PS 43-180 - Short-term litterfall production with climatic factors in Nanjenshan tropical forest, Taiwan

Abstract: Litterfall is a crucial carbon pool that influences the soil nutrient content and regulates the carbon cycle of forest ecosystems, especially in the context of global climate change. Nanjenshan, a tropical forest located in the southernmost of Taiwan, is characterized by highly heterogeneous environmental conditions, which are frequently disrupted by tropical cyclones in summer and northeast monsoon winds in the winter. To understand how short-term litterfall changes over time, we collected and weighed litterfall on a monthly basis in the Nanjenshan forest from October 2012 to September 2020, while also recording monthly temperature, precipitation, and wind speed from the nearest climate station. Using regression analysis, we investigated the relationship between litterfall production and monthly climate factors.

Our results show that the mean total annual litterfall was 195.84 Mg ha^-1, with a range of 121.37 to 336.73 Mg ha^-1. The monthly litterfall production varied significantly throughout the study period. Specifically, we observed two seasonal peaks in litterfall production: summer and spring. The summer peak occurred between August and September and had the highest mean production, while the spring peak occurred from March to April. Precipitation, maximum temperature, and maximum wind speed were the main factors affecting litterfall accumulation in the tropical forest. Tropical cyclones brought strong winds and high precipitation, resulting in high litterfall quantities during the summer peak, while the warm temperature and humid environment during the bud burst season led to old leaves falling in spring.

Overall, our research highlights the seasonal patterns of litterfall in the Nanjenshan tropical forest, which are driven by specific climate factors and physiological mechanisms in corresponding seasons. Our findings have important implications for understanding the impacts of climate change on forest ecosystems, particularly in tropical forest.