phenology (version 7.2)

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. The lastest version of this package can always been installed using: install.packages("http://www.ese.u-psud.fr/epc/conservation/CRAN/HelpersMG.tar.gz", repos=NULL, type="source") 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:	7.2 build 727
Date:	2018-09-26
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.

Girondot, M., 2017. Optimizing sampling design to infer marine turtles seasonal nest number for low-and high-density nesting beach using convolution of negative binomial distribution. Ecological Indicators 81, 83<U+2013>89.

Rivalan, P., Godfrey, M.H., Pr<U+00E9>vot-Julliard, A.-C., Girondot, M., 2005. Maximum likelihood estimates of tag loss in leatherback sea turtles. Journal of Wildlife Management 69, 540-548.

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., B<U+00E9>del, 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<U+2019>s largest green turtle nesting population. Biodiversity and Conservation 23, 3005-3018.

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

Fossette S, Kelle L, Girondot M, Goverse E, Hilterman ML, Verhage B, Thoisy B, de, Georges J-Y (2008) The world's largest leatherback rookeries: A review of conservation-oriented research in French Guiana/Suriname and Gabon. Journal of Experimental Marine Biology and Ecology 356:69-82

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, fixed.parameters=NULL)
# Run the optimisation
result_Gratiot <- fit_phenology(data=data_Gratiot, 
		fitted.parameters=parg, fixed.parameters=NULL)
data(result_Gratiot)
# Plot the phenology and get some stats
output <- plot(result_Gratiot)
# }