By: Maya Arruda Email: marruda7@umassd.edu
You ever get that feeling of frustration when you get stuck cleaning up someone else’s mess? I’m sure anyone who ever worked in a fast food joint or a service industry can relate.
Anyone in the environmental conservation field feels the same way, having to clean up the damage our ancestors did from overhunting, to pollution, to over-logging, to the gaping hole in the ozone layer.
Species conservation of near extinct species has taken a special role in people’s hearts, nowadays. Most people are interested in saving species from extinction, especially when humans are the direct or indirect cause. Seeing those efforts produce results and that these species’s populations are going up is usually a source of joy. However, just because we got the population numbers up a little bit doesn’t mean we truly finished cleaning up the mess. Most charts on population recovery only show the population after it was almost extinct, not what the population sizes were before whatever led to the almost extinction, whether it be poaching or pollution.
A research project led by Dr. Catherine Foley took the population ecology of a population of Arctic fur seals off the coast of the island of South Georgia, a semi-glacial island between South America and the Antarctic. Officially, the South Georgian Arctic fur seal population has, for the most part, recovered with a species population estimated between 4.5 to 6.2 million according to Grebieniow et al.’s paper in 2020. This species has been listed by the IUCN as of “least concern.”
Most of the Arctic fur seal population (97% according to Hoffman et al. 2018’s paper about gene flow in Arctic Fur Seals) resides within the South Georgia island vicinity. The island of South Georgia, actual uninhabited island, is very hard to get to with no facilities for aircraft. Winters on this island are especially hard for humans as the extremely cold weather makes the island inhospitable to any living being not adapted to living on the giant ice continent (i.e. Antarctica), which makes keeping track of Arctic fur seal populations very difficult. The Arctic fur seal faced near extinction in the 1900s after being over hunted, similarly to the buffalo in North America. At one point, no seals could be found on the South Georgia coast (i.e. their main land-based habitat/ mating ground). Before the early 1900s was not a good time to be a seal. Or anything, really.
No one had any records or counts on Arctic fur seal populations before their near extinction, so Foley and squad had to make their own estimate. Using historical records of seal hunting trips, Foley and team collected data on the approximate mortality rate of fur seals prior to the early 1900s, when hunting seals was finally criminalized. Using this mortality rate in addition to other species information (such as lifespan, birth rate, life history, etc), she crafted a model to estimate the initial Arctic fur seal population.
Moreover, her project included a method to obtain a more accurate measure of today’s Arctic fur seal population (because, let’s be real here, 4.5 to 6.2 million seals is pretty vague). She used a mix of time-lapse photography, high res photography, drone photography and satellite imagery to directly count the number of seals on the South Georgia coast. Seal species, and their gender/age, were identified from higher resolution pictures by volunteers at Seal Watch. Anyone with a computer can try their hand at seal identification, even though the project officially finished. Wink, wink, nudge, nudge.
To the surprise of absolutely no one, there was a statistically significant difference between the estimated B.H. (before hunting) and A.H. populations. Even with the gigantic error bars on both populations.
She presented this case study, along with four more aquatic species research projects (yes, including penguins), in a seminar titled “Leveraging quantitative methods and emerging technologies for marine conservation” on the UMass Dartmouth campus February 11, 2022. Highlights include usage of AI, courtesy of AI Fish, to identify whales and usage of belly patterns to identify individuals in Weddell seal populations.