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.
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.
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.
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!
Snapshot Serengeti is in the limelight again!
A new paper titled “No respect for apex carnivores: Distribution and activity patterns of honey badgers in the Serengeti” has been published by a team from the University of Wisconsin and University of Ljubljana using the Snapshot Serengeti data classified by our citizen scientists.
Honey badgers are surprisingly understudied. Although extremely charismatic the fact that they have large territories, up to 541km2 for an adult male in the Kalahari, and no clear habitat preferences makes it hard to predict where to find and study them.
The Snapshot Serengeti data of course is a dream come true to many researchers enabling them to ask scientific questions without having to wait potentially years to collect data themselves.The team took advantage of the open access data, courtesy of Snapshot Serengeti to look at what they could learn about honey badgers and how they live alongside other predators. Ferocious as they are honey badgers are killed by lion, hyena and leopard and so the team wanted to know whether they avoided areas where these large carnivores were active.
Well it seems that despite ending up as an occasional victim the honey badger is quite happy living alongside the larger carnivores, at least in the Serengeti anyway according to the authors. It appears as if the honey badger actively seeks out the same habitats as the large carnivores. The authors modelled a variety of different explanatory scenarios to see which would be the best fit to explain honey badger distribution across the Serengeti study area. Included where variables such as habitat preference, water availability, cover availability, lion abundance, and leopard abundance. Their best models showed that the presence of all three large carnivores coincided with the presence of honey badgers and that there was also a positive correlation temporally between leopard, hyena and honey badger showing that they use the same habitat at the same time.
It’s interesting stuff. The authors do point out that although the data set was huge there was actually very few incidence of honey badger over the 3 year period covered by their work and so their sample size was small. It does however show just how valuable the data collected by Snapshot Serengeti and the other Snapshot Safari projects can be, if nothing else to give scientists a relatively inexpensive way to explore questions before undertaking more specific research work themselves.
You can read the paper here, although it is not open access unfortunately: https://www.sciencedirect.com/science/article/pii/S1616504717302720
These two images illustrate the point nicely, you can clearly see the same camera has captured honey badger and spotted hyena with in 13 days of each other. Interestingly both in day light.
Whilst stretching the corners of my brain to think about a new topic to write about in the Snapshot Serengeti blogs it astounds me to realise just how long we have been going for; over 7 years now as Snapshot Serengeti and almost 10 if you include the Serengetilive days.
It is also humbling to know how dedicated our followers are and what support we get from them. Our fun would have been over long ago if the community had not backed us. It has occurred to me that Snapshot Serengeti’s followers do so in differing ways. Those who follow our facebook and twitter pages or WordPress fans who follow us through our blogs may have missed what it is we are up to. So at risk of boring those of you who do know I thought it was about time to reiterate what it is we at Snapshot Serengeti do and how it all works.
Our largest group of followers do so at www.snapshotserengeti.org helping us classify the millions of camera-trap images that are produced by around 225 camera-traps placed in a permanent grid pattern in our study zone in the Serengeti National Park. For continuity’s sake these sites, after an initial bit of trial and error have remained in their fixed spots since they were first chosen by the projects designer, Dr Ali Swanson back in 2010.
Originally the camera-trap grid was set up to answer questions on carnivore interactions specifically if carnivores were avoiding one another spatially and temporally, it soon became apparent that it could be used to pose many more scientific questions amongst them herbivore coexistence and predator prey relationships. The wisdom to leave this permanent window of observance into the lives of the Serengeti animals should lead to many future studies and has spawned many new similar camera-trap projects around the world.
It’s not all about the animals, in fact since teaming with Zooniverse the project has been as much about the advancement of citizen science as anything else. Back in the Serengetilive days there were so few of us taking part that we used to have our names up in a sort of league table of who had classified the most images. Each classified image was labelled by the classifiers name. Now of course there are far too many participants to bother with that kind of thing, besides with multiple people having to agree on each classification it might get messy. The work on developing a robust algorithm that dealt with the uncertainties in each individual classification was so involved it also paved the way for many more projects and several scientific papers.
