Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/95490
標題: Estimating species pools for a single ecological assemblage
作者: Shen, Tsung-Jen
Chen, Youhua
Chen, You-Fang
關鍵字: Asymptotic variance;Distributional aggregation;Jackknife estimator;Regional processes;Sampling theory;Unseen species
出版社: BMC ECOLOGY
Project: BMC ecology, Volume 17, Issue 1, Page(s) 45.
摘要: 
The species pool concept was formulated over the past several decades and has since played an important role in explaining multi-scale ecological patterns. Previous statistical methods were developed to identify species pools based on broad-scale species range maps or community similarity computed from data collected from many areas. No statistical method is available for estimating species pools for a single local community (sampling area size may be very small as ≤ 1 km2). In this study, based on limited local abundance information, we developed a simple method to estimate the area size and richness of a species pool for a local ecological community. The method involves two steps. In the first step, parameters from a truncated negative trinomial model characterizing the distributional aggregation of all species (i.e., non-random species distribution) in the local community were estimated. In the second step, we assume that the unseen species in the local community are most likely the rare species, only found in the remaining part of the species pool, and vice versa, if the remaining portion of the pool was surveyed and was contrasted with the sampled area. Therefore, we can estimate the area size of the pool, as long as an abundance threshold for defining rare species is given. Since the size of the pool is dependent on the rarity threshold, to unanimously determine the pool size, we developed an optimal method to delineate the rarity threshold based on the balance of the changing rates of species absence probabilities in the sampled and unsampled areas of the pool.
URI: http://hdl.handle.net/11455/95490
DOI: 10.1186/s12898-017-0155-7
Appears in Collections:統計學研究所

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