Here, we talk about how the detection probabilities we estimated in Chapter 1 help us to estimate abundance by adjusting the counts of animals we observed (detected) in the field for those we missed.

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• We first need to work out what the detection probability of all detectors combined is - not just around one detector.

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• Then, we use an example at a relatively coarse resolution to illustrate how the study area is broken up into small regions. The number of detected animals in each small region is divided by the average detection probability within the small region. This gives us an estimate of abundance for the smll region.  In reality we divide the survey region into very many very tiny regions to do this - many more much smaller regions than the 25 regions shown in the video. You can think of these little regions as ``pixels'' which combine to make up the whole abundance picture.

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• We obtain an estimate of abundance of animals within the study area by summing the abundances in each ``pixel'' across the whole study region. 

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• You can think of an estimate of density in each region being obtained by dividing the estmated abundance in each little region by the area of the little region. An estimate of average density in the study region can be obtained by diving the abundance estimate for the whole study region by the size (area) of the study region.

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