Snapshot Gems
Whilst we wait for season 12 of Snapshot Serengeti to be launched we have put together some of the great images from the previous seasons. Snapshot Serengeti has been going for eight years with its 200+ camera-traps never sleeping (except for the occasional malfunction/animal destruction). Its just possible that you may have missed some of these great images during that time, so sit back and enjoy.
Machine learning and citizen science…a winning combination!
Hartebeest through a dislodged camera-trap cover.
* Sarah Huebner, who heads up the Snapshot Safari team has written the following blog to give all participants of Snapshot Safari projects the low down on machine learning advances that are being introduced today*
In the era of Big Data, when equipment allows us to collect data faster than we assess it, researchers are always looking for ways to enhance and accelerate the process between data collection and analysis. We here at Snapshot Safari are proud to have been the first camera trapping project partnering with citizen scientists on Zooniverse when we introduced Snapshot Serengeti, and to have expanded that model from one African park to dozens. Now we hope to improve the data pipeline once again by integrating machine learning to reduce the amount of volunteer effort required to classify data from our participating sites.
‘Machine learning’ refers to Artificial Intelligence algorithms that have been trained for a specific task or purpose. These algorithms are fed millions of images labeled with their correct names and are ‘trained’ to recognize those animals again in different settings. These models generate ‘predictions’ based on the training they’ve received and provide confidence levels to let us know how sure they are that is the correct label. Because Snapshot Serengeti has been running since 2010, it has generated millions of images over the years, which make a perfect training dataset for machine learning (ML) algorithms. We are employing ML models to drastically reduce the effort required to retire empty images (no animals present) and to retire images of common animals like wildebeest and zebra.
First, our ML models have become quite good at telling us whether animals are present or not. This helps us to more easily spot cameras where vegetation has grown in front of the lens, resulting in hundreds of pictures of grass blowing in the wind. Pretty, but not quite what we’re after, so we can eliminate those prior to upload. Secondly, we have modified the retirement rules on Snapshot projects (implemented starting today as new seasons are launched) so that only two volunteers need to confirm the computer’s prediction of ‘empty’. This means instead of 10 or even 20 people viewing those photos, only two people will see them and can push them out of the dataset quickly.
Those of you who have been working on this project for a while know that the wildlife you’re most likely to see are zebras and wildebeest, and you all are great at identifying those! Because those are easy identifications, they too will retire with fewer views than before. What this means practically is that you should see more images of rare and cryptic species like predators and fewer blank images. We have implemented a number of retirement rules behind the scenes to make this happen, based on varying confidence levels produced by the algorithm. For example, our simulations have proven that even at only 50% confidence, the computer is right 99.6% of the time when it tells us that an image is empty. Therefore, any ‘empty’ prediction with confidence of 50% or more will only need two human views to confirm that the computer is correct. Likewise, if the model tells us that it’s a human with a confidence level of 80% or higher, we will retire with just two confirmations.
We will continue to improve the algorithm’s capabilities by using our most valuable asset—all of you! We hope that you will be as interested as we are in advancing the use of ML to make the classifying process more fun and satisfying. The algorithm is pretty good at species, but now we need to improve its ability to count animals, so we will soon be introducing a special project, ‘Snapshot Focus’, which will feature images the algorithm has reviewed and marked each animal with a bounding box. We will ask you to tell us whether the ML model got it right. Stay tuned for that and other special projects!
We are launching three new sites today—Camdeboo National Park, Kgalagadi Transfrontier Park, and DeHoop Nature Reserve, all from South Africa. These three projects have the new retirement rules in place, as will Season 12 of Snapshot Serengeti, which will launch in June. As new seasons or new projects come online, they will be set up with these rules and perhaps more as we refine the data pipeline. Let us and the moderators know how it goes. We are so thankful for your efforts and support, which help us to return data to our collaborators at reserves in Africa quickly and with confidence that it is correct thanks to the combination of citizen science and machine learning. Happy classifying!
