Innovative wildlife photo-identification tracking technology developed by researchers at Dartmouth College has shed new light on African wildebeest population in northern Tanzania. Their technology, aptly named "Wild-ID," showed that the iconic species remains vulnerable, despite recent efforts made to combat habitat fragmentation and poaching.
In one of the largest and longest-distance mammal migrations on Earth, about 1.3 million East Africa wildebeests travel round-trip between protected areas in Tanzania and Kenya annually. The animals time their migration to coincide with seasonal patterns of rainfall and grass growth.
However, such migrations require large connected landscapes and access to seasonally available resources. Therefore, human development - roads, livestock fences, farms, suburban settlements and energy infrastructure - greatly interferes with the animals' travel, creating fragmented migration corridors and fewer foraging options.
Previously, wildlife biologists would monitor large mammal populations by counting them from the air or attaching expensive GPS collars. Dartmouth's new technology, however, uses an unusual computer-assisted photographic capture-mark-recapture method. With this, researchers are able to better assess the link between wildebeest abundance and their ability to freely move within the Tarangire-Manyara Ecosystem.
"A lot of people didn't think tracking hundreds, let alone thousands, of individual wildebeest was possible, but we managed with Wild-ID," said lead author Tom Morrison, who conducted the wildebeest study as part of his Ph.D. in Dartmouth's Ecology and Evolutionary Biology program.
Although wildlife photo-recognition software has previously been used to track cheetahs and zebras, for example, who have unique spotted or striped markings, similar technology proves to be ineffective for species like giraffes and wildebeest, due to their irregular coats.
That's why Dartmouth scientists integrated an irregular pattern-matching algorithm in "Wild-ID," originally developed in 2011. Wild-ID has proven to be much more accurate, with an error rate of virtually zero for giraffes and about eight percent for wildebeest. Wild-ID is also less invasive, expensive and time consuming.
"The Wild-ID technique not only provided an understanding of population size, but importantly, it also allowed us to know the movement and migration patterns of individual animals over time," Morrison added. "Together, this information provides a basis for predicting the future prospects of this wildebeest population."
Using this technology, researchers found that wildebeest populations have declined with fewer migration routes available in Tanzania. Specifically, researchers also found diminished connectivity within and between seasonal areas.
"What was probably once a population of tens of thousands of animals now numbers roughly 10,000 despite a landscape that rivals the Serengeti-Mara Ecosystem in total area," Morrison explained. "Recent conservation efforts to protect seasonal habitat and to enforce anti-poaching policies outside protected areas have likely helped stabilize the population, at least temporarily, since the early 2000s relative to the severe declines observed in the 1990s, but we caution that several key vulnerabilities remain."
Wild-ID therefore has the potential to improve conservation measures. Their study was recently published in the journal Biological Conservation.
