Ontogenetic changes in water-use efficiency (δ13C) and leaf traits differ among tree species growing in a semiarid region of the Loess Plateau, China

The uncertainty of carbon fluxes of the terrestrial ecosystem is the highest among all flux components, calling for more accurate and efficient means to monitor land sinks. Gross primary productivity (GPP) is a key index to estimate the terrestrial ecosystem carbon flux, which describes the total amount of organic carbon fixed by green plants through photosynthesis. In recent years, the solar-induced chlorophyll fluorescence (SIF), which is a probe for vegetation photosynthesis and can quickly reflect the state of vegetation growth, emerges as a novel and promising proxy to estimate GPP. The launch of Orbiting Carbon Observatory 2 (OCO-2) further makes it possible to estimate GPP at a finer spatial resolution compared with Greenhouse Gases Observing Satellite (GOSAT), Global Ozone Monitoring Experiment-2 (GOME-2) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). However, whether the relationship between GPP and SIF is linear or non-linear has always been controversial. In this research, we proposed a new model to estimate GPP using SIF and the atmospheric CO2 concentration from OCO-2 as critical driven factors simultaneously (SIF-CO2-GPP model). Evidences from all sites show that the introduction of the atmospheric CO2 concentration improves accuracies of estimated GPP. Compared with the SIF-CO2-GPP linear model, we found the SIF-GPP model overestimated GPP in summer and autumn but underestimated it in spring and winter. A series of simulation experiments based on SCOPE (Soil-Canopy Observation of Photosynthesis and Energy) was carried out to figure out the possible mechanism of improved estimates of GPP due to the introduction of atmospheric CO2 concentrations. These experiments also demonstrate that there could be a non-linear relationship between SIF and GPP at half an hour timescale. Moreover, such relationships vary with CO2 concentration. As OCO-2 is capable of providing SIF and XCO2 products with identical spatial and temporal scales, the SIF-CO2-GPP linear model would be implemented conveniently to monitor GPP using remotely sensed data. With the help of OCO-3 and its successors, the proposed SIF-CO2-GPP linear model would play a significant role in monitoring GPP accurately in large geographical extents.

https://www.mdpi.com/2072-4292/12/9/1377/pdf

CO2 Concentration, A Critical Factor Influencing the Relationship between Solar-induced Chlorophyll Fluorescence and Gross Primary Productivity

Physiological indices of six green plants in large scale Pig Farm of Fuxin city were tested by LI-6400 photosynthesis testing system. Furthermore, the water releasing, heat-absorbing and temperature-declining potential of these plants were studied. The results indicated that diurnal change of transpiration rate mostly presents the double-peak curve in May and in July, and the peak value appears in 9:00 and 13:00. It appears single-peak curve in September, and the peak value appears about 11:00. The water-releasing, heat absorbing and temperature-declining potential of six green trees was stronger in June, July and August, and took second place in May, and was lowest in September. The water releasing, heat-absorbing and temperature-declining potential of Populus alba berolinensis was the highest, and followed by Pyrus ussuriensis Miaxim. f., Pyrus ussuriensis Maxim., Populus simonii Carr and Passer montanus saturatus Stejneger, and those of Syringa oblata Lindl were the lowest. The amount of water-releasing of four arbor trees exceeded 1500 g/m2/d, which indicated that the water-releasing, heat absorbing and temperature-declining potential of arbor trees were better than those of shrub trees, and were suitable green trees in large-scale pig farm.

Study on Water-Releasing, Heat-absorbing and Temperature-declining Potential of Six Green Plants in Large-Scale Pig Farm

By using LI-6400 infrared gas analyzer, this paper studied the diurnal and seasonal variations of the photosynthetic rate of main arbor species (Populus alba x P berolinensis, Salix matsudana, Ulmus pumila, Robinia pseudoacacia and Prunus davidiana) in Shenyang urban area The correlations between net photosynthetic rate and environmental factors (photosynthetic active radiation, temperature, and stomatal conductance) were assessed by multivariate regression analysis, and related equations were constructed The results showed that for test arbor species, the diurnal variation of photosynthetic rate mainly presented a single peak curve, and the seasonal variation was in the order of summer > autumn > spring The major factors affecting the photosynthetic rate were photosynthetic active radiation, stomatal conductance, and intercellular CO2 concentration

Photosynthetic characteristics of five arbor species in Shenyang urban area

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Photosynthetic characteristics of five arbor species in Shenyang urban area