Spatial variation in water supply and demand across river basins of India

Water supply / Water demand / River basins / Catchment areas / Water availability / Water scarcity / Estimation / Irrigation water / Domestic water / Population growth / Urbanization / Groundwater extraction / Crop production / Policy / Water transfer / India

Economic Valuation for Water Supply From Merapi Volcano National Park Case Study: Kali Kuning Sub Watershed

The Merapi Volcano National Park (MVNP) is developed based on particular considerations such as protecting ecosystem or preserving certain species. Management of national park will not succeed unless the communities surrounding park support the park itself. However, it will be challenging because the park was established through a ‘top-down' process. Therefore, it is important to ensure that the surrounding communities are able to derive benefit economically from the park, especially environmental services such as water supply. The goal of this study is to estimate the economic value for water supply from MVNP with Kali Kuning Sub Watershed as the study case. The economic valuation is estimated based on three different land use maps: 2015's (deforestation), 2025's (afforestation) and extreme condition which is grassland (without national park). The economic value is approached by market price for water use value. Lastly, cost and benefit analysis based on several scenarios (deforestation, afforestation and ‘without national park') is implemented. The study shows that afforestation scenario presents the highest economic value from water supply for the surrounding communities as well as the downstream communities

Two Mosquito LRR Proteins Function as Complement Control Factors in the TEP1-Mediated Killing of Plasmodium

SummaryPlasmodium development within Anopheles mosquitoes is a vulnerable step in the parasite transmission cycle, and targeting this step represents a promising strategy for malaria control. The thioester-containing complement-like protein TEP1 and two leucine-rich repeat (LRR) proteins, LRIM1 and APL1, have been identified as major mosquito factors that regulate parasite loads. Here, we show that LRIM1 and APL1 are required for binding of TEP1 to parasites. RNAi silencing of the LRR-encoding genes results in deposition of TEP1 on Anopheles tissues, thereby depleting TEP1 from circulation in the hemolymph and impeding its binding to Plasmodium. LRIM1 and APL1 not only stabilize circulating TEP1, they also stabilize each other prior to their interaction with TEP1. Our results indicate that three major antiparasitic factors in mosquitoes jointly function as a complement-like system in parasite killing, and they reveal a role for LRR proteins as complement control factors

How I treat ... the athlete's foot and its non-mycotic cutaneous pathology

peer reviewedSkin and nails of the foot of sport practitioners of various disciplines are subjected to the effects of benign but invalidating pathologies. Microtraumatisms are frequently involved. Beside dermatomycoses and onychomycoses, a dozen of typical disorders are identified

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

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

Arabidopsis receptor-like protein30 and receptor-like kinase suppressor of BIR1-1/EVERSHED mediate innate immunity to necrotrophic fungi

Effective plant defense strategies rely in part on the perception of non-self determinants, so-called microbe-associated molecular patterns (MAMPs), by transmembrane pattern recognition receptors leading to MAMP-triggered immunity. Plant resistance against necrotrophic pathogens with a broad host range is complex and yet not well understood. Particularly, it is unclear if resistance to necrotrophs involves pattern recognition receptors. Here, we partially purified a novel proteinaceous elicitor called SCLEROTINIA CULTURE FILTRATE ELICITOR1 (SCFE1) from the necrotrophic fungal pathogen Sclerotinia sclerotiorum that induces typical MAMP-triggered immune responses in Arabidopsis thaliana. Analysis of natural genetic variation revealed five Arabidopsis accessions (Mt-0, Lov-1, Lov-5, Br-0, and Sq-1) that are fully insensitive to the SCFE1-containing fraction. We used a forward genetics approach and mapped the locus determining SCFE1 sensitivity to RECEPTOR-LIKE PROTEIN30 (RLP30). We also show that SCFE1-triggered immune responses engage a signaling pathway dependent on the regulatory receptor-like kinases BRASSINOSTEROID INSENSITIVE1-ASSOCIATED RECEPTOR KINASE1 (BAK1) and SUPPRESSOR OF BIR1-1/EVERSHED (SOBIR1/EVR). Mutants of RLP30, BAK1, and SOBIR1 are more susceptible to S. sclerotiorum and the related fungus Botrytis cinerea. The presence of an elicitor in S. sclerotiorum evoking MAMP-triggered immune responses and sensed by RLP30/SOBIR1/BAK1 demonstrates the relevance of MAMP-triggered immunity in resistance to necrotrophic fungi

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.

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

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