phenology (version 5.1)

phenology-package: Tools to Manage a Parametric Function that Describes Phenology

Description

Functions used to fit and test the phenology of species based on counts. Note that only the most significant changes are reported in the NEWS. To do: * There are problems with SE for fitRMU(). * Auto-scaling for optim during fitRMU search. * I must adapt TCF (total clutch frequency) fit from OCF-ECF (observed clutch frequency-estimated cluth frequency) table based on: Briane, J.-P., Rivalan, P., Girondot, M., 2007. The inverse problem applied to the Observed Clutch Frequency of Leatherbacks from Yalimapo beach, French Guiana. Chelonian Conservation and Biology 6, 63-69. Until now it is an Excel spreadsheet. * Fit tag-loss rate based on: Rivalan, P., Godfrey, M.H., Prévot-Julliard, A.-C., Girondot, M., 2005. Maximum likelihood estimates of tag loss in leatherback sea turtles. Journal of Wildlife Management 69, 540-548. Until now it is a RealBasic software. The lastest version of this package can always been installed using: install.packages("http://www.ese.u-psud.fr/epc/conservation/CRAN/phenology.tar.gz", repos=NULL, type="source")

Details

Fit a parametric function that describes phenology

Package:

phenology

Type:

Package

Version:

5.1 build 354

Date:

2016-05-02

License:

GPL (>= 2)

LazyLoad:

yes

References

Girondot, M. 2010. Estimating density of animals during migratory waves: application to marine turtles at nesting site. Endangered Species Research, 12, 85-105.

Girondot M. and Rizzo A. 2015. Bayesian framework to integrate traditional ecological knowledge into ecological modeling: A case study. Journal of Ethnobiology, 35, 339-355.

Girondot, M. 2010. Editorial: The zero counts. Marine Turtle Newsletter, 129, 5-6.

See Also

Girondot, M., Rivalan, P., Wongsopawiro, R., Briane, J.-P., Hulin, V., Caut, S., Guirlet, E. & Godfrey, M. H. 2006. Phenology of marine turtle nesting revealed by a statistical model of the nesting season. BMC Ecology, 6, 11.

Delcroix, E., Bédel, S., Santelli, G., Girondot, M., 2013. Monitoring design for quantification of marine turtle nesting with limited human effort: a test case in the Guadeloupe Archipelago. Oryx 48, 95-105.

Weber, S.B., Weber, N., Ellick, J., Avery, A., Frauenstein, R., Godley, B.J., Sim, J., Williams, N., Broderick, A.C., 2014. Recovery of the South Atlantic’s largest green turtle nesting population. Biodiversity and Conservation 23, 3005-3018.

Examples

## Not run: 
# library(phenology)
# # Get the lastest version at:
# # install.packages("http://www.ese.u-psud.fr/epc/conservation/CRAN/phenology.tar.gz", 
#      repos=NULL, type="source")
# # Read a file with data
# data(Gratiot)
# # Generate a formatted list nammed data_Gratiot 
# data_Gratiot<-add_phenology(Gratiot, name="Complete", 
# 		reference=as.Date("2001-01-01"), format="%d/%m/%Y")
# # Generate initial points for the optimisation
# parg<-par_init(data_Gratiot, parametersfixed=NULL)
# # Run the optimisation
# result_Gratiot<-fit_phenology(data=data_Gratiot, 
# 		parametersfit=parg, parametersfixed=NULL, trace=1)
# data(result_Gratiot)
# # Plot the phenology and get some stats
# output<-plot(result_Gratiot)
# ## End(Not run)