“Tracking Blue Whales in the Great Southern Australian Coastal Upwelling System”

Day 5 of 30DayMapChallenge: « A Journey » (previously).

Thirteen Blue whales (Balaenoptera musculus) were satellite tagged in 2015 in Australia (Mӧller et al. 2020). We’ll follow their summer in the Great Southern Australian Coastal Upwelling System (GSACUS).

Data is available from the Australian Antarctic Data Centre (Andrews-Goff et al. 2020), directly as a R RDS file.

library(dplyr)
library(readr)
library(sf)
library(leaflet)

unzip("AAS_4101_pygmy_blue_whale_SSSM.zip",
      files = "bw_3h_ssm.RDS")
bm <- read_rds("bw_3h_ssm.RDS")
# str(bm)

journeys <- bm$summary |>
  st_as_sf(coords = c("lon", "lat"), crs = "EPSG:4326") |>
  group_by(id) |>
  arrange(date) |>
  summarise(do_union = FALSE) %>%
  st_cast("LINESTRING") |>
  group_by(indiv = as.factor(parse_number(as.character(id)))) |>
  summarise()

After joining GPS points as lines and lines from the same whale as multilines, we can use {leaflet} for an interactive map.

pal <- colorFactor("viridis", sort(unique(journeys$indiv)))

journeys |>
  leaflet() |>
  addTiles() |>
  addPolylines(color = ~ pal(indiv),
               popup = ~ indiv) |>
  addLegend(pal = pal,
            values = sort(unique(journeys$indiv)))

Continue reading: Whales movements

Long-term Implications and Possible Future Developments

In 2015, thirteen Blue whales were satellite tagged in Australia, their movements tracked during the summer in the Great Southern Australian Coastal Upwelling System (GSACUS). The data was obtained from the Australian Antarctic Data Centre, providing a unique insight into the whales’ migratory patterns. This knowledge has potential long-term implications for understanding and protecting Blue whales.

“Day 5 of 30DayMapChallenge: « A Journey » (previously). Thirteen Blue whales (Balaenoptera musculus) were satellite tagged in 2015 in Australia (Mӧller et al. 2020). We’ll follow their summer in the Great Southern Australian Coastal Upwelling System (GSACUS).
Data is available from the Australian Antarctic Data Centre (Andrews-Goff et al. 2020), directly as a R RDS file.”

Detailed Mapping and Tracking Provides New Insights

The mapping represents a notable stride in the study of blue whale migrations and behavior. By employing R code to unify GPS points as lines and collate lines from the same whale into multilines, an interactive map using the Leaflet package was created. This progressive use of technology allows for more precise tracking and predictions of migratory routes, which could lead to improved protection measures for these creatures.

Potential Future Developments

We can expect more comprehensive and insightful studies in the future about the migratory behaviors of not just blue whales but of marine life in general. Cuttin-edge technology and data science methods can help create a more accurate picture of the sea’s giants’ movements. It can reveal their feeding grounds, breeding areas, and preferred routes, essential factors in their habitat protection. Future studies may employ machine learning algorithms for predictive analysis of migratory behavior to establish sanctuaries in anticipation of their movements.

Actionable Advice

This case shows the value of satellite tagging and advanced data science tools in tracking and analyzing the behavior of marine life. Organizations and researchers dedicated to marine conservation should invest in similar technologies to gather comprehensive data on threatened species. Utilizing available open-source libraries, such as Leaflet package in R, for interactive and user-friendly data representation can make previously impenetrable data accessible and understandable to a wider audience. Combining technology and data handling strategies with marine biology will continually provide innovative solutions ensuring the survival of iconic but threatened species like the blue whale.

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