Contributions of individual variation in temperature, solar radiation and precipitation to crop yield in the North China Plain, 1961–2003

An understanding of the relative impacts of the changes in climate variables on crop yield can help develop effective adaptation strategies to cope with climate change. This study was conducted to investigate the effects of the interannual variability and trends in temperature, solar radiation and precipitation during 1961–2003 on wheat and maize yields in a double cropping system at Beijing and Zhengzhou in the North China Plain (NCP), and to examine the relative contributions of each climate variable in isolation. 129 climate scenarios consisting of all the combinations of these climate variables were constructed. Each scenario contained 43 years of observed values of one variable, combined with values of the other two variables from each individual year repeated 43 times. The Agricultural Production Systems Simulator (APSIM) was used to simulate crop yields using the ensemble of generated climate scenarios. The results showed that the warming trend during the study period did not have significant impact on wheat yield potential at both sites, and only had significant negative impact on maize yield potential at Beijing. This is in contrast with previous results on effect of warming. The decreasing trend in solar radiation had a much greater impact on simulated yields of both wheat and maize crops, causing a significant reduction in potential yield of wheat and maize at Beijing. Although decreasing trends in rainfed yield of both simulated wheat and maize were found, the substantial interannual variability of precipitation made the trends less prominent

Climate-Agriculture-Modeling and Decision Tool (CAMDT): A software framework for climate risk management in agriculture

Seasonal climate forecasts (SCFs) have received a lot of attention for climate risk management in agriculture. The question is, how can we use SCFs for informing decisions in agriculture? SCFs are provided in formats not so conducive for decision-making. The commonly issued tercile probabilities of most likely rainfall categories i.e., below normal (BN), near normal (NN) and above normal (AN), are not easy to translate into metrics useful for decision support. Linking SCF with crop models is one way that can produce useful information for supporting strategic and tactical decisions in crop production e.g., crop choices, management practices, insurance, etc. Here, we developed a decision support system (DSS) tool, Climate-Agriculture-Modeling and Decision Tool (CAMDT), that aims to facilitate translations of probabilistic SCFs to crop responses that can help decision makers adjust crop and water management practices that may improve outcomes given the expected climatic condition of the growing season

Greenhouse gas emissions in the agricultural and forestry sectors of Uruguay and opportunities in the carbon market

Fossil fuel combustion and changes in the land use (including deforestation) has resulted in an annual rate of carbon dioxide (CO2) accumulation in the atmosphere of 3,500 million metric tones. The accumulation of CO2 and other greenhouse gases is expected to cause observable climatic changes in the 21st century. The International Panel on Climate Change (IPCC) has been publishing assessment reports to governments since the early 1990’s. The newest report to be published in 2001 concludes that the global temperature in the 20th century has increased 0.6 ± 0.2°C, and that the globally averaged surface temperature is projected to warm 1.4°C to 5.8°C by 2100 relative to 1990. The report also includes observational evidence indicating that raises in regional temperatures have already affected several biological systems around the world. Even though it is still difficult to determine how much of the global warming can be attributed to human activity, there is overwhelming agreement that measures should be taken to reverse the current trend of increased accumulation of greenhouse gases (GHG) in the atmosphere. There are basically two paths to reverse such trend: (a) reducing GHG emissions through cleaner energy generation, and (b) removing CO2 through carbon “sinks” or carbon sequestration. Regarding the option of removing CO2 from the atmosphere, IPCC has estimated that agricultural lands have the potential for removing 40,000 - 80,000 million metric tones of carbon over the next 50 to 100 years. Thus, soil carbon sequestration in agricultural lands alone might offset the effects of fossil fuel emissions and land use changes for 10-20 years or longer. Additional carbon can be sequestered in well-managed forests and grassland soils. The present article describes the current situation in the agricultural and forestry sectors of Uruguay with respect to greenhouse gas emissions and discusses the possibility of trading carbon certificates if a carbon trading market is established

Climate services and insurance: scaling climate smart agriculture

One of the main challenges of climate-smart agriculture (CSA) is finding ways to promote the adoption at scale (Editor’s note: 'scaling', 'at scale' or 'to scale' are used throughout this article to mean ‘scaling-out’) of CSA practices and technologies. Climate services and insurance can constitute a tool to scale CSA by providing an enabling environment that can support the adoption of CSA practices while protecting against the impacts of climate extremes. By using a definition of climate services which includes the production, translation, transfer, and use of climate knowledge and information in climate-informed decision-making and climatesmart policy and planning, this paper aims to discuss how climate services and insurance can bring CSA to scale. Three case studies are presented. It is recognised that understanding the knowledge networks through which information flows, and affects the use of climate information, is critical for promoting CSA at scale

