A Case of Mistaken Identity?

How improving ID skills can impact snow leopard population counts. Snow leopards are famously elusive, making them challenging to observe and study. We rely on technology like research cameras to be our window into their wild lives.

Take a good look at the two photos of snow leopards above. Is it the same cat or two different ones? Now imagine the wind is blowing the fur in different directions, or there are snowflakes obscuring the rosette pattern, or maybe half the cat is behind a rock. Would you be able to know for sure if it’s the same cat? Welcome to the world of snow leopard research.

The use of motion-activated research cameras to survey “hard-to-count” species has grown over the last decades. Researchers use them to estimate populations of many species, including tree kangaroos, wolverines, bears, and many species of cats. But how accurate are the resulting population estimates? There is a widespread assumption that when looking at remote camera images, scientists can readily identify individual animals from one another based on their unique characteristics. To ensure we are getting the most accurate population counts, we’re testing that assumption.

We’ve launched a robust study to better understand how well we identify one cat from another and how the errors influence the population estimates, allowing us to take that into account when developing our own population estimates of wild snow leopards.  To do this, we need remote camera photos of animals with known identities.

But where do we find cats with known identities? This is where zoo animal ambassadors get the opportunity to help their wild counterparts. Our scientists have asked experts from over 40 zoos to deploy the same kind of research cameras we use in the field to capture photos of each individual cat species in the study: amur tiger, lynx, amur leopard and snow leopard.

Why all four cats? Snow Leopard Trust scientists will examine how identification error rates may vary according to different fur types in wild animals by comparing data from four species of cats with contrasting patterns. 

  • amur tiger = stripes and short fur
  • lynx = small spots and long fur
  • amur leopard = large spots and short fur
  • snow leopard = large spots and long fur

It’s relatively easy to tell these four different species apart. But how did you do on the first test above? Did you know it’s the same snow leopard in both photos? If you didn’t, then you could have overestimated the population skewing our conservation strategies for snow leopard protection. (For the record, the cat in both photos is Dagina.)

The remote cameras in zoos will take photos of both sides of the cat where there is 100% certainty of its identity.  We will send these photos to scientists who normally ID the species of interest in the wild (lynx photos to lynx researchers and so on) through remote camera studies. Researchers involved in the project will not know how many cats are in the database, which cat is which, or where it is from – only our lead scientist knows the true identities. The researchers will ID the cats in the zoo photos. We can then assess how accurate they are at identifying individual cats because we are certain of the true identities of the zoo animals. We can also assess the types of errors that most commonly occur. For example, if it is more common to say that photos of the same cat are two different cats, that leads to an overestimation of the population. In contrast, if it is more common to classify two photos of different cats as the same cat, that will lead to an underestimation of the population.

We could not learn the answer to this vital question about ID accuracy without these known cats and the generous conservation partnership of zoos in this study. Once we have the final results, we hope to have a clear understanding of the margin of error. We can incorporate that into our research findings to better analyze and estimate snow leopard populations. This will help us take another leap forward in securing a future for wild felids. And we have zoo cats to thank for it.

Bonus ID test: Are these photos two different cats or the same one?

We made this one kind of easy for you by giving you photos of cats from similar angles.

Answer: It’s Dagina again! Notice the distinctive rosette pattern on her right front leg.

Between remote cameras and GPS collars, we have monitored Dagina for 12 years from 2009 to 2021. She will turn 13 years old in spring 2022; the oldest recorded female in Tost and South Gobi. She has had five different litters between 2012 and 2021.

Many thanks to the following zoos who participated in this 2021-2022 Photo ID project:

ABQ BioPark
Assiniboine Park Zoo
Bellewaerde Parc
Binder Park Zoo
Buffalo Zoo
Chattanooga Zoo
Cheyenne Mountain Zoo
Chicago Zoological Society/Brookfield Zoo
Cleveland Metroparks Zoo
Como Park Zoo
Dartmoor Zoo
Dublin Zoo
Franklin Park Zoo
Goldau Tierpark
Kölner Zoo
Korkeasaari Zoo
Lee Richardson Zoo
Mesker Park Zoo
Miller Park Zoo
Niabi Zoo
Nordens Ark
Omaha’s Henry Doorly Zoo
Orsa Rovdjurspark
Paradise Wildlife Park
Parco Zoo Punta Verde
Potawatomi Zoo
Rolling Hills Zoo
San Diego Zoo
Seneca Park Zoo
Tallinn Zoo
Tierpark Berlin
Tierpark Hellabrunn
The Big Cat Sanctuary
Toledo Zoo
Utah’s Hogle Zoo
Woodland Park Zoo
Zoo Basel
Zoo Berlin
Zoo Boise
Zoo Dresden
Zoo Zurich

See a full list of Zoo Partners supporting wild snow leopard conservation.

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