 Hello everyone! This tutorial is about CameraTrap distance sampling, and particularly about how to process your CameraTrap videos to obtain the data needed for a CameraTrap distance sampling analysis. Our final goal is the estimation of animal density from CameraTrap videos using CameraTrap distance sampling. And for that we need data. In CameraTrap distance sampling, some of these data include measures of the radial distances between the animals, between the field of view of the camera, and the camera lens. The field of view is basically anything you will see in your CameraTrap video. Here it is represented by the yellow triangle, while the radial distance for the animal in view is represented by the black arrow. Depending on the species you may also need other data to get a reliable density estimate, for example availability. To measure the radial distances of the animals captured in your videos, we will make use of reference videos, previously recorded in the field. During this video I first introduce you to the equipment needed for successfully extracting distances. Then I will show you how to record distances using reference videos, providing some guidance on how to overcome some of the issues you may encounter during this process. By the end I hope you will be able to successfully carry out the process yourself. So let's get started. Very little equipment is needed. Everything can be done from your computer or laptop. First you will need a spreadsheet manager such as Microsoft Excel if you're using a PC or numbers if you're using a Mac. Then you must have a video player application to visualize your camera footage. And finally, although you could work on a single screen, it makes the process much easier and faster if you have a second screen to work with. Make sure you're able to sit in a comfortable working position, get the videos of your species of interest ready, as well as the reference videos for each camera. You also need to have a spreadsheet ready. This will at minimum include the following columns. The camera trap name or identifier, indicating which camera captured the animal, the folder path and names of your videos. Correctly entering this will help you another researcher to easily find a video of interest among the hundreds you will have. In the future it might also be used in automating the distance measurements. Also record the date and time of your observations. Seconds in particular are very important for reasons we will discuss later. You must always have a column for radial distances. This is the most important information in camera trap distance sampling and it is required for estimating animal density. Finally you should at least have columns for animal AD, age class, in, out, reaction and behavior type. Animal AD will be used to identify the one or more animals in the video frame and this will be complemented by the class or age information. In, out indicates whether or not the midpoint of the animal falls within the camera's field of view. Reaction is particularly important as I will show you later and information in the behavior type column is a crucial complement here. You may want to add a field identifying the species, for example if you decide to enter the information for different species in the same spreadsheet. However, you can add all the information you want. As a rule of thumb the more the better. You never know what you will need in your analysis and you do not want to go back to the same videos too many times. Prepare your computer to play your reference videos and animal videos simultaneously. A second screen is handy here as you can have the reference video on one screen and the animal video on the other. However, it is also possible to split a single screen in two like this. Before starting with measuring distances it is important to stress a few important concepts of camera trap distance sampling. First, let's remember what our objective is. We want to measure the radial distance of the animal to the camera lens. As we said before, we will use reference videos to accomplish our task. In short, we will compare the position of a field technician in the reference video to that of the animal of interest. Then, how do we measure those radial distances? Luckily, we do not need an exact distance. Normally, we are happy if we locate the animal within a meter interval. This means between 0 and 1 meter, 1 and 2 meter, 3 and 4, and so on. Do not attempt anything more sophisticated than that. Your measurement should always be halfway between an interval's cut points. Keep in mind that we are looking at circular sections in the camera's field of view. Here, the yellow cross represents an animal located within the circular section that lies between 2 and 3 meters from the camera. The radial distance recorded in this case will be 2.5 meters. If our animal is between 4 and 5 meters, we will record 4.5 meters. Be aware that the farther the animals are from the camera, the harder it will be to measure distances. For this reason, we usually recommend using distance intervals larger than 1 meter from 8 meters onwards. In this example, the distance interval goes from 8 to 10 meters. If an animal is observed within such an interval, we will record its radial distance as the mean distance between 8 and 10 meters, which is 9 meters. Similarly, if our protocol requires us to record