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Indicator summary

 Summary of indicator structure and function

Definition and/or background

The following is from Fulton et al 2004a -

Size-spectra is a community property that can be effectively measured by analysing the slope and intercepts of the size-spectra slope for fish assemblages, where the spectra are based on either biomass or numbers per size interval (Jennings et al. 2001). Wide ranging empirical studies have shown that this is usually a robust measure for detecting trends in overall size composition of a community that has been subject to fishing pressure (Rijnsdorp et al. 1996, Bianchi et al. 2000, Rice 2000), though it is not equally strong in all systems (Macpherson and Gordoa 1996, Bianchi et al. 2000). The biological basis for the sensitivity of the slope to changes in size composition resulting from fishing is that fishing selectively harvests larger individuals first, while simultaneously increasing the mortality rate for all sizes taken by fishing gear (Rice 2000). As a result, communities shift to smaller sized fish, and this occurs within and across species and therefore the intercept of the spectrum increases, as does the steepness of the slope of the spectrum. ... Moreover, it appears that there is a strong relationship between body size and trophic level, which means that size-spectra parameterised with these relationships could also describe the trophic structure of marine ecosystems (Jennings et al. 2002a, 2002b). This is a very important finding as size-based analyses can be far easier and cheaper to use and parameterise than explicit foodweb models. The primary disadvantages with the size-spectra approach is that the slope and intercept are not independent (so a time-series of either is difficult to interpret), the minimum size class included is often an arbitrary choice (ICES 2001A) and the size-spectra may actually be non-linear (Rochet and Trenkel 2003).

Non-linear size-spectra

As the linearity of size-spectra can be questioned some researchers (Duplisea and Kerr 1995, Duplisea et al. 1997, Trenkel and Rochet 2003) have tried a dome-shaped or trigonometric rather than a linear model to describe the size spectrum, as this allows for non-linearities. An application of the trigonometric size-spectra to the Celtic sea ecosystem has shown that this form of the indicator has potential. However, more theoretical and empirical work is required before it is known how reliable non-linear size-spectra are as indicators of the effects of fishing (Rochet and Trenkel 2003, Trenkel and Rochet 2003).

Attribute

Community structure, Trophic shifts and Predator-prey balance

Purpose

Fisheries

Data required

The following is from Fulton et al 2004a -

• Length frequency or weight frequency by spp. Note that weight-based size-spectra will differ from size-spectra constructed from length measurements (Bianchi et al. 2000) and there is less bias when using length-based data.
• Catch in numbers.
• Long time series.
• Baseline data on species composition and size structure from unfished reference communities - e.g. no-take marine reserves or areas recovering from fishing. Though if sufficiently long time series exist (ideally pre-dating fishing in the area) then that can be used (with caution) in place of baselines from unfished areas.

Ecosystem applicability

The following is from Fulton et al 2004a -

Should be applicable to all systems.

Robustness

The following is from Fulton et al 2004a -

High potential: It has been demonstrated as most effective for detecting changes in fish assemblages in temperate regions. However the usefulness of size spectrum analysis is limited where there is inadequate empirical and theoretical ecological or baseline data (e.g. from reference areas) for interpreting observed values of slopes and intercepts of the regression analysis. As with many indicators of system or community change, this method will detect changes that are not due to the effects of fishing (e.g. increasing nutrients can increase system productivity, which will increase the intercept of size-spectra of that system), therefore reference points or background knowledge of the system is crucial. Moreover, high latitude areas produced more conclusive size-spectra results, probably because of the slower growth rates of the fish relative to tropical species. It is recommended that size-spectra analysis be used in conjunction with substrate/sediment indicators for examining community structure.

Current status and trends

The following is from Fulton et al 2004a -

In studies to test the sensitivity of size-spectra analysis to community change, Bianchi et al. (2000) analysed community level data sets of bony fish and elasmobranch bycatch from a range of marine ecosystems (from tropical to temperate), and found that the slope of the size-spectra responded consistently to different exploitation levels and showed a decreasing trend (i.e. decline in larger fish) in communities subject to overfishing. Results were more robust for temperate regions and less conclusive for tropical regions. This is possibly due to less consistent time series data in tropical areas, but may also be due to higher growth rates of tropical fish making the slope less sensitive to fishing induced changes. In a recent evaluation of metrics of community structure for evaluating fishery impacts, Rice (2000) concluded that the slope and intercept of the size spectrum are useful measures to use as indicators for impacts of fishing on fish assemblages.

Background knowledge

Beyond these explicit analyses of the approach, there are many examples of shifts in community size structure that support the principle underlying the use of size-spectra analysis to detect the effects of fishing. For example, in shelf habitats off north-western Australia the fish community changed over an 11 yr period from larger ambush predators (Lutjanus and Lethrinus), which inhabit structurally complex habitats dominated by large epibenthic fauna such as sponges, to smaller fish typical of open habitats (Saurida and Nemipterus). A model relating the fish species abundance to habitat structure showed that this change was most likely due to destruction of large epibenthic sponges, alcyonarians and gorgonians by trawl gear that provided cover, shelter and food for the displaced species (Sainsbury et al. 1997). Another example can be found on Georges Banks in the North Atlantic, there the fish community structure changed from gadoids and flounders to small elasmobranchs (dogfish and skates). This shift in community structure appears to be the result of indirect effects of reducing the abundance of the gadoids and flounders. Removal of these species reduced competition for the replacement species and impacted on foraging by seabirds and mammals, which had previously utilised the gadoid and flounder as prey.

