to sustain a recreational fishery based on natural reproduction requires that a viable adult population be maintained. We have arbitrarily chosen to define a sustainable breeding population as at least 50 pairs of mature bull trout for the baseline simulations. This is based on a minimum sustainable population (minimum viable population [MVP]) that is approximately 6% of the unfished equilibrium population (given our baseline parameter set) and a population size generally considered to be viable from a genetic standpoint (Allendorf and Leary 1986; Lande and Barrowclough 1987; Rieman and Allendorf 2001). In addition, we assessed the sensitivity of our predictions of sustainable fishing effort to our choice of MVP by also simulating twice the MVP and one-half the MVP. The quality of the fishery resulting from combinations of minimum size regulations and fishing effort was assessed for the equilibrium population with measures of total annual catch, total annual

27

FIGURE 1.—Equilibrium abundance of adult bull trout across a range of total annual mortalities estimated with model parameters appropriate for the adfluvial population in Lower Kananaskis Lake, Alberta. The dashed line at a total annual mortality of 0.20 represents the equilibrium density of an unfished population with a natural mortality of 0.20.

harvest, catch per unit effort, and mean length of the catch. Simulation Results Recruitment, Mortality, and Dynamics Equilibrium adult density (log10 scale) decreased relatively uniformly with increases in total annual mortality up to approximately 0.28/year (Figure 1). Further increases in total annual mortality beyond 0.28 led to an increased rate of population decline. This threshold change in equilibrium abundance marks a progression from growth overfishing to recruitment overfishing. At a total annual mortality of less than 0.28, the number of adults is limited by fishing mortality. At total annual mortality greater than 0.28/year, the number of adults is limited both directly by mortality from fishing and indirectly by reduced recruitment as adult stocks decline. Size Limits, Effort, and Sustainability A wide range of minimum size limits are capable of ensuring that the population remains sustainable when angling effort is less than 5 anglerhours · ha21 · year21 (Figure 2a, solid line). If the fishery is regulated with a 40-cm minimum size limit and angler effort exceeds 5 angler-hours · ha21 · year21, the fishery will not be sustainable and will decline below the MVP. For minimum size limits less than approximately 60 cm, approximately the size-at-maturity, small increases in effort to more than 5 angler-hours · ha21 · year21 are sufficient to push populations from sustainable

28

POST ET AL.

cruits per unit adult, i.e., the initial slope of the stock–recruitment relationship; Figure 2b). The selection of a more conservative criterion for defining MVP reduces the maximum effort that is sustainable (Figure 2a), yet differences over the range of 50–200 adults have little effect on the amount of fishing effort that results in sustainable populations at low minimum length regulations. Moreover, as expected, stocks that are more productive at low densities are capable of sustaining substantially greater fishing efforts (Figure 2b). Therefore, precise predictions of maximum sustainable fishing effort require estimates of both the MVP and the number of recruits per spawner, but the qualitative patterns between effort and regulations are robust over broad ranges of both of these parameters. Catch, Harvest, Catch per Unit Effort, and Fish Size

FIGURE 2.—Combinations of annual angler effort and minimum size for harvest that give rise to sustainable (left of the curve) and nonsustainable (right of the curve) populations of adfluvial bull trout. The solid lines are for the nominal run with a minimum viable population (MVP) of 100 adults and 2.4 recruits per adult stock (R/ S). Panel (a) shows the effect of variations in the MVP criterion on sustainable combinations of effort and minimum size, panel (b) the effect of variations in stock productivity (recruits per unit stock at low population size).

to nonsustainable. For minimum length regulations exceeding size at maturity, sustainability is less sensitive to small changes in angling effort. For example, a fishery with a minimum size limit of 65 cm can be sustained at angling efforts up to approximately 12 angler-hours · ha21 · year21, and one with an 80-cm minimum size limit can be sustained at efforts up to approximately 20 anglerhours · ha21 · year21. Given the growth trajectory we use, a minimum size limit of 80 cm is marginally larger than the asymptotic size, which means this regulation represents a CR fishery. At angling efforts that exceed these thresholds for various minimum size limits, including CR, the combination of natural, harvest, and hooking and noncompliance mortality exceeds the total annual mortality that is sustainable. Predictions of angling effort thresholds are sensitive to assumptions of MVP (Figure 2a) and of stock productivity (the maximum number of re-

Catch, harvest, fishing mortality, proportion of fishing mortality that is nonharvest, catch per unit effort, and mean length in the catch all vary with harvest regulation and fishing effort (Figure 3). The selection of a minimum size limit does not ensure a particular level of performance as measured by these indices but rather sets a profile that is determined by the fishing effort applied to the fishery. Catch–effort curves for various regulations are qualitatively similar, with low catch at low effort, maximum catch at an intermediate effort, and catch approaching zero at efforts that exceed those that are sustainable (Figure 3a). Maximum catches occur at 0.36, 0.84, and 1.57 fish · ha21 for 40-cm limit, 65-cm limit, and CR regulations, respectively. The greatest harvest occurs at low fishing effort with the lowest minimum size regulation because there are more younger fish than older fish in a population at equilibrium (Figure 3b). As effort exceeds approximately 5 anglerhours · ha21 · year21, harvest in a 65-cm minimum size fishery exceeds that in a 40-cm minimum size fishery because the fishery with the larger minimum size limit is less depleted at these higher angling efforts. Of course, there is no legal harvest in a CR fishery. These patterns in catch and harvest can best be understood by examining total fishing mortality, which is the sum of natural, harvest, hooking, and noncompliance mortality (Figure 3c). The angler effort that maximizes total fishing mortality increases with increasing size restrictions (Figure 3c). The percentage of the total fishing mortality not generated by harvest, the daily catch rates, and


29

FIGURE 3.—Fishery statistics for populations of adfluvial bull trout managed with a 40-cm minimum length limit, a 65-cm minimum length limit, or a catch-and-release (C&R) regulation across a range of annual fishing effort. Panels are as follows: (a) total annual catch in numbers of fish per hectare, (b) total annual legal harvest, (c) total annual fishing mortality, (d) percentage of total annual fishing mortality not attributable to legal harvest, (e) catch per 8 h of fishing, and (f) mean length of catch.

the mean length of the catch all vary substantially with angling effort (Figures 3c, d, and e). The percentage of total fishing mortality made up of nonharvest (i.e., hooking and noncompliance) increases with both effort and increasing size restrictions. In a CR fishery, 100% of the harvest is essentially bycatch—the fish are dying because of either postrelease hooking mortality or poaching. Catch per 8 h fishing is high at low effort, regardless of the minimum size regulation (Figure 3e), declining most rapidly with effort under the least restrictive minimum size limits and least rapidly in the CR fishery. Catch per 8 h fishing declines at high levels of effort regardless of minimum size restrictions to 1 fish per 5–10 d of an-

gling as the populations are pushed into the nonsustainable region of Figure 2. The mean length of the catch declines with increasing effort in all three minimum size limit regulations, being most pronounced for the small minimum size limit and least pronounced for the CR fishery (Figure 3f). Uncertainty in Catchability, Hooking Mortality, and Noncompliance The combination of minimum size regulation and angling effort that defines the sustainability threshold is sensitive to estimates of catchability (Figure 4a). Qualitatively, the isoclines look the same across minimum size regulations with a threshold change in slope at age at maturity. The

30

POST ET AL.

FIGURE 4.—Combinations of annual angler effort and minimum size for harvest that give rise to sustainable (left of the curve) and nonsustainable (right of the curve) populations of adfluvial bull trout. The solid lines are for the nominal run. Panel (a) shows the effect of variations in catchability (q) on sustainable combinations of effort and minimum size, panel (b) the effect of variations in hook-and-release mortality. Note that the effect of variations in noncompliance (2, 10, and 25%) with minimum size regulations is identical to the that of the same values for hook-and-release mortality.

combination of minimum size regulations and angling effort that defines the sustainability threshold is more sensitive to estimates of hooking mortality at larger size limits than at lower size limits (Figure 4b). At a 40-cm minimum size, the magnitude of hooking mortality has little effect on the sustainable levels of angling effort because there is little CR mortality of undersized individuals. At the other extreme, in a CR fishery, hooking mortality determines the maximum fishing efforts congruent with a sustainable fish population. A CR fishery with a nominal hooking mortality rate of 10% produces a maximum sustainable fishing effort of 21 angler-hours · ha21 · year21. If hooking mortality were reduced to 2%, the maximum sustainable fishing effort would be 31 angler-hours · ha21 · year21 but would be only 12 angler-hours · ha 21 · year21 if hooking mortality were 25%. Because hook-and-release and noncompliance mortality are

FIGURE 5.—Panel (a) shows a characterization of angler effort responses to the quality of angling, as represented by the number of vulnerable fish in the population; the fixed effort curve is for no effort response. Panel (b) shows the impact of angler effort on total annual catch (light bars), total annual harvest (dark bars), and catch per day (dashed line) in a population of adfluvial bull trout with a 65-cm minimum sizelength limit. The population exposed to a strong dynamic angler effort response was nonsustainable. All parameter values were set at the nominal levels.

both applied to undersized fish that were caught and should be returned live, the pattern shown in Figure 4b would be the same for noncomplianceinduced mortalities of 2, 10, and 25%. Angler Effort Dynamics We contrasted catch, harvest, and daily catch for a fishery with a 65-cm minimum size limit for a fixed effort and for weak, medium, and strong effort responses. The fixed effort response scenario was run for an effort of 8 angler-hours · ha21 · year21, which is the effort that maximizes total catch of a fishery regulated by a 65-cm minimum length regulation (Figure 3a). The dynamic effort response was defined as a maximum effort of 18 angler-hours · ha21 · year21, a minimum that is 10% of the maximum, and vulnerable fish densities producing one-half of the maximum effort of 1,000, 600, and 200 fish. This range of effort is meant to represent weak, medium, and strong effort responses (Figure 5a; Table 1). Fixed and weak effort responses produced very similar catches, harvests, and daily catch rates (Figure 5b).


Over the range of weak to strong effort, catch dropped by 43%, harvest by 69%, and catch rate by 67% (Figure 5b). The strong effort response led to a fishery that is not sustainable. Catch rate declines from approximately 1 fish/d to 1 fish every 3 d across this range of angler effort response strengths. Note that the minimum and maximum angler effort remained constant; only the responsiveness of anglers to angling quality varied. If we instead chose a more conservative MVP of 200 adults to define a sustainable fishery, the medium strength effort response would also lead to an unsustainable fishery. Discussion Harvest regulations in recreational fisheries that are implemented to reduce total fishing mortality can fail for two reasons: failure to account for hooking and noncompliance and the effects of dynamic angler effort. Imposition of restrictive regulations may temporarily dissuade some fishing effort, but consequent improvements in quality (catch per unit effort or fish size) are likely to reattract effort. This dynamic interaction between regulations, fishing quality, and angler behavior may render the regulations useless in sustaining native stocks in regions near high concentrations of potential anglers. A systematic assessment of all sources of fishing mortality as a function of minimum size regulations and fishing effort led us to an interesting observation. A byproduct of trophy (i.e., large minimum size) regulations is that the majority of the sustainable harvest is actually ‘‘discarded’’ (i.e., fish die as a result of hooking mortality) or is lost to illegal harvesting. Therefore, such policies can be criticized based on the ‘‘waste’’ of the resource they are designed to protect. What are the implications of these findings to bull trout fisheries specifically and to recreational fisheries in general? Primarily, species such as bull trout, with relatively slow growth, late age at maturity, low fecundity, and high catchability have low sustainable levels of fishing effort and harvest. The large catches of bull trout seen in photographs taken before 1950 (Mackay et al. 1997) probably represent a couple of decades of cumulative production that would take another couple of decades to replace, and only if the fish population is unexploited. Therefore, the population declines that have been identified in many jurisdictions (Mackay et al. 1997) will probably not quickly recover. For the small number of bull trout populations in which populations have increased in response to

