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Indicator summary
Summary of indicator structure and function (or another title??)
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| Indicator examples | Current status and trends | Management objective/direction | Stakeholder/Public acceptability |
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| Examples of how the indicator is used. | Pick one of the following:
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| George Bank | increasing exploitation of the groundfish fishery | ||
| no-fish area of Tasmania | tenfold increase in biomass of rock lobsters (Janus edwardsii) after a six year period of closure | ||
Definition and/or background
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Various ways of treating biomass data can be used by researchers in investigating impacts of fishing on community structure. Aside from using simple measures (e.g. biomass expressed as mean percent change by weight for aggregated species or individuals of species over time), examples of more specific treatments give insight into how measures of biomass may be used as potential indicators. In field studies, trends in biomass can give some indication of the health of the system. For example, when biomass of one or more important species or assemblages falls below a defined minimum acceptable limit for successful recruitment, recovery time, or for a species threatened with extinction, the ecosystem can be regarded as overfished (Murawski 2000). Measures of biomass are also used in a wide range of ecological models. For example, to measure dominance changes over time of a keystone species (sea urchin), McClanahan (1995) used biomass in an energy-based coral reef simulation model (Figure 5.31) to examine the impact of fishing on community structure. The model indicated that the intensity and selectivity of fishing can affect reef structure and processes, as the abundance and interactions of the coral and algae are controlled by the herbivores, which are in turn controlled by carnivores (often the targets of fishing). The changes in system state predicted by the model are obvious in the biomass trends it predicts, an example of which is given in Figure 51.3.
In traditional single species management measures of biomass (frequently trends over time in biomass / pristine biomass) have been used to judge the health of the stock, and thus the fishery. Thus, measures in biomass can be informative at a population level, but by extending the number of species tracked or choosing species carefully (e.g. using keystone or vulnerable species) more system-level information maybe encapsulated in these simple measures.
Figure 5.31: The model output of biomass (wet weight) when all fish components are fished after 39 years of simulation. It shows the response of the coral ecosystem to overfishing, in particular, the increased biomass of sea urchins, which are keystone species in this system (after McClanahan 1995). (Figure provided by Fulton et al 2004a).
Abundance of keystone species
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The biomass of certain groups can also be used to consider aspects of the system such as community composition. Predator-prey responses to fishing impacts can provide important and potentially robust indicators of biomass changes in an ecosystem. This is true not only of field data, but also of the output of simulation models. There have been numerous simulation modelling studies recently investigating the impacts of removing key predators from an ecosystem (e.g. for chondrichthyans, Stevens et al. 2000), the over-harvesting of prey species on seabird species (Furness 1999), and the over-harvesting of prey species in Port Phillip Bay, Victoria (Fulton and Smith in press). An example of the time-series output of these kinds of models is given in Figure 52.4.
Figure 5.42: ECOSIM simulation of the functional response to an aggressive sand lance fishery showing biomass declines in seabirds (which prey on sand lance) and other species (after Okey and Pauly 1999). (Figure provided by Fulton et al 2004a).
Attribute
Community structure; trophic structure; population structure; predator-prey balance
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Should be suitable for all ecosystems. For certain species of interest the method may be more restricted. For example, the use of the biomass of keystone species will only be applicable in ecosystems where there is a keystone species that determines system state. Unfortunately, the existence of such a species may not be apparent before large-scale changes in an ecosystem have already occurred.
Identified capability
Is there any additional information that would be of interest in regards to the identified capability?
Otherwise can leave this section blank and just fill in the table instead.
Biological classification level
Is there any additional information that would be of interest in regards to the biological classification?
Otherwise can leave this section blank and just fill in the table instead.
Response variable
Is there any additional information that would be of interest in regards to the response variable?
Otherwise can leave this section blank and just fill in the table instead.
Drivers
Is there any additional information that would be of interest in regards to ecological drivers?
If not can leave this section blank and just fill in the table instead.
Robustness
The following is from Fulton et al 2004a -
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Stevens et al. (2000) is a good example of the methodology. They used ECOSIM to model the impacts of removing shark predators by fishing over a 100-year period in 3 ecosystems of differing latitudes and regimes (Alaskan Gyre, Venezuela and Pacific-Hawaii). The outputs of the model provide a very preliminary indication of the sorts of changes that could be expected to occur with the removal of trophically important top predators like sharks. The output was also dependent on the ecosystem type and the results differed widely between tropical Pacific ecosystems and boreal systems. The results indicate that for boreal systems (Alaskan Gyre), there the removal of top predators (sharks) would result in a rapid increase to a peak in the biomass of many of the shark’s main prey species after about 15-20 years from the onset of the removal of sharks. This is then followed by a slow, sustained decline back to baseline values (taking about 80 years) for these groups, though a few declined still further (e.g. the “large fish” ends the 100 year period at 50% of its initial biomass, despite booming soon after the intensive fishing of sharks begins). In contrast, on the Venezuelan shelf there were strong and persistent changes (up to 2.5x original biomass) in relative abundance of many species, some of which were only minor components of the diet of sharks. More surprisingly, two groups that are not preyed upon by sharks also showed substantial changes after the removal of sharks began, squid and benthic producers fell by about 10% and 15% respectively. All of these results for the Venezuelan shelf suggest that shark depletion propagates through the food chain in a complex way. The results for the coastal Hawaiian coral reef system were different again. There was a counterintuitive total and rapid crash in the abundance of tuna and jacks (possibly triggered by a twofold increase in abundance of the seabirds, which are their main predators), whereas the other species preyed up on by sharks all increased in abundance.
Management strategies and/or objectives
define a standard set of management objectives?? ie from Indiseas
- Conservations biodiversity
- Ecosystem stability and resistance to perturbations
- ecosystem structure and functioning
- resource potential
has it been used in a management strategy? if so how?
relationship to management strategies/ objectives
Stakeholder/public acceptability
Acceptability with stakeholders
- by all stakeholder
- by the public
- understandable to the stakeholders
Associated links
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.
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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.
Possible references for updating this indicator
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