%0 Journal Article
%A Solymos, P.
%A Matsuoka, S.M.
%A Bayne, E.M.
%A Lele, S.R.
%A Fontaine, P.
%A Cumming, S.G.
%A Stralberg, D.
%A Schmiegelow, F.K.A.
%A Song, S.J.
%T Calibrating indices of avian density from non-standardized survey data: Making the most of a messy situation
%B Methods in Ecology and Evolution
%D 2013
%V 4
%P 1047-1058
%N 11
%X 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. We estimated singing rates
and EDR for 75 boreal forest songbird species and found that survey
protocol, especially point-count radius, explained most of the variation
in detectability. However, environmental and temporal covariates
(date, time, vegetation) affected singing rates and EDR for 73% and
59% of species, respectively. Unadjusted survey counts increased
by an average of 201% from a 5-min, 50-m radius survey to a 10-min,
100-m radius survey (n = 75 species). This variability was decreased
to 8·5% using detection probabilities estimated from a combination
of removal and distance sampling models. Our modelling approach reduced
computation 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. © 2013 British Ecological Society.
%2 Cited By (since 1996):2
Export Date: 27 November 2013
Source: Scopus
doi: 10.1111/2041-210X.12106
%( 2041210X (ISSN)
%K Boreal forest songbirds, Conditional maximum likelihood, Distance
sampling, Generalized linear models, Point counts, Predictive mapping,
Removal sampling, Statistical offsets
%# Luc
%Z timestamp=(2013.11.27)
%U http://www.scopus.com/inward/record.url?eid=2-s2.0-84885362142&partnerID=40&md5=1beecd3c22ebc78fa5e3b0bd05837664
%F SolymosMatsuokaBayneEtAl2013
%3 BibTeX type = ARTICLE