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Quantifying gross primary production (GPP), the largest flux of the terrestrial carbon cycle, remains difficult at the landscape scale. Evergreen needleleaf (coniferous) forests in the western United States constitute an important carbon reservoir whose annual GPP varies from year-to-year due to drought, mortality, and other ecosystem disturbances. Evergreen forest productivity is challenging to determine via traditional remote sensing indices (i.e., NDVI and EVI), because detecting environmental stress conditions is difficult. We investigated the utility of solar-induced chlorophyll fluorescence (SIF) to detect year-to-year variation in GPP in four coniferous forests varying in species composition in the western United States (Sierra Nevada, Cascade, and Rocky Mountains). We show that annually averaged, satellite-based observations of SIF (retrieved from GOME-2) were significantly correlated with annual GPP observed at eddy covariance towers over several years. Further, SIF responded quantitatively to drought-induced mortality, suggesting that SIF may be capable of detecting ecosystem disturbance in coniferous forests. Plain Language Summary Understanding and quantifying how the productivity of coniferous forests responds to environmental change (e.g., drought and bark beetle-induced mortality) is important for the western United States, as these forests dominate the montane landscape. Often, carbon uptake by plants is tracked by measuring changes in light reflected from leaves, but these methods have proven problematic for evergreen forests. A new means of studying carbon uptake using solar-induced chlorophyll fluorescence (light emitted, rather than reflected, from sunlit leaves) is promising to study photosynthesis at the regional to global scales. We show that solar-induced fluorescence better tracks interannual variation of conifer productivity than reflectance-based methods. Further, we demonstrate that solar-induced fluorescence captures decreasing productivity associated with drought-induced forest mortality.