Feed aggregator

Quantitative assessment of social and economic impact of African swine fever outbreaks in northern Uganda

Our latest outputs -

Quantitative assessment of social and economic impact of African swine fever outbreaks in northern Uganda Chenais, Erika; Boqvist, Sofia; Emanuelson, Ulf; Brömssen, C. von; Ouma, Emily; Aliro, T.; Masembe, Charles; Ståhl, Karl; Sternberg Lewerin, Susanna African swine fever (ASF) is one of the most important pig diseases, causing high case fatality rate and trade restrictions upon reported outbreaks. In Uganda, a low-income country with the largest pig population in East Africa, ASF is endemic. Animal disease impact is multidimensional and include social and economic impact along the value chain. In low-income settings, this impact keep people poor and push those that have managed to escape poverty back again. If the diseases can be controlled, their negative consequences can be mitigated. However, to successfully argue for investment in disease control, its cost-benefits need to be demonstrated. One part in the cost-benefit equations is disease impact quantification. The objective of this study was therefore to investigate the socio-economic impact of ASF outbreaks at household level in northern Uganda. In a longitudinal study, structured interviews with two hundred, randomly selected, pig-keeping households were undertaken three times with a six month interval. Questions related to family and pig herd demographics, pig trade and pig business. Associations between ASF outbreaks and economic and social impact variables were evaluated using linear regression models. The study showed that pigs were kept in extreme low-input-low-output farming systems involving only small monetary investments. Yearly incidence of ASF on household level was 19%. Increasing herd size was positively associated with higher economic output. The interaction between ASF outbreaks and the herd size showed that ASF outbreaks were negatively associated with economic output at the second interview occasion and with one out of two economic impact variables at the third interview occasion. No significant associations between the social impact variables included in the study and ASF outbreaks could be established. Trade and consumption of sick and dead pigs were coping strategies used to minimize losses of capital and animal protein. The results indicate that causality of social and economic impact of ASF outbreaks in smallholder systems is complex. Pigs are mostly kept as passive investments rather than active working capital, complicating economic analyses and further disqualifying disease control arguments based only on standard economic models.

Meta-analysis of average estimates of genetic parameters for growth, reproduction and milk production traits in goats

Animal science for sustainable productivity program:Outputs -

Meta-analysis of average estimates of genetic parameters for growth, reproduction and milk production traits in goats Jembere, T.; Dessie, Tadelle; Rischkowsky, B.; Kebede, K.; Okeyo Mwai, Ally; Haile, A. A meta-analysis of 84 published reports on goats was conducted to calculate weighted and unweighted average direct heritability (ha2), maternal genetic effect (hm2), common environmental effect (c2), repeatability (R), genetic (rg) and phenotypic (rp) correlations for growth, reproduction and milk production traits. Weighted average ha2, hm2, and c2 for growth traits ranged from 0.03 to 0.45, 0.05 to 0.27, and 0.02 to 0.10, respectively. Weighted average ha2 for reproduction and milk production traits ranged from 0.00 to 0.17 and 0.15 to 0.22, respectively. Weighted R for the growth, reproduction, and milk production traits ranged from 0.06 to 0.56, 0.06 to 0.13, and 0.50 to 0.61, respectively. Weighted averages of rp and rg among growth traits ranged from −0.06 to 0.84 and 0.01 to 0.98, respectively. Weighted average rp among milk production traits ranged from 0.18 to 0.94. In most cases average ha2 and rg had higher observed standard deviations compared to the theoretical standard error. The present finding revealed that weighted average ha2, hm2, c2, R, and rg are more reliable for two reasons: estimates of ha2 for some growth traits were more conservative than values from relatively higher number of records and the absence of significant effects of the tested fixed factors on some parameter estimates. However, studies on genetic parameter estimations are required for growth, reproduction, and milk traits in goats.

