Rahmat Pramulya, Rahmat Asy'Ari, Nihawa Hajar Pudjawati, Abd Malik A Madinu, Azelia Dwi Rahmawati, Fachruddin Fachruddin, Muhammad Reza Aulia, Dahlan Dahlan, Tarmizi Tarmizi, Fakhruddin Fakhruddin, Elida Novita, Adi Sutrisno, Devi Maulida Rahmah, Moh Zulfajrin, Heru Bagus Pulunggono, Fitria Yuliasmara, Rika Ratna Sari, Danny Dwi Saputra, Yudi Setiawan
Gayo coffee based on tropical agroforestry systems in Aceh plays an ecological role in mitigating climate change and a socio-economic role as a social livelihood in Indonesia. Ecologically, coffee agroforestry systems can increase soil carbon stocks through complex vegetation that produces litter as a source of nutrients. However, studies on measuring the contribution of vegetation to soil carbon dynamics in agroforestry lands using advanced machine learning-based statistical models in Indonesia are still very rare. Therefore, this study involved 18 complex vegetation variables to prove their contribution to soil organic carbon (SOC) dynamics using machine learning-based predictions with the random forest (RF) algorithm and hyperparameter tuning settings. The SOC available in the study area reached 173.46 ± 60.34 Mg ha-1, with 9.20 % ± 3.87 % organic C, in agroforestry systems characterized by vegetation density of 1752.94 ± 459.20 trees ha-1 (range: 850–2850 trees ha-1), and consisted of 11 overstory species. Based on two RF model tests (rf and ranger model), SOC dynamics were influenced by vegetation by 95 % (R-squared) with an error rate of 0.05 (RMSE) and 0.04 (MAE). The contribution of vegetation focuses on the variable of agroforestry richness as the most important factor in predicting SOC, even though the species Leucaena leucocephala dominates around 88 % of the species composition. These results recommend that increasing agroforestry species diversity is key to increasing SOC in coffee agroforestry. This information is expected to strengthen the implementation of SFA policies and enhance the sustainability of climate change mitigation-based social livelihoods in tropical Indonesia. © 2025
Faculty of Agriculture, University of Teuku Umar, West Aceh Regency, Aceh, 23681, Indonesia; Low Carbon Development Research Center (P3RK), University of Teuku Umar, West Aceh Regency, Aceh, 23681, Indonesia; Community of Climate Resilient of Nusantara Coffee (CiCoFest Coffee Indonesia), Jember, East Java, 68121, Indonesia; SSRS Gayo Leuser Highland Ecosystem Research Facility, SSRS Institute Indonesia, Central Aceh Regency, Aceh, Indonesia; SSRS Tropical Agroforestry Program, SSRS Institute Indonesia, Bogor Regency, Indonesia; Pulih-Indonesia, Sustain Group Indonesia, Bogor Regency, Indonesia; SSRS Indonesia Tropical Ecological Observatory, SSRS Institute Indonesia, Bogor Regency, Indonesia; Traceability and Sustainability System for Indonesian Agricultural Commodities (Calgris Indonesia), Sustain Group Indonesia, Bogor, Indonesia; Department of Civil Engineering, University of Teuku Umar, West Aceh Regency, Aceh, 23681, Indonesia; Department of Forestry, Syiah Kuala University, Aceh, Indonesia; Redelong Institute, Bener Meriah Regency, Aceh, Indonesia; Department of Agricultural Engineering, University of Jember, Jember, East Java, 68121, Indonesia; Department of Agribusiness, Faculty of Agriculture, BorneoTarakan University, Tarakan, 77124, Indonesia; Department of Agroindustrial Technology, Faculty of Agriculture Engineering, University of Padjadjaran, Sumedang, Indonesia; Computational Soil Science Research Group, Bogor, Indonesia; Department of Soil Science and Land Resources, Faculty of Agriculture, Bogor Agricultural University (IPB), Bogor, Indonesia; Indonesia Coffee and Cocoa Research Institute, PT Riset Perkebunan Nusantara, Jember, Indonesia; Research group of Tropical Agroforestry, Faculty of Agriculture, University of Brawijaya, Malang, Indonesia; Center for Environmental Research (PPLH), Bogor Agricultural University (IPB), Bogor, Indonesia
