8 ToR e Prioritizing fish species for research on fishing mortality
8.5 Estimating fishing mortality for vulnerable species
8.5.1 Species that are vulnerable because of their life‐history
Species can be vulnerable because of particular life‐history characteristics (Hutchings, 2002; Gislason et al., 2009) or ecology. According to Garcia et al., 2008, species can be vulnerable to fishing pressure because of life‐history characteristics such as are, for example, species with low productivity, i.e., low fecundity, slow growth rates, late sexual maturity and long interbirth interval, are less able to compensate for increased mortality and are therefore more vulnerable to depletion (MacArthur and Wilson, 1967). Long lived late maturing species will be adapted to a low natural mortality and even rather modest levels of fishing mortality can cause population decline. Sharks, rays and chimaeras as a group have life‐history traits that make them particularly vulnerable to fishing (see Figure 8.5.1.1).
Figure 8.5.1.1. Fextinct (the fishing mortality needed to drive a species to extinction) for sharks, rays and chimaeras (class Chondrichthyes) of the three main marine habitats. Bold line, median; box, interquartile range; whiskers, range (excluding outliers) and open circles, outliers. From Garcia et al., 2008.
8.5.1.1 Specific approaches for identifying species vulnerable because of particular life history or ecology
Identifying species which are vulnerable because of particular life history or ecology can be difficult because most candidate species are not well studied. However, basic life‐history information can contribute to estimating sustainable mortality rates for many marine species. Several approaches to identifying vulnerable species in situa‐
tions of poor data availability are conceivable. The approaches suggested here use various strategies to derive an estimate for a reference point for fishing mortality from basic life‐history information. Depending on the method, the reference point may be a limit for F, a bound on a target for F, or a surrogate for Fpa. Species where the estimates are comparatively low are considered vulnerable. Knowing the actual fishing mortality of these species would be of particular interest.
a ) An approach previously suggested in the literature is to estimate the natural mortality M for a species, and use that as a maximum bound on an allowable incidental F; the F=M strategy (see Clark, 1991 and references therein). If it is possible to age individuals of a species, then samples from fisheries or surveys can be used to get an estimate of maximum age (MaxAge) for the species in the area. If the fisheries of concern have been operating for many years, historical samples or literature values from a period when the population was not heavily exploited should be strongly pre‐
ferred.
Two different lines of reasoning have been used to support an F=M strat‐
egy as appropriate to relatively long‐lives and late‐maturing species. The first rationale is just the logic that doubling mortality on a long‐lived spe‐
cies (if F=M then Z=2M) might be near the limit of the ability of a low productivity species to compensate for increased mortality through in‐
creasing productivity. The other rationale is that many long life species that have been targeted in fisheries have undergone major declines in abundance when F exceeded M (Musick, 1999; Heifetz et al., 2007; Love et al., 2005). For additional discussion and references, including approaches for estimating M, see Clark, 1991 and García et al., 2008.
b ) The approach outlined under a) has been extended and imple‐
mented by WGECO (Appendix 8.7). Estimates of MaxAge are ob‐
tained indirectly form estimates of the von Bertalanffy parameters K and Linf and an estimate for the age of initial capture in fisheries of concern. Assuming the latter age is older than the period of high larval and juvenile mortality, such that M can be assumed to be constant between the age‐of‐recruitment and MaxAge, the method provides an estimate of M. Estimates of sustainable fish‐
ing mortality are derived and compared with estimates of actual fishing mortality. By comparing sustainable fishing mortality with actual fishing mortality, a measure of fishing pressure is de‐
rived. This measure is demonstrated to correlate well with the rate of population decline determined from survey time‐series.
Details are described in Appendix 8.7.
c ) In an approach suggested by Myers and Mertz, 1998 and Garcia et al., 2008 Fextinct is defined as the average fishing mortality needed to drive a species to extinction. For deep‐water chondrichthyan species the Fextinct was estimated to be 38–58% of that estimated for oceanic and continental shelf species, respectively by Garcia et al., 2008. Following Myers and Mertz (1998), Fextinct can be calculated iteratively from the following equation:
where ᾷ is the annual reproductive rate corrected by embryonic sex ratio; amat is the age at maturation; asel is the age at which fish enter the fishery; and M is natural mortality. When asel is set equal to 1 F‐extinct is equivalent to the maximum intrinsic rate of popu‐
lation increase (rmax), which is a standard measurement of popula‐
tion productivity and extinction risk (Dulvy et al., 2005). We suggest that WGQAF might use this approach to estimate Fextinct for species as this will be useful for assessing the vulnerability of the stocks to present level of fishing mortality.
d ) Yet another approach, with similarly low data requirements, de‐
rives from the observation that Flim or Fpa are often positively cor‐
related with a stock’s non‐fishing biomass B0 (the biomass it would have in the absence of fishing pressure), Figure 8.5.2.1. It is currently unclear if this correlation is mainly as a result of al‐
lometric scaling relations or mainly because of variations of popu‐
lation growth rates within Lmax size classes. In the latter case, estimates of Flim or Fpa for non‐assessed species could be obtained by interpolating established values of Flim for well‐studied species.
This would imply that species with low biomass are particularly vulnerable to fishing mortality.
0 500 1000 1500 2000
II & III (Barents Sea and the Norwegian Sea)
0 100 200 300 400 500
Va (Iceland)
0 5 10 15 20
VIIa (Irish Sea)
cod
Figure 8.5.2.1. Assessment results for Flim or Fpa (annual mortalities) in relation to the zero‐catch biomass B0 for specific ICES regions as reported by ICES 2008. The correlations exhibited in the graphs could help identifying precautionary limits for non‐assessed species. (*) Fpa for Icelandic Cod estimated as 2Fmsy.