The expansion of moso bamboo (Phyllostachys edulis) may potentially impact regional isoprene emissions. Modeling based on field measurements is an effective approach for assessing the potential impact of the moso bamboo expansion. The G93 algorithm is one of the most widely used models, however no studies have tested the applicability of the algorithm for moso bamboo isoprene emission. This study was undertaken to establish a model for reproducing moso bamboo isoprene emission fluxes. To this aim, this study examined 1) the isoprene emission ability of moso bamboo, and 2) its responses to environmental factors such as leaf temperature and light. We also tested 3) the reproducibility of the G93 algorithm for moso bamboo isoprene emission fluxes. This study used a chamber method with a modified photosynthesis system and carbon absorbents to quantify isoprene emitted from bamboo leaves in central Taiwan under the humid subtropical climate. First, we screened isoprene emission from 12 bamboo species, and the results confirmed that moso bamboo exhibited significant isoprene emission potential. Second, we measured isoprene emission fluxes from moso bamboo leaves with light controls every month from summer to spring. The isoprene emission fluxes increased with photosynthetic photon flux density (PPFD); under sufficient PPFD conditions, the seasonal changes in the isoprene emission fluxes were regulated by leaf temperature, and low isoprene emission fluxes were found in low leaf temperature conditions. Thirdly, overestimations were observed in the G93 algorithm with the original parameters in periods with leaf temperatures <23 °C. Using the G93 algorithm with site-specific parameters could improve the overestimation in the low-temperature period. This study suggests the necessity of parameterization in the G93 algorithm to reproduce the suppression of isoprene emission fluxes from moso bamboo leaves in the low-temperature period.
All Science Journal Classification (ASJC) codes
- Environmental Science(all)
- Atmospheric Science