Despite the obvious limitations of our analyses, consistent patterns have emerged that would otherwise be unsupported by single studies. On average, the immediate impact of fishing disturbance was to remove about half the individuals. However, the magnitude of the response varied significantly with gear type, habitat and among taxa.
With respect to gear type our results are broadly consistent with expectations—inter-tidal dredging has more marked initial effects than scallop dredging, which in turn is greater than otter trawling. Although, at first sight, the apparent lack of effect from beam trawling is somewhat surprising, we suspect that the relative paucity of data for this gear is almost certainly part of the explanation. It should also be borne in mind, however, that beam-trawling studies were generally conducted in relatively dynamic sandy areas, where initial effects may be less apparent.
Our expectations for a habitat effect were that initial responses and rates of recovery from trawling impacts would be related to, and could be predicted from, the physical stability of the sea bed. It makes intuitive sense that animals living in unconsolidated sediments are adapted to periodic sediment resuspension and smothering. Indeed, such intuition has been the cornerstone of our own thinking about impacts and recovery dynamics for benthos (e.g. Hall 1994; Jennings & Kaiser 1998). However, our initial impact results with respect to habitat were somewhat inconsistent among analyses. It does appear that responses in sand habitats were usually less negative than in the other habitats, but a clear ranking for expected impacts did not emerge. The inconsistencies may reflect interactions between the factors arising from the unbalanced nature of the data, with many combinations of gear and habitat unrepresented. For example, the relatively low impact on mud habitats may be explained by the fact that most studies were done with otter trawls. If data were also available for the effect of dredgers a more negative response for this habitat may have been observed. Whether these inconsistencies can be explained in this way can only await further study.
Perhaps the most consistently interpretable result was with respect to faunal vulnerability, with a ranking of initial impacts that seems broadly congruent with expectations based on morphology and behaviour.
Our regression tree analysis provides the first quantitative basis for predicting the relative impacts of fishing under different situations. Following the tree from its root to the branches we can make predictions, for example, about how a particular taxon would be affected initially by disturbance from a particular fishing gear in a particular habitat. Thus, we would predict from Fig. 3 that trawling would reduce anthozoans by 68%, whereas Asteroids would only be reduced by 21%. Similarly, for dredging chronic exposure (repeated dredging) is predicted to lead to 93% reductions for anthozoa, malacostraca, ophiuroidea and polychaeta, whereas acute fishing (a single dredge event) is predicted to lead to a 76% reduction. At this stage, it would clearly be unwise to use this analysis as anything other than illustrative, but we argue that the approach might ultimately provide a useful quantitative framework for predicting fishing impacts, particularly because it is readily amenable to updating in the light of new data.
Recovery from trawling impacts
Our recovery data, while very preliminary, permit us to speculate about the level of physical disturbance that is sustainable in a particular habitat. For example, if, as our results suggest, sandy sediment communities are able to recover within 100 days, this implies that they could perhaps withstand 2–3 incidents of physical disturbance per year without changing markedly in character. This is the average predicted rate of disturbance for the whole of the southern North Sea, for example. However, when fishing effort data is collected at fine spatial (9 km2) resolution (Rijnsdorp et al. 1998), it becomes clear that effort is patchily distributed and that some relatively small areas of the seabed are visited by > 400 trawlers per year. This level of fishing equates to a total disturbance of approximately eight times per year (Rijnsdorp et al. 1998). If our recovery rate estimates for sandy habitats are realistic, this is a rate that will result in a resident community that is not representative of the fauna that originally occurred in that habitat.
While the above example is illustrative, there are some important caveats. First, the small spatial scale of most of the trawl impact studies make it likely that much of the recolonization was through immigration into disturbed patches, rather than reproduction within patches. We found recovery to be slower if the spatial scale of impact was larger, as it would be on heavily fished grounds. Secondly, it should be noted, that while we might accurately predict the recovery rate for small-bodied taxa such as polychaetes, which dominate the data set, sandy sediment communities often contain one or two long-lived and therefore vulnerable species. Note, for example, the occurrence of the large bivalve Mya truncata in the inter-tidal zone of the Wadden Sea. While the majority of the benthos in this environment recovered within 6 months of lugworm dredging, the biomass of M. truncata remained depleted for at least 2 years (Beukema 1995). Given the effects observed in many studies, we anticipate a shift from communities dominated by relatively high biomass species towards dominance by high abundances of small-sized organisms.
It is clear that intensively fished areas are likely to be maintained in a permanently altered state, inhabited by fauna adapted to frequent physical disturbance. This is, of course, much more likely for the most stable types of habitats containing structural biogenic components. It is for these habitats that the paucity of data is most apparent and where recovery rates will be longest. While it would appear that none of the habitats included in our study for which recovery data are available fall into this category, some data are emerging. Recent work by Hall-Spencer & Moore (1999) on Maerl beds, for example, showed that 4 years after the initial disturbance had occurred, certain fauna, such as the nest building bivalve Limaria hians, had still not recolonized trawl tracks. Similarly, work by Sainsbury et al. (1997) suggests that recovery rates may exceed 15 years for sponge and coral habitats off the western coast of Australia. As a matter of urgency we need to identify other habitats that show long recovery times—the most likely candidates are of course those that, like Maerl beds, contain a high proportion of structural fauna.
Despite our efforts to predict the outcome of fishing activities for existing benthic communities, we are often unable to deduce the original composition of the fauna because data gathered prior to the era of intensive bottom fishing are sparse. This is an important caveat because recent analyses of the few existing historical datasets suggest that larger bodied organisms (both fish and benthos) were more prevalent prior to intensive bottom trawling (Greenstreet & Hall 1996; Frid & Clark 1999; Veale et al. in press). Moreover, in general, epifaunal organisms are less prevalent in areas subjected to intensive bottom fishing (Collie et al. 1997; Sainsbury et al. 1997; Thrush et al. 1998; Veale et al. in press). An important consequence of this effect is the reduction in habitat complexity (architecture) that accompanies the removal of sessile epifauna, which appears to have important consequences for fish communities (see, for example, Sainsbury et al. 1997). Our current understanding of the functional role of many of the larger-bodied long-lived species (e.g. as habitat features, bioturbators, etc.) is limited and should be addressed to predict the outcome of permitting chronic fishing disturbance in areas where these animals occur.
While short-term, site-specific fishing impact studies have yielded useful quantitative data, there is clearly a need for continued synthesis. More studies are needed, particularly of recovery dynamics from comparative studies that examine the large-scale effects of fishing disturbance at intensities imposed by commercial fleets (e.g. Collie et al. 1997). There is also a paucity of quantitative studies undertaken in deeper water (> 100 m), or in stable and structurally complex habitats for which the recovery trajectory will be measured in years.
With respect to the design of future studies, we feel that experimentalists wishing to address the fishing impacts issue will be best served by abandoning short-term, small-scale pulse experiments (sensuBender et al. 1984). Instead, the scientific community should be arguing for support to undertake much larger scale press and relaxation experiments. One half of the experiment has already been done—since fishing activity has been providing the press for many years, what we now require are carefully designed closed area contrasts. There are two principal advantages to this approach. First, the results obtained are clearly interpretable in terms of real world intensities of fishing disturbance. Secondly, the spatial scale of the protected areas can probably be relatively small (and hence replicated to fulfil the requirements for sound experimental design) without compromising unduly the interpretation of recovery dynamics: estimates of recovery in small protected areas in a sea of disturbance are likely to be conservative, while recovery in small deliberately disturbed patches are not. Thirdly, the experiments would be conducted in the very habitats (i.e. real fishing grounds) about which the question of recovery is actually being posed.