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 Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near-surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated.  Here, we integrate on-the-ground phenological observations, leaf-level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, towerbased CO 2 flux measurements, and a predictive model to simulate seasonal canopy color dynamics.  We show that seasonal changes in canopy color occur independently of new leaf production, but track changes in chlorophyll fluorescence, the photochemical reflectance index, and leaf pigmentation. We demonstrate that at winter-dormant sites, seasonal changes in canopy color can be used to predict the onset of canopy-level photosynthesis in spring, and its cessation in autumn. Finally, we parameterize a simple temperature-based model to predict the seasonal cycle of canopy greenness, and we show that the model successfully simulates interannual variation in the timing of changes in canopy color.  These results provide mechanistic insight into the factors driving seasonal changes in evergreen canopy color and provide opportunities to monitor and model seasonal variation in photosynthetic activity using color-based vegetation indices.

At the seasonal time scale, daily photochemical reflectance index (PRI) measurements track changes in photoprotective pigment pools as plants respond to seasonally variable environmental conditions. As such, remotely sensed PRI products present opportunities to study seasonal processes in evergreen conifer forests, where complex vegetation dynamics are difficult to capture due to small annual changes in chlorophyll content or leaf structure. Because PRI is tied explicitly to short-and long-term changes in photoprotective pigments that are responsible for regulating stress, we hypothesize that PRI by extension could serve as a proxy for stomatal response to seasonally changing hydroclimate, assuming plant functional responses to stress covary in space and time. To test this, we characterized PRI in a semiarid, montane mixed conifer forest in the Madrean sky islands of Arizona, USA, during the monsoon growing season subject to precipitation pulse dynamics. To determine the sensitivity of PRI to ecohydrologic variability and associated changes in gross primary productivity (GPP), canopy spectral measurements were coupled with eddy covariance CO 2 flux and sap flow measurements. Seasonally, there was a significant relationship between PRI and sap flow velocity (R 2 = 0.56), and multiple linear regression analysis demonstrated a PRI response to dynamic water and energy limitations in this system. We conclude that PRI has potential to serve as a proxy for forest functional response to seasonal ecohydrologic forcing. The coordination between photoprotective pigments and seasonal stomatal regulation demonstrated here could aid characterization of vegetation response to future changes in hydroclimate at increasing spatial scales. Plain Language Summary In order to understand how ecosystems interact with climate and how these relationships may change under future conditions, it is necessary to study how carbon and water move between plants and the atmosphere and how environmental stress, such as changing water availability, impacts these processes. For decades, satellites used in remote sensing studies have been able to measure how "green" an ecosystem is, but for forests that remain visibly green year-round even under stressful conditions, these greenness indices may not probe deeply enough beneath the surface to provide a clear picture of plant function. An alternative reflectance-based index, termed the photochemical reflectance index, or PRI, is able to detect seasonal changes in leaf pigments that are responsible for regulating plant stress. Here, we use tower-based PRI data from a semiarid conifer forest to show that variations in PRI correspond to the way in which plants regulate their water loss as moisture and temperature conditions change throughout the growing season. This result demonstrates that PRI is an effective indicator of how ecosystems respond to stressful environmental conditions, and therefore has the potential to advance our ability to distinguish how water availability influences forest productivity.

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