Note: Meredith wrote this blog post, but is having internet problems in Africa, so I am posting it on her behalf.
Pole sana on the lack of recent field updates – it’s been a busy week or two and I’ve traveled halfway across Africa in the meanwhile! Sad to say, I’ve left Serengeti behind for now. I was able to set up almost all of the replacement cameras I brought down with me and completed three new rounds for my playback experiments. I then took a few days off and spent my birthday traveling around in Ethiopia, soaking in some history and culture (and eating really excellent food!). It’s nice to have a break from constant science every once in a while. I went around what is known as the “Northern Circuit” and visited the four historic cities of Gondar, Lalibella, Aksum, and Bahir Dar. I got to visit island monasteries, rock-hewn churches, the palace of the Queen of Sheba, and even made a trip to the church purported to be where the True Ark of the Covenant is kept! Have to say, the trip made me feel very “Indiana Jones”, right up until the point where I got ill from drinking the water…
After a week in Ethiopia, I flew down to Johannesburg, South Africa, to meet up with Craig and another graduate student we’re working with, Natalia. Natalia is interested in cognition and has been testing the creative problem solving and impulse control of different kinds of carnivores. We’ve spent the last few days at a reserve outside of Pretoria called Dinokeng, run by Kevin “the Lion Whisperer” Richardson. Kevin maintains a park with dozens of semi-captive lions, leopards, and hyenas which Natalia can work with for her intelligence experiments. While Natalia has been busy with her research, I’ve been putting together a rig that will enable me to examine herbivore responses to four predator species: cheetah, wild dog, lion, and hyena. Two of these predators (lion and cheetah) hunt by sneaking up on their prey, whereas the others (wild dog and hyena) rely on endurance to run prey down. I’m looking to see whether prey respond to each species of predator differently, or whether there are consistent differences in anti-predatory response by predator hunting type. I’ll be simulating predator encounters because it would be incredibly difficult to observe a sufficient number of actual encounters in the wild. As soon as I find a good internet connection, I’ll post pictures of just exactly how I plan on doing this — it’s pretty great, and I don’t want to ruin the surprise!
Just this morning, the three of us packed up all of our gear and took a small plane out of Pretoria up to South Africa’s Northern Cape province. We’ll be spending the next three to four weeks up here in the Kalahari conducting our experiments. In addition to looking at anti-predator responses, I’ll be helping to set up a NEW camera trap grid (perhaps Snapshot Serengeti will be joined by Kalahari Cameras sometime in the near future…?). Now that we’re back in action, more updates soon!
First field update! I’ve been out in Serengeti Park for just over a week now, and I’m fairly surprised to report that things are going rather swimmingly. It was certainly my smoothest travel experience from the USA to date: no plane delays (unlike last time), no missing luggage (unlike last time), no egregiously extended stay in Arusha waiting for permits (unlike last time). To be sure, field life takes a bit of getting used to again. We’ve had spitting cobras in the bathroom, ververt monkeys breaking into my car, and little black flies are out in full force. But the Serengeti this time of year is completely worth it. Last time, my field season only encompassed the dry season, but in the current rainy period, Serengeti is a completely different place. Everything is so green it almost hurts your eyes to look at it. Up in Barafu, along the eastern edge of our camera trap grid, are herds of wildebeest, zebra, and buffalo so large you can hardly believe it. (My first time driving through a herd of buffalo several hundred strong required more courage than I’d care to admit – buffalo are big and mean and certainly warrant a healthy respect. They’ve been known to ram our field vehicles before and cause all sorts of trouble).
There’s a few projects I’m working on this year with the camera traps: first and foremost finishing up the playback experiments I began last season. Every morning for ten consecutive days, I’d head out to particular camera traps and play lion roars, simulating the short-term presence of predators in an area. We see from the camera traps that herbivores start to evacuate from these scary areas (or, “areas of artificially elevated predation risk”, to use a more scientific jargon) for not just days or hours, but periods of up to three weeks! I’m interested generally in the trade-offs that herbivores have to make between avoiding areas where predators are and still obtaining enough resources to get by. Do they only avoid areas where there’s a high chance predators will be, like lion territories, despite all the tasty forage that may be contained inside? Or is the avoidance being exhibited on a finer scale – like days to weeks, rather than months to years, like we’re seeing in this experiment? Perhaps there are some species of ungulates that don’t try and avoid predators on a spatial scale at all, but rather rely heavily on evasive and defensive behaviors when they encounter a hungry carnivore. Hopefully these continued experiments and the Snapshot data in general will help elucidate answers to some of these questions!
I’m also working on another round of habitat characterization – this time, we’re interested in the soils and vegetation that help to determine the forage quality at a particular site. Now, to tell the truth, I wasn’t originally that enthused about these particular collection tasks, but I’ve discovered that there’s incredibly satisfying about grubbing around in the mud scraping out soil samples. My inner 8-year old is feeling more rejuvenated by the day. Lion House is started to become more than a little cluttered with sample bags of dirt and grass clippings – pole sana, other field assistants, it’s for Science!
