Birds in atmosphere – r.iresmi.net

A photo of a gannet in the sky — Northern Gannet - Morus bassanus – CC-BY by caroline legg

Day 18 of 30DayMapChallenge: « Atmosphere » (previously).

Thanks to a post from @ClareEGordon@mastodon.social I found a dataset (Warwick-Evans et al. 2017) that could (vaguely) relates to the theme of atmosphere.

It describes the trajectories of GPS tracked Northern Gannets (Morus bassanus L.) breeding on Alderney in the English Channel.

Setup

library(tidyverse)
library(sf)
library(glue)
library(janitor)
library(rnaturalearth)
library(ggspatial)

Data

# GPS data
# https://datarepository.movebank.org/entities/datapackage/8e78d67d-24d9-49cd-9f0a-9b2bccaa70fa
mb_file <- "northern_gannets-les_etacs-alderney.csv"

if (!file.exists(mb_file)) {
  download.file("https://datarepository.movebank.org/bitstreams/dd6099d7-74fb-4be4-86e4-0e4b84177d65/download", mb_file)
}

mb <- read_csv(mb_file) |> 
  clean_names()

# countries from Natural Earth
countries <- ne_countries(scale = 10, returnclass = "sf") |> 
  st_make_valid()

Build polylines from points

The do_union = FALSE is important to keep the points’ ordering in the line.

mb_traj <- mb |> 
  st_as_sf(coords = c("location_long", "location_lat"), crs = "EPSG:4326") |> 
  group_by(tag_local_identifier) |> 
  summarise(do_union = FALSE) |> 
  st_cast("LINESTRING") |> 
  st_transform("EPSG:3035")

Map

bbox <- st_bbox(mb_traj)
min_year <- year(min(mb$timestamp))
max_year <- year(max(mb$timestamp))

mb_traj |> 
  ggplot() +
  geom_sf(data = countries, color = NA) +
  geom_sf(aes(color = tag_local_identifier), alpha = 0.4) +
  geom_sf(data = countries, fill = NA) +
  annotation_scale(height = unit(1, "mm"), 
                   text_col = "darkgrey", line_col = "grey", 
                   bar_cols = c("white", "grey")) +
  coord_sf(xlim = bbox[c(1, 3)], ylim = bbox[c(2, 4)]) +
  labs(title = "Northern Gannets tracking study",
       subtitle = glue("Alderney, {min_year} - {max_year}"),
       caption = glue("{st_crs(mb_traj)$Name}
                    Data: DOI:10.5441/001/1.30r98tb3
                    Basemap: Natural Earth
                    https://r.iresmi.net/ {Sys.Date()}")) +
  theme(legend.position = "none",
        plot.caption = element_text(size = 6), )

Map of Northern Gannets from Alderney — Figure 1: Northern Gannets from Alderney

Next stage would be to make an animation like @ClareEGordon@mastodon.social post with {gganimate}…

References

Warwick-Evans, Victoria, Louise M. Soanes, Roland D. Gauvain, Phil W. Atkinson, John P. Y. Arnould, and Jon A. Green. 2017. “Data from: Changes in Behaviour Drive Inter‐annual Variability in the at‐sea Distribution of Northern Gannets.” Movebank Data Repository. https://doi.org/10.5441/001/1.30R98TB3.

--- title: "Birds in atmosphere" description: "Day 18 of 30DayMapChallenge" author: "Michaël" date: "2023-11-18T22:00:00" date-modified: last-modified categories: - R - 30DayMapChallenge - spatial - datavisualization - ecology draft: false freeze: true editor_options: chunk_output_type: console chunk_output_type: console execute: eval: true --- [![Northern Gannet - Morus bassanus -- CC-BY by caroline legg](images/52928472818_c8b0e2697c_c.jpg){fig-alt="A photo of a gannet in the sky"}](https://flic.kr/p/2oD7fYb) Day 18 of [30DayMapChallenge](https://30daymapchallenge.com/): « Atmosphere » ([previously](/#category=30DayMapChallenge)). Thanks to a [post](https://mastodon.social/@ClareEGordon/111427146383129170) from [\@ClareEGordon\@mastodon.social](https://mastodon.social/@ClareEGordon) I found a dataset [@Warwick-EvansDataChangesbehaviour2017] that could (vaguely) relates to the theme of atmosphere. It describes the trajectories of GPS tracked [Northern Gannets](https://en.wikipedia.org/wiki/Northern_gannet) (*Morus bassanus* L.) breeding on Alderney in the English Channel. ## Setup ```{r} #| label: setup library(tidyverse) library(sf) library(glue) library(janitor) library(rnaturalearth) library(ggspatial) ``` ## Data ```{r} #| label: data # GPS data # https://datarepository.movebank.org/entities/datapackage/8e78d67d-24d9-49cd-9f0a-9b2bccaa70fa mb_file <- "northern_gannets-les_etacs-alderney.csv" if (!file.exists(mb_file)) { download.file("https://datarepository.movebank.org/bitstreams/dd6099d7-74fb-4be4-86e4-0e4b84177d65/download", mb_file) } mb <- read_csv(mb_file) |> clean_names() # countries from Natural Earth countries <- ne_countries(scale = 10, returnclass = "sf") |> st_make_valid() ``` ## Build polylines from points The `do_union = FALSE` is important to keep the points' ordering in the line. ```{r} #| label: layer mb_traj <- mb |> st_as_sf(coords = c("location_long", "location_lat"), crs = "EPSG:4326") |> group_by(tag_local_identifier) |> summarise(do_union = FALSE) |> st_cast("LINESTRING") |> st_transform("EPSG:3035") ``` ## Map ```{r} #| label: fig-map #| fig-cap: Northern Gannets from Alderney #| fig-alt: Map of Northern Gannets from Alderney #| dev: png #| out-width: "100%" #| dev.args: #| bg: transparent #| fig-width: 7 #| fig-height: 6.5 bbox <- st_bbox(mb_traj) min_year <- year(min(mb$timestamp)) max_year <- year(max(mb$timestamp)) mb_traj |> ggplot() + geom_sf(data = countries, color = NA) + geom_sf(aes(color = tag_local_identifier), alpha = 0.4) + geom_sf(data = countries, fill = NA) + annotation_scale(height = unit(1, "mm"), text_col = "darkgrey", line_col = "grey", bar_cols = c("white", "grey")) + coord_sf(xlim = bbox[c(1, 3)], ylim = bbox[c(2, 4)]) + labs(title = "Northern Gannets tracking study", subtitle = glue("Alderney, {min_year} - {max_year}"), caption = glue("{st_crs(mb_traj)$Name} Data: DOI:10.5441/001/1.30r98tb3 Basemap: Natural Earth https://r.iresmi.net/ {Sys.Date()}")) + theme(legend.position = "none", plot.caption = element_text(size = 6), ) ``` Next stage would be to make an animation like [\@ClareEGordon\@mastodon.social post](https://mastodon.social/@ClareEGordon/111427146383129170) with {gganimate}... ## References