Temperature Characteristics of Two Fomitiporia Fungi Determine Their Geographical Distributions in Japan

Two morphologically similar fungi, Fomitiporia torreyae and Fomitiporia punctata, are causal fungi of various tree diseases in Japan and are speculated to be distributed in different climatic zones. Clarifying their distribution ranges and climatic preferences would contribute to the prediction of disease occurrences and consideration of controls. In this study, we predicted the present geographical distributions of F. torreyae and F. punctata in Japan using a Maxent species distribution model to analyze our data and previously published collection records. In addition, we examined the importance of temperature on these predictions via jackknife analysis and evaluated the effects of temperature on mycelial growth and survival to elucidate determinants of their distribution. The predicted potential distributions showed that F. torreyae is mainly distributed in warmer areas compared to F. punctata. Jackknife analysis indicated the high importance of temperature variables for each fungal prediction. The two fungi were usually found at locations within upper or lower temperature limits for the growth and survival of each species. These results suggest that temperature is a key determinant of their distributions in Japan. This is the first report to predict fungal distribution based on species distribution modeling and evaluation of fungal physiological characteristics. This study indicates that the projected global warming will influence the future ranges of the two fungal species.

Temporal trends in Podarcis muralis and Lacerta bilineata populations in a fragmented landscape in western France: Results from a 14 year time series

Identifying population changes is a prerequisite for any conservation efforts, but to evaluate trends requires long-term data sets. In this paper, changes in population numbers in two species of European lizards, Lacerta bilineata and Podarcis muralis, are described. The results are based on counts of mortalities and live lizard presence on roads collected over a 14 year period, which indicated wide annual fluctuations in numbers in both species, with inter-specific annual trends strongly correlated. Snout to vent lengths (SVL) in L. bilineata were generally longer when annual numbers were higher but not in P. muralis. Regression analysis of the logarithmic transforms of annual lizard numbers as dependent variables and year as the independent variable indicated that despite population fluctuations, numbers of both species were stable or increased during the period of observation. Jackknife analysis identified unusually high numbers of L. bilineata in 2012 and P. muralis in 2010, but data from these years had minimal influence on the general trends with the peudo-regression coefficients generated from the Jackknife analysis in agreement with the true regressions. The results were therefore congruent, indicating annual fluctuations in both species were underpinned by long-term population stability.

Environmental Suitability of the Cassava Mealybug Assessments Using Ecological Niche Modelling

The cassava mealybug (Phenacoccus manihoti) is one of the main pests in the world and the risk of invasion posed by this pest is becoming more and more serious with regard to increasing areas of planting cassava in Asia. It is urgent to analyze the potential geography distribution of P. manihoti among cassava in China. In this study, three different ecological modeling methods (Maxent, ENFA and Mahalanobis typicality) were used to predict its potential distribution. The results show that Maxent has the best prediction performance, followed by ENFA, and Mahalanobis typicality has the poorest performance. Based on prediction outcome of Maxent suitable areas of P. manihoti in China are limited in Hainan, Yunnan, Guangxi, Guangdong, Fujian and a few regions of Sichuan, Hunan and Jiangxi. The jackknife analysis indicates that four variables have notable influence on the distribution pattern of P. manihoti, including in in Temperature annual range, Min temperature of coldest month, r, Temperature seasonality and Isothermality.

Sample Size, Library Composition, and Genotypic Diversity among Natural Populations of Escherichia coli from Different Animals Influence Accuracy of Determining Sources of Fecal Pollution

ABSTRACT A horizontal, fluorophore-enhanced, repetitive extragenic palindromic-PCR (rep-PCR) DNA fingerprinting technique (HFERP) was developed and evaluated as a means to differentiate human from animal sources of Escherichia coli. Box A1R primers and PCR were used to generate 2,466 rep-PCR and 1,531 HFERP DNA fingerprints from E. coli strains isolated from fecal material from known human and 12 animal sources: dogs, cats, horses, deer, geese, ducks, chickens, turkeys, cows, pigs, goats, and sheep. HFERP DNA fingerprinting reduced within-gel grouping of DNA fingerprints and improved alignment of DNA fingerprints between gels, relative to that achieved using rep-PCR DNA fingerprinting. Jackknife analysis of the complete rep-PCR DNA fingerprint library, done using Pearson's product-moment correlation coefficient, indicated that animal and human isolates were assigned to the correct source groups with an 82.2% average rate of correct classification. However, when only unique isolates were examined, isolates from a single animal having a unique DNA fingerprint, Jackknife analysis showed that isolates were assigned to the correct source groups with a 60.5% average rate of correct classification. The percentages of correctly classified isolates were about 15 and 17% greater for rep-PCR and HFERP, respectively, when analyses were done using the curve-based Pearson's product-moment correlation coefficient, rather than the band-based Jaccard algorithm. Rarefaction analysis indicated that, despite the relatively large size of the known-source database, genetic diversity in E. coli was very great and is most likely accounting for our inability to correctly classify many environmental E. coli isolates. Our data indicate that removal of duplicate genotypes within DNA fingerprint libraries, increased database size, proper methods of statistical analysis, and correct alignment of band data within and between gels improve the accuracy of microbial source tracking methods.

Use of Repetitive DNA Sequences and the PCR To DifferentiateEscherichia coli Isolates from Human and Animal Sources

ABSTRACT The rep-PCR DNA fingerprint technique, which uses repetitive intergenic DNA sequences, was investigated as a way to differentiate between human and animal sources of fecal pollution. BOX and REP primers were used to generate DNA fingerprints from Escherichia coli strains isolated from human and animal sources (geese, ducks, cows, pigs, chickens, and sheep). Our initial studies revealed that the DNA fingerprints obtained with the BOX primer were more effective for grouping E. coli strains than the DNA fingerprints obtained with REP primers. The BOX primer DNA fingerprints of 154 E. coli isolates were analyzed by using the Jaccard band-matching algorithm. Jackknife analysis of the resulting similarity coefficients revealed that 100% of the chicken and cow isolates and between 78 and 90% of the human, goose, duck, pig, and sheep isolates were assigned to the correct source groups. A dendrogram constructed by using Jaccard similarity coefficients almost completely separated the human isolates from the nonhuman isolates. Multivariate analysis of variance, a form of discriminant analysis, successfully differentiated the isolates and placed them in the appropriate source groups. Taken together, our results indicate that rep-PCR performed with the BOX A1R primer may be a useful and effective tool for rapidly determining sources of fecal pollution.