Explain one of the following distance sampling concepts in your own way:
Detectability
One of the four assumptions of distance sampling, and why it matters
Random placement
Detection is certain
No movement
Accurate measurements
Detection functions
Effective strip width
You can explain the concept however you wish, for example:
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Tell a story from your own experience
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Whatever way works best for you, and allows you to express your ideas!
Detectability is basically about the fact that we don’t see every animal that is actually there. I Imagined walking on a transect in a dense forest, a chimpanzee standing right next to the transect line is easy to be spotted, but one that is far away, hidden behind thick vegetation or large trunk of a tree, or moving quietly in fear of human presence is much harder to be detected. But distance sampling accepts this reality and models it by assuming that the probability of detecting a chimpanzee decreases as distance from the transect or camera increases.
By estimating detectability, distance sampling allows us to correct for the chimpanzees we missed and avoid underestimating population density. Without accounting for detectability, we would wrongly assume that the number of chimpanzees observed equals the number present, which is especially problematic in forests where visibility is low and some species are shy.
Random Placement is one of the key assumptions of distance sampling. The species or objects that you are surveying may or may not be randomly distributed, but it’s crucial that the transects are randomly placed to account for variation in distribution and detectability across the sampling area. Alignment of transects with spatial features like roads or certain types of terrain can influence sampling results, as animals could be attracted to or away from certain habitat or features within the sampling area.
This ensures that the detection function derived from the observed distance histogram is based on the detectability of the the objects rather than the habitat selection or other biases. This gives us a more accurate estimation of detectability across the sampling area. So, while we want to maximize detectability, selecting transects where we expect to see more animals, as opposed to random placement, incorrectly correlates detectability to density and doesn’t give a true measure of detectability and density across the entire area.
Detectability –> The capacity that we have to visualize a specific group of individuals/ species/ populations when surveying them.
**I think of it this way: me with glasses and binoculars == higher detectability // me with no glasses and equipment and a hangover == lower detectability**
Assumption of random placement —> When doing distance sampling, the condition that we must take into account that consists of setting the location of our surveying transect/ points without being biased towards where we think we can see the study species more (or less).
Assumption of Detection to be certain —> When doing distance sampling, knowing that you can potentially see the study species where you are going to survey it.
Assumption of No movement —> One has to keep in mind that when you see an individual of your study species/ population, you have to catch its precise (or at least as much as possible) location before it runs away.
Assumption of Accurate measures —> The necessity to be accurate of the location of the surveyed individuals when doing distance sampling.
** Set my transect points randomly just knowing that I will not go surveying into a river searching for grasshoppers and keeping in mind that I have to be particularly silent to not scare what I encounter away. At the time of encounter, like Pokemon, I got to be sharp and catch its specific location.**
Detection functions –—> the mathematical and statistical explanation behind the fact that I will be sharper in detecting things that are closer.
**Just a fancy term and complex maths that explain how well (or not) I get to see an individual at different distances away from me **
Effective strip width —> When surveying, the distance from you at which you have a 50:50 chance to detect the study individuals.
** I see (almost) everything that happens at 0.2m away from me/ I see (barely) nothing that happens at 500m away/ ESW = the distance in the middle at which I will catch the 50% of things (but then apply it to your study individuals)**