Yield gap analyses to estimate attainable bovine milk yields and evaluate options to increase production in Ethiopia and India

Feed and forages bioscience program:Outputs -

Yield gap analyses to estimate attainable bovine milk yields and evaluate options to increase production in Ethiopia and India Mayberry, D.; Ash, A.; Prestwidge, D.; Godde, Cécile; Henderson, Ben; Duncan, Alan; Blummel, M.; Ramana Reddy, Y.; Herrero, Mario Livestock provides an important source of income and nourishment for around one billion rural households worldwide. Demand for livestock food products is increasing, especially in developing countries, and there are opportunities to increase production to meet local demand and increase farm incomes. Estimating the scale of livestock yield gaps and better understanding factors limiting current production will help to define the technological and investment needs in each livestock sector. The aim of this paper is to quantify livestock yield gaps and evaluate opportunities to increase dairy production in Sub-Saharan Africa and South Asia, using case studies from Ethiopia and India. We combined three different methods in our approach. Benchmarking and a frontier analysis were used to estimate attainable milk yields based on survey data. Household modelling was then used to simulate the effects of various interventions on dairy production and income. We tested interventions based on improved livestock nutrition and genetics in the extensive lowland grazing zone and highland mixed crop-livestock zones of Ethiopia, and the intensive irrigated and rainfed zones of India. Our analyses indicate that there are considerable yield gaps for dairy production in both countries, and opportunities to increase production using the interventions tested. In some cases, combined interventions could increase production past currently attainable livestock yields.

Remote sensing monitoring of land restoration interventions in semi-arid environments with a before–after control-impact statistical design

Our latest outputs -

Remote sensing monitoring of land restoration interventions in semi-arid environments with a before–after control-impact statistical design Meroni, M.; Schucknecht, A.; Fasbender, D.; Rembold, F.; Fava, F.; Mauclaire, M.; Goffner, D.; Lucchio, L.M. Di; Leonardi, U. Restoration interventions to combat land degradation are carried out in arid and semi-arid areas to improve vegetation cover and land productivity. Evaluating the success of an intervention over time is challenging due to various constraints (e.g. difficult-to-access areas, lack of long-term records) and the lack of standardised and affordable methodologies. We propose a semi-automatic methodology that uses remote sensing data to provide a rapid, standardised and objective assessment of the biophysical impact, in terms of vegetation cover, of restoration interventions. The Normalised Difference Vegetation Index (NDVI) is used as a proxy for vegetation cover. Recognising that changes in vegetation cover are naturally due to environmental factors such as seasonality and inter-annual climate variability, conclusions about the success of the intervention cannot be drawn by focussing on the intervention area only. We therefore use a comparative method that analyses the temporal variations (before and after the intervention) of the NDVI of the intervention area with respect to multiple control sites that are automatically and randomly selected from a set of candidates that are similar to the intervention area. Similarity is defined in terms of class composition as derived from an ISODATA classification of the imagery before the intervention. The method provides an estimate of the magnitude and significance of the difference in greenness change between the intervention area and control areas. As a case study, the methodology is applied to 15 restoration interventions carried out in Senegal. The impact of the interventions is analysed using 250-m MODIS and 30-m Landsat data. Results show that a significant improvement in vegetation cover was detectable only in one third of the analysed interventions, which is consistent with independent qualitative assessments based on field observations and visual analysis of high resolution imagery. Rural development agencies may potentially use the proposed method for a first screening of restoration interventions.

Countdown to ANH Academy Week 2017: Learning Lab on Measuring Women’s Empowerment

CRP 4 program news -

Are you hoping to integrate measures of women’s empowerment into your work? A4NH researchers Hazel Malapit, Jessica Heckert, and Elena Martinez will present a Learning Lab about using the Women’s Empowerment in Agriculture Index (WEAI) in nutrition-sensitive agricultural projects at the upcoming ANH Academy Week in Kathmandu. The WEAI, released in 2012, is a comprehensive, >> Read more

Harnessing the power of data: data management workshop at the BecA-ILRI Hub

Beca news -

The Biosciences eastern and central Africa-International Livestock Research Institute (BecA-ILRI) Hub held a two-week training workshop on Data Management and Genotyping by Sequencing (GBS) analysis from 5–16 June 2017. The focus of the workshop was to equip scientists with computational skills needed to manage and analyze GBS data. 