31

restrictive regulations (Allan 1997; Stelfox 1997; Mushens and Post 2000), we urge caution because angler effort responses to the opportunity to fish large-bodied salmonids could be strong and render even particularly restrictive harvest regulations unsustainable. In Lower Kananaskis Lake, the population of bull trout has increased from approximately 60 to 1,500 adults in less than a decade in response to a CR regulation imposed in 1992 (Stelfox 1997; Mushens and Post 2000). This demonstrates that growth overfishing in the late 1980s and early 1990s under a 40-cm minimum size limit was unsustainable, given the fishing effort imposed at that time. Recent indications are that total mortality rates of vulnerable individuals are increasing quickly despite the no-harvest policy (Mushens and Post 2000). Therefore, the Lower Kananaskis Lake bull trout population may provide a test of some of our predictions over the next decade. These predictions are not without uncertainty, which stems from uncertainty in the parameter estimates and the underlying processes (Hilborn and Walters 1992). Key parameter uncertainty includes fishery and biological rates. Published empirical estimates of hooking mortality vary widely. Gear restriction policies reduce, but do not eliminate, the hooking mortality rate. Illegal harvest also can be reduced by education and enforcement but is unlikely to be eliminated. Estimates of the magnitude of these two rates are necessary because these factors contribute to total fishing mortality and increase in importance as regulations become more restrictive. Catchability is also crucial to know because it is the process that links the vulnerable fish population to the fishery, and the magnitude of catchability contributes to the level of sustainable effort and harvest. Uncertainty in biological parameters involves primarily the recruitment processes and the population size required to ensure sustainability (Thera et al. 2001). Because we have reliable estimates of the maximum recruitment of bull trout from Lower Kananaskis Lake (Mushens and Post 2000), we could derive the initial slope of the stock–recruitment curve by assuming that at low density the adults would replace themselves 6 years after spawning. Myers et al. (1995), in their review of hundreds of fish stocks, suggested that there is remarkable similarity within families for the maximum recruits per unit stock at low stock size, which may be useful in developing general models. Interpopulation variability in parameter values will lead to different quantitative predictions of sustainable levels of ef-

32

POST ET AL.

fort and harvest; however, the qualitative patterns for sustainable levels of effort and harvest should be similar. Although population biology provides the theory and models to estimate minimum viable populations, field biology rarely provides sufficient data to develop precise predictions. Stochastic variation in vital rates and the underlying genetic structure of small populations is rarely known. For these reasons, Reiman and Allendorf (2001) suggested that management use conservative minimum population sizes, in the range that we simulated or even larger, to maintain genetic diversity and to enhance the probability of population persistence. Populations with highly variable vital rates require larger minima, and metapopulations with reasonable exchange rates may persist at lower minimum population sizes. Our analysis could be enhanced with stochastic simulations if more becomes known about interannual variation in growth, survival, and recruitment rates of particular populations. Uncertainties involving the functional forms of various processes should be of more concern than parameter estimation in our attempt to manage fisheries by using a precautionary approach. For example, although anecdotal observations of angler effort response are not uncommon (Carpenter et al. 1994; Johnson and Carpenter 1994), the functional form and intensity of this response are not known. Yet we demonstrate here that these are important factors in the assessment of sustainable fisheries. Moreover, single fisheries do not function in isolation. Anglers make decisions about where and how much to fish over regions based on assessments of angling quality, travel time, and other costs, about which we currently know very little (Walters and Cox 1999; Cox 2000; Post et al. 2002). The literature appears to indicate that recreational fisheries are self-regulating (see Hansen et al. 2000). However, without alternative opportunities in regions adjacent to large urban centers, the minimum fishing quality at which anglers abandon fishing may be sufficiently low that natural self-sustaining stocks cannot persist (Cox 2000), resulting in fisheries that are maintained only by stocking (Evans and Wilcox 1991). Inverse density-dependent, or depensatory, processes may also hinder management for sustainable fisheries. These processes, which have been identified in several commercial fisheries, are capable of destabilizing predator–prey interactions, and their effect on recreational fisheries may be no different (Myers et al. 1995; Shelton and Healey

