The use of DNA barcodes to estimate phylogenetic diversity in forest communities of southern China

To elucidate potential ecological and evolutionary processes associated with the assembly of plant communities, there is now widespread use of estimates of phylogenetic diversity that are based on a variety of DNA barcode regions and phylogenetic construction methods. However, relatively few studies consider how estimates of phylogenetic diversity may be influenced by single DNA barcodes incorporated into a sequence matrix (conservative regions vs. hypervariable regions) and the use of a backbone family‐level phylogeny. Here, we use general linear mixed‐effects models to examine the influence of different combinations of core DNA barcodes (rbcL, matK, ITS, and ITS2) and phylogeny construction methods on a series of estimates of community phylogenetic diversity for two subtropical forest plots in Guangdong, southern China. We ask: (a) What are the relative influences of single DNA barcodes on estimates phylogenetic diversity metrics? and (b) What is the effect of using a backbone family‐level phylogeny to estimate topology‐based phylogenetic diversity metrics? The combination of more than one barcode (i.e., rbcL + matK + ITS) and the use of a backbone family‐level phylogeny provided the most parsimonious explanation of variation in estimates of phylogenetic diversity. The use of a backbone family‐level phylogeny showed a stronger effect on phylogenetic diversity metrics that are based on tree topology compared to those that are based on branch lengths. In addition, the variation in the estimates of phylogenetic diversity that was explained by the top‐rank models ranged from 0.1% to 31% and was dependent on the type of phylogenetic community structure metric. Our study underscores the importance of incorporating a multilocus DNA barcode and the use of a backbone family‐level phylogeny to infer phylogenetic diversity, where the type of DNA barcode employed and the phylogenetic construction method used can serve as a significant source of variation in estimates of phylogenetic community structure.     

Methodology matters when estimating deer abundance: a global systematic review and recommendations for improvements

Deer (Cervidae) are key components of many ecosystems and estimating deer abundance or density is important to understanding these roles. Many field methods have been used to estimate deer abundance and density, but the factors determining where, when, and why a method was used, and its usefulness, have not been investigated. We systematically reviewed journal articles published during 2004–2018 to evaluate spatio-temporal trends in study objectives, methodologies, and deer abundance and density estimates, and determine how they varied with biophysical and anthropogenic attributes. We also reviewed the precision and bias of deer abundance estimation methods. We found 3,870 deer abundance and density estimates. Most estimates (58%) were for white-tailed deer (Odocoileus virginianus), red deer (Cervus elaphus), and roe deer (Capreolus capreolus). The 6 key methods used to estimate abundance and density were pedestrian sign (track or fecal) counts, pedestrian direct counts, vehicular direct counts, aerial direct counts, motion-sensitive cameras, and harvest data. There were regional differences in the use of these methods, but a general pattern was a temporal shift from using harvest data, pedestrian direct counts, and aerial direct counts to using pedestrian sign counts and motion-sensitive cameras. Only 32% of estimates were accompanied by a measure of precision. The most precise estimates were from vehicular spotlight counts and from capture–recapture analysis of images from motion-sensitive cameras. For aerial direct counts, capture–recapture methods provided the most precise estimates. Bias was robustly assessed in only 16 studies. Most abundance estimates were negatively biased, but capture–recapture methods were the least biased. The usefulness of deer abundance and density estimates would be substantially improved by 1) reporting key methodological details, 2) robustly assessing bias, 3) reporting the precision of estimates, 4) using methods that increase and estimate detection probability, and 5) staying up to date on new methods. The automation of image analysis using machine learning should increase the accuracy and precision of abundance estimates from direct aerial counts (visible and thermal infrared, including from unmanned aerial vehicles [drones]) and motion-sensitive cameras, and substantially reduce the time and cost burdens of manual image analysis.     

