neonUtilities (>= 2.0.1), magrittr, rhdf5 (>= 2.33.7), R.utils,
Packaged: 2021-07-06 20:21:47 UTC; richfiorella

Imports: dplyr, zoo, httr, lubridate, neonUtilities (>= 2.0.1),
magrittr, rhdf5 (>= 2.33.7), R.utils, tidyselect, data.table,
Packaged: 2021-08-12 17:54:59 UTC; richfiorella

Packaged: 2021-11-17 15:55:52 UTC; rfiorella

Authors@R: c(person("Rich", "Fiorella", email = "rfiorella@lanl.gov",
Calibration tools are provided for carbon and water isotope products.
Carbon isotope calibration details are found in Fiorella et al. (2021)
file at <https://github.com/lanl/NEONiso>. Tools for calibrating water
isotope products have been added as of 0.6.0, but have known deficiencies
and should be considered very experimental currently.
rlang, lifecycle, caret, ggplot2, gridExtra
Packaged: 2022-08-08 15:24:24 UTC; rfiorella
Author: Rich Fiorella [aut, cre] (<https://orcid.org/0000-0002-0824-4777>)

Packaged: 2022-09-22 19:14:25 UTC; rfiorella

Title: Calculating effective sizes based on known demographic
Author: Annegret Grimm, Bernd Gruber & Klaus Henle
Description: NEff is an individual based model. This package uses demographic parameter of a population to calculate annual effective sizes and effective population sizes (per generation). It assumes that no migration and mutation is occurring. A defined number of alleles and loci will be used to simulate the genotypes of the individuals. These results will help managers to define existing populations as viable or not.

Title: Calculating Effective Sizes Based on Known Demographic
Description: Effective population sizes (often abbreviated as "Neff") are essential in biodiversity monitoring and conservation. For the first time, calculating effective sizes with data obtained within less than a generation but considering demographic parameters is possible. This individual based model uses demographic parameters of a population to calculate annual effective sizes and effective population sizes (per generation). A defined number of alleles and loci will be used to simulate the genotypes of the individuals. Stepwise mutation rates can be included. Variations in life history parameters (sex ratio, sex-specific survival, recruitment rate, reproductive skew) are possible. These results will help managers to define existing populations as viable or not.