The effects of regional angling effort, angler behavior, and harvesting efficiency on landscape patterns of overfishing


  • Len M. Hunt,

    Corresponding author
    1. Centre for Northern Forest Ecosystem Research, Ontario Ministry of Natural Resources, Thunder Bay, Ontario P7B 5E1 Canada
    Search for more papers by this author
  • Robert Arlinghaus,

    1. Department of Biology and Ecology of Fishes, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany
    2. Inland Fisheries Management Laboratory, Department for Crop and Animal Sciences, Faculty of Agriculture and Horticulture, Humboldt-University of Berlin, Berlin, Germany
    Search for more papers by this author
  • Nigel Lester,

    1. Aquatic Research and Development Section, Ontario Ministry of Natural Resources, Peterborough, Ontario K9J 7B8 Canada
    Search for more papers by this author
  • Rob Kushneriuk

    1. Centre for Northern Forest Ecosystem Research, Ontario Ministry of Natural Resources, Thunder Bay, Ontario P7B 5E1 Canada
    Search for more papers by this author

  • Corresponding Editor (ad hoc): J. R. Post.


We used a coupled social-ecological model to study the landscape-scale patterns emerging from a mobile population of anglers exploiting a spatially structured walleye (Sander vitreus) fishery. We systematically examined how variations in angler behaviors (i.e., relative importance of walleye catch rate in guiding fishing site choices), harvesting efficiency (as implied by varying degrees of inverse density-dependent catchability of walleye), and angler population size affected the depletion of walleye stocks across 157 lakes located near Thunder Bay (Ontario, Canada). Walleye production biology was calibrated using lake-specific morphometric and edaphic features, and angler fishing site choices were modeled using an empirically grounded multi-attribute utility function. We found support for the hypothesis of sequential collapses of walleye stocks across the landscape in inverse proportionality of travel cost from the urban residence of anglers. This pattern was less pronounced when the regional angler population was low, density-dependent catchability was absent or low, and angler choices of lakes in the landscape were strongly determined by catch rather than non-catch-related attributes. Thus, our study revealed a systematic pattern of high catch importance reducing overfishing potential at low and aggravating overfishing potential at high angler population sizes. The analyses also suggested that density-dependent catchability might have more serious consequences for regional overfishing states than variations in angler behavior. We found little support for the hypotheses of systematic overexploitation of the most productive walleye stocks and homogenized catch-related qualities among lakes sharing similar access costs to anglers. Therefore, one should not expect anglers to systematically exploit the most productive fisheries or to equalize catch rates among lakes through their mobility and other behaviors. This study underscores that understanding landscape overfishing dynamics involves a careful appreciation of angler population size and how it interacts with the attributes that drive angler behaviors and depensatory mechanisms such as inverse density-dependent catchability. Only when all of these ingredients are considered and understood can one derive reasonably predictable patterns of overfishing in the landscape. These patterns range from self-regulating systems with low levels of regional fishing pressure to sequential collapse of walleye fisheries from the origin of angling effort.