Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

Modelling an expert GIS system based on knowledge to evaluate oil spill environmental sensitivity

Oil spills cause great damage to coastal habitats, especially when rapid and suitable response measures are not taken. Establishing high priority areas is fundamental for the operation of response teams. Under this context and considering the need for keeping all geographical information up-to-date for emergencial use, the present study proposes employing a decision tree coupled with a knowledge-based approach using GIS to assign oil sensitivity indices to Brazilian coastal habitats. The modelled system works based on rules set by the official standards of Brazilian Federal Environment Organ. We tested it on one of the littoral regions of Brazil where transportation of petroleum is most intense: the coast of the municipalities of Sao Sebastiao and Caraguatatuba in the northern littoral of São Paulo state, Brazil. The system automatically ranked the littoral sensitivity index of the study area habitats according to geographical conditions during summer and winter; since index ranks of some habitats varied between these seasons because of sediment alterations. The obtained results illustrate the great potential of the proposed system in generating ESI maps and in aiding response teams during emergency operations. (C) 2009 Elsevier Ltd. All rights reserved.

Mapping oil spill environmental sensitivity in cardoso island state park and surroundings areas, São Paulo, Brazil

This study presents an environmental oil spill sensitivity map of Cardoso Island State Park, located in São Paulo state, Brazil, including some of its surrounding areas. This map was designed following the procedures determined by the Brazilian Federal Environment Organ (Ministry of the Environment), which separates coastal habitats in different littoral sensitivity indexes (LSI) to oil spills. We have also analysed some seasonal variations in morphologic and textural parameters at the local marine beaches that could affect their sensitivity, having found that they are more sensitive during summer due to a wider foreshore zone during these periods. Local most sensitive habitats are estuarine mangroves (LSI 10) and estuarine mud banks (LSI 9). Marine beaches were ranked LSI 3, and littoral rocky shores were subdivided in exposed flat rocky shores (LSI 1), boulder rocky shores (LSI 6) and sheltered rocky shores (LSI 8). Due to the elevated sensitivity of an estuarine system in the area, we considered necessary the installation of an Environmental Emergency Centre and the design of an emergency plan for the region in case of an accident resulting in oil spills within its vicinities. (C) 2007 Elsevier Ltd. All rights reserved.

Environmental sensitivity index (ESI) mapping of oil spill in the amazon coastal zone: the PIATAM Mar project

A importância do monitoramento ambiental é medida pelos vários casos de derramamentos de óleo ocorridos no mundo durante as últimas três décadas. Isto tem incentivado as empresas e órgãos do governo envolvidos na prevenção e combate a estes acidentes a aperfeiçoarem cada vez mais os métodos, tanto preventivos como corretivos, para a minimização dos danos gerados por acidentes com derramamento de óleo. Este trabalho objetiva contextualizar de forma histórica como os acidentes com derramamento de óleo propiciaram o desenvolvimento de pesquisa tecnológica a partir de parcerias entre empresas de petróleo, agências de governo, universidades e institutos de pesquisa no Brasil, em especial na zona costeira Amazônica. Como resultado, índices de sensibilidade ambiental ao derramamento de óleo (ISA) foram definidos especialmente para a Amazônia costeira, onde processos fluviais e marinhos se encontram na foz do maior rio do mundo, o rio Amazonas. Perspectivas de pesquisa e respostas de emergência a acidentes são apresentadas, a fim de se conservar a diversidade socioambiental da mais importante região tropical do planeta.

Reaction norm model to describe environmental sensitivity across first lactation in dairy cattle under tropical conditions

Reaction norm models have been widely used to study genotype by environment interaction (G × E) in animal breeding. The objective of this study was to describe environmental sensitivity across first lactation in Brazilian Holstein cows using a reaction norm approach. A total of 50,168 individual monthly test day (TD) milk yields (10 test days) from 7476 complete first lactations of Holstein cattle were analyzed. The statistical models for all traits (10 TDs and for 305-day milk yield) included the fixed effects of contemporary group, age of cow (linear and quadratic effects), and days in milk (linear effect), except for 305-day milk yield. A hierarchical reaction norm model (HRNM) based on the unknown covariate was used. The present study showed the presence of G × E in milk yield across first lactation of Holstein cows. The variation in the heritability estimates implies differences in the response to selection depending on the environment where the animals of this population are evaluated. In the average environment, the heritabilities for all traits were rather similar, in range from 0.02 to 0.63. The scaling effect of G × E predominated throughout most of lactation. Particularly during the first 2 months of lactation, G × E caused reranking of breeding values. It is therefore important to include the environmental sensitivity of animals according to the phase of lactation in the genetic evaluations of Holstein cattle in tropical environments.

