Uncertainty associated with river health assessment in a varying environment: The case of a predictive fish-based index in France

Sensitive biological measures of river ecosystem quality are needed to assess, maintain or restore ecological conditions of water bodies. Since our understanding of these complex systems is imperfect, decision-making requires recognizing uncertainty. In this study, a new predictive multi-metric index based on fish functional traits was developed to assess French rivers. Information on fish assemblage structure, local environment and human-induced disturbances of 1654 French river sites was compiled. A Bayesian framework was used to predict theoretical metric values in absence of human pressure and to estimate the uncertainty associated with these predictions. The uncertainty associated with the index score gives the confidence associated with the evaluation of site ecological conditions.Among the 228 potential metrics tested, only 11 were retained for the index computation. The final index is independent from natural variability and sensitive to human-induced disturbances. In particular, it is affected by the accumulation of different degradations and specific degradations including hydrological perturbations. Predictive uncertainty is globally lower for IPR+ than for underlying metrics.This new methodology seems appropriate to develop bio-indication tools accounting for uncertainty related to reference condition definition and could be extended to other biological groups and areas. Our results support the use of multi-metric indexes to assess rivers and strengthen the idea that examination of uncertainty could contribute greatly to the improvement of the assessment power of bio-indicators.     

Stable isotope-based statistical tools as ecological indicator of pollution sources in Mediterranean transitional water ecosystems

N-stable isotope analysis of macroalgae has become a popular method for the monitoring of nitrogen pollution in aquatic ecosystems. Basing on changes in their δ¹⁵N, macroalgae have been successfully used as biological traps to intercept nitrogen inputs. As different nitrogen sources differ in their isotopic signature, this technique provides useful information on the origin of pollutants and their extension in the water body. However, isotopic fractionation potentially resulting from microbial nitrogen processing, and indirect isotopic variations due to effects of physicochemical conditions on algal nutrient uptake and metabolism, may affect anthropogenic N isotopic values during transportation and assimilation. This in turn can affect the observed isotopic signature in the algal tissue, inducing isotopic variations not related to the origin of assimilated nitrogen, representing a “background noise” in isotope-based water pollution studies.In this study, we focused on three neighbouring coastal lakes (Caprolace, Fogliano and Sabaudia lakes) located south of Rome (Italy). Lakes were characterized by differences in terms of anthropogenic pressure (i.e. urbanization, cultivated crops, livestock grazing) and potential “background noise” levels (i.e. nutrient concentration, pH, microbial concentration). Our aim was to assess nitrogen isotopic variations in fragments of Ulva lactuca specimens after 48 h of submersion to identify and locate the origins of nitrogen pollutants affecting each lake. δ¹⁵N were obtained for replicated specimens of U. lactuca spatially distributed to cover the entire surface of each lake, previously collected from a benchmark, unpolluted site. In order to reduce the environmental background noise on isotopic observations, a Bayesian hierarchical model relating isotopic variation to environmental covariates and random spatial effects was used to describe and understand the distribution of isotopic signals in each lake.Our procedure (i) allowed to remove background noise and confounding effects from the observed isotopic signals; (ii) allowed to detect “hidden” pollution sources that would not be detected when not accounting for the confounding effect of environmental background noise; (iii) produced maps of the three lakes providing a clear representation of the isotopic signal variation even where background noise was high. Maps were useful to locate nitrogen pollution sources, identify the origin of the dissolved nitrogen and quantify the extent of pollutants, showing localized organic pollution impacting Sabaudia and Fogliano, but not Caprolace. This method provided a clear characterization of both intra- and inter-lake anthropogenic pressure gradients, representing a powerful approach to the ecological indication and nitrogen pollution management in complex systems, as transitional waterbodies are.     

