The comparison of isolation techniques for nematophagous fungi from soil

Using a single soil, a comparison was made of six well-known techniques for the isolation of nematophagous fungi. Each technique was tested for its ability to isolate the fungi present with regard to the number of species recovered, the number of plates needed to be 95% sure of isolating all the species possible and the amount of soil required. The advantages and disadvantages of each method are discussed. The results show that specific techniques are required for the isolation of endoparasites and predators respectively. The soil sprinkling technique and the Baermann funnel technique are shown to be the most efficient methods overall, with six and seven replicates required for 95% probability of isolating all the predator and endoparasite species respectively.     

A framework for estimating the sensitivity of eDNA surveys

Imperfect sensitivity, or imperfect detection, is a feature of all survey methods that needs to be accounted for when interpreting survey results. Detection of environmental DNA (eDNA) is increasingly being used to infer species distributions, yet the sensitivity of the technique has not been fully evaluated. Sensitivity, or the probability of detecting target DNA given it is present at a site, will depend on both the survey method and the concentration and dispersion of target DNA molecules at a site. We present a model to estimate target DNA concentration and dispersion at survey sites and to estimate the sensitivity of an eDNA survey method. We fitted this model to data from a species‐specific eDNA survey for Oriental weatherloach, Misgurnus anguillicaudatus, at three sites sampled in both autumn and spring. The concentration of target DNA molecules was similar at all three sites in autumn but much higher at two sites in spring. Our analysis showed the survey method had ≥95% sensitivity at sites where target DNA concentrations were ≥11 molecules per litre. We show how these data can be used to compare sampling schemes that differ in the number of field samples collected per site and number of PCR replicates per sample to achieve ≥95% sensitivity at a given target DNA concentration. These models allow researchers to quantify the sensitivity of eDNA survey methods to optimize the probability of detecting target species, and to compare DNA concentrations spatially and temporarily.     

Statistical properties of bootstrap estimation of phylogenetic variability from nucleotide sequences. I. Four taxa with a molecular clock.

The statistical properties of sample estimation and bootstrap estimation of phylogenetic variability from a sample of nucleotide sequences are studied by using model trees of three taxa with an outgroup and by assuming a constant rate of nucleotide substitution. The maximum-parsimony method of tree reconstruction is used. An analytic formula is derived for estimating the sequence length that is required if P, the probability of obtaining the true tree from the sampled sequences, is to be equal to or higher than a given value. Bootstrap estimation is formulated as a two-step sampling procedure: (1) sampling of sequences from the evolutionary process and (2) resampling of the original sequence sample. The probability that a bootstrap resampling of an original sequence sample will support the true tree is found to depend on the model tree, the sequence length, and the probability that a randomly chosen nucleotide site is an informative site. When a trifurcating tree is used as the model tree, the probability that one of the three bifurcating trees will appear in > or = 95% of the bootstrap replicates is < 5%, even if the number of bootstrap replicates is only 50; therefore, the probability of accepting an erroneous tree as the true tree is < 5% if that tree appears in > or = 95% of the bootstrap replicates and if more than 50 bootstrap replications are conducted. However, if a particular bifurcating tree is observed in, say, < 75% of the bootstrap replicates, then it cannot be claimed to be better than the trifurcating tree even if > or = 1,000 bootstrap replications are conducted. When a bifurcating tree is used as the model tree, the bootstrap approach tends to overestimate P when the sequences are very short, but it tends to underestimate that probability when the sequences are long. Moreover, simulation results show that, if a tree is accepted as the true tree only if it has appeared in > or = 95% of the bootstrap replicates, then the probability of failing to accept any bifurcating tree can be as large as 58% even when P = 95%, i.e., even when 95% of the samples from the evolutionary process will support the true tree. Thus, if the rate-constancy assumption holds, bootstrapping is a conservative approach for estimating the reliability of an inferred phylogeny for four taxa.     

