Plasticity in probabilistic reaction norms for maturation in a salmonid fish

The relationship between body size and the probability of maturing, often referred to as the probabilistic maturation reaction norm (PMRN), has been increasingly used to infer genetic variation in maturation schedule. Despite this trend, few studies have directly evaluated plasticity in the PMRN. A transplant experiment using white-spotted charr demonstrated that the PMRN for precocious males exhibited plasticity. A smaller threshold size at maturity occurred in charr inhabiting narrow streams where more refuges are probably available for small charr, which in turn might enhance the reproductive success of sneaker precocious males. Our findings suggested that plastic effects should clearly be included in investigations of variation in PMRNs.     

Risk of symptomatic dengue for foreign visitors to the 2014 FIFA World Cup in Brazil

Brazil will host the FIFA World Cup™, the biggest single-event competition in the world, from June 12-July 13 2014 in 12 cities. This event will draw an estimated 600,000 international visitors. Brazil is endemic for dengue. Hence, attendees of the 2014 event are theoretically at risk for dengue. We calculated the risk of dengue acquisition to non-immune international travellers to Brazil, depending on the football match schedules, considering locations and dates of such matches for June and July 2014. We estimated the average per-capita risk and expected number of dengue cases for each host-city and each game schedule chosen based on reported dengue cases to the Brazilian Ministry of Health for the period between 2010-2013. On the average, the expected number of cases among the 600,000 foreigner tourists during the World Cup is 33, varying from 3-59. Such risk estimates will not only benefit individual travellers for adequate pre-travel preparations, but also provide valuable information for public health professionals and policy makers worldwide. Furthermore, estimates of dengue cases in international travellers during the World Cup can help to anticipate the theoretical risk for exportation of dengue into currently non-infected areas.     

Exposure to Dishwashing Liquid Assessed in University Students from Brest City: A Preliminary Study—A First Approach to Household Products Exposure in France

In recent years, more attention has been paid to exposure of the general population to household products. In order to assess exposure, it is necessary to generate exposure data. For this reason, a preliminary study of dishwashing liquid contact on Brest university students was performed. Dishwashing liquid is frequently used and when it is improperly mixed it can liberate harmful molecules. As for university students, they may have a repetitive contact with dishwashing liquid during their academic studies. Relevant parameters as frequency of dishwashing, duration, and amount of dishwashing liquid were assessed from questionnaires and laboratory tests. Tests revealed that overall no difference between the sexes and the type of residential household on dishwashing was present on this population. Amount of washed items and duration was significantly correlated, which could seem logical but remarkable considering the lack of correlation between other parameters. Values of 1.39 and 58.8 μg/kg bw/day for the 95th percentile of dermal and inhalation probabilistic exposure were found, respectively. Dermal exposure coincides with deterministic published data. In the case of inhalation exposure no published data are available. Higher inhalation exposure value may show that dermal exposure is diminished by high dilution of dishwashing liquid in water.     

Towards a more transparent use of the potential natural vegetation concept – an answer to Chiarucci et al.

In this paper, the concerns of Chiarucci et al. ( 2010 ) regarding use of the potential natural vegetation (PNV) concept are addressed, as voiced in the forum section of the Journal of Vegetation Science. First, we rectify some unfounded expectations concerning PNV, including a relationship with prehuman vegetation and phytosociology. Second, we point out issues that pose considerable challenges in PNV and require common agreement. Here, we address the issue of time and disturbance. We propose to use the static PNV concept as a baseline, a null model for landscape assessment and in comparisons. Instead of changing the PNV concept itself, we introduce a new term, potential future natural vegetation (PFV) to cover estimations of potential successional outcomes. Finally, we offer a new view of PNV with which we intend to make the use of PNV estimates more transparent. We formalize the PNV theory into a partial cause‐effect model of vegetation that clearly states which effects on vegetation are factored out during its estimation. Further, we also propose to assess PNV in a probabilistic setting, rather than providing a single estimate for one location. This multiple PNV would reflect our uncertainty about the vegetation entity that could persist at the locality concerned. Such uncertainty arises from the overlap of environmental preferences of different mature vegetation types. Thus reformulated, we argue that the PNV concept has much to offer as a null model, especially in landscape ecology and in site comparisons in space and time.     

Evaluation of Sampling-Based Methods for Sensitivity Analysis: Case Study for the E. coli Food Safety Process Risk Model

This article evaluates selected sensitivity analysis methods applicable to risk assessment models with two-dimensional probabilistic frameworks, using a microbial food safety process risk model as a test-bed. Six sampling-based sensitivity analysis methods were evaluated including Pearson and Spearman correlation, sample and rank linear regression, and sample and rank stepwise regression. In a two-dimensional risk model, the identification of key controllable inputs that can be priorities for risk management can be confounded by uncertainty. However, despite uncertainty, results show that key inputs can be distinguished from those that are unimportant, and inputs can be grouped into categories of similar levels of importance. All selected methods are capable of identifying unimportant inputs, which is helpful in that efforts to collect data to improve the assessment or to focus risk management strategies can be prioritized elsewhere. Rank-based methods provided more robust insights with respect to the key sources of variability in that they produced narrower ranges of uncertainty for sensitivity results and more clear distinctions when comparing the importance of inputs or groups of inputs. Regression-based methods have advantages over correlation approaches because they can be configured to provide insight regarding interactions and nonlinearities in the model.     