So what do we ask classifiers to do? Well first you are presented with either a run of 3 images (day time) or 1 image (night time). You are then asked to decide and record what animals are present, numbers of each species, behaviour and whether there are young present or not. It’s pretty straight forward with prompts along the way. If you don’t know what the animal is you simply guess. Yes you read that right, you guess. One thing the developers worked out is that the whole project works better if you cannot skip images. For one thing it avoids all the hard or boring images being left till the end. As each image has to be agreed upon by several classifiers before it is retired this tends to smooth out any miss classifications and research has shown we are around 97% accurate.
If you find something good or something you cannot id and are curious you can add the image to Talk which is the discussion forum. There we have some very dedicated moderators who will help you with your queries.
All in all Snapshot Serengeti is about learning and sharing both for the researchers and for the community of classifiers so if you have been enjoying the facebook posts or reading the blogs but have never had a go classifying get yourself over there to www.snapshotserengeti.org and have a go.
I promised I would have some news about what the Serengeti team has been up to recently in the field. Our beloved camera-trap grid is still being cared for, cards downloaded, batteries replaced and cameras given the once over. So all is well on that front but what is the latest question being asked by the team.
Well thanks to the spatial occupancy modelling of the Snapshot Serengeti camera-trap grid we have learned a lot about how the animals share the environment. What we can’t derive from the camera trap images is the details of what the different species are doing when they are in those spaces and how so many large herbivores can exist together. It could be that they simply facilitate each others foraging or maybe they are using different resources. Scientists have identified what is known as niche partitioning, a mechanism that sees different species specialising in eating different proportions of grasses verses non-grasses; pure grazers and pure browsers and a sliding scale between the two. A second mechanism sees different species eating different parts of the same plant.
These two mechanisms seem to make perfect sense but it is not understood to what extent these two truly affect coexistence of large herbivores. This is where the Snapshot Serengeti team research comes in.
Under our own Dr Michael Anderson they have teamed up with Dr Rob Pringle and researchers at Princeton University in using a revolutionary new analysis method known as DNA metabarcoding to see what exactly each animal is eating.
Up until recently scientists studying herbivore diet had two choices, they could watch their subjects and try to identify what they were eating or they could use microhistology, whereby plant parts in faeces are visually identified. As you can imagine these methods are fine for differentiating between, say, grasses and trees but don’t allow scientists to classify down to individual plant species. With DNA metabarcoding they now have that ability and it should tell us a whole lot more about how the animals divide their resources in space and time.
So that’s the science but how does the team collect this data. Well as with microhistology it involves dung. Our intrepid scientists are roaming the Serengeti collecting poop from as many different herbivores as they can and then it all has to be shipped back to the labs for analysis.
If you are thinking that our team must be highly skilled detectives able to identify a wide variety of brown pellets in the savannah grasses then think again. That’s not to say they can’t but this work relies on 100% knowing which species produced said dung its sex and age as well as a sample that has not been contaminated in anyway. The method of collection relies then, on stealthy observation waiting for an individual to lift its tail and sprinkle the ground with brown pellets before running in with your sample jar at the ready to collect the freshly deposited “clean” offerings. I have some experience with this work and believe me it does feel slightly odd to be observing animals in this way, willing them on to have a bowel movement so you can move on to the next species. It is also a little risky as you can get so engrossed at watching your target animal that you forget there are predators there watching and waiting. At least in this project it is only herbivores the team are interested in, to do the same with predator’s faeces, that’s a whole lot more smelly.
The study is still in its early stages but the team reports they are already seeing some noteworthy things.
Spoiler alert, early results suggest that there are only two ‘pure’ grazers in Serengeti (zebra and warthog) and lots of variation between wet and dry season.