Natural Conditions and Environmental Impacts in a Coastal Hydrographic Basin in the Brazilian Amazon

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Environmental fragility evaluation and guidelines for environmental zoning: a study case on Ibiuna (the Southeastern Brazilian region)

Environmental fragility models are important decision tools for policy makers as they help quantify environmental sensitivity and understand the relationship between human activities and environmental quality. The objective of this study was to evaluate three different environmental fragility models within the Brazilian rainforest region and to use the results to develop environmental zone classes. Two rural river basins located in Ibiuna, Sao Paulo state, Brazil, were studied. Input variables, including slope class, relief dissection rate, soil class, lithology, land cover, and climate data, were used to compute environmental fragility classes using three standard models. The model outputs were evaluated on their ability to accurately predict the most sensitive and least sensitive areas. The best models for each region were used to derive environmental zoning maps, including restoration priorities, best regions for agriculture, and areas with high needs for soil management. These maps will help support land use strategies for environmental restoration. This study provides insight into territorial ordering and management of environmental services with a regional perspective.

Evaluating responses to land degradation mitigation measures in Southern Italy

The main factors affecting environmental sensitivity to degradation are soil, vegetation, climate and management, through either their intrinsic characteristics or by their interaction on the landscape. Different levels of degradation risks may be observed in response to particular combinations of the aforementioned factors. For instance, the combination of inappropriate management practices and intrinsically weak soil conditions will result in a severe degradation of the environment, while the combination of the same type of management with better soil conditions may lead to negligible degradation.The aim of this study was to identify factors and their impact on land degradation processes in three areas of the Basilicata region (southern Italy) using a procedure that couples environmental indices, GIS and crop-soil simulation models. Areas prone to desertification were first identified using the Environmental Sensitive Areas (ESA) procedure. An analysis for identifying the weight that each of the contributing factor (climate, soil, vegetation, management) had on the ESA was carried out using GIS techniques. The SALUS model was successfully executed to identify the management practices that could lead to better soil conditions to enhance land use sustainability. The best management practices were found to be those that minimized soil disturbance and increased soil organic carbon. Two alternative scenarios with improved soil quality and subsequently improving soil water holding capacity were used as mitigation measures. The ESA were recalculated and the effects of the mitigation measures suggested by the model were assessed. The new ESA showed a significant reduction on land degradation.

Detection and impacts of leakage from sub-seafloor deep geological carbon dioxide storage

Fossil fuel power generation and other industrial emissions of carbon dioxide are a threat to global climate1, yet many economies will remain reliant on these technologies for several decades2. Carbon dioxide capture and storage (CCS) in deep geological formations provides an effective option to remove these emissions from the climate system3. In many regions storage reservoirs are located offshore4, 5, over a kilometre or more below societally important shelf seas6. Therefore, concerns about the possibility of leakage7, 8 and potential environmental impacts, along with economics, have contributed to delaying development of operational CCS. Here we investigate the detectability and environmental impact of leakage from a controlled sub-seabed release of CO2. We show that the biological impact and footprint of this small leak analogue (<1 tonne CO2 d−1) is confined to a few tens of metres. Migration of CO2 through the shallow seabed is influenced by near-surface sediment structure, and by dissolution and re-precipitation of calcium carbonate naturally present in sediments. Results reported here advance the understanding of environmental sensitivity to leakage and identify appropriate monitoring strategies for full-scale carbon storage operations.

Detection and impacts of leakage from sub-seafloor deep geological carbon dioxide storage

Fossil fuel power generation and other industrial emissions of carbon dioxide are a threat to global climate1, yet many economies will remain reliant on these technologies for several decades2. Carbon dioxide capture and storage (CCS) in deep geological formations provides an effective option to remove these emissions from the climate system3. In many regions storage reservoirs are located offshore4, 5, over a kilometre or more below societally important shelf seas6. Therefore, concerns about the possibility of leakage7, 8 and potential environmental impacts, along with economics, have contributed to delaying development of operational CCS. Here we investigate the detectability and environmental impact of leakage from a controlled sub-seabed release of CO2. We show that the biological impact and footprint of this small leak analogue (<1 tonne CO2 d−1) is confined to a few tens of metres. Migration of CO2 through the shallow seabed is influenced by near-surface sediment structure, and by dissolution and re-precipitation of calcium carbonate naturally present in sediments. Results reported here advance the understanding of environmental sensitivity to leakage and identify appropriate monitoring strategies for full-scale carbon storage operations.

