| Abstract: | Wildlife practitioners concerned with midcontinent mallard (Anas platyrhynchos) management in the United States have instituted a system of adaptive harvest management (AHM) as an objective format for setting harvest regulations. Under the AHM paradigm, predictions from a set of models that reflect key uncertainties about processes underlying population dynamics are used in coordination with optimization software to determine an optimal set of harvest decisions. Managers use comparisons of the predictive abilities of these models to gauge the relative truth of different hypotheses about density-dependent recruitment and survival, with better-predicting models giving more weight to the determination of harvest regulations. We tested the effectiveness of this strategy by examining convergence rates of ‘predictor‘ models when the true model for population dynamics was known a priori. We generated time series for cases when the a priori model was 1 of the predictor models as well as for several cases when the a priori model was not in the model set. We further examined the addition of different levels of uncertainty into the variance structure of predictor models, reflecting different levels of confidence about estimated parameters. We showed that in certain situations, the model-selection process favors a predictor model that incorporates the hypotheses of additive harvest mortality and weakly density-dependent recruitment, even when the model is not used to generate data. Higher levels of predictor model variance led to decreased rates of convergence to the model that generated the data, but model weight trajectories were in general more stable. We suggest that predictive models should incorporate all sources of uncertainty about estimated parameters, that the variance structure should be similar for all predictor models, and that models with different functional forms for population dynamics should be considered for inclusion in predictor model! sets. All of these suggestions should help lower the probability of erroneous learning in mallard ABM and adaptive management in general. |
| Genre: | Article |
| ProdID: | 5224404 |
| Citation Author: | Conn, P.B.; Kendall, W.L. |
| Citation Contributing Office: | Patuxent Wildlife Research Center |
| Citation Datum: | |
| Citation Day: | |
| Citation Edition: | |
| Citation Editor: | |
| Citation End Page: | 1081 |
| Citation Issue: | 4 |
| Citation Keywords: | |
| Citation Language: | English |
| Citation Larger Work Title: | Journal of Wildlife Management |
| Citation LatN: | |
| Citation LatS: | |
| Citation LonE: | |
| Citation LonW: | |
| Citation Month: | |
| Citation No Pagination: | |
| Citation Number Of Pages: | 17 |
| Citation Online Only Flag: | |
| Citation Phsyical Description: | 1065-1081 |
| Citation Projection: | |
| Citation Public Comments: | 6286_Conn.pdf |
| Citation Publisher: | |
| Citation Series: | |
| Citation Series Code: | |
| Citation Series Number: | |
| Citation Search Results Text: | Evaluating mallard adaptive management models with time series; 2004; Article; Journal; Journal of Wildlife Management; Conn, P.B.; Kendall, W.L. |
| Citation Start Page: | 1065 |
| Citation Volume: | 68 |
| Citation Year: | 2004 |
| Type: | citation/reference |
| Text: | Evaluating mallard adaptive management models with time series; 2004; Article; Journal; Journal of Wildlife Management; Conn, P.B.; Kendall, W.L. |
| URL (THUMBNAIL): | http://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg |
| URL (DOCUMENT): | http://www.bioone.org/perlserv/?request=get-abstract&doi=10.1670%2F125-04N ; http://www.jstor.org/stable/3803662 |
| Date Other: | Wed, 16 Jun 2010 12:18 -0500 |
| Publisher: | |
