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We introduce a fast, new algorithm for inferring from allele count data the FST parameters describing genetic distances among a set of populations and/or unrelated diploid individuals, and a tree with branch lengths corresponding to FST values. The tree can reflect historical processes of splitting and divergence, but seeks to represent the actual genetic variance as accurately as possible with a tree structure. We generalise two major approaches to defining FST, via correlations and mismatch probabilities of sampled allele pairs, which measure shared and non-shared components of genetic variance. A diploid individual can be treated as a population of two gametes, which allows inference of coancestry coefficients for individuals as well as for populations, or a combination of the two. A simulation study illustrates that our fast method-of-moments estimation of FST values, simultaneously for multiple populations/individuals, gains statistical efficiency over pairwise approaches when the population structure is close to tree-like. We apply our approach to genome-wide genotypes from the 26 worldwide human populations of the 1000 Genomes Project. We first analyse at the population level, then a subset of individuals and in a final analysis we pool individuals from the more homogeneous populations. This flexible analysis approach gives advantages over traditional approaches to population structure/coancestry, including visual and quantitative assessments of long-standing questions about the relative magnitudes of within- and between-population genetic differences.

© 2018 Elsevier B.V. Recently, Lund and Iyer (L&I) raised an argument regarding the use of likelihood ratios in court. In our view, their argument is based on a lack of understanding of the paradigm. L&I argue that the decision maker should not accept the expert's likelihood ratio without further consideration. This is agreed by all parties. In normal practice, there is often considerable and proper exploration in court of the basis for any probabilistic statement. We conclude that L&I argue against a practice that does not exist and which no one advocates. Further we conclude that the most informative summary of evidential weight is the likelihood ratio. We state that this is the summary that should be presented to a court in every scientific assessment of evidential weight with supporting information about how it was constructed and on what it was based.

© 2018 Elsevier B.V. Recently, Lund and Iyer (L&I) raised an argument regarding the use of likelihood ratios in court. In our view, their argument is based on a lack of understanding of the paradigm. L&I argue that the decision maker should not accept the expert's likelihood ratio without further consideration. This is agreed by all parties. In normal practice, there is often considerable and proper exploration in court of the basis for any probabilistic statement. We conclude that L&I argue against a practice that does not exist and which no one advocates. Further we conclude that the most informative summary of evidential weight is the likelihood ratio. We state that this is the summary that should be presented to a court in every scientific assessment of evidential weight with supporting information about how it was constructed and on what it was based.

Novel species of fungi described in this study include those from various countries as follows: Australia: Banksiophoma australiensis (incl. Banksiophoma gen. nov.) on Banksia coccinea, Davidiellomycesaustraliensis (incl. Davidiellomyces gen. nov.) on Cyperaceae, Didymocyrtis banksiae on Banksia sessilis var. cygnorum, Disculoides calophyllae on Corymbia calophylla, Harknessia banksiae on Banksia sessilis, Harknessia banksiae-repens on Banksia repens, Harknessia banksiigena on Banksia sessilis var. cygnorum, Harknessia communis on Podocarpus sp., Harknessia platyphyllae on Eucalyptus platyphylla, Myrtacremonium eucalypti (incl. Myrtacremonium gen. nov.) on Eucalyptus globulus, Myrtapenidiella balenae on Eucalyptus sp., Myrtapenidiella eucalyptigena on Eucalyptus sp., Myrtapenidiella pleurocarpae on Eucalyptuspleurocarpa, Paraconiothyrium hakeae on Hakea sp., Paraphaeosphaeria xanthorrhoeae on Xanthorrhoea sp., Parateratosphaeria stirlingiae on Stirlingia sp., Perthomyces podocarpi (incl. Perthomyces gen. nov.) on Podocarpus sp., Readeriella ellipsoidea on Eucalyptus sp., Rosellinia australiensis on Banksia grandis, Tiarosporella corymbiae on Corymbia calophylla, Verrucoconiothyriumeucalyptigenum on Eucalyptus sp., Zasmidium commune on Xanthorrhoea sp., and Zasmidium podocarpi on Podocarpus sp. Brazil: Cyathus aurantogriseocarpus on decaying wood, Perenniporia brasiliensis on decayed wood, Perenniporia paraguyanensis on decayed wood, and Pseudocercospora leandrae-fragilis on Leandrafragilis.Chile: Phialocephala cladophialophoroides on human toe nail. Costa Rica: Psathyrella striatoannulata from soil. Czech Republic: Myotisia cremea (incl. Myotisia gen. nov.) on bat droppings. Ecuador: Humidicutis dictiocephala from soil, Hygrocybe macrosiparia from soil, Hygrocybe sangayensis from soil, and Polycephalomyces onorei on stem of Etlingera sp. France: Westerdykella centenaria from soil. Hungary: Tuber magentipunctatum from soil. India: Ganoderma mizoramense on decaying wo

