MÉTHODES D’HARMONISATION DES DONNÉES ET ANALYSE

 

Nous avons mis au point des méthodes statistiques spécialisées pour harmoniser des ensembles de données disparates en apportant des corrections qui tiennent compte de la méthode d’inventaire utilisée et de la détectabilité des espèces, afin d’en estimer la densité — en savoir plus. 

PUBLICATIONS

Evaluating time-removal models for estimating availability of boreal birds during point-count surveys: sample size requirements and model complexity. 2018. Condor 120, 765–786. https://doi.org/10.1650/CONDOR-18-32.1

Phylogeny and species traits predict bird detectability. 2018. Ecography 41, 1595–1603. https://doi.org/10.1111/ecog.03415

Ecological monitoring through harmonizing existing data: Lessons from the boreal avian modelling project. 2015. Wildlife Soc B 39, 480–487. https://doi.org/10.1002/wsb.567

Reviving common standards in point-count surveys for broad inference across studies. 2014. Condor 116, 599–608. https://doi.org/10.1650/CONDOR-14-108.1

Calibrating indices of avian density from non-standardized survey data: making the most of a messy situation. 2013. Methods Ecol Evol 4, 1047–1058. https://doi.org/10.1111/2041-210X.12106

Using binomial distance-sampling models to estimate the effective detection radius of point-count surveys across boreal Canada. 2012. Auk 129, 268–282. https://doi.org/10.1525/auk.2012.11190

RESOURCES

Ensembles Logiciels en R: detect, QPAD, lhreg, paired, bSims, and more...

Online Workshop: learn more about point count data analysis using these training videos and workshop resources...

QPAD Book: provides material for the workshop “Analysis of point-count data in the presence of variable survey methodologies and detection error”.