Finished! Looks like this project is out of data at the moment!
We've reached our classification goal! Thank you SO MUCH for your help!
Check out our first paper using these data, and read our blog post here.
See this awesome explanation from Snapshot Serengeti researchers for an excellent description of the problem. In essence, by asking lots of volunteers to give their 'best guess', we can actually glean quite a bit of information about the image, even if the identifications don't agree with each other. For instance, if a blurred, small, furry thing darts past the camera, volunteers are likely to guess something like "hare" or "jackal" or "genet". From these, researchers can say it's probably a small carnivore or hare, and certainly not an ungulate. So we could likely exclude that image for questions that only pertain to ungulates. But if "unknown" had been an option, the researcher would have 10 classifications that all say "unknown", but with no information about what is actually in the image.
In order to compare the effect of water on animal behavior, we need to have a control reference! Images without water are our 'Control' sites, which are located at least 1 km from any water source.
Sometimes grass, clouds, and trees can trigger the camera when no animal is present. In some rarer cases, a rapidly-moving animal can trigger the camera, but it has moved out of the frame by the time that the image is actually taken (there is a < 1 second delay).
Occasionally a camera has to be reset, or a new camera isn't properly programmed to the correct date when it's deployed. But don't worry! We check all the image metadata and correct any times that are incorrect. Unfortunately, we can't change the timestamp on the image though!
If the image is of a watering hole or watering pan, then we count the animal as 'drinking' if we can directly observe the animal taking water. We do not assume that the animal is drinking if it is merely standing next to water.
We count 'grazing' when the animal's mouth is touching the ground to ingest grass or roots. We don't assume that an animal is grazing if its head is just slightly lowered.
We've also had some species-specific questions:
We prefer not to count the animal is drinking if the trunk is wet because our goal is to quantify the amount of time that the animal spends drinking. An elephant's trunk might stay wet for a much longer period than it spends drinking!
Yes, since we are quantifying time spend actively drinking, this counts.
This is a bit of a gray area, but yes, this can be counted.
Usually you can see an elephant ripping vegetation from the ground and then carrying it to its mouth in the next image.
Since there are often large herds of cattle at watering holes, we don't expect you to count each one precisely. A rough estimate is sufficient. If the entire water source is completely surrounded, it is probably safe to assume that 30+ cattle are present. If there are a moderate number, then 21-30 could be estimated. We recognize that often we are underestimating the total number of cows and will account for this in our analyses.
To maintain consistency, we prefer to only count animals as drinking if we can see them actively drinking. Each image set is usually part of a longer image sequence, so even if you don't observe the giraffe drinking in your current image set, it's likely to be counted in another image, thereby giving us a more precise measurement of time spent contacting water.
No, you do not need to count those animals. They were unlikely to have triggered the camera, are not interacting with the water, and are probably biased toward larger species.
Yes, this can be counted as grazing, as it may be especially relevant to warthogs that feed on roots.
In these less common cases, it can be assumed that the animal is grazing if this seems reasonable.
In an ideal scenario, these gray areas wouldn't exist! We thank you for taking the time to help us to make careful classifications, but we also encourage you not to worry when you may be uncertain. We value consistency across images, as this helps us to make unbiased comparisons across our experimental treatments and periods. Thank you!