Seasonal and annual dynamics of litterfall

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.