Predator–prey models: an application for the plankton dynamics of lake Geneva

In this paper we present a hierarchical Bayesian analysis for a predator–prey model applied to ecology considering the use of Markov Chain Monte Carlo methods. We consider the introduction of a random effect in the model and the presence of a covariate vector. An application to ecology is considered using a data set related to the plankton dynamics of lake Geneva for the year 1990. We also discuss some aspects of discrimination of the proposed models.     

Modulation of attention and urgent decisions by affect-laden roadside advertisement in risky driving scenarios

In road safety literature the effects of emotional content and salience of advertising billboards have been scarcely investigated. The main aim of this work was to uncover how affect-laden roadside advertisements can affect attention – eye-movements – and subsequent risky decisions – braking – on the Honda Riding Trainer motorcycle simulator. Results indicated that the number of fixations and total fixation time elicited by the negative and positive emotional advertisements were larger than the neutral ones. At the same time, negative pictures got later gaze disengagement than positive and neutral ones. This attentional capture results in less eye fixation times on the road relevant region, where the important driving events happen. Finally, the negative emotional valence advertisements sped up braking on subsequent risky situations. Overall results demonstrated how advertisements with emotional content modulate attention allocation and driving decisions in risky situations and might be helpful for designing roadside advertisements regulations and risk prevention programs.     

Genomic erosion in a demographically recovered bird species during conservation rescue

The pink pigeon (Nesoenas mayeri) is an endemic species of Mauritius that has made a remarkable recovery after a severe population bottleneck in the 1970s to early 1990s. Prior to this bottleneck, an ex situ population was established from which captive-bred individuals were released into free-living subpopulations to increase population size and genetic variation. This conservation rescue led to rapid population recovery to 400–480 individuals, and the species was twice downlisted on the International Union for the Conservation of Nature (IUCN) Red List. We analyzed the impacts of the bottleneck and genetic rescue on neutral genetic variation during and after population recovery (1993–2008) with restriction site-associated sequencing, microsatellite analyses, and quantitative genetic analysis of studbook data of 1112 birds from zoos in Europe and the United States. We used computer simulations to study the predicted changes in genetic variation and population viability from the past into the future. Genetic variation declined rapidly, despite the population rebound, and the effective population size was approximately an order of magnitude smaller than census size. The species carried a high genetic load of circa 15 lethal equivalents for longevity. Our computer simulations predicted continued inbreeding will likely result in increased expression of deleterious mutations (i.e., a high realized load) and severe inbreeding depression. Without continued conservation actions, it is likely that the pink pigeon will go extinct in the wild within 100 years. Conservation rescue of the pink pigeon has been instrumental in the recovery of the free-living population. However, further genetic rescue with captive-bred birds from zoos is required to recover lost variation, reduce expression of harmful deleterious variation, and prevent extinction. The use of genomics and modeling data can inform IUCN assessments of the viability and extinction risk of species, and it helps in assessments of the conservation dependency of populations.     

Conservation state of two paintings in the Santa Margherita cliff cave: role of the environment and of the microbial community

Environmental Science and Pollution Research - The conservation of ancient paintings sited in humid environments is an actual challenge for restorers, because it needs the knowledge of the...     

Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange

Net ecosystem CO₂ exchange (NEE) is typically measured directly by eddy covariance towers or is estimated by ecosystem process models, yet comparisons between the data obtained by these two methods can show poor correspondence. There are three potential explanations for this discrepancy. First, estimates of NEE as measured by the eddy-covariance technique are laden with uncertainty and can potentially provide a poor baseline for models to be tested against. Second, there could be fundamental problems in model structure that prevent an accurate simulation of NEE. Third, ecosystem process models are dependent on ecophysiological parameter sets derived from field measurements in which a single parameter for a given species can vary considerably. The latter problem suggests that with such broad variation among multiple inputs, any ecosystem modeling scheme must account for the possibility that many combinations of apparently feasible parameter values might not allow the model to emulate the observed NEE dynamics of a terrestrial ecosystem, as well as the possibility that there may be many parameter sets within a particular model structure that can successfully reproduce the observed data. We examined the extent to which these three issues influence estimates of NEE in a widely used ecosystem process model, Biome-BGC, by adapting the generalized likelihood uncertainty estimation (GLUE) methodology. This procedure involved 400,000 model runs, each with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in estimates of NEE that were compared to daily NEE data from young and mature Ponderosa pine stands at Metolius, Oregon. Of the 400,000 simulations run with different parameter sets for each age class (800,000 total), over 99% of the simulations underestimated the magnitude of net ecosystem CO₂ exchange, with only 4.07% and 0.045% of all simulations providing satisfactory simulations of the field data for the young and mature stands, even when uncertainties in eddy-covariance measurements are accounted for. Results indicate fundamental shortcomings in the ability of this model to produce realistic carbon flux data over the course of forest development, and we suspect that much of the mismatch derives from an inability to realistically model ecosystem respiration. However, difficulties in estimating historic climate data are also a cause for model-data mismatch, particularly in a highly ecotonal region such as central Oregon. This latter difficulty may be less prevalent in other ecosystems, but it nonetheless highlights a challenge in trying to develop a dynamic representation of the terrestrial biosphere.     

