MSY is the target in both the classical and neoclassical views and its presence remains in many international, national and regional standards and legislative acts to this day (Quinn & Deriso 1999
, ch. 11). Various policies evolved to achieve MSY, include constant catch, exploitation and escapement policies. It has been clear that a constant catch at the MSY level is not sustainable, because insufficient production is available at any other biomass level than that producing MSY. Consequently, a constant catch policy must be at a lower level than MSY. Alternatively, constant exploitation or fishing mortality policies automatically adjust for variations in biomass and proper implementation should keep the population near the level producing MSY (albeit with variations depending on the level of stochasticity in the population).
presaged many recent concerns in his Epitaph to MSY: ‘Here lies the concept, MSY. / It advocated yields too high, …’. His concerns included a reduction in genetic variability, the observations of catastrophic declines in some fish populations and the inability to accommodate interactions among species. He concluded: ‘It is certain that the concept of MSY will alone not be sufficient’.
As time-series became long enough to examine spawner–recruit curves in the 1980s, it was clear that there was substantial uncertainty in the spawner–recruit relationship, presumably owing to environmental variability. Consequently, alternatives to FMSY were sought, which were not based on a spawner–recruit relationship, such as maximizing the yield per recruit by adjusting fishing mortality (Fmax) and minimum size. However, Fmax is often larger than FMSY because it does not account for density dependence and, consequently, it is often not as conservative. An important development for increased conservatism was F0.1, which is the fishing mortality that produces a marginal 10% increase in yield per recruit compared to that at F=0; F0.1 is necessarily less than Fmax (but not necessarily less than FMSY.
All these biological reference points involve yield optimization as their primary objective. In a landmark paper, Sissenwine & Shepherd (1987)
tied together yield per recruit, MSY and spawner–recruit theory and suggested a move to preserving spawning biomass (or egg production) or spawning biomass per recruit. By shifting the focus from the fishery to the resource, conservation and sustainability were explicitly made the primary objectives. Further work by Clark (1993)
, Thompson (1993)
and Mace & Sissenwine (1993)
suggested that a constant fishing mortality policy, Fx%
, that preserves expected spawning biomass (or egg production) per recruit at x
% of an unfished population, would be a suitable proxy for FMSY
. Typical values of x
are between 35 and 45 (Quinn & Deriso 1999
, ch. 11).
Another important development occurred in the 1990s: the formal consideration of risk (Francis & Shotton 1997
; Punt & Hilborn 1997
). This development stemmed from advances in assessment methodology and decision-making by considering Bayesian methods and decision analysis. As one example, the International Council for the Exploration of the Sea has adopted a precautionary reference point, Fpa
, a fishing mortality rate with a low probability of stock collapse (ICES 1998
). The major consequence of considering risk has been the recommendation of lower harvests and related management measures. This has led to quantitative harvest policies (also known as control rules), in which FMSY
has changed from a target to a limit (Mace 2001
). Thus, the permissible set of fishing mortalities and abundances that constitutes sustainability in the modern view () has been further restricted over that in the neoclassical view (). In this figure, there is a new grey area of caution between the target and limit values. Some people would consider the grey area sustainable; others would not.
Figure 17 The modern notion of sustainability, with sustainable combinations of fishing and abundance shown in white, cautionary ones in grey, and unsustainable ones in black. FMSY is now the limiting fishing mortality rather than the target. Different people would (more ...)
More risk-averse control rules have been implemented in several fisheries than those based on constant fishing mortality. These rules include the aforementioned threshold level, below which fishing is curtailed, or biomass-based adjustment, which implements lower F at population abundance lower than the target level (). One advantage of the biomass-based adjustment is that more risk-averse action is taken continuously as a population drops below its desired target level, rather than waiting until it drops below the threshold level.
Figure 18 A biomass-based control rule with a target and a limit. In this example, a constant fishing mortality occurs when the population is above the target up to its carrying capacity. The target fishing mortality is smaller than the limiting fishing mortality (more ...)
To illustrate the modern view of sustainability, we calculated the biological reference points mentioned above for the classical Ricker prototype (. Average natural mortality is ca
. 0.30, which can be viewed as an upper bound for reasonable harvest policies, in the sense that higher values are usually above the level producing MSY (Deriso 1982
). In this case, FMSY
is the most risk-averse, perhaps because of strong density dependence and that the age of 50% maturity occurs two years after the age of 50% selectivity of the fishing gear. Fishing mortality reference points based on spawning biomass per recruit (40% of unfished), egg production per recruit (40%), and spawning abundance per recruit (50%) are similar and close to F0.1
. These reference points exploit a small proportion of total abundance (6% or less) and exploitable abundance (25% or less) and preserve spawning biomass per recruit at 38% or more. Fmax
is much larger than the others and would be at best on the outer bounds of sustainability.
Biological reference points for the classical Ricker prototype, their average exploitation fractions (μ1=C/N;μ2=C/EN), and their values of spawning biomass per recruit.
Discounting is an economic term that relates to sustainability. With a positive discount rate, future yields from a fish stock are valued less than the same yield taken at present (Clark 1985
). Positive discount rates are commonly used for investment and management decisions, because of the uncertainty that future harvests will be available and because of alternative investment opportunities for capital. Clark (1985)
stated a fundamental principle of renewable resource economics: ‘Higher discount rates normally imply lower levels of resource conservation by private resource owners, other things being equal’. Positive discount rates are inconsistent with the modern view of sustainability, which assumes that fish stocks will be valued in the future at least as much as they are now. In fact, some environmental groups have advocated the use of negative discount rates, which would assign higher value to future harvests (see Quinn & Deriso 1999
, p. 447).
To illustrate the effect of discounting we calculated the sum of discounted yields from years 3 to 50 in 50-year simulations of the Ricker prototype model with different levels of fishing mortality. The first two years were omitted from the sum to remove the influence of the initial population sizes, which were the same for each value of fishing mortality. Simulations were run with high and low starting populations and with five different discount rates. For both starting population sizes, fishing mortality resulting in maximum discounted yield was higher with positive discounting (), because most of the value is obtained in the early years and catch in the later years has smaller value. Positive discounting is inconsistent with any definition of sustainability because discounted yield would be maximized at a fishing mortality greater than Fext (0.37).
Fishing mortality, Fmdy, which produces maximum discounted yield over the time horizon for various values of the discount rate δ, for the classical Ricker prototype with low and high starting populations.
With negative discounting, a slightly lower fishing mortality rate would maximize yield for the high starting population (). The reason that we did not see bigger differences is that fishing mortality was fixed over the entire simulation time-frame. To obtain high yields in the future, one would need to allow the population to rebuild and then to fish it down again. However, a sustainable yield in the future would be the same as a sustainable yield today, so a negative discount rate may not be a useful concept. One could argue that the fish stock has a future value whether it is harvested or not and that the negative discount rate should be applied to stock abundance instead of yield. In this case, value would be maximized with no fishing, irrespective of the discount rate. A more useful approach is to explicitly recognize the trade-offs among conflicting objectives as discussed in § 6.
In conclusion, the modern view of sustainability is more focused on preservation of spawning biomass and production at all life stages than ever before. Many reference points are similar and usually lower than average natural mortality. Generally, assessment science has evolved to the point at which scientists know what levels of F are safe to preserve spawning biomass, avoid risk and allow harvest. Nevertheless, there are many situations in which the uncertainties in the information make it difficult to formulate prudent management decisions.
The objectives of scientific advice in the single-species setting have also become explicit and well defined. Quantitative control rules have been implemented for most US marine fisheries and the operational approach with simulation testing has been implemented around the world. Nevertheless, the choice of a particular reference point needs a process that can lead to scientific and political agreement(s) and must be adaptable to particular populations and situations. Our examination of discounted yield shows that the specified objective has major effects on the decision-making.