dealing with varying detection probability, unequal sample sizes and clumped distributions in count data处理不同的探测概率,不平等的样本大小和成群分布统计数据.pdf

Dealing with Varying Detection Probability, Unequal Sample Sizes and Clumped Distributions in Count Data 1 2,3 ¨ 1,4 D. Johan Kotze *, Robert B. O’Hara , Susanna Lehvavirta 1 Department of Environmental Sciences, University of Helsinki, Helsinki, Finland, 2 Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, 3 Biodiversity and Climate Research Centre, Frankfurt am Main, Germany, 4 Botanic Garden, Finnish Museum of Natural History, University of Helsinki, Helsinki, Finland Abstract Temporal variation in the detectability of a species can bias estimates of relative abundance if not handled correctly. For example, when effort varies in space and/or time it becomes necessary to take variation in detectability into account when data are analyzed. We demonstrate the importance of incorporating seasonality into the analysis of data with unequal sample sizes due to lost traps at a particular density of a species. A case study of count data was simulated using a spring- active carabid beetle. Traps were ‘lost’ randomly during high beetle activity in high abundance sites and during low beetle activity in low abundance sites. Five different models were fitted to datasets with different levels of loss. If sample sizes were unequal and a seasonality variable was not included in models that assumed the number of individuals was log-normally distributed, the models severely under- or overestimated the true effect size. Results did not improve when seasonality and number of trapping days were included in these models as offset terms, but only performed well when the response variable was specified as following a negative binomial distribution. Finally, if seasonal variation of a species is unknown, which is oft