An implementation of Spatially Explicit Capture-Recapture (SECR) for estimating the density of gibbon groups from acoustic surveys.
This package also contains a user interface which can be accessed using the
gui function. See the online manual for more details
gibbonsecr relies on several functions from the secr package and uses an analagous system of objects. Model fitting is performed in a similar way using a fine grid of points called a mask to approximate the spatial integration component of the SECR likelihood. The defintion of 'trap' and 'session' are also consistent with secr. However gibbonsecr differs from secr in the following respects:
Supplementary information on detected animals in the form of estimated bearings and estimated distances can be incorporated in addition to the recapture data to improve precision in the density estimate.
Stochastic availability of animals can be modelled using the parameter
pcall. In general, this represents the proportion of animals being availablity
for detection on each survey occasion. For gibbons, it can be interpreted as the
proportion of groups that call on a given survey day.
Trap data objects associated with capture history objects are always
no group cov.
session cov and timecov attributes.
The main functions in gibbonsecr are:
||importing survey data, listening post locations and non-spatial covariates|
|| importing GIS shapefiles (
||constructing mask objects|
N.annamensis for an example data set from a survey of
Nomascus annamensis in northwestern Cambodia.
Darren Kidney [email protected]
Kidney D., Rawson B.M., Borchers D.L., Stevenson B.C., Marques T.A., & Thomas L. 2016. An Efficient Acoustic Density Estimation Method with Human Detectors Applied to Gibbons in Cambodia. PLoS ONE 11(5): e0155066.
Borchers, D. L., Stevenson, B. C., Kidney, D., Thomas, L., & Marques, T. A. 2015. A Unifying Model for Capture-Recapture and Distance Sampling Surveys of Wildlife Populations. Journal of the American Statistical Association, 110(509), 195-204.
N.annamensis, import_data, gfit
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