Non-parametric Richness Estimators Research Articles

Nitrous oxide reductase (nosZ) gene fragments differ between native and cultivated Michigan soils.

The effect of standard agricultural management on the genetic heterogeneity of nitrous oxide reductase (nosZ) fragments from denitrifying prokaryotes in native and cultivated soil was explored. Thirty-six soil cores were composited from each of the two soil management conditions. nosZ gene fragments were amplified from triplicate samples, and PCR products were cloned and screened by restriction fragment length polymorphism (RFLP). The total nosZ RFLP profiles increased in similarity with soil sample size until triplicate 3-g samples produced visually identical RFLP profiles for each treatment. Large differences in total nosZ profiles were observed between the native and cultivated soils. The fragments representing major groups of clones encountered at least twice and four randomly selected clones with unique RFLP patterns were sequenced to verify nosZ identity. The sequence diversity of nosZ clones from the cultivated field was higher, and only eight patterns were found in clone libraries from both soils among the 182 distinct nosZ RFLP patterns identified from the two soils. A group of clones that comprised 32% of all clones dominated the gene library of native soil, whereas many minor groups were observed in the gene library of cultivated soil. The 95% confidence intervals of the Chao1 nonparametric richness estimator for nosZ RFLP data did not overlap, indicating that the levels of species richness are significantly different in the two soils, the cultivated soil having higher diversity. Phylogenetic analysis of deduced amino acid sequences grouped the majority of nosZ clones into an interleaved Michigan soil cluster whose cultured members are alpha-Proteobacteria. Only four nosZ sequences from cultivated soil and one from the native soil were related to sequences found in gamma-Proteobacteria. Sequences from the native field formed a distinct, closely related cluster (D(mean) = 0.16) containing 91.6% of the native clones. Clones from the cultivated field were more distantly related to each other (D(mean) = 0.26), and 65% were found outside of the cluster from the native soil, further indicating a difference in the two communities. Overall, there appears to be a relationship between use and richness, diversity, and the phylogenetic position of nosZ sequences, indicating that agricultural use of soil caused a shift to a more diverse denitrifying community.

WHEN TO QUIT? ESTIMATING SPIDER SPECIES RICHNESS IN A NORTHERN EUROPEAN DECIDUOUS FOREST

Terrestrial arthropod surveys and inventories frequently suffer from undersampling bias; common species are over-represented and rare species may be missed entirely. This study compared a rapid (3 days) and intense inventory of spiders from one hectare of a mature beech forest (Fagus sylvaticus) in Hestehaven, Denmark, comprising 8,710 adult spiders of 66 species to a previous, much more thorough, bi-weekly survey of two years duration from the same site that comprised 42,273 spiders (adult and juvenile) of 141 species. Non-parametric species richness estimators were used to assess the degree of undersampling bias in various data partitions. The current study used five experienced, four novice col- lectors, and five semi-quantitative collecting methods. Method and time of day strongly affected numbers of species and adults per sample. Collector experience affected numbers of species but not numbers of adults per sample. Despite the intensive collecting, number of adults per sample did not decrease over the course of the study. At the end of the sampling, 31 species were still rare in the sample (singletons or doubletons). Non-parametric richness estimators suggest that the actual richness of adult spiders in the study plot at this time of year and susceptible to the methods used was about 80 species. Species turnover between the two surveys (ca 23 years) was remarkably small: the two lists were 92% identical. The base- line study suggests that the rarity of 12 of the 31 rare species was artifactual (10 due to phenology, one to method, another to spatial edge effects). The rarity of the remainder is unexplained and by default is interpreted as undersampling bias.