Assessing methods for developing crop forecasting in the Iberian Peninsula

Seasonal climate prediction may allow predicting crop yield to reduce the vulnerability of agricultural production to climate variability and its extremes. It has been already demonstrated that seasonal climate predictions at European (or Iberian) scale from ensembles of global coupled climate models have some skill (Palmer et al., 2004)

Interannual-to-multidecadal Hydroclimate Variability and its Sectoral Impacts in northeastern Argentina

This study examines the joint variability of pre- cipitation, river streamflow and temperature over northeast- ern Argentina; advances the understanding of their links with global SST forcing; and discusses their impacts on water re- sources, agriculture and human settlements. The leading pat- terns of variability, and their nonlinear trends and cycles are identified by means of a principal component analysis (PCA)complemented with a singular spectrum analysis (SSA). In- terannual hydroclimatic variability centers on two broad fre- quency bands: one of 2.5?6.5 years corresponding to El Niño Southern Oscillation (ENSO) periodicities and the second of about 9 years. The higher frequencies of the precipita- tion variability (2.5?4 years) favored extreme events after 2000, even during moderate extreme phases of the ENSO. Minimum temperature is correlated with ENSO with a main frequency close to 3 years. Maximum temperature time se- ries correlate well with SST variability over the South At- lantic, Indian and Pacific oceans with a 9-year frequency. Interdecadal variability is characterized by low-frequency trends and multidecadal oscillations that have induced a tran- sition from dryer and cooler climate to wetter and warmer decades starting in the mid-twentieth century. The Paraná River streamflow is influenced by North and South Atlantic SSTs with bidecadal periodicities.The hydroclimate variability at all timescales had signif- icant sectoral impacts. Frequent wet events between 1970 and 2005 favored floods that affected agricultural and live- stock productivity and forced population displacements. On the other hand, agricultural droughts resulted in soil mois- ture deficits that affected crops at critical growth stages. Hy-drological droughts affected surface water resources, caus- ing water and food scarcity and stressing the capacity for hydropower generation. Lastly, increases in minimum tem- perature reduced wheat and barley yields.Fil: Lovino, Miguel Angel. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Müller, Omar Vicente. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; ArgentinaFil: Müller, Gabriela V.. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; ArgentinaFil: Sgroi, Leandro Carlos. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; ArgentinaFil: Baethgen, Walter. Columbia University; Estados Unido

Linking seasonal climate forecasts with crop models in Iberian Peninsula

Translating seasonal climate forecasts into agricultural production forecasts could help to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. In this study, we use seasonal rainfall forecasts and crop models to improve predictability of wheat yield in the Iberian Peninsula (IP). Additionally, we estimate economic margins and production risks associated with extreme scenarios of seasonal rainfall forecast

Innovations in Climate Risk Management: Protecting and Building Rural Livelihoods in a Variable and Changing Climate

We argue that more effective management of climate risk must be part of the response of the international agriculture community to the double crisis of persistent poverty and a changing climate. The most promising opportunities to adapt to climate change involve action on shorter time scales that also contributes to immediate development challenges. Climate risk management (CRM) combines systematic use of climate information, and technology that reduces vulnerability and policy that transfers risk. The cost of climate risk comes both through damaging extreme events and through forfeited opportunity in climatically-favorable years. Effective CRM therefore involves managing the full range of variability, balancing hazard management with efforts to capitalize on opportunity. We discuss several innovations for managing climate risk in agriculture, which have not yet been fully mainstreamed in international agricultural research-for-development. First, effective rural climate information services enable farmers to adopt technology, intensify production, and invest in more profitable livelihoods when conditions are favorable; and to protect families and farms against the long-term consequences of adverse extremes. Second, information and decision support systems synthesize historic, monitored and forecast climate information into forms that are directly relevant to institutional decisions (planning, trade, food crisis response) that impact farmer livelihoods. Third, innovations in index-based insurance and credit overcome some of the limitations of traditional insurance, and are being applied to pre-financing food crisis response, and to removing credit constraints to adopting improved technology. We present a typology of CRM interventions around the concept of dynamic poverty traps