Ecopath with Ecosim: methods, capabilities and limitations

https://doi.org/10.1016/j.ecolmodel.2003.09.003Get rights and content

Abstract

The Ecopath with Ecosim (EwE) modeling approach combines software for ecosystem trophic mass balance analysis (Ecopath), with a dynamic modeling capability (Ecosim) for exploring past and future impacts of fishing and environmental disturbances as well as for exploring optimal fishing policies. Ecosim models can be replicated over a spatial map grid (Ecospace) to allow exploration of policies such as marine protected areas, while accounting for spatial dispersal/advection effects.

The Ecopath approach and software has been under development for two decades, with Ecosim emerging in 1995, and Ecospace in 1998, leading to an integrated and widely applied package. We present an overview of the computational aspects of the Ecopath, Ecosim and Ecospace modules as they are implemented in the most recent software version. The paper summarizes the capabilities of the modeling system with respect to evaluating how fisheries and the environment impact ecosystems. We conclude by a warning about pitfalls in the use of the software for policy exploration.

Introduction

The modeling approach ‘Ecopath with Ecosim’ (EwE, http://www.ecopath.org) is being widely used as a tool for analysis of exploited aquatic ecosystems, having reached 2400 registered users in 120 countries, and leading to in excess of 150 publications. EwE combines software for ecosystem trophic mass balance (biomass and flow) analysis (Ecopath) with a dynamic modeling capability (Ecosim) for exploring past and future impacts of fishing and environmental disturbances. It has an elaborate user interface that eases a variety of data management chores and calculations that are a cumbersome but necessary part of any endeavor to systematically examine an ecosystem, its resources, and their interactions and exploitation.

Recent versions of the software have brought Ecosim much closer to traditional single-species stock assessment, by allowing age-structured representation of particular, important populations and by allowing users to ‘fit’ the model to data. Ecosim models can be replicated over a spatial map grid (Ecospace) to allow exploration of policies such as marine protected areas, while accounting for spatial dispersal/advection effects and migration.

The Ecopath approach was initiated by Polovina (1984) in the early 1980s, and has been under continuous development since 1990 (Christensen and Pauly, 1992), with Ecosim emerging in 1995 (Walters et al., 1997, Walters et al., 2000), and Ecospace in 1998 (Walters et al., 1999), leading to an integrated software package, ‘Ecopath with Ecosim’. We give an overview of the computational aspects and capabilities of the Ecopath, Ecosim and Ecospace modules as they are implemented in the most recent software version (EwE Version 5), along with some reflections of potential pitfalls related to application of the software.

Section snippets

Mass-balance modeling: Ecopath

The core routine of Ecopath is derived from the Ecopath program of Polovina (1984), and since modified to make superfluous its original assumption of steady state. Ecopath instead bases the parameterization on an assumption of mass balance over a given time period (usually 1 year, but see discussion below about seasonal modeling). In its present implementation Ecopath parameterizes models based on two master equations, one to describe the production term (Eq. (1)), and one for the energy

Time-dynamic simulation: Ecosim

The basics of Ecosim are described in detail by Walters et al., 1997, Walters et al., 2000, and will only be given a cursory treatment here, omitting details that have been previously published, focusing instead in describing more recent additions to the modeling approach. In overview, Ecosim consists of biomass dynamics expressed through a series of coupled differential equations. The equations are derived from the Ecopath master Eq. (1), and take the formdBidt=gijQjijQij+Ii−(M0i+Fi+ei)×Bi

Spatial simulation: Ecospace

Ecospace is a dynamic, spatial version of Ecopath, incorporating all key elements of Ecosim and is described in detail by Walters et al. (1999). It works by dynamically allocating biomass across a user-defined grid map while accounting for:

  • 1.

    symmetrical movements from a cell to its four adjacent cells modified by whether a cell is defined as ‘preferred habitat’ or not;

  • 2.

    user-defined increased predation risk and reduced feeding rate in non-preferred habitat; and

  • 3.

    a level of fishing effort that is

Capabilities and limitations

EwE has been developed largely through case studies, where users have challenged us to add various capabilities and as we have seen inadequacies through comparison to data; see as a good example the discussions in the proceedings from two recent FAO/UBC workshops on the application of EwE (Pauly and Weingartner, 1998, Pitcher and Cochrane, 2002). Various capabilities have been added to EwE in response to these challenges, and there has inevitably been some uncertainty about what the approach

Major pitfalls in the application of EwE

EwE can produce misleading predictions about even the direction of impacts of policy proposals. Erroneous predictions usually result from bad estimates or errors of omission for a few key parameters, rather than ‘diffuse’ effects of uncertainties in all the input information. We warn EwE users to be particularly careful about the following problems that we have seen in various case studies.

Acknowledgements

We thank the Pew Charitable Trust for funding the ‘Sea Around Us’ project at the Fisheries Centre, University of British Columbia, making the further development of the Ecopath with Ecosim approach and software possible. Villy Christensen also acknowledges support from the European Union INCO-DC Concerted Action ERBIC18CT97175, while Carl Walters acknowledges support from Canada’s National Scientific and Engineering Research Council. The paper has benefited from discussions with and comments by

References (52)

  • Fletcher, R., 1987. Practical Methods of Optimization. Wiley/Interscience, New...
  • Froese, R., Pauly, D. (Eds.), 2000. FishBase 2000: concepts, design and data sources. ICLARM [Distributed with 4...
  • Funtowicz, S.O., Ravetz, J.R., 1990. Uncertainty and Quality in Science for Policy. Kluwer Academic Publishers,...
  • R Hilborn et al.

    A general model for simulation of stock and fleet dynamics in spatially heterogeneous fisheries

    Can. J. Fish. Aquat. Sci.

    (1987)
  • Hilborn, R., Walters, C.J., 1992. Quantitative Fisheries Stock Assessment: Choice, Dynamics and Uncertainty. Chapman...
  • Kavanagh, P., Newlands, N., Christensen, V., Pauly, D., 2004 Automated parameter optimization for Ecopath ecosystem...
  • Leontief, W.W., 1951. The Structure of the U.S. Economy. Oxford University Press, New...
  • M Liermann et al.

    Depensation in fish stocks: a hierarchic Bayesian meta-analysis

    Can. J. Fish. Aquat. Sci.

    (1997)
  • D Ludwig et al.

    Uncertainty, resource exploitation, and conservation: lessons from history

    Science

    (1993)
  • Mackay, A., 1981. The generalized inverse. Pract. Comput. (September),...
  • K.G Magnusson

    An overview of the multispecies VPA—theory and applications

    Rev. Fish Biol. Fish.

    (1995)
  • S Martell

    Incorporating seasonality into Ecopath

    FishBytes

    (1999)
  • Martell, S.J.D., Beattie, A.I., Walters, C.J., Nayar, T., Briese, R., 2002. Simulating fisheries management strategies...
  • M.K McAllister et al.

    A Bayesian approach to stock assessment and harvest decisions using the sampling/importance resampling algorithm

    Can. J. Fish. Aquat. Sci.

    (1994)
  • More, J.J., 1977. The Levenberg–Marquardt algorithm: implementation and theory. In: Watson, G.A. (Ed.), Numerical...
  • R.A Myers et al.

    Population dynamics of exploited fish stocks at low population levels

    Science

    (1995)
  • Cited by (0)

    Manuscript PFITEC-2 (EMECS 9) for Ecological Modeling, May 2003.

    View full text