-Sarah Huebner
Research Manager, Snapshot Safari
May 28, 2019
For more information about the machine learning algorithms created using Snapshot Serengeti images, see:
Willi, Marco, Pitman, Ross Tyzack, Cardoso, Annabelle W., Locke, Christina, Swanson, Alexandra, Boyer, Amy, Veldthuis, Marten, and Fortson, Lucy. (2019) Identifying animal species in camera trap images using deep learning and citizen science. Methods in Ecology and Evolution 10(1):80-91.
Norouzzadeh, Mohammad Sadegh, Nguyen, Anh, Kosmala, Margaret, Swanson, Alexandra, Palmer, Meredith S., Packer, Craig, and Clune, Jeff. (2017) Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning. Proceedings of the National Academy of Sciences 115(25):E5716-E5725.
To read about how algorithms make decisions in comparison to humans, see:
Miao, Z., Gaynor, K.M., Wang, J., Liu, Z., Muellerklein, O., Norouzzadeh, M.S., McInturff, A., Bowie, R.C., Nathon, R., Stella, X.Y. and Getz, W.M. (2018) A comparison of visual features used by humans and machines to classify wildlife. bioRxiv, p.450189.
Ostrich
Whilst we are waiting for the next season of Snapshot Serengeti images I have been reviewing some of the amazing images that season 11 turned up. I always have to remind myself that these cameras do not have some avid photographer sat behind them snapping away at the opportune moment but are activated merely by sensing a change in heat within their detection zone. It is truly amazing how often we get stunning images.
Here a beautiful male ostrich struts across the field of view showing off his amazingly pink legs. The bare parts of male ostrich are usually a pale grey to pink colour but during the breeding season hormones influence the pigmentation and a flush of red blazes through his neck and legs. Given the extent of these legs and neck contrasted with the bold black and white feathers it makes for an arresting sight. Compared with the drab browny grey of the female the male is a real show off.
What’s strange about this scenario is that in most bird species where the male changes feather of bare parts colour it is the female alone that rears the chicks. The colourful male would perhaps attract too much predator attention around the vulnerable nest or chicks. In ostrich though, the male takes his share of sitting on eggs and looking after chicks. In fact he and his primary female will take turns incubating a clutch of eggs that typically include both hers and other females eggs so he will generally have more invested in the chicks as a direct parent than the female who may only be ‘aunt’ to some of the chicks.
I guess the shear size, power and speed of the ostrich, who is perfectly adapted to the open plains of the Serengeti, means he can afford the fancy show of pink legs if it means winning the ladies.
Wondering About African Wild Dogs
African Wild Dog Photo Credit Pexels from Pixabay
The Serengeti is renowned for being one of the few relatively intact large ecosystems remaining in the world. Sure, it isn’t without its problems, nowhere, not even protected areas (PA’s), are exempt from the onslaught of effects from humans either directly on the ground or through climate change but in general the health of the Serengeti is robust.
So why is it in this well balanced, large ecosystem that we don’t ever see African wild dogs (Lycaon pictus) on the Snapshot Serengeti cameras? Of course, African wild dog numbers everywhere are low even within (PA’s) but they are part of the carnivore guild alongside lion, leopard, hyena, cheetah in most of the big PA’s like South Africa’s Kruger National Park and Botswana’s Okavango Delta. So why not the Serengeti National Park (SNP)?
Not so long ago wild dog were present in the SNP in small numbers. In 1970, when studies began, there were an estimated 95 individuals in 12 packs. They were studied sporadically until 1991 when all 12 packs had seemingly died or disappeared. Here in lays the mystery, what killed them?
At the time the rapid disappearance of the wild dogs coincided with a renewed period of research that saw individuals from several packs immobilised and fitted with radio collars. The research community at the time were baffled and a hypothesis was proposed by Roger Burrows that implemented researchers handling of the dogs as being causal to their decline, the theory being that the stress imparted to the animals made them susceptible to rabies which eventually killed them. It is a controversial hypothesis and has had the research community at each other’s throats for the last 25 years. Some argue that invasive handling of study animals is un-ethical and can lead to tragic outcomes (as hypothesised by Burrows for the African wild dog) others argue that collaring and taking blood samples from study animals is vital to understanding processes which effect conservation management.
