For some reason I missed this in 2013 and 2014. Maybe it was because I was finishing up my dissertation the first time and then recovering from a cross-country move the second time. But now I am totally excited about 2015’s
What is Mammal March Madness? I’ll let organizer Katie Hinde explain:
In honor of the NCAA College Basketball March Madness Championship Tournament, Mammals Suck is featuring *simulated* combat competition among mammals. … Battle outcome is a function of the two species’ attributes within the battle environment. Attributes considered in calculating battle outcome include temperament, weaponry, armor, body mass, fight style, and other fun facts that are relevant to the outcome.
As a spectator to Mammal March Madness, you fill out a bracket and then follow along on Twitter or on the Mammals Suck … Milk! blog. The first game is on Monday, March 9, and direct elimination games continue until the championship on March 26.
I’ll note that the 2014 winner was Hyena who defeated Orca in the championship game. This year, we’ve got some Serengeti representation as well. But with Lion, Baboon, and Vervet monkey ranked just 8th, 12th, and 13th in the ‘Sexy Beasts’ division, they’re going to need all the cheering-on they can get.
So head on over, print out a bracket, and tell me who you think will make it all the way to the top this year.
(And just to be clear, I am not involved in Mammal March Madness in any way except as a participant. But it looks fun!)
We’re partnering with National Geographic to put together a photo book of animal selfies from Snapshot Serengeti. We’ve got some selfies already from the first seven seasons, but because no one has looked through Season 8 yet, we don’t know what great selfies might be in there.
You can help! If you find an animal selfie, please tag it as #selfie in Talk. (Click the ‘Discuss’ button after you’ve classified the image and then enter #selfie below the image on the Talk page. You can get back to classifying using the button in the upper right.)
All proceeds from book sales will go to supporting Snapshot Serengeti. We’re planning for a fall 2016 publication date, so it will be a while. But we’re excited to get working on it.
It’s been quiet here on the blog, but we’ve been busy behind the scenes. In 2014, we revamped our data management procedures and structures. Season 7 — the one you finished classifying most recently — was the first where images and metadata were fully pre-processed and vetted before being sent to the Zooniverse. This pre-processing makes things much easier on us after we get all your classifications back from Zooniverse. But it does add some lead time.
Season 8 is the first good news. We’ve been pre-processing all December, finding weirdnesses like 84 images in a row all with the same timestamp, miscellaneous video files, timestamps from the future, and so forth. We are just about to start sending the images to Zooniverse, a processes which takes a few days. You should see Season 8 up within a couple weeks. We’ve also tweaked the interface a tiny bit. More on that soon.
The bad news is bad. After waiting since August for a reply from the National Science Foundation about our most recent grant proposal, we finally got it at the very end of December: declined. That means that we are again scrambling to find funds to keep the cameras rolling for 2015. And this time without much warning.
Season 8 is the first half of 2014 and Season 9 is the second half of 2014. Those are already in the bag. The cameras are rolling right now, and so there will be at least something of a Season 10. Worst case scenario is that we have to shut everything down for a while until we get more funding. But Craig is working hard to find interim funds.
The other good news is that we’ve been talking with some other Serengeti researchers who have set up a small camera trap survey in the western part of the ecosystem. They have tons of images and we’re talking with them about putting their images up on Snapshot Serengeti for classification. These images would be of new locations in the Serengeti and potentially a few new animal species. Could be a lot of fun. So even if there’s a pause in our image collection, hopefully we’ll have these other images to classify from the Serengeti that will be useful for ecological research.
We have just been awarded a second Expedition Council grant from the National Geographic Society to extend Snapshot Serengeti until the end of the year. This covers the end of Season 9.
You, our Snapshot Serengeti volunteers, are the people who make this work possible. Your careful classifications provide the necessary rigor to make Snapshot a truly scientific endeavor, and we also rely on your enthusiasm and insights in highlighting the many interesting, intriguing and unusual photos, which will someday be compiled in articles and books.