The importance of including imperfect detection models in eDNA experimental design

Environmental DNA (eDNA) is DNA that has been isolated from field samples, and it is increasingly used to infer the presence or absence of particular species in an ecosystem. However, the combination of sampling procedures and subsequent molecular amplification of eDNA can lead to spurious results. As such, it is imperative that eDNA studies include a statistical framework for interpreting eDNA presence/absence data. We reviewed published literature for studies that utilized eDNA where the species density was known and compared the probability of detecting the focal species to the sampling and analysis protocols. Although biomass of the target species and the volume per sample did not impact detectability, the number of field replicates and number of samples from each replicate were positively related to detection. Additionally, increased number of PCR replicates and increased primer specificity significantly increased detectability. Accordingly, we advocate for increased use of occupancy modelling as a method to incorporate effects of sampling effort and PCR sensitivity in eDNA study design. Based on simulation results and the hierarchical nature of occupancy models, we suggest that field replicates, as opposed to molecular replicates, result in better detection probabilities of target species.     

Replication levels,false presences and the estimation of the presence/absence from eDNA metabarcoding data

Environmental DNA (eDNA) metabarcoding is increasingly used to study the present and past biodiversity. eDNA analyses often rely on amplification of very small quantities or degraded DNA. To avoid missing detection of taxa that are actually present (false negatives), multiple extractions and amplifications of the same samples are often performed. However, the level of replication needed for reliable estimates of the presence/absence patterns remains an unaddressed topic. Furthermore, degraded DNA and PCR/sequencing errors might produce false positives. We used simulations and empirical data to evaluate the level of replication required for accurate detection of targeted taxa in different contexts and to assess the performance of methods used to reduce the risk of false detections. Furthermore, we evaluated whether statistical approaches developed to estimate occupancy in the presence of observational errors can successfully estimate true prevalence, detection probability and false‐positive rates. Replications reduced the rate of false negatives; the optimal level of replication was strongly dependent on the detection probability of taxa. Occupancy models successfully estimated true prevalence, detection probability and false‐positive rates, but their performance increased with the number of replicates. At least eight PCR replicates should be performed if detection probability is not high, such as in ancient DNA studies. Multiple DNA extractions from the same sample yielded consistent results; in some cases, collecting multiple samples from the same locality allowed detecting more species. The optimal level of replication for accurate species detection strongly varies among studies and could be explicitly estimated to improve the reliability of results.     

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.     

The use of jackknifing for the evaluation of geographic profiling reliability

The use of geographic profiling (GP), based on “Rossmo's formula”, a technique derived from criminology, has been previously proven to be effective in assessing the origin of invading species. The application on Caulerpa taxifolia showed the most probable center of spread of the invasion. This article discusses a method of assessing the degree of robustness of the results obtained with Rossmo's method.To provide an evaluation of the reliability of geographic profiling results we used the jackknife technique, randomly eliminating part of the data set for a given number of replicates (500) in order to analyze the obtained result for each replicate. In GP the results are a series of images with geoprofiling prioritization, each produced with one of the replicates. These images can be summarized in three different ways: (1) OR, depicting all the high probability pixels from the series of replicates; (2) AND, depicting only those high probability pixels present in every replicate; and (3) MEAN, depicting the mean color value for each pixel calculated from all the replicates. We show that jackknifing can be a useful method to increase robustness of GP analysis in criminology, epidemiology and biological invasions. Summarizing jackknifing results with the OR logical operator yields the highest sensitivity and worst specificity, while the use of the AND operator increases specificity but reduces sensitivity. Using the mean of the pixel values maintains the visualization of the areas of highest priority (specificity), while also showing the surrounding area with varying colors, analogous to confidence limits.     

Estimation of the size of freshwater ciliate populations by a sub-sampling technique

A technique is described for the estimation of the size of ciliate populations based on replicated counts. Sample drops were taken by automatic pipettes of different volume from activated sludge and from a small oligotrophic stream. Specific aims were: 1) the estimation of the number of species; 2) the estimation of the number of individual in each species; 3) the selection of a suitable sub-sample size and number of replicates. For each volume the cumulative increase in species taken in successive sub-samples was determined. For each species the minimum permissible sub-sample volume and the number of replicates required for an allowable error of 10% and 25% were determined. Lastly, the relationship between the mean number of individuals counted for each species and the relative coefficient of variation was visualized.     

