This chapter looks more qualitatively at Asia as a single region and focuses more speculatively on the longer run. It is also more personal, since views of the 2025, like beauty, depend inevitably on the eyes of the beholder. The chapter begins by running history backwards via a thought experiment. Suppose in 1975 that one had been predicting the contours of the Asian maize economy in 2000. What variables and parameters would forecasters have missed in significant ways? This procedure turns out to be a very sobering exercise for anyone now predicting events in 2025.

Biofuels from land-rich tropical countries may help displace foreign petroleum imports for many industrialized nations, providing a possible solution to the twin challenges of energy security and climate change. But concern is mounting that crop-based biofuels will increase net greenhouse gas emissions if feedstocks are produced by expanding agricultural lands. Here we quantify the 'carbon payback time' for a range of biofuel crop expansion pathways in the tropics. We use a new, geographically detailed database of crop locations and yields, along with updated vegetation and soil biomass estimates, to provide carbon payback estimates that are more regionally specific than those in previous studies. Using this cropland database, we also estimate carbon payback times under different scenarios of future crop yields, biofuel technologies, and petroleum sources. Under current conditions, the expansion of biofuels into productive tropical ecosystems will always lead to net carbon emissions for decades to centuries, while expanding into degraded or already cultivated land will provide almost immediate carbon savings. Future crop yield improvements and technology advances, coupled with unconventional petroleum supplies, will increase biofuel carbon offsets, but clearing carbon-rich land still requires several decades or more for carbon payback. No foreseeable changes in agricultural or energy technology will be able to achieve meaningful carbon benefits if crop-based biofuels are produced at the expense of tropical forests.

Estimates of climate change impacts are often characterized by large uncertainties that reflect ignorance of many physical, biological, and socio-economic processes, and which hamper efforts to anticipate and adapt to climate change. A key to reducing these uncertainties is improved understanding of the relative contributions of individual factors. We evaluated uncertainties for projections of climate change impacts on crop production for 94 crop–region combinations that account for the bulk of calories consumed by malnourished populations. Specifically, we focused on the relative contributions of four factors: climate model projections of future temperature and precipitation, and the sensitivities of crops to temperature and precipitation changes. Surprisingly, uncertainties related to temperature represented a greater contribution to climate change impact uncertainty than those related to precipitation for most crops and regions, and in particular the sensitivity of crop yields to temperature was a critical source of uncertainty. These findings occurred despite rainfall’s important contribution to year-to-year variability in crop yields and large disagreements among global climate models over the direction of future regional rainfall changes, and reflect the large magnitude of future warming relative to historical variability. We conclude that progress in understanding crop responses to temperature and the magnitude of regional temperature changes are two of the most important needs for climate change impact assessments and adaptation efforts for agriculture.

Rising populations and incomes throughout the world have boosted meat demand by over 75% in the last 20 years, intensifying pressures on production systems and the natural resources to which they are linked. As a growing proportion of global meat production is traded, the environmental impacts of production become increasingly separated from where the meat is consumed. In this paper, we quantify the use of three important resources associated with industrial livestock production and trade - water, land, and nitrogen - using a country-specific model that combines trade, agronomic, biogeochemical, and hydrological data. Our model focuses on pigs and chickens, as these animals are raised predominantly in intensive systems using concentrated, compound feeds. The results describe the geographical patterns of environmental resource use due to meat production, trade, and consumption. We show that US feed, animal, and meat destined for export require almost as much nitrogen and land, and 20% more water, than products destined for domestic consumption. Model results also demonstrate that among various production factors, improvements in crop yields and animal feed conversion efficiencies result in the most significant reductions in environmental harm. By explicitly tracking the externalities of meat production, we hope to bolster suppliers' accountability and provide better information to meat consumers.

The overall goal of the paper is to better understand the development of groundwater markets in northern China. Field survey shows that groundwater markets in northern China have emerged and are developing rapidly. Developing in a number of ways that make them appear somewhat similar to markets that are found in South Asia, groundwater markets in northern China also differ by the impersonality and case bases. The privatization of tubewells is one of the most important driving factors encouraging the development of groundwater markets. Increasing water and land scarcity are also major determinants that induce the development of groundwater markets.

Geographic information systems (GIS) present new opportunities for empirical agronomic research that can complement experimental and modeling approaches. In this study, GIS databases of irrigation practices for more than 4000 fields were compared with wheat yields derived from remote sensing for five growing seasons in the Yaqui Valley of Northwest Mexico. Significant yield effects were observed for both number and timing of irrigations, but not for reported water volumes, suggesting that proper timing is more important to yields than total water amounts. In most years, yield losses were observed when the second irrigation occurred more than 60 d after preplant irrigation, with an average loss of 11 kg ha^-1 for each day above this value. Overall, we estimate that optimal timing and number of irrigations for all fields in Yaqui Valley could increase average yields by roughly 5%. Results varied by year, in part because of variability in growing season rainfall and in part because of variations in water allocations. Interactions with soil types were also evident, with greater yield variability attributed to irrigation on soils with higher clay contents. The results of this study provide new insight into specific causes of yield losses in farmers' fields, which can inform future field experiments, management, and water policy in this region. In general, empirical studies of large GIS databases can help to improve crop management, and meet the dual needs of higher yields and improved water use efficiency.

Expansion of irrigated land can cause local cooling of daytime temperatures by up to several degrees Celsius. Here the authors compare the expected cooling associated with rates of irrigation expansion in developing countries for historical (1961-2000) and future (2000-30) periods with climate model predictions of temperature changes from other forcings, most notably increased atmospheric greenhouse gas levels, over the same periods. Indirect effects of irrigation on climate, via methane production in paddy rice systems, were not considered. In regions of rapid irrigation growth over the past 40 yr, such as northwestern India and northeastern China, irrigation's expected cooling effects have been similar in magnitude to climate model predictions of warming from greenhouse gases. A masking effect of irrigation can therefore explain the lack of significant increases in observed growing season maximum temperatures in these regions and the apparent discrepancy between observations and climate model simulations. Projections of irrigation for 2000-30 indicate a slowing of expansion rates, and therefore cooling from irrigation expansion over this time period will very likely be smaller than in recent decades. At the same time, warming from greenhouse gases will likely accelerate, and irrigation will play a relatively smaller role in agricultural climate trends. In many irrigated regions, therefore, temperature projections from climate models, which generally ignore irrigation, may be more accurate in predicting future temperature trends than their performance in reproducing past observed trends in irrigated regions would suggest.