A model of drop size distribution for a system with evaporation

Abstract. The size and shape of drops on leaf surfaces strongly affect their persistence. The relationship between volume and exposed surface area of drops on wheat leaves and the log-normal drop size distribution in a wheat canopy after rain are used to derive equations to describe how the total volume and drop number change with evaporation. Firstly, the behaviour of a single drop as it evaporates is considered and then equations describing the change in a population of drops with an initial log-normal distribution are derived. The time taken for all the drops to reach complete dryness is about thirty times that for the same volume of water spread uniformly over the surface with the same potential evaporation rate.     

Probabilistic measures of climate change vulnerability,adaptation action benefits,and related uncertainty from maximum temperature metric selection

Predictions of the projected changes in species distributions and potential adaptation action benefits can help guide conservation actions. There is substantial uncertainty in projecting species distributions into an unknown future, however, which can undermine confidence in predictions or misdirect conservation actions if not properly considered. Recent studies have shown that the selection of alternative climate metrics describing very different climatic aspects (e.g., mean air temperature vs. mean precipitation) can be a substantial source of projection uncertainty. It is unclear, however, how much projection uncertainty might stem from selecting among highly correlated, ecologically similar climate metrics (e.g., maximum temperature in July, maximum 30‐day temperature) describing the same climatic aspect (e.g., maximum temperatures) known to limit a species’ distribution. It is also unclear how projection uncertainty might propagate into predictions of the potential benefits of adaptation actions that might lessen climate change effects. We provide probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty stemming from the selection of four maximum temperature metrics for brook trout (Salvelinus fontinalis), a cold‐water salmonid of conservation concern in the eastern United States. Projected losses in suitable stream length varied by as much as 20% among alternative maximum temperature metrics for mid‐century climate projections, which was similar to variation among three climate models. Similarly, the regional average predicted increase in brook trout occurrence probability under an adaptation action scenario of full riparian forest restoration varied by as much as .2 among metrics. Our use of Bayesian inference provides probabilistic measures of vulnerability and adaptation action benefits for individual stream reaches that properly address statistical uncertainty and can help guide conservation actions. Our study demonstrates that even relatively small differences in the definitions of climate metrics can result in very different projections and reveal high uncertainty in predicted climate change effects.     

Range‐constrained co‐occurrence simulation reveals little niche partitioning among rock‐dwelling Montenegrina land snails (Gastropoda: Clausiliidae)

Aim

Taxon co‐occurrence analysis is commonly used in ecology, but it has not been applied to range‐wide distribution data of partly allopatric taxa because existing methods cannot differentiate between distribution‐related effects and taxon interactions. Our first aim was to develop a taxon co‐occurrence analysis method that is also capable of taking into account the effect of species ranges and can handle faunistic records from museum databases or biodiversity inventories. Our second aim was to test the independence of taxon co‐occurrences of rock‐dwelling gastropods at different taxonomic levels, with a special focus on the Clausiliidae subfamily Alopiinae, and in particular the genus Montenegrina.

Location

Balkan Peninsula in south‐eastern Europe (46N–36N, 13.5E–28E).

Methods

We introduced a taxon‐specific metric that characterizes the occurrence probability at a given location. This probability was calculated as a distance‐weighted mean of the taxon's presence and absence records at all sites. We applied corrections to account for the biases introduced by varying sampling intensity in our dataset. Then we used probabilistic null‐models to simulate taxon distributions under the null hypothesis of no taxon interactions and calculated pairwise and cumulated co‐occurrences. Independence of taxon occurrences was tested by comparing observed co‐occurrences to simulated values.

Results

We observed significantly fewer co‐occurrences among species and intra‐generic lineages of Montenegrina than expected under the assumption of no taxon interaction.

Main conclusions

Fewer than expected co‐occurrences among species and intra‐generic clades indicate that species divergence preceded niche partitioning. This suggests a primary role of non‐adaptive processes in the speciation of rock‐dwelling gastropods. The method can account for the effects of distributional constraints in range‐wide datasets, making it suitable for testing ecological, biogeographical, or evolutionary hypotheses where interactions of partly allopatric taxa are in question.     

Detecting outliers in species distribution data: Some caveats and clarifications on a virtual species study

Liu et al. (2018) used a virtual species approach to test the effects of outliers on species distribution models. In their simulations, they applied a threshold value over the simulated suitabilities to generate the species distributions, suggesting that using a probabilistic simulation approach would have been more complex and yield the same results. Here, we argue that using a probabilistic approach is not necessarily more complex and may significantly change results. Although the threshold approach may be justified under limited circumstances, the probabilistic approach has multiple advantages. First, it is in line with ecological theory, which largely assumes non‐threshold responses. Second, it is more general, as it includes the threshold as a limiting case. Third, it allows a better separation of the relevant intervening factors that influence model performance. Therefore, we argue that the probabilistic simulation approach should be used as a general standard in virtual species studies.