Size-spectra changes in no-take areas may provide important reference points

The average and maximum sizes of large fish species and invertebrates have been shown to increase significantly inside no-take marine reserves after closure to fishing in sub-tidal temperate reefs, Tasmania, Australia (Edgar and Barrett 1999) and temperate kelp communities in California (Paddack and Estes 2000). Size-spectra analysis of data generated for fish community assemblages in these studies may produce useful reference points for interpreting the status of similar communities in fished areas. For example, in the long-term monitoring of Maria Island Marine Reserve (eastern Tasmania, Australia) a shift in size-structure was recorded for two ‘indicator species’ of the sub-tidal reef community there. Over a 6-year period commencing when the reserve was closed to fishing, the mean size of blue-throated wrasse (Notolabrus tetricus) and black lipped abalone (Haliotis rubra) both increased significantly in comparison to locations outside the reserve. Increases in abundances and densities of large fish, invertebrate and algal species also occurred in the reserve, exemplifying the importance of such reference areas for developing robust indicators (Edgar and Barrett 1999).

References

Fulton, E.A., Smith, A.D.M., Webb, H., and Slater, J. (2004a) Ecological indicators for the impacts of fishing on non-target species, communities and ecosystems: Review of potential indicators. AFMA Final Research Report, report Number R99/1546.

References that Fulton et al uses for this indicator:

Bianchi, G., H. Gislason, K. Graham, L. Hill, X. Jin, K. Koranteng, S. Manickchand-Heileman, I. Paya, K. J. Sainsbury, F. Sanchez, and K. Zwanenburg. 2000. Impact of fishing on size composition and diversity of demersal fish communities. ICES Journal of Marine Science 57: pp 558-71.

Duplisea, D. E., and S. R. Kerr. 1995. Application of a biomass size spectrum model to demersal fish data from the Scotian Shelf. Journal of Theoretical Biology 177: pp 263-69.

Duplisea, D. E., S. R. Kerr, and L. M. Dickie. 1997. Demersal fish biomass size spectra on the Scotian Shelf, Canada: species replacement at the shelfwide scale. Canadian Journal of Fisheries and Aquatic Sciences  54: pp 1725-35.

Edgar, G. J., and N. S. Barrett. 1999. Effects of the declaration of marine reserves on Tasmanian reef fishes, invertebrates and plants. Journal of Experimental Marine Biology and Ecology 242: pp 107-44.

ICES. 2001a. Report of the Working Group on Ecosystem Effects of Fishing Activities. International Council for the Exploration of the Seas, CM 2001/ACME: 09, 102pp.

Jennings, S., S.P.R. Greenstreet, L. Hill, G.J. Piet, J.K. Pinnegar, K.J. Warr. 2002. Long-term trends in the trophic structure of the North Sea fish community: evidence from stable-isotope analysis, size-spectra and community metrics. Marine Biology 141: 1085-1097.

Jennings, S., M.J. Kaiser, and J.D. Reynolds. 2001.  Marine fisheries ecology.,. 417 p . London: Blackwell Science.

Jennings, S., K.J. Warr, and S. Mackinson, 2002b. Use of size-based production and stable isotope analyses to predict trophic transfer efficiencies and predator-prey body mass ratios in food webs. Marine ecology progress series, 240: 11 – 20.

Macpherson, E., and A. Gordoa. 1996. Biomass spectra in benthic fish assemblages in the Benguela system. Marine Ecology Progress Series 138: pp 27-32.

Paddack, M. J., and J. A. Estes. 2000. Kelp forest fish populations in marine reserves and adjacent exploited areas of central California. Ecological Applications 10, no. 3: pp 855-70.

Rice, J.C. 2000. Evaluating fishery impacts using metrics of community structure. ICES Journal of Marine Science 57: pp 682-88.

Rijnsdorp, A. D., P. I. Van Leeuwen, N. Daan, and H. J. L. Heessen. 1996. Changes in abundance of demersal fish species in the North Sea between 1906-1909 and 1990-1995. ICES Journal of Marine Science 53: pp 105401062.

Rochet, M.-J., and V. M. Trenkel. 2003. Which community indicators can measure the impact of fishing? a review and proposals. Canadian Journal of Fisheries and Aquatic Science 60: pp 86-99.

Sainsbury, K.J., R. A.Campbell , R. Lindholm and A.W. Whitelaw 1997. Experimental management of an Australian multispecies fishery: examining the possibility of trawl-induced habitat modification. In: Global Trends: Fisheries Management, Editor(s) E.K. Pikitch, D.D. Huppert, and M.P. Sissenwine, pp 107-112. American Fisheries Society: Bethesda, Maryland.

Trenkel, V.M., and M.-J. Rochet. 2003. Performance of indicators derived from abundance estimates for detecting the impact of fishing on a fish community. Canadian Journal of Fisheries and Aquatic Sciences 60: pp 67-85.

Background reading

Fulton, E.A., Fuller,M., Smith, A.D.M., and Punt, A. (2004) Ecological indicators of the ecosystem effects of fishing: Final report. AFMA Final Research Report, report Number R99/1546.

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