http://fse.stanford.edu/publications/Recent publications from FSEen-usPublic domainhttp://fse.stanford.edu/images/feed-icon-48x48.jpghttp://fse.stanford.edu/publications/60http://fse.stanford.edu/publications/22207Science vol. 321, 2008
Rapid economic growth in China and India is the envy, and worry, of the world. Never in history have so many people been pulled out of poverty so quickly. But the newly emergent middle class in both countries has familiar desires: better diets, more comfortable housing, more pleasant places to shop, and more convenient transportation (including personal automobiles). The demands these rapidly expressed desires are placing on global resources have stirred new Malthusian fears. Is there enough food and fuel for China and India to live like Europe and the United States?]]>Thu, 07 Aug 2008 13:41:43 PSThttp://fse.stanford.edu/publications/22207?http://fse.stanford.edu/publications/22194Environmental Modeling and Assessment, 2008
]]>Thu, 07 Aug 2008 16:56:45 PSThttp://fse.stanford.edu/publications/22194?http://fse.stanford.edu/publications/22190Economic Development and Cultural Change vol. 56, 2008
Although genetically modified (GM) crops are being grown on increasing large areas in both developed and developing countries, with few minor exceptions, there has been almost no country that has commercialized a GM major food crop. One reason may be that it is unclear how the commercialization of GM crops will help poor, small farmers. The objective of this article is to report on the results of an economic analysis that uses 3 years of data from a series of quasi-experimental areas (called preproduction trials) in China's GM rice program that were carried out in the fields of small and relatively poor producers in two provinces in China. The article shows that the use of GM rice by farmers in preproduction trials allows farmers to reduce pesticide use and labor input. The effect on yields is less clear, and the findings suggest that there is very little if any yield effect. The article concludes by arguing that the commercialization of GM rice in China could have consequences that exceed the direct impacts on China's farmers and could be a key step in breaking the world's current plant biotechnology logjam.]]>Mon, 30 Jun 2008 18:58:20 PSThttp://fse.stanford.edu/publications/22190?http://fse.stanford.edu/publications/22189World Development vol. 36, 2008
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.]]>Tue, 08 Jul 2008 13:29:51 PSThttp://fse.stanford.edu/publications/22189?http://fse.stanford.edu/publications/22188Agronomy Journal vol. 100,
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 ha1 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.]]>Fri, 27 Jun 2008 13:47:11 PSThttp://fse.stanford.edu/publications/22188?http://fse.stanford.edu/publications/22187Geophysical Research Letters vol. 35, 2008
Previous studies of the long-term climate effects of irrigation have focused on average monthly temperatures. Given the importance of temperature (T) extremes to agriculture and human health, we evaluated irrigation induced changes in various metrics of T extremes using daily observations in California and Nebraska. In addition, simulations from a regional climate model were used to evaluate irrigation effects on T and heat index (HI; also known as the discomfort index) extremes in California, with the latter representing a combined measure of T and humidity. Contrary to our expectation that irrigation would have larger effects on hot days when sensible heat fluxes are higher, both observations and a regional climate model indicate that irrigation cools T on the hottest days of the year by a similar magnitude as on an average summer day. The HI is also reduced by irrigation, but by a much smaller magnitude than T because of the higher humidity above irrigated surfaces. Interestingly, HI is influenced less on the most extreme days than on average days, because of the nonlinear effect of humidity on HI at high T.]]>Fri, 27 Jun 2008 13:41:02 PSThttp://fse.stanford.edu/publications/22187?http://fse.stanford.edu/publications/22186Earth Interactions vol. 12, 2008
]]>Fri, 15 Aug 2008 23:16:05 PSThttp://fse.stanford.edu/publications/22186?http://fse.stanford.edu/publications/22185J. Climate vol. 21, 2008
The response of air temperatures to widespread irrigation may represent an important component of past and/or future regional climate changes. The quantitative impact of irrigation on daily minimum and maximum temperatures (Tmin and Tmax) in California was estimated using historical time series of county irrigated areas from agricultural censuses and daily climate observations from the U.S. Historical Climatology Network. Regression analysis of temperature and irrigation changes for stations within irrigated areas revealed a highly significant (p < 0.01) effect of irrigation on JuneAugust average Tmax, with no significant effects on Tmin (p > 0.3). The mean estimate for Tmax was a substantial 5.0°C cooling for 100% irrigation cover, with a 95% confidence interval of 2.0°7.9°C. As a result of small changes in Tmin compared to Tmax, the diurnal temperature range (DTR) decreased