The following paragraphs are taken from our successful application, and give an overview of Snapshot Serengeti’s success broadly:
Our large-scale camera trap grid provides a continuous record of the abundance and distribution of herbivores, insectivores and carnivores in the northern 1000-km2 of the long-term Serengeti lion study area. The camera traps provide accurate abundance estimates of 20 different herbivore species across the Serengeti and near-perfect measures of lion numbers in the woodlands portion of our long-term study area. The camera traps also reveal that cheetahs are able to coexist with lions by waiting a minimum of 12 hrs after the lions have departed from a particular site and that lions and hyenas largely come into contact with each other as a result of their mutual attraction to wildebeest and gazelle. Our grid also provides a remarkably detailed portrait of the wildebeest migration, showing how movements vary from year to year in response to annual variations in rainfall. Besides providing novel scientific data, many of the camera-trap images are artistic, captivating, breathtaking and hilarious. Because daytime pictures are taken in sequences of three, they can be combined into a brief animation that make the portraits come alive.
The camera-trap imagery has also provided the foundation for a successful online “citizen-science” initiative, called Snapshot Serengeti, where hundreds of thousands of volunteers have counted and identified the animal species captured in over 4,000,000 photographs. We have developed a series of “consensus criteria” for accepting their species identifications, which have 97% accuracy compared to the assessments of a panel of expert field biologists, and our Snapshot volunteers have developed an active online community who share particularly exciting images.
With funding from the Howard Hughes Medical Institute, we have partnered with the College of Biological Sciences at the University of Minnesota to develop an undergraduate laboratory sequence in “Savanna Ecology” where students read relevant articles from the scientific literature, form hypotheses about the behavior and ecology of a species of particular interest, classify and count animals from a random subset of online camera-trap photos, access the overall database, test predictions with simple statistics and present lab reports in a group setting.
Our pre-proposal to extend the camera-trap project for an additional 3-5 yrs has recently been approved by the National Science Foundation, and we will submit the full proposal at the beginning of August. If funded, we will collaborate with National Geographic to submit a proposal to the educational program at NSF to expand the classroom activities of Snapshot Serengeti to middle- and high-school students around the US.
We have discussed the pictorial potential of SnapshotSerengeti with senior staff at National Geographic, who are interested in featuring a selection of Snapshot highlights in a 2015 article for the Magazine and are also considering publishing the Snapshot photos in either hardcopy or as an e-book. Many of the individual photos are stunningly beautiful, and many more have a unique freshness because the animals have no sense of a human presence. The daytime “triplet” animations live and breathe like pictures in a fantasy novel.
Our first Expedition Council grant covered the first 3 mos of a 15-month gap in NSF funding when our most recent NSF grant ended in September 2013. In addition to the first EC grant of $30,000, we raised $55,000 from an Indiegogo crowd-funding effort. A small NSF grant to support my upcoming sabbatical includes a supplementary $25,000 to cover fieldwork in July, August and September. The $30,000 awarded in the second Expedition Council grant assures continuity of the Serengeti studies until the end of December 2014.
For the upcoming NSF renewal, we have assembled a well-regarded scientific team to study the Serengeti food web by integrating the lion tracking and Snapshot cameras with new measurements of grasses and soils. The approval of our NSF pre-proposal means that we have survived the first 75% cut in grant applications, so we have a reasonably good chance of sustaining the project long term. But even if not successful, the extension of the camera traps for another few months will be extremely valuable, as this will be the first opportunity to measure the wildebeest migration during an active El Nino – rainfall in the Serengeti is highly sensitive to the Southern Oscillation Index (SOI), and the short rains of November-December have largely failed during the past 3-4 yrs of La Nina weather patterns.
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.
Hello! I haven’t written in a while. After I defended my dissertation in December, I’ve been busy getting ready to move to the Boston area. I have now started a research position (technically called a “postdoctoral fellowship”) at Harvard University.
In this new job, I am putting together a new citizen science project. This project will help scientists better understand and forecast the effects of climate change on North American trees and plants. We have cameras up throughout the U.S. and Canada taking automatic pictures of forests, grasslands, shrublands, desserts, and even tundra. There are already several years of images recorded, so it’s a great data set to play with.
In order to understand the seasonality of trees and plants, we talk about “phenology,” which is the timing of when trees and plants go through their various life stages. You can think about a maple tree, for example, which puts out leaf buds in the spring, grows those leaves into a full green canopy, then those leaves start to change color, and eventually they all fall off the tree in the autumn. These phenology events define all sorts of processes that are important to people – ranging from how much carbon trees and plants take out of the air to the timing of seasonal pollen release (which you might care about if you have allergies).
