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Monitoring drought stress is crucial for estimating productivity and assessing the health status of forest ecosystems under global climate change. Solar-induced chlorophyll fluorescence (SIF) is mechanistically coupled to photosynthesis and has advantages over greenness-based vegetation indices in detecting drought. In recent years, SIF has commonly been used in monitoring drought stress in crop ecosystems. However, the response of tower-based SIF to drought stress in forest ecosystems remains unclear. In this study, we investigated the potential of tower-based SIF to monitor drought, which was quantified using the plant water stress index (PWSI) in a Chinese cork oak plantation. The results show the negative effect of drought on SIF, and afternoon depression of SIF emission under drought stress was observed. Canopy SIF (F) exhibited a nonlinear relationship with PWSI, while the quantum yield of SIF (ΦF) exhibited a significant linear relationship with PWSI at 687 nm and 760 nm (ΦF687: R2 = 0.90; ΦF760: R2 = 0.85). Incident radiation (PAR) and canopy structure affected the response of SIF to drought stress, with PAR as the main factor causing the nonlinear relationship between F and PWSI. Afternoon depression was described as the afternoon/morning ratio (AMR). AMRF and AMRΦF exhibited a negative linear response to PWSI. AMRF was less affected than F by PAR and canopy structures, and AMRΦF was more physiologically representative than ΦF. Moreover, AMRΦF was sensitive to VPD and REW, and it might be a good indicator of drought. Red SIF was more sensitive to drought than far-red SIF, as the R2 of PWSI with AMRΦF687 (R2 = 0.89) was higher than that with AMRΦF687 (R2 = 0.84). These results highlight the potential of tower-based SIF, especially red SIF, for drought monitoring in a plantation, and consideration of the physiological diurnal variation in SIF under drought stress is crucial for improving the accuracy of drought stress monitoring.

With the development of spectrum observation technology, solar-induced chlorophyll fluorescence (SIF)—an effective substitute for photosynthesis—has been widely used to monitor crop stress, vegetation phenology and ecosystem productivity. The relationship between fluorescence and photosynthesis is complicated because they are sensitive to environmental changes. Understanding the response of SIF to environmental factors is of great significance for clarifying the variation dynamic and relationship between SIF and photosynthesis under different conditions. In this study, the canopy SIF and the environmental factors of a Quercus variabilis BI. plantation were observed simultaneously, and the response of SIF to environmental factors at a daily scale and at a half-hour scale was analyzed. The results showed that SIF had obvious seasonal and diurnal dynamics and was mainly driven by photosynthetically active radiation (PAR). The influence of PAR, air temperature (Ta), vapor pressure deficit (VPD), soil moisture (SM) and wind speed (Ws) on SIF varied with the lapse of the growing season. After eliminating the covariant effect of PAR on the Ta and VPD during the whole growing season, the relationship between VPD and SIF was found to be negative, and the effect of Ta on SIF disappeared. This study enriched the ground observation dataset and provided support for understanding the variations in the relationship between SIF and photosynthesis under different conditions.

Light use efficiency (LUE) models have been widely used to estimate terrestrial gross primary production (GPP). However, the estimation of GPP still has large uncertainties owing to an insufficient understanding of the complex relationship between water availability and photosynthesis. The plant water stress index (PWSI), which is based on canopy temperature, is very sensitive to the plant stomatal opening and has been regarded as a good indicator for monitoring plant water status at the regional scale. In this study, we selected a cork oak plantation in northern China with an obvious seasonal drought as the research object. Using the ground-observed data, we evaluated the applicability of the LUE models with typical water stress scalars (MOD17, MODTEM, EC-LUE, ECM-LUE, SM-LUE, GLO-PEM, and Wang) in a GPP simulation of the cork oak plantation and explored whether the model’s accuracy can be improved by applying PWSI to modify the above models. The results showed that among the seven LUE models, the water stress scalar had a greater impact on the model’s performance than the temperature stress scalar. On sunny days, the daily GPP simulated by the seven LUE models was poorly matched with the measured GPP, and all models explained only 23–52% of the GPP variation in the cork oak plantation. The modified LUE models can significantly improve the prediction accuracy of the GPP and explain 49–65% of the variation in the daily GPP. On cloudy days, the performance of the modified LUE models did not improve, and the evaporative fraction was more suitable for defining the water stress scalar in the LUE models. The ECM-LUE and the modified GLO-PEM based on PWSI had optimal model structures for simulating the GPP of the cork oak plantation under cloudy and sunny days, respectively. This study provides a reference for the accurate prediction of GPP in terrestrial ecosystems in the future.

Canopy temperature (Tc) is used to characterize plant water physiology, and thermal infrared (TIR) remote sensing is a convenient technology for measuring Tc in forest ecosystems. However, the images produced through this method contain background pixels of forest gaps, thereby reducing the accuracy of Tc observations. Extracting Tc data from TIR images is of great significance for understanding changes in ecosystem water status. In this study, a temperature threshold method was developed to rapidly, accurately, and automatically extract forest canopy pixels for Tc data obtention. Specifically, this method takes the temperature corresponding to the point with a slope of 0.5 in the curve composed of the normalized average temperature and the normalized cumulative number of pixels as the segmentation threshold to separate the forest gap pixels from the forest canopy pixels in the TIR images and extract the separated forest canopy pixels based on the pixel coordinates for Tc data obtention. Taking the Tc values, measured using a thermocouple, as the standard, Tc extraction using the new temperature threshold method and traditional methods (the Otsu algorithm and direct extraction) was compared in cork oak plantations. The results showed that the temperature threshold method offered the highest extraction accuracy, followed by the direct extraction method and the Otsu algorithm. The temperature threshold method was determined to be the most suitable for extracting Tc data from the TIR images of cork oak plantations.

Solar-induced chlorophyll fluorescence (SIF) is a hopeful indicator, which along with remote sensing, is used to measure the photosynthetic efficiency and gross primary production (GPP) of vegetation in regional terrestrial ecosystems. Studies have found a significant linear correlation between SIF and GPP in a variety of ecosystems. However, this relationship has mainly been established using SIF and GPP data derived from satellite remote sensing and continuous ground-based observations, respectively, which are difficult to accurately match. To overcome this, some studies have begun to use tower-based automatic observation instruments to study the changes of near-surface SIF and GPP. This study conducts continuous simultaneous observation of SIF, carbon flux, and meteorological factors on the forest canopy of a cork oak plantation during the growing season to explore how meteorological factors impact on canopy SIF and its relationship with GPP. This research found that the canopy SIF has obvious diurnal and day-to-day variations during the growing season but overall is relatively stable. Furthermore, SIF is greatly affected by incident radiation in different weather conditions and can change daily. Meteorological factors have a major role in the relationship between SIF and GPP; overall, the relationship shows a significant linear regression on the 30 min scale, but weakens when aggregating to the diurnal scale. Photosynthetically active radiation (PAR) drives SIF on a daily basis and changes the relationship between SIF and GPP on a seasonal timescale. As PAR increases, the daily slopes of the linear regressions between SIF and GPP decrease. On the 30 min timescale, both SIF and GPP increase with PAR until it reaches 1250 μmol·m−2·s−1; subsequently, SIF continues to increase while GPP decreases and they show opposite trends. Soil moisture and vapor pressure deficit influence SIF and GPP, respectively. Our findings demonstrate that meteorological factors affect the relationship between SIF and GPP, thereby enhancing the understanding of the mechanistic link between chlorophyll fluorescence and photosynthesis.