© 2004 Kluwer Academic Publishers. Printed in the Netherlands. Dealing with uncertainty in spatially explicit population models
Abstract. It has been argued that spatially explicit population models (SEPMs) cannot provide reliable guidance for conservation biology because of the difficulty of obtaining direct esti-mates for their demographic and dispersal parameters and because of error propagation. We argue that appropriate...
| Main Authors: | , , |
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| Format: | Text |
| Language: | English |
| Published: |
2002
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| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.516.2758 http://www.oesa.ufz.de/towi/pdf/WiegandEtAl2004_Uncertainty.pdf |
| Summary: | Abstract. It has been argued that spatially explicit population models (SEPMs) cannot provide reliable guidance for conservation biology because of the difficulty of obtaining direct esti-mates for their demographic and dispersal parameters and because of error propagation. We argue that appropriate model calibration procedures can access additional sources of informa-tion, compensating the lack of direct parameter estimates. Our objective is to show how model calibration using population-level data can facilitate the construction of SEPMs that produce reliable predictions for conservation even when direct parameter estimates are inadequate. We constructed a spatially explicit and individual-based population model for the dynamics of brown bears (Ursus arctos) after a reintroduction program in Austria. To calibrate the model we developed a procedure that compared the simulated population dynamics with distinct fea-tures of the known population dynamics (=patterns). This procedure detected model param-eterizations that did not reproduce the known dynamics. Global sensitivity analysis of the uncalibrated model revealed high uncertainty in most model predictions due to large parameter uncertainties (coefficients of variation CV ≈ 0.8). However, the calibrated model yielded pre-dictions with considerably reduced uncertainty (CV ≈ 0.2). A pattern or a combination of |
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