Detection limits of quantitative and digital PCR assays and their influence in presence–absence surveys of environmental DNA

A set of universal guidelines is needed to determine the limit of detection (LOD) in PCR‐based analyses of low‐concentration DNA. In particular, environmental DNA (eDNA) studies require sensitive and reliable methods to detect rare and cryptic species through shed genetic material in environmental samples. Current strategies for assessing detection limits of eDNA are either too stringent or subjective, possibly resulting in biased estimates of species’ presence. Here, a conservative LOD analysis grounded in analytical chemistry is proposed to correct for overestimated DNA concentrations predominantly caused by the concentration plateau, a nonlinear relationship between expected and measured DNA concentrations. We have used statistical criteria to establish formal mathematical models for both quantitative and droplet digital PCR. To assess the method, a new Grass Carp (Ctenopharyngodon idella) TaqMan assay was developed and tested on both PCR platforms using eDNA in water samples. The LOD adjustment reduced Grass Carp occupancy and detection estimates while increasing uncertainty—indicating that caution needs to be applied to eDNA data without LOD correction. Compared to quantitative PCR, digital PCR had higher occurrence estimates due to increased sensitivity and dilution of inhibitors at low concentrations. Without accurate LOD correction, species occurrence and detection probabilities based on eDNA estimates are prone to a source of bias that cannot be reduced by an increase in sample size or PCR replicates. Other applications also could benefit from a standardized LOD such as GMO food analysis and forensic and clinical diagnostics.     

Genetic mark–recapture population estimation in black bears and issues of scale

Abundance estimates for black bears (Ursus americanus) are important for effective management. Recently, DNA technology has resulted in widespread use of noninvasive, genetic capture–mark–recapture (CMR) approaches to estimate populations. Few studies have compared the genetic CMR methods to other estimation methods. We used genetic CMR to estimate the bear population at 2 study sites in northern New Hampshire (Pittsburg and Milan) in 2 consecutive years. We compared these estimates to those derived from traditional methods used by the New Hampshire Fish and Game Department (NHFG) using hunter harvest and mortality data. Density estimates produced with genetic CMR methods were similar both years and were comparable to those derived from traditional methods. In 2006, the estimated number of bears in Pittsburg was 79 (95% CI = 60–98) corresponding to a density of 15–24 (95% CI) bears/100 km²; the 2007 estimate was 83 (95% CI = 67–99; density = 16–24 bears/100 km²). In 2006, the estimated number of bears in Milan was 95 (95% CI = 74–117; density = 16–25 bears/100 km²); the 2007 estimate was 96 (95% CI = 77–114; density = 17–25 bears/100 km²). We found that genetic CMR methods were able to identify demographic variation at a local scale, including a strongly skewed sex ratio (2 M:1 F) in the Milan population. Genetic CMR is a useful tool for wildlife managers to monitor populations of local concern, where abundance or demographic characteristics may deviate from regional estimates. Future monitoring of the Milan population with genetic CMR is recommended to determine if the sex ratio bias continues, possibly warranting a change in local harvest regimes. © 2011 The Wildlife Society.     

Comparison of survey methods for wintering grassland birds

ABSTRACT Although investigators have evaluated the efficacy of survey methods for assessing densities of breeding birds, few comparisons have been made of survey methods for wintering birds, especially in grasslands. In winter, social behavior and spatial distributions often differ from those in the breeding season. We evaluated the degree of correspondence between density estimates based on different survey methods. Surveys were conducted during two winters (2001–2002 and 2002–2003) on 16 grassland sites in southwestern Oklahoma. Line‐transect (using a detection function to account for birds present but not detected) and area‐search (where density was based on the total count within a given area) methods were employed. Observations on line transects were also analyzed as strip transects, where density was based on total count within a given strip width and no detection function was used. Savannah Sparrows (Passerculus sandwichensis), LeConte's Sparrows (Ammodramus leconteii), Song Sparrows (Melospiza melodia), Smith's Longspurs (Calcarius pictus), Chestnut‐collared Longspurs (C. ornatus), and Eastern Meadowlarks (Sturnella magna) were sufficiently abundant to allow comparison. Area‐search density estimates tended to be higher than line‐transect estimates for Savannah Sparrows, Song Sparrows, and Eastern Meadowlarks, suggesting that some individuals initially located close to the transect line were not detected on line transects. The area‐search and line‐transect methods gave similar density estimates for Chestnut‐collared and Smith's longspurs. Area‐search estimates of Eastern Meadowlarks were significantly higher in the second year of the study only. For this species, area‐search estimates did not differ from those of strip transects covering an equal area, so the reason for the differing meadowlark estimates is not clear. Higher density estimates using the area‐search method likely resulted from: (1) birds that might escape detection by hiding were more likely detected (flushed) during area searches because of the repeated passes through the area, and (2) birds close to the line in line transects escape detection by hiding, biasing those estimates low. We also evaluated the correspondence of density rankings for the six species as determined by the different survey methods and for the same species across survey sites. Correlations among the six species of the area‐search results with those of line transects and strip transects generally were high, increasing in 2002–2003 when densities of birds were greater. All three methods provided similar density rankings among species. Density rankings within species across sites for the four non‐longspur species generally were concordant for the three methods, suggesting that any of them will adequately reflect among‐site differences, especially when densities vary greatly across sites. Further research is needed to determine the extent to which grassland birds are missed on line transects. We suggest that workers using line transects to study these species give careful consideration and make additional efforts to satisfy the distance‐sampling assumption that all birds on or near the line are detected. If density is measured as a total count in a fixed area, we recommend that observers pass within <10 m of all points in the area.     

