ICES CM 2001/ T:13 Use and Information Content of Ecosystem Metrics and Reference Points Dynamic ecosystem models and the evaluation of ecosystem effects of fishing: can we make meaningful predictions? L. A. ROBINSON and C.L.J. FRID Dove Marine Laboratory, Department of Marine Sciences & Coastal Management, University of Newcastle upon Tyne, Cullercoats, North Shields. NE30 4PZ. U.K. ABSTRACT The effects of fishing on marine ecosystems are probably the most widespread anthropogenic influence. The introduction of ecosystem considerations into fisheries management requires a knowledge of the relative scale of the various fisheries effects, development of suitable metrics of these and consideration of suitable limit values (reference points) for them. This will involve the application of suitable models. The direct and indirect effects of fishing on marine ecosystems are catalogued. We then identify 31 applications of models of marine ecosystems that might provide useful insights into the ecological effects of fisheries. Analysis was possible for only 22 of the models due to poor documentation of the other 9. These however included representatives of 7 generic model types. No model formulation provided coverage in all the areas necessary to cover the identified effects of fisheries. Eight models provided good coverage – nutrient dynamics and benthos were the least well represented aspects of the ecosystem. The ECOPATH with Ecosim family of models, the European Regional Seas Ecosystem Model (ERSEM) and the Anderson & Ursin multispecies extension to the Beverton & Holt model all seem likely to yield good insights. In developing these models consideration must be given to explicitly incorporate spatial factors and extrinsic forcing functions, such as climate. KEY WORDS: fishing impacts; ecosystem, models, predictions INTRODUCTION In recent times it has become necessary to find measurable metrics of the impacts of fisheries on the whole ecosystem (ICES, 1998; Frid et al., 1999; Hall, 1999a & b; ICES, 2000). This ecosystem approach has in part been driven by the need to uphold the key provisions of the convention agreed at 1 the UN Rio summit, which include conservation of biological diversity and sustainable use of the biosphere (Tasker et al., 2000). It is perhaps this urgency that has prompted the inclusion of an entire session on ‘Ecosystem and Environmental Management’ at this years’ ICES ASC. The scientific community has accepted that a holistic approach to understanding ecosystem effects is appropriate, but in many cases, particularly when considering fisheries effects, the focus is still restricted to an incomplete section of the whole system. Marine ecosystems are influenced by fishing activities at all levels and in a variety of ways (for reviews see Gislason, 1994; Dayton et al., 1995; Hall, 1999b; Gislason et al., 2000). These include: I. direct removal of target species II. direct changes in size structure of target populations III. alteration in non-target populations of fish and benthos (Rumohr and Krost, 1991; Camphuysen et al., 1995; Tuck et al., 1998) IV. alteration of the physical environment (Churchill, 1989; Messieh, 1991; Riemann and Hoffmann, 1991; Auster et al., 1995; Schwinghamer et al., 1996; Collie et al., 1997). V. alterations in the chemical environment, including nutrient availability (ICES, 1998). VI. trophic cascades (Carpenter et al., 1985) and altered predation pressure (Stevens et al., 2000; Frid et al., 1999). To offer an insight at the whole system level any tool should provide a good representation of all ecosystem components that can be impacted by fishing, whether the impacts are direct or indirect. It is evident that changes occur across the full spectrum of trophic levels, ranging from the phytoplankton through altered nutrient fluxes, to the top-predators by provisioning or direct mortality and altered food resources (Kaiser and de Groot, 2000; Stevens et al., 2000; Tasker et al., 2000). These ecological effects also extend over multi-decadal time scales (Frid and Clark, 2000) and operate at spatial scales ranging from processes within the trawl tracks (Kaiser and Spencer, 1994) to changes at the scale of the coastal sea (Hall, 1999b; Frid et al., 2000). 