156 research outputs found

    Can global precipitation datasets benefit the estimation of the area to be cropped in irrigated agriculture?

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    The area to be cropped in irrigation districts needs to be planned according to the available water resources to avoid agricultural production loss. However, the period of record of local hydro-meteorological data may be short, leading to an incomplete understanding of climate variability and consequent uncertainty in estimating surface water availability for irrigation area planning. In this study we assess the benefit of using global precipitation datasets to improve surface water availability estimates. A reference area that can be irrigated is established using a complete record of 30 years of observed river discharge data. Areas are then determined using simulated river discharges from six local hydrological models forced with in situ and global precipitation datasets (CHIRPS and MSWEP), each calibrated independently with a sample of 5 years extracted from the full 30-year record. The utility of establishing the irrigated area based on simulated river discharge simulations is compared against the reference area through a pooled relative utility value (PRUV). Results show that for all river discharge simulations the benefit of choosing the irrigated area based on the 30 years of simulated data is higher compared to using only 5 years of observed discharge data, as the statistical spread of PRUV using 30 years is smaller. Hence, it is more beneficial to calibrate a hydrological model using 5 years of observed river discharge and then to extend it with global precipitation data of 30 years as this weighs up against the model uncertainty of the model calibration.</p

    Linear regression for numeric symbolic variables: an ordinary least squares approach based on Wasserstein Distance

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    In this paper we present a linear regression model for modal symbolic data. The observed variables are histogram variables according to the definition given in the framework of Symbolic Data Analysis and the parameters of the model are estimated using the classic Least Squares method. An appropriate metric is introduced in order to measure the error between the observed and the predicted distributions. In particular, the Wasserstein distance is proposed. Some properties of such metric are exploited to predict the response variable as direct linear combination of other independent histogram variables. Measures of goodness of fit are discussed. An application on real data corroborates the proposed method

    Multiplex quantitative PCR for single-reaction genetically modified (GM) plant detection and identification of false-positive GM plants linked to Cauliflower mosaic virus (CaMV) infection.

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    BACKGROUND:Most genetically modified (GM) plants contain a promoter, P35S, from the plant virus, Cauliflower mosaic virus (CaMV), and many have a terminator, TNOS, derived from the bacterium, Agrobacterium tumefaciens. Assays designed to detect GM plants often target the P35S and/or TNOS DNA sequences. However, because the P35S promoter is derived from CaMV, these detection assays can yield false-positives from non-GM plants infected by this naturally-occurring virus. RESULTS:Here we report the development of an assay designed to distinguish CaMV-infected plants from GM plants in a single multiplexed quantitative PCR (qPCR) reaction. Following initial testing and optimization via PCR and singleplex-to-multiplex qPCR on both plasmid and plant DNA, TaqMan qPCR probes with different fluorescence wavelengths were designed to target actin (a positive-control plant gene), P35S, P3 (a CaMV-specific gene), and TNOS. We tested the specificity of our quadruplex qPCR assay using different DNA extracts from organic watercress and both organic and GM canola, all with and without CaMV infection, and by using commercial and industrial samples. The limit of detection (LOD) of each target was determined to be 1% for actin, 0.001% for P35S, and 0.01% for both P3 and TNOS. CONCLUSIONS:This assay was able to distinguish CaMV-infected plants from GM plants in a single multiplexed qPCR reaction for all samples tested in this study, suggesting that this protocol is broadly applicable and readily transferrable to any interested parties with a qPCR platform

    Managing uncertainty: a review of food system scenario analysis and modelling

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    Complex socio-ecological systems like the food system are unpredictable, especially to long-term horizons such as 2050. In order to manage this uncertainty, scenario analysis has been used in conjunction with food system models to explore plausible future outcomes. Food system scenarios use a diversity of scenario types and modelling approaches determined by the purpose of the exercise and by technical, methodological and epistemological constraints. Our case studies do not suggest Malthusian futures for a projected global population of 9 billion in 2050; but international trade will be a crucial determinant of outcomes; and the concept of sustainability across the dimensions of the food system has been inadequately explored so far. The impact of scenario analysis at a global scale could be strengthened with participatory processes involving key actors at other geographical scales. Food system models are valuable in managing existing knowledge on system behaviour and ensuring the credibility of qualitative stories but they are limited by current datasets for global crop production and trade, land use and hydrology. Climate change is likely to challenge the adaptive capacity of agricultural production and there are important knowledge gaps for modelling research to address

    Exceptional Diversity, Maintenance of Polymorphism, and Recent Directional Selection on the APL1 Malaria Resistance Genes of Anopheles gambiae

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    The three-gene APL1 locus encodes essential components of the mosquito immune defense against malaria parasites. APL1 was originally identified because it lies within a mapped QTL conferring the vector mosquito Anopheles gambiae natural resistance to the human malaria parasite, Plasmodium falciparum, and APL1 genes have subsequently been shown to be involved in defense against several species of Plasmodium. Here, we examine molecular population genetic variation at the APL1 gene cluster in spatially and temporally diverse West African collections of A. gambiae. The locus is extremely polymorphic, showing evidence of adaptive evolutionary maintenance of genetic variation. We hypothesize that this variability aids in defense against genetically diverse pathogens, including Plasmodium. Variation at APL1 is highly structured across geographic and temporal subpopulations. In particular, diversity is exceptionally high during the rainy season, when malaria transmission rates are at their peak. Much less allelic diversity is observed during the dry season when mosquito population sizes and malaria transmission rates are low. APL1 diversity is weakly stratified by the polymorphic 2La chromosomal inversion but is very strongly subdivided between the M and S “molecular forms.” We find evidence that a recent selective sweep has occurred at the APL1 locus in M form mosquitoes only. The independently reported observation of a similar M-form restricted sweep at the Tep1 locus, whose product physically interacts with APL1C, suggests that epistatic selection may act on these two loci causing them to sweep coordinately

