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Getting good data: part 1 (of many)

Despite the site being quiet, there’s a lot going on behind the scenes on Snapshot Serengeti at the moment. Season 8 is all prepped and currently being uploaded and should be online next week! And on my end, I’ve been busily evaluating Snapshot Serengeti data quality to try and develop some generalisable guidelines to producing expert quality data from a citizen science project. These will actually be submitted as a journal article in a special section of the journal Conservation Biology, but as that is a slowwwwwww process, I thought I’d share them with you in the meanwhile.
So! Recall that we use a “plurality” algorithm to turn your many different answers into a “consensus dataset” — this has one final answer of what is in any given image, as well as various measures of certainty about that image. For example, back in 2013, Margaret described how we calculate an “evenness score” for each image: higher evenness means more disagreement about what is in an image, which typically means that an images is hard. For example, everyone who looks at this photo
would probably say there is 1 giraffe , but we’d expect a lot more diversity of answers for this photo:
(It’s a warthog, btw.)
To test how good the plurality algorithm answers were, we created a “gold-standard dataset” by asking experts to identify ~4,000 images. Overall, we found that consensus answers from your contributions agreed with experts nearly 97% of the time!  Which is awesome. But now I want to take a closer look.  So I took all the images that had gold standard data and I looked at Evenness, Number of “nothing here” responses, and %support for final species, and evaluated how those measures related to whether the answer was right or wrong (or, impossible). Even though we don’t have an “impossible” button on the SS interface, some images simply are impossible, and we let the experts tell us so so these wouldn’t get counted as just plain “wrong.”
A note on boxplots: If you’re not familiar with a boxplot, what you need to know is this: the dark line in the middle shows the median value for that variable; the top and bottom of the boxes shows the 25 and 75 percentiles; and the “whiskers” out the ends show the main range of values (calculated as 1.5 * interquartile range, details here). Any outliers are presented as dots.
Evenness: The boxplot below shows the mean “Evenness” score described above vs. how the consensus answer matched the gold standard answer.   What you can see below is that the average evenness score for “correct” answers is about 0.25, and the average evenness score for wrong and impossible answers is 0.75. Although there are some correct answers with high evenness scores, there are almost no wrong/impossible answers with evenness scores below 0.5.
 EvennessVsAccuracy
Percent Support: This number tells us how many people voted for the final answer out of the total number of classifiers. So, if 9 out of 10 classifiers said something was a giraffe, it would have 90% support. It’s similar to evenness, but simpler, and it shows essentially the same trend. Correct answers tended to have more votes for what was ultimately decided as the final species.
PercentSupport
NumBlanks: So with the evenness and percent support scores, we can do a decent job of predicting whether the consensus answer for an image is likely to be right or wrong. But with Number of Blanks we can get a sense of whether it is identifiable at all. Margaret noticed a while back that people sometimes say “nothing here” if they aren’t sure about an animal, so the number of “nothing here” votes for an image ultimately classified as an animal also reflects how hard it is. We see that there isn’t a huge difference in the number of “nothing here” answers on images that are right or wrong — but images that experts ultimately said were impossible have much higher average numbers of “nothing here” answers.
 NumBlanksVsAccuracy
So, what does this tell us? Well, we can these metrics on the entire dataset to target images that are likely to be incorrect. In any given analysis, we might limit our dataset to just those images with >0.50 evenness, or go back through all those images with >0.05% evenness to see if we can come up with a final answer. We can’t go through the millions of Snapshot Serengeti images on our own, but we can take a second look at a few thousand really tricky ones.
There’s all sorts of cool analyses still to come — what species are the hardest, and what’s most often mistaken for what. So stay tuned!

Good news, bad news, good news, 2015 edition

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.

The predator of my predator is my friend.

If you’re a prey animal, you spend an awful lot of your time trying to not wind up like this:

lions_ngm_0813_006_brnd

 

As we’ve talked about an awful lot on this blog (here, here, and here, for example), the same holds true for a lot of predators. Just because you kill and eat other animals, doesn’t mean you don’t have to worry about being killed yourself (as this hyena so unceremoniously discovered).

