Thanks to you, we’ve already plowed through the entire “lost season” of Snapshot Serengeti. Granted, it was pretty small – only about 16,780 or so subjects, but you guys really knocked it out of the park.
So, first, let me say THANK YOU for your help!! It’s always such a thrill to announce a new season of data, and then watch that progress bar blast forward.
Second, speaking of progress bars, some of you have noticed that this progress bar went from zero to gone in, well, no time at all. Turns out we had a small bug in our code that meant we couldn’t see the progress bar advance. So finishing the lost season really took us by surprise too.
Third, if you feel like you’ve gone all excited by a new season to classify, only to have it ripped away, I promise that things will get better soon. We’ve now finished the major pre-processing for Seasons 9 and 10, and just need a couple weeks of minor pre-processing/porting to the Zooniverse. We’ll get them up online in early 2016 and you can classify to your heart’s content. Hopefully it will be something to cheer us all up as we return to work after the holidays. Seasons 9 and 10 are both really big, so there’s no risk you’ll miss out on them!
In the meanwhile, if you need an animal fix, Chicago Wildlife Watch could use your help!
Over the last few years, you’ve helped us identify almost 2 million photos (since there are often multiple frames per “subject”, that’s actually about 5.5 million individual frames!). And you might remember that a few months ago the first 1.2 million of those were just made available to researchers everywhere. But along the way, a few (thousand) photos fell through the cracks for one reason or another. Some sites didn’t get uploaded because of a quirk in the file structure. Some SD cards were corrupted and only months later the brilliant UMN IT department was able to recover the photos. Whatever the reason, we’ve accumulated 16,780 capture events that we’ve called “The lost season” — and we’ve added those images to the site today!
It’s a bit of a blast from the past — most of the images were taken in Seasons 3 and 4. But they’ve never been seen before…so go check it out! Who knows what you’ll find!
This week we have a guest post from herpetologist and Zooniverse volunteer Steve Allain (find him as “The Newt Guy” on Zooniverse), who has used Snapshot Serengeti data (available here) to dig a little deeper into our little-studied reptiles. Steve is a zoology graduate from Anglia Ruskin, Cambridge and has a particular passion and focus on British amphibian and reptile species. He is the current chairman of the Cambridgeshire and Peterborough Amphibian & Reptile Group (CPARG) where he helps to organise and coordinate a number of amphibian and reptile surveys around the county to map the distribution of amphibians within Cambridgeshire. More recently Steve has joined the IUCN SSC Amphibian Red Listing Authority as an intern.
In the summer of 2014 I visited Tanzania and went on a tour of the north of the country visiting such places as Arusha, Mount Meru, Ngorogoro Crater and the Serengeti. Before I went, I prepared myself for the wildlife I would encounter by helping out with the Snapshot Serengeti project. As a herpetologist (someone that studies amphibians and reptiles) I was not familiar with the mammalian fauna of Africa apart from the large and obvious animals that you are taught as a child. When I was in Africa, the identification skills I’d learnt through helping with the project really did pay off when it came to narrowing what species we had seen.
Recently I was reading a scientific paper regarding the monitoring of Komodo dragons using camera traps; this is an unusual method as reptiles generally don’t trigger camera traps due to their biology. I pondered some thoughts for a while and then it suddenly dawned on me that I knew of a project that had recently published a large amount of data from which I could filter out when reptiles had been captured by the camera traps. I decided to get in contact with some of the people involved with Snapshot Serengeti to help me get started.
One of the main questions that I have is when is the most likely time to capture a reptile on a camera trap, be it a snake or a lizard etc.? Is it in the morning or the afternoon? With the data published by the Snapshot Serengeti project I have been investigating this by first identifying all of the trapping events which contain reptiles. The original project identified 131 events which have been a good baseline to work from but with some extra digging I have identified another 120 events and I’m only just getting started.
Once I have a list of all of the trapping events, I intend to collate the data relating to my first question using time stamps as well as identifying which species are present. There are other questions which I am still formulating and so far most of the animals I’ve managed to identify have been species of rock lizard which like to bask on rocks and outcrops called kopjes. I’m hoping that my findings will be able to inform scientists in the future about the possibilities of using camera traps for studying the behaviour and distribution of reptiles over a large area.
We know you’re eager to get back to classifying wildebeest and other crazy critters, and good news is that Meredith has recently returned from the field with the next instalment of Snapshot Serengeti! So get ready! But we’re still in the process of uploading the photographs, checking timestamps, and doing all the other tedious but necessary pre-processing, and it will be a few more weeks before we get the next season online.
So while you’re waiting, why not checkout the Zooniverse’s newest camera trapping project: Wildcam Gorongosa?
Nestled in nearby Mozambique, Wildcam Gorongosa was developed as a joint effort between the Howard Hughes Medical Institute Biointeractive Program, the Gorongosa Restoration Project, and, of course, the Zooniverse. Previously decimated by almost 20 years of civil war, Gorongosa National Park wildlife is rebounding thanks to an enormous conservation initiative. As part of that initiative, researchers have set out a grid of cameras, much like ours in the Serengeti. And now they need your help to identify the animals caught on their cameras. While many of the animals present in Gorongosa are the same as in Serengeti, they also have some critters we don’t: otters, nyala, oribi, and – my personal favorite – African wild dogs.
Zooniverse is currently looking for a front-end developer to join the Oxford team. The key aim of the position is to help build data querying and visualization tools for educators and researchers, and, well, everyone, to better explore and engage with data from Snapshot Serengeti-style projects.
More details can be found here.
We are accepting applications *now* until August 10, so please share this with anyone you know who might be interested.
Can’t get enough of these gnarly gnus? Head on over to our new spinoff project, Wildebeest Watch!
In collaboration with Dr Andrew Berdhal from the Santa Fe Institute, and Dr Allison Shaw at the University of Minnesota, we are taking a closer look at what the wildebeest are doing in the Snapshot Serengeti images to try and better understand the details of the world’s largest mammal migration.
Every year, 1.3 million wildebeest chase the rain and fresh grass growth down from the northern edge of the ecosystem down to the short grass plains in the southeast. We have a broad-scale understanding of where they are moving across the landscape, but don’t understand how they make these detailed decisions of where and when to move on a moment-to-moment basis. Wildebeest as individuals aren’t known for being particularly smart — so we want to know how they use the “wisdom of the crowd” to make herd-level decisions that get them where they need to go.
So while you’re waiting for more photos of lions, hyenas, and other sharp-toothed beasts, why not wander over to Wildebeest Watch to help us understand the collective social behavior of these countless critters?
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!
Champagne corks will be popping tonight. Snapshot Serengeti’s first peer reviewed scientific publication comes out today in Nature’s Scientific Data journal. Please give yourselves a round of applause, because we’d never have been able to do this without you.
The paper is a “data descriptor” instead of a traditional research article, meaning that we describe the detailed methods that led to the Snapshot Serengeti consensus dataset. In addition to describing all the excrutiating details of how we set the cameras in the field, we talk about the design of Snapshot Serengeti, setting retirement rules and aggregation algorithms to combine all of our answers into a single expert-quality dataset. We don’t talk about the cool ecological results just yet (those are still only published in my dissertation), but we do talk about all the cool things we hope the dataset will lead to. The dataset is publicly available here. Anyone can use it — to ask ecological questions about Serengeti species, evaluate better aggregation algorithms for citizen science research, or — we get this a lot — use the images plus consensus data to train and test better computer recognition algorithms.
Feel free to download the dataset and explore the data on your own. We’d love to hear what you find!