A recent paper by Jackson et al, “No evidence of handling‐induced mortality in Serengeti’s African wild dog population” an open access paper published in Ecology and Evolution, revisits the question and aims to shed new light on the argument with research.
I am not trying to weigh in on the argument, my expertise is inadequate for that but I thought it was an interesting take on the question of wild dog in the Serengeti and it used data generated by Snapshot Serengeti, all be it in a small way, to help with its argument.
Surrounding the eastern side of the SNP are two PA’s, the Ngorongoro Conservation Area (NCA, a multi use area occupied by a large population of Maasai pastoralists) and Loliondo Game Controlled Area (LGCA, a multi use area with some settlements, hunting and tourist concessions.) One would argue that these areas are not as pristine as SNP itself with a good dose of human impact but the wild dogs have been studied here since 2005 and as of 2017 there was an estimated population of 120 individuals in 10 packs.
Collaring has shown that the wild dogs do venture back to the Serengeti plains from time to time (proving there is no physical barrier to dispersal) but that they do not settle there, choosing instead to stay in an environment where one would imagine it was harder to survive on the periphery of human habitation. Our own Snapshot Serengeti work comes in to play here to prove that even with an extensive network of cameras that have been in operation for several years no wild dog has been recorded in SNP.
So what do Jackson et al imagine could be the route cause if not the direct handling leading to stress related rabies outbreaks hypothesis.
The team have studied wild dogs for over a decade in areas adjacent to SNP that arguably have an equal or higher rabies risks (think of the domestic dogs associated with people) to the SNP. They have used the same invasive methods of study as the SNP researchers including using intervention to fit collars, take blood and in one incidence an attempt at relocation back to SNP. They believe that they have the perfect scenario in which to test the hypothesis.
They found, in contrast to the earlier study which saw the entire population disappear, that 12 month survival rate in handled wild dogs was 87.6% and in a group of 67 wild dogs captured and translocated back to SNP, held for almost a year in translocation enclosures, a long term stress situation, 95.5% survived over 12 months. Incidentally, most of the relocated dogs did not stay in the SNP, returning to the adjoining PA’s. One pack did remain but not in the former study area of grassland plains but rather in a rugged area just outside the original study area.
The team argues that the wild dogs in both NCA and LGCA have been subject to handling just as much as the original study yet have shown a population increase, secondly, there has been no repopulation of the original study area either naturally through dispersal nor through attempted reintroduction something that arguably should have happened if the only reason for the die off was human induced.
Instead they believe that the demise of the wild dog coincided with a rise in lion and hyena numbers on the plains of the Serengeti. Wild dog are killed by these predators but perhaps more importantly they also have their hard earned prey stolen from them by larger predators. Their theory is that the competition from increasing lion and hyena numbers as well as out breaks of rabies and canine distemper saw the death of some packs and the dispersal into the adjoining PA’s of the rest. Compared with the endless grassy plains of the Serengeti, the NCA and LGCA are much more varied terrain with a mixture of hilly, rocky areas as well as open woodland and open grassland. This kind of mosaic gives wild dogs a much better chance of avoiding larger more dominant predators and so their chance of survival is greater.
So could this be why we see no wild dog in our camera traps. Whatever the reason it highlights that even with what we imagine as well protected areas the space we have left for wildlife is minimal and to protect a wide range of biodiversity we should be doing more to protect a wide range of ecosystems and habitats.
If you want to read the Jackson paper you can find it here: https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.4798
There are links within the paper to the original Burrows work so you can get a feel for both sides of the story.
Machine Learning Update
Hartebeest through a dislodged camera-trap cover.
It has been just over a year now since Snapshot Safari was launched. Snapshot Serengeti as the original Zooniverse citizen science camera trap project has remained the flagship project but there are now several other projects under the Safari banner.
One of the good things about joining forces with all these other projects is that collaboration tends to bring perks that operating on your own doesn’t. For example, different areas of expertise that some of us would just never have thought of, being somewhat far from the mind of field researchers and ecologists.
I am talking about the computer learning side of things, ML (Machine Learning) in particular. The team behind Snapshot Safari have been working hard on this aspect essentially to help speed up the rate of classification needed now that there is so much data across different projects.