But, what we haven’t talked so much about, is that the same holds true for plants. If you’re a plant, you get eaten by these terrifying animals:

But, just like prey animals and mesopredators can change their behaviour to minimise the risk of being killed, plants have a few tricks up their sleeves. They can spend a lot of energy growing big thorns, for example, that makes them less delectable.

Or! They can grow in places that their predators avoid — the places where their predators’ predators hang out. Got that?  It’s a trickle-down landscape of fear, which had, until now, only been really well documented in small experimental systems with critters like spiders and grasshoppers. But researcher Dr. Adam Ford and colleagues just published an elegant paper in Science showing that leopards and African wild dogs can make the Kenyan savanna less thorny through this cascade. Basically, leopards and wild dogs eat impala. Impala eat Acacia trees. Impala much prefer to eat acacias with fewer thorns (because really, who doesn’t?) – and, if given the opportunity, impala will can eat these small-thorned acacias so much that they can suppress the acacia population.

But! Leopards and wild dogs seem to be offering these tasty small-thorned acacias a refuge. Leopards and wild dogs spend most of their time in denser thickets, where they have more cover to hunt. Impala avoid these thickets and rarely venture in —  when they do, however, they have a much higher probability of being killed. And this creates this spiral – those tasty small-thorned trees survive and grow in these thickets because predators scare impala away.

So it’s a trickle down landscape of fear – a compelling and really exciting story. But, what sets Adam’s paper apart from many other attempts to document this effect in large predators, is the series of elegant experiments in which he and colleagues explicitly tested each step in this cascade.  Controlling for habitat use to confirm that impala aren’t getting killed in the woods simply because they spend more time there (and in fact, they get killed more even though the spend less time there). Adding and removing thorns to acacias to see if it was really the thorns that mattered. Creating herbivore exclosures to measure whether impala could really suppress acacia density. I spent my entire time reading the article alternating between saying “This is so cool!” and “I am so jealous!” It’s an amazing story. Read more about it here (or here, or or here)!

 

Zooniverse advent calendar

At the Zooniverse, we love any excuse to have fun, be festive, and highlight cool things from our awesome projects. Check out the Christmas countdown Advent Calendar at https://www.zooniverse.org/advent!

Welcome Darren

Darren, our new Community Builder

Darren, our new Community Builder

Hey everyone – I just wanted to introduce you to one of the Zooniverse’s newest members, Darren McRoy, who is our new Community Builder. 

As Community Builder, Darren serves as the Zooniverse’s liaison with its citizen science community, including Snapshot Serengeti. He also assists with Zooniverse’s general communications efforts and is working closely with designers and developers on the next generation of the Talk discussion system.

Darren is a 2010 graduate of the Medill School of Journalism at Northwestern University and has a background in journalism and digital communications. He is a resident of the northern Chicago suburbs, and enjoys golf, volleyball, fiction writing, gaming, and participating in a variety of online communities.

Darren can be reached at darren@zooniverse.org, and posts on Talk under the handle “DZM.” Please feel free to get in touch with him if you have any thoughts, comments, questions, etc about how the Zooniverse communicates with its community — you!

Serengeti Lions win Wildlife Photo of the Year award!

lions_ngm_0813_006_brnd

You might remember that National Geographic did a big story on “our” lions last year. David Quammen spent a while being bounced around in our land rovers and Nick Nichols and his crew spent months on end camping in the southeastern corner of our study area, following the Vumbi pride’s every move.

Well, one of Nick’s pictures from that trip has just won him the prized Wildlife Photographer of the Year award!   The competition, co-run by London’s Natural History Museum and the BBC, has just turned 50 years old, and is a pretty big deal (you can read about it here). Nick’s winning piece is a black and white photo of the Vumbi pride sprawled in rather epic fashion over the kopjes. We can’t post the picture here for copyright purposes, unfortunately, but go check it out!  And go check out some of the other fantastic runners-up here while you’re at it.

 

 

Cheetahs rocking the boat…again!

