BMC plant biology · 2025
Estimating CO2 response in a mixed broadleaf forest using the dynamic assimilation technique.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Hu Huiting, Jiang Wei, Fan Xiuhua
Аннотация
BACKGROUND: Estimating the CO2 response of forest trees is of great significance in plant photosynthesis research. CO2 response measurement is traditionally employed under steady state conditions. With the development of open-path gas exchange systems, the Dynamic Assimilation Technique (DAT), allows measurement under non-steady state conditions. This greatly improves the efficiency and data density of CO2 response measurement. This study aims to assess the accuracy and effectiveness of different models in fitting DAT data, addressing the current gap in verification of model performance.
RESULTS: This research was conducted for three common broadleaf tree species (Ulmus macrocarpa, Fraxinus mandshurica, and Tilia amurensis) in North Eastern China. Among the three species, Fraxinus mandshurica is the most adapted to high CO2 concentration conditions. Four models were compared, the rectangular hyperbola (RH) model, the Michaelis-Menten (MM) model, the modified rectangular hyperbola (MRH) model and a non-rectangular hyperbola (NRH) model.
CONCLUSIONS: Considering the model parsimony and parameter accuracy, the NRH model emerged as the best choice (R2 = 0.9966, RMSE = 0.1862, AIC=-199.86). This study provides a reference for the further application of DAT in the field of photosynthesis.
RESULTS: This research was conducted for three common broadleaf tree species (Ulmus macrocarpa, Fraxinus mandshurica, and Tilia amurensis) in North Eastern China. Among the three species, Fraxinus mandshurica is the most adapted to high CO2 concentration conditions. Four models were compared, the rectangular hyperbola (RH) model, the Michaelis-Menten (MM) model, the modified rectangular hyperbola (MRH) model and a non-rectangular hyperbola (NRH) model.
CONCLUSIONS: Considering the model parsimony and parameter accuracy, the NRH model emerged as the best choice (R2 = 0.9966, RMSE = 0.1862, AIC=-199.86). This study provides a reference for the further application of DAT in the field of photosynthesis.