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QPAD: Calibrating indices of avian density from non-standardized survey data

The analysis of large heterogeneous data sets of avian point-count surveys compiled across studies is hindered by a lack of analytical approaches that can deal with detectability and variation in survey protocols.

We reformulated removal models of avian singing rates and distance sampling models of the effective detection radius (EDR) to control for the effects of survey protocol and temporal and environmental covariates on detection probabilities.

  • These estimating procedures as described in Solymos et al. (2013) are implemented in the detect R package.

  • The estimates of singing rates and effective detection distances for North American boreal forest songbird species is provided as part of the QPAD package.

Using offsets derived from these estimates can significantly reduce the computational burden when fitting complex models to large data sets and can be used with a wide range of statistical techniques for inference and prediction of avian densities.

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Get the recent version as:

library(devtools)
install_github("psolymos/QPAD")

If you have trouble with devtools, try this repo and drat.

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Cite

Solymos et al. 2013. Calibrating indices of avian density from non-standardized survey data: making the most of a messy situation Methods in Ecology and Evolution, 4, 1047-1058.

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