Incorporating ‘recruitment’ in matrix projection models : estimation, parameters, and the influence of model structure
MetadataShow full item record
Advances in the estimation of population parameters using encounter data from marked individuals have made it possible to include estimates of the probability of recruitment in population projection models. However, the projected growth rate of the population, and the sensitivity of projected growth to changes in recruitment, can vary significantly depending upon both the structural form of the model and how recruitment is parameterized. We show that the common practices of (1) collapsing some age classes into a single, terminal ‘aggregated’ age-class, and (2) parameterizing recruitment using the proportion of recruited individuals (breeders) in a given age-class may confound analysis of age-based (Leslie) matrix projection models in some instances, relative to state-based projection models where recruited and pre-recruited individuals are treated as separate states. Failing to account for these differences can lead to misinterpretation of the relative role of recruitment in the dynamics of an age-structured population.We show that such problems can be avoided, either by structural changes to the terminal aggregated age-class in age-based models, or by using using a state-based model instead. Since all the metrics of general interest from a classical age-based matrix models are readily derived from a state-based model equivalent, this suggests there may be little reason to use the classical age-based approach in situations where recruitment is a parameter of interest.
Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Journal of Ornithology 152, Suppl.2 (2012):585-595, doi:10.1007/s10336-010-0573-1.
Suggested CitationPreprint: Cooch, Evan G., Cam, Emmanuelle, Caswell, Hal, "Incorporating ‘recruitment’ in matrix projection models : estimation, parameters, and the influence of model structure", 2010-07, https://doi.org/10.1007/s10336-010-0573-1, https://hdl.handle.net/1912/5548
Showing items related by title, author, creator and subject.
Historical and idealized climate model experiments : an intercomparison of Earth system models of intermediate complexity Eby, Michael; Weaver, Andrew J.; Alexander, K.; Zickfeld, K.; Abe-Ouchi, A.; Cimatoribus, A. A.; Crespin, E.; Drijfhout, S. S.; Edwards, N. R.; Eliseev, A. V.; Feulner, G.; Fichefet, T.; Forest, C. E.; Goosse, H.; Holden, P. B.; Joos, Fortunat; Kawamiya, M.; Kicklighter, David W.; Kienert, H.; Matsumoto, K.; Mokhov, I. I.; Monier, Erwan; Olsen, S. M.; Pedersen, J. O. P.; Perrette, M.; Philippon-Berthier, G.; Ridgwell, Andy; Schlosser, A.; Schneider von Deimling, T.; Shaffer, G.; Smith, R. S.; Spahni, R.; Sokolov, Andrei P.; Steinacher, M.; Tachiiri, K.; Tokos, K.; Yoshimori, M.; Zeng, Ning; Zhao, F. (Copernicus Publications on behalf of the European Geosciences Union, 2013-05-16)Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate ...
Zhang, Huai-Min (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 1995-02)Inverse modeling activities in oceanography have recently been intensified, aided by the oncoming observational data stream of WOCE and the advance of computer power. However, interpretations of inverse model results ...
Evaluation of Arctic sea ice thickness simulated by Arctic Ocean Model Intercomparison Project models Johnson, Mark; Proshutinsky, Andrey; Aksenov, Yevgeny; Nguyen, An T.; Lindsay, Ron; Haas, Christian; Zhang, Jinlun; Diansky, Nikolay; Kwok, Ron; Maslowski, Wieslaw; Hakkinen, Sirpa M. A.; Ashik, Igor M.; de Cuevas, Beverly (American Geophysical Union, 2012-03-15)Six Arctic Ocean Model Intercomparison Project model simulations are compared with estimates of sea ice thickness derived from pan-Arctic satellite freeboard measurements (2004–2008); airborne electromagnetic measurements ...