Seasonal and annual dynamics of litterfall
Wang, Cunguo et al. (2021), Seasonal and annual dynamics of litterfall, Dryad, Dataset, https://doi.org/10.5061/dryad.gmsbcc2ng
Long-term data of litterfall can indicate overall forest functions in forest ecosystems. We collected monthly (May – October) and annual (1981 – 2018) litterfall including leaves, twigs, bark, reproductive and miscellaneous fractions in a mixed mature Pinus koraiensis forest on Changbai Mountain in Northeast, China, across 30 years. Based on these long-term litterfall data, we analyzed the seasonal and annual variations in different litterfall fractions and their relationships with climatic factors. Climate data were obtained from the meteorological observation field (738 m above sea level) of the Changbai Mountain forest ecosystems research station, Institute of Applied Ecology, Chinese of Academy of Sciences. Both the leaf and total litterfall exhibited a strong, similar seasonal pattern, with the highest levels between September and October, and the annual litterfall had an “S-shaped” increasing pattern from 1981 – 2018. Distinct monthly and yearly fluctuations for the other litterfall fractions across the 30 years were observed. Mean monthly evapotranspiration and temperature (minimum and maximum) were the best predictors for monthly litterfall. By contrast, the models that best predicted the annual litterfall production included mean annual precipitation, and mean monthly precipitation and temperature in May and October. This unique dataset of detailed long-term litterfall dynamics has potentially major significance for enhancing our understanding on the role of climatic factors controlling forest litterfall amount and seasonality in temperate mixed mature forests.