envPred-package: The 'envPred' package.

In dbarneche/envPred: Calculate Environmental Predictability for Even and Uneven Time Series Data

Description

'envPred' provides user-friendly functions to calculate five statistics from environmental time-series data: seasonality, the colour of environmental noise, constancy, contingency and predictability. These statistics can be calculated using the main function env_stats, which takes both evenly/unevenly-distributed, complete/incomplete date environmental time series.

Seasonality entails the regularity in the timing and magnitude of fluctuations in the average environmental state over seasons. Colour is defined by how predictable and similar the environment is between successive time points, or how far into the future the environmental state is likely to stay the same, independent of the mean environmental state. Constancy measures the extent to which the environment is the same for all months in all years. Contingency measures the extent to which the environmental differences between months are the same in all years. Predictability is the sum of constancy and contingency. Maximum predictability can be attained as a consequence of either complete constancy, complete contingency, or a combination of constancy and contingency.

The user can visually inspect whether the seasonal interpolation and the colour of environmental noise are appropriate to the input data using a ggplot2 wrapper gg_envpred.

References

Barneche DR, Burgess SC & Marshall DJ (2018) Global environmental drivers of marine fish egg size. Global Ecology and Biogeography, 27(8), 890-898. doi: 10.1111/geb.12748

Colwell RK (1974) Predictability, constancy, and contingency of periodic phenomena. Ecology, 55(5), 1148-1153. doi: 10.2307/1940366

Marshall DJ & Burgess SC (2015) Deconstructing environmental predictability: seasonality, environmental colour and the biogeography of marine life histories. Ecology Letters, 18(2), 174-181. doi: 10.1111/ele.12402

Vasseur DA & Yodzis P (2004) The color of environmental noise. Ecology, 85(4), 1146-1152. doi: 10.1890/02-3122

dbarneche/envPred documentation built on June 28, 2020, 5:04 p.m.