Combining NDVI, PRI and the quantum yield of solar-induced fluorescence improves estimations of carbon fluxes in deciduous and evergreen forests

Analysis of spatial and temporal changes in vegetation cover and its drivers in the Aksu River Basin, China

Exploring vegetation dynamics in arid areas and their responses to different natural and anthropogenic factors is critical for understanding ecosystems. Based on the monthly MOD13Q1 (250 m) remote sensing data from 2000 to 2019, this study analyzed spatio-temporal changes in vegetation cover in the Aksu River Basin and predicted future change trends using one-dimensional linear regression, the Mann-Kendall test, and the Hurst index. Quantitative assessment of the magnitude of anthropogenic and natural drivers was performed using the Geodetector model. Eleven natural and anthropogenic factors were quantified and analyzed within five time periods. The influence of the driving factors on the changes in the normalized difference vegetation index (NDVI) in each period was calculated and analyzed. Four main results were found. (1) The overall vegetation cover in the region significantly grew from 2000 to 2019. The vegetation cover changes were dominated by expected future improvements, with a Hurst index average of 0.45. (2) Land use type, soil moisture, surface temperature, and potential vapor dispersion were the main drivers of NDVI changes, with annual average q-values above 0.2. (3) The driving effect of two-factor interactions was significantly greater than that of single factors, especially land use type interacts with other factors to a greater extent on vegetation cover. (4) The magnitude of the interaction between soil moisture and potential vapor dispersion and the magnitude of the interaction between anthropogenic factors and other factors showed an obvious increasing trend. Current soil moisture and human activities had a positive influence on the growth of vegetation in the area. The findings of this study are important for ecological monitoring and security as well as land desertification control.

Estimation of photosynthetic dynamics in forests from daily measured fluorescence and PRI data with adjustment for canopy shadow fraction

We conducted year-long measurements of the photochemical reflectance index (PRI) and solar-induced fluorescence in the O2A oxygen band (SIFA) at a Norway spruce forest and a European beech forest to study relationships of these remote sensing variables to photosynthesis by trees in grown forest stands. Measured PRI and SIFA values were linked to changes in forest gross primary productivity (GPP) and light-use efficiency (LUE). Changes in the shadow fraction (αS) within tree crowns influenced PRI and fluorescence signals. In the spruce forest, the quantum yield of SIFA (FYSIFA) decreased around midday together with photosynthesis and GPP. Such decreases in FYSIFA were accompanied by an increase in the αS. In the beech forest, we detected an increase in FYSIFA together with a decrease in αS in the afternoon hours. The overall sensitivity of PRI to LUE was variable according to the season, presumably influenced by complex changes in photosynthetic pigments. PRI and FYSIFA showed weak correlations with canopy LUE; however, when considered together, the correlation was strengthened (R2 was 0.63 and 0.34 in spruce and beech forest, respectively). Our model predicting LUE dynamics includes a diurnal minimum of PRI and canopy αS to make allowances for seasonal changes in photosynthetic pigments and for diurnal variability of the shadow fraction in forests. The incorporation of these correcting factors allowed us to estimate LUE at R2 = 0.68 (spruce) and 0.53 (beech). The modeling equations appeared sensitive to the absorbed photosynthetically active radiation (APAR), but less sensitive to the GPP of these forests. Substituting pigments correction with introducing differential PRI (ΔPRI) into the model did not significantly improve the LUE estimation across the season. Our results show that the joint use of PRI and fluorescence improves LUE and GPP estimation accuracy in both daily and seasonal observations.

Remote Sensing of Instantaneous Drought Stress at Canopy Level Using Sun-Induced Chlorophyll Fluorescence and Canopy Reflectance

Climate change amplifies the intensity and occurrence of dry periods leading to drought stress in vegetation. For monitoring vegetation stresses, sun-induced chlorophyll fluorescence (SIF) observations are a potential game-changer, as the SIF emission is mechanistically coupled to photosynthetic activity. Yet, the benefit of SIF for drought stress monitoring is not yet understood. This paper analyses the impact of drought stress on canopy-scale SIF emission and surface reflectance over a lettuce and mustard stand with continuous field spectrometer measurements. Here, the SIF measurements are linked to the plant’s photosynthetic efficiency, whereas the surface reflectance can be used to monitor the canopy structure. The mustard canopy showed a reduction in the biochemical component of its SIF emission (the fluorescence emission efficiency at 760 nm—ϵ760) as a reaction to drought stress, whereas its structural component (the Fluorescence Correction Vegetation Index—FCVI) barely showed a reaction. The lettuce canopy showed both an increase in the variability of its surface reflectance at a sub-daily scale and a decrease in ϵ760 during a drought stress event. These reactions occurred simultaneously, suggesting that sun-induced chlorophyll fluorescence and reflectance-based indices sensitive to the canopy structure provide complementary information. The intensity of these reactions depend on both the soil water availability and the atmospheric water demand. This paper highlights the potential for SIF from the upcoming FLuorescence EXplorer (FLEX) satellite to provide a unique insight on the plant’s water status. At the same time, data on the canopy reflectance with a sub-daily temporal resolution are a promising additional stress indicator for certain species.