Mechanistic evidence for tracking the seasonality of photosynthesis with solar-induced fluorescence

Significance

Recent advances in satellite remote sensing of solar-induced fluorescence (SIF) are promising for estimating gross primary production (GPP). However, the empirical link between GPP and SIF has mostly been observed at coarse spatial and temporal scales and lacks a direct mechanistic explanation. Here, we compare high-resolution SIF with GPP and needle-scale physiology at a winter-dormant coniferous forest. Needles retained chlorophyll year-round despite cold temperatures and high light in winter; meanwhile SIF tracks GPP at hourly to weekly timescales. We show that both GPP and SIF are regulated by seasonal changes in photoprotective pigments and that SIF is directly related to needle physiology. This highlights the unique ability of SIF compared with traditional remote-sensing methods to capture GPP seasonality.

Abstract

Northern hemisphere evergreen forests assimilate a significant fraction of global atmospheric CO₂ but monitoring large-scale changes in gross primary production (GPP) in these systems is challenging. Recent advances in remote sensing allow the detection of solar-induced chlorophyll fluorescence (SIF) emission from vegetation, which has been empirically linked to GPP at large spatial scales. This is particularly important in evergreen forests, where traditional remote-sensing techniques and terrestrial biosphere models fail to reproduce the seasonality of GPP. Here, we examined the mechanistic relationship between SIF retrieved from a canopy spectrometer system and GPP at a winter-dormant conifer forest, which has little seasonal variation in canopy structure, needle chlorophyll content, and absorbed light. Both SIF and GPP track each other in a consistent, dynamic fashion in response to environmental conditions. SIF and GPP are well correlated (R² = 0.62–0.92) with an invariant slope over hourly to weekly timescales. Large seasonal variations in SIF yield capture changes in photoprotective pigments and photosystem II operating efficiency associated with winter acclimation, highlighting its unique ability to precisely track the seasonality of photosynthesis. Our results underscore the potential of new satellite-based SIF products (TROPOMI, OCO-2) as proxies for the timing and magnitude of GPP in evergreen forests at an unprecedented spatiotemporal resolution.

Northern hemisphere evergreen forests represent a substantial fraction of the global carbon pool (1) and contribute significantly to the fluxes of CO₂ between the biosphere and the atmosphere (2). Evidence suggests that many high-latitude evergreen ecosystems have increased in productivity in recent years in conjunction with increasing temperature (3–5). Conversely, increasing temperature can place a strain on plant available water, thereby restricting carbon uptake and increasing ecosystem respiration and therefore net carbon loss to the atmosphere (6). Consequently, predicting the fate of evergreen systems in the context of climate change has been challenging (7). While networks of eddy covariance flux towers (8) and new satellite technologies (9, 10) observe local net CO₂ fluxes, disentangling the gross CO₂ flux components, gross primary production (GPP) (CO₂ uptake) and total ecosystem respiration (CO₂ released), is difficult (11). This is especially true for evergreen ecosystems, which undergo large seasonal shifts in light-use efficiency (LUE) (carbon gained per light absorbed) while canopy structure and green leaf/needle area remain relatively constant (12), making classical remote-sensing parameters—such as the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI)—poorly suited for detecting seasonal GPP change (13, 14). Additional challenges in vegetation remote sensing arise in high-latitude ecosystems due to pervasive cloudiness, shadow contamination, snow, and open water surfaces (15). Further, the complex terrain of high-elevation evergreen systems is generally not amenable to eddy covariance carbon flux measurements. As a result, accurately determining the timing of seasonal GPP onset and cessation in evergreen forests remains a major challenge in terrestrial biosphere models and satellite remote sensing (7, 16, 17).

Recent advances in satellite remote sensing of solar-induced chlorophyll fluorescence (SIF) may help overcome these challenges (18–22) by providing a proxy for GPP (16, 23–25). SIF represents an emission of energy emanating from chlorophyll molecules, which is a function of the activity of competing pathways for de-excitation [principally by photochemistry and nonphotochemical quenching (NPQ)] (26). Evergreen forests experience strong seasonality and endure significant physiological stress during the winter while still absorbing considerable sunlight (27). To acclimate, conifers reduce the abundance of reaction center proteins and increase their investment in photoprotective pigments (zeaxanthin and antheraxanthin) associated with NPQ (28–30). Consequently, fluorescence is strongly inhibited. Some of the low level of residual fluorescence in winter-acclimated needles may be associated with photosystem I (PSI), but a small dynamic component may indicate the presence of some photosystem II (PSII) activity. However, it is unclear how this process manifests at scales observable via remote sensing.

A growing body of evidence suggests that the relationship between GPP and SIF becomes more linear over increasing spatial (31–34) and temporal (35–37) extents. A key driver of both SIF and GPP is absorbed photosynthetically active radiation (APAR) by chlorophyll (38, 39). Thus, some research suggests that SIF is primarily responding to changes in APAR—a quantity related to incident light and green leaf area—rather than actual changes in the efficiency of photosynthesis, which may be the case in deciduous forests and cropping systems (39–41). In fact, currently established parameterizations of fluorescence yields predict potential reductions in the fluorescence yields to only about 50% of their maximum (42). This should still result in substantial SIF values in cold environments when a de facto shutdown of photosynthesis occurs coincident with little change in APAR. Seasonally snow-covered evergreen systems at midlatitudes and high altitude (cold but high light in winter) provide an ideal case study for examining the relationship between SIF and GPP independent of seasonal changes in chlorophyll or APAR. We investigated this at a subalpine conifer forest (codominated by Pinus contorta, Picea engelmannii, and Abies lasiocarpa) at Niwot Ridge, CO. We measured SIF and NDVI continuously from June 2017 to June 2018 with a spectrometer system (43) mounted on top of an eddy covariance flux tower. Spectroscopic data were compared with APAR, meteorology, GPP, and approximately monthly characterizations of needle pigment composition and quantum efficiencies measured via active pulse-amplitude modulated (PAM) fluorimetry.

Results

Seasonal and Diurnal Dynamics of Canopy Photosynthesis and SIF.

Flux tower observations indicated full cessation of CO₂ uptake at Niwot Ridge during the winter (Fig. 1B), with a rapid resumption of activity in April–May, and a slower decrease of activity in fall—in agreement with (44, 45). During the same time period, we observed no significant seasonal change in APAR, NDVI, or needle chlorophyll concentration, as was expected (Fig. 1 C and D). The timing and magnitude of changes in GPP during the fall and spring transition periods closely corresponded with those in SIF (Fig. 1B), coincident with changes in dark-acclimated xanthophyll cycle conversion state and the maximum quantum efficiency of photosystem II (F_v/F_m, Fig. 1D). The retention of zeaxanthin (Z) and antheraxanthin (A) in dark-acclimated foliage in winter (i.e., a high xanthophyll cycle conversion state) is associated with sustained photoprotection (28), which manifests as decreases in the maximum quantum efficiency of photosystem II when conditions are unsuitable for photosynthesis (46). The seasonal trends in needle-scale parameters confirm findings from a previous study at Niwot Ridge (27), but also provide insight into the timing of changes in leaf physiology and indicate that needles experience significant physiological stress in the winter. The 5-d running means of SIF tracked GPP closely during the growing season (Fig. 1B), coincident with changes in environmental conditions and relