The challenges on out-scaling participatory methods in agricultural research

For the last decade or so, participatory research has become an attractive mechanism for conducting adaptive agricultural research. This is mainly motivated by the perception that closer association with resource-poor farmers in identifying the problem and involving them in research implementation presents greater chance of success and adoption of research outputs; hence; enhancing the impact of agricultural research. The advantage of participatory research is considered more prominent in, although not limited to, the adaptation of technologies that require local knowledge of the social, economic and biophysical environments or need high level of human capital or require cooperation of different stakeholders. Resource-poor households in the dry and marginalized areas who face complex biophysical and socioeconomic constraints have benefited less from the agricultural research successes, which led to the green revolution, compared to the farmers in well endowed environments. The result is high prevalence of poverty and malnutrition in the dry areas. However, there is potential to improve the welfare of these households through agricultural research and development. The development of participatory research approach and its application came form the necessity of reaching out these resource-poor farmers whom their participation in the research and development process is considered as key in bringing about a desirable change

Strengthening livelihood resilience in upper catchments of dry areas by integrated natural resources management

The Livelihood Resilience project evolved around the hypothesis that better integrated management can improve the livelihoods of poor farming communities and increase the environmental integrity and water productivity of upstream watersheds in dry areas. This hypothesis was tested by researchers from different Iranian research and executive organizations and farming communities in two benchmark research watersheds in upper Karkheh River Basin in Iran, under the guidance of the ICARDA scientists. Participatory technology development, water, soil, erosion, land degradation and vegetation assessments, livelihood, gender and policy analyses, and integrated workshops delivered a set of principles for watershed management in dry areas

Impacts of climate change on farm income security in Central Asia: An integrated modeling approach

Increased risk due to global warming has already become embedded in agricultural decision making in Central Asia and uncertainties are projected to increase even further. Agro-ecology and economies of Central Asia are heterogenous and very little is known about the impact of climate change at the sub-national levels. The bio-economic farm model (BEFM) is used for ex ante assessment of climate change impacts at sub-national levels in Central Asia. The BEFM is calibrated to 10 farming systems in Central Asia based on the household survey and crop growth experiment data. The production uncertainties and the adaptation options of agricultural producers to changing environments are considered paramount in the simulations. Very large differences in climate change impacts across the studied farming systems are found. The positive income gains in large-scale commercial farms in the northern regions of Kazakhstan and negative impact in small-scale farms in arid zones of Tajikistan are likely to happen. Producers in Kyrgyzstan may expect higher revenues but also higher income volatilities in the future. Agricultural producers in Uzbekistan may benefit in the near future but may lose their income in the distant future. The negative impacts could be further aggravated in arid zones of Central Asia if irrigation water availability decline due to climate change and water demand increase in upstream regions. The scenario simulations show that market liberalization and improved commodity exchange between the countries have very good potential to cope with the negative consequences of climate change

Index-based insurance for climate risk management and rural development in Syria

This is an Author’s Accepted Manuscript of an article published in Climate and Development, 2014, available online: http://www.tandfonline.com/ http://dx.doi.org/10.1080/17565529.2013.84467

Measuring the economic impact of climate change on agriculture: a Ricardian analysis of farmlands in Tajikistan

We apply the Ricardian approach to analyse the economic impact of climate change on agriculture using the 2007 World Bank Tajikistan Living Standards Survey. The study analyses data of 2557 farm households in 166 villages across the 10 agro-ecological country zones. In general, the results indicated that increasing temperature and precipitation will both be damaging to Tajikistan agriculture and consequently to the net revenue (NR) of farmers in the medium and long term. Regressing NR on climate parameters, household and soil variables showed that these variables have a significant impact on the farmers' NR per hectare. We examined the impact of the current climate on farmers' NR per hectare, and how that is affected by future climate scenarios: one +2.9°C warming and one 4.6°C warming scenarios. Although the analysis did not incorporate variables such as the carbon fertilization effect, the role of technology or the change in prices in the future, significant information for policy-making can be extracted. Tajikistan has very diverse regions in terms of geography, population density and socio-economic situation; our results will help policy-makers to anticipate the adaptation effort needed in different locations of the country

Modeling Farmers’ Adoption Decisions of Multiple Crop Technologies: The Case of Barley and Potatoes in Ethiopia

This paper argues and provides empirical evidence that adoption decisions on multiple technologies involve a series of three sequential sub-decisions. Using a multivariate tobit and multivariate probit models and a nationally representative data from Ethiopian highlands, we find that decisions on the area shares of barley and potatoes in total farm size and the plot/field-level decision on the adoption of improved varieties of the two crops are independent. The farm-level decisions on the adoption of improved varieties of the two crops however exhibit strong simultaneity. A striking result from this analysis is that, the number of extension visits affects neither crop choice nor variety adoption decisions which, along with the relatively high density of extension agents in Ethiopia, shows the poor performance of the extension system. Targeting farmers dedicating higher proportion of their lands to the particular crop and introducing other models of extension could increase technology adoption