REMOTE SENSING FOR AGRICULTURAL WATER MANAGEMENT (RS4AWM) EDUCATIONAL COURSE WITHIN POST-GRADUATE PROGRAM FOR WATER PROFESSIONALS

Geospatial technology has become a core subject in many of the graduate and post-graduate educational curriculum. Last two decades saw substantial development in the field of geospatial science including earth observation and remote sensing and these technologies are widely being used in applications related to land and water resources monitoring, agricultural water management, hydrology, climate science, ecology, environmental science, civil and planning etc. Among these geospatial technologies for agricultural water management is extremely valuable because food and water security are among the biggest challenges that many countries are facing. This is widely recognized in the United Nations Sustainable Development Goals (SDGs) 2 and 6. Reliable information at local and regional scales are the building block for identifying effective and sustainable coping strategies. In this context, developing the capacity of the local experts in using these technologies to support informed decision making is important. RS4AWM course aims at contributing toward this goal by training future generation of water and agriculture professional who will be equipped to use geospatial tools and data in addressing future food and water challenges at different scales. In this manuscript, we explain the evolution and structure of this course and how it is designed to cater the water professionals globally

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

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

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

Sustainable intensification of agriculture for human prosperity and global sustainability

There is an ongoing debate on what constitutes sustainable intensification of agriculture (SIA). In this paper, we propose that a paradigm for sustainable intensification can be defined and translated into an operational framework for agricultural development. We argue that this paradigm must now be defined—at all scales—in the context of rapidly rising global environmental changes in the Anthropocene, while focusing on eradicating poverty and hunger and contributing to human wellbeing. The criteria and approach we propose, for a paradigm shift towards sustainable intensification of agriculture, integrates the dual and interdependent goals of using sustainable practices to meet rising human needs while contributing to resilience and sustainability of landscapes, the biosphere, and the Earth system. Both of these, in turn, are required to sustain the future viability of agriculture. This paradigm shift aims at repositioning world agriculture from its current role as the world’s single largest driver of global environmental change, to becoming a key contributor of a global transition to a sustainable world within a safe operating space on Earth

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

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

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

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

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

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

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

Functionally Redundant RXLR Effectors from <em>Phytophthora infestans</em> Act at Different Steps to Suppress Early flg22-Triggered Immunity

Genome sequences of several economically important phytopathogenic oomycetes have revealed the presence of large families of so-called RXLR effectors. Functional screens have identified RXLR effector repertoires that either compromise or induce plant defense responses. However, limited information is available about the molecular mechanisms underlying the modes of action of these effectors in planta. The perception of highly conserved pathogen- or microbe-associated molecular patterns (PAMPs/MAMPs), such as flg22, triggers converging signaling pathways recruiting MAP kinase cascades and inducing transcriptional re-programming, yielding a generic anti-microbial response. We used a highly synchronizable, pathogen-free protoplast-based assay to identify a set of RXLR effectors from Phytophthora infestans (PiRXLRs), the causal agent of potato and tomato light blight that manipulate early stages of flg22-triggered signaling. Of thirty-three tested PiRXLR effector candidates, eight, called Suppressor of early Flg22-induced Immune response (SFI), significantly suppressed flg22-dependent activation of a reporter gene under control of a typical MAMP-inducible promoter (pFRK1-Luc) in tomato protoplasts. We extended our analysis to Arabidopsis thaliana, a non-host plant species of P. infestans. From the aforementioned eight SFI effectors, three appeared to share similar functions in both Arabidopsis and tomato by suppressing transcriptional activation of flg22-induced marker genes downstream of post-translational MAP kinase activation. A further three effectors interfere with MAMP signaling at, or upstream of, the MAP kinase cascade in tomato, but not in Arabidopsis. Transient expression of the SFI effectors in Nicotiana benthamiana enhances susceptibility to P. infestans and, for the most potent effector, SFI1, nuclear localization is required for both suppression of MAMP signaling and virulence function. The present study provides a framework to decipher the molecular mechanisms underlying the manipulation of host MAMP-triggered immunity (MTI) by P. infestans and to understand the basis of host versus non-host resistance in plants towards P. infestans