distances between 12 and 15 meters under the same interval, we will record a distance of 13.5 meters for all animals observed within that interval. However, we must keep in mind that distances must be measured only to the midpoint of the animal in view. This means that if we only see the head, the tail, or a leg, we do not measure a distance because of the increased difficulty of getting an accurate measurement. For animals with the midpoint in view, we must also add in to the in-out field, otherwise we will put our value of out. Even though animals with midpoints are not included in the distance sampling analysis, they can be included in the analysis to estimate animal availability for detection by the camera trap, which is also an extremely important parameter for estimating density accurately. Also, someone else looking at the video and data sheet will see that the animals was not missed, but classed as being out. Here, the midpoint of this red diker is in full view, and we are able to record its radial distance. But here, we only see its rear. As the midpoint is not in view, we do not record the radial distance. So finally, when do we measure the radial distances? The answer is only at predefined moments, called snapshot moments. More practically, snapshot moments are instances in time corresponding to predefined seconds within a minute, separated by the constant time. For example, in this video, we'll set the time between snapshot moments to two seconds. Therefore, we will measure distances only at zero seconds, two seconds, four seconds, six, eight, and so on within each minute, starting from midnight, zero minute, and zero seconds. This will be our snapshot moments. However, the interval can be different. For example, four seconds, six seconds, or ten seconds. It is important that you know at what time the videos were taken. In this case, I have the time here at the bottom of my screen. As we have stopped this video at 30 seconds, it means we are looking at a snapshot moment. We must record the radial distance to this yellow back diker. We would not record a distance 31 seconds, because it is not a predefined snapshot moment. But we record another distance at 32 seconds, or two seconds after the previous snapshot moment. Then at 34 seconds, and so on, until the diker's midpoint leaves the field of view. However, some makes or camera traps do not show the seconds on the video's info strip. Only the hour and the minute. As we need to know the exact snapshot moment, we must know the exact time when the video started. The simplest solution is to right click on the video we are watching, and look at the properties. Here, we have information about when the video was created and modified, including the seconds. The last time the video was modified tells us when the camera trap stopped recording. Because our video is one minute long, all we have to do is to subtract one minute from the modified time provided in the properties, and we will know the exact time the video started. The same result can be obtained using video processing or statistical software. Be aware that not all camera traps work in the same way. Before starting to record radial distances, you will need to find the most appropriate way to extract the starting times of your videos. We are ready to start and look at an example. First, we simultaneously open the video of an animal and the reference video that corresponds to the same camera. To the right, we see a blue diker capturing the forest on Mabelendoki National Park, Congo. To the left is the reference video where a field technicians shows the distance to the camera at one of several points in the field of view. We will use these reference videos to identify the blue diker's distance interval from the camera trap at each snapshot moment. But remember, we first need to know when, to the second, the video was recorded. If the time the camera trap starts to record on the video is not displayed, or only the hours and the minutes are shown, then remember, we can open the video properties and look at the time the video was modified. It says 7, 29, 0, 2, which means the video started me recorded one minute earlier, at 7, 28, 0, 2. Because all daytime videos were set to be one minute long for those devices. Now that we know the exit time when the video was recorded, let's rewind the video with the blue diker back to the beginning. First, we need to remember that we can now measure any distance until the midpoint of the diker is in view. Here, the diker midpoint is immediately visible. We have just determined that this video started at 7, 28, and 2 seconds. This time is a snapshot moment and we can measure our first radial distance. Let's look carefully at the position of the diker. We can now play the reference video and try to figure out where the diker was standing. To do so, we need to concentrate on the position of the technician. I recommend paying particular attention to his feet, which usually give us a better idea of his real position in the field of view. We can also concentrate on objects close to the technician, like the little tree in the middle of the field of view. This will help us identify points of reference to correctly estimate the animal's location. In this video, the field team has conveniently placed color tape at predetermined distances, which will also help us in determining the