UMBS Ice Cover
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library(tidyverse)## Warning: package 'lubridate' was built under R version 4.3.3## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.3 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.4 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.0
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
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lake_ice_noNA <- read_csv("douglaslake_southfishtailbay_icecover_1931-2024.csv",) %>%
drop_na()## Rows: 105 Columns: 2
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): observation
## date (1): date
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.lake_ice_noNAwrite_csv(lake_ice_noNA,"douglaslake_southfishtailbay_icecover_1931-2024.csv")# Convert the 'date' column to a Date object
lake_ice <- lake_ice_noNA %>%
mutate(date = ymd(date))
# Create a lagged version of the 'date' and 'observation' column and calculate the duration
lake_ice <- lake_ice %>%
arrange(date) %>%
mutate(lead_observation = lead(observation),
lead_date = lead(date)) %>%
filter(observation == "ice in", lead_observation == "ice out") %>%
mutate(duration = lead_date - date)
# Identify winter by subtracting a year from the 'date' if 'date' is in Jan or Feb
lake_ice <- lake_ice %>%
mutate(winter = ifelse(month(date) %in% 1:2, year(date) - 1, year(date)))
# Create a column for the winter season string representation
lake_ice <- lake_ice %>%
mutate(winter = paste(winter, winter + 1, sep="-"))
# Select the relevant columns
new_lake_ice <- lake_ice %>%
select(winter, date, lead_date, duration)
# Rename the columns to be more informative
new_lake_ice <- rename(new_lake_ice,
`Ice On Date` = date,
`Ice Off Date` = lead_date,
`Duration` = duration)
# View the new table
print(new_lake_ice)## # A tibble: 50 × 4
## winter `Ice On Date` `Ice Off Date` Duration
## <chr> <date> <date> <drtn>
## 1 1933-1934 1933-11-16 1934-04-28 163 days
## 2 1950-1951 1950-11-24 1951-04-13 140 days
## 3 1973-1974 1973-12-12 1974-04-21 130 days
## 4 1974-1975 1974-12-13 1975-05-01 139 days
## 5 1975-1976 1975-12-07 1976-04-14 129 days
## 6 1979-1980 1979-12-02 1980-04-21 141 days
## 7 1980-1981 1980-12-03 1981-04-01 119 days
## 8 1981-1982 1981-12-11 1982-04-30 140 days
## 9 1982-1983 1982-12-12 1983-04-14 123 days
## 10 1983-1984 1983-12-03 1984-04-13 132 days
## # ℹ 40 more rowslibrary(ggplot2) # Part of tidyverse, for plotting
# Convert Duration to numeric in case it's not already.
new_lake_ice <- new_lake_ice %>%
mutate(Duration = as.numeric(Duration))
# Create a column with just the starting year of the winter for plotting
new_lake_ice <- new_lake_ice %>%
mutate(Year = as.numeric(sub("-.*", "", winter)))
# Use ggplot to create a scatter plot with Year and Duration
ggplot(new_lake_ice, aes(x = Year, y = Duration)) +
geom_point() + # Add points representing each observation
geom_smooth(method = "lm", se = FALSE, color = "blue") + # Add a linear trend line, no confidence interval shading
labs(x = "Year", y = "Ice Duration (days)", title = "Trend of Lake Ice Duration Over Years") +
theme_minimal() # Use the minimal theme for a cleaner look## `geom_smooth()` using formula = 'y ~ x'
library(ggplot2)
library(patchwork)## Warning: package 'patchwork' was built under R version 4.3.3# Modify the data to fix November as the start of the period
new_lake_ice <- new_lake_ice %>%
mutate(`Ice On Fixed` = as.Date(ifelse(month(`Ice On Date`) < 6,
format(`Ice On Date`, "2001-%m-%d"),
format(`Ice On Date`, "2000-%m-%d"))),
`Ice Off Fixed` = as.Date(ifelse(month(`Ice Off Date`) < 6,
format(`Ice Off Date`, "2001-%m-%d"),
format(`Ice Off Date`, "2000-%m-%d"))))
# Custom colors from the user
ice_on_color <- "#1b9e77"
ice_off_color <- "#d95f02"
duration_color <- "#7570b3"
# Create the 'Ice On' and 'Ice Off' dates plot
ice_dates_plot <- ggplot(new_lake_ice, aes(x = Year)) +
geom_point(aes(y = `Ice On Fixed`), color = ice_on_color) +
geom_point(aes(y = `Ice Off Fixed`), color = ice_off_color) +
geom_smooth(aes(y = `Ice On Fixed`), method = "lm", se = FALSE, color = ice_on_color) +
geom_smooth(aes(y = `Ice Off Fixed`), method = "lm", se = FALSE, color = ice_off_color) +
scale_y_date(date_breaks = "1 month", labels = scales::date_format("%B")) +
labs(title = "Douglas Lake ice on, off and duration") +
theme_minimal() +
theme(plot.margin = margin(b = 0),
axis.title.x = element_blank(),
axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
legend.position = "none")
# Annotation position calculation
last_year <- max(new_lake_ice$Year)
latest_ice_on <- max(new_lake_ice$`Ice On Fixed`, na.rm = TRUE)
earliest_ice_off <- min(new_lake_ice$`Ice Off Fixed`, na.rm = TRUE)
# Annotate the Ice On and Ice Off trend lines
ice_dates_plot <- ice_dates_plot +
annotate("text", x = last_year, y = latest_ice_on, label = "Ice On", hjust = 13.3, vjust = 2,
color = ice_on_color, size = 3.5, angle = 0) +
annotate("text", x = last_year, y = earliest_ice_off, label = "Ice Off", hjust = 13.6, vjust = -0.5,
color = ice_off_color, size = 3.5, angle = 0)
# Modify the 'Duration' plot to include linear trend lines and annotations
shortest_duration <- min(new_lake_ice$Duration, na.rm = TRUE)
duration_plot <- ggplot(new_lake_ice, aes(x = Year, y = Duration)) +
geom_point(color = duration_color) +
geom_smooth(method = "lm", se = FALSE, color = duration_color) +
annotate("text", x = last_year, y = shortest_duration, label = "Ice Duration", hjust = 7.3, vjust = -9,
color = duration_color, size = 3.5, angle = 0) +
labs(x = "Year", y = "Ice Duration (days)") +
theme_minimal()
# Combine the plots
combined_plot <- (ice_dates_plot + plot_layout(heights = c(1))) /
(duration_plot + plot_layout(heights = c(1)))
# Display the combined plot
combined_plot## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
ggsave(combined_plot,
filename = "UMBS_ice_cover_plot.jpeg",
device = "jpeg",
height = 4, width = 6, units = "in")## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'