They have recently engaged a specialist in machine learning at the University of Minnesota who is helping them to develop ML for use with the Snapshot Safari projects.
The idea is to run an algorithm on the data prior to uploading it to the Zooniverse, this will identify most of the misfire and vegetation only images meaning us volunteers will be left with more of the good stuff, the actual animal images.
The algorithm has been trained on millions of images from Snapshot Serengeti, now for these latest batches the team have asked the ‘machine’ to predict which species it is seeing, how many and what the behaviour of the animals is. Don’t panic we really are in the early stages and the idea is to compare what it came up with against the actual results from the volunteers whom we already know are pretty darn accurate. The team doesn’t expect great things yet from the ML and doesn’t foresee computers taking over any time soon but it will be interesting to see how the ML goes.
So, for now things will be continuing as normal, no changes in how you classify or what you do but hopefully there will be fewer blank images with no animals. As the team stresses, they are a looonnng way from machines taking over.
For those of you who enjoy being part of this developmental side of the project the Safari team will soon be launching a side project called Snapshot Focus. It is designed to also look at how well the ML is at recognising animals in trickier images, especially those with multiple animals. If you feel like helping out as a break from the usual work flow it couldn’t be simpler. All you have to do is answer yes/no as to whether the computer has managed to put a bounding box around every animal in the image.
Look out for updates from the team over the coming months to learn more about these developments but meanwhile there are still lots of images to classify on Snapshot Serengeti.
The Lone Lion
Kalamas and Lakes pride female Photo Credit: KopeLion, Ingela Jansson
It seems as though when it comes to lion ecology most of the experts seem to agree that male coalitions are usually the most successful at holding on to females and siring cubs. Certainly when take-overs happen it is usually the coalition with more members that wins the day and lone males find it hard to stand their ground. Numbers seem to count.
Of course that isn’t to say that single males can’t have fun or success. Take Kalamas, a male known to us in the Ngorongoro Conservation Area. He is a nomadic male who wanders far and wide across the area even daring to take trips into the Crater itself, an area that in terms of lions is heavily defended by resident males, competition is very strong there and really not a place for a none resident lone male to be seen.
So what is so different about Kalamas. Well firstly he doesn’t seem concerned about the competition. Earlier this year whilst monitoring the Crater Lion’s Ingela Jansson of KopeLion project spotted a very distinctive dark maned male that she recognised as Kalamas. The last time he had been spotted in the Crater was in November 2015 but this time there he was in full view lounging around mating with one of the Lakes pride females. In the background four contesting males could be heard roaring their presence.
Kalamas ignored them and had the audacity to stay put in the crater with the female for three days before walking back up the steep Crater slope and out onto the open plains of the Ngorongoro Conservation Area where despite being surrounded by Maasai herders and their live stock he managed to stay out of trouble.
A few weeks later however we received a frantic message early one morning to say that Kalamas was sitting out in the open with many herders starting to gather. Fearing some sort of conflict our team rushed to the area, luckily fairly close to headquarters. Once there we could see that people were sensibly keeping a safe distance and approaching by car it was evident that Kalamas had been fighting. He showed deep wounds characteristic of fighting male lions and there was much blood splattered around.
He attempted to stand but couldn’t quite make it and so we feared he may have been fatally injured.
We decided to stay around and monitor the situation; Kalamas just lay there for many hours. As the sun climbed to its midday point kalamas managed to drag himself into the shade of our vehicle where he remained for the rest of the day. Just as we were starting to wonder what on earth to do next, with night fall approaching, Kalamas took us totally by surprise and stood straight up, shook himself gently and, rather shakily started to walk towards the safety of a well treed gully. Satisfied that we had done all we could and that Kalamas would take care of himself we left.
For the next few weeks we monitored his movements and he seemed to lay low, recovering, but you can’t keep a good lion down. Far from learning his lesson about encroaching on other male’s territories he has since been seen in the presence of other females from the Crater rim. His modus operandi seems to be to hang around on the periphery and entice the ladies away for a few days at a time. They just don’t seem to be able to get enough of him. Something about that Jon Snowesque mane of dark shaggy dark hair.
