Ecological Niche Modeling and Sustainable Agroforestry: Climate Change Mitigation for Guatemalan Coffee

Authors' Affiliations

April Bledsoe, Department of Geosciences, College of Arts and Sciences, East Tennessee State University, Johnson City, TN. Danika Mosher, Department of Geosciences, College of Arts and Sciences, East Tennessee State University, Johnson City, TN. Mitchell Ogden, Department of Geosciences, College of Arts and Sciences, East Tennessee State University, Johnson City, TN. Monica Ayala, Department of Geosciences, College of Arts and Sciences, East Tennessee State University, Johnson City, TN. Andrew T. Joyner, Department of Geosciences, College of Arts and Sciences, East Tennessee State University, Johnson City, TN. Ingrid Luffman, Department of Geosciences, College of Arts and Sciences, East Tennessee State University, Johnson City, TN.

Location

Ballroom

Start Date

4-12-2019 9:00 AM

End Date

4-12-2019 2:30 PM

Poster Number

9

Faculty Sponsor’s Department

Geosciences

Name of Project's Faculty Sponsor

Dr. T. Andrew Joyner

Classification of First Author

Graduate Student-Master’s

Type

Poster: Competitive

Project's Category

Environmental Geography, Sustainable Agriculture, Climate Change

Abstract or Artist's Statement

Coffea arabica is a species with far-reaching impacts on the global economy. Nevertheless, climate-related challenges threaten the coffee industry at its source: its growing regions. The coffee industry is a significant economic driver in Guatemala, but farmers are increasingly reporting losses in crop yield and arable land due to climate-related challenges. Ecological niche modeling (ENM) can be employed to make predictions about the current and future suitability of regions for a species by identifying significant biotic or abiotic indicators. An ENM was used to project suitable land into the future using climate change projection models known as representative concentration pathways (RCPs), for the coffee plant and a number of other species. Due to the potential of shade trees to lessen heat stress on coffee plants, common shade trees for the region were modeled. Additionally, a fungus species responsible for detrimental coffee leaf rust was modeled. Results of these models indicated potential for substantial climate-related habitat losses for the coffee plant in the coming decades. Examination of model predictions allow for greater understanding of the climate-related variables affecting the ecology of the coffee plant, and the potential risks to the industry, in a changing climate. Additionally, ENM models for coffee rust and shade trees can help Guatemalan farmers make informed decisions about farm management.

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Apr 12th, 9:00 AM Apr 12th, 2:30 PM

Ecological Niche Modeling and Sustainable Agroforestry: Climate Change Mitigation for Guatemalan Coffee

Ballroom

Coffea arabica is a species with far-reaching impacts on the global economy. Nevertheless, climate-related challenges threaten the coffee industry at its source: its growing regions. The coffee industry is a significant economic driver in Guatemala, but farmers are increasingly reporting losses in crop yield and arable land due to climate-related challenges. Ecological niche modeling (ENM) can be employed to make predictions about the current and future suitability of regions for a species by identifying significant biotic or abiotic indicators. An ENM was used to project suitable land into the future using climate change projection models known as representative concentration pathways (RCPs), for the coffee plant and a number of other species. Due to the potential of shade trees to lessen heat stress on coffee plants, common shade trees for the region were modeled. Additionally, a fungus species responsible for detrimental coffee leaf rust was modeled. Results of these models indicated potential for substantial climate-related habitat losses for the coffee plant in the coming decades. Examination of model predictions allow for greater understanding of the climate-related variables affecting the ecology of the coffee plant, and the potential risks to the industry, in a changing climate. Additionally, ENM models for coffee rust and shade trees can help Guatemalan farmers make informed decisions about farm management.