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Estimation of local extinction rates when species detectability covaries with extinction probability: is it a problem?
Author(s) -
Jenouvrier Stephanie,
Boulinier Thierry
Publication year - 2006
Publication title -
oikos
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.672
H-Index - 179
eISSN - 1600-0706
pISSN - 0030-1299
DOI - 10.1111/j.0030-1299.2006.14276.x
Subject(s) - extinction (optical mineralogy) , estimator , covariance , statistics , complement (music) , sampling (signal processing) , local extinction , econometrics , extinction probability , range (aeronautics) , mathematics , ecology , sampling bias , sample size determination , biology , computer science , population , detector , population size , materials science , biological dispersal , sociology , composite material , paleontology , telecommunications , biochemistry , demography , complementation , gene , phenotype
Estimating the rate of change of the composition of communities is of direct interest to address many fundamental and applied questions in ecology. One methodological problem is that it is hard to detect all the species present in a community. Nichols et al. presented an estimator of the local extinction rate that takes into account species probability of detection, but little information is available on its performance. However, they predicted that if a covariance between species detection probability and local extinction rate exists in a community, the estimator of local extinction rate complement would be positively biased. Here, we show, using simulations over a wide range of parameters that the estimator performs reasonably well. The bias induced by biological factors appears relatively weak. The most important factor enhancing the performance (bias and precision) of the local extinction rate complement estimator is sampling effort. Interestingly, a potentially important biological bias, such as the covariance effect, improves the estimation for small sampling efforts, without inducing a supplementary overestimation when these sampling efforts are high. In the field, all species are rarely detectable so we recommend the use of such estimators that take into account heterogeneity in species detection probability when estimating vital rates responsible for community changes.