Inferring global species richness from megatransect data and undetected species estimates

IF 2.1 2区 生物学 Q1 ZOOLOGY Contributions to Zoology Pub Date : 2019-05-11 DOI:10.1163/18759866-20191347
B. Huber, A. Chao
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引用次数: 3

Abstract

Ratio-like approaches for estimating global species richness have been criticised for their unjustified extrapolation from regional to global patterns. Here we explore the use of cumulative percentages of ‘new’ (i.e., not formally described) species over large geographic areas (‘megatransects’) as a means to overcome this problem. In addition, we take into account undetected species and illustrate these combined methods by applying them to a family of spiders (Pholcidae) that currently contains some 1,700 described species. The raw global cumulative percentage of new species (‘new’ as of the end of 2008, when 1,001 species were formally described) is 75.1%, and is relatively constant across large biogeographic regions. Undetected species are estimated using the Chao2 estimator based on species incidence data (date by species and locality by species matrices). The estimated percentage of new species based on the date by species matrices is 76.0% with an estimated standard error (s.e.) of 2.6%. This leads to an estimated global species richness of about 4,200 with a 95% confidence interval of (3,300, 5,000). The corresponding values based on locality by species matrices are 84.2% (s.e. 3.0%) and 6,300 with a 95% confidence interval of (4,000, 8,600). Our results suggest that the currently known 1,700 species of Pholcidae may represent no more than about 25–40% of the total species richness. The impact of further biasing factors like geography, species size and distribution, cryptic species, and model assumptions needs to be explored.
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从大断面数据和未发现物种估计推断全球物种丰富度
估算全球物种丰富度的类似比率的方法因其从区域到全球模式的不合理推断而受到批评。在这里,我们探讨了在大地理区域(“样带”)内使用“新”(即未正式描述的)物种的累积百分比作为克服这一问题的手段。此外,我们还考虑到了未被发现的物种,并通过将其应用于蜘蛛科(磷虾科)来说明这些组合方法,该科目前包含约1700种已描述的物种。全球新物种的原始累积百分比(截至2008年底,1001个物种被正式描述为“新”)为75.1%,在大型生物地理区域中相对恒定。基于物种发生率数据(按物种的日期和按物种的位置矩阵),使用Chao2估计器来估计未检测到的物种。根据物种矩阵的数据,新物种的估计百分比为76.0%,估计标准误差为2.6%。这导致全球物种丰富度估计约为4200,置信区间为(33005000)。基于物种矩阵的局部性的相应值为84.2%(s.e.3.0%)和6300,95%置信区间为(40008600)。我们的研究结果表明,目前已知的1700种磷虾科物种可能不超过总物种丰富度的25-40%。需要探索地理、物种大小和分布、神秘物种和模型假设等进一步偏置因素的影响。
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来源期刊
Contributions to Zoology
Contributions to Zoology 生物-动物学
CiteScore
4.00
自引率
4.50%
发文量
16
审稿时长
>12 weeks
期刊介绍: Contributions to Zoology solicits high-quality papers in all systematics-related branches of comparative zoology (including paleozoology). Preference will be given to manuscripts dealing with conceptual issues and to integrative papers (e.g., ecology and biodiversity, morphology and phylogeny and character state evolution, phylogeny and historical biogeography, systematics and bioinformatics, bioinformatics and biodiversity, habitat disturbance and biogeography, etc.). Reviews and alpha-taxonomic contributions are considered for publication, but acceptance will depend on their high quality and exceptional nature.
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