Date of Award

Fall 2021

Project Type


Program or Major

Natural Resources and Environmental Studies

Degree Name

Master of Science

First Advisor

Shadi Atallah

Second Advisor

Stephanie Brockmann

Third Advisor

Marek Petrik


Coffee is the most valuable agricultural product in international trade. It is projected to face a decrease in production by as much as 50% by 2050, mainly due to rising temperature, changes in rainfall patterns, deforestation, and the spread of fungal pathogens and pests. Among the biological threats to coffee, the Coffee Leaf Rust (CLR) has the most destructive economic impact all around the world. The most recent widespread outbreak resulted in a 16% harvest loss in Central America and a 31% loss in Colombia during the 2012-2013 season, and a record of 50% loss was reported in Costa Rica during 2013-2014. The warm episode of the El Niño Southern Oscillations (ENSO) cycle in 2007-08 was a major contributor to the CLR outbreak during 2008-11 and a higher frequency of warm episodes is expected with the current trend of greenhouse warming. In fact, climate change is expected to affect 25 million coffee growers, mainly smallholders in 70 countries around the world. One of the channels through which climate change is expected to exacerbate declines in coffee production is by creating temperature and humidity conditions that are ideal for CLR outbreaks on higher altitudes. One ecosystem-based climate adaptation strategy that is recommended for coffee farmers is intercropping coffee shrubs with shade trees, but it has remained controversial because of the nonlinear effects of shade on CLR and coffee yields and profits. Shade trees provide disease regulation and other ecosystem services, but they compete with coffee shrubs for soil water, soil nutrition, and sunlight. Also, a price premium may be awarded to coffee growers whose production practices align with shade-grown certification programs. We propose a bioeconomic model that integrates an ecological model capturing the effect of shading trees on the CLR temperature and humidity-dependent infestation dynamics, crop growth, and timber production, with a farmer profit-maximization model of optimal shading selection in the presence of CLR infestation. Using agronomic, economic, and climatic data from the Coffee Triangle region in Colombia, our simulations indicate that the farm net present values (NPV) over 25 years are higher in a shade-grown coffee (SGC) system than a sun-grown coffee system at the presence of CLR. The optimal shade cover is 26% under the baseline scenario. The value of disease regulation provided by shade trees is $22,440 in present value terms for a half-hectare, over 25 years, or a 12% improvement relative to the sun-grown system. In the presence of 8% and 16% price premiums the NPVs increase by 23% and 35, but the optimal shade level remains at 26%. Under the scenario of expected doubling of El Niño cycle duration and no price premium, the optimal shade level decreases by 1 percentage point. Notably, shade-grown NPV falls below the sun-grown system under the climate change scenario indicating that farmers might not find it economically feasible to transition from sun-grown to shade-grown coffee if El Niño cycle durations double unless they are paid large price premiums.Keywords: Bioeconomic Models, Cellular Automata, Colombia, Disease Control, Coffee Leaf Rust Disease, Ecosystem Services, Spatial Dynamic Processes. JEL Codes: C63, Q54, Q57.