Of course, computer algorithms can only do so much, which is where citizen science comes in. The human eye is great at looking at fine details in images and figuring out what’s going on in strange images. For example, one of my colleagues was looking at a measure of greenness in grassland images from Hawaii. This measure was calculated automatically from the images. But something seemed strange. When he went and looked at the individual images themselves, he discovered that there was a common plant that flowered yellow all at once, which changed the greenness in a surprising way.
I’m excited about this new job, but I’m still involved with Snapshot Serengeti. These past couple months, Ali and I have been training Meredith on all the behind-the-scenes image and data processing that goes on both before you see the images and after you’ve classified them. This has slowed down the release of Season 7 (sorry), but ensuring continuity means fewer problems down the line. (By the way, Meredith is a fast learner – it’s just that there’s a lot to learn!) And I’ll still be blogging here periodically.
I’ve had a couple people ask about my dissertation. It’s now published and available online. Note, though, that it doesn’t contain any Snapshot Serengeti content. I was already rather far along in writing it when Snapshot Serengeti launched, so I didn’t have time to include it. We’re working on the first Snapshot Serengeti papers now, though, and we will be sure to let you know when they’re ready to read.
In processing Seasons 5 and 6, I recently stumbled upon a bunch of video files amongst the stills. You may recall that while we have our cameras set to take still images, every once in a while a camera gets accidentally switched to video mode. Then it takes 10-second (silent) clips. Most of these are “blanks” triggered by grass waving in the wind. But every once in a while, we get ten seconds of animal footage. Here are some from Season 5.
And, what do you think this is?
Apologies for such sporadic blog posts recently. We’ve all been quite busy. I successfully defended my dissertation last week. And then I enjoyed the true spirit of Minnesota for the next couple of snowy days, getting to catch up with friends and colleagues whom I haven’t seen in quite some time. But I’m not quite done! I need to make some minor revisions to the dissertation text before submitting it, and this has been occupying much of my time this week, as I need to get it all done before the end of the month – and preferably earlier if I want to enjoy the holidays.
Ali, meanwhile, is deep in analyses of the Snapshot Serengeti data gathered to date. We’re still working on the time issues. If you’ve got crazy Python and/or SQL skills and some free time in the next few weeks, drop us a note. A little help would accelerate Ali’s research while I’m busy finishing up my dissertation work.
And Craig’s diving into the next round of National Science Foundation proposals. The preliminary proposals are due in mid-January and an accepted proposal would restart long-term funding for Snapshot Serengeti starting in 2015. The preliminary proposals are relatively short, but in some ways that makes them harder than the longer ones – we not only have to concisely describe the research, but also convince the reviewers that citizen science yields high-quality data.
While some ecologists are still skeptical of citizen science, more and more are coming to accept it as a valid and valuable way to gather and analyze science data. The astronomy field may be a bit ahead of ecology in this respect, but we’re glad they’re paving the way. And did you hear? The Zooniverse was awarded a $1.8 million Global Impact Award by Google that’s going to allow them to scale up their citizen science platform to host many more projects. I only wonder what citizen scientists will do in the (perhaps not too distant) future, when they have hundreds of citizen science projects to select among. How will you choose which ones to try?
Tomorrow is American Thanksgiving. Whether or not you celebrate Thanksgiving this week, I hope you’re able to spend time with family,
hang out with friends,
find some tasty food to eat,
get some rest,
and give thanks for the good things in life.
And a special thank you from us to you for all the work you’ve put in to classifying animals on Snapshot Serengeti.
Maybe from time to time you’ve wondered: Who are these scientists running Snapshot Serengeti? How did they get where they are? (And why am I sitting here instead of traipsing across the Serengeti myself?)
Ali and I are both graduate students at the University of Minnesota. What that means is that a while ago (seven years for me!) we filled out an application and wrote some essays for admission to the University of Minnesota’s graduate school — just like you would do for college admissions. The difference is that for graduate school, you also need to identify an advisor — a faculty member who will become both your mentor and your judge — and an area of research that you want to pursue. And while the admissions materials matter, it’s very important that your future advisor want to take you on as a student and that your area of research interest meshes well with hers or his.
In the U.S., you can apply for a Masters program or a Ph.D. program. In some places you can get a Masters on the way to a Ph.D., but that’s not the case at Minnesota. So I applied for the Ph.D., got admitted and started as a Ph.D. student in the fall of 2007. I’m pretty much only going to talk about Ph.D.s from here on out. And I should point out that graduate school systems vary from country to country. I’m just going to talk about how it works in the U.S. because I’m not terribly familiar with what happens in other countries.
