Census planning and data analysis for burrow-nesting petrels
Analysing
census data
Once survey data have been collected in the ways set out by our planning guidance, and saved in the file format shown below, this page will guide you through a series of shiny apps that will guide you through the computing of parameters necessary for making final population estimates.
It begins by calculating response rates from playback surveys if necessary, highlighting issues with systematic biases such as changing response rates over the course of a survey.
Response rates are then combined with single visit survey data, and extrapolated to provide a whole-colony population estimate. Confidence intervals are bootstrapped.
The app will make reference to specific sections of Bolton et al.’s accompanying census planning guidance. It is advised to consult this document before survey design, during surveying and during analysis using Stormie Shiny apps and the Rmarkdown file below
Habitat 1 (grass)
Habitat 2 (bluebells)
Habitat 1 (boulders/rocks)
Unsurveyed area
Single playback survey
Multi-visit calibration
An island is shown with three different habitat types: grass, bluebells and boulders/rocks. The first premise is that response rates to playback might vary across these habitat types (or some other known variable). This could be because sound permeates the habitat differently, or because birds differ in condition etc. The reason is, however, of secondary importance. Of primary importance is measuring response rates independently for areas where there are biological reasons to think they might vary, or randomly selecting areas to measure response rates for. The multi-visit calibration areas aim to do this, providing sites are chosen properly. At these sites, repeated visits to representative plots will allow a habitat specific/ sub-colony specific response rate to be calculated. Then survey plots (the single playback survey squares) can receive single-visit playback and using the response rate suitable for that habitat, or sub-colony, a number of AOS can be estimated for the single-visit survey plot. This can then be extrapolated to the area that is the same habitat to give a global estimate, and this can be summed across habitat types.
Which app(s) do I need?
Is this a 'blind' playback survey*?
YES
NO
First calculate response rates using a Response Rate App (see below), then use the Extrapolation App
Go straight to the Extrapolation App
* a blind playback survey is where it is unknown whether the sites tested are occupied
STORMIE apps
Calculate response rates using the du feu method:
https://seabirdshiny.shinyapps.io/dufeu_3/
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calculate response rates using the geometric series method:
https://seabirdshiny.shinyapps.io/maximum_likelihood/
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population estimate Extrapolation
Once you have response rates, Download the extrapolation r markdown file below:
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This approach requires some experience of coding with R.
Follow the steps in the file and get in touch with us if guidance is needed.
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