Multi-level Policy Coalitions An Interpretative Model Of Water Conflicts ιn The Americas

This article proposes an analytical approach to conflicts and policy-making related to urban water management based on multi-level policy coalitions. This is necessary to articulate four main issues. First, the repositioning of social and political struggles for access to water, along with policy variables. Second, the analysis of the effects of ecological transition, including climate change. Third, the reincorporation of these struggles and challenges in a multi-level approach. Finally, the enquiry into the apparent contradiction, in contemporary policymaking. The article proposes a definition of multi-level coalitions as collective preference systems that influence the content of policies (ideas/advocacy, decisions, policy tools) and their implementation, groups of actors that arise from engagement in policy issues. In the first section, the article presents the objectives of research on urban water management in the Americas, within the framework of which this analytical approach by multi-level coalitions is fashioned. In the second section, the article details four analytical issues. In the third section, it gives a definition of multi-level coalitions.19415317

A Land Cover Map of Africa. Carte de l'Occupation du Sol de l'Afrique.

Abstract not availableJRC.H-Institute for environment and sustainability (Ispra

Performance of the ROX index to predict intubation in immunocompromised patients receiving high-flow nasal cannula for acute respiratory failure

Background Delayed intubation is associated with high mortality. There is a lack of objective criteria to decide the time of intubation. We assessed a recently described combined oxygenation index (ROX index) to predict intubation in immunocompromised patients. The study is a secondary analysis of randomized trials in immunocompromised patients, including all patients who received high-flow nasal cannula (HFNC). The first objective was to evaluate the accuracy of the ROX index to predict intubation for patients with acute respiratory failure. Results In the study, 302 patients received HFNC. Acute respiratory failure was mostly related to pneumonia (n = 150, 49.7%). Within 2 (1-3) days, 115 (38.1%) patients were intubated. The ICU mortality rate was 27.4% (n = 83). At 6 h, the ROX index was lower for patients who needed intubation compared with those who did not [4.79 (3.69-7.01) vs. 6.10 (4.48-8.68), p < 0.001]. The accuracy of the ROX index to predict intubation was poor [AUC = 0.623 (0.557-0.689)], with low performance using the threshold previously found (4.88). In multivariate analysis, a higher ROX index was still independently associated with a lower intubation rate (OR = 0.89 [0.82-0.96], p = 0.04). Conclusion A ROX index greater than 4.88 appears to have a poor ability to predict intubation in immunocompromised patients with acute respiratory failure, although it remains highly associated with the risk of intubation and may be useful to stratify such risk in future studies

Ecological and genetic relationships of the Forest-M form among chromosomal and molecular forms of the malaria vector Anopheles gambiae sensu stricto

<p>Abstract</p> <p>Background</p> <p><it>Anopheles gambiae sensu stricto</it>, one of the principal vectors of malaria, has been divided into two subspecific groups, known as the M and S molecular forms. Recent studies suggest that the M form found in Cameroon is genetically distinct from the M form found in Mali and elsewhere in West Africa, suggesting further subdivision within that form.</p> <p>Methods</p> <p>Chromosomal, microsatellite and geographic/ecological evidence are synthesized to identify sources of genetic polymorphism among chromosomal and molecular forms of the malaria vector <it>Anopheles gambiae s.s</it>.</p> <p>Results</p> <p>Cytogenetically the Forest M form is characterized as carrying the standard chromosome arrangement for six major chromosomal inversions, namely 2La, 2Rj, 2Rb, 2Rc, 2Rd, and 2Ru. Bayesian clustering analysis based on molecular form and chromosome inversion polymorphisms as well as microsatellites describe the Forest M form as a distinct population relative to the West African M form (Mopti-M form) and the S form. The Forest-M form was the most highly diverged of the <it>An. gambiae s.s</it>. groups based on microsatellite markers. The prevalence of the Forest M form was highly correlated with precipitation, suggesting that this form prefers much wetter environments than the Mopti-M form.</p> <p>Conclusion</p> <p>Chromosome inversions, microsatellite allele frequencies and habitat preference all indicate that the Forest M form of <it>An. gambiae </it>is genetically distinct from the other recognized forms within the taxon <it>Anopheles gambiae sensu stricto</it>. Since this study covers limited regions of Cameroon, the possibility of gene flow between the Forest-M form and Mopti-M form cannot be rejected. However, association studies of important phenotypes, such as insecticide resistance and refractoriness against malaria parasites, should take into consideration this complex population structure.</p

