By Nancy McCarthy* | [email protected] | Senior Researcher, Lead Analytics
The Intergovernmental Panel on Climate Change, established by the United Nations Environmental Programme and the World Meteorological Organization , in its Working Group I report, confirmed that it is extremely likely that human activity has contributed to increases in global average surface temperatures through the release of greenhouse gases.
The report also states that it is very likely that human activity has contributed to increased frequency of extreme weather events. Given current trends in emissions, further climate changes and frequency of extreme weather events is projected to continue through the 21st century. This underscores the importance of developing and implementing adaptation strategies, particularly for vulnerable sectors.
The Working Group II report documents current evidence on vulnerable sectors, likely impacts in the absence of adaptation, and more limited evidence on adaptation strategies. As documented in this report, a particularly vulnerable sector is agriculture. Those dependent on agriculture for their livelihoods are also often those with limited resources to adapt to climate changes, including expected increases in the frequency of weather extremes. This then presents a double challenge, supporting those with limited resources to adapt to climate change in a sector particularly vulnerable to such changes.
A recent IDB study synthesizes current empirical evidence on a number of agricultural practices that have been posited to increase yields and reduce yield variability by building soil quality, increasing water use efficiency, and reducing soil and water erosion.
Such practices often increase carbon sequestered in soils, thereby contributing to climate change mitigation. Because of benefits in terms of increased productivity, greater resilience to weather extremes and potential to mitigate of green house emissions, the Food and Agricultural Organization has dubbed this set of methods and theories as “climate-smart agriculture” practices, also known as CSA among experts in the field.
The review considers in depth four broad categories of CSA practices: conservation agriculture (minimum soil disturbance in combination with permanent soil cover and crop rotations), irrigation, agroforestry, and soil conservation structures. Empirical evidence on the benefits as well as the costs and barriers to adoption is presented, followed by a discussion of the implications for designing project impact evaluations, given unique characteristics of each set of practices. The review also considers evidence on two potential policy mechanisms to increase adoption of CSA practices, “payment for environmental services”-type programs and agriculture insurance.
The study captures the fact that available empirical evidence is highly concentrated in Mexico and Brazil, and to a lesser extent Argentina and Chile, with far more limited empirical evidence on the benefits and costs of CSA practices in Central America and the Caribbean in particular.
Although information is somewhat limited, evidence suggests that in most countries there is currently limited adoption of CSA practices, in spite of the fact that smallholders are vulnerable to floods, droughts, and extreme night-time temperatures. But, the size of both benefits and costs of different CSA practices vary depending on underlying agro-ecological as well as socio-economic conditions, making it difficult to extrapolate evidence from Mexico and Brazil, for instance, to other Latin American countries.
In order to help fill knowledge gaps and generate information needed to prioritize adaptation actions, the study highlights some important features of CSA practices and potential policy mechanisms that need to be incorporated into the design of impact evaluations.
In particular, evidence suggests that improvements in average yields may take many years to materialize; shorter-term benefits, however, may be expected in terms of reduced yield variability. This latter poses interesting challenges in terms of impact assessment given that many methodologies can recover “average” impacts, but are not necessarily well-suited to recovering impacts on, say, yield variability or exposure to down-side losses.
*Nancy McCarthy earned a PhD in Agriculture and Resource Economics from UC Berkeley in 1996, and a JD from the George Mason University School of Law in 2009, and founded LEAD Analytics in 2010. McCarthy, who has more than 15 years of experience working in developing countries, collaborates with a wide network of research partners and development practitioners both in the United States and abroad. McCarthy is a contributing author on the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) Working Group 2 chapter on Adaptation and Food Security.
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