1999; Frank and Brickman 2000; Post et al. 2002). Evidence is mounting that catchability in recreational fisheries may be inversely densitydependent because recreational fish species tend to aggregate and are sought by anglers that can identify these aggregations (Lester and Shuter 1993; Shuter et al. 1998; Hansen et al. 2000). Noncompliance with regulations can also increase as catch rate declines (Sullivan 2002). Because many recreational species are large-bodied piscivores, depletion can lead to a predatory release of smaller-bodied species that are competitors with or predators on juveniles of the recreational species. This results in a competitive or predator pit from which recreational species might not emerge when angling effort declines (Walters and Kitchell 2001; Post et al. 2002). These three inverse density-dependent processes can result in depensation in the angler–fish interaction, which will render our predictions of sustainable levels of harvest and effort overly optimistic. We are currently quantifying these processes and exploring the impact of depensatory processes on sustainable levels of harvest and angling effort. Therefore, we believe that adfluvial bull trout are capable of producing trophy fisheries; because of their life history and high catchability, however, they are sustainable over only narrow ranges of angling effort. Uncontrolled growth in angling effort can, regardless of harvest regulations, deplete spawning stocks and collapse fisheries (Post et al. 2002). Recreational fisheries for other species with life histories similar to bull trout (i.e., relatively slow growth and late age at maturity), such as northern populations of walleyes, pike, and lake trout, may also be susceptible to overfishing (Ryerson and Sullivan 1998; Shuter et al. 1998; Post et al. 2002; Sullivan, in press). Acknowledgments We acknowledge the foresight of the Alberta Bull Trout Task Force, which was instrumental in the development of Alberta’s Bull Trout and Management and Recovery Plan. The development of the approach we have taken to assess sustainable harvest of bull trout benefited substantially from interactions with participants at several workshops held at the University of Calgary. In particular, we acknowledge the participation of Jim Stelfox, Dave Christiansen, Brian Lajeunesse, Brian Parker, Cal McLeod, Trevor Thera, Paul Hvenegaard, Terry Clayton, Duane Radford, Ken Zelt, Dave Berry, and Kerry Brewin. This research was funded by Alberta Buck for Wildlife, the Alberta Con-


servation Association, TransAlta Utilities, and the Natural Sciences and Engineering Research Council of Canada. References Allan, J. H. 1997. Increases in the number of bull trout spawning in Line Creek, British Columbia. Pages 235–236 in W. C. Mackay, M. K. Brewin, and M. Monita, editors. Friends of the Bull Trout conference proceedings. Trout Unlimited Canada, Bull Trout Task Force, Calgary, Alberta. Allendorf, F. W., and R. F. Leary 1986. Heterozygosity and fitness in natural populations of animals. Pages 57–76 in M. E. Soule, editor. Conservation biology: the science of scarcity and diversity. Sinauer, Sunderland, Massachusetts. Beamesderfer, R. C. P., and J. A. North. 1995. Growth, natural mortality, and predicted response to fishing for largemouth bass and smallmouth bass populations in North America. North American Journal of Fisheries Management 15:688–704. Bendock, T., and M. Alexandersdottir. 1993. Hooking mortality of chinook salmon released in the Kenai River, Alaska. North American Journal of Fisheries Management 13:540–549. Bulak, J. S., D. S. Wethey, and M. G. White III. 1995. Evaluation of management options for a reproducing striped bass population in the Santee–Cooper system, South Carolina. North American Journal of Fisheries Management 15:84–94. Carpenter, S. R., A. Munoz-del-Rio, S. Newman, P. W. Rasmussen, and B. M. Johnson. 1994. Interactions of anglers and walleyes in Escanaba Lake, Wisconsin. Ecological Applications 4:822–832. Cook, M. F., T. J. Goeman, P. J. Radomski, J. A. Younk, and P. C. Jacobson. 2001. Creel limits in Minnesota: a proposal for change. Fisheries 26(5):19–26. Cox, S. 2000. Angling quality, effort response, and exploitation in recreational fisheries: field and modelling studies on British Columbia rainbow trout (Oncorhynchus mykiss) lakes. Doctoral dissertation. University of British Columbia, Vancouver. Dextrase, A. J., and H. E. Ball. 1991. Hooking mortality of lake trout angled through the ice. North American Journal of Fisheries Management 11:477–479. Donald, D. B., and D. J. Alger. 1993. Geographic distribution, species displacement, and niche overlap for lake trout and bull trout in mountain lakes. Canadian Journal of Zoology 71:238–247. Evans, D. O., and C. C. Wilcox. 1991. Loss of exploited, indigenous populations of lake trout, Salvelinus namaycush, by stocking of non-native stocks. Canadian Journal of Fisheries and Aquatic Sciences 48: 134–147. Frank, K. T., and D. Brickman. 2000. Allee effects and compensatory population dynamics within a stock complex. Canadian Journal of Fisheries and Aquatic Sciences 57:513–517. Gerhardt, D. R., and W. A. Hubert. 1991. Population dynamics of a lightly exploited channel catfish stock in the Powder River system, Wyoming–Montana.

