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Precipitation influences on the net primary productivity of a tropical seasonal rainforest in Southwest China: A 9-year case study

Authors :
Wenfu Zhang
Min Cao
Ewuketu Linger
J. Aaron Hogan
Yue-Hua Hu
Xiaofei Yang
Source :
Forest Ecology and Management. 467:118153
Publication Year :
2020
Publisher :
Elsevier BV, 2020.

Abstract

The net primary productivity (NPP) of tropical forests is a key part of the global carbon cycle. Numerous studies have estimated tropical forest NPP, yet most of them focus on how annual NPP dynamics vary over several years. Little is known about how NPP responds to long-term climatic variation at the monthly or seasonal scales. We estimated NPP at three-month intervals from 2009 to 2017 for a tropical seasonal rainforest in Xishuangbanna, Southwest China using data from >2000 dendrometer bands and litter fall traps within a 20-ha permanent forest dynamics plot. We asked which climatic factor has the greatest effect on forest NPP at the sub annual scale, and how the relationships vary with seasonality. Calculations showed that NPP ranged from 12 to 20 t ha−1 yr−1, and that forest productivity showed a slight, but insignificant increase from 2009 to 2017. NPP was significantly higher in the wet season than that in the dry season and was significantly related to precipitation only when all data were concerned. During the dry season, precipitation had a significant positive influence on NPP, but no effect during the wet season. We further identified that there was a threshold effect of precipitation on NPP. Specifically, productivity increased more rapidly when monthly precipitation below 229 mm. In summary, we conclude that periods of low rainfall strongly regulate the productivity in this tropical seasonal rainforest which could guide the management design of water use efficiency in tree based land-use system, like agroforestry ecosystems.

Details

ISSN :
03781127
Volume :
467
Database :
OpenAIRE
Journal :
Forest Ecology and Management
Accession number :
edsair.doi...........352b6999f028dc491eeb147df2298c8f
Full Text :
https://doi.org/10.1016/j.foreco.2020.118153