significantly in both spring and summer months. Effects on percentiles of Tmax within summer months were not statistically distinguishable, suggesting that irrigations impact is similar on warm and cool days in California. Finally, average trends for stations within irrigated areas were compared to those from nonirrigated stations to evaluate the robustness of conclusions from previous studies based on pairwise comparisons of irrigated and nonirrigated sites. Stronger negative Tmax trends in irrigated sites were consistent with the inferred effects of irrigation on Tmax. However, Tmin trends were significantly more positive for nonirrigated sites despite the apparent lack of effects of irrigation on Tmin from the analysis within irrigated sites. Together with evidence of increases in urban areas near nonirrigated sites, this finding indicates an important effect of urbanization on Tmin in California that had previously been attributed to irrigation. The results therefore demonstrate that simple pairwise comparisons between stations in a complex region such as California can lead to misinterpretation of historical climate trends and the effects of land use changes.]]>Fri, 27 Jun 2008 13:50:02 PSThttp://fse.stanford.edu/publications/22185?http://fse.stanford.edu/publications/22184Environmental Science and Technology, 2008
]]>Wed, 02 Jul 2008 16:33:39 PSThttp://fse.stanford.edu/publications/22184?http://fse.stanford.edu/publications/22178Boston Review vol. 33, May/June 2008
]]>Fri, 30 May 2008 12:41:42 PSThttp://fse.stanford.edu/publications/22178?http://fse.stanford.edu/publications/22158Geophysical Research Letters vol. 35, 2008
There is a widely recognized need in the scientific and policy communities for probabilistic estimates of climate change impacts, beyond simple scenario analysis. Here we propose a methodology to evaluate one major climate change impact - changes in global average yields of wheat, maize, and barley by 2030 - by a probabilistic approach that integrates uncertainties in climate change and crop yield responses to temperature, precipitation, and carbon dioxide. The resulting probability distributions, which are conditional on assuming the SRES A1B emission scenario and no agricultural adaptation, indicate expected changes of +1.6%, 14.1%, 1.8% for wheat, maize, and barley, with 95% probability intervals of (4.1, +6.7), (28.0, 4.3), (11.0, 6.2) in percent of current yields, respectively. This fully probabilistic analysis aims at quantifying the range of plausible outcomes and allows us to gauge the relative importance of different sources of uncertainty.]]>Mon, 21 Apr 2008 09:56:07 PSThttp://fse.stanford.edu/publications/22158?http://fse.stanford.edu/publications/22149in "Principles of Natural Resource Stewardship: Resilience-Based Management in a Changing World", Chapin, Kofinas, Folke (eds), March 2009
]]>Mon, 05 May 2008 17:50:42 PSThttp://fse.stanford.edu/publications/22149?http://fse.stanford.edu/publications/22133Wendt Lecture, American Enterprise Institute, 2007
]]>Thu, 10 Jul 2008 11:28:13 PSThttp://fse.stanford.edu/publications/22133?http://fse.stanford.edu/publications/22108Global Change Biology vol. 14, 2008
The effect of elevated carbon dioxide (CO2) on crop yields is one of the most uncertain and influential parameters in models used to assess climate change impacts and adaptations. A primary reason for this uncertainty is the limited availability of experi- mental data on CO2 responses for crops grown under typical field conditions. However, because of historical variations in CO2, each year farmers throughout the world perform uncontrolled yield experiments under different levels of CO2. In this study, measure- ments of atmospheric CO2 growth rates and crop yields for individual countries since 1961 were compared with empirically determine the average effect of a 1 ppm increase of CO2 on yields of rice, wheat, and maize. Because the gradual increase in CO2 is highly correlated with major changes in technology, management, and other yield controlling factors, we focused on first differences of CO2 and yield time series. Estimates of CO2 responses obtained from this approach were highly uncertain, reflecting the relatively small importance of year-to-year CO2 changes for yield variability. Combining estimates from the top 20 countries for each crop resulted in estimates with substantially less uncertainty than from any individual country. The results indicate that while current datasets cannot reliably constrain estimates beyond previous experimental studies, an empirical approach supported by large amounts of data may provide a potentially valuable and independent assessment of this critical model parameter. For example, analysis of reliable yield records from hundreds of individual, independent locations (as opposed to national scale yield records with poorly defined errors) may result in empirical estimates with useful levels of uncertainty to complement estimates from experimental studies.]]>Thu, 07 Feb 2008 14:09:46 PSThttp://fse.stanford.edu/publications/22108?http://fse.stanford.edu/publications/22099,
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