It is an interesting tactic. We ponder whether perhaps mating with pride females belonging to other males in this sneaky way may mean that when (and if) they give birth the resident male is duped into believing that Kalamas’s offspring are their own.
It is certainly a great way for Kalamas to get as many females as possible but not have the burden of looking after any of the offspring.
It is certainly an unusual story and far from the norm. It remains to be seen if Kalamas was at all successful or if the resident males were harder to fool than he imagined. We are looking out for cubs with dark manes though.
The ladies just love Kalamas Photo Credit: KopeLion, Ingela Jansson
Watching For Whisker Spots
I recently met with Meritho, who has to have one of the best jobs in the world; he is paid to watch lions.
Yes it does sound like the dream job, following lions all day, observing their behaviour and trying to identify them but Meritho’s job is not quite the dream it would seem. For various reasons the long running Serengeti Lion Project was put on hold for three years which meant that all the diligently followed lion prides known intimately by researchers have done a lot of growing up, giving birth and dying. Not surprisingly it’s hard to work out who’s who and who belongs to whom.
Meritho has inherited the arduous task of re-establishing the family connections and splits within the Serengeti’s lion prides. Armed with some old scribbled maps and a stack of cards with drawings of lion whisker spots he has to compare each lion he sees with these cards to help him workout just who is still out there in the Serengeti lion society. Of course the camera trap images help a little but only if they capture the perfect close up, in focus image of the lions muzzle showing the spot pattern. In reality its all down to traipsing around the Serengeti looking out for lions and comparing each and every one with the hundreds of hand drawn cards.
I asked Meritho how he tackles this mammoth task. Making a plan is key, he says, with most of the tracking collars non functional you have to think hard where the lions might be and just drive around looking for them.
Ok you can narrow it down a bit as Meritho does by getting up by 5 am, making sure your vehicle is puncture free and stocked with fuel and water and then heading out to try and catch the big cats as they finish up for the night. At this early hour they are often looking for a good spot to spend the day or joining back up with young cubs that have been left somewhere safe whilst mothers where out hunting. All this movement increases his chances of running into lions.
Most of the time Meritho is far from base so eats lunch in the car only returning home around 5:30 as it starts to get dark. Its long hours and most of the time you are either sitting waiting or driving, briefly interspersed with spells actually watching the lions. In return they themselves are often infuriatingly sleepy and won’t lift their heads for you to get good pictures of their whiskers meaning even when you do find lions you cannot always see who they are.
So far he has managed to identify around 150 individual lions and is monitoring around 18 prides. Monitoring lions gives him a sense of pleasure that he is out there doing a scientific job he never dreamt, as a Tanzanian, he would get the chance to do. He says ‘ when I look at where I come from and where I am going as a researcher it brings a lot of value to my life, knowing what research means is one thing but doing research makes me feel like I am contributing something to the world and my home environment’. He is gaining knowledge and experience daily and hopes to continue doing great things within conservation, an inspiration to aspiring local scientists.
It’s great to know that Meritho is out there following the lions again and that the Snapshot Serengeti cameras are still going to be clicking away for sometime to come.
Trials and Tribulations
Data collection is the back bone of field research work and can sound glamorous and exciting to those who are office bound but I will let you into a little secret, it can be exhausting and frustrating and unrewarding too.
Firstly, you have to remember that researchers often work in remote places and whilst this is amazing it does lead to some logistical nightmares. Take for instance my recent experience. My task was to visit 18 Ilchokuti or lion guardians from KopeLion to collect the data they had recorded during the previous month. Now they are spread out over 1300k2, in itself quite a distance but when you factor in the rough at best, non-existent at worst roads you begin to have an idea of the task. I would be lucky if it didn’t rain, that would only add to the woes. Another thing to remember is that, barring a few lucky people working for high profile organisations, most researchers have to nurse their aged vehicles along, fixing things as you go. This trip wasn’t too bad as we seemed to only suffer from door catches failing so nothing a bit of string or a Leatherman wouldn’t fix. The budgets just never seem to run to decent cars.
