Abstract
The Central Highlands of Vietnam is the biggest Robusta coffee (Coffea
canephora Pierre ex A.Froehner) growing region in the world. This study
aims to identify the most important climatic variables that determine
the current distribution of coffee in the Central Highlands and build a
“coffee suitability” model to assess changes in this distribution due
to climate change scenarios. A suitability model based on neural
networks was trained on coffee occurrence data derived from national
statistics on coffee-growing areas. Bias-corrected regional climate
models were used for two climate change scenarios (RCP8.5 and RCP2.6) to
assess changes in suitability for three future time periods (i.e.,
2038-2048, 2059-2069, 2060-2070) relative to the 2009-2019 baseline.
Average expected losses in suitable areas were 62% and 27% for RCP8.5
and RCP2.6, respectively. The loss in suitability due to RCP8.5 is
particularly pronounced after 2060. Increasing mean minimum temperature
during harvest (October-November) and growing season (March-September)
and decreasing precipitation during late growing season (July-September)
mainly determined the loss in suitable areas. If the policy commitments
made at the Paris agreement are met, the loss in coffee suitability
could potentially be compensated by climate change adaptation measures
such as making use of shade trees and adapted clones.