Temperature and Precipitation Diversely Control Seasonal and Annual Dynamics of Litterfall in a Temperate Mixed Mature Forest, Revealed by Long?Term Data Analysis

Litterfall is a good indicator of overall forest functions in ecosystems. Globally, litterfall has been extensively investigated, however, there lack long-term data analysis to show the various components relation environmental factors on monthly and yearly scales. Here, (May–October) annual (1981–2018) including leaves, twigs, bark, reproductive, miscellaneous fractions were collected mixed mature Pinus koraiensis Changbai Mountain Northeast, China, across 30 years. Based these data, we analyzed seasonal variations different internal/external drivers. We observed that both leaf total exhibited strong, similar pattern, with highest levels between September October, had an “S-shaped” increasing pattern from 1981 2018. The other showed distinct fluctuations Mean evapotranspiration temperature (minimum maximum) best predictors for litterfall. By contrast, models predicted production included mean precipitation May October. Our study, using unique dataset detailed dynamics, potentially major significance enhancing our understanding role climatic controlling amount seasonality temperate forests. This insight paramount importance modeling estimating soil carbon sequestration nutrient cycling forests under climate change.