Combine Telemetry and Detection Data

Share:

Description

Animal locations determined by radiotelemetry can be used to augment capture–recapture data. The procedure in secr is first to form a capthist object containing the telemetry data and then to combine this with true capture–recapture data (e.g. detections from hair-snag DNA) in another capthist object. secr.fit automatically detects the telemetry data in the new object.

Usage

1
2
addTelemetry (detectionCH, telemetryCH)
xy2CH (CH, inflation = 1e-08)

Arguments

detectionCH

single-session capthist object, detector type ‘proximity’ or ‘count’

telemetryCH

single-session capthist object, detector type ‘telemetry’

CH

single-session capthist object with xylist attribute

inflation

numeric tolerance for polygon

Details

It is assumed that a number of animals have been radiotagged in the vicinity of the detector array, and their telemetry data (xy-coordinates) have been input to telemetryCH, perhaps using read.capthist with detector = "telemetry" and fmt = "XY", or with read.telemetry.

A new capthist object is built comprising all the detection histories in detectionCH, plus empty (all-zero) histories for every telemetered animal not in detectionCH. The telemetry locations are carried over from telemetryCH as attribute ‘xylist’ (each component of xylist holds the coordinates of one animal; use telemetryxy to extract).

xy2CH partly reverses addTelemetry: the location information in the xylist attribute is converted back to a capthist with detector type ‘telemetry’. A search polygon is formed from the convex hull (minimum convex polygon) of the detectors, slightly inflated (factor inflation) to avoid numeric inclusion errors at the vertices.

Value

A single-session capthist object with the same detector type as detectionCH, but possibly with empty rows and an ‘xylist’ attribute.

Note

Telemetry provides independent data on the location and presence of a sample of animals. These animals may be missed in the main sampling that gives rise to detectionCH i.e., they may have all-zero detection histories.

The ‘telemetry’ detector type is like a ‘polygon’ detector (detections have x-y coordinates). Although perimeter coordinates are required they are not at present used in analyses.

Combining telemetry and detection data is not yet fully documented.

See Also

capthist, make.telemetry, read.telemetry, telemetryxy

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
## Not run: 

# Generate some detection and telemetry data, combine them using
# addTelemetry, and perform analyses

# detectors
te <- make.telemetry()
tr <- make.grid(detector = "proximity")

# simulated population and 50% telemetry sample
totalpop <- sim.popn(tr, D = 20, buffer = 100)
tepop <- subset(totalpop, runif(nrow(totalpop)) < 0.5)

# simulated detection histories and telemetry
# the original animalID (renumber = FALSE) are needed for matching
trCH <- sim.capthist(tr,  popn = totalpop, renumber = FALSE, detectfn = "HHN")
teCH <- sim.capthist(te, popn = tepop, renumber=FALSE, detectfn = "HHN",
    detectpar = list(lambda0 = 3, sigma = 25))

combinedCH <- addTelemetry(trCH, teCH)

# summarise and display
summary(combinedCH)
plot(combinedCH, border = 150)
ncapt <- apply(combinedCH,1,sum)
points(totalpop[row.names(combinedCH)[ncapt==0],], pch = 1)
points(totalpop[row.names(combinedCH)[ncapt>0],], pch = 16)

fit.tr <- secr.fit(trCH, CL = TRUE, detectfn = "HHN")  ## trapping alone
fit.te <- secr.fit(teCH, CL = TRUE, start = log(20),   ## telemetry alone
    detectfn = "HHN") 
fit2   <- secr.fit(combinedCH, CL = TRUE,              ## combined
    detectfn = "HHN")                                 
fit2a   <- secr.fit(combinedCH, CL = TRUE, details =   ## combined, using info
    list(telemetrysigma = TRUE), detectfn = "HHN")     ## on sigma from telemetry

# improved precision when focus on realised population
# (compare CVD)
derived(fit.tr, distribution = "binomial")
derived(fit2, distribution = "binomial")

# may also use CL = FALSE
secr.fit(combinedCH, CL = FALSE, detectfn = "HHN", trace = FALSE)

## End(Not run)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.