Looks like everyone is sinking their teeth into Season 8! As a reminder, feel free to ask questions or chat with us through the Snapshot Serengeti Discussion board or in the comments of any of our blog posts.
Now, there’s some data from this new season that hasn’t made it online — sometimes, instead of taking pictures, our cameras accidentally switch into “video” mode and capture 10-second clips of animals doing their Serengeti thing. While this isn’t very good for us in terms of data collection (although we’ve been tossing around the idea of setting up a Snapshot Serengeti: Video Edition!…), it gives you a unique perspective on the lives of these animals.
(Okay, so it’s mostly animals eating grass. They eat a lot of grass. Perhaps not the most “unique” insight on their behaviors, but they’re still pretty fun to watch). Here’s some of my favorite accidental movies from our new Season!
And now, the moment you’ve all been waiting for … Can I present to you:
I’m particularly proud of this, the first season that I’ve helped to bring all the way from the field to your computers. We’ve got a lot of data here, and I can’t wait for you guys to discover a whole host of exciting things in this new season.
This season is accompanied by IMPORTANT changes to our interface!
There’s a few more bits of data we think we can pull out of the camera trap photos this time around, in addition to all the great information we already get. One thing we’re particularly interested in is the occurrence of fire. Now, fire is no fun for camera traps (because they tend to melt), but these wildfires are incredibly important to the cycle of ecosystem functioning in Serengeti. Burns refresh the soil and encourage new grass growth, which attracts herbivores and may in turn draw in the predators. We have added a fire checkbox for you to tick if things look hot. Now, because we’re looking for things other than just animals, we replaced your option to click on “nothing there” with “no animals visible“, just to avoid confusion.
Some of the more savvy creature-identifiers among you may have noticed that there are a few Serengeti animals that wander into our pictures that we didn’t have options for. For this new season, we’ve added six new animal choices: duiker, steenbok, cattle, bat, insect/spider, and vultures. Keep an eye out for the following:
This season runs all the way from September 2013 until July 2014, when I retrieved them this summer, my first field season. Our field assistants, Norbert and Daniel, were invaluable (and inhumanly patient) in helping me learn to navigate the plains, ford dry river beds, and avoid, as much as possible, driving the truck into too many holes. Together, we set out new cameras, patched up some holes in our camera trap grid, and spent some amazing nights camped out in the bush.
Once I got the hang of the field, I spend my mornings running around to a subset of the cameras conducting a pilot playback experiment to see if I could artificially “elevate” the predation risk in an area by making it seem as though it were frequented by lions (I’m interested in the reactions of the lion’s prey, and to see whether they change their behaviors in these areas and how long it takes them to go back to normal). I’m more than a bit camera-shy (and put a lot of effort into carefully sneaking up around the cameras’ blind spots) but perhaps you’ll catch a rare glimpse of me waving my bullhorn around blaring lion roars…
Back in the lab, there’s been a multi-continental collaboration to get these data cleaned up and ready for identification. We’ve been making some changes to the way we store our data, and the restructuring, sorting, and preparing process has been possible only through the substantial efforts of Margaret, over here with me in the States, and Ali, all the way across the pond, running things from the Zooniverse itself!
But for now, our hard work on this season is over – it’s your turn! Dig in!
P.S. Our awesome developers have added some fancy code, so the site looks great even on small phone and tablet screens. Check it out!
Formerly titled: I love the Zooniverse, and all its ridiculousness.
Some of you might be familiar with the silly manoeuvres we undertake to trigger the camera traps in the field. The sensors on the cameras are best at capturing movement side-to-side, hence ridiculousness such as this:
Well, fellow Zoo-ites Rob and Grant have now generously attempted their own version of this last one. Check it out on the Zooniverse Advent Calendar here!! And, if you’re feeling especially brave, send in your own recreation to email@example.com!
I am sure you were all enthralled by the recent shots of a male lion with a hyena clamped in his jaw. A truly awesome capture. The reality is that action shots like that are few and far between. Snapshot Serengeti has had only a handful in the millions of images that have been classified to date.
So when Karen and Deon Scheepers caught the following action on camera trap on the nature reserve in South Africa where I used to live I just had to share it with you;
What a capture… a leopard on the hunt. The out come was unknown, reserve staff looked for a carcass but didn’t find anything. To think I used to walk those trails every day, I wonder how many times a leopard walked out behind me!
Thanks Karen and Deon Scheepers for sharing these shots.
So those of you who have read my blogs are probably used to hearing me bemoaning the fact that I am no longer in Africa but am back in France whilst I am studying towards a degree. I can’t really complain, life is still good, but the European wildlife feels a bit lacking when you have been used to the mega fauna of Africa.
I have however continued to put out my camera traps in order to survey my property and the surrounding countryside and it’s busier than you would think. Badgers, foxes, hares, otters, roe deer, squirrels, stone martens and wild boar make regular contact with my paltry two cameras. Not really enough camera power to base a study on but interesting all the same.
