Assessment of the uncertainty of trace metal and nitrogen concentrations in mosses due to sampling,sample preparation and chemical analysis based on the French contribution to ICP-Vegetation

Moss bio-monitoring is a convenient tool for establishing specific or large-scale exposure to atmospheric trace metals and nitrogen pollution. However, the uncertainty associated with sampling, sample preparation and chemical analysis of bio-monitors has been poorly documented, with the exception of one study dealing with lichens; thus, the uncertainty associated with moss bio-monitoring has never been assessed. Here, we propose following the Eurachem guidelines to determine the uncertainties associated with the concentrations of elements measured in mosses during the sampling survey across France in 2011. In addition, we assess the analytical method used in four surveys from 1996 to 2011. Uncertainties were expressed as linear functions of the element concentrations, with minimum and maximum slopes of 14 and 61%, corresponding to nitrogen and chromium, and a median of 32%. Although the data reveal that some steps of the protocol should be performed carefully, they also indicate that the protocol was executed properly and is reproducible. The chemical analyses contribute to a small proportion of the uncertainty associated with the protocol, except for the analysis of chromium. The sampling period, and intra-site variability largely contribute to this uncertainty. The moss species did not introduce additional uncertainty. This integrative assessment of measurement uncertainty will help improve the protocol for future surveys. Such studies could be useful for developing a standard operating procedure and could be used to improve comparisons between countries and to identify temporal trends across Europe.     

Fluctuating natural selection accounts for the evolution of diversification bet hedging

Natural environments are characterized by unpredictability over all time scales. This stochasticity is expected on theoretical grounds to result in the evolution of ‘bet-hedging’ traits that maximize the long term, or geometric mean fitness even though such traits do not maximize fitness over shorter time scales. The geometric mean principle is thus central to our interpretation of optimality and adaptation; however, quantitative empirical support for bet hedging is lacking. Here, I report a quantitative test using the timing of seed germination—a model diversification bet-hedging trait—in Lobelia inflata under field conditions. In a phenotypic manipulation study, I find the magnitude of fluctuating selection acting on seed germination timing—across 70 intervals throughout five seasons—to be extreme: fitness functions for survival are complex and multimodal within seasons and significantly dissimilar among seasons. I confirm that the observed magnitude of fluctuating selection is sufficient to account for the degree of diversification behaviour characteristic of individuals of this species. The geometric mean principle has been known to economic theory for over two centuries; this study now provides a quantitative test of optimality of a bet-hedging trait in nature.     

A review of the use of uncertainty factors in the health risk assessment of some metals

Because metals can produce health risks, standards for regulating metal exposure are necessary. The purpose of this chapter is to review the application of uncertainty factors to mercury, arsenic, and cadmium. By the conventional method, uncertainty factors are often applied to animal studies to establish the reference dose (RfD) in humans. However, with the availability of a better database from improved study designs, it was demonstrated that uncertainty factors can be decreased. Incorporation of more pharmacokinetic and mechanistic data into the risk assessment process, as well as discussions between risk assessors and the research community to identify research needs are essential in reducing uncertainty factors.     

Two-Dimensional Monte Carlo Simulation and Beyond: A Comparison of Several Probabilistic Risk Assessment Methods Applied to a Superfund Site

Four different probabilistic risk assessment methods were compared using the data from the Sangamo Weston/Lake Hartwell Superfund site. These were one-dimensional Monte Carlo, two-dimensional Monte Carlo considering uncertainty in the concentration term, two-dimensional Monte Carlo considering uncertainty in ingestion rate, and microexposure event analysis. Estimated high-end risks ranged from 2.0×10^?4 to 3.3×10^?3. Microexposure event analysis produced a lower risk estimate than any of the other methods due to incorporation of time-dependent changes in the concentration term.     

Uncertainty in Nutrient Spiraling: Sensitivity of Spiraling Indices to Small Errors in Measured Nutrient Concentration

Abstract Proper assessment of ecological data must consider uncertainty. However, reported estimation of uncertainty in calculated values of nutrient spiraling indices is rare. Interpretations based on single values of spiraling indices, may therefore be unwittingly flawed. We investigated the sources of analytical uncertainty in the nutrient concentrations used to calculate two spiraling indices, uptake length (S _w ) and uptake velocity (V _f ), and used Monte Carlo Simulation (MCS) to estimate the resultant uncertainty in index values. We also examined the effect of the level of nutrient enrichment on the magnitude of index uncertainty. Outcomes under high and low nutrient uptake capacity were compared by performing nutrient addition experiments in two streams with contrasting ambient nutrient concentrations. We found that small differences (or uncertainties) in the average plateau nutrient concentration resulted in large uncertainties in spiraling indices. The uncertainty resulted from a combination of small differences in nutrient concentrations between upstream and downstream stations (particularly for the low uptake case), the low nutrient concentration added into the stream, and the sample matrix and storage. The stream with low nutrient uptake capacity had larger relative uncertainties in S _w than when the nutrient uptake capacity was high. The presence of such errors demands that S _w and V _f values should be reported with uncertainty, rather than the normal practice of a single calculated value. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Applying Fuzzy and Probabilistic Uncertainty Concepts to the Material Flow Analysis of Palladium in Austria

