Journal article
Improving precision and reducing bias in biological surveys: estimating falseânegative error rates
Andrew J Tyre, undefined Brigitte Tenhumberg, undefined Scott A. Field, undefined Darren Niejalke, undefined Kirsten Parris, undefined Hugh P. Possingham
Ecological Applications | Published : 2003
DOI: 10.1890/02-5078
Abstract
The use of presence/absence data in wildlife management and biological surveys is widespread. There is a growing interest in quantifying the sources of error associated with these data. We show that falseânegative errors (failure to record a species when in fact it is present) can have a significant impact on statistical estimation of habitat models using simulated data. Then we introduce an extension of logistic modeling, the zeroâinflated binomial (ZIB) model that permits the estimation of the rate of falseânegative errors and the correction of estimates of the probability of occurrence for falseânegative errors by using repeated visits to the same site. Our simulations show that e..
View full abstract