Temperature and Precipitation Diversely Control Seasonal and Annual Dynamics of Litterfall in a Temperate Mixed Mature Forest, Revealed by Long‐Term Data Analysis. Issue 7 (8th July 2021)

• Record Type: Journal Article
• Authors: Wang, C. G.; Zheng, X. B.; Wang, A. Z.; Dai, G. H.; Zhu, B. K.; Zhao, Y. M.; Dong, S. J.; Zu, W. Z.; Wang, W.; Zheng, Y. G.; Li, J. G.; Li, M.‐H.
• Is Part Of: Journal of geophysical research. Volume 126:Issue 7(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-07-08
• Subjects: Changbai Mountain -- leaf -- long‐term -- month -- pattern -- reproductive litterfall; Geobiology -- Periodicals; Biogeochemistry -- Periodicals; Biotic communities -- Periodicals; Geophysics -- Periodicals; 577.14
• DOI: 10.1029/2020JG006204
• Languages: English
• ISSNs: 2169-8953

Abstract

Abstract: Litterfall is a good indicator of overall forest functions in forest ecosystems. Globally, forest litterfall has been extensively investigated, however, there is a lack of long‐term data analysis to show the various litterfall components in relation to environmental factors on the monthly and yearly scales. Here, monthly (May–October) and annual (1981–2018) litterfall including leaves, twigs, bark, reproductive, and miscellaneous fractions were collected 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 the internal/external drivers. We observed that 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 to 2018. The other litterfall fractions showed distinct monthly and yearly fluctuations across the 30 years. 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. Our study, using a unique dataset of detailed long‐term litterfall dynamics, has potentially major significance for enhancing our understanding of the role of climatic factors controlling forest litterfall amount and seasonality in temperate mixed mature forests. This insight is of paramount importance for modeling and estimating soil carbon sequestration and nutrient cycling of temperate forests under climate change. Plain Language Summary: Forest litterfall is very important for nutrient cycling in forest ecosystems. Many researchers have studied forest litterfall, but still, there is an obvious lack of long‐term data analysis to show the relationships between forest litterfall and environmental factors. In this study, we analyzed the monthly and annual litterfalls of various components (leaf, reproductive, twig, bark, and miscellaneous litterfall) collected over 30 years in a mixed broad‐leaved Pinus koraiensis old‐growth forest on Changbai Mountain in northeastern China, in relation to climatic factors. We found that the highest monthly values of both leaf and total litterfall occurred during September‐October, and the annual litterfall of all components had an increasing trend from 1981 to 2018. The monthly litterfall was strongly influenced by the mean monthly evapotranspiration and temperature (minimum and maximum). The annual litterfall was mainly influenced by the mean annual precipitation, mean monthly precipitation, and temperature in May and October. These long‐term data based findings have important implications for better understanding the role of climatic factors on forest litterfall dynamics under climate change. Key Points: Leaf and total litterfall exhibited a strong and similar seasonal pattern There was an "S‐shaped" increasing pattern in the annual litterfall Contrasting climatic factors controlled seasonal and annual litterfall dynamics