The dominant Anopheles vectors of human malaria in the Asia-Pacific region: occurrence data, distribution maps and bionomic précis

<p>Abstract</p> <p>Background</p> <p>The final article in a series of three publications examining the global distribution of 41 dominant vector species (DVS) of malaria is presented here. The first publication examined the DVS from the Americas, with the second covering those species present in Africa, Europe and the Middle East. Here we discuss the 19 DVS of the Asian-Pacific region. This region experiences a high diversity of vector species, many occurring sympatrically, which, combined with the occurrence of a high number of species complexes and suspected species complexes, and behavioural plasticity of many of these major vectors, adds a level of entomological complexity not comparable elsewhere globally. To try and untangle the intricacy of the vectors of this region and to increase the effectiveness of vector control interventions, an understanding of the contemporary distribution of each species, combined with a synthesis of the current knowledge of their behaviour and ecology is needed.</p> <p>Results</p> <p>Expert opinion (EO) range maps, created with the most up-to-date expert knowledge of each DVS distribution, were combined with a contemporary database of occurrence data and a suite of open access, environmental and climatic variables. Using the Boosted Regression Tree (BRT) modelling method, distribution maps of each DVS were produced. The occurrence data were abstracted from the formal, published literature, plus other relevant sources, resulting in the collation of DVS occurrence at 10116 locations across 31 countries, of which 8853 were successfully geo-referenced and 7430 were resolved to spatial areas that could be included in the BRT model. A detailed summary of the information on the bionomics of each species and species complex is also presented.</p> <p>Conclusions</p> <p>This article concludes a project aimed to establish the contemporary global distribution of the DVS of malaria. The three articles produced are intended as a detailed reference for scientists continuing research into the aspects of taxonomy, biology and ecology relevant to species-specific vector control. This research is particularly relevant to help unravel the complicated taxonomic status, ecology and epidemiology of the vectors of the Asia-Pacific region. All the occurrence data, predictive maps and EO-shape files generated during the production of these publications will be made available in the public domain. We hope that this will encourage data sharing to improve future iterations of the distribution maps.</p

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Not AvailableMulches, organic or inorganic in nature, favorably moderate soil's hydrothermal regime, assume significance in the context of climate change. The in-situ mulching under conservation agriculture avoids crop residue burning. Besides improving crop growth, moderation of soil moisture regime, buffering soil temperature fluctuations, facilitating soil aeration, seedling emergence, improving root growth, efficient water and nutrient use by crop plants it also improves the environment by facilitating carbon sequestration and reducing greenhouse gas emissions from the soil. Appropriate policy decisions to overcome limitations in adoption of conservation agriculture and mulching are required by providing technical and financial support to the farmersNot Availabl

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Multi-disciplinary research article.The study examines the energy requirement and energy input–output relationship of soybean-based crop production systems viz., soybean (Glycine max (L.) Merr.)–wheat (Triticum aestivum L.), soybean–mustard (Brassica juncea (L.) Czern & Coss.) and soybean–chickpea (Cicer arietinum L.) in central India. Using a pre-tested questionnaire, 135 farmers were selected through a multi-stage stratified random sampling technique. Results revealed that manures and chemical fertilizers (50.87%), seedbed preparation (18.30%) and sowing management (17.69%) consumed the bulk of the energy (operational and non-operational) for all crops, it was highest in soybean–wheat and the lowest in soybean–chickpea . Wheat, with the highest grain productivity, produced the most biomass energy and highest grain-energy productivity . The total bioenergy output of the crop production systems followed the order: soybean–wheat soybean–mustard soybean–chickpea . But this order was reversed for energy-use efficiency (EUE): soybean–chickpea (5.91)> soybean–mustard (5.86)> soybean–wheat (5.54). Specific energy was highest in (soybean grain) followed by (mustard seed), (chickpea grain) and (wheat grain) indicating that soybean is the most energy-investment intensive crop. Regarding energy intensiveness the results were contrary to EUE. Energy intensiveness was higher in wheat (1.40) followed by mustard (1.11), soybean (0.89) and chickpea (0.87) and the soybean–wheat system (1.13) emerged as the most energy-intensive system compared to soybean–mustard (0.97) and soybean–chickpea (0.88). Though the net return from soybean–wheat was marginally higher than other systems, the soybean–chickpea system is more suitable in the central ecological niche of India due to its low requirement for non-renewable resources, higher EUE and benefit–cost ratio.Not Availabl

