AgMIP Regional Integrated Assessment Case Study featured in new FAO Climate Smart Agriculture Book
By: Jenna Behrendt
PHOTO 1 | Climate Smart Agriculture – Building Resilience to Climate Change Publication
The anticipated effects of climate change require a multi-dimensional approach to evaluate agricultural system performance under uncertain conditions in future. Agricultural models have historically focused on agronomic and economic impacts without adequately considering environmental and social variables and their tradeoffs in modeling methodology. Sustainable agricultural planning in a changing climate requires incorporating social and environmental factors, as well as integrating adaptation, mitigation and resilience measures.
Climate Smart Agriculture – Building Resilience to Climate Change was published by the Food and Agriculture Organization of the United Nations (FAO) in response to evolving interest in agricultural planning, combining research and leading professionals’ expertise to inform Climate Smart Agriculture (CSA). CSA focuses on transforming agricultural systems to ensure food security in a changing climate and reduction of greenhouse gas emissions by evaluating performance under existing and possible future conditions. Standard approaches for agricultural system performance evaluation, including conventional field experiments, are not effective for CSA evaluation given high levels of climate and socio-economic uncertainty. AgMIP developed an alternative methodology, known as of the Regional Integrated Assessment (RIA), to analyze agricultural systems and achieve CSA multi-dimensionality.
Using AgMIP Regional Integrated Assessment Methods to Evaluate Vulnerability, Resilience and Adaptive Capacity for Climate Smart Agricultural Systems is a chapter within Climate Smart Agriculture – Building Resilience to Climate Change that uses RIA methodology for regional climate impact assessment in Nkayi, Zimbabwe. This study not only documents and describes RIA use but also examines resilience and vulnerability among smallholder farms in Africa.
The AgMIP RIA approach to climate change impact, adaptation, mitigation and vulnerability provides a framework for CSA assessment using key indicators of system performance identified through expert and stakeholder input. The AgMIP RIA method quantifies economic or other well-being (e.g. health) gains and losses from climate change, and categorizes any negative impacts as being vulnerable. The RIA method enables researchers working with stakeholders to answer the following questions:
1. What is the sensitivity of current agricultural production systems to climate change?
2. What are the effects of adaptation in the current state of the world?
3. What is the impact of climate change on future agricultural production systems?
4. What are the benefits of climate change adaptations?
The RIA approach combined observational data with biophysical and economic models across a variety of future climate and socio-economic scenarios, as shown in Figure 1.
Assessing Crop-Livestock Adaptations in Zimbabwe:
Evaluating climate impacts on agriculture for smallholders in semi-arid Zimbabwe is extremely important, given their dependence on subsistence farming and already challenging climatic conditions for agriculture. Erratic rainfall leads to droughts every 5 years and predominantly nutrient-deficit Kalahari sands challenge agricultural efforts. According to AgMIP’s regional economics team co-leader Roberto Valdivia, “limited capital combined with other bio-physical conditions such as poor and depleted soils, and unfavorable climatic conditions prevents the adoption of agricultural technologies and makes these smallholders extremely vulnerable to climate change impacts. Understanding climate impacts for these systems is critical for informing CSA strategies and maintaining food security.” Sabine Homann-Kee Tui, PI for the crop livestock study in Zimbabwe adds, “the models project great potential for increasing production and resilience through better integration of crops and livestock in areas like Nkayi district. Business as usual is not an option, but improved decision making to guide farmers’ investments in more diversified and profitable farming.” This study suggests that smallholder farming systems assessments require the following considerations:
|•||Integrated farm and household approach to adequately account for all components of household income and evaluate economic vulnerability and resilience.|
|•||Bio-physical and socio-economic heterogeneity across farm household populations. Farmers vary tremendously, including but not limited to, size, soil conditions, famer behavioral differences and access to capital and information. Current modeling methods for smallholder systems often fail to account for variation across smallholders, seasonal variation and household relationships to the farmland.|
|•||Temporal variation and system dynamics throughout seasons is particularly critical for evaluating adaptation, mitigation and resiliency over time. |
The AgMIP RIA methods were applied to a crop and livestock system in western Zimbabwe typical smallholder agricultural systems for semi-arid drought prone Southern Africa to illustrate how RIA methods can evaluate alternative practices for CSA. In this study, the TOA-MD model was used to implement the RIA approach. The TOA-MD uses a statistical representation of the farming systems in the region and accounts for heterogeneity across biophysical and socio-economic conditions in a population of farm households. This enabled the evaluation of various scenarios’ impact on incomes, vulnerability and resilience. The following adaptation methods were successful in mitigating climate change impacts on crop yield:
|•||Adopting long duration maize varieties over short duration varieties; |
|•||Shifting a portion of maize farmland to a maize-mucuna rotation and using some of the mucuma biomass as organic fertilizer; and|
|•||TMicro-dosing on maize fields during the second year after maize-mucuna rotation.|
John Antle, AgMIP Executive Committee member and regional economics team co-leader said, “the experience in Zimbabwe with AgMIP RIA methods shows the potential for a new, more computation-intensive, system-based approach to agricultural research. This work confirms that collaboration between scientists and stakeholders, supported by new and better data and analytics, can provide the kind of detailed information about the performance of farm household production systems that is needed to make more informed decisions. Now we need to apply these methods more widely to develop a portfolio of options to support much needed investments in climate-smart agricultural research and development.”
FIGURE 1 | AgMIP Regional Integrated Assessment approach simulates climate change impact, vulnerability and adaptation through climate data, bio-physical simulation models and economic models representing a population of heterogeneous farm household systems. (a) RAPS together with global and national price, productivity and land use projections define the bio-physical and socio-economic environment in which (b) complex farm household systems operate in heterogeneous regions (c). Analysis of technology adoption and impact assessment is implemented in these heterogeneous farm household populations (d). This regional analysis may feed back to the country and global scales (e) (Source: Antle et al. 2015a).