For the first 2-3 years in our program, students spend much of their time taking classes. These are mostly higher level classes that assume you already took college-level classes in basic biology, math, etc. I came in with an college degree in computer science, and so a bunch of the classes I took were actually more fundamental ecology and evolution classes so I could get caught up. But many classes are reserved for just graduate students or for grad students plus motivated seniors.
At the same time as taking these classes, students are expected to come up with a research plan to pursue. The first couple years are filled with a lot of anxiety about what exactly to do, and there are plenty of missteps. My first attempt at a research project involved tracking the movement of wildebeest in the Serengeti using satellites and airplane surveys. (Yes, you can see individual wildebeest in Google Earth if you hunt around!) But it turned out not to be a logically or financially feasible project, so I discarded it — after a lot of time and energy investment.
Around the end of the second year and beginning of the third year, grad students in the U.S. take what are called “preliminary” or “comprehensive” exams. These vary from school to school and from department to department. But they usually consist of both a written and oral component. In some places the goal of these exams to to assess whether you know enough about the broad discipline to be allowed to proceed. In other places, the goal is to judge whether or not you’ve put together a reasonable research plan. The program Ali and I are in leans more toward the latter. It requires a written proposal about what you plan to do for research. This proposal is reviewed by several faculty who decide whether it passes or not.
If you pass your written component, you then give a public talk on your proposed research followed by a grueling two to three hour interview with your committee. In our program, students choose their committee members, following a few sets of rules about who can be on it. My committee had five people, including my two advisors. They took turns asking me questions about my proposed research, how I would collect data, analyze it, how I would deal with adversity. The committee then met without me to decide whether I passed or not. (spoiler: I passed)
So, assuming a student passes the preliminary exams, she or he is then considered a “Ph.D. Candidate,” which basically means that all requirements except the actual dissertation itself have been fulfilled. If you’ve ever heard the term “A.B.D.” or “All But Dissertation,” that is what this means. The student got through the first hurdles, but never got a dissertation done (or accepted).
Now it’s time for the research. With luck, persistence, motivation, and lack of confounding factors, a student can do the research and write the dissertation in about three years. Doing research at first is slow because, like learning anything new, you make mistakes. I spent a lot of time gathering data that I’m not going to end up using. Now that I’ve been doing research for a few years, I can better estimate which data is worth collecting and which is not. And so I’m more efficient. While doing research, the student is also reading other people’s related research, and often picking up a side-project or two.
Eventually, the student, together with the advisor(s) and committee members, decides that she or he has done enough research to prove that she or he is a capable professional scientist. All the research gets written up into a massive tome called the dissertation. These days, it’s not uncommon for graduate students in the sciences to write up their dissertation chapters as formal papers that then get published in scientific journals. Sometimes one or more chapters is already published by the time the dissertation is submitted.
When the writing of the dissertation is finished, it gets sent to the committee to read. The student then gives a formal, public talk on the results of the dissertation research, followed by another two to three hour interview with the committee. This time it’s called the “Dissertation Defense,” and the committee asks questions about the research results (and possibly asks the student to fight a snake). The committee then meets without the student and comes up with a decision of whether the student passes or not. There is also often a conditional part of this decision that requires some portion of the dissertation to be revised or added to. So, a decision of “pass, conditional on the following revisions:” is pretty common.
I should mention that while being a grad student has been mostly quite fun, you may not want to drop your day job and run off to academia just yet. There’s the issue of funding. On the plus side, you can acquire funding in the sciences so that you don’t have to take on debt to do your degree (which is not so true in the humanities). Ali and I have both applied for and received fellowships that have allowed us to do most of our graduate program without having to work. But many — maybe most — grad students in the sciences work essentially part-time jobs (20 hours/week) as teaching assistants for faculty. This can really slow down research progress, as well as making some types of research impossible (for example, those that require lengthy trips to the Serengeti). Whether working or on fellowship, students typically gross no more than $30,000 annually, and often less than $25,000, which can be quite reasonable (single person living in a low-cost-of-living area) or prohibitive (person supporting a family living in a high-cost-of-living area). Benefits are pretty much non-existent, with the exception of health coverage, which can range from great (thanks, Minnesota!) to really bad to non-existent.
I mention all this this because I am about to defend my dissertation! In a little less than two weeks I will give a talk, sit down with my committee, and try to convince them I’m a decent scientist. Wish me luck.