Cheetahs, it seems, just can’t stop shattering everything we believed to be true about them.

Scientists have long believed that lions (and hyenas to some extent) threaten cheetah conservation efforts —  in large part because they kill so many cheetah cubs. But last year, researchers from South Africa revealed that lions probably don’t kill as many cheetah cubs as folks previously believed. And shortly after that, our research showed that regardless of the amount of lion-inflicted cheetah cub mortality, cheetahs do just fine around large lion populations.

Just last month, another story broke that shakes up how we think about cheetahs. It turns out that not only are cheetahs not as vulnerable to killing by lions, but they cheetahs aren’t nearly as vulnerable to non-lethal bullying either. It was thought that because cheetahs couldn’t fight back against lions – or hyenas – they lost a lot of their hard-earned kills to these ruthless scavengers. (Yes, both lions and hyenas do steal food from each other and from cheetahs.) We knew that wild dogs expend so much energy hunting that they can’t afford to lose even moderate levels of food, and assumed that cheetahs were similarly vulnerable. But, as a recent study from Bostwana and South Africa found out, they aren’t.  It turns out that despite being super fast, cheetahs don’t expend all that much energy chasing down their prey. Researchers estimate that cheetahs could lose a full 50% of their kills to lions and hyenas, and still get all the calories they need!

All in all, it’s beginning to look a lot like the biggest threats to cheetahs aren’t lions and hyenas. Instead, availability of denning sites (as suggested by our research) and human destruction of habitat that forces cheetahs to travel far and wide in search of prey (suggested by this most recent study) are probably much, much greater threats to their survival.

 

Tidbits on wild dogs

One of our long-time Snapshot Serengeti members (thanks Reid!) sent me this NY Times article on African wild dogs. As you know, we don’t have wild dogs in the study area (though keep your eyes peeled! TANAPA did reintroduce them into the western corridor the other year, and I keep hoping we’ll catch one traveling through our grid).

But I am very interested in how dogs interact with the larger carnivore community. And these animals are just *so* cool – incredibly energetic and full of nerve. Watching a small group of dogs defend their kill against a hunting party of hyenas was one of the highlights of my trip to South Africa in June.

Photo by Ingela Jansson

Photo by Ingela Jansson

The article points out that wild dogs may fare better when lions fare worse (which I’ve reported on here) — and that raises some questions about questions about how to target conservation efforts. Do we have to choose between which species to protect? I’d say “not necessarily.” My dissertation research suggests that although dogs fare worse in small reserves with lions, there are places where wild dogs seem to do just fine. Selous Game Reserve (TZ) and Kruger National Park (SA), for example – big areas that have complex habitat structures. So the answer to protecting the entire carnivore guild may lie in larger, diverse reserves.

There are currently efforts in place to do create a protected area the size of Sweden that spans five southern & east African countries. If successful, according to the NY Times, the Kavango-Zambezi Transfrontier Conservation Area will be the largest terrestrial protected area in the world. Now that’s something to celebrate.

Back from the field!

Hi guys! Sorry for the long hiatus on my front. Africa was just as exciting and frustrating and marvelous and difficult as I had imagined it would be, and I’m missing it terribly. I made it back to the US just a week or so ago, my suitcases full of lion manes, camera traps, dead telemetry equipment for repair, and several very important hard drives full of new data to analyze! It’s going to be a busy semester synthesizing everything I learned this summer and planning ahead for the next go around.

Coming home from the field for me typically means a week of celebratory eating (ice cream for breakfast! fruits all day every day!), celebratory showering (hot water! running water!), celebratory lavatory use (it flushes!), among other things. This time, though, I’ll have to admit that even these luxuries didn’t soften the blow of leaving.

(Impending statistics classes awaiting me in Minnesota probably didn’t help either).

There is one primary advantage to coming home, the one thing that makes me appreciate every day that I’m back, and it the fact that for a few blissful months, I will no longer have to deal with these little devils:

P1140874The Tsetse Fly: Evil on Wings

Good riddance, tsetses! Hello, Minnesota!

 

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