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Seasonal variation of light fraction organic matter in degraded red soil after vegetation restoration.

XIE Jin-sheng1; YANG Yu-sheng1; YANG Zhi-jie1; HUANG Shi-de2; CHEN Guang-shui1    

  1. 1Provincial Key Laboratory of Subtropical Resources and Environment, College of Geographical Science, Fujian Normal University, Fuzhou 350007, China; 2Fujian Academy of Forestry, Fuzhou 350002, China
  • Received:2007-06-08 Revised:1900-01-01 Online:2008-03-21 Published:2008-03-21

Abstract: This paper studied the seasonal variation of light fraction organic matter (LFOM) in the red soils of severely eroded bare land, and of the bare lands restored to Pinus massoniana forest land,Castanea mollissima plantation, and Paspalum notatum grassland in the Hetian Town of Changting County, Fujian Province, with secondary forest soil as the control. The results showed that in the surface soil of the bare land, LFOM content was between 0.05-0.14 g·kg-1 and with no significant seasonal variation, while in that of P. massoniana forest land, C. mollissima plantation and P. notatum grassland, LFOM content had a distinct seasonal variation, and was 58%-122% higher in spring, autumn, and winter than in summer. The C content and C/N ratio of the LFOM in the three restored lands were lower in summer than in other seasons, while the nitrogen content of the LFOM was in adverse, indicating that the high temperature and humidity in summer induced a rapid decomposition of soil LFOM. The LFOM in secondary forest soil had the similar variation trend to that in the three restored lands, but the variation range was significantly narrower. The seasonal dynamics of surface soil LFOM was affected not only by micro-climate but also by vegetation types, and the variation range was greater in P. notatum grassland than in forest lands. It was suggested that to enhance the observation precision of soil LFOM, repeated sampling or integrating the factors such as climate, vegetation type, and management measures should be taken to determine the appropriate sampling time.

Key words: Pinus tabuliformis plantation, regression modeling, aboveground biomass, leave-one-out cross validation, GF-2