A novel method for estimating the number of species within a region

Ecologists are often required to estimate the number of species in a region or designated area. A number of diversity indices are available for this purpose and are based on sampling the area using quadrats or other means, and estimating the total number of species from these samples. In this paper, a novel theory and method for estimating the number of species is developed. The theory involves the use of the Laplace method for approximating asymptotic integrals. The method is shown to be successful by testing random simulated datasets. In addition, several real survey datasets are tested, including forests that contain a large number (tens to hundreds) of tree species, and an aquatic system with a large number of fish species. The method is shown to give accurate results, and in almost all cases found to be superior to existing tools for estimating diversity.     

On the estimation of species richness based on the accumulation of previously unrecorded species

Estimation of species richness of local communities has become an important topic in community ecology and monitoring. Investigators can seldom enumerate all the species present in the area of interest during sampling sessions. If the location of interest is sampled repeatedly within a short time period, the number of new species recorded is typically largest in the initial sample and decreases as sampling proceeds, but new species may be detected if sampling sessions are added. The question is how to estimate the total number of species. The data collected by sampling the area of interest repeatedly can be used to build species accumulation curves: the cumulative number of species recorded as a function of the number of sampling sessions (which we refer to as “species accumulation data”). A classic approach used to compute total species richness is to fit curves to the data on species accumulation with sampling effort. This approach does not rest on direct estimation of the probability of detecting species during sampling sessions and has no underlying basis regarding the sampling process that gave rise to the data. Here we recommend a probabilistic, nonparametric estimator for species richness for use with species accumulation data. We use estimators of population size that were developed for capture‐recapture data, but that can be used to estimate the size of species assemblages using species accumulation data. Models of detection probability account for the underlying sampling process. They permit variation in detection probability among species. We illustrate this approach using data from the North American Breeding Bird Survey (BBS). We describe other situations where species accumulation data are collected under different designs (e.g., over longer periods of time, or over spatial replicates) and that lend themselves to of use capture‐recapture models for estimating the size of the community of interest. We discuss the assumptions and interpretations corresponding to each situation.     

Bayesian estimation of group sizes for a coastal cetacean using aerial survey data

Many small cetacean, sirenian, and pinniped species aggregate in groups of large or variable size. Accurate estimation of group sizes is essential for estimating the abundance and distribution of these species, but is challenging as individuals are highly mobile and only partially visible. We developed a Bayesian approach for estimating group sizes using wide‐angle aerial photographic or video imagery. Our approach accounts for both availability and perception bias, including a new method (analogous to distance sampling) for estimating perception bias due to small image size in wide‐angle images. We demonstrate our approach through an application to aerial survey data for an endangered population of beluga whales (Delphinapterus leucas) in Cook Inlet, Alaska. Our results strengthen understanding of variation in group size estimates and allow for probabilistic statements about the size of detected groups. Aerial surveys are a standard tool for estimating the abundance and distribution of various marine mammal species. The role of aerial photographic and video data in wildlife assessment is expected to increase substantially with the widespread uptake of unmanned aerial vehicle technology. Key aspects of our approach are relevant to group size estimation for a broad range of marine mammal, seabird, other waterfowl, and terrestrial ungulate species.     

Three reasons to re-evaluate fungal diversity ‘on Earth and in the ocean’

Attempts to assess fungal global species richness are confounded by several problems: uncertainty about the number of described species, incomplete fungal inventories even at a high taxonomic level, high diversity of unknown, often small and elusive taxa, high levels of morphological conservation, and incomplete knowledge of their ecological and biogeographical distributions. The two main bases for estimating total fungal diversity are (1) the number of described species and their taxonomic structure, and (2) extrapolating species-area relationships. We argue that knowledge of fungal taxonomy and environmental sampling of fungi are both too incomplete for either approach to be reliable. However, it is likely that the true number of fungal species on the planet is a seven-digit number, and may even be an order of magnitude higher.     

