A maize farmer near Alauca, Honduras, digs irrigation channels in advance of maize planting. Photo: Neil Palmer, CIAT/CC BY-NC-SA 2.0 - Flickr

Making Agriculture “Climate-Smart” in Latin America and the Caribbean

Sharon Gourdji, , UCS | October 11, 2016, 4:23 pm EST
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I recently returned to the United States from Cali, Colombia where I worked for the International Center for Tropical Agriculture (or CIAT, its Spanish-language abbreviation) for a couple years. CIAT is part of a global network of 15 agricultural research centers in the CGIAR (Consultative Group on International Agricultural Research), which have traditionally focused on crop breeding to raise yields of staple crops around the world. 

At CIAT, I managed the Crop and Climate Modeling group in the Decision and Policy Analysis division, where we focused on improving seasonal climate forecasting for agriculture and estimating longer-term climate change impacts on crops in Colombia and the wider Latin American and Caribbean (LAC) region. The goal was to produce actionable information using the best data available, and then work directly with decision-makers and farmers to tailor scientific results to local needs.

Global climate change due to greenhouse gases, along with regional land-use change, is already leading to hotter and drier conditions across a large portion of the LAC region, particularly in the Caribbean, Central America, northern Colombia, Venezuela, and other parts of northern South America. In these areas, farmers are reporting more erratic rainfall and increasing drought conditions in their fields, while historical data and projections from climate models show temperature increases of up to 3°C from the 1980s to the 2030s.

Inter-annual climate variability has always been a concern for farmers; however, there is evidence that the weather extremes are becoming more extreme and losses are increasing. For example, in Colombia, the 2010-2011 La Niña episode led to massive flooding, landslides and crop losses, while the 2015-2016 El Niño led to record-high temperatures, water shortages, and crop failures in the north of the country.

A recent study* completed by our Crop and Climate modeling group for the Inter-American Development Bank (IDB) shows that projected climate change from the 1980s to 2030s alone would have decreased yields of maize and dry bean (important crops for food security and income) by up to 50% in the Caribbean, Central America and northern South America. However, crop yields throughout Latin America and the Caribbean grew spectacularly in the last half-century due to widespread adoption of improved crop varieties, increased fertilizer use, better management and consolidation of land holdings.

It may now be the case, however, that climate change has started to slow yield growth for some crops and areas, e.g. in Central America. For maize, reported national yield growth data from recent decades does suggest that actual yields are beginning to level out or even decline in the areas expected to face the greatest impacts, particularly in low-income countries like Jamaica and Haiti.

Projected climate change impacts (1971-2049) for maize from Gourdji et al. (in prep) on the x-axis plotted against reported national maize yield growth from the FAOSTAT database (1971-2014) on the y-axis. The red line is the fit from a simple regression showing a significant negative relationship between estimated climate change impacts and reported yield growth rates at the national scale. The orange line represents the same significant relationship that remains after accounting for national GDP per capita levels (averaged from 2000-2014) and fertilizer growth rates (1971-2013) in a multi-linear regression. Since the estimation period (1971-2049) is almost halfway over, we can see that yields are still growing despite the estimated negative impacts from climate change. This is because new varieties, more inputs, etc. have been able to overcome the negative climate impacts thus far.

Projected climate change impacts (1971-2049) for maize from Gourdji et al. (in prep) on the x-axis plotted against reported national maize yield growth from the FAOSTAT database (1971-2014) on the y-axis. The red line is the fit from a simple regression showing a significant negative relationship between estimated climate change impacts and reported yield growth rates at the national scale. The orange line represents the same significant relationship that remains after accounting for national GDP per capita levels (averaged from 2000-2014) and fertilizer growth rates (1971-2013) in a multi-linear regression. Since the estimation period (1971-2049) is almost halfway over, we can see that yields are still growing despite the estimated negative impacts from climate change. This is because new varieties, more inputs, etc. have been able to overcome the negative climate impacts thus far.

One approach CIAT has taken to help farmers adapt to long-term progressive climate change and inter-annual climate variability in Colombia is to encourage “climate-smart agriculture” in partnership with the Colombian Ministry of Agriculture. A key focus of this effort has been to develop tools to generate seasonal climate forecasts before each growing season, develop weather scenarios consistent with those forecasts, and then use the resulting weather scenarios in crop models to create “agro-climatic forecasts” for end-of-season yields. With these modeling tools, scientists suggest optimal sowing dates and crop varieties before the growing season even starts to help reduce losses in bad weather years and take advantage of good years. The seasonal agro-climatic forecasts are then discussed in agricultural round-tables to generate two-way feedback between scientists and farmers, and hopefully exchange useful information.

Figure 1: Rainwater harvesting project in Nicaragua, 2012. Credit: Neil Palmer, CIAT.

Figure 1: Rainwater harvesting project in Nicaragua, 2012. Photo: Neil Palmer, CIAT.

One success story for CIAT and the Ministry of Agriculture was a suggestion for rice farmers to not plant in the north of Colombia at the start of the El Niño period in 2015. This advice saved these farmers from large economic losses as the season progressed and drought conditions worsened. Another way that CIAT has promoted climate-smart agriculture in the region is through the development of rainwater harvesting projects in Nicaragua, where water stored during the rainy season can be used to irrigate a third crop in the dry season with sunny and cool conditions. CIAT has also been involved with local partners in efforts to preserve soil moisture, prevent erosion, reduce deforestation, and mitigate climate impacts through agroecological methods, like quesungual in Honduras, that replace slash-and-burn with “slash-and-mulch” methods that maintain tree cover.

The Latin American and Caribbean region is diverse in terms of farming systems—compare industrialized large-scale soybean production in southern Brazil with small-scale, low-input dry bean production in Honduras and Nicaragua. Though these systems are different from one another and require different management strategies attuned to the local socioeconomic context, scientists in many countries can learn from CIAT’s efforts to promote climate-smart agriculture for staple crops in Colombia. By embedding themselves in local decision-making processes and working with local partners, researchers can help to improve the resilience of the agricultural sector to both climate variability and change. Sustained funding for international agricultural research will be a necessity in the upcoming decades as climate change impacts start to become more severe and noticeable across the globe, and scientists can and should do more to demonstrate the value in the investment.

*Gourdji, S.M., J. Mesa-Diez, D. Obando-Bonilla, L.P. Moreno-Cadena, C.E. Navarro-Racines, M. Fisher, S.D. Prager, J. Ramirez-Villegas, “Near-term impacts of climate change on yields of five major crops across Latin America and the Caribbean”, article in preparation.


With an undergraduate degree in mathematics, Sharon Gourdji completed her Ph.D. in environmental engineering from the University of Michigan, where her dissertation focused on using geostatistical inverse models to estimate carbon sources and sinks. Her more recent work lies in the field of climate change and agriculture. She first visited the International Center for Tropical Agriculture (CIAT) in Cali, Colombia through a Fulbright exchange visit in 2013, collaborating on a study about climate change impacts on maize and dry bean in Nicaragua. She then led the Crop and Climate Modeling group at CIAT in 2014-2015 before returning to the US. Most recently, she is back to improving carbon monitoring techniques in urban areas with the National Institute of Standards and Technology.

Photo: Neil Palmer, CIAT/CC BY-NC-SA 2.0, Flickr

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