Just as I was about to feel smug about the lack of rain hampering our journey it dawned on me that dry conditions held their bad points too. Dust! The fine dust covering some of the landscape here is deadly. It penetrates everything and with a three-day trip planned with no opportunity for a shower, boy does it get tiring. Forget enjoying the scenery as you drive, you mostly feel as if you are in a cloud only with a yellow tinge that makes it hard to breath in place of the fluffy white.
Anyway, I can’t really complain it was a wonderful three days and meeting up with a couple of our guys in the middle of nowhere under a great baobab tree acting as our office for an hour or so was something to make you smile.
Data collection. Credit: KopeLion
My colleague, Meritho Katei, over in the Serengeti has an even harder job under similar conditions. I was simply rendezvousing with other people, collecting and issuing data sheets and downloading GPS data. Meritho is trying to pick up on the lion monitoring for the Serengeti Lion project that has been on hold for a while.
His task is to reconnect with the prides of lions previously being followed and studied and to catch up on the family histories. New members need to be identified, files made on them and changes in pride composition noted. He is working with the Snapshot Serengeti camera trap data to see where the prides are hanging out but of course we aren’t quite up to date with the classifying so that’s not the greatest help. Instead he is relying on a lot of kilometres driving, following up on tourist sightings and tracking data and a good set of eyes to track down the prides and observe them.
So as I washed the dust out of my hair, luxuriating in a hot shower after my three day successful, mission accomplished trip, I had to reflect that poor Meritho was in for many months of hard slog catching up with those lions and with the rains coming things are about to get even harder. Good luck Meritho!
Serengeti lion pride
Lion Fight
Photo Credit: Edward Lopatto
These incredible images of a major lion turf war have been taken by the team in the Serengeti and come with the fantastic announcement that the long running Serengeti Lion Project is back up and running.
Although the camera-trap aspect of the project has continued without pause, the main work of the Serengeti Lion project has been on hiatus for the past few years. Now, it is finally being restored and the priority is to sort out who’s who in all the study area prides. Comparing existing id’s and adding new ones is going to take some time.
Looks like these boys are trying to shake up the genes even more. Two coalitions both looking strong have clashed over ownership of prime real estate. The team report that all the males involved looked strong and healthy so this is probably not the definitive battle.
We will have more news for you soon on how the work is going as well as reports from the field, so stay tuned. Meanwhile enjoy these stunning images.
A Team Effort
Snapshot Serengeti has been on the go since 2010 in one form or another and over those years a team of dedicated people has kept it running. The base of the effort is the 225 camera-traps that have been snapping away continuously for that whole period. Of course for that to happen there needs to be researchers and assistants on the ground physically looking after camera-traps, a scientific team who coordinate all data processing and analysis, a management team running the administration of the project and generous funders to keep everything alive and kicking.
Snapshot Serengeti could also not work without all the thousands of volunteer citizen scientist who generously give their time and energy to classifying all the millions of images, ultimately helping the researchers to answer scientific questions we hope will aid in the conservation of all that we love about the Serengeti.
Here in these blogs we have celebrated all these people but it dawned on me recently that there is one group of people that seem to have been forgotten, our moderators.
Our amazing team at Snapshot Serengeti deserve a special mention. They, like our citizen scientists are volunteers, dedicating their time and expertise for free. Contrary to what some may think they are not part of the scientific team in as far as they are not university students who do the job as part of their studies. No, they are a mixed bunch in terms of back ground and do the job plain and simply because they love the Serengeti and love the project. They spend a huge amount of time online helping other users with their classifications, guiding new users through some of the pit falls they know only too well and sharing their collective knowledge through prompt responses to questions and great information posts helping others with less experience to understand the Serengeti and its wildlife. They also have to deal with the odd, luckily very infrequent, troll which is a thankless task in diplomacy. We are privileged to have such an amazing team and I know that they are greatly appreciated by Snapshot Serengeti’s participants.
So thank you to davidbygott, maricksu and tillydad who have been with us since the beginning and welcome to parsfan and nmw. You Guy’s are the best and Snapshot Serengeti would not be the experience it is without all your help.
Hartebeest through a dislodged camera-trap cover.
Snapshot Serengeti 