Three reasons to re-evaluate fungal diversity ‘on Earth and in the ocean’

Attempts to assess fungal global species richness are confounded by several problems: uncertainty about the number of described species, incomplete fungal inventories even at a high taxonomic level, high diversity of unknown, often small and elusive taxa, high levels of morphological conservation, and incomplete knowledge of their ecological and biogeographical distributions. The two main bases for estimating total fungal diversity are (1) the number of described species and their taxonomic structure, and (2) extrapolating species-area relationships. We argue that knowledge of fungal taxonomy and environmental sampling of fungi are both too incomplete for either approach to be reliable. However, it is likely that the true number of fungal species on the planet is a seven-digit number, and may even be an order of magnitude higher.     

Bayesian estimation of species richness from quadrat sampling data in the presence of prior information

We consider the problem of estimating the number of species of an animal community. It is assumed that it is possible to draw up a list of species liable to be present in this community. Data are collected from quadrat sampling. Models considered in this article separate the assumptions related to the experimental protocol and those related to the spatial distribution of species in the quadrats. Our parameterization enables us to incorporate prior information on the presence, detectability, and spatial density of species. Moreover, we elaborate procedures to build the prior distributions on these parameters from information furnished by external data. A simulation study is carried out to examine the influence of different priors on the performances of our estimator. We illustrate our approach by estimating the number of nesting bird species in a forest.     

Estimating the species accumulation curve using mixtures

As a significant tool in ecological studies, the species accumulation curve or the collector's curve is the graph of the expected number of detected species as a function of sampling effort. The problem of estimating the species accumulation curve based on an empirical data set arising from quadrat sampling is studied in a nonparametric binomial mixture model. It will be shown that estimating the species accumulation curve not only is independent of the unknown number of species but also includes estimating the number of species as a limiting case. For the purpose of interpolation, moment-based estimators, associated with asymptotic confidence intervals, are developed from several points of view. A likelihood-based procedure is developed for the purpose of extrapolation, associated with bootstrap confidence intervals. The proposed methods are illustrated by ecological data sets.     

Estimation of species extinction: what are the consequences when total species number is unknown?

The species–area relationship (SAR) is known to overestimate species extinction but the underlying mechanisms remain unclear to a great extent. Here, I show that when total species number in an area is unknown, the SAR model exaggerates the estimation of species extinction. It is proposed that to accurately estimate species extinction caused by habitat destruction, one of the principal prerequisites is to accurately total the species numbers presented in the whole study area. One can better evaluate and compare alternative theoretical SAR models on the accurate estimation of species loss only when the exact total species number for the whole area is clear. This presents an opportunity for ecologists to simulate more research on accurately estimating Whittaker’s gamma diversity for the purpose of better predicting species loss.     

The relationship between species detection probability and local extinction probability

In community-level ecological studies, generally not all species present in sampled areas are detected. Many authors have proposed the use of estimation methods that allow detection probabilities that are <1 and that are heterogeneous among species. These methods can also be used to estimate community-dynamic parameters such as species local extinction probability and turnover rates (Nichols et al. Ecol Appl 8:1213–1225; Conserv Biol 12:1390–1398). Here, we present an ad hoc approach to estimating community-level vital rates in the presence of joint heterogeneity of detection probabilities and vital rates. The method consists of partitioning the number of species into two groups using the detection frequencies and then estimating vital rates (e.g., local extinction probabilities) for each group. Estimators from each group are combined in a weighted estimator of vital rates that accounts for the effect of heterogeneity. Using data from the North American Breeding Bird Survey, we computed such estimates and tested the hypothesis that detection probabilities and local extinction probabilities were negatively related. Our analyses support the hypothesis that species detection probability covaries negatively with local probability of extinction and turnover rates. A simulation study was conducted to assess the performance of vital parameter estimators as well as other estimators relevant to questions about heterogeneity, such as coefficient of variation of detection probabilities and proportion of species in each group. Both the weighted estimator suggested in this paper and the original unweighted estimator for local extinction probability performed fairly well and provided no basis for preferring one to the other.     

Of beta diversity,variance, evenness,and dissimilarity

The amount of variation in species composition among sampling units or beta diversity has become a primary tool for connecting the spatial structure of species assemblages to ecological processes. Many different measures of beta diversity have been developed. Among them, the total variance in the community composition matrix has been proposed as a single‐number estimate of beta diversity. In this study, I first show that this measure summarizes the compositional variation among sampling units after nonlinear transformation of species abundances. Therefore, it is not always adequate for estimating beta diversity. Next, I propose an alternative approach for calculating beta diversity in which variance is substituted by a weighted measure of concentration (i.e., an inverse measure of evenness). The relationship between this new measure of beta diversity and so‐called multiple‐site dissimilarity measures is also discussed.     

