Understanding the process of litterfall production is crucial for sustainable development of plantations. However, the underlying dynamics of litterfall and its nutrient return in plantation agroforestry systems remain unclear. In this study, we investigated litterfall, including leaves, branches, flowers, and fruits, in three patterns: Hevea monoculture system (RM), Hevea–Michelia intercropping system (RAS1), and Hevea–Mytilaria intercropping system (RAS2) in Hainan Island, China. Our findings indicate that total litterfall was significantly higher in RAS1 (27,309 kg ha−1) and RAS2 (34,477 kg ha−1) than in RM (22,364 kg ha−1) and was predominantly composed of leaf litterfall in all three patterns, followed by branches, flowers, and fruits. The seasonal dynamics litterfall production of RM, RAS1, and RAS2 showed characteristic patterns. Litterfall nutrients exhibited peak and sub-peak monthly dynamics, peaking from February to March, during the dry season. Total nitrogen (TN), total phosphorus (TP), and total potassium (TK) content of annual litterfall in RAS1 significantly increased by 120 kg ha−1, 30 kg ha−1, and 139 kg ha−1, respectively, compared to those in RM, with percentage increases of 67.88%, 122.79% and 96.27%, respectively. Similarly, TN, TP, and TK content of annual litterfall in RAS2 significantly increased by 185 kg ha−1, 35 kg ha−1, and 170 kg ha−1, respectively, with percentage increases of 103.70%, 159.15% and 139.46%, respectively, for the abovementioned in RM. Litterfall showed a strong correlation with monthly average temperature, monthly minimum temperature, and monthly average wind speed, contributing 80.5%, 75.5%, 69.8%, and 69.6% to the total litterfall and its components, respectively. Further analysis indicated that monthly average temperature, monthly minimum temperature, and monthly average wind speed contributed 73.9%, 43.0%, and 66.6%, respectively, to TN, TP, and TK content of the annual litterfall, highlighting the significant influence of temperature and wind speed. These findings enhance our understanding of carbon and nutrient cycling and contribute to the sustainable management of tropical plantation ecosystems.
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