Journal
JOURNAL OF PLANT RESEARCH
Volume 123, Issue 4, Pages 563-576Publisher
SPRINGER JAPAN KK
DOI: 10.1007/s10265-009-0270-4
Keywords
AsiaFlux Takayama site; Canopy and leaf photosynthesis; Deciduous broadleaf forest; Forest ecosystem carbon cycle; Phenology
Categories
Funding
- Ministry of Environment, Japan
- JSPS [18710006]
- JSPS-KOSEF-NSFC
- Grants-in-Aid for Scientific Research [22248017, 18710006] Funding Source: KAKEN
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Revealing the seasonal and interannual variations in forest canopy photosynthesis is a critical issue in understanding the ecological mechanisms underlying the dynamics of carbon dioxide exchange between the atmosphere and deciduous forests. This study examined the effects of temporal variations of canopy leaf area index (LAI) and leaf photosynthetic capacity [the maximum velocity of carboxylation (V (cmax))] on gross primary production (GPP) of a cool-temperate deciduous broadleaf forest for 5 years in Takayama AsiaFlux site, central Japan. We made two estimations to examine the effects of canopy properties on GPP; one is to incorporate the in situ observation of V (cmax) and LAI throughout the growing season, and another considers seasonality of LAI but constantly high V (cmax). The simulations indicated that variation in V (cmax) and LAI, especially in the leaf expansion period, had remarkable effects on GPP, and if V (cmax) was assumed constant GPP will be overestimated by 15%. Monthly examination of air temperature, radiation, LAI and GPP suggested that spring temperature could affect canopy phenology, and also that GPP in summer was determined mainly by incoming radiation. However, the consequences among these factors responsible for interannual changes of GPP are not straightforward since leaf expansion and senescence patterns and summer meteorological conditions influence GPP independently. This simulation based on in situ ecophysiological research suggests the importance of intensive consideration and understanding of the phenology of leaf photosynthetic capacity and LAI to analyze and predict carbon fixation in forest ecosystems.
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