Estimating the Occupancy Rate of Spatially Rare or Hard to Detect Species: A Conditional Approach

Summary We consider the problem of estimating the occupancy rate of a target species in a region divided in spatial units (called quadrats); this quantity being defined as the proportion of quadrats occupied by this species. We mainly focus on spatially rare or hard to detect species that are typically detected in very few quadrats, and for which estimating the occupancy rate (with an acceptable precision) is problematic. We develop a conditional approach for estimating the quantity of interest; we condition on the presence of the target species in the region of study. We show that conditioning makes identifiable the occurrence and detectability parameters, regardless of the number of visits made in the sampled quadrats. Compared with an unconditional approach, it proves to be complementary, in that this allows us to deal with biological questions that cannot be addressed by the former. Two Bayesian analyses of the data are performed: one is noninformative, and the other takes advantage of the fact that some prior information on detectability is available. It emerges that taking such a prior into account significantly improves the precision of the estimate when the target species has been detected in few quadrats and is known to be easily detectable.     

鸟类调查的样线法和样点法比较:以崇明东滩春季盐沼鸟类调查为例

为了探讨样线法和样点法对盐沼湿地鸟类调查的有效性及适用性, 我们于2008年3–5月采用固定距离样线法和固定半径样点法对崇明东滩盐沼鸟类进行了调查。5次调查共记录到鸟类24种, 其中样线法记录到19种, 样点法记录到21种, 两种调查方法平均每次记录到的鸟类种数没有显著差异, 表明两种方法对盐沼鸟类种类的发现能力相似。两种方法得到的鸟类密度之间有显著的相关性,说明两种方法在反映鸟类群落中每种鸟类的相对数量方面具有可比性。但除了仅在一种调查方法中记录到的种类, 样点法调查得到的每种鸟类密度和鸟类总密度均高于样线法的调查结果。因此, 在对鸟类种群或群落的时空特征进行比较时, 需要考虑所采用的调查方法对调查结果的影响。     

Species diversity estimation of ambrosia and bark beetles in temperate mixed forests in Japan based on host phylogeny and specificity

Understandings of the effect of host plant phylogeny on the structure of herbivore assemblage is useful for estimating global species richness of herbivores. Here we test the relationship between host plant phylogeny and two assemblages including ambrosia beetle assemblage that have been considered to be the lowest host specificity among plant-dependent guilds. These results of local scale were used for estimating regional species richness by extrapolating to the number of plant order and species in Japan. The estimated numbers were compared with the numbers of described species in Japan. Tree trunks of 17 plant species representing 17 orders of all major lineages of Japanese tree flora were exposed for collecting wood boring beetle species. A total of 12 ambrosia and four bark beetle species were collected. Similarity of both ambrosia and bark beetle assemblages showed a significant negative trend with phylogenetic distance between focal host plant species. The regression model for this relationship was well fit by a linear model whereas previous studies used a semi-log model, which suggests a difference in mechanism of host utilization with host taxonomic levels. Our results showed a broader host range of ambrosia beetle assemblage in temperate forest than to a comparable study in tropical rainforests. Species richness estimated is lower than the described species in Japan, suggesting the need for more samples along the altitudinal gradients for accurate estimation for the Japanese fauna.     

西双版纳傣族利用野生蔬菜种类变化及原因分析

运用民族植物学的方法,选择西双版纳自然及社会经济发展不同的三个傣族村寨曼安、曼伞和曼广囡为研究对象,调查当地村民利用野生蔬菜情况,并探讨利用种类变化的原因。三个傣族村寨村民利用的野生蔬菜有228种,分属于75个科,其中曼安村寨147种,曼伞村寨144种,曼广囡村寨105种。通过Multivariate方差分析(P<0.05)表明:不同村寨的村民平均每人提及的野生蔬菜物种数存在显著差异;年轻组平均每人提及的野生蔬菜物种数明显低于年长组,不同性别之间差异不显著;野生蔬菜知识的流失在男性之间比女性更为严重。最后对影响野生蔬菜利用的因素,野生蔬菜利用变化的原因以及传统野生蔬菜知识的流失进行了分析,就如何保护传统知识进行了探讨。     

