No abstract

Climate change impacts on agriculture have become evident, and threaten the achievement of global food security. On the other hand, the agricultural sector itself is a cause of climate change, and if actions are not taken, the sector might impede the achievement of global climate goals. Science-policy engagement efforts are crucial to ensure that scientific findings from agricultural research for development inform actions of governments, private sector, non-governmental organizations (NGOs) and international development partners, accelerating progress toward global goals. However, knowledge gaps on what works limit progress. In this paper, we analyzed 34 case studies of science-policy engagement efforts, drawn from six years of agricultural research for development efforts around climate-smart agriculture by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Based on lessons derived from these case studies, we critically assessed and refined the program theory of the CCAFS program, leading to a revised and improved program theory for science-policy engagement for agriculture research for development under climate change. This program theory offers a pragmatic pathway to enhance credibility, salience and legitimacy of research, which relies on engagement (participatory and demand-driven research processes), evidence (building scientific credibility while adopting an opportunistic and flexible approach) and outreach (effective communication and capacity building).

No abstract

Evaporation estimates are needed for efficient management of water resources at a farm scale as well as at a regional or catchment scale. This paper presents application of artificial neural networks (ANN), statistical regression and climate based models viz.: Penman, Priestley-Taylor and Stephens and Stewart, for estimation of daily pan evaporation. Six different measured weather variables comprising various combinations of maximum and minimum air temperature, sun shine hours, wind speed, relative humidity I and II were used. Randomly selected 1,096 daily records were used to develop the models of ANN and regression, and 365 daily records were used as independent data set for performance evaluation, which was not used previously in any of the model development process. The results of the developed ANN and multiple linear regression (MLR) models along with Penman, Priestley-Taylor and Stephens and Stewart models were compared statistically with observed pan evaporation values. Comparison showed that there is slightly better agreement between the ANN estimations and measurements of daily pan evaporation than other models.

No abstract

Increasing agricultural production to meet the growing demand for food whilst reducing agricultural greenhouse gas (GHG) emissions is the major challenge under the changing climate. To develop long-term policies that address these challenges, strategies are needed to identify high-yield low-emission pathways for particular agricultural production systems. In this paper, we used bio-physical and socio-economic models to analyze the impact of different management practices on crop yield and emissions in two contrasting agricultural production systems of the Indo-Gangetic Plain (IGP) of India. The result revealed the importance of considering both management and socio-economic factors in the development of high-yield low-emission pathways for cereal production systems. Nitrogen use rate and frequency of application, tillage and residue management and manure application significantly affected GHG emissions from the cereal systems. In addition, various socio-economic factors such as gender, level of education, training on climate change adaptation and mitigation and access to information significantly influenced the adoption of technologies contributing to high-yield low-emission pathways. We discussed the policy implications of these findings in the context of food security and climate change.Electronic supplementary materialThe online version of this article (doi:10.1007/s11027-017-9752-1) contains supplementary material, which is available to authorized users.

No abstract

No abstract