We will bring you further updates once the team has finished their analysis work and have the full results. It promises to be exciting stuff. In the meantime you can think on the glamorous job a field scientist has whilst you stay clean at home helping with the job of classification.
Symbiotic relationships are common in the Serengeti. They fall into two main types, mutualism, whereby both partners benefit from one another and commensalism, whereby one partner benefits from the actions of the other but the other partner is largely unaffected or unharmed. I wrote recently of oxpeckers and large herbivores, large herbivores provide food in the form of ticks for the oxpeckers and oxpeckers provide a cleaning service for the large herbivores, a good example of mutualism. Birds such as cattle egrets that follow buffalo around to catch the invertebrates the buffalo disturb as they graze is an example of commensalism. Of course it is not just animals that have symbiotic relationships; my blog last week on termites and mushrooms was another example of mutualism.
So what about zebras and wildebeests? We see them all the time on Snapshot Serengeti in mixed herds, grazing peaceably with one another. Is this just coincidence or is this a form of symbiosis?
It is actually hard to say and of course that is why labelling things, especially behaviour is often tricky.
Zebra and wildebeest are both grazers meaning they mostly eat grasses but that doesn’t mean they share the same diet. They preferentially eat different parts of the plants that they consume. Zebras are quite content chewing longer tougher grasses where as wildebeest prefer shorter, more tender shoots. This partition of resources means they can quite happily graze side by side with out exerting pressure on each other.
Another good reason to team up is the extra safety that numbers provide. Not only do more ears and eyes provide better early warning systems but the odds of the individual being targeted by a predator are reduced when there are greater numbers to choose from. Apparently zebra have better eyesight but wildebeest have better hearing so the two complement each other.
There could be another reason. Our very own Meredith Palmer just published a paper about interspecies reaction to each other’s alarm calls, you can read it here: https://www.sciencedirect.com/science/article/pii/S0003347217304207
She found that zebra, wildebeest and impala recognise each other’s alarm calls but that they did not always respond in the same manner. When zebra sounded the alarm all three herbivores reacted strongly but when impala gave the alarm zebra where likely to ignore it, or assess the relative danger themselves. It seems that this varied response is down to predator size. Impala are prey to a wide range of smaller predators that would not be able to handle a mammal the size of a zebra, so when impala give the call it doesn’t always signal danger for the zebra. However when a zebra, the largest of the three herbivores sounds the alarm, whatever it has seen will probably be able to take down the wildebeest or the impala too so it’s prudent that all three scarper.
It is an interesting reaction and maybe wildebeest hang out with zebra because they are more trustworthy alarmists. I am not sure that the companionship of zebra and wildebeest can be classed as symbiotic I think it is more of an interaction due to a shared habitat but it seems that on some level they can benefit each other.
You are probably aware that the 225 camera traps of Snapshot Serengeti are set out in a grid pattern, spaced every 1km over a part of the Serengeti National Park. It sounds relatively simple but actually there is a lot of painstaking scientific pondering as to how exactly to set out your camera traps.
Over the last couple of decades there has been much debate as to the best way to design a camera trap study. The main choice, in terms of placement pattern, is whether to place your camera traps randomly or selectively and what kind of spacing/density to use.
Truly random is to grid your study site and then let a computer randomly choose which grid squares to place the cameras. Alternately you can choose a line or grid and place your camera trap at regular intervals regardless of where that may fall, still a random point. With selective placement each site is carefully chosen for a specific feature.
In reality most projects use a mixture of the above methods and the best method is really determined by what your scientific question is. For instance, if you where trying to acess the number of leopards in a given area it is better to place your camera traps strategically in places you know or guess leopards are most likely to pass rather than using a randomised method. However if you are carrying out a census of an area and wish to know what species are present then a randomised grid is ideal.
