Inventory statistics meet big data: complications for estimating numbers of species

PeerJ

article

Ali Khalighifar¹  Laura Jiménez¹  Claudia Nuñez-Penichet¹  Benedictus Freeman¹  Kate Ingenloff¹  Daniel Jiménez-García¹  Town Peterson¹ 

[1] Biodiversity Institute, University of Kansas;Department of Ecology and Evolutionary Biology, University of Kansas;Centro de Agroecología y Ambiente, Benemerita Universidad Autónoma de Puebla

关键词: Chao estimator;    Data quality;    Species richness;    Virtual biotas;   

DOI  :  10.7717/peerj.8872

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

We point out complications inherent in biodiversity inventory metrics when applied to large-scale datasets. The number of units of inventory effort (e.g., days of inventory effort) in which a species is detected saturates, such that crucial numbers of detections of rare species approach zero. Any rare errors can then come to dominate species richness estimates, creating upward biases in estimates of species numbers. We document the problem via simulations of sampling from virtual biotas, illustrate its potential using a large empirical dataset (bird records from Cape May, NJ, USA), and outline the circumstances under which these problems may be expected to emerge.

【 授权许可】

CC BY