33

North American Journal of Fisheries Management 11:200–205. Hale, R. S., M. E. Lundquist, R. Miller, and R. W. Petering. 1999. Evaluation of a 254-mm minimum length limit on crappies in Delaware Reservoir, Ohio. North American Journal of Fisheries Management 19:804–814. Hansen, M. J., T. D. Beard, Jr., and S. W. Hewett. 2000. Catch rates and catchability of walleyes in angling and spearing fisheries in northern Wisconsin lakes. North American Journal of Fisheries Management 20:109–118. Hilborn, R., and C. J. Walters. 1992. Quantitative fisheries stock assessment: choice, dynamics and uncertainty. Chapman and Hall, New York. Johnson, B. M., and S. R. Carpenter. 1994. Functional and numerical responses: a framework for fish–angler interactions. Ecological Applications 4:808– 821. Lande, R., and G. F. Barrowclough. 1987. Effective population size, genetic variation, and their use in population management. Pages 87–123 in M. E. Soule, editor. Viable populations for conservation. Cambridge University Press, Cambridge, UK. Lester, N. P., and B. J. Shuter. 1993. Review of ‘‘Catch effort sampling strategies: their application to freshwater fisheries management,’’ edited by I. G. Cowx. Transactions of the American Fisheries Society 122: 1031–1032. Luecke, C., T. C. Edwards, Jr., M. W. Wengert, Jr., S. Brayton, and R. Schneidervin. 1994. Simulated changes in lake trout yields, trophies and forage consumption under various slot limits. North American Journal of Fisheries Management 14:14–21. Lyons, J., P. D. Kanehl, and D. M. Day. 1996. Evaluation of a 356-mm minimum-length limit for smallmouth bass in Wisconsin streams. North American Journal of Fisheries Management 16:952–957. Maceina, M. J., P. W. Bettoli, S. D. Finely, and V. J. DiCenzo. 1998b. Analysis of the sauger fishery with simulated effects of a minimum size limit in the Tennessee River of Alabama. North American Journal of Fisheries Management 18:66–75. Maceina, M. J., O. Ozen, M. S. Allen, and S. M. Smith. 1998a. Use of equilibrium yield models to evaluate length limits for crappies in Weiss Lake, Alabama. North American Journal of Fisheries Management 18:854–863. Mackay, W. C., M. K. Brewin, and M. Monita, editors. 1997. Friends of the bull trout conference proceedings. Trout Unlimited Canada, Bull Trout Task Force, Calgary, Alberta. Munger, C. R., and J. E. Kraai. 1997. Evaluation of length and bag limits for walleyes in Meredith Reservoir, Texas. North American Journal of Fisheries Management 17:438–445. Muoneke, M. I. 1994. Dynamics of a heavily exploited Texas white bass population. North American Journal of Fisheries Management 14:415–422. Mushens, C. J., and J. R. Post. 2000. Population dynamics of the Lower Kananaskis Lake bull trout.

34

POST ET AL.

