When and where can fisheries benefits be expected to occur?

14.3.4 When and where can fisheries benefits be expected to occur?

Many factors will affect the likelihood of fisheries benefits occurring, but given the number of unknowns, it is worthwhile focusing on a few which might act as useful predictors. These factors include biological characteristics of the organ- isms, features of MPAs and their environments, and modes of exploitation.

One factor affecting MPA success in terms of fisheries benefits is the mobility of the species con- cerned. As mobility of species is a key determinant of the build-up of biomass within MPAs, it is clear that it will affect the likelihood not only of spillover effects, but also of the recruitment func- tions of MPAs. This can be simply expressed by comparing species that are highly mobile with those that are not (Table 14.4). Where species are highly mobile, the probability of movement out of MPAs will be high and biomass will not build up within them; this means not only that recruitment effects, will be small, but also that spillover will be small, on the grounds that it is a function, of biomass and the probability of movement (Table 14.4). Conversely, for sedentary species, the recruitment function of MPAs will be maximal, but the spillover effects will be small; on this basis, the greatest spillover is likely to be brought about by species of ‘intermediate’ mobility. This is sup- ported by modelling, where the greatest yield per recruit occurred in a fish of intermediate mobility, although only the most mobile species exhibited

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Chapter 14

Table 14.4 Consequences of species mobility for recruitment through increased egg output and spillover functions of MPAs in intensively fished areas.

Low mobility Biomass accumulation in MPA

High mobility

Moderate mobility

High Recruitment function

Low

Medium

Maximal Spillover function

increase in yield with increasing MPA size, pro- mackerels (Scombridae) was greater with an MPA vided the fishing mortality was sufficiently high much less than 1 km 2 in area (c. 25% of the ground) (DeMartini 1993). In the case of Sumilon Island in than without (Alcala and Russ 1990). In temperate the Philippines, increases in yield were supported waters, measurements of yield effects come princi- especially by fusiliers (Caesionidae), but also by pally from MPAs spanning 10000–>500000km 2 jacks (Carangidae) and mackerels (Scombridae) (Table 14.3), but results at the lower end of this (Alcala and Russ 1990), which are relatively spatial scale are equivocal, as in the case of mobile species for reefs (e.g. Holland et al. 1996).

the North Sea ‘plaice box’, and Cyprus and Other biological characteristics may also help Georges Bank (2500–6000 km 2 ) closures (Piet and predict fishing impacts and the likelihood for re- Rijnsdorp 1998), although the seasonal closure in covery from exploitation in MPAs. For the North Cyprus had a dramatic effect on yield (Garcia Sea, age at maturity, maximum size and potential and Demetropoulos 1986). While these data con- rate of population increase are useful predictors of trast the effects of MPAs in reef and temperate dem- fishery depletion (Jennings et al. 1997), while in ersal fisheries, the indication is that absolute size is reef fisheries, maximum size can help predict not a good predictor of fishery effects. Modelling decline in target-fish abundance (Jennings et al. studies help to emphasize that it is the proportion 1999). Where a stock is depleted through direct of whole fishing grounds which is important (e.g. effects of fishing alone, body size may help to pre- Guénette and Pitcher 1999), rather than absolute dict recovery in MPAs. Body size is clearly related size, and, further, that fishing mortality relative to to a number of other characteristics, including po- natural mortality is going to be important. tential longevity, natural mortality, growth rate

The time-scales over which MPA benefits can and recruitment, and thus does not of itself provide

be expected have been examined in a few empirical an explanation for variations in recovery rate and modelling studies. For some large vulnerable among organisms (Russ and Alcala 1998b).

reef predators in the Philippines, spillover effects

On tropical reefs, very few studies have exam- may take about ten years to become evident (Russ ined changes over time, and it appears that only two and Alcala 1996). The accumulation of biomass to date have determined effects on yield, and pro- within MPAs of site-attached species vulnerable to duced different results, from intensive fisheries fishing can occur within 10 years (Fig. 14.3) (see (Table 14.3). In Kenya, a fishery with an MPA also Borley et al. 1923; Margetts and Holt 1948;

10 km 2 in area, which is about 60% of the ground, Polunin and Roberts 1993), if the MPA is large had produced no increase after seven years in a enough to accommodate the mobility and vulnera- total catch contributed to mostly by rabbitfish bility of the species concerned. In spite of the fact (Siganidae), parrotfishes (Scaridae), octopus and that the scientific basis for it is better understood squid (McClanahan and Kaunda-Arara 1996; than for other strategies such as spillover and lar- T.R. McClanahan and S. Mangi, unpublished data val recruitment through spawning biomass accu- 1999). In the Philippines, a reef catch predominant- mulation, pulse fishing of MPAs is considered ly of fusiliers (Caesionidae), jacks (Carangidae) and by some not to be a feasible option. This is on the

305 (a)

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20 aesthetic. These criteria have served implicit

2 Y = 2.58e purposes of attracting tourism, educating the pub- 0.18X r = 0.89

16 lic or signalling the presence of sensitive commu- nities in particular areas (see below). However, the

science of reserve design and location in relation to

12 issues such as larval supply to depleted fisheries has scarcely progressed beyond an elementary

8 Sumilon

modelling stage (e.g. Man et al. 1995; Guénette and Pitcher 1999; Sladek Nowlis and Roberts 1999;

Reserve

2 ) 4 Planes et al. 2000; Sánchez Lizaso et al. 2000). Some general guidelines on the design of MPAs can

0 be offered (e.g. Carr and Reed 1993; DeMartini –1

1 3 5 7 9 11 1993). In practice, the actual condition of particu- Years of protection

lar sites is unknown. For example, the recruitment (b)

12 source or sink status of sites is rarely established, Y = 1.61e 0.16X 2

and this is especially so over long time-scales.

r = 0.83

Mean biomass (kg/1000m 8