The highlight has been the discovery that one little favourite of mine from Africa has followed me to France; the genet. Yes the common genet (Genetta genetta) lives in France and I am ecstatic to say right by my house too.
It seems no-one really knows how they got here but it was probably something to do with the Romans centuries ago being brought over from the Magreb region of North Africa. They are now naturalised animals in Spain, Portugal and France. Refreshingly for an introduced animal they are not invasive and have little impact if any on the native wildlife, so I can go on loving them with a clear conscience.
Here are a couple of shots of genets in France for your enjoyment!
As Meredith posted the other day, one of our camera traps caught a melanistic serval. Melanism is known across a broad variety of animals, but is particularly prevalent in the cat family. Of 37 known species of cat, at least 13 species have melanistic individuals: the domestic cat, the jungle cat, the leopard, the jaguar, the bobcat, Geoffroy’s cat, the kodkod, the oncilla, the colocolo, the jaguarundi, the Asian golden cat, the marbled cat, and the serval.
Why some individuals are melanistic and why cats are particularly prone to melanism is still a bit of a mystery. It is generally thought that melanism is maladaptive – that is, that individuals with melanism are at a disadvantage because they stand out more than normally colored individuals and so are more likely to be targets of predators and competitors. The consequence is that in populations with a lot of melanism, there ought to be some sort of advantage to offset the disadvantage.
One possible explanation for melanism is that cats’ black fur helped keep them warm at higher elevations by absorbing more sunlight. This idea came from the fact that many cat populations with high rates of melanism are found at higher elevations. More recently, there have been studies suggesting that melanistic individuals are more resistant to disease.
There’s not a lot of literature on melanistic servals. But I did find an article in the Journal of East African Natural History that listed the known locations of melanistic serval populations in East Africa. Interestingly, the four main populations with melanism are all highland locations: Mt. Kenya and the nearby Aberdare highlands in Kenya and Mt. Kilimanjaro and North Pare Mountains in Tanzania. All of these are in the general geographic region of Serengeti National Park, so it’s perhaps not too surprising that melanistic servals are there too. What is unusual is that the Serengeti is not a highland.
Our long-term Serengeti experts, with their decades of experience in the Serengeti, are surprised by the melanistic serval snapped by our cameras. David Bygott says that he’s never heard of a melanistic serval in the Serengeti, and Craig Packer says that while he’s seen melanistic individuals of other animals up on the rim of Ngorongoro Crater (a highland), he’s never seen a melanistic serval anywhere. So this Snapshot Serengeti image is likely the only documented evidence of melanistic serval in the Serengeti.
As I’m writing up my dissertation (ahh!), I’ve been geeking out with graphs and statistics (and the beloved/hated stats program R). I thought I’d share a cool little tidbit.
Full disclosure: this is just a bit of an expansion on something I posted back in March about how well the camera traps reflect known densities. Basically, as camera traps become more popular, researchers are increasingly looking for simple analytical techniques that can allow them to rapidly process data. Using the raw number of photographs or animals counted is pretty straightforward, but is risky because not all animals are equally “detectable”: some animals behave in ways that make them more likely to be seen than other animals. There are a lot of more complex methods out there to deal with these detectability issues, and they work really well — but they are really complex and take a long time to work out. So there’s a fair amount of ongoing debate about whether or not raw capture rates should ever be used even for quick and dirty rapid assessments of an area.
Since the Serengeti has a lot of other long term monitoring, we were able to compare camera trap capture rates (# of photographs weighted by group size) to actual population sizes for 17 different herbivores. Now, it’s not perfect — the “known” population sizes reflect herbivore numbers in the whole park, and we only cover a small fraction of the park. But from the graph below, you’ll see we did pretty well.
Actual herbivore densities (as estimated from long-term monitoring) are given on the x-axis, and the # photographic captures from our camera survey are on the y-axis. Each species is in a different color (migratory animals are in gray-scale). Some of the species had multiple population estimates produced from different monitoring projects — those are represented by all the smaller dots, and connected by a line for each species. We took the average population estimate for each species (bigger dots).
We see a very strong positive relationship between our photos and actual population sizes: we get more photos for species that are more abundant. Which is good! Really good! The dashed line shows the relationship between our capture rates and actual densities for all species. We wanted to make sure, however, that this relationship wasn’t totally dependent on the huge influx of wildebeest and zebra and gazelle — so we ran the same analysis without them. The black line shows that relationship. It’s still there, it’s still strong, and it’s still statistically significant.
Now, the relationship isn’t perfect. Some species fall above the line, and some below the line. For example, reedbuck and topi fall below the line – meaning that given how many topi really live in Serengeti, we should have gotten more pictures. This might be because topi mostly live in the northern and western parts of Serengeti, so we’re just capturing the edge of their range. And reedbuck? This might be a detectability issue — they tend to hide in thickets and so might not pass in front of cameras as often as animals that wander a little more actively.
Ultimately, however, we see that the cameras do a good overall job of catching more photos of more abundant species. Even though it’s not perfect, it seems that raw capture rates give us a pretty good quick look at a system.