diker's position. Nevertheless, this is not a trivial task at all and we might need to play the video several times before we get an idea of where the diker was. When we are convinced, we can finally record the distance. To me, it appeared that at the first snapshot moment, the diker's midpoint was between 2 and 3 meters. So in my spreadsheet, I will insert 2.5 in the distance column. And that's your first distance. We will then move to the second snapshot moment. We'll let the video play until the next snapshot moment, which will be two seconds later. In this case, it is simply two seconds after the video started. We can verify this by using the time bar of the video player. When the bar shows two seconds, we will stop the video and compare the new position to that of the technician. The diker has moved away from the camera, but we want to know if its midpoint is now beyond 3 meters. So we look at the position of the technician at 3 and 4 meters. To me, it looks like the diker is just before 4 meters, between 3 and 4. So in the spreadsheet, I will enter that at 7, 28, 0, 4. Two seconds after the first snapshot moment, the diker was at 3.5 meters. And repeat the process until the animal exits the field of view. As our blue diker remained the field of view for 24 seconds, or 12 snapshot moments, our spreadsheet for this video will look something like this. 12 radial distances recorded for the same animal, one for each snapshot moment with the animal's midpoint in the field of view. Sometimes animals move in pairs or in groups. As camera trap distance sampling requires distances to single animals, we need to measure the distance to each animal in the field of view, at a particular snapshot moment. Here we see two Congo P-folds, a species endemic to the democratically public of the Congo. The blue bird is a male and the brown one a female. In this case, you need to insert two lines in your spreadsheet for each snapshot moment, one for the male and one for the female. Like this. Here we make use of the animal ID column to specify whether we were referring to the male or to the female. But sometimes you will need many more lines, as in the case of this female red river hug and our four piglets. Just make sure you specify each individual's ID at each snapshot moment, like this. Occasionally you may also observe two different species at the same snapshot moment. In this case, as before, you will add a row for each animal and have a column-nose species to enter this information for each animal. If you tend to have mixed species groups more often, then you might also like to have an additional column that indicates whether a snapshot moment corresponds to a single species or mixed species detection. One of the most important issues in camera trap distance sampling is animals' reaction to the cameras. To avoid bias density estimates, we need to exclude snapshots of reactive animals. There are several kinds of reaction. The most obvious is attraction. Here we see a red diker approaching the camera. As the diker has changed its normal path to examine the camera, we will need to discard the distances recorded at these snapshots. In principle, we could avoid measuring these distances altogether. However, you must flag the reactive behavior in your spreadsheet in the reaction column, like this, where y means yes. In this way, you could always go back and check in case of any uncertainty in reactive behavior. If you do enter the distances, then a researcher disagreeing with your assessment of reactive behavior would already have the distance measurement at hand. This is another case, with two golden-bellied manganese, a rare and dangerous species endemic to the Democratic Republic of the Congo, reacting to the camera. However, notice the manganese on the bottom right corner that appears at 50 seconds. It did not react to the camera trap. The spreadsheet will look like this. One entry for each individual. Make sure you specify which individuals are reacting and which are not. However, other reactions are more subtle. For example, Bonobos have the habit of stopping a few meters from the camera to examine it. If we include these snapshots, we will risk overestimating density. We do not want that. Therefore, we need to flag reactive snapshot moments and exclude them from our analysis. Let's see how. In this example, the Bonobo notices the camera at 55 seconds, stops and looks at it for a few seconds. It then changes its path and leaves the field of view. Here, I would only record the snapshot moments until 54 seconds. Then flag a reaction for 5 consecutive snapshots from 56 seconds to 4 seconds. Then I record again at the last snapshot moment at 6 seconds, when the Bonobos live in the field of view. Like this. Elephants are even more complicated. They do not always look directly at the camera, but stop and examine the area with their trunk, smelling and feeling everything. They can do that for a long time. In this video, I recorded only the first snapshot, although the elephant was already reacting, and flagged all those remaining. Elephants also pose another problem. They are so big that we need to consider not only their length, but also their width. As a rule of thumb, if the elephant displays horizontally with regard to the camera, we would add an additional meter to the distance measured at the closer point. And that's it.