Nonlinear relationships between vital rates and state variables in demographic models

Ecology

Volumn 92, Issue 5, 2011, Pages 1181-1187

  Dahlgren, Johan P ^a   García, Maria B ^b   Ehrlén, Johan ^a  

^a STOCKHOLM UNIVERSITY   (Sweden)

^b INSTITUTO PIRENAICO DE ECOLOGÍA   (Spain)

Author keywords

Borderea pyrenaica; Demography; Integral projection models; Linearity assumption; Matrix models; Natural splines; Nonlinear regression; Plant population dynamics; Restricted cubic splines

Indexed keywords

ACCURACY ASSESSMENT; AGE STRUCTURE; DEMOGRAPHY; ESTIMATION METHOD; HERB; MATRIX; NONLINEARITY; NUMERICAL MODEL; POPULATION GROWTH; POPULATION MODELING; REGRESSION ANALYSIS; SIZE STRUCTURE;

DIOSCOREA PYRENAICA;

EID: 79955887506     PISSN: 00129658     EISSN: None     Source Type: Journal    
DOI: 10.1890/10-1184.1     Document Type: Article

References (16)

1. Caswell, H. 2001. Matrix population models: construction, analysis, and interpretation. Sunderland, Massachusetts, USA.
2. Easterling, M. R., S. P. Ellner, and P. M. Dixon. 2000. Size-specific sensitivity: applying a new structured population model. Ecology 81:694-708. (Pubitemid 30437994)
3. Ellner, S. P., and M. Rees. 2006. Integral projection models for species with complex demography. American Naturalist 167:410-428.
4. García, M. B., and R. J. Antor. 1995. Age and size structure in populations of a long-lived dioecious geophyte: Borderea pyrenaica (Dioscoreaceae). International Journal of Plant Sciences 156:236-243. (Pubitemid 26449103)
5. Harrell, F. E. 2001. Regression modeling strategies. Springer-Verlag, New York, New York, USA.
6. Hastie, T., and R. Tibshirani. 1990. Generalized additive models. Chapman and Hall, London, UK.
7. Lefkovitch, L. P. 1965. The study of population growth in organisms grouped by stages. Biometrics 21:1-18.
8. Leslie, P. H. 1945. On the use of matrices in certain population mathematics. Biometrika 33:183-212.
9. Low, M., and T. Pärt. 2009. Patterns of mortality for each life-history stage in a population of the endangered New Zealand stitchbird. Journal of Animal Ecology 78:761-771.
10. Morris, W. F., and D. F. Doak. 2002. Quantitative conservation biology: theory and practice of population viability analysis. Sinauer Associates, Sunderland, Massachusetts, USA.
11. Pfister, C. A., and F. R. Stevens. 2003. Individual variation and environmental stochasticity: implications for matrix model predictions. Ecology 84:496-510. (Pubitemid 36893086)
12. R Development Core Team. 2009. R, a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. (http://www.R-project.org)
13. Royston, P., and D. G. Altman. 1994. Regression using fractional polynomials of continuous covariates: parsimonious parametric modelling. Journal of the Royal Statistical Society C 43:429-467.
14. Sauerbrei, W., P. Royston, and H. Binder. 2007. Selection of important variables and determination of functional form for continuous predictors in multivariate model building. Statistics in Medicine 26:5512-5528. (Pubitemid 351193578)
15. Stone, C. J., and C. Y. Koo. 1985. Additive splines in statistics. Proceedings of the Statistical Computing Section. Journal of the American Statistical Association 80:45-48.
16. Zuidema, P. A., E. Jongejans, P. D. Chien, H. J. During, and F. Schieving. 2010. Integral Projection Models for trees: a new parameterization method and a validation of model output. Journal of Ecology 98:345-355.