Model misspecification confounds the estimation of rates and exaggerates their time dependency

While welcoming the comment of Ho et al. ( 2015 ), we find little that undermines the strength of our criticism, and it would appear they have misunderstood our central argument. Here we respond with the purpose of reiterating that we are (i) generally critical of much of the evidence presented in support of the time‐dependent molecular rate (TDMR) hypothesis and (ii) specifically critical of estimates of μ derived from tip‐dated sequences that exaggerate the importance of purifying selection as an explanation for TDMR over extended timescales. In response to assertions put forward by Ho et al. ( 2015 ), we use panmictic coalescent simulations of temporal data to explore a fundamental assumption for tip‐dated tree shape and associated mutation rate estimates, and the appropriateness and utility of the date randomization test. The results reveal problems for the joint estimation of tree topology, effective population size and μ with tip‐dated sequences using beast . Given the simulations, beast consistently obtains incorrect topological tree structures that are consistent with the substantial overestimation of μ and underestimation of effective population size. Data generated from lower effective population sizes were less likely to fail the date randomization test yet still resulted in substantially upwardly biased estimates of rates, bringing previous estimates of μ from temporally sampled DNA sequences into question. We find that our general criticisms of both the hypothesis of time‐dependent molecular evolution and Bayesian methods to estimate μ from temporally sampled DNA sequences are further reinforced.     

Beyond F<Subscript>ST</Subscript>: Analysis of population genetic data for conservation

Both the ability to generate DNA data and the variety of analytical methods for conservation genetics are expanding at an ever-increasing pace. Analytical approaches are now possible that were unthinkable even five years ago due to limitations in computational power or the availability of DNA data, and this has vastly expanded the accuracy and types of information that may be gained from population genetic data. Here we provide a guide to recently developed methods for population genetic analysis, including identification of population structure, quantification of gene flow, and inference of demographic history. We cover both allele-frequency and sequence-based approaches, with a special focus on methods relevant to conservation genetic applications. Although classical population genetic approaches such as F _st (and its derivatives) have carried the field thus far, newer, more powerful, methods can infer much more from the data, rely on fewer assumptions, and are appropriate for conservation genetic management when precise estimates are needed.     

Divergent estimates of herd‐wide caribou calf survival: Ecological factors and methodological biases

Population monitoring is a critical part of effective wildlife management, but methods are prone to biases that can hinder our ability to accurately track changes in populations through time. Calf survival plays an important role in ungulate population dynamics and can be monitored using telemetry and herd composition surveys. These methods, however, are susceptible to unrepresentative sampling and violations of the assumption of equal detectability, respectively. Here, we capitalized on 55 herd‐wide estimates of woodland caribou (Rangifer tarandus caribou) calf survival in Newfoundland, Canada, using telemetry (n = 1,175 calves) and 249 herd‐wide estimates of calf:cow ratios (C:C) using herd composition surveys to investigate these potential biases. These data included 17 herd‐wide estimates replicated from both methods concurrently (n = 448 calves and n = 17 surveys) which we used to understand which processes and sampling biases contributed to disagreement between estimates of herd‐wide calf survival. We used Cox proportional hazards models to determine whether estimates of calf mortality risk were biased by the date a calf was collared. We also used linear mixed‐effects models to determine whether estimates of C:C ratios were biased by survey date and herd size. We found that calves collared later in the calving season had a higher mortality risk and that C:C tended to be higher for surveys conducted later in the autumn. When we used these relationships to modify estimates of herd‐wide calf survival derived from telemetry and herd composition surveys concurrently, we found that formerly disparate estimates of woodland caribou calf survival now overlapped (within a 95% confidence interval) in a majority of cases. Our case study highlights the potential of under‐appreciated biases to impact our understanding of population dynamics and suggests ways that managers can limit the influence of these biases in the two widely applied methods for estimating herd‐wide survival.     

