Rapid Eradication Assessment (REA) is a software interface to allow island eradication managers to estimate the probability of successful eradication of a pest animal species from an island using a grid of passive monitoring devices (i.e. absence following repeated non-detection). REA was designed by a collaboration of the University of Auckland, Landcare Research, and Conservacion de Islas. The original description of the method can be found in the paper by Samaniego-Herrera et al. published 2013 in the Journal of Applied Ecology.
There are two ways to use REA. The first is to estimate the probability of eradication success following an actual eradication program using an uploaded existing monitoring grid.
This grid is only done when grid-spacing is set to zero.
The second use estimates the probability of eradication success of a hypothetical monitoring regime specified by the user.
This is done by simulating random grids of specified uniform spacing when grid-spacing is set to >0.
This is useful for eradication managers planning eradication monitoring to a given level of confidence before placing devices in the field.
Confirming eradication is challenging as absence of evidence is not evidence of absence, i.e. just because no animals are detected does not mean none are present. REA works through repeated simulations of low density eradication survivors being monitored under a specified scenario of data and parameters. The user chooses an acceptable lower bound over which they would be confident of eradication success (e.g. Target = 90%). The REA model provides a measure of how often this level of confidence would be met. Managers should aim for their acceptable minimum level of confidence to be met nearly 100% (i.e. 97.5%) of the time. The REA outputs this as the red line in the graph (posterior 2.5% quantile) with the median estimate as the blue line (posterior 50% quantile). Exact numerical estimates are also returned.
Users must first enter the target island's geography as a GIS shape file. All components of the shapefile (shp, shx, dbf etc) must be combined into a single zip file, before being uploaded. If spacing is set to zero to estimate the probability of eradication success using an existing grid, the users must also upload a CSV file with x (easting) and y (northing) locations of the devices.
Monitoring data can be uploaded as a CSV file or entered manually for up to 12 sessions of eradication follow-up monitoring.
These data include the uniform grid spacing for simulation of hypothetical grids (or set spacing to zero for uploaded grids),
the number of nights of monitoring, the number of simulations to be undertaken (e.g. 2,000), the target minimum acceptable threshold probability for confirming absence (e.g. 0.90), and the number of years since eradication (e.g. 0.5 is 6 months).
Biological parameters can also be uploaded as a CSV file or entered manually. These include minimum, most likely and maximum values for g0 (probability a single device would detect an animal if it encountered it on a single night), sigma (the standard deviation of a half-normal home-range kernel), the prior probability of eradication having been successful (e.g. 0.80 for global rat eradication attempts), the probability of animals reinvading the island from elsewhere (e.g. 0.01), the annual growth rate of the target pest species if left uncontrolled (e.g. 5), and the average dispersal distance for a juvenile from its parent's home-range centre (e.g. 125 m).
to download an example containing Muertos data.
The zip contains 4 files:
the Device Locations (MuertosDeviceLocations.csv)
the Shapefile (MuertosMain.zip)
the Monitoring Data (MuertosMonitoringData.csv)
and the Biological Parameters (MuertosParameters.csv).
Or automatically populate the user interface with the button below:
Samaniego-Herrera, A., Anderson, D. P., Parkes, J. P., & Aguirre-Muoz, A. (2013). Rapid assessment of rat eradication after aerial baiting. Journal of Applied Ecology, 50(6), 1415-1421.
Russell, J. C., Binnie, H. R., Oh, J., Anderson, D. P., Samaniego-Herrera, A. (2016). Optimizing confirmation of invasive species eradication with rapid eradication assessment. Journal of Applied Ecology.
REA core R script
REA simulation R script
For any questions, problems or feedback please e-mail firstname.lastname@example.org