Extensive population subdivision of the cuttlefish Sepia officinalis (Mollusca: Cephalopoda) around the Iberian Peninsula indicated by microsatellite DNA variation

8 páginas, 3 tablas, 3 figurasThe Atlantic Ocean-Mediterranean Sea junction has been proposed as an important phylogeographical area on the basis of concordance in genetic patterns observed at allozyme, mtDNA and microsatellite DNA markers in several marine species. This study presents microsatellite DNA data for a mobile invertebrate species in this area, the cuttlefish Sepia officinalis, allowing comparison of this relatively new class of DNA marker with previous allozyme results, and examination of the relative effects on gene flow of the Strait of Gibraltar and the Almerı´a-Oran oceanographic front. Genetic variation at seven microsatellite loci screened in six samples from NE Atlantic and Mediterranean coasts of the Iberian Peninsula was high (mean Na = 9.6, mean He = 0.725). Microsatellites detected highly significant subpopulation structuring (FST = 0.061; RST = 0.104), consistent with an isolation-by-distance model of low levels of gene flow. Distinct and significant clinal changes in allele frequencies between Atlantic and Mediterranean samples found at five out of seven loci, however indicate these results might be also consistent with an alternative model of secondary contact and introgression between previously isolated and divergent populations, as previously proposed for other marine species from the Atlantic-Mediterranean area. A pronounced ‘step’ change between SW Mediterranean samples associated with the Almerı´a-Oran front suggests this oceanographic feature may represent a contemporary barrier to gene flow.This research was partially supported by project AMB94-0371 (CICYT, Spain). MP-L was supported by a fellowship from University of Vigo (Spain).Peer reviewe

Patterns in the distribution of fish assemblages and their association with habitat variables in the Suaza River on its way through the Cueva de los Guácharos National Park, Colombia

Knowledge of the fish assemblages of Andean mountain streams is restricted to accessible areas. This study is the first biological survey of the remote Suaza River in the Colombian Andes, at its source in the Cueva de los Guácharos National Park. Mechanistic insight into the ecological patterns and gradients of the river is provided, focusing on the spatial distribution of fish communities in relation to environmental variables and habitat characteristics. Electrofishing surveys and macroinvertebrate sampling were carried out, the river habitat was characterized, three environmental quality indices were applied, and potential water pollutant concentrations were measured. Twenty-seven fish species were recorded - two of them exotic (Poecilia reticulata and Xiphophorus hellerii) - as well as 45 macroinvertebrate families. Fish species richness was higher at lower altitudes with gentle slopes, where habitat temperature, size and heterogeneity were higher. Although macroinvertebrate diversity slightly increased downstream following a similar pattern as fish species richness, it declined at lower sites. Fish assemblages were distributed in three clusters corresponding to headwaters, middle sections and lower reaches of the river, showing correlations with environmental factors, suggesting habitat preferences. Although the headwaters of the Suaza River remains pristine inside the park, human influence is responsible for ecosystem alteration downstream. © 2018 Université Laval

A hybrid Bayesian hierarchical model combining cohort and case–control studies for meta-analysis of diagnostic tests: Accounting for partial verification bias

To account for between-study heterogeneity in meta-analysis of diagnostic accuracy studies, bivariate random effects models have been recommended to jointly model the sensitivities and specificities. As study design and population vary, the definition of disease status or severity could differ across studies. Consequently, sensitivity and specificity may be correlated with disease prevalence. To account for this dependence, a trivariate random effects model had been proposed. However, the proposed approach can only include cohort studies with information estimating study-specific disease prevalence. In addition, some diagnostic accuracy studies only select a subset of samples to be verified by the reference test. It is known that ignoring unverified subjects may lead to partial verification bias in the estimation of prevalence, sensitivities and specificities in a single study. However, the impact of this bias on a meta-analysis has not been investigated. In this paper, we propose a novel hybrid Bayesian hierarchical model combining cohort and case-control studies and correcting partial verification bias at the same time. We investigate the performance of the proposed methods through a set of simulation studies. Two case studies on assessing the diagnostic accuracy of gadolinium-enhanced magnetic resonance imaging in detecting lymph node metastases and of adrenal fluorine-18 fluorodeoxyglucose positron emission tomography in characterizing adrenal masses are presented