Overview

The R package ‘phenesse’ provides functions to calculate phenological estimates for multiple phenological metrics.

library(phenesse)

Loading example data

We provide example incidental observations from iNaturalist for four species and a small extent of the United States. These data are for the year 2019 up until mid October and are not scored by phenological phases. The four species are Speyeria cybele, Danaus plexippus, Rudbeckia hirta, and Asclepias syriaca.

example iNaturalist data:

inat_examples <- inat_examples

Use the Weibull-corrected estimates for any percentile of a distribution.

Estimate the onset, 10% and 50% of when Speyeria cybele has been observed in 2019 across the entire extent.

s_cybele <- inat_examples %>% 
  dplyr::filter(scientific_name == "Speyeria cybele")

# calculate onset
weib_percentile(observations = s_cybele$doy, percentile = 0, iterations = 100)
#> [1] 112.046
#calculate 1st percentile
weib_percentile(observations = s_cybele$doy, percentile = 0.1, iterations = 100)
#> [1] 151.1009
#calculate 50th percentile
weib_percentile(observations = s_cybele$doy, percentile = 0.5, iterations = 100)
#> [1] 194.2431

Use non-parametric bootsrapping to calculate confidence interaval of estimate

s_cybele <- inat_examples %>% 
  dplyr::filter(scientific_name == "Speyeria cybele")

# calculate onset
weib_percentile_ci(observations = s_cybele$doy, iterations = 50, percentile = 0.5, bootstraps = 50)
#> Warning in norm.inter(t, adj.alpha): extreme order statistics used as
#> endpoints
#>   estimate   low_ci  high_ci
#> 1 194.5909 182.6539 209.9167