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Not AvailableIncreasing production of wheat from a limited water supply can result from efficient irrigation and nutrient management. A 3‐year field experiment was conducted at the Indian Institute of Soil Science, Bhopal, to study the growth, yield, seasonal evapotranspiration (ET) and water use efficiency (WUE), and the water–yield relationship of wheat in a soybean–wheat cropping system on vertisols. Three levels of irrigation, viz. I0, no post‐sowing irrigation; I1, two irrigations [crown root initiation (CRI) and flowering stage]; and I2, three irrigations (CRI, maximum tillering and flowering stage) and three nutrient management treatments, viz. F0, control (without fertilizer/manure); F1, 100 % NPK (100–21.5–24.9 kg ha−1); and F2, 100 % NPK + farmyard manure (FYM‐10 t ha−1) were tested in a split‐plot design with three replication. It has been established (through anova) that the year effect was rather negligible and the interaction effects of irrigation and nutrient management on the growth parameters, ET, yield components, yield and WUE were significant. Plant height, progressive leaf area index, dry matter accumulation and crop growth rate were higher in I2F2, and I2F1 and I1F2 were statistically at par. The seasonal ET increased significantly with the increase in water supply in every nutrient treatment and it was highest in I2F2 and lowest in I0F0. The highest grain yield was obtained in I2F2; and a similar yield was recorded in I3F1 and I2F2. This shows a strong interaction effect between irrigation and nutrients. Yield components, viz. number of ears m−2, number of grains ear−1 and 1000‐grain weight were significant. The higher number of ears m−2 containing greater number of grains with relatively heavier weights appeared to have contributed to the higher yield in I1F2, I2F1 and I2F2. The highest WUE obtained in I0F2 did not correspond to the highest yield and maximum ET, but a WUE of 10.43 kg ha−1 mm−1 in the I2F2 combination corresponded with the highest yield and the seasonal ET requirement was 391.8, which was 137 % greater than the water use at maximum WUE. The ET–grain yield relationship was linear, with a lowest regression slope (i.e. marginal WUE) and elasticity of water production (Ewp) in F0 and a considerably higher slope and Ewp in F1 and F2. As the Ewp is positive and close to one in 100 % NPK treatment, the scope of improving WUE and yield with only inorganic fertilizer is very little, and relatively greater scope exists in the integrated management of organic manure and inorganic fertilizer. The results suggest that integrated nutrient management (100 % NPK + FYM) in conjunction with three irrigations maximized yield of wheat with concomitant improvement in ET and WUE under limited water availabilityNot Availabl

