Capitalizing on opportunistic data for monitoring relative abundances of species.
With the internet, a massive amount of information on species abundance can be collected by citizen science programs. However, these data are often difficult to use directly in statistical inference, as their collection is generally opportunistic, and the distribution of the sampling effort is often not known. In this article, we develop a general statistical framework to combine such "opportunistic data" with data collected using schemes characterized by a known sampling effort. Under some structural assumptions regarding the sampling effort and detectability, our approach makes it possible to estimate the relative abundance of several species in different sites. It can be implemented through a simple generalized linear model. We illustrate the framework with typical bird datasets from the Aquitaine region in south-western France. We show that, under some assumptions, our approach provides estimates that are more precise than the ones obtained from the dataset with a known sampling effort alone. When the opportunistic data are abundant, the gain in precision may be considerable, especially for rare species. We also show that estimates can be obtained even for species recorded only in the opportunistic scheme. Opportunistic data combined with a relatively small amount of data collected with a known effort may thus provide access to accurate and precise estimates of quantitative changes in relative abundance over space and/or time.
Laboratoire de Mathématiques d'Orsay, UMR 8628, Université Paris-Sud, 91405 Orsay Cedex, France.|CMAP, UMR 7641, Ecole Polytechnique, route de Saclay, 91128 Palaiseau Cedex, France.
Christophe
C
Giraud
Office national de la chasse et de la faune sauvage, Saint Benoist, BP 20. 78612 Le Perray en Yvelines, France.
Clément
C
Calenge
Laboratoire de Mathématiques d'Orsay, UMR 8628, Université Paris-Sud, 91405 Orsay Cedex, France.
Camille
C
Coron
CESCO, UMR 7204, MNHN-CNRS-UPMC, CP51, 55 rue Buffon, 75005 Paris, France.
Romain
R
Julliard
D000818:Animals; D001699:Biometry / Q000379:methods; D001717:Birds; D003627:Data Interpretation, Statistical; D005602:France; D015233:Models, Statistical; D011156:Population Density; D011157:Population Dynamics
Detection probability; Opportunistic data; Sampling effort; Species distribution map