2 It is the large spatial and temporal scales of fishing activities in addition to the great number of potential indirect effects that makes the application of classical experimental approaches untenable (Dayton et al., 1995; Underwood, 1996; Dayton, 1998). Instead research has been directed towards community metrics that give a measurable and easily communicable understanding of the ‘health’ or ‘state’ of the ecosystem following fishery disturbance. It is desirable that these metrics have ‘target’ and ‘limit’ reference points, as have been used in single species management, as the outcomes can then be easily translated directly to frame management measures. ICES has long been involved in the management of single components of the ecosystem, such as the target fish stocks. Spawning stock biomass (SSB) is one example of such a measure, and it is set at a minimum acceptable level as a limit reference point. In theory, it should be possible to apply reference points to any, or all, taxa in the ecosystem. ICES (2000) have however contended that even if this were practical for a significant number of taxa, it may not ensure adequate protection of all the ecosystem components at risk. There is a need therefore to develop reference points for system level emergent properties as a measure of ecosystem health (Hall, 1999b; Gislason et al., 2000). The utilization of sound ecological models as a tool in the exploration and evaluation of ecosystem ‘health’ and ‘state’, has been encouraged and endorsed by the leading bodies in ecosystem-based fisheries research and management (NRC, 1999; ICES, 1999). Dynamic ecosystem models provide an opportunity to make advances in this area, as they can both evaluate the state of the system and also make predictions about the ecosystem under various fishing scenarios. Further they allow an examination of the behaviour of possible metrics such as a change in energy flow or average trophic level, both of which can be easily translated into understandable reference points. Through systems modelling it should be possible to gain an understanding of the indirect (higher order) effects and to develop metrics of the ecosystem 3 which could form the basis for precautionary management. The potential of the available dynamic ecosystem models, to make measurable and meaningful predictions about the effects of fishing on ecosystems, has not however been fully assessed. Although over the last two decades there has been considerable growth in the use of multispecies models to answer fisheries questions, there are problems associated with their use in the development of theory and predictions concerning ecosystem effects. Too often they are still restricted to a subset of the complete ecosystem and data is often aggregated over functionally different species or age groups (Hollowed et al., 2000). Yodzis (2001) has highlighted the problems associated with the over- simplification of marine ecosystems in modelling. When considering competition between a fishery and a top predator for example, a simple model would predict that with the removal (cull) of the top predator, prey release would lead to an increase in the target fish stocks, therefore benefiting the fishery. If however one were to add a fish predator that competed with the top predator for the target species, but was also eaten by the top predator, a cull would lead to a lag increase in the fish predator and therefore ultimately a further decline in the target fish stock. This example illustrates the complexity of the issues when trying to make meaningful predictions about complex ecosystems. In order to resolve the problems surrounding the potential use of dynamic ecosystem models for the evaluation of ecosystem effects of fishing, the inherent mismatch between the wide spectrum of impacts and the narrow outlook of the majority of ecosystem models must be addressed. In this paper we set out to; I. Provide a succinct summary of the proposed ecosystem level effects arising from fishing activities – this includes the direct and indirect effects but for now we restrict our analyses to effects at the species and ecosystem levels. 4 II. Review the applications of dynamic ecosystem models currently available (and documented in the scientific literature) for coastal marine ecosystems. In particular we consider the extent to which various components of the ecosystem are represented and their ability to respond to extrinsic drivers i.e. climatic variation. III. Based on (I) and (II) we examine the available models for their ability to generate quantitative, testable, predictions about the response of the ecosystem to fishing effects. Ultimately these models will be the ones that may provide a basis for the consideration of ecosystem properties that might form useful metrics of ecosystem health and so become the basis for ecosystem reference points. 5 Table 1: Direct and indirect impacts of fishing on ecosystems Impact Direct effect Indirect effect References Removal of • Mortality of target • Changes in trophic Anderson & target species species and other fish interactions such as Ursin, 1977; and incidental and invertebrate predator-prey dynamics, Carpenter et al., catch species incidental to trophic cascades 1985; Hall,1999b catch • Altered life history • Prey decreases for