Vers le haut : la valeur d’usage du toit vert privé : le point de vue de professionnels de l’immobilier œuvrant sur le Plateau Mont-Royal

Cette recherche s’intéresse à la valeur d’usage du toit vert dans l’arrondissement du Plateau Mont-Royal, de la Ville de Montréal. Spécifiquement, elle s’intéresse à l’état problématique qu’est l’étalement urbain en tentant l’estimation de la valeur d’usage du toit vert, de la cour arrière et du balcon-terrasse soutenue par le dispositif argumentaire immobilier propre à chacun des aménagements. L’étalement urbain est la source de graves problèmes et la résorption de ses effets néfastes est devenue une priorité dans l’aménagement du territoire. L’une des principales raisons sousjacentes à l’exode urbain est la valeur d’usage accordée à la parcelle extérieure qu’offre l’habitat unifamilial pavillonnaire. Dans cette situation, la question est de savoir si l’insertion d’espaces verts privés en milieu urbain peut participer à la résorption de l’exode urbain. Or, dans l’agglomération, le sol manque. Le toit vert privé apparaît comme une alternative astucieuse, bien que limitée, au terrain entourant la maison. Reste à savoir si les gens le valorisent tel un espace vert privé d’extrême proximité, à même le sol. À la lueur de l’analyse, il advient que le toit vert ne présente pas de valeur d’usage comparable à celle de la cour arrière dans le contexte observé, précisément parce que leurs publics cibles s’opposent d’emblée. En revanche, le balcon-terrasse et le toit vert semblent être, en fonction des données construites, des aménagements à valeur d’usage comparable.

A genome-wide test of the differential susceptibility hypothesis reveals a genetic predictor of differential response to psychological treatments for child anxiety disorders

Background: The differential susceptibly hypothesis suggests that certain genetic variants moderate the effects of both negative and positive environments on mental health and may therefore be important predictors of response to psychological treatments. Nevertheless, the identification of such variants has so far been limited to preselected candidate genes. In this study we extended the differential susceptibility hypothesis from a candidate gene to a genome-wide approach to test whether a polygenic score of environmental sensitivity predicted response to Cognitive Behavioural Therapy (CBT) in children with anxiety disorders. Methods: We identified variants associated with environmental sensitivity using a novel method in which within-pair variability in emotional problems in 1026 monozygotic (MZ) twin pairs was examined as a function of the pairs’ genotype. We created a polygenic score of environmental sensitivity based on the whole-genome findings and tested the score as a moderator of parenting on emotional problems in 1,406 children and response to individual, group and brief parent-led CBT in 973 children with anxiety disorders. Results: The polygenic score significantly moderated the effects of parenting on emotional problems and the effects of treatment. Individuals with a high score responded significantly better to individual CBT than group CBT or brief parent-led CBT (remission rates: 70.9%, 55.5% and 41.6% respectively). Conclusions: Pending successful replication, our results should be considered exploratory. Nevertheless, if replicated, they suggest that individuals with the greatest environmental sensitivity may be more likely to develop emotional problems in adverse environments, but also benefit more from the most intensive types of treatment.

Metodologia de utilização de dados de sensoriamento remoto em zonas costeiras sob influência da indústria petrolífera

Oil spills in marine environments represent immediate environmental impacts of large magnitude. For that reason the Environmental Sensitivity to Oil Maps constitute a major instrument for planning actions of containment and cleanup. For both the Environmental Sensitivity Maps always need to be updated, to have an appropriate scale and to represent accurately the coastal areas. In this context, this thesis presents a methodology for collecting and processing remote sensing data for the purpose of updating the territorial basis of thematic maps of Environmental Sensitivity to Oil. To ensure greater applicability of the methodology, sensors with complementary characteristics, which provide their data at a low financial cost, were selected and tested. To test the methodology, an area located on the northern coast of the Northeast of Brazil was chosen. The results showed that the products of ASTER data and image hybrid sensor PALSAR + CCD and HRC + CCD, have a great potential to be used as a source of cartographic information on projects that seek to update the Environmental Sensitivity Maps of Oil