南亚热带森林群落种-多度的对数正态分布模型研究

通过对地处南亚热带的广东省黑石顶自然保护区森林群落的定点研究结果的分析表明：当用１,２,３,…分组每种个体数ｒ时,５个不同类型的群落样地的种一多度分布的直方图都呈明显的倒Ｊ－形;经Ｐｒｅｓｔｏｎ“倍程（ｏｃｔａｖｅｓ）”法分组ｒ后,其种－多度都服从对数正态分布。由种－多度模型可以推出另一新的模型一个体一多度分布模型,即Ｉ（Ｒ）＝２R0ＳＯＥＸＰ［［１ｎ２）２／４ａ２〕ＥＸＰ｛－ａ２（Ｒ－（ＲＯ＋１ｎ２／２ａ２）］２｝,它也符合对数正态分布。另外,还运用积分方法推导出估计总体（整个群落）中总种数Ｓ*和总个体数Ｉ*理论值的公式,用此公式估计的结果较为合理。     

Composition and diversity of the spider fauna in the canopy of a montane forest in Tanzania

Spiders were sampled using insecticide knockdown in an African montane forest in the Uzungwa Mountains of Tanzania. The results are used to discuss the faunal composition at the site and in comparison to other sites, and the implications of the results for estimating spider diversity in Africa are discussed. A total of 5233 adults comprising 149 species were collected from 11 samples covering a total of 906 m² of projected area. Three species contributed 45% of the sample. Previous insecticide knockdown studies of tropical lowland forest canopies have shown a dominance of Theridiidae, Salticidae and Araneidae. In the present study Linyphiidae dominated in abundance and were the second most diverse in terms of species richness. Other abundant families were Oonopidae and Pholcidae, while Theridiidae, Salticidae and Araneidae were rich in species. This supports a previous study, which indicated that the importance of linyphiids increases with altitude. Species richness was predicted using a number of estimators, which produced relatively similar results. Using the abundance-based estimator, Chao 1, the predicted richness for the total area sampled is 183 ± 15 species. This indicates that at least 20% of the area's spider community remains unsampled. A high ratio of undescribed species (approximately 80%) and a relatively high species turnover compared to a site 20 km away within the same forest complex suggests that the number of spiders in Africa could well be much higher than the current, published estimate of 20000 species.     

Estimating species richness from quadrat sampling data: a general approach

We consider the problem of estimating the number of species (denoted by S) of a biological community located in a region divided into n quadrats. To address this question, different hierarchical parametric approaches have been recently developed. Despite a detailed modeling of the underlying biological processes, they all have some limitations. Indeed, some assume that n is theoretically infinite; as a result, n and the sampling fraction are not a part of such models. Others require some prior information on S to be efficiently implemented. Our approach is more general in that it applies without limitation on the size of n, and it can be used in the presence, as well as in the absence, of prior information on S. Moreover, it can be viewed as an extension of the approach of Dorazio and Royle (2005, Journal of the American Statistical Association 100, 389-398) in that n is a part of the model and a prior distribution is placed on S. Despite serious computational difficulties, we have perfected an efficient Markov chain Monte Carlo algorithm, which allows us to obtain the Bayesian estimate of S. We illustrate our approach by estimating the number of species of a bird community located in a forest.     

Estimating the fraction of invariable codons with a capture-recapture method

Summary A codon-based approach to estimating the number of variable sites in a protein is presented. When first and second positions of codons are assumed to be replacement positions, a capture-recapture model can be used to estimate the number of variable codons from every pair of homologous and aligned sequences. The capture-recapture estimate is compared to a maximum likelihood estimate of the number of variable codons and to previous approaches that estimate the number of variable sites (not codons) in a sequence. Computer simulations are presented that show under which circumstances the capture-recapture estimate can be used to correct biases in distance matrices. Analysis of published sequences of two genes, calmodulin and serum albumin, shows that distance corrections that employ a capture-recapture estimate of the number of variable sites may be considerably different from corrections that assume that the number of variable sites is equal to the total number of positions in the sequence. Offprint requests to: A. Sidow