mastif-package: Mast Inference and Forecasting

In mastif: Mast Inference and Forecasting

Mast Inference and Forecasting

Description

Seed production is estimated from censuses of trees and seed collections from traps. From locations of known trees and seed traps, infers source strength, coefficients for predictor variables, and parameters for a dispersal kernel. Fecundity is a state-space model allowing for random individual (tree) effects, random year effects and random AR(p) lag effects. Estimates unknown redistribution of seed types to known species identities of trees. Functions begin with 'mast' to avoid conflicts with other packages.

Details

Package:	mastif
Type:	Package
Version:	2.0
Date:	2023-1-20
License:	GPL (>= 2)
URL:	http://sites.nicholas.duke.edu/clarklab/code/

The package mastif estimates fecundity of trees and dispersion of seed observed at seed traps, using information on locations of sources and detectors, and covariates that could explain source strength. Data sets of this type are common and used to understand a range of processes related to seed dispersal, masting, environmental controls on reproduction, sex ratio, and allocation.

Posterior simulation is done by Gibbs sampling. Analysis is done by these functions:

mastif fits model with Gibbs sampling.

mastSim simulates data for analysis by mastif.

mastFillCensus aligns sample years in tree census data with seed trap data.

mastClimate annotates tree data with covariates for fecundity modeling.

mastPlot generates plots of the output from mastif.

Author(s)

Author: James S Clark, [e-mail]

References

Clark, JS, C Nunes, and B Tomasek. 2019. Masting as an unreliable resource: spatio-temporal host diversity merged with consumer movement, storage, and diet. Ecological Monographs, e01381.

See Also

mastif, mastSim

A more detailed vignette is can be obtained with:

browseVignettes('mastif')

mastif documentation built on Feb. 16, 2023, 5:30 p.m.