The training was offered in response to the needs of national agricultural research systems (NARS) scientists identified through various engagements with the BecA-ILRI Hub including annual workshops on Advanced Genomics and Bioinformatics in and Introduction to Molecular Biology and Bioinformatics. 

Twenty participants from nine African countries—Burundi, Ethiopia, Kenya, Madagascar, Nigeria, Rwanda, South Sudan and Uganda—had an opportunity to work through their GBS data under the guidance of facilitators from Earlham Institute, UK; Fathom Labs, Kenya; and Ohio State University, USA as well as bioinformatics research associates from the BecA-ILRI Hub.

In this five-minute video, participants from different countries share how they hope to apply the skills they acquired from the workshop. 


Special Issue of Agriculture for Development on Climate-Smart Agriculture

CRP 7 News -

Read the special issue on climate-smart agriculture

In 2016, the editors of Agriculture for Development, the journal of the Tropical Agriculture Association (TAA), invited Bruce Campbell and Dhanush Dinesh to guest edit a special issue on climate-smart agriculture. In consultation with the Coordinating Editor of the journal, they interacted with colleagues and partners at the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) to produce a broad-ranging selection of articles, news from the field, and book reviews. The special issue of the journal (Ag4Dev30) was published in May 2017. Read the special issue here.

In their guest editorial, Campbell and Dinesh explain how agriculture and food systems stand at the nexus of three of the greatest challenges of the 21st century: overcoming food insecurity, coping with the impact of climate change, and reducing greenhouse gas (GHG) emissions. For these reasons, a major movement has arisen around ‘climate-smart agriculture (CSA)’, which is focussed on the three pillars of productivity, adaptation and mitigation. The development of the CSA concept and its relationship with climate change and agricultural development is described in a new book entitled Climate change and agricultural development: improving resilience through climate smart agriculture, agroecology and conservation, edited by Udaya Sekhar Nagothu and reviewed in this special issue by Manyewu Mutamba.

In the first article, The rise in Climate-Smart Agricultural strategies, policies, partnerships and investments across the globe, Dinesh et al summarise key CSA efforts at global, regional and national levels. These include the growth in publications using the term ‘CSA’; global and regional alliances of national governments; regional and national strategies, policies and action plans; CSA concepts, programmes and projects; and investments in, and funding for, CSA. It is clear from this overview, that CSA really is one of the key ‘movements’ of our times. In CSA-Plan: strategies to put CSA into practice, Girvetz et al present guidance for operational planning and implementation of CSA. CSA-Plan frames actions into four components: situation analysis, targeting and prioritisation, programme design, and monitoring and evaluation. Putting CSA into practice requires knowing what is climate-smart in different locations and what best suits the context. There are therefore often trade-offs between the three goals of CSA: productivity, adaptation/resilience, and mitigation. CSA-Plan has already been successfully applied in many countries and with various partners.

The third pillar of CSA focuses on mitigation. This is a challenge, particularly for developing countries, where food security and adaptation are the main priorities. In many countries, fertiliser applications are below levels required for increased, sustainable production, and therefore need to increase. However, this usually leads to rises in GHG emissions. An article by Lini Wollenberg, entitled The mitigation pillar of CSA – targets and options, argues that agriculture in developing countries should be put on a low emissions development (LED) pathway. She justifies a mitigation target, for agriculture globally, of 1 gigatonne of carbon dioxide equivalent (CO2e) per year by 2030 to stay within a 2˚C emissions budget of 6-8 gigatonnes CO2e for agriculture generally.  However, LED alone will not be sufficient to achieve this, so more ‘transformative actions’ will also be necessary. These include innovations such as methane inhibitors for dairy cows, and breeds of cattle and crops that reduce GHG emissions; policies such as more rigorous carbon pricing, taxes and subsidies; sequestering soil carbon; reducing deforestation; and decreasing food loss and waste.