Subcellular localization and tissue specific expression of amidase 1 from Arabidopsis thaliana

Amidase 1 (AMI1) from Arabidopsis thaliana converts indole-3-acetamide (IAM), into indole-3-acetic acid (IAA). AMI1 is part of a small isogene family comprising seven members in A. thaliana encoding proteins which share a conserved glycine- and serine-rich amidase-signature. One member of this family has been characterized as an N-acylethanolamine-cleaving fatty acid amidohydrolase (FAAH) and two other members are part of the preprotein translocon of the outer envelope of chloroplasts (Toc complex) or mitochondria (Tom complex) and presumably lack enzymatic activity. Among the hitherto characterized proteins of this family, AMI1 is the only member with indole-3-acetamide hydrolase activity, and IAM is the preferred substrate while N-acylethanolamines and oleamide are not hydrolyzed significantly, thus suggesting a role of AMI1 in auxin biosynthesis. Whereas the enzymatic function of AMI1 has been determined in vitro, the subcellular localization of the enzyme remained unclear. By using different GFP-fusion constructs and an A. thaliana transient expression system, we show a cytoplasmic localization of AMI1. In addition, RT-PCR and anti-amidase antisera were used to examine tissue specific expression of AMI1 at the transcriptional and translational level, respectively. AMI1-expression is strongest in places of highest IAA content in the plant. Thus, it is concluded that AMI1 may be involved in de novo IAA synthesis in A. thaliana

Mapping and monitoring carbon stocks with satellite observations: a comparison of methods

Mapping and monitoring carbon stocks in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions, and are now included in climate change negotiations. We review the potential for satellites to measure carbon stocks, specifically aboveground biomass (AGB), and provide an overview of a range of approaches that have been developed and used to map AGB across a diverse set of conditions and geographic areas. We provide a summary of types of remote sensing measurements relevant to mapping AGB, and assess the relative merits and limitations of each. We then provide an overview of traditional techniques of mapping AGB based on ascribing field measurements to vegetation or land cover type classes, and describe the merits and limitations of those relative to recent data mining algorithms used in the context of an approach based on direct utilization of remote sensing measurements, whether optical or lidar reflectance, or radar backscatter. We conclude that while satellite remote sensing has often been discounted as inadequate for the task, attempts to map AGB without satellite imagery are insufficient. Moreover, the direct remote sensing approach provided more coherent maps of AGB relative to traditional approaches. We demonstrate this with a case study focused on continental Africa and discuss the work in the context of reducing uncertainty for carbon monitoring and markets

Mapping biomass with remote sensing: a comparison of methods for the case study of Uganda

<p>Abstract</p> <p>Background</p> <p>Assessing biomass is gaining increasing interest mainly for bioenergy, climate change research and mitigation activities, such as reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+). In response to these needs, a number of biomass/carbon maps have been recently produced using different approaches but the lack of comparable reference data limits their proper validation. The objectives of this study are to compare the available maps for Uganda and to understand the sources of variability in the estimation. Uganda was chosen as a case-study because it presents a reliable national biomass reference dataset.</p> <p>Results</p> <p>The comparison of the biomass/carbon maps show strong disagreement between the products, with estimates of total aboveground biomass of Uganda ranging from 343 to 2201 Tg and different spatial distribution patterns. Compared to the reference map based on country-specific field data and a national Land Cover (LC) dataset (estimating 468 Tg), maps based on biome-average biomass values, such as the Intergovernmental Panel on Climate Change (IPCC) default values, and global LC datasets tend to strongly overestimate biomass availability of Uganda (ranging from 578 to 2201 Tg), while maps based on satellite data and regression models provide conservative estimates (ranging from 343 to 443 Tg). The comparison of the maps predictions with field data, upscaled to map resolution using LC data, is in accordance with the above findings. This study also demonstrates that the biomass estimates are primarily driven by the biomass reference data while the type of spatial maps used for their stratification has a smaller, but not negligible, impact. The differences in format, resolution and biomass definition used by the maps, as well as the fact that some datasets are not independent from the reference data to which they are compared, are considered in the interpretation of the results.</p> <p>Conclusions</p> <p>The strong disagreement between existing products and the large impact of biomass reference data on the estimates indicate that the first, critical step to improve the accuracy of the biomass maps consists of the collection of accurate biomass field data for all relevant vegetation types. However, detailed and accurate spatial datasets are crucial to obtain accurate estimates at specific locations.</p