Material flow analysis (MFA) is a widely applied tool to investigate resource and recycling systems of metals and minerals. Owing to data limitations and restricted system understanding, MFA results are inherently uncertain. To demonstrate the systematic implementation of uncertainty analysis in MFA, two mathematical concepts for the quantification of uncertainties were applied to Austrian palladium (Pd) resource flows and evaluated: (1) uncertainty ranges expressed by fuzzy sets and (2) uncertainty ranges defined by normal distributions given as mean values and standard deviations. Whereas normal distributions represent the traditional approach for quantifying uncertainties in MFA, fuzzy sets may offer additional benefits in relation to uncertainty quantification in cases of scarce information. With respect to the Pd case study, the fuzzy representation of uncertain quantities is more consistent with the actual data availability in cases of incomplete databases, and fuzzy sets serve to highlight the effect of uncertainty on resource efficiency indicators derived from the MFA results. For both approaches, data reconciliation procedures offer the potential to reduce uncertainty and evaluate the plausibility of the model results. With respect to Pd resource management, improved formal collection of end‐of‐life (EOL) consumer products is identified as a key factor in increasing the recycling efficiency. In particular, the partial export of EOL vehicles represents a substantial loss of Pd from the Austrian resource system, whereas approximately 70% of the Pd in the EOL consumer products is recovered in waste management. In conclusion, systematic uncertainty analysis is an integral part of MFA required to provide robust decision support in resource management.     

Reconstructing the origins of high-alpine niches and cushion life form in the genus Androsace S.L. (Primulaceae)

Relatively, few species have been able to colonize extremely cold alpine environments. We investigate the role played by the cushion life form in the evolution of climatic niches in the plant genus Androsace s.l., which spreads across the mountain ranges of the Northern Hemisphere. Using robust methods that account for phylogenetic uncertainty, intraspecific variability of climatic requirements and different life-history evolution scenarios, we show that climatic niches of Androsace s.l. exhibit low phylogenetic signal and that they evolved relatively recently and punctually. Models of niche evolution fitted onto phylogenies show that the cushion life form has been a key innovation providing the opportunity to occupy extremely cold environments, thus contributing to rapid climatic niche diversification in the genus Androsace s.l. We then propose a plausible scenario for the adaptation of plants to alpine habitats.     

Climate warming and the decline of amphibians and reptiles in Europe

Aim We explore the relationship between current European distributions of amphibian and reptile species and observed climate, and project species potential distributions into the future. Potential impacts of climate warming are assessed by quantifying the magnitude and direction of modelled distributional shifts for every species. In particular we ask, first, what proportion of amphibian and reptile species are projected to lose and gain suitable climate space in the future? Secondly, do species projections vary according to taxonomic, spatial or environmental properties? And thirdly, what climate factors might be driving projections of loss or gain in suitable environments for species? Location Europe. Methods Distributions of species are modelled with four species–climate envelope techniques (artificial neural networks, generalized linear models, generalized additive models, and classification tree analyses) and distributions are projected into the future using five climate‐change scenarios for 2050. Future projections are made considering two extreme assumptions: species have unlimited dispersal ability and species have no dispersal ability. A novel hybrid approach for combining ensembles of forecasts is then used to group linearly covarying projections into clusters with reduced inter‐model variability. Results We show that a great proportion of amphibian and reptile species are projected to expand distributions if dispersal is unlimited. This is because warming in the cooler northern ranges of species creates new opportunities for colonization. If species are unable to disperse, then most species are projected to lose range. Loss of suitable climate space for species is projected to occur mainly in the south‐west of Europe, including the Iberian Peninsula, whilst species in the south‐east are projected to gain suitable climate. This is because dry conditions in the south‐west are projected to increase, approaching the levels found in North Africa, where few amphibian species are able to persist. Main conclusions The impact of increasing temperatures on amphibian and reptile species may be less deleterious than previously postulated; indeed, climate cooling would be more deleterious for the persistence of amphibian and reptile species than warming. The ability of species to cope with climate warming may, however, be offset by projected decreases in the availability of water. This should be particularly true for amphibians. Limited dispersal ability may further increase the vulnerability of amphibians and reptiles to changes in climate.