Big data informs conservation research and protects endangered species

Many animal biotelemetry technologies, used to remotely monitor and measure activity and movement, routinely capture 3D location data. Vertical coordinates, however, rarely make their way into studies of animal movement. Yet disregarding this component can limit understanding of habitat use and separation. If an animal is threatened or endangered, ecological insights drawn from data become all the more critical.

Researchers at the US Geological Survey (USGS) and the Institute for Conservation Research (ICR) at the San Diego Zoo in California, US, have developed a new methodology that combines advanced 3D technologies to provide detailed data on the range and movements of wildlife species. Their paper is published online in PLoS-ONE.

2D or not 2D

The project’s advancements center on the use of 3D technology for home range estimators, as opposed to traditional 2D systems typically used by ecologists. “This provides us with deeper insights into patterns of animal space-use and informs strategies for the conservation management of endangered species and their habitats,” says James Sheppard, a senior researcher in the Applied Animal Ecology Division of ICR.

The team developed a movement-based kernel density estimator (MKDE) to estimate animal movements. “We show that analyses and visualization using 3D MKDEs are more accurate and informative than traditional 2D estimators in representing the space use of animals that have a substantive vertical component, such as those that fly, traverse steep terrain, or dive in the water,” says Jeff Tracy, an ecologist at the USGS and lead author of the study. “Biologists and ecologists are only beginning to recognize the value of incorporating the vertical aspect into analyses, which more realistically represents the space used by an animal.”

By land, sea, and air

While the California condor population now stands at approximately 400 birds — up from only 22 in the 1980s — conservation efforts to reintroduce the species to its former habitat have been hampered by a lack of understanding about condor movement patterns and habitat use. To gather valuable tracking data, the San Diego researchers attach miniature, GPS biotelemetry units to every condor released into the wild.

“We have been calculating home ranges for the tracked condors in three dimensions for the first time using this GPS location data, and our movement-based kernel density estimator (MKDE),” says James Sheppard, a senior researcher in the Applied Animal Ecology Division of the ICR.

In addition to the California condor, the researchers developed simulations to track two other endangered species: the giant panda and the dugong — a marine animal similar to the manatee. To study the home range of a free-ranging giant panda, researchers used a version of MKDE to create a detailed simulation. The model includes vertical dimension, restricted to follow the topology of a particular region.

Dugongs face numerous threats including boat-strikes, incidental capture in fishing nets, and habitat degradation. Unless their habitat and circumstances improve, they are likely to become endangered. The researchers focused on the movements of a free-ranging dugong in Hervey Bay, in Queensland, Australia, tracking 41 days in seagrass habitat. They used a 3D version of MKDE that enabled tracking of the dugong even during steep dives and other vertical movements.

From days to minutes

What started as a supercomputing challenge — 3D modeling is much more computationally expensive than 2D — actually became an exercise in optimizing codes to make it possible for research to be done on laptops or even smart phones. 

“We were able to speed up their software by several orders of magnitude,” says Robert Sinkovits, director of the scientific applications group at the San Diego Supercomputing Center (SDSC), which helps researchers make optimal use of SDSC's supercomputers including Gordon and Trestles.“In this case, calculations that had formerly taken four days to complete were finished in less than half an hour.”

Amit Chourasia, senior visualization scientist at SDSC, contributed visualization expertise. “We made changes to write the data into a more compact format, which enabled swift output and ingestion,” says Chourasia. “A key goal was to allow the experts to visualize the data directly on Gordon via remote access, as it is essential to minimize data movement and replication especially when data sizes grow. Currently, we’re working to fuse data from various sources such as topography and climate to further aid the understanding of such habitats.”

Sheppard notes that the field of ecology is entering the era of big data, so it is imperative that new analytical and visualization tools — that can process, manage, and analyze increasingly large and accurate multidimensional, biotelemetry data sets — be developed. “Otherwise ecologists and conservation managers may literally not be able to see the forest for the trees.”

A video of the projectis available on SeedMe.

To read the extended, original version of Jan Zverina’s article, visit the San Diego Supercomputing Center’s website.