Leveraging whole genome sequencing data for demographic inference with approximate Bayesian computation

Accounting for historical demographic features, such as the strength and timing of gene flow and divergence times between closely related lineages, is vital for many inferences in evolutionary biology. Approximate Bayesian computation (ABC) is one method commonly used to estimate demographic parameters. However, the DNA sequences used as input for this method, often microsatellites or RADseq loci, usually represent a small fraction of the genome. Whole genome sequencing (WGS) data, on the other hand, have been used less often with ABC, and questions remain about the potential benefit of, and how to best implement, this type of data; we used pseudo‐observed data sets to explore such questions. Specifically, we addressed the potential improvements in parameter estimation accuracy that could be associated with WGS data in multiple contexts; namely, we quantified the effects of (a) more data, (b) haplotype‐based summary statistics, and (c) locus length. Compared with a hypothetical RADseq data set with 2.5 Mbp of data, using a 1 Gbp data set consisting of 100 Kbp sequences led to substantial gains in the accuracy of parameter estimates, which was mostly due to haplotype statistics and increased data. We also quantified the effects of including (a) locus‐specific recombination rates, and (b) background selection information in ABC analyses. Importantly, assuming uniform recombination or ignoring background selection had a negative effect on accuracy in many cases. Software and results from this method validation study should be useful for future demographic history analyses.     

Effect of Zeitgeber Intensity Reduction on a Simulated Dual-Oscillator Human Circadian System: Classical and Dynamic Analysis

The two-oscillator model of human circadian rhythmicity was analyzed when a zeitgeber relative intensity of 1, 0.5, or 0.1 was introduced into the equations. Fourier analysis was compared with dynamic analysis such as attractor reconstruction or Liapunov exponent calculation. After a 50 or 90% reduction in zeitgeber intensity, the dynamics of the system became equivalent and differed significantly from those of a system with maximal zeitgeber intensity. When 10% aleatory noise was added to the data, the analysis was still applicable, and the results obtained were essentially the same as in the absence of noise. Dynamic analysis could thus provide a distinct classification for periodic data, based on the type of analysis.     

日本血吸虫童虫在终宿主体内的生长发育

本文对日本血吸虫童虫从终宿主的皮肤至肝门脉系移行过程的生长发育特点进行观察和分析,发现皮肤、肺、秆门三型童虫的体形、体长、体积、面积,发育率及生长速度均呈动态变化,而且这些变化与其生理功能是相适应的,因而为童虫体外培养、血吸虫病的免疫和药物预防研究提供材料来源和评价标准。     

Linkage analysis for 18 enzyme loci in Pinus rigida Mill.

Summary Estimates of recombination frequency among enzyme loci of pitch pine revealed two new linkages, Mdh3:Pgm2 (=0.01) and Pep1:Mdh4 (=0.38), and confirmed two previously established linkages. Tighter linkage (=0.30) was ruled out for nearly all gene pairs examined. In general, the Bayesian approach used in this study to test for linkage performed better than alternative methods.This work was supported by the School of Natural Resources, College of Agricultural and Life Sciences, University of Wisconsin, Madison, WI, and by McIntyre-Stennis, project no. 142-C385     

Computerized matching of relevés and association tables,with an application to the British National Vegetation Classification

When a new relevé is to be assigned to a pre-existing type, its composition is compared with an association table. Bayesian inference may seem a good way to make the comparison, but presents difficulties. In an alternative approach, three indices of goodness-of-fit are proposed. Compositional satisfaction is a measure of how well the species composition of the relevé fits the constancy classes in the table; it is a minor modification of the Czekanowski coefficient of similarity between observed and expected numbers of species in each constancy class. Dominance satisfaction is a modification of the Czekanowski similarity between the relevé and cover values that might be expected from the association table. Dominance constancy is a weighted mean of the constancy class of the four most abundant species in the relevé. A computer program, TABLEFIT, combines them into a single index. It has been tested on British mire vegetation.     

Probabilistic reconstruction of ancestral protein sequences

Using a maximum-likelihood formalism, we have developed a method with which to reconstruct the sequences of ancestral proteins. Our approach allows the calculation of not only the most probable ancestral sequence but also of the probability of any amino acid at any given node in the evolutionary tree. Because we consider evolution on the amino acid level, we are better able to include effects of evolutionary pressure and take advantage of structural information about the protein through the use of mutation matrices that depend on secondary structure and surface accessibility. The computational complexity of this method scales linearly with the number of homologous proteins used to reconstruct the ancestral sequence.