Previous studies have suggested that solar‐induced chlorophyll fluorescence (SIF) is correlated with Gross Primary Production (GPP). However, it remains unclear to what extent this relationship is due to absorbed photosynthetically active radiation (APAR) and/or light use efficiency (LUE). Here we present the first time series of near‐surface measurement of canopy‐scale SIF at 760 nm in temperate deciduous forests. SIF correlated with GPP estimated with eddy covariance at diurnal and seasonal scales (r² = 0.82 and 0.73, respectively), as well as with APAR diurnally and seasonally (r² = 0.90 and 0.80, respectively). SIF/APAR is significantly positively correlated with LUE and is higher during cloudy days than sunny days. Weekly tower‐based SIF agreed with SIF from the Global Ozone Monitoring Experiment‐2 (r² = 0.82). Our results provide ground‐based evidence that SIF is directly related to both APAR and LUE and thus GPP, and confirm that satellite SIF can be used as a proxy for GPP.

Plant phenology research has gained increasing attention because of the sensitivity of phenology to climate change and its consequences for ecosystem function. Recent technological development has made it possible to gather invaluable data at a variety of spatial and ecological scales. Despite our ability to observe phenological change at multiple scales, the mechanistic basis of phenology is still not well understood. Integration of multiple disciplines, including ecology, evolutionary biology, climate science, and remote sensing, with long‐term monitoring data across multiple spatial scales is needed to advance understanding of phenology. We review the mechanisms and major drivers of plant phenology, including temperature, photoperiod, and winter chilling, as well as other factors such as competition, resource limitation, and genetics. Shifts in plant phenology have significant consequences on ecosystem productivity, carbon cycling, competition, food webs, and other ecosystem functions and services. We summarize recent advances in observation techniques across multiple spatial scales, including digital repeat photography, other complementary optical measurements, and solar‐induced fluorescence, to assess our capability to address the importance of these scale‐dependent drivers. Then, we review phenology models as an important component of earth system modeling. We find that the lack of species‐level knowledge and observation data leads to difficulties in the development of vegetation phenology models at ecosystem or community scales. Finally, we recommend further research to advance understanding of the mechanisms governing phenology and the standardization of phenology observation methods across networks. With the opportunity for “big data” collection for plant phenology, we envision a breakthrough in process‐based phenology modeling.

Forest mortality is accelerating due to climate change and the largest trees may be at the greatest risk, threatening critical ecological, economic, and social benefits. Here, we combine high-resolution airborne LiDAR and optical data to track tree-level mortality rates for ~2 million trees in California over 8 years, showing that tree height is the strongest predictor of mortality during extreme drought. Large trees die at twice the rate of small trees and environmental gradients of temperature, water, and competition control the intensity of the height-mortality relationship. These findings suggest that future persistent drought may cause widespread mortality of the largest trees on Earth.

Recent advances in remote sensing of solar‐induced chlorophyll fluorescence (SIF) have garnered wide interest from the biogeoscience and Earth system science communities, due to the observed linearity between SIF and gross primary productivity (GPP) at increasing spatiotemporal scales. Three recent studies, Maguire et al., (2020, https://doi.org/10.1029/2020GL087858), He et al. (2020, https://doi.org/10.1029/2020GL087474), and Marrs et al. (2020, https://doi.org/10.1029/2020GL087956) highlight a nonlinear relationship between fluorescence and photochemical yields and show empirical evidence for the decoupling of SIF, stomata, and the carbon reactions of photosynthesis. Such mechanistic studies help advance our understanding of what SIF is and what it is not. We argue that these findings are not necessarily contradictory to the linear SIF‐GPP relationship observed at the satellite scale and provide context for where, when, and why fluorescence and photosynthesis diverge at smaller spatiotemporal scales. Understanding scale dependencies of remote sensing data is crucial for interpreting SIF as a proxy for GPP.