Page 175 - Contributed Paper Session (CPS) - Volume 1

CPS1255 Tsung-Jen Shen et al.

Predicting the number of newly
found rare species
Tsung-Jen Shen ,Youhua Chen 2
1
1 Institute of Statistics & Department of Applied Mathematics, National Chung Hsing
University, Taiwan
2 CAS Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization &
Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province,
Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China

Abstract
In natural ecological communities, most species are rare and thus susceptible
to extinction. Consequently, the prediction and identification of rare species
are of enormous value for conservation purposes. How many newly found
species will be rare in the next field survey? From a Bayesian viewpoint, by
using observed species abundance information in an ecological sample, we
developed an accurate estimator for estimating the number of new rare
species (e.g., singletons, doubletons, and tripletons) that will be found in an
additional unknown sample. A semi-numerical test showed that the proposed
Bayesian-weight estimator accurately predicted the number of rare new
species with low relative bias and relative root mean squared error and
accordingly, high accuracy.

Keywords
species rarity; biodiversity survey; Bayesian statistics; sampling theory; diversity
estimation

1. Introduction
Species abundance distribution, or rank-abundance distribution, is one of
the most important community patterns with wide applications in ecology
(Fisher et al. 1943; Preston 1948; Chen & Shen 2017). One of its key
applications is to predict species richness and diversity in ecological
communities, particularly when additional ecological surveys are needed
(Shen et al. 2003). However, almost all previous studies have utilized sample
relative abundance derived directly from sampled ecological communities to
generate rank-abundance distribution curves (Magurran 2004). This practice
tends to overestimate the true relative abundance of species (Chao et al. 2015),
with the overestimation being magnified for rare species or when the sample
size of the studied community is small.
Because rare species are highly vulnerable and prone to extinction when
exposed to climate change and habitat loss, the identification and protection
of rare species is always a top research priority in conservation biology and

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