In inbo/watervogelanalysis: Analysis of the Wintering Birds

Summarising tables

trend_class <- function(lcl, ucl, treshold) {
  ifelse(
    ucl < 0,
    ifelse(
      ucl < -abs(treshold),
      "--",
      ifelse(lcl < -abs(treshold), "-", "-≈")
    ),
    ifelse(
      lcl > 0,
      ifelse(
        lcl > abs(treshold),
        "++",
        ifelse(ucl < abs(treshold), "+≈", "+")
      ),
      ifelse(
        ucl < abs(treshold),
        ifelse(lcl > -abs(treshold), "≈", "?-"),
        ifelse(lcl > -abs(treshold), "?+", "?")
      )
    )
  ) %>%
    factor(levels = c("++", "+", "+≈", "≈", "-≈", "-", "--", "?+", "?-", "?"))
}
trend <- function(mean, duration = 1, round = 1) {
  round(100 * exp(mean * duration) - 100, round)
}
estimate <- function(mean, round = 1) {
  round(exp(mean), round)
}
publication <- function(mean, magnitude) {
  magnitude <- magnitude - 2
  round(exp(mean) / 10 ^ magnitude) * 10 ^ magnitude
}

Average yearly change over the last twelve year based on monthly totals

results %>%
  filter(ModelType == "imputed trend: Total ~ Year + Month", Duration == 12,
         Parameter == "cYear") %>%
  transmute(Area = LocationGroup, Species = scientific_name,
            Class = trend_class(LCL, UCL, log(0.75) / Duration),
            Estimate = trend(Estimate, 1, 1),
            LCL = trend(LCL, 1, 1),
            UCL = trend(UCL, 1, 1)) %>%
  arrange(Class, desc(Estimate)) %>%
  datatable(rownames = FALSE)

Average total change over the last twelve year based on monthly totals

results %>%
  filter(ModelType == "imputed trend: Total ~ Year + Month", Duration == 12,
         Parameter == "cYear") %>%
  transmute(Area = LocationGroup, Species = scientific_name,
            Class = trend_class(LCL, UCL, log(0.75) / Duration),
            Estimate = trend(Estimate, Duration, 0),
            LCL = trend(LCL, Duration, 0),
            UCL = trend(UCL, Duration, 0)) %>%
  arrange(Class, desc(Estimate)) %>%
  datatable(rownames = FALSE)

Average yearly change over the entire dataset based on monthly totals

results %>%
  filter(
    ModelType == "imputed trend: Total ~ Year + Month",
    Duration == max(Duration), Parameter == "cYear"
  ) %>%
  transmute(Area = LocationGroup, Species = scientific_name,
            Class = trend_class(LCL, UCL, log(0.75) / Duration),
            Estimate = trend(Estimate, 1, 1),
            LCL = trend(LCL, 1, 1),
            UCL = trend(UCL, 1, 1)) %>%
  arrange(Class, desc(Estimate)) %>%
  datatable(rownames = FALSE)

Average total change over the entire dataset based on monthly totals

results %>%
  filter(
    ModelType == "imputed trend: Total ~ Year + Month",
    Duration == max(Duration), Parameter == "cYear"
  ) %>%
  transmute(Area = LocationGroup, Species = scientific_name,
            Class = trend_class(LCL, UCL, log(0.75) / Duration),
            Estimate = trend(Estimate, Duration, 0),
            LCL = trend(LCL, Duration, 0),
            UCL = trend(UCL, Duration, 0)) %>%
  arrange(Class, desc(Estimate)) %>%
  datatable(rownames = FALSE)

Detailed winter maximum averaged of the last five years

results %>%
  filter(ModelType == "imputed average: Total ~ cPeriod",
         Parameter == "(Intercept)") %>%
  transmute(Area = LocationGroup, Species = scientific_name,
            Estimate = estimate(Estimate, 0),
            LCL = estimate(LCL, 0),
            UCL = estimate(UCL, 0)) %>%
  arrange(desc(Estimate)) %>%
  datatable(rownames = FALSE)

Winter maximum averaged of the last five years, rounded for publication

results %>%
  filter(ModelType == "imputed average: Total ~ cPeriod",
         Parameter == "(Intercept)") %>%
  mutate(
    Magnitude = ceiling(log10(exp(UCL))),
    Magnitude = Magnitude - (1.5 * 10 ^ Magnitude > exp(UCL))
  ) %>%
  transmute(Area = LocationGroup, Species = scientific_name,
            Estimate = publication(Estimate, Magnitude),
            LCL = publication(LCL, Magnitude),
            UCL = publication(UCL, Magnitude)) %>%
  arrange(desc(Estimate)) %>%
  datatable(rownames = FALSE)

Percentage change in averaged winter maximum between the last two five year periods

results %>%
  filter(ModelType == "imputed average: Total ~ cPeriod",
         Parameter == "cPeriod") %>%
  transmute(Area = LocationGroup, Species = scientific_name,
            Class = trend_class(LCL, UCL, log(0.75)),
            Estimate = trend(Estimate, 1, 1),
            LCL = trend(LCL, 1, 1),
            UCL = trend(UCL, 1, 1)) %>%
  arrange(Class, desc(Estimate)) %>%
  datatable(rownames = FALSE)

inbo/watervogelanalysis documentation built on Oct. 10, 2024, 7:17 a.m.