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Résumé :
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Large-scale monitoring programs represent a two-level, nested sampling scheme: first, a spatial sample of quadrats or other study sites is selected, within which a second sample, of individuals, occupied quadrats or species, is chosen. To produce meaningful numbers, a monitoring program ought to be based on a spatial probability sample, otherwise the inferences obtained may be biased with respect to the desired statistical population about which one wants to learn something. Moreover, all bird counts and detection-nondetection records (misleadingly also called "presence-absence data") are binomial random variables, much like the flip of a coin. The binomial distribution is the theoretical basis of all animal or plant surveys and explains and predicts all of their most salient features: 1. repeated counts C vary automatically, even under identical conditions; 2. on average, a count amounts to a proportion p of true population size N, where p is the detection probability and 3. any comparison between two or more counts represents the simultaneous comparison of the associated true population size N and of the detection probability p. For instance, a temporal trend in Counts may be due to a genuine trend in the underlying population size or to a trend in detection probability or to a combination of the two. Any direct interpretation of counts always implies one of two assumptions, either that of p = I or that of p
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