© 2017 An update was performed of the classic experiments that led to the view that profile probability assignments are usually within a factor of 10 of each other. The data used in this study consist of 15 Identifiler loci collected from a wide range of forensic populations. Following Budowle et al. [1], the terms cognate and non-cognate are used. The cognate database is the database from which the profiles are simulated. The profile probability assignment was usually larger in the cognate database. In 44%–65% of the cases, the profile probability for 15 loci in the non-cognate database was within a factor of 10 of the profile probability in the cognate database. This proportion was between 60% and 80% when the FBI and NIST data were used as the non-cognate databases. A second experiment compared the match probability assignment using a generalised database and recommendation 4.2 from NRC II (the 4.2 assignment) with a proxy for the matching proportion developed using subpopulation allele frequencies and the product rule. The findings support that the 4.2 assignment has a large conservative bias. These results are in agreement with previous research results.

© 2017 An update was performed of the classic experiments that led to the view that profile probability assignments are usually within a factor of 10 of each other. The data used in this study consist of 15 Identifiler loci collected from a wide range of forensic populations. Following Budowle et al. [1], the terms cognate and non-cognate are used. The cognate database is the database from which the profiles are simulated. The profile probability assignment was usually larger in the cognate database. In 44%–65% of the cases, the profile probability for 15 loci in the non-cognate database was within a factor of 10 of the profile probability in the cognate database. This proportion was between 60% and 80% when the FBI and NIST data were used as the non-cognate databases. A second experiment compared the match probability assignment using a generalised database and recommendation 4.2 from NRC II (the 4.2 assignment) with a proxy for the matching proportion developed using subpopulation allele frequencies and the product rule. The findings support that the 4.2 assignment has a large conservative bias. These results are in agreement with previous research results.

With the advance to one scientific name for each fungal species, the generic names in the class Sordariomycetes typified by sexual and asexual morphs are evaluated based on their type species to determine if they compete with each other for use or protection. Recommendations are made for which of the competing generic names should be used based on criteria such as priority, number of potential names changes, and frequency of use. Some recommendations for well-known genera include Arthrinium over Apiospora, Colletotrichum over Glomerella, Menispora over Zignoëlla, Microdochium over Monographella, Nigrospora over Khuskia, and Plectosphaerella over Plectosporium. All competing generic names are listed in a table of recommended names along with the required action. If priority is not accorded to sexually typified generic names after 2017, only four names would require formal protection: Chaetosphaerella over Oedemium, Diatrype over Libertella, Microdochium over Monographella, and Phaeoacremonium over Romellia and Togninia. Concerning species in the recommended genera, one replacement name (Xylaria benjaminii nom. nov.) is introduced, and the following new combinations are made: Arthrinium sinense, Chloridium caesium, C. chloroconium, C. gonytrichii, Corollospora marina, C. parvula, C. ramulosa, Juncigena fruticosae, Melanospora simplex, Seimatosporium massarina, Sporoschisma daemonoropis, S. taitense, Torpedospora mangrovei, Xylaria penicilliopsis, and X. termiticola combs. nov.