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All Journal Journal of Degraded and Mining Lands Management AGRIVITA, Journal of Agricultural Science
Fitra, Ahmad Ali Yuddin
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology

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Optimizing coffee yields in agroforestry systems using WaNuLCAS model: A case study in Malang, Indonesia Fitra, Ahmad Ali Yuddin; Oakley, Simon; Prayogo, Cahyo; Ratna Sari, Rika; Saputra, Danny Dwi; Ishaq, Rizqi Maulana; Suprayogo, Didik
Journal of Degraded and Mining Lands Management Vol. 11 No. 4 (2024)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2024.114.6337

Abstract

Agroforestry systems have significant potential for development in increasing coffee production in Indonesia. Besides providing economic benefits, agroforestry can also have ecological impacts, such as improving soil structure, reducing erosion, and other environmental services. There is a complex interaction between trees, soil, and crops in agroforestry systems, making modeling a valuable approach to unraveling these processes. We utilized the spatial and temporal explicit model WaNuLCAS to (i) evaluate the model's performance in depicting actual events (through coffee production and soil water content), (ii) assess the dynamic processes influencing coffee production and the environmental impact of management patterns, (iii) formulate and simulate optimal scenarios for coffee production optimization. Data from a one-year period involving five agroforestry management patterns for coffee-pine in UB Forest were used as input for the model. The model validation results showed satisfactory and acceptable outcomes for coffee production and groundwater dynamics. WaNuLCAS simulation results indicated that pruning and thinning management are crucial factors in increasing coffee production and are related to creating optimal conditions for coffee plants (light, humidity, and inter-plant competition). Additionally, fertilization management can be combined as a supporting factor to meet the nutritional needs of coffee plants. WaNuLCAS simulation results also suggested that pruning and thinning can improve soil physical properties, but thinning increases surface runoff within the system. This research provides insights into how modeling can be used as a decision-making tool.
Enhancing Coffee Productivity and Carbon Stock in Agroforestry Systems Using the WaNuLCAS Model under Climate Change Nurwarsito, Heru; Suprayogo, Didik; Prayogo, Cahyo; Fitra, Ahmad Ali Yuddin
AGRIVITA Journal of Agricultural Science Vol 47, No 3 (2025)
Publisher : Faculty of Agriculture University of Brawijaya in collaboration with PERAGI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17503/agrivita.v47i3.4935

Abstract

The coffee-pine agroforestry model, where coffee is grown under shade trees, provides environmental benefits such as carbon sequestration and soil health improvement. However, maintaining carbon stocks over time is challenging due to climate change, which alters water and nutrient availability. Using the WaNuLCAS model, this study assessed system optimization under various climate scenarios, focusing on coffee yield, carbon stock, and biomass balance. The model simulates water and nitrogen cycling as well as coffee–pine interactions. The results showed that an increase in rainy season enhanced coffee growth, while applying Best Management Practice (BMP) led to a 44.64% higher coffee yield and a 4.52% increase in biomass production compared with the control. Conversely, low coffee (LC) with poor management increased carbon stock by 6.91% and biomass by 26.74%, the largest differences observed between treatments. This highlights trade-offs in land use performance. Previous studies mainly emphasized agroforestry’s contributions to carbon sequestration, biodiversity, and timber, with limited quantification of trade-offs between yield, carbon, and biomass under varying rainfall. By integrating site-specific calibration of the WaNuLCAS model, this study offers a novel approach showing how contrasting strategies (BMP vs. LC) differently optimize productivity and ecological services, guiding climate-resilient coffee agroforestry.
Co-Authors Cahyo Prayogo, Cahyo Didik Suprayogo Heru Nurwarsito Ishaq, Rizqi Maulana Oakley, Simon RATNA SARI, RIKA Saputra, Danny Dwi