Animals live in 3D, and now scientists do, too
Animals live in a world of three dimensions. There’s the North-South axis, the East-West axis, and a third axis that tells you the elevation, altitude, or depth at which an animal can be found depending on whether the animal is terrestrial, aerial, or marine, respectively. If that seems obvious and not worth pointing out, you’re right. But most studies of animals’ space use have left out that important third vertical dimension.
In 1943, William Henry Burt provided the definition for an animal’s “home range” that has been used by biologists ever since: “that area traversed by an individual in its normal activities of food gathering, mating, and caring for young.” Biologists have long relied on estimates of home range size not just to better understand the basics of animal behavior and of population dynamics, but also to assess a given species’ vulnerability to extinction. It seems a given that part of that picture involves information related to elevation, altitude, or depth, but until recently the technology that researchers have used to track wildlife have not been up to the task. Even when GPS loggers do record data from the “Z” axis, most biotelemetry software leaves it out.
But that’s starting to change. United States Geological Survey researcher Jeff A. Tracey and colleagues have developed a new set of computer programs and visualization techniques for incorporating the third dimension. “Disregarding the vertical component may seriously limit understanding of animal habitat use and niche separation,” they say. By better understanding the way that animals move in all three dimensions, conservationists and biologists can better integrate the needs of wildlife into their land management plans. Different species might use different elevations, altitudes, or depths during different parts of the year, or during different parts of the day, or when they’re feeding versus resting or breeding. That information is critical when it comes to pitting human needs against those of the animals with whom we share space.
To see whether their new 3D mathematical models and visualization software offered improvements over the older 2D models, the researchers used three different endangered species as case studies: a Giant panda, a California condor breeding pair, and a dugong. Pandas live on steep mountain slopes in China, making elevation an important consideration. Condors naturally have different altitude requirements, and dugongs make use both of shallow and deeper waters off the coast of Australia.
Overall, the 3D modeling techniques indeed offered improvements over the more traditional methods for studying biotelemetry. Perhaps most importantly, the visualization offered researchers a way of “more intuitively understand[ing] how [the animals] spatially related to the environmental covariates and bounding layers within their ranges, such as bathymetry or topography.” In other words, they were able to see and intuit how a proposed wind farm would have interfered – potentially catastrophically – with the condor breeding pair. The 3D data provided the researchers with “more specific guidance to mitigate bird injuries and mortalities because it account[ed] for condor elevation and topography,” compared with the 2D models. More generally, such data can combine the movements of birds, bats, and other aerial critters more usefully with information about aircraft flight paths, power lines, or skyscrapers.
In addition, by including the vertical component, 3D estimations of home ranges are simply more biologically accurate than 2D estimations. That information will allow researchers a more thorough understanding of animal behavior, such as how multiple individuals within a population interact, or how multiple species within a particular ecosystem coexist. Dugongs, for example, spent more time near shore during higher tides, and moved away from shore as the tide went down. That basic information can then be used to help the fisheries industry avoid entangling dugongs in their nets and to help the shipping industry avoid striking dugongs with their vessels. Similar data would be useful for protecting other endangered species, like marine turtles. Animal movements could be combined with information about ocean currents or water temperatures in order to better predict when, where, and how marine animals might come into contact with waterborne contaminants.
Last, 3D biotelemetry provides better information for determining a species’ conservation status. When it came to the giant panda, the conventional 2D estimate returned a much smaller estimate of the home range surface area than the new 3D technique. Since home range size is correlated with extinction risk – the greater the space needs of an animal, the more likely a species is to face extinction – then wildlife biologists may be systematically underestimating the extinction risk for species that have live in a topographically, aerially, or bathymetrically complex environment.
Tracey and colleagues suggest that their 3D modeling and visualization techniques can also be used for just about any situation in which there is a strong vertical component to animal behavior. Rainforest biodiversity falls along a vertical gradient rather than a horizontal one, making 3D information far more valuable. Some butterfly species spend the dry season at one elevation and the rainy season at another, for example. The new technique could also allow researchers better insight into the spatial dynamics of species that create underground burrows.
By simply allowing researchers access to the third dimension, animals can escape the 2D “Flatland” and enter a more realistic, accurate, and informative 3D world. – Jason G. Goldman | 16 July 2014
Source: Tracey J.A., James Sheppard, Jun Zhu, Fuwen Wei, Ronald R. Swaisgood & Robert N. Fisher (2014). Movement-Based Estimation and Visualization of Space Use in 3D for Wildlife Ecology and Conservation, PLoS ONE, 9 (7) e101205. DOI: http://dx.doi.org/10.1371/journal.pone.0101205
Header image: California condor with visible number tags; public domain.
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