Tropical tree simulation with a process-based, daily timestep simulation model (ALMANAC): Description of model adaptation and examples with coffee and cocoa simulations

Authors: Kiniry, James; FERNANDES, J - Agronomic Institute Of Paraná (IAPAR); AZIZ, FATI - Texas A&M University; JACOT, JACQUELINE - Oak Ridge National Laboratory; Williams, Amber; MEKI, MANYOWA - Texas Agrilife Research; OSORIO, JAVIER - Texas Agrilife Research; BAEZ-GONZALEZ, ALMA - Instituto Nacional De Investigaciones Forestales Y Agropecuarias (INIFAP); JOHNSON, MARI-VAUGHN - University Of Hawaii

Submitted to: Agronomy
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/15/2023
Publication Date: N/A
Citation: N/A

Interpretive Summary: Coffee and cocoa are important cash crops grown in the tropics but traded globally. This study was conducted to apply a simulation model (ALMANAC) to these crops for the first time, and to test its ability to simulate them under both with and without overstory trees and with varying rainfall. For these simulations, we simulated coffee in Kauai, Hawaii, USA and cocoa in Sefwi Bekwai, Ghana. A generic tropical overstory tree was created for agroforestry simulations. For both crops, ALMANAC realistically simulated yields when compared to collected yield data. On Kauai, the mean simulated yield was 2% different from the mean measured yield and all three years the simulated values were within 10% of the measured values. For cocoa, the mean simulated yield was 3% different from the mean measured yield and the simulated yield was within 10% of measured yields for all four available years. When rainfall patterns were altered, Ghana, the wetter site showed lower percent changes in yield than the drier site in Hawaii. When an agroforestry-style management was simulated, a low leaf area cover of the overstory showed positive or no effect on yields, but when LAI climbed too high the simulation was able to show the detrimental effect this competition had on crop yields. These simulation results are supported by other literature documenting the effects of agroforestry on tropical crops. This research has applied ALMANAC to new crops and tested its ability to predict the outcomes of different managements and environmental conditions. The results show promise for ALMANAC’s applicability to these scenarios as well as its potential to be further tested and utilized in new circumstances.

Technical Abstract: Coffee (Coffea species) and Cocoa (Theobroma cacao) are important cash crops grown in the tropics but traded globally. This study was conducted to apply the ALMANAC model to these crops for the first time, and to test its ability to simulate them under agroforestry management schemes and varying precipitation amounts. To create this simulation, coffee was grown on a site in Kauai, Hawaii, USA and cocoa was grown on a site in Sefwi Bekwai, Ghana. A stand-in for a tropical overstory tree was created for agroforestry simulations using altered parameters for carob. For both crops, ALMANAC was able to realistically simulate yields when compared to collected total yield data. On Kauai, the mean simulated yield was 2% different from the mean measured yield and all three years the simulated values were within 10% of the measured values. For cocoa, the mean simulated yield was 3% different from the mean measured yield and the simulated yield was within 10% of measured yields for all four available years. When precipitation patterns were al-tered, Ghana, the wetter site showed lower percent changes in yield than the drier site in Hawaii. When an agroforestry-style management was simulated, a low Leaf Area Index (LAI) of the overstory showed positive or no effect on yields, but when LAI climbed too high the simulation was able to show the detrimental effect this competition had on crop yields. These simulation results are supported by other literature documenting the effects of agroforestry on tropical crops. This research has applied ALMANAC to new crops and tested its ability to predict the outcomes of different managements and environmental conditions. The results show promise for ALMANAC’s applicability to these scenarios as well as its potential to be further tested and utilized in new circumstances.