Besbeas, Panagiotis, Morgan, Byron J. T. (2012) A threshold model for heron productivity. Journal of Agricultural, Biological, and Environmental Statistics, 17 (1). pp. 128-141. ISSN 1085-7117. (doi:10.1007/s13253-011-0080-8) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:31264)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1007/s13253-011-0080-8 |
Abstract
We demonstrate the potential of conditionally Gaussian state-space models in integrated
population modeling, when certain model parameters may be functions of previous
observations. The approach is applied to a heron census, and the data are best
described by a model with three population-size thresholds which determine the population
productivity. The model provides an explanation of how the population rebounds
rapidly after major falls in size, which are characteristic of the data. By contrast, a
simple logarithmic regression of productivity on population size was not significant.
The results are of ecological interest, and suggest hypotheses for further investigation.
Item Type: | Article |
---|---|
DOI/Identification number: | 10.1007/s13253-011-0080-8 |
Uncontrolled keywords: | Conditionally Gaussian, Density dependence, Integrated population modeling, Kalman filter, Non-linear models, P-splines, State-space model |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Depositing User: | Byron Morgan |
Date Deposited: | 04 Oct 2012 16:09 UTC |
Last Modified: | 05 Nov 2024 10:13 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/31264 (The current URI for this page, for reference purposes) |
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):