13:45 〜 14:00
[ACG39-01] Influence of disturbances on transpiration and evaporation in tropical peat swamp forest
キーワード：排水、渦相関、火災、地下水位、ヘイズ
Tropical peat swamp forests are widely distributed throughout Southeast Asia and are known as huge carbon reservoirs. In addition, they play a major role in the water cycle on both local and global scales due to their humid pedospheric and atmospheric environments. Most of the water exchange with the atmosphere is driven by precipitation and evapotranspiration (ET), and the eddy covariance method is widely used to evaluate ET. The eddy covariance method has the feature that it can continuously measure the latent heat flux (or ET) that changes every moment, but it cannot directly measure evaporation (E) and transpiration (T) separately. Generally, E is determined by physical environmental factors such as soil surface moisture and atmospheric dryness, while T is regulated by physiological factors, stomatal behavior which is controlled by leaf water status and wind speed near the leaf surface. Thus, the response to environmental changes is different between E and T. Therefore, partitioning ET into E and T is very useful for evaluating and predicting the water cycle in response to environmental changes caused by anthropogenic and natural disturbances.
Various methods have been proposed for the evaluation of E and T (Stoy et al., 2019). Among them, using turbulent flux data and meteorological data have the advantage of being able to evaluate E and T over a long period of time under varying environmental conditions, ensuring spatial representativeness. In this study, three models with turbulent flux data and meteorological data were used to evaluate the influence of fire and drainage disturbances on E and T in three peat swamp forest sites with different degrees of disturbance in Central Kalimantan, Indonesia.
The three models are: assuming constant water use efficiency under negligible E contribution (Zhou et al., 2016, Model 1), assuming a linear relationship between T and gross primary production (GPP, Scott and Biederman, 2017, Model 2), and using the conductance of E and T (Li et al, 2019, Model 3). In the interannual variation in monthly T, Model 1 showed that T occasionally exceeded ET, especially under waterlogged conditions due to La Niña. This may be due to the lack of sufficient data under negligible E. Model 2 showed monotonous seasonal variation in T regardless of fire. This would be because suitable regression between T and GPP was not performed due to small variability in ET and GPP in each season. In other words, the variability of T is mostly determined by the slope of the regression line, i.e., T/GPP, which is extremely overestimated or underestimated. Meanwhile, Model 3 showed possible T values. Model 3 showed that T increased with the recovery of vegetation after the fire, T decreased with the decrease of groundwater level due to ditch excavation, and T decreased in the environment where the photosynthetically active radiation is attenuated due to the haze caused by the fire. Since these methods do not directly measure E or T, further analysis will be conducted to investigate the validity of these methods.
References:
Li, X., Gentine, P., Lin, C., Zhou, S., Sun, Z., Zheng, Y., ... & Zheng, C. (2019). A simple and objective method to partition evapotranspiration into transpiration and evaporation at eddy-covariance sites. Agricultural and Forest Meteorology, 265, 171-182.
Scott, R. L., & Biederman, J. A. (2017). Partitioning evapotranspiration using long-term carbon dioxide and water vapor fluxes. Geophysical Research Letters, 44(13), 6833-6840.
Stoy, P. C., El-Madany, T. S., Fisher, J. B., Gentine, P., Gerken, T., Good, S. P., ... & Wolf, S. (2019). Reviews and syntheses: Turning the challenges of partitioning ecosystem evaporation and transpiration into opportunities. Biogeosciences, 16(19), 3747-3775.
Zhou, S., Yu, B., Zhang, Y., Huang, Y., & Wang, G. (2016). Partitioning evapotranspiration based on the concept of underlying water use efficiency. Water Resources Research, 52(2), 1160-1175.
Various methods have been proposed for the evaluation of E and T (Stoy et al., 2019). Among them, using turbulent flux data and meteorological data have the advantage of being able to evaluate E and T over a long period of time under varying environmental conditions, ensuring spatial representativeness. In this study, three models with turbulent flux data and meteorological data were used to evaluate the influence of fire and drainage disturbances on E and T in three peat swamp forest sites with different degrees of disturbance in Central Kalimantan, Indonesia.
The three models are: assuming constant water use efficiency under negligible E contribution (Zhou et al., 2016, Model 1), assuming a linear relationship between T and gross primary production (GPP, Scott and Biederman, 2017, Model 2), and using the conductance of E and T (Li et al, 2019, Model 3). In the interannual variation in monthly T, Model 1 showed that T occasionally exceeded ET, especially under waterlogged conditions due to La Niña. This may be due to the lack of sufficient data under negligible E. Model 2 showed monotonous seasonal variation in T regardless of fire. This would be because suitable regression between T and GPP was not performed due to small variability in ET and GPP in each season. In other words, the variability of T is mostly determined by the slope of the regression line, i.e., T/GPP, which is extremely overestimated or underestimated. Meanwhile, Model 3 showed possible T values. Model 3 showed that T increased with the recovery of vegetation after the fire, T decreased with the decrease of groundwater level due to ditch excavation, and T decreased in the environment where the photosynthetically active radiation is attenuated due to the haze caused by the fire. Since these methods do not directly measure E or T, further analysis will be conducted to investigate the validity of these methods.
References:
Li, X., Gentine, P., Lin, C., Zhou, S., Sun, Z., Zheng, Y., ... & Zheng, C. (2019). A simple and objective method to partition evapotranspiration into transpiration and evaporation at eddy-covariance sites. Agricultural and Forest Meteorology, 265, 171-182.
Scott, R. L., & Biederman, J. A. (2017). Partitioning evapotranspiration using long-term carbon dioxide and water vapor fluxes. Geophysical Research Letters, 44(13), 6833-6840.
Stoy, P. C., El-Madany, T. S., Fisher, J. B., Gentine, P., Gerken, T., Good, S. P., ... & Wolf, S. (2019). Reviews and syntheses: Turning the challenges of partitioning ecosystem evaporation and transpiration into opportunities. Biogeosciences, 16(19), 3747-3775.
Zhou, S., Yu, B., Zhang, Y., Huang, Y., & Wang, G. (2016). Partitioning evapotranspiration based on the concept of underlying water use efficiency. Water Resources Research, 52(2), 1160-1175.