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Not AvailableIn Vertisols of central India erratic rainfall and prevalence of drought during crop growth, low infiltration rates and the consequent ponding of water at the surface during the critical growth stages are suggested as possible reasons responsible for poor yields (<1 t ha−1) of soybean (Glycine max (L.) Merr.). Ameliorative tillage practices particularly deep tillage (subsoiling with chisel plough) can improve the water storage of soil by facilitating infiltration, which may help in minimizing water stress in this type of soil. In a 3-year field experiment (2000–2002) carried out in a Vertisol during wet seasons at Bhopal, Madhya Pradesh, India, we determined infiltration rate, root length and mass densities, water use efficiency and productivity of rainfed soybean under three tillage treatments consisting of conventional tillage (two tillage by sweep cultivator for topsoil tillage) (S1), conventional tillage + subsoiling in alternate years using chisel plough (S2), and conventional tillage + subsoiling in every year (S3) as main plot. The subplot consisted of three nutrient treatments, viz., 0% NPK (N0), 100% NPK (N1) and 100% NPK + farmyard manure (FYM) at 4 t ha−1 (N2). S3 registered a significantly lower soil penetration resistance by 22%, 28% and 20%, respectively, at the 17.5, 24.5 and 31.5 cm depths over S1 and the corresponding decrease over S2 were 17%, 19% and 13%, respectively. Bulk density after 15 days of tillage operation was significantly low in subsurface (15–30 cm depth) in S3 (1.39 mg m−3) followed by S2 (1.41 mg m−3) and S1 (1.58 mg m−3). Root length density (RLD) and root mass density (RMD) of soybean at 0–15 cm soil depth were greater following subsoiling in every year. S3 recorded significantly greater RLD (1.04 cm cm−3) over S2 (0.92 cm cm−3) and S1 (0.65 cm cm−3) at 15–30 cm depth under this study. The basic infiltration rate was greater after subsoiling in every year (5.65 cm h−1) in relation to conventional tillage (1.84 cm h−1). Similar trend was also observed in water storage characteristics (0–90 cm depth) of the soil profile. The faster infiltration rate and water storage of the profile facilitated higher grain yield and enhanced water use efficiency for soybean under subsoiling than conventional tillage. S3 registered significantly higher water use efficiency (17 kg ha−1 cm−1) over S2 (16 kg ha−1 cm−1) and S1 (14 kg ha−1 cm−1). On an average subsoiling recorded 20% higher grain yield of soybean over conventional tillage but the yield did not vary significantly due to S3 and S2. Combined application of 100% NPK and 4 t farmyard manure (FYM) ha−1 in N2 resulted in a larger RLD, RMD, grain yield and water use efficiency than N1 or the control (N0). N2 registered significantly higher yield of soybean (1517 kg ha−1) over purely inorganic (N1) (1392 kg ha−1) and control (N0) (898 kg ha−1). The study indicated that in Vertisols, enhanced productivity of soybean can be achieved by subsoiling in alternate years and integrated with the use of 100% NPK (30 kg N, 26 kg P and 25 kg K) and 4 t FYM ha−1Not Availabl

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Not AvailableField experiments were conducted in a deep Vertisol at the Indian Institute of Soil Science, Bhopal during the years 2001–2005 to assess the effect of five different irrigation strategies through combinations of sprinkler and flood irrigation and two N application methods on yield and water use efficiency of wheat (cv WH 147). The amount of irrigation applied each year differed according to the availability of water in the water harvesting pond to simulate the actual water crisis faced by the farmers in this region during these years due to monsoon failure. Results indicated that when wheat was grown only with 8-cm irrigation at sowing or 14 cm up to the crown root initiation stage, dry sowing of wheat immediately followed by sprinkler and subsequent irrigation through flooding produced the highest yield and water and nitrogen use efficiencies. However, when 20-cm irrigation was supplied up to the flowering stage or 14-cm irrigation was supplied up to tillering stage through sprinkler in 4 and 3 splits, respectively, at critical growth stages, maximized the grain yield and water and nitrogen use efficiencies. Across the years, the crop yield and water and nitrogen use efficiencies increased with increase in water supply.Not Availabl