Spatial variability of throughfall chemistry and selected soil properties as influenced by stem distance in a mature Norway spruce (Picea abies,Karst.) stand

Our aims were to investigate the spatial variability of throughfall chemistry and soil parameters as influenced by stem distance and to evaluate the implication of the observed systematic and random patterns for the sampling strategy.One hundred throughfall samplers with a sampling area of 106 cm² each were established in a systematic grid around 5 trees in a mature Norway spruce; site of the Fichtelgebirge (Germany). One hundred soil cores were taken with an auger of 50 cm² next to the throughfall samplers. Soil samples were stratified according to genetic soil horizons and analysed for pH, exchangeable NH₄ ⁺, SO₄ ^2– and total-S. Throughfall samples were collected over a period of 6 months. For each sampler an aliquod sample was mixed over the observation period and analysed for major ions.The spatial variability of the element concentrations in throughfall, expressed by the coefficient of variance, was 21–164%, depending on the element considered. For precipitation volume, the coefficient of variance was only 3%. The distance to the stem influenced most element concentrations in throughfall with increasing concentrations approaching the stem. Steepest gradients were observed in case of SO₄ ^2– and H⁺.The spatial variability of the investigated soil parameters was also very high with the exception of pH. The SO₄ ^2– content of the forest floor reflected the gradients observed in throughfall, while for the other investigated soil parameters and soil horizons no significant relations to stem distance were found.To determine site representative throughfall concentrations and soil properties with the sample volumes and time intervals we used, the number of samples required to get a statistical error of less than 10% (with 95% probability) can be very high. In case of throughfall, more than 100, and in case of the soil parameters, more than 300 replicates would be required.     

Microwave irradiation is a useful tool for improving isolation of actinomycetes from soil

Actinomycetes are an important source of novel, biologically active compounds. New methods need to be developed for isolating previously unknown actinomycetes from soil. The objective of this experiment was to study microwave irradiation of soil as a means for isolating previously unknown actinomycetes. Soil samples were collected at ten elevations between 800 m and 3670 m on Taibai Mountain, Shaanxi Province, China. Moistened soil samples were irradiated at 120 W heating power (2450 MHz) for 3 min using a household microwave oven. Irradiation increased total actinomycete, streptomycete, and antagonistic actinomycete counts on three types of culture media. Irradiation also increased the number of culturable actinomycete isolates. Some actinomycete isolates were culturable only after the soil was irradiated, whereas other isolates could not be cultured after irradiation. Irradiation of soil from elevations >3000 m increased actinomycete counts significantly but had little effect on the number of culturable actinomycete isolates. In contrast, irradiation of samples from elevations <3000 m had relatively little effect on actinomycete counts, but significantly increased the number of culturable actinomycete isolates. We used 16S rDNA sequence analysis to identity 14 actinomycete isolates that were only culturable after irradiation. Microwave irradiation of soil was helpful for isolating Streptomyces spp., Nocardia spp., Streptosporangium spp., and Lentzea spp. Slightly more than 90% of the identified actinomycete species were biologically active. In conclusion, microwave irradiation is a useful tool for isolating biologically active actinomycetes from soil.     

Sample size considerations in genetic polymorphism studies.

OBJECTIVES: Molecular studies for genetic polymorphisms are being carried out for a number of different applications, such as genetic disorders in different populations, pharmacogenomics, genetic identification of ethnic groups for forensic and legal applications, genetic identification of breed/stock in animals and plants for commercial applications and conservation of germ plasm. In this paper, for a random sampling scheme, we address two questions: (A) What should be the minimum size of the sample so that, with a prespecified probability, all alleles at a given locus (or haplotypes at a given set of loci) are detected? (B) What should be the sample size so that the allele frequency distribution at a given locus (or haplotype frequency distribution at a given set of loci) is estimated reliably within permissible error limits? METHODS: We have used combinatorial probabilistic arguments and Monte Carlo simulations to answer these questions. RESULTS: We found that the minimum sample size required in case A depends mainly on the prespecified probability of detecting all alleles, while in case B, it varies greatly depending on the permissible error in estimation (which will vary with the application). We have obtained the minimum sample sizes for different degrees of polymorphism at a locus under high stringency, as well as a relaxed level of permissible error. We present a detailed sampling procedure for estimating allele frequencies at a given locus, which will be of use in practical applications. CONCLUSION: Since the sample size required for reliable estimation of allele frequency distribution increases with the number of alleles at the locus, there is a strong case for using biallelic markers (like single nucleotide polymorphisms) when the available sample size is about 800 or less.     

