Population control based on abundance estimates: Frequency does not compensate for uncertainty |
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| Affiliation: | 1. Leibniz Institute for Zoo and Wildlife Research IZW, Department of Evolutionary Ecology, Alfred Kowalke-Str. 17, 10315 Berlin, Germany;2. Freiburg University, Chair of Wildlife Ecology and Management,Tennenbacherstr. 4, 79106 Freiburg, Germany;3. University of Koblenz-Landau, Institute for Environmental Sciences, Fortstr. 7, 76829 Landau, Germany;4. Bavarian Forest National Park, Freyunger Str. 2, 94481 Grafenau, Germany;1. Instituto Murciano de Investigación y Desarrollo Agrario y Alimentario, Estación de Acuicultura Marina, Puerto de San Pedro del Pinatar, 30740, Murcia, Spain;2. MENDIJOB S.L, C/. Rambla 22, El Palmar, 30120, Murcia, Spain;1. Animal Ecology, Department of Ecology and Genetics, Uppsala University, Uppsala, Sweden;2. Department of Life Sciences, University of Trieste, Trieste, Italy;3. Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden;1. ECT Oekotoxikologie GmbH, Böttgerstrasse 2-14, 65439 Flörsheim, Germany;2. Fraunhofer Institute for Ceramic Technologies and Systems, Winterbergstrasse 28, 01277 Dresden, Germany;3. Dresden University of Technology, Budapesterstrasse 27, 01069 Dresden, Germany;4. Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden;5. Institute for Environmental Sciences, University of Koblenz-Landau, Forststrasse 7, 76829 Landau, Germany |
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| Abstract: | For decision making processes related to a sustainable harvest, two aspects are of fundamental importance: first, the insufficient accuracy of abundance estimates and second, the fact that an increased mortality will not necessarily decrease the population size. To optimise decision making, we investigated how uncertainty, namely incomplete information and inadequate understanding about the conditions and the relationships between system components, affect the feasibility of population control. To this end, we developed an age-structured population model for roe deer, one of the most common ungulates in Europe. The model simulates hunting processes that are affected by uncertainties related to abundance estimates and species demography. The results indicated that uncertainty related to abundance estimates largely reduced the ability to achieve target population densities. Surprisingly, this effect was not weakened by more frequent estimations. We conclude that decreasing the interval of abundance estimates counterintuitively cannot compensate for lacking accuracy. This novel aspect should therefore be considered in the management of dynamic ecological systems. |
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| Keywords: | Decision making Population simulation model Abundance estimates Uncertainty Monitoring |
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