As I said a mix of methods is often used. Imagine setting out a grid in the comfort of your office on your computer. It looks good, covers a large area and promises good results. Once out in the field you navigate to your carefully worked out GPS reference point only to discover it is slap bang in the middle of a marsh or in a thick overgrown patch of thorn trees. This is where the scientists allow themselves a little leeway. Often they will take the GPS point as home base but choose an ideal spot within a certain radius of this point where perhaps there is a game trail or some other sign of animals passing, thus allowing them to select a good site within the vicinity.
I have recently had experience of this type of placement and I can say the work done in selecting your study site and then laying out your grid onto a map is laborious but not nearly as much as stomping through the bush keeping your fingers crossed that your next randomly selected site will be perfect. Turning up to emplacement three to find a thick tangle of vegetation is a little soul destroying, mostly you wonder if any animal is likely to bother to pass that way. The reality is that you normally find a spot that is better within 10 meters and with some slight pruning of the vegetation the sites can often turn out remarkably productive.
So that is the placement sorted but there is a long list of other agonising variables to consider, what settings to use on the camera trap itself, how many to use and how long to keep them up. Believe me every scientist designing studies deliberates the pros and cons of these factors and worries incessantly about if they have made the right choice. You don’t want to set up all you camera traps and leave them for a few months only to find your set up was not great, something which happened to me recently when I chose to set the camera trap on high sensitivity to make sure I had every chance of capturing the small, fast critters. The problem was it was so hot, 40°c plus, that the ambient waves of heat set the camera trap off almost permanently between 12pm and 5pm leaving me with 2000 images of nothing. I have had to compromise and reduce the sensitivity to avoid all the miss triggers; hopefully it won’t miss too many small things.
Snapshots camera traps have now been up for over 7 years so most of these teething problems have been ironed out. But as with the best laid plan you cannot control everything, the odd camera still malfunctions as I am sure that our regular classifiers can attest to!
*This weeks blog was written by Jamee Snyder, project coordinator and administrative assistant with the Lion Lab, University of Minnesota. She tells us all about a wider a project that Snapshot Serengeti has evolved into and what we can look forward to in the near future.*
Seven years ago, the University of Minnesota Lion Center set out 225 cameras in Tanzania’s Serengeti National Park. These cameras have recorded over 50 species including some of the most threatened species on Earth. With help from over 140,000 citizen scientists from around the world, millions of photographs were reviewed and classified over the past seven years, which provided park managers, conservationists, and researchers with the necessary information to analyze African wildlife population dynamics. This collective effort is a major contribution to ecological research, allowing for the evaluation of long term trends in wildlife populations as well as best practices in conservation management of charismatic african mammals.
Snapshot Serengeti was one of the first camera trap surveys to document wildlife populations in a national park and is now one of the longest running camera trap surveys in the world. We have learned a lot over the years, from how to keep our cameras safe from hyena jowls to retrieving data from memory cards that have gone through a wildfire. We are continuously looking for ways to improve this project.
Thanks to years of experience, your participation, and help from several organizations in the U.S. and Africa, we are excited to announce that Snapshot Serengeti is expanding into an international conservation initiative called, “SnapshotSafari.”
Don’t worry! Snapshot Serengeti isn’t going anywhere. In fact, it will remain essentially the same as we transition into our new platform. The discussion forums and personal image collections will still be available to current and future users. Now, participants will be able to see numerous other parks in addition to the Serengeti. SnapshotSafari will showcase camera trap images from multiple camera trap grids inside dozens of parks and reserves located in six African countries. Intrepid citizen scientists will be able to choose from various exotic habitats, including but not limited to: the Sand Forests of KwaZulu-Natal, the Lowveld of Limpopo, the Fynbos of South Africa’s Cape, and the Karoo desert, in addition to such remarkable ecosystems as Mozambique’s Niassa Reserve, Tanzania’s Ruaha National Park, Swaziland’s Mbuluzi Game Reserve, and Botswana’s Makgadikgadi Pans National Park.