Correlation analysis between sulphate content and leaching of sulphates in recycled aggregates from construction and demolition wastes

In some recycled aggregates applications, such as component of new concrete or roads, the total content of soluble sulphates should be measured and controlled. Restrictions are usually motivated by the resistance or stability of the new structure, and in most cases, structural concerns can be remedied by the use of techniques such as sulphur-resistant cements. However, environmental risk assessment from recycling and reuse construction products is often forgotten. The purpose of this study is to analyse the content of soluble sulphate on eleven recycled aggregates and six samples prepared in laboratory by the addition of different gypsum percentages. As points of reference, two natural aggregates were tested. An analysis of the content of the leachable amount of heavy metals regulated by European regulation was included. As a result, the correlation between solubility and leachability data allow suggest a limiting gypsum amount of 4.4% on recycled aggregates. This limit satisfies EU Landfill Directive criteria, which is currently used as reference by public Spanish Government for recycled aggregates in construction works.     

Global burned-land estimation in Latin America using MODIS composite data.

This paper presents results of the AQL2004 project, which has been develope within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLatif). The project intended to obtain monthly burned-land maps of the entire region, from Mexico to Patagonia, using MODIS (moderate-resolution imaging spectroradiometer) reflectance data. The project has been organized in three different phases: acquisition and preprocessing of satellite data; discrimination of burned pixels; and validation of results. In the first phase, input data consisting of 32-day composites of MODIS 500-m reflectance data generated by the Global Land Cover Facility (GLCF) of the University of Maryland (College Park, Maryland, U.S.A.) were collected and processed. The discrimination of burned areas was addressed in two steps: searching for "burned core" pixels using postfire spectral indices and multitemporal change detection and mapping of burned scars using contextual techniques. The validation phase was based on visual analysis of Landsat and CBERS (China-Brazil Earth Resources Satellite) images. Validation of the burned-land category showed an agreement ranging from 30% to 60%, depending on the ecosystem and vegetation species present. The total burned area for the entire year was estimated to be 153 215 km2. The most affected countries in relation to their territory were Cuba, Colombia, Bolivia, and Venezuela. Burned areas were found in most land covers; herbaceous vegetation (savannas and grasslands) presented the highest proportions of burned area, while perennial forest had the lowest proportions. The importance of croplands in the total burned area should be taken with reserve, since this cover presented the highest commission errors. The importance of generating systematic products of burned land areas for different ecological processes is emphasized.     

儿童肺功能的多因子及交互影响分析

在儿童肺功能横断面数据基础上,运用多元线性回归,研究了影响儿童肺功能的多因子及其交互效应.结果表明,儿童肺功能指标主要受儿童基本体质情况、呼吸系统疾病和家庭室内暴露因子以及这些因子的交互影响.儿童肺功能与空气颗粒物(PM10-2.5和TSP)的负相关比较显著,未发现与SO₂和NO_x有显著相关性.作者还对空气颗粒物与年均取暖期燃煤取暖、母乳喂养、呼吸系统疾病等因子的交互效应进行了研究,发现细颗粒物对儿童肺功能的影响更为不利.     

空气污染与儿童呼吸系统患病率的相关分析

 在流行病学调查和空气污染物监测的基础上，研究讨论了儿童呼吸系统患病率与空气污染之间的相关关系，结果表明，空气中细颗粒物（PM_2.5）和可吸入颗粒物（PM₁₀）与儿童呼吸系统患病率呈线性正相关关系，其影响比SO₂、Nox更密切．哮喘明显受颗粒物、SO₂、Nox的综合作用的影响．未感冒咳嗽发生率明显受细颗粒物和Nox污染综合作用的影响．