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Multi-disciplinary Research WorkThe study attempts to analyze the energy input-output relationship and economic returns of the cropping systems in central India. The data collected from farmers through multistage random sampling techniques, were subjected to descriptive analysis of simple proportions and percentages. Findings reveal that total energy involved in soybean- wheat system (19817 MJ ha 1; renewable 5507 MJ ha 1 and non-renewable 14310 MJ ha 1) is much greater than soybean-chickpea (11239 MJ ha 1; renewable 4883 MJ ha 1 and non-renewable 6356 MJ ha 1), pigeonpea monocropping (2329 MJ ha 1; renewable 714 MJ ha 1 and non-renewable 1616 MJ ha 1), fallow-wheat (13716 MJ ha 1; renewable 2810 MJ ha 1 and non-renewable 10906 MJ ha 1) and fallow- chickpea (4445 MJ ha 1; renewable 2526 MJ ha 1 and non-renewable 1919 MJ ha 1). The percentage of non-renewable energy is higher than renewable energy inputs. Soybean-wheat (70%) and fallow-wheat (78%) systems resorted to more use of non-renewable energy than renewable energy. In soybean-chickpea system share of non-renewable energy is 52%. The energy outputs follow the order: soybean-wheat (70495 MJ ha 1) > fallow-wheat (52084 MJ ha 1) > soybean-chickpea (44485 MJ ha 1) > pigeonpea monocropping (20427 MJ ha 1) > fallow-chickpea (20357 MJ ha 1); energy efficiency is the highest in pigeonpea monocropping (8.76); for other systems it ranged from 3.67 in soybean-wheat to 4.63 in fallow-chickpea system. The net energy of the systems is 50678 MJ ha 1 in soybean-wheat, 38368 MJ ha 1 in fallow-wheat, 33246 MJ ha 1 in soybean-chickpea, 18098 MJ ha 1 in pigeonpea monocropping and 15912 MJ ha 1 in fallow-chickpea. Though the soybean-wheat system results in highest net energy, its energy productivity (0.269 kg MJ 1) is the lowest and that of fallow-wheat system is 0.288 kgMJ 1. It is comparatively higher for other systems, viz., soybean-chickpea (0.307 kg MJ 1), pigeonpea monocropping (0.643 kg MJ 1) and fallow-chickpea (0.342 kg MJ 1). Further, energy intensity is 3.84 MJ kg 1 and 0.887 MJ Rs. 1 in physical and economic terms, respectively, in the soybean- wheat system, and are greater than other systems, viz., soybeanchickpea (3.43 MJ kg 1 and 0.577 MJ Rs. 1), pigeonpea monocropping (1.55 MJ kg 1 and 0.243 MJ Rs. 1), fallow-wheat (3.59 MJ kg 1 and 1.408 MJ Rs. 1) and fallow-chickpea (2.96 MJ kg 1 and 0.569 MJ Rs. 1). But the soybean-wheat cropping system has been found more remunerative in terms of benefit-cost ratio (1.27) owing to its ability to generate the highest return per rupee investment than soybean-chickpea (1.23) and pigeonpea monocropping (1.23). The fallow-based systems are having comparatively better benefit/cost ratio. The investment requirement and also net return is highest for soybean-wheat system, thus is preferred by the large farmers. Farmers are forced to use soybeanchickpea crop rotation whenever there is lack of adequate rainfall during rainy season and irrigation facilities in succeeding winter season. Thus, fallow-chickpea rotation is suitable for extremely poor farmers with no irrigation facilities.Not Availabl

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Not AvailablePedotransfer functions (PTFs) for estimation of soil water retention at field capacity (θFC, -33 kPa) and permanent wilting point (θPWP, -1500 kPa) were developed under three soil categories (<20%, 20-40% and >40% clay) through linear, log-linear and stepwise-regression (SR) approach, using particle size distribution and bulk density data. Under <20% clay, the log-linear model was better than other models in predicting θFC, whereas SR model was better for predicting θPWP. Under 20-40% clay category, all the three approaches predicted θFC with equal efficiency, while SR was superior for θPWP. The log-linear models performed better in predicting both the θFC and θPWP with >40% soil clay.Not AvailableNot Availabl

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Not AvailableSoil field capacity (FC) and permanent wilting point (PWP) are important input parameters in many biophysical models. Although these parameters can be measured directly, their measurement is quite difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. A study has been conducted to evaluate PTFs of FC and PWP created using artificial neural networks (ANNs). A total of 721 different sampling locations spread all over India are selected to develop PTFs using ANN. Results indicate that six neurons in hidden layers are best suited for prediction of FC and PWP. The statistical criteria (value of R2, RMSE, MBE, ME, and d) is used to evaluate ANN, indicated an unbiased and higher predictability of developed models.Not Availabl