Probability of detecting nematode infestations for quarantine sampling with imperfect extraction efficacy

For quarantine sampling, it is of fundamental importance to determine the probability of finding an infestation when a specified number of units are inspected. In general, current sampling procedures assume 100% probability (perfect) of detecting a pest if it is present within a unit. Ideally, a nematode extraction method should remove all stages of all species with 100% efficiency regardless of season, temperature, or other environmental conditions; in practice however, no method approaches these criteria. In this study we determined the probability of detecting nematode infestations for quarantine sampling with imperfect extraction efficacy. Also, the required sample and the risk involved in detecting nematode infestations with imperfect extraction efficacy are presented. Moreover, we developed a computer program to calculate confidence levels for different scenarios with varying proportions of infestation and efficacy of detection. In addition, a case study, presenting the extraction efficacy of the modified Baermann's Funnel method on Aphelenchoides besseyi, is used to exemplify the use of our program to calculate the probability of detecting nematode infestations in quarantine sampling with imperfect extraction efficacy. The result has important implications for quarantine programs and highlights the need for a very large number of samples if perfect extraction efficacy is not achieved in such programs. We believe that the results of the study will be useful for the determination of realistic goals in the implementation of quarantine sampling.     

How many replicates of arrays are required to detect gene expression changes in microarray experiments? A mixture model approach

Background  

It has been recognized that replicates of arrays (or spots) may be necessary for reliably detecting differentially expressed genes in microarray experiments. However, the often-asked question of how many replicates are required has barely been addressed in the literature. In general, the answer depends on several factors: a given magnitude of expression change, a desired statistical power (that is, probability) to detect it, a specified Type I error rate, and the statistical method being used to detect the change. Here, we discuss how to calculate the number of replicates in the context of applying a nonparametric statistical method, the normal mixture model approach, to detect changes in gene expression.     

The shapes of neutral gene genealogies in two species: probabilities of monophyly,paraphyly, and polyphyly in a coalescent model

Abstract.— The genealogies of samples of orthologous regions from multiple species can be classified by their shapes. Using a neutral coalescent model of two species, I give exact probabilities of each of four possible genealogical shapes: reciprocal monophyly, two types of paraphyly, and polyphyly. After the divergence that forms two species, each of which has population size N , polyphyly is the most likely genealogical shape for the lineages of the two species. At ∼ 1.300 N generations after divergence, paraphyly becomes most likely, and reciprocal monophyly becomes most likely at ∼1.665 N generations. For a given species, the time at which 99% of its loci acquire monophyletic genealogies is ∼5.298 N generations, assuming all loci in its sister species are monophyletic. The probability that all lineages of two species are reciprocally monophyletic given that a sample from the two species has a reciprocally monophyletic genealogy increases rapidly with sample size, as does the probability that the most recent common ancestor (MRCA) for a sample is also the MRCA for all lineages from the two species. The results have potential applications for the testing of evolutionary hypotheses.     

