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Observer error in vegetation surveys:a review

Journal of Plant Ecology 2016年第4期9卷 367-379页

作者： Lloyd W.Morrison Department of Biology Missouri State University901 S.National AvenueSpringfieldMO 65897USA National Park Service Heartland Inventory and Monitoring Program6424 W.Farm Road 182RepublicMO 65738USA

Aims vegetation sampling employing observers is prone to both inter-observer and intra-observer *** types of errors are common:(i)overlooking error(*** observing species actually present),(ii)misidentification error(*** correctly identifying species)and(iii)estimation error(*** accurately estimating abundance).I conducted a literature review of 59 articles that provided quantitative estimates or statistical inferences regarding observer error in vegetation *** FindingsAlmost all studies(92%)that tested for a statistically significant effect of observer error found at least one significant *** surveys of species composition,mean pseudoturnover(the percentage of species overlooked by one observer but not another)was 10-30%.Species misidentification rates were on the order of 5-10%.The mean coefficient of variation(CV)among observers in surveys of vegetation cover was often several hundred%for species with low cover,although CVs of 25-50%were more representative of species with mean covers of>50%.A variety of metrics and indices(including commonly used diversity indices)and multivariate data analysis techniques(including ordinations and classifications)were found to be sensitive to observer *** of error commonly include both characteristics of the vegetation(*** size of populations,rarity,morphology,phenology)and attributes of the observers(*** fatigue,personal biases,differences in experience,physical stress).The use of multiple observers,additional training including active feedback approaches,and continual evaluation and calibration among observers are recommended as strategies to reduce observer error in vegetation surveys.

关键词： interobserver error intraobserver error misidentification pseudoturnover vegetation sampling

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