By incorporating multiple sites, we can ask more complex questions regarding African wildlife populations and the factors that contribute to ecosystem stability. For example, researchers can compare population dynamics of reserves that are fenced versus those that are unfenced, or theycan evaluate the environments that successfully host multiple predator species without depleting prey populations. Researchers at the Lion Center will use this dynamic platform to investigate the cascading effects of large mammal reintroductions and ways to limit direct human interventions while still maintaining stable ecosystems within fenced reserves. SnapshotSafari provides an opportunity for participating reserves to collaborate and subsequently develop the most effective conservation strategies for protecting biodiversity.
We are working hard to get SnapshotSafari ready to launch in January. We just completed beta-testing, and the feedback has been very positive. To all of the citizen scientists who participated and to those who continue to be involved with Snapshot Serengeti, we are extremely grateful!
Now, we need your help to finish classifying the final series of images on our original platform, Season 10, at http://www.snapshotserengeti.org before we initiate SnapshotSafari, which will host Season 11. We are very close to finishing classification of these images, so don’t hesitate to invite your friends and family to take a trip to the Serengeti through the lens of one of our camera traps and classify wildlife. Let’s push this meter to the end!
Stay tuned for an official count down, so you can be one of the first to participate in SnapshotSafari and contribute to our collective knowledge and ability to successfully conserve African wildlife.
Snapshot Serengeti has around 225 camera-traps laid out in a grid in the heart of the Serengeti National Park. They have been there for around 7 years and make up one of the longest running camera-trap monitoring projects in the world. Snapshot was launched on the Zooniverse portal in December 2012 and has inspired many more similar camera-trap projects from around the world. So Happy 5th Birthday to us, may there be many more to come.
There is no doubt that camera-trapping has gripped the hearts and imagination of both scientists and the public. Eight years ago when I first used camera-traps I had to explain them very carefully to friends and family as they had never encountered them, these days references to camera-traps appear in popular press articles and wildlife documentaries and most people have a basic idea of their use in conservation.
It was K. Ullas Karanth, an Indian wildlife zoologist, who is credited with pioneering the use of camera-traps as scientific tools in his study of tigers in the 1990’s. In the last two decades the technique has advanced at a hugely fast pace and has revolutionised the study of elusive and seemingly well known species alike. It is a scientists dream to observe animals without being present yourself to influence their behaviour.
But looking at the history of the discipline I can across many references to much earlier work using camera-traps. Back in 1927 National Geographic published an article by Frank M Chapman titled delightfully “Who Treads Our Trails”. The piece opens with this amazing paragraph
“If there be any sport in which the joys of anticipation are more prolonged, the pleasures of realisation more enduring, than that of camera trapping in the Tropics I have yet to find it!”
This guy would have loved Snapshot Serengeti. This is most likely the very first scientific paper to report on using camera-traps all be it very different cameras. His rig involved a tripwire the animal steps on rigged up to the camera shutter and bowls of magnesium that will explode and create the flash needed to illuminate the animal at night time. It seems incredible now that this would be allowed considering today’s ethically minded ethos but the author himself points out that the alternatives to studying animals could include using dogs or trappers to catch an animal or even poison bait. He decides he wants a census of the living not a record of the dead and so the idea of camera-traps for scientific study are born. He drew heavily from the work of George Shiras who published the first pictures taken by remote camera back in 1906 (also in National Geographic). George Shiras took the pictures for the pictures sake only later becoming involved with conservation but Frank Chapman was a true scientist.
Obviously the technology has changed a lot and the loud noisy explosions that accompanied Franks work have been replaced by covert black IR where even the glow of the infra-red flash is almost invisible. He would marvel at the amount of pictures that can be stored on an average SD card and that camera-traps are being used from the tropics to the snowfields of Antarctica.
You can look for the original article with this reference:
Chapman, F.M., September 1927. “Who Treads Our Trails?“, National Geographic, 52(3), 331-345
Or visit this site to see some of Frank Chapman’s images: http://www.naturespy.org/2014/03/camera-traps-science/