Absence of evidence is not evidence of absence: Feral pigs as vectors of soil‐borne pathogens

Invasive soil‐borne pathogens are a major threat to forest ecosystems worldwide. The newly discovered soil pathogen, Phytophthora ‘taxon Agathis’ (PTA), is a serious threat to endemic kauri (Agathis australis: Araucariaceae) in New Zealand. This study examined the potential for feral pigs to act as vectors of PTA. We investigated whether snouts and trotters of feral pigs carry soil contaminated with PTA, and using these results determined the probability that feral pigs act as a vector. We screened the soil on trotters and snouts from 457 pigs for PTA using various baiting techniques and molecular testing. This study detected 19 species of plant pathogens in the soil on pig trotters and snouts, including a different Phytophthora species (Phytophthora cinnamomi). However, no PTA was isolated from the samples. A positive control experiment showed a test sensitivity of 0–3% for the baiting methods and the data obtained were used in a Bayesian probability modelling approach. This showed a posterior probability of 35–90% (dependent on test sensitivity scores and design prevalence) that pigs do vector PTA and estimated that a sample size of over 1000 trotters would be required to prove a negative result. We conclude that feral pigs cannot be ruled out as a vector of soil‐based plant pathogens and that there is still a high probability that feral pigs do vector PTA, despite our negative results. We also highlight the need to develop a more sensitive test for PTA in small soil samples associated with pigs due to unreliable detection rates using the current method.     

Methodologies for estimating the sample size required for genetic conservation of outbreeding crops

Summary The main purpose of germplasm banks is to preserve the genetic variability existing in crop species. The effectiveness of the regeneration of collections stored in gene banks is affected by factors such as sample size, random genetic drift, and seed viability. The objective of this paper is to review probability models and population genetics theory to determine the choice of sample size used for seed regeneration. A number of conclusions can be drawn from the results. First, the size of the sample depends largely on the frequency of the least common allele or genotype. Genotypes or alleles occurring at frequencies of more than 10% can be preserved with a sample size of 40 individuals. A sample size of 100 individuals will preserve genotypes (alleles) that occur at frequencies of 5%. If the frequency of rare genotypes (alleles) drops below 5%, larger sample sizes are required. A second conclusion is that for two, three, and four alleles per locus the sample size required to include a copy of each allele depends more on the frequency of the rare allele or alleles than on the number. Samples of 300 to 400 are required to preserve alleles that are present at a frequency of 1%. Third, if seed is bulked, the expected number of parents involved in any sample drawn from the bulk will be less than the number of parents included in the bulk. Fourth, to maintain a rate of breeding (F) of 1 %, the effective population size (N _e) should be at least 150 for three alleles, and 300 for four alleles. Fifth, equalizing the reproductive output of each family to two progeny doubles the effective size of the population. Based on the results presented here, a practical option is considered for regenerating maize seed in a program constrained by limited funds.Part of this paper was presented at the Global Maize Germplasm Workshop, CIMMYT, El Batan, Mexico, March 6–12, 1988     

Exploring the main factors influencing habitat preference of Popillia japonica in an area of recent introduction

The possibility of establishment of an invasive species in an area of new introduction is influenced by several factors, including weather conditions, soil characteristics, and species spread dynamics. Disentangling the role of multiple variables on habitat preference can provide important elements supporting the management of invasive species. In this work, we present a modelling framework that allows i) the identification of the main drivers influencing the probability of the presence of the invasive pest Japanese beetle Popillia japonica, in an area of recent introduction in Northern Italy, and ii) the evaluation of bi-dimensional niches to investigate the non-linear combined effects of couples of variables on the potential distribution of this species. Occurrence records of larval populations sampled between 2017 and 2019 in 8488 sites in Northern Italy were used in the present study. The sample sites were characterised based on a set of explanatory variables related to land use, soil characteristics, meteorological conditions, and infestation history. We performed a stepwise logistic regression analysis for testing the statistical significance of explanatory variables on the occurrence of local larval populations. Then, we implemented a Generalized Additive Model to investigate the bi-dimensional ecological niche determined by the interaction of two variables on the probability of the presence of P. japonica. The results highlight the prominent role of soil and weather variables and the infestation history of the species in driving the presence of P. japonica larvae. Less acidic soils, especially with sandy-skeletal particles, are preferred. A high density of P. japonica larvae is associated with medium content of soil organic carbon in the soil. Long drought periods or high precipitation levels reduce the probability of the presence of the species. Non-linear effects are observed between soil temperature variables and habitat preferences of P. japonica. The probability of the presence of P. japonica is also related to the number of years since the first occurrence of the species at the site. The results of the present work provide fundamental elements for guiding the assessment of the risk and the management of P. japonica.     