Alberta Conservation Association and TransAlta Utilities, Progress Report, Calgary, Alberta. Myers, R. A., N. J. Barrowman, J. A. Hutchings, and A. A. Rosenberg. 1995. Population dynamics of exploited stocks at low population levels. Science 269:1106–1108. Newman, S. P., and M. H. Hoff. 2000. Evaluation of a 16-inch minimum length limit for smallmouth bass in Pallette Lake, Wisconsin. North American Journal of Fisheries Management 20:90–99. Paul, A. J. 2000. Recruitment dynamics in bull trout (Salvelinus confluentus): linking theory and data to species management. Doctoral dissertation. University of Calgary, Calgary, Alberta. Paul, A. J., J. R Post, and J. D. Stelfox. 2003. Can anglers influence the abundance of native and nonnative salmonids in a stream from the Canadian Rocky Mountains? North American Journal of Fisheries Management 23:109–119. Pierce, R. B., and C. M. Tomcko. 1998. Angler noncompliance with slot length limits for northern pike in five small Minnesota lakes. North American Journal of Fisheries Management 18:720–724. Post, J. R., and F. D. Johnston. 2001. The status of bull trout (Salvelinus confluentus) in Alberta. Alberta Environmental Protection, Wildlife Management Division, Wildlife Status Report 39, Calgary, Alberta. Post, J. R., C. J. Mushens, and A. J. Paul. 2001. Sustainable exploitation of bull trout: biology, management and models. Page 215 in M. K. Brewin, A. J. Paul, and M. Monita, editors. Bull trout II conference proceedings. Trout Unlimited, Calgary, Alberta. Post, J. R., M. Sullivan, S. Cox, N. P. Lester, C. J. Walters, E. A. Parkinson, A. J. Paul, L. Jackson, and B. J. Shuter. 2002. Canada’s recreational fisheries: the invisible collapse? Fisheries 27(1):6–17. Power, M., and G. Power. 1996. Comparing minimumsize and slot limits for brook trout management. North American Journal of Fisheries Management 16:49–62. Quinn, N. W. S., R. M. Korver, F. J. Hicks, B. P. Monroe, and R. R. Hawkins. 1994. An empirical model for lentic brook trout. North American Journal of Fisheries Management 14:692–709. Radomski, P. J., G. C. Grant, P. C. Jacobson, and M. F. Cook. 2001. Visions for recreational fishing regulations. Fisheries 26(5):7–18. Rieman, B. E., and F. W. Allendorf. 2001. Effective population size and genetic conservation criteria for bull trout. North American Journal of Fisheries Management 21:756–764. Rieman, B. E., and J. D. McIntyre. 1996. Spatial and temporal variability in bull trout redd counts. North American Journal of Fisheries Management 16: 132–141. Ryerson, D., and M. Sullivan. 1998. Where have all the northern pike gone? Federation Alberta Naturalists 28:12–13.

Shelton, P. A., and B. P. Healey. 1999. Should depensation be dismissed as a possible explanation for the lack of recovery of the northern cod (Gadus morhua) stock? Canadian Journal of Fisheries and Aquatic Sciences 56:1521–1524. Shuter, B. J., M. L. Jones, R. M. Corver, and N. P. Lester. 1998. A general, life history based model for regional management of fish stocks: the inland lake trout (Salvelinus namaycush) fisheries of Ontario. Canadian Journal of Fisheries and Aquatic Sciences 55:2161–2177. Slipke, J. W., M. J. Maceina, V. H. Travnichek, and K. C. Weathers. 1998. Effects of a 356-mm minimum length limit on the population characteristics and sport fishery of smallmouth bass in the Shoals Reach of the Tennessee River, Alabama. North American Journal of Fisheries Management 18:76–84. Stelfox, J. D. 1997. Seasonal movements, growth, survival and population status of the adfluvial bull trout population in Lower Kananaskis Lake, Alberta. Pages 309–316 in W. C. Mackay, M. K. Brewin, and M. Monita, editors. 1997. Friends of the bull trout conference proceedings. Trout Unlimited Canada, Bull Trout Task Force, Calgary, Alberta. Sullivan, M. 2001. How much angling can a bull trout population sustain? Pages 85 in M. K. Brewin, A. J. Paul, and M. Monita, editors. Bull trout II conference proceedings. Trout Unlimited, Calgary, Alberta. Sullivan, M. 2002. Illegal angling harvest of walleyes protected by length limits in Alberta. North American Journal of Fisheries Management 22:1053– 1063. Sullivan, M. In press. Active management of Alberta’s walleyes: dilemmas of managing recovering fisheries. North American Journal of Fisheries Management. Taylor, M. J., and K. R. White. 1992. A meta-analysis of hooking mortality of non-anadromous trout. North American Journal of Fisheries Management 12:760–767. Thera, T. M., A. J. Paul, P. J. Hvenegaard, and J. R. Post. 2001. Identification of research priorities for a fluvial bull trout (Salvelinus confluentus) population using a quantitative life-cycle model in a simulation modelling framework. Pages 105–107 in M. K. Brewin, A. J. Paul, and M. Monita, editors. Bull trout II conference proceedings. Trout Unlimited, Calgary, Alberta. Walters, C. J., and S. Cox. 1999. Maintaining quality in recreational fisheries: how success breeds failure in the management of open access sport fisheries. University of British Columbia Fisheries Centre Research Reports 7:22–29. Walters, C. J., and J. F. Kitchell. 2001. Cultivationdepensation effects on juvenile survival and recruitment: a serious flaw in the theory of fishing? Canadian Journal of Fisheries and Aquatic Sciences 58:39–50.