Implications of seasonal climate forecasts on world wheat trade: a stochastic, dynamic analysis

Improvements in seasonal climate forecasts have potential economic implications for international agriculture. A stochastic, dynamic simulation model of the international wheat economy is developed to estimate the potential effects of seasonal climate forecasts for various countries' wheat production, exports and world trade. Previous studies have generally ignored the stochastic and dynamic aspects of the effects associated with the use of climate forecasts. This study shows the importance of these aspects. In particular with free trade, the use of seasonal forecasts results in increased producer surplus across all exporting countries. In fact, producers appear to capture a large share of the economic surplus created by using the forecasts. Further, the stochastic dimensions suggest that while the expected long-run benefits of seasonal forecasts are positive, considerable year-to-year variation in the distribution of benefits between producers and consumers should be expected. The possibility exists for an economic measure to increase or decrease over a 20-year horizon, depending on the particular sequence of years.

Archaeological Identification and Significance of ÉSAG (Agricultural Storage Pits) at Kaman-Kalehöyük, Central Anatolia

Evidence for the presence of storage pits described in Hittite texts by the Sumerogram "ÉSAG" is presented from Kaman-Kalehöyük, a multi-period tell site in central Turkey occupied during the second and first millennia BC. Small earthen pits matching the description of "ÉSAG" were part of the normal suite of domestic installations at the site throughout the period. Similar to pits seen across western Eurasia, they were probably used to store seed corn or seed for trade. Large earthen pits (>7m in diameter) were also present that matched the description of the "ÉSAG" form, and in some cases contained archaeological cereal remains. Evidence from Kaman shows "ÉSAG" were part of Anatolian life for at least 4,000 years and suggests that the term was generic for lined, earthen storage pits. The presence of so many small pits at Kaman-Kalehöyük showed that it was an agricultural production site for much of its existence. The appearance of the large pits, confined to the Hittite period, reflects centralised control of grain supply, probably by the Hittite Kingdom, and fits a pattern seen at other sites in the region during the second millennium BC. /// Hitit metinlerinde Sumerogram "ÉSAG" ile tanimlanan depo çukurlarinin varliğina dair kanit, Orta Anadolu'da M.Ö. İkinci ve Birinci binde iskan edilmiş çok dönemli bir yerleşim alani olan Kaman-Kalehöyük'ten taninmaktadir. Küçük toprak çukurlar "ÉSAG" in tanimlamasina uygun olarak bu dönem süresince normal ev düzeninin bir parçasi olarak karşimiza çikmiştir. Çukurlar, Bati Avrasya'daki benzer çukurlar gibi olasilikla ticaret maksadi ile misir tohumu ya da tohum muhafaza etmişlerdir. "ÉSAG" formunun tanimina uyan büyük toprak çukurlara (çapi 7m. den büyük) rağmen bunlarin tahil depolama ile ilgili bağlantilari tam olarak belirlenmemiştir. Kaman'daki delil, "ÉSAG" in en az 4,000 yildir Anadolu yaşaminin bir parçasi olduğunu ve bu sözcüğün sivanmiş toprak çukurlar için kullanildiğini işaret etmektedir. Kaman-Kalehöyük'te ele geçen birçok küçük çukur, yerleşimin varliğini sürdürdüǧü sürecin büyük bir bölümünde zirai üretim yapildiğini göstermektedir. Hitit Döneminde büyük çukurlarin ortaya çikmasi muhtemelen Hitit Kralliği tarafindan gerçekleştirilen tahil tedarikinin merkezi kontrolünü yansitmakta ve M.Ö. İkinci binde bu bölgedeki diğer yerleşim alanlarinda görülen şekle uymaktadir.

Optimising profitability and environmental trade-offs in managing cropping systems using differential evolution

Whilst traditional optimisation techniques based on mathematical programming techniques are in common use, they suffer from their inability to explore the complexity of decision problems addressed using agricultural system models. In these models, the full decision space is usually very large while the solution space is characterized by many local optima. Methods to search such large decision spaces rely on effective sampling of the problem domain. Nevertheless, problem reduction based on insight into agronomic relations and farming practice is necessary to safeguard computational feasibility. Here, we present a global search approach based on an Evolutionary Algorithm (EA). We introduce a multi-objective evaluation technique within this EA framework, linking the optimisation procedure to the APSIM cropping systems model. The approach addresses the issue of system management when faced with a trade-off between economic and ecological consequences.