Shrikant Jagtap

U.S. agriculture and climate change: New results

We examined the impacts on U.S. agriculture of transient climate change assimulated by 2 global general circulation models focusing on the decades ofthe 2030s and 2090s. We examined historical shifts in the location of cropsand trends in the variability of U.S. average crop yields, finding thatnon-climatic forces have likely dominated the north and westward movement ofcrops and the trends in yield variability. For the simulated future climateswe considered impacts on crops, grazing and pasture, livestock, pesticide use,irrigation water supply and demand, and the sensitivity to international tradeassumptions, finding that the aggregate of these effects were positive for theU.S. consumer but negative, due to declining crop prices, for producers. Weexamined the effects of potential changes in El Niño/SouthernOscillation (ENSO) and impacts on yield variability of changes in mean climateconditions. Increased losses occurred with ENSO intensity and frequencyincreases that could not be completely offset even if the events could beperfectly forecasted. Effects on yield variability of changes in meantemperatures were mixed. We also considered case study interactions ofclimate, agriculture, and the environment focusing on climate effects onnutrient loading to the Chesapeake Bay and groundwater depletion of theEdwards Aquifer that provides water for municipalities and agriculture to theSan Antonio, Texas area. While only case studies, these results suggestenvironmental targets such as pumping limits and changes in farm practices tolimit nutrient run-off would need to be tightened if current environmentalgoals were to be achieved under the climate scenarios we examined

Agrometeorological aspects of agriculture in the sub-humid and humid zones of Africa and Asia

Entire sub-Saharan Africa and pockets of Asian population is at risk of starvation. The problems and possibilities are however quite different amongst the two regions. Africa with its less than 8% of land irrigated, 3% or more population growth rate, continues to practice only rudimentary, nonscientific form of agriculture. In Asia where input use is high, farmers are approaching economically optimum yield levels, making it difficult to sustain the same rate of yield gains. While efforts to improve long-term productivity on small scale farm must be accelerated, more emphasis must also be placed on research that will help farmers and governments better cope with expected increases in risks resulting from climatic fluctuations, use of limited water resources, poor market integration and other problems. Finally we believe that all appropriate scientific tools including advanced weather forecasting, information technologies such as models, decisions tools should be mobilized to help solve the problems facing small-scale farmers in developing countries. Due to lack of financial support, the network of meteorological stations do not adequately cover various agrometeorological zones to meet user needs. The general lack of confidence in the reliability of weather forecasts has caused farmers not trust and use the weather forecasts. Training opportunities for meteorological services staff in the use of modern tools like computer simulation modeling, remote sensing, geographic information systems as well as electronic instrumentation is needed.

Stratification and synthesis of crop-livestock production system using GIS

Population increases, land-use changes and marketing opportunities are important factors affecting crop-livestock integration particularly with respect to their effect on soil fertility and feed supply for ruminant livestock. As the human population density rises, crop farmers and grazers are finding it profitable to establish contracts for paddocking, and they are reaching agreement on equitable ways to make use of crop residues and take care of livestocks. As the processes of intensification proceed, mixed crop-livestock systems are evolving as the viable and dominant farming system, allowing smallholder farmers to capitalize on the complementarity between crops and livestock. Strategies directed to raise the productivity of specific crop-livestock systems need to consider the stage of development of the target area in relation to intensification and the nature of crop-livestock interactions. Information related to crop and livestock systems in West Africa is currently available from various sources e.g., household surveys, aerial surveys, rural appraisal, experimental etc., and held by different agencies. The approach used in this study shows how such data (biophysical and socioeconomic) can be integrated within a GIS environment and synthesized to identify the evolution of systems across environments and also to identify constraints and potential of the systems. Potential for integrated crop-livestock systems remains untapped and/or knowledge of its existence is unknown for large parts of Nigeria. Using data from 36 case studies and georeferenced data on cropping intensities and livestock population for the entire country, it was possible to predict emerging crop-livestock systems using GIS. Indeed, depending on availability of data, it is now possible to extend a similar approach in other African countries. The potential contribution of this technology is largely unknown in West and Central Africa, where few operational programs use them. Major technological innovations and appropriate government policies have potential to shift the balance in regional developments, if targeted carefully at areas where the right conditions exist. Further research could then target specific areas thus ensuring efficient allocation of resources while policy makers can achieve development goals by directing policies and resources to domains that have the greatest potential.

A multivariate spatial model for soil water profiles

Pedotransfer functions are classes of models used to estimate soil water holding characteristics based on commonly measured soil composition data as well as other soil characteristics. These models are important on their own but are particularly useful in modeling agricultural crop yields where only soil composition is known. In this article, an additive, multivariate spatial process model is introduced that offers the flexibility to capture the complex structure typical of the relationship between soil composition and water holding characteristics, thus defining a new form of pedotransfer function. Further, the uncertainty in the soil water characteristics is quantified in a manner to simulate ensembles of soil water profiles. Using this capability, a small study is conducted with the CERES maize crop model to examine the sources of variation in the yields of maize. Here it is shown that the interannual variability of weather is a more significant source of variation in crop yield than the uncertainty in the pedotransfer function for two specific soil textures.

Water Use and Seasonal Differences in Maize Performance in the Transitional Humid Zone of Nigeria

ABSTRACT Maize (Zea mays) was grown in four consecutive (wet and dry) seasons in two years at the experimental fields of the International Institute of Tropical Agriculture, Ibadan, Nigeria. Water use of maize and yield responses in the humid forest-Savanna transition zone of Nigeria were assessed using drainage lysimeters which were irrigated daily depending on the evaporative demand of the atmosphere. Results show significant differences (p < 0.01) in water use, yields and yield components between the seasons and the years. Seasonal averages of water used from sowing to harvest were 363 mm and 271 mm for the wet and dry seasons, respectively. These are equivalent to mean water use efficiency (WUE) of 122 g and 176 g of water per gram dry matter for the wet and dry seasons, respectively. Significant yield differences were recorded between the wet (7.6 t ha−1) and dry (3.8 t ha−1) seasons and between the first (6.6 t ha−1) and second (4.8 t ha−1) years, respectively. Also, the lysimeter surfaces gave superior maize yields when compared to the rain-fed plots. Two years average lysimeter yields were 9.1 t ha−1 and 4.3 t ha −1 for the wet and dry seasons, respectively, compared to rain-fed plots yields of 5.6 and 3.3 tonnes ha−1 during the same period. The result shows a significant yield response irrespective of the season, to increased water input from higher rainfall amount, distribution or supplementary irrigation.