Performance of nonparametric species richness estimators in a high diversity plant community

Abstract. The efficiency of four nonparametric species richness estimators — first‐order Jackknife, second‐order Jackknife, Chao2 and Bootstrap — was tested using simulated quadrat sampling of two field data sets (a sandy ‘Dune’ and adjacent ‘Swale’) in high diversity shrublands (kwongan) in south‐western Australia. The data sets each comprised > 100 perennial plant species and > 10 000 individuals, and the explicit (x‐y co‐ordinate) location of every individual. We applied two simulated sampling strategies to these data sets based on sampling quadrats of unit sizes 1/400th and 1/100th of total plot area. For each site and sampling strategy we obtained 250 independent sample curves, of 250 quadrats each, and compared the estimators’ performances by using three indices of bias and precision: MRE (mean relative error), MSRE (mean squared relative error) and OVER (percentage overestimation). The analysis presented here is unique in providing sample estimates derived from a complete, field‐based population census for a high diversity plant community. In general the true reference value was approached faster for a comparable area sampled for the smaller quadrat size and for the swale field data set, which was characterized by smaller plant size and higher plant density. Nevertheless, at least 15–30% of the total area needed to be sampled before reasonable estimates of St (total species richness) were obtained. In most field surveys, typically less than 1% of the total study domain is likely to be sampled, and at this sampling intensity underestimation is a problem. Results showed that the second‐order Jackknife approached the actual value of St more quickly than the other estimators. All four estimators were better than Sobs (observed number of species). However, the behaviour of the tested estimators was not as good as expected, and even with large sample size (number of quadrats sampled) all of them failed to provide reliable estimates. First‐ and second‐order Jackknives were positively biased whereas Chao2 and Bootstrap were negatively biased. The observed limitations in the estimators’ performance suggests that there is still scope for new tools to be developed by statisticians to assist in the estimation of species richness from sample data, especially in communities with high species richness.

Species-Area and Species-Individual Relationships for Tropical Trees: A Comparison of Three 50-ha Plots

1 Species-accumulation curves for woody plants were calculated in three tropical forests, based on fully mapped 50-ha plots in wet, old-growth forest in Peninsular Malaysia, in moist, old-growth forest in central Panama, and in dry, previously logged forest in southern India. A total of 610 000 stems were identified to species and mapped to < Im accuracy. Mean species number and stem number were calculated in quadrats as small as 5 m x 5 m to as large as 1000 m x 500 m, for a variety of stem sizes above 10 mm in diameter. Species-area curves were generated by plotting species number as a function of quadrat size; species-individual curves were generated from the same data, but using stem number as the independent variable rather than area. 2 Species-area curves had different forms for stems of different diameters, but species-individual curves were nearly independent of diameter class. With < 10(4) stems, species-individual curves were concave downward on log-log plots, with curves from different forests diverging, but beyond about 104 stems, the log-log curves became nearly linear, with all three sites having a similar slope. This indicates an asymptotic difference in richness between forests: the Malaysian site had 2.7 times as many species as Panama, which in turn was 3.3 times as rich as India. 3 Other details of the species-accumulation relationship were remarkably similar between the three sites. Rectangular quadrats had 5-27% more species than square quadrats of the same area, with longer and narrower quadrats increasingly diverse. Random samples of stems drawn from the entire 50 ha had 10-30% more species than square quadrats with the same number of stems. At both Pasoh and BCI, but not Mudumalai. species richness was slightly higher among intermediate-sized stems (50-100mm in diameter) than in either smaller or larger sizes, These patterns reflect aggregated distributions of individual species, plus weak density-dependent forces that tend to smooth the species abundance distribution and 'loosen' aggregations as stems grow. 4 The results provide support for the view that within each tree community, many species have their abundance and distribution guided more by random drift than deterministic interactions. The drift model predicts that the species-accumulation curve will have a declining slope on a log-log plot, reaching a slope of O.1 in about 50 ha. No other model of community structure can make such a precise prediction. 5 The results demonstrate that diversity studies based on different stem diameters can be compared by sampling identical numbers of stems. Moreover, they indicate that stem counts < 1000 in tropical forests will underestimate the percentage difference in species richness between two diverse sites. Fortunately, standard diversity indices (Fisher's sc, Shannon-Wiener) captured diversity differences in small stem samples more effectively than raw species richness, but both were sample size dependent. Two nonparametric richness estimators (Chao. jackknife) performed poorly, greatly underestimating true species richness.