Abstract
Forest vegetation is an essential source of negative air ion (NAI) and influencing factor of the process. A number of studies have focused on the temporal and spatial changes of NAI in different forest communities and their relationship with meteorological factors; however, there is no literature on the relationship between solar-induced chlorophyll fluorescence intensity (SIF) and NAI, and quantitative research on relationship between NAI and photosynthesis of forest vegetation is comparatively limited. In this study, we investigated the dynamic changes NAI, SIF, and meteorological parameters in canopy during the growing season by using a flux tower at the sites Xiaolangdi and Minquan in a warm-temperate monsoon climate zone from June to September of 2019 and 2020. Results showed that the canopy NAI, SIF, and photosynthetically active radiation (PAR) showed significant diurnal and seasonal dynamic change characteristics, and that the changes in the observed indicators at different times were significantly different. The seasonal change characteristics of canopy NAI and SIF were relatively similar, and canopy SIF could accurately capture the dynamic changes of NAI. Additionally, the NAI–SIF relationship was increasingly significant at higher PAR levels, and the coefficient of determination (R2) of the two sites reached 0.652 and 0.570. It showed that when vegetation photosynthesis was fully activated, the dynamic change process of the canopy NAI provided a more robust correlation and more accurate estimation in the vegetation's main growth stage, thus demonstrating the reliability of SIF as an indicator for tracking NAI seasonal changes. In the future, automatic, continuous SIF observations could provide reliable understanding of the photosynthetic characteristics of terrestrial ecosystems, thereby quantifying the contribution potential of forest to NAI application in ground-based optical measurement and airborne and satellite remote sensing. This provides a working foundation for direct assessment of spatial and temporal distribution patterns of global seasonal NAI.
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