Population Estimates of Snowshoe Hares in the Southern Rocky Mountains

Abstract: In 1999 Canada lynx (Lynx canadensis) were reintroduced to the southern Rocky Mountains and in 2000 the species was listed as threatened under the Endangered Species Act in the contiguous United States (Colorado Division of Wildlife 2000, U.S. Fish and Wildlife Service 2000). To better evaluate the progress of this reintroduction, we conducted field studies to estimate population densities of snowshoe hares (Lepus americanus), the primary prey of lynx in Colorado, USA. We conducted our field studies in southwestern Colorado in winters 2002 and 2003. We estimated population densities in forested stands of mature Engelmann spruce (Picea engelmannii)-subalpine fir (Abies lasiocarpa) and mature lodgepole pine (Pinus contorta) using mark-recapture data and 3 methods for estimating effective area trapped: half trap interval, mean maximum distance moved (MMDM), and half MMDM. In Engelmann spruce-subalpine fir, we found density estimates ranged from 0.08 ± 0.03 (SE) hares/ha to 1.32 ± 0.15 hares/ha and in lodgepole pine, density estimates ranged from 0.06 ± 0.01 hares/ha to 0.34 ± 0.06 hares/ha, depending on year and method used for estimating effective area trapped. Our density estimates are similar to those reported at the low phase of the hare cycle in populations to the north (<0.1–1.1 hares/ha), where Canada lynx persist (Hodges 2000a). Although density estimates are a useful comparative tool, they depend upon methods used to estimate effective area trapped. Therefore, we urge caution in comparing our density estimates with those from other areas, which may have used dissimilar methods. We also examined effects of temperature and moon phase on capture success of snowshoe hares; extremely low temperatures affected capture success but moon phase did not. Capture success can be improved by trapping snowshoe hares at temperatures above their lower critical temperature (T_lc). If abundance estimates are derived from mark-recapture studies then effects of temperature should be included when modeling capture probabilities.     

Comparison of environmental inference approaches for ecometric analyses: Using hypsodonty to estimate precipitation

1. Ecometrics is the study of community‐level functional trait–environment relationships. We use ecometric analyses to estimate paleoenvironment and to investigate community‐level functional changes through time.
2. We evaluate four methods that have been used or have the potential to be used in ecometric analyses for estimating paleoenvironment to determine whether there have been systematic differences in paleoenvironmental estimation due to choice of the estimation method. Specifically, we evaluated linear regression, polynomial regression, nearest neighbor, and maximum‐likelihood methods to explore the predictive ability of the relationship for a well‐known ecometric dataset of mammalian herbivore hypsodonty metrics (molar tooth crown to root height ratio) and annual precipitation. Each method was applied to 43 Pleistocene fossil sites and compared to annual precipitation from global climate models. Sites were categorized as glacial or interglacial, and paleoprecipitation estimates were compared to the appropriate model.
3. Estimation methods produce results that are highly correlated with log precipitation and estimates from the other methods (p < 0.001). Differences between estimated precipitation and observed precipitation are not significantly different across the four methods, but maximum likelihood produces the most accurate estimates of precipitation. When applied to paleontological sites, paleoprecipitation estimates align more closely with glacial global climate models than with interglacial models regardless of the age of the site.
4. Each method has constraints that are important to consider when designing ecometric analyses to avoid misinterpretations when ecometric relationships are applied to the paleontological record. We show interglacial fauna estimates of paleoprecipitation more closely match glacial global climate models. This is likely because of the anthropogenic effects on community reassembly in the Holocene.

     

Measuring oxidative damage to DNA; HPLC and the comet assay compared

Depending on the analytical method employed estimates of background levels of base oxidation in human DNA vary over orders of magnitude. It is now realised that oxidation of guanine in vitro can result in serious overestimation of the nucleoside by HPLC (with electrochemical detection). We have modified procedures of isolation, hydrolysis and storage of DNA with the aim of eliminating this artefact. Vacuum- or freeze-drying, and dialysis, tend to encourage oxidation. We compare results obtained with HPLC and with the comet assay, which employs lesion-specific enzymes to introduce breaks in DNA at sites of oxidative damage. Although estimates of background levels of DNA oxidation using the comet assay are several-fold lower than the estimates by HPLC, both approaches have been used successfully to detect differences between human subjects or population groups that seem to relate to human disease and nutritional factors.     