    Anopheles Imd Pathway Factors and Effectors in Infection Intensity-Dependent Anti-Plasmodium Action

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    The Anopheles gambiae immune response against Plasmodium falciparum, an etiological agent of human malaria, has been identified as a source of potential anti-Plasmodium genes and mechanisms to be exploited in efforts to control the malaria transmission cycle. One such mechanism is the Imd pathway, a conserved immune signaling pathway that has potent anti-P. falciparum activity. Silencing the expression of caspar, a negative regulator of the Imd pathway, or over-expressing rel2, an Imd pathway-controlled NFkappaB transcription factor, confers a resistant phenotype on A. gambiae mosquitoes that involves an array of immune effector genes. However, unexplored features of this powerful mechanism that may be essential for the implementation of a malaria control strategy still remain. Using RNA interference to singly or dually silence caspar and other components of the Imd pathway, we have identified genes participating in the anti-Plasmodium signaling module regulated by Caspar, each of which represents a potential target to achieve over-activation of the pathway. We also determined that the Imd pathway is most potent against the parasite's ookinete stage, yet also has reasonable activity against early oocysts and lesser activity against late oocysts. We further demonstrated that caspar silencing alone is sufficient to induce a robust anti-P. falciparum response even in the relative absence of resident gut microbiota. Finally, we established the relevance of the Imd pathway components and regulated effectors TEP1, APL1, and LRIM1 in parasite infection intensity-dependent defense, thereby shedding light on the relevance of laboratory versus natural infection intensity models. Our results highlight the physiological considerations that are integral to a thoughtful implementation of Imd pathway manipulation in A. gambiae as part of an effort to limit the malaria transmission cycle, and they reveal a variety of previously unrecognized nuances in the Imd-directed immune response against P. falciparum

    How Close Do We Live to Water? A Global Analysis of Population Distance to Freshwater Bodies

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    Traditionally, people have inhabited places with ready access to fresh water. Today, over 50% of the global population lives in urban areas, and water can be directed via tens of kilometres of pipelines. Still, however, a large part of the world's population is directly dependent on access to natural freshwater sources. So how are inhabited places related to the location of freshwater bodies today? We present a high-resolution global analysis of how close present-day populations live to surface freshwater. We aim to increase the understanding of the relationship between inhabited places, distance to surface freshwater bodies, and climatic characteristics in different climate zones and administrative regions. Our results show that over 50% of the world's population lives closer than 3 km to a surface freshwater body, and only 10% of the population lives further than 10 km away. There are, however, remarkable differences between administrative regions and climatic zones. Populations in Australia, Asia, and Europe live closest to water. Although populations in arid zones live furthest away from freshwater bodies in absolute terms, relatively speaking they live closest to water considering the limited number of freshwater bodies in those areas. Population distributions in arid zones show statistically significant relationships with a combination of climatic factors and distance to water, whilst in other zones there is no statistically significant relationship with distance to water. Global studies on development and climate adaptation can benefit from an improved understanding of these relationships between human populations and the distance to fresh water

    De Novo Transcriptome Sequencing in Anopheles funestus Using Illumina RNA-Seq Technology

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    BACKGROUND: Anopheles funestus is one of the primary vectors of human malaria, which causes a million deaths each year in sub-Saharan Africa. Few scientific resources are available to facilitate studies of this mosquito species and relatively little is known about its basic biology and evolution, making development and implementation of novel disease control efforts more difficult. The An. funestus genome has not been sequenced, so in order to facilitate genome-scale experimental biology, we have sequenced the adult female transcriptome of An. funestus from a newly founded colony in Burkina Faso, West Africa, using the Illumina GAIIx next generation sequencing platform. METHODOLOGY/PRINCIPAL FINDINGS: We assembled short Illumina reads de novo using a novel approach involving iterative de novo assemblies and "target-based" contig clustering. We then selected a conservative set of 15,527 contigs through comparisons to four Dipteran transcriptomes as well as multiple functional and conserved protein domain databases. Comparison to the Anopheles gambiae immune system identified 339 contigs as putative immune genes, thus identifying a large portion of the immune system that can form the basis for subsequent studies of this important malaria vector. We identified 5,434 1:1 orthologues between An. funestus and An. gambiae and found that among these 1:1 orthologues, the protein sequence of those with putative immune function were significantly more diverged than the transcriptome as a whole. Short read alignments to the contig set revealed almost 367,000 genetic polymorphisms segregating in the An. funestus colony and demonstrated the utility of the assembled transcriptome for use in RNA-seq based measurements of gene expression. CONCLUSIONS/SIGNIFICANCE: We developed a pipeline that makes de novo transcriptome sequencing possible in virtually any organism at a very reasonable cost ($6,300 in sequencing costs in our case). We anticipate that our approach could be used to develop genomic resources in a diversity of systems for which full genome sequence is currently unavailable. Our An. funestus contig set and analytical results provide a valuable resource for future studies in this non-model, but epidemiologically critical, vector insect
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