These are the slides from my talk at id2ox. http://id2-ox.co.uk/
It presents a method for estimating animal abundance using camera traps or acoustic detectors.
The method does not require individual identification of individuals (as capture-mark-recapture does), nor does it require knowledge of the distance between animal and sensor (as distance sampling does).
Instead it builds a mechanistic model of whether animals can be detected by the sensor depending on the acoustic/visual properties of the species and sensor. The expected numbers of encounters, assuming completely random movement.
This work is now published in Methods in Ecology and Evolution.
http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12346/abstract
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Tim lucas-id2ox
1. Estimating abundance from camera
traps and acoustic sensors
Tim C.D. Lucas & Elizabeth A. Moorcroft
CoMPLEX, UCL
@timcdlucas @statsforbios
18. Sensor Angle, θ
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0 π 2π
0Ï€2Ï€
r
π θ − cos α
2 + 1
r
π θ sin α
2 − cos α
2 + 1
r
π (θ + 2)
2r
2r sin α
2
r
π θ − cos α
2 + cos α
2 + θ
r
π θ + 2 sin θ
2
r
π θ sin α
2 − cos α
2 + cos α
2 + θ
Expressions for ¯p
19. Sensor Angle, θ
CallAngle,α
0 π 2π
0Ï€2Ï€
r
π θ − cos α
2 + 1
r
π θ sin α
2 − cos α
2 + 1
r
π (θ + 2)
2r
2r sin α
2
r
π θ − cos α
2 + cos α
2 + θ
r
π θ + 2 sin θ
2
r
π θ sin α
2 − cos α
2 + cos α
2 + θ
D = z/(¯pvt)
27. Any Questions ?
Tim C.D. Lucas & Elizabeth A. Moorcroft
@timcdlucas @statsforbios
Sensor Angle, θ
CallAngle,α
0 π 2π
0Ï€2Ï€
r
π θ − cos α
2 + 1
r
π θ sin α
2 − cos α
2 + 1
r
π (θ + 2)
2r
2r sin α
2
r
π θ − cos α
2 + cos α
2 + θ
r
π θ + 2 sin θ
2
r
π θ sin α
2 − cos α
2 + cos α
2 + θ