Use of classical bird census transects as spatial replicates for hierarchical modeling of an avian community

New monitoring programs are often designed with some form of temporal replication to deal with imperfect detection by means of occupancy models. However, classical bird census data from earlier times often lack temporal replication, precluding detection‐corrected inferences about occupancy. Historical data have a key role in many ecological studies intended to document range shifts, and so need to be made comparable with present‐day data by accounting for detection probability. We analyze a classical bird census conducted in the region of Murcia (SE Spain) in 1991 and 1992 and propose a solution to estimating detection probability for such historical data when used in a community occupancy model: the spatial replication of subplots nested within larger plots allows estimation of detection probability. In our study, the basic sample units were 1‐km transects, which were considered spatial replicates in two aggregation schemes. We fit two Bayesian multispecies occupancy models, one for each aggregation scheme, and evaluated the linear and quadratic effect of forest cover and temperature, and a linear effect of precipitation on species occupancy probabilities. Using spatial rather than temporal replicates allowed us to obtain individual species occupancy probabilities and species richness accounting for imperfect detection. Species‐specific occupancy and community size decreased with increasing annual mean temperature. Both aggregation schemes yielded estimates of occupancy and detectability that were highly correlated for each species, so in the design of future surveys ecological reasons and cost‐effective sampling designs should be considered to select the most suitable aggregation scheme. In conclusion, the use of spatial replication may often allow historical survey data to be applied formally hierarchical occupancy models and be compared with modern‐day data of the species community to analyze global change process.     

Global soil ciliate (Protozoa, Ciliophora) diversity: a probability-based approach using large sample collections from Africa, Australia and Antarctica

Large sample collections from Africa (92 samples), Australia (157) and Antarctica (90) were investigated for soil ciliates using the non-flooded Petri dish method, which re-activates the ciliates' resting cysts from air-dried samples. Species were determined from life and by silver impregnation. The African samples were the richest, containing 507 species (240 undescribed,=47%), followed by the Australian (361 species, 154=43% undescribed) and the Antarctic (95 species, 14=15% undescribed) samples. The percentage of new species/sample was consistently low, viz. 4–8% on average, indicating that new species were considerably undersampled relative to described ones, very probably due to methodological shortcomings, i.e. usually only cysts of the more euryoecious species could be reactivated. Thus, a probability theory-based statistical approach was applied to the data sets to compensate for the underestimated number of undescribed species. This procedure indicated that, depending on the region, 70–80% of the soil ciliates are still unknown and global soil ciliate diversity amounts to at least 1330–2000 species. Several indicators, especially the constant rate at which new species have been found during a 20-year period of intensive research, suggest that this estimate is conservative. This revised version was published online in August 2006 with corrections to the Cover Date.     

Does microhabitat influence the testate amoebae communities in the Nameri National Park,northeastern India? A tropical forest perspective

The community structure of testate amoebae inhabiting different microhabitats (soil and tree-moss) within a tropical forest biome in Nameri National Park, northeastern India, was investigated. A total of 33 testate amoebae species belonging to 13 genera were identified. Species belonging to the class Lobosea constituted 73% of total testate amoebae density in the soil habitat, whereas the class Filosea constituted the most dominant forms (58%) in the moist tree-moss habitat. The relative abundance of species was higher in the tree-moss habitat compared to the soil habitats of the forest. Although multivariate analysis suggested a significant difference in assemblage patterns between the habitats, the turnover in species (i.e., beta diversity) was insignificant. Species accumulation curves (SAC) constructed using both parametric and non-parametric species richness estimators revealed that the asymptote of species richness was achieved by a low number of sample replicates in both habitats. The temperature and pH of the substratum on testate amoebae distribution patterns suggest the importance of additional background factors on testate amoebae community structure. Further studies involving more biotopes, seasons, and trophic interactions are recommended to document a complete record of testate amoebae diversity and their interactions with environmental gradients in the tropical forest biomes of northeastern India.