Estimates of relatedness and inbreeding in goose strains from DNA fingerprints

The purpose of this study was to determine if DNA fingerprints (DFPs) could be used to estimate relatedness and inbreeding of strains of geese and to compare three methods of calculating relatedness indices. Strains included a control and selected strain from each of the Chinese and Synthetic (Chinese, Hungarian and Pilgrim) breeds. DFP patterns for each strain were based on individual DNA samples from six females, or on pooled DNA from 15 females different from those used for individual samples. Three relatedness indices were used, namely, genetic distance, modified Rogers distance and band sharing. All relatedness indices showed a closer relationship of strains within than between breeds. Correlation coefficients among relatedness indices were higher based on pooled DNA (r ≥|0·97|) than those based on individual DNA (r ≥|0·741). Inbreeding estimates were higher for selected compared with control strains. It appears that the use of DFPs to estimate relatedness, regardless of index used, and inbreeding can be valuable for studying geese where there is a limited breeding history.     

Comparison of methods for estimating density of forest songbirds from point counts

New analytical methods have been promoted for estimating the probability of detection and density of birds from count data but few studies have compared these methods using real data. We compared estimates of detection probability and density from distance and time-removal models and survey protocols based on 5- or 10-min counts and outer radii of 50 or 100 m. We surveyed singing male Acadian flycatchers (Empidonax virescens), cerulean warblers (Dendroica cerulea), Kentucky warblers (Oporornis formosus), Louisiana waterthrushes (Parkesia motacilla), wood thrushes (Hylocichla mustelina), and worm-eating warblers (Helmitheros vermivorum) in bottomland and upland forest across 5 states in the Central Hardwoods Bird Conservation Region during the breeding season in 2007 and 2008. Detection probabilities differed between distance and time-removal models and species detectabilities were affected differently by year, forest type, and state. Density estimates from distance models were generally higher than from time-removal models, resulting from lower detection probabilities estimated by distance models. We found support for individual heterogeneity (modeled as a finite mixture model) in the time-removal models and that 50-m radius counts generated density estimates approximately twice as high as 100-m radius counts. Users should be aware that in addition to estimating different components of detectability, density estimates derived from distance and time-removal models can be affected by survey protocol because some count durations and plot radii may better meet model assumptions than others. The choice of a method may not affect the use of estimates for relative comparisons (e.g., when comparing habitats) but could affect conclusions when used to estimate population size. We recommend careful consideration of assumptions when deciding on point-count protocol and selection of analysis methods. © 2011 The Wildlife Society.     

A Comparison of Methods for Estimating Northern Bobwhite Covey Detection Probabilities

Abstract: We compared the time-of-detection and logistic regression methods of estimating probability of detection for northern bobwhite (Colinus virginianus) coveys. Both methods are unusual in that they allow estimation of the total probability of detection (i.e., the product of the probability that a covey is available for detection [i.e., that a covey vocalizes] and detection given availability). The logistic regression method produced an average detection probability of 0.596 (SE = 0.020) and the time-of-detection method produced a detection probability estimate of 0.540 (SE = 0.086), and the 2 estimates were not significantly different. This is the first evaluation of the time-of-detection method with empirical field data. Although the time-of-detection and logistic regression method each have advantages, both can be used under appropriate conditions to improve estimates of bobwhite abundance by allowing for the estimation of detection probabilities. Improved estimates of bobwhite abundance will allow land managers to make more informed management decisions.     

Evidence of multiple vicariance in a marine suture‐zone in the Gulf of Mexico

Aim Our aim was to assess whether single or multiple vicariance event(s) have occurred in a marine suture‐zone in the northern Gulf of Mexico. We estimated the divergence time of two genetically distinct groups of lane snapper (Lutjanus synagris), distributed on either side of this zone, and compared it to the timing of other vicariance events described previously in the area. Location The northern Gulf of Mexico from the Texas coastline to the Atlantic coast of South Florida, USA. The marine suture‐zone is proximal to Mobile Bay in Alabama. Methods A Bayesian Markov chain Monte Carlo (MCMC) approach was used to estimate mutation‐corrected divergence and genetic migration between eastern and western groups of lane snapper, based on genotypic differences at 13 nuclear‐encoded microsatellites obtained previously from 77 and 171 individual samples, respectively. A second estimate of divergence time for eastern and western groups of lane snapper was generated, based on 590 base pairs of DNA sequence from the mitochondrially encoded NADH dehydrogenase subunit 4 (ND4) obtained previously from 45 and 93 individual samples, respectively. Results Both classes of genetic markers (microsatellites and mtDNA) indicated a fairly recent divergence. Confidence intervals for microsatellite‐based estimates suggested that divergence began less than 21 thousand years ago (ka), while confidence intervals for mitochondrial DNA‐based estimates suggested divergence began less than 130 ka. These estimates were not consistent with vicariance events in the literature, which are hypothesized to have occurred well before 135 ka. Main conclusions These results indicate that the marine suture‐zone in the northern Gulf of Mexico features multiple vicariance events and may be characterized by a complex geological/environmental history. We suggest that processes during or after the Wisconsin glaciation (c. 110–18 ka) may have created a previously unrecognized barrier for lane snapper and possibly other species as well.     

Branch Length Heterogeneity Leads to Nonindependent Branch Length Estimates and Can Decrease the Efficiency of Methods of Phylogenetic Inference

Branch length estimates play a central role in maximum-likelihood (ML) and minimum-evolution (ME) methods of phylogenetic inference. For various reasons, branch length estimates are not statistically independent under ML or ME. We studied the response of correlations among branch length estimates to the degree of among-branch length heterogeneity (BLH) in the model (true) tree. The frequency and magnitude of (especially negative) correlations among branch length estimates were both shown to increase as BLH increases under simulation and analytically. For ML, we used the correct model (Jukes–Cantor). For ME, we employed ordinary least-squares (OLS) branch lengths estimated under both simple p-distances and Jukes–Cantor distances, analyzed with and without an among-site rate heterogeneity parameter. The efficiency of ME and ML was also shown to decrease in response to increased BLH. We note that the shape of the true tree will in part determine BLH and represents a critical factor in the probability of recovering the correct topology. An important finding suggests that researchers cannot expect that different branches that were in fact the same length will have the same probability of being accurately reconstructed when BLH exists in the overall tree. We conclude that methods designed to minimize the interdependencies of branch length estimates (BLEs) may (1) reduce both the variance and the covariance associated with the estimates and (2) increase the efficiency of model-based optimality criteria. We speculate on possible ways to reduce the nonindependence of BLEs under OLS and ML. Received: 9 March 1999 / Accepted: 4 May 1999     

Estimating mountain goat abundance using DNA from fecal pellets

Non-invasive collection of tissue samples to obtain DNA for microsatellite genotyping required to estimate population size has been used for many wildlife species but rarely for ungulates. We estimated mountain goat (Oreamnos americanus) population size on a mountain complex in southwestern British Columbia by identification of individuals using DNA obtained from fecal pellet and hair samples collected during 3 sampling sessions. We identified 55 individuals from 170 samples that were successfully genotyped, and estimated a population of 77 mountain goats (SE = 7.4). Mean capture probability was 0.38 (SE = 0.037) per session. Our technique provides one of the first statistically rigorous estimates of abundance of an ungulate species using DNA derived primarily from fecal pellets. Our technique enables managers to obtain minimum counts or population estimates of ungulates in areas of low sightability that can be used for conservation and management. © 2011 The Wildlife Society.     

DNA isolation from soil samples for cloning in different hosts

Many protocols to extract DNA directly from soil samples have been developed in recent years. We employed two extraction methods which differed in the method of lysis and compared these methods with respect to yield, purity and degree of shearing. The main focus was on the specific isolation of DNA from different microorganisms, especially DNA from actinomycetes, as these cells are very difficult to lyse, in contrast to non-actinomycetes. Thus, we used both methods to isolate DNA from Pseudomonas, Arthrobacter and Rhodococcus and from soil spiked with the respective microorganisms. Both methods rendered high DNA yields with a low degree of shearing, but differed in the type of cells that were lysed. By one protocol (utilizing enzymatic lysis) only DNA from the Gram-negative Pseudomonas strain could be obtained whereas, by the other protocol (utilizing mechanical lysis), all microorganisms that were used could be lysed and DNA extracted from them. Using a combination of both protocols, DNA from those organisms could be obtained selectively. Furthermore, one of the protocols was modified, resulting in higher DNA yield and purity.