In their article Agricultural diversification as an adaptation strategy, Noriega et al explain how agricultural biodiversity plays a key role in sustaining ecosystem services and adapting to climate change. However, the full potential of agricultural biodiversity is yet to be realised because it is context-specific, and is often dependent on appropriate enabling policies.

Loboguerrero et al highlight important contributions from outside the agricultural community in their paper Climate services and insurance: scaling CSA. Promoting CSA ‘at scale’ is a key challenge, yet climate services and insurance can provide tools to scale-up CSA by providing an enabling environment and protecting against the impact of climate extremes. In this context, climate services include the production, translation, transfer and use of climate knowledge and information to support climate-informed decision-making and climate-smart policy and planning. Index-based insurance, whereby payouts are based not on farmers’ actual losses, but on an objectively measured index that is correlated with losses, has overcome many obstacles associated with traditional crop insurance. This in turn has facilitated climate change adaptation and climate-resilient development goals.

Differentiation and inequality within communities can provide barriers that constrain women’s ability to adapt to climate change, thereby further widening the gender gap in agriculture. In their paper Closing the gender gap in agriculture under climate change, Nyasimi and Huyer demonstrate how gender-responsive climate-smart agricultural practices and technologies can provide opportunities to close the gender-gap, while at the same time adapting to climate change.

Van Etten et al argue that ‘big data’, including emerging techniques of machine-learning and citizen science, can help CSA to achieve scale and reach millions of farmers with options for tackling climate change. In their paper How can the Data Revolution contribute to climate action in smallholder agriculture? they describe and illustrate five data-related concepts linked to agricultural climate action: lean data, crowdsourcing, big data, ubiquitous computing, and information design.

A selection of Newsflashes and News from the Field articles illustrate some of the many CSA projects currently on-going around the world, including Climate-Smart Agriculture across scales in Latin America, where Loboguerrero et al highlights how policy makers of Central America and Dominican Republic are producing a regional CSA Strategy, complemented by national efforts to promote and implement CSA, for example in the Nicaraguan coffee sector. At the local level, an approach for decision making in the context of climate change was developed in Colombia, and given the success of this initiative enabling farmers to make decisions using climate forecasts, the National Government have decided to scale this up in their Nationally Determined Commitments.

Other examples of the scaling up of CSA are the climate-smart village approach, the Adaptation for Smallholder Agriculture Programme (ASAP), and the VUNA project. Geoff Hawtin reports on climate change research in mountain areas; and Philip Thornton provides a salutary opinion piece on Climate change and CSA in the current political climate.

Finally, the TAA’s 11th Hugh Bunting Memorial Lecture, entitled Climate change and agriculture: risks and opportunities to food and farming systems in the tropics, presented by Tim Wheeler, summarises the challenge of global food production in the context of a growing population, over- and under-consumption of food, and a warming world. Impacts of climate change are presented, and some of the opportunities and responses are described.

Download the special issue: Campbell BM, Dinesh D, (Eds.). 2017. Special issue on climate-smart agriculture (CSA). Agriculture for Development no. 30.

Download the articles separately:

Webinar: Community forestry. Where and why has devolution of forest rights contributed to better governance and livelihoods?

CRP 2: program news -

Initiatives promoting community forestry have taken place in many developing countries over the past three decades. This webinar will summarize the findings of selected meta-analyses of the community forestry experience, present case studies, and preview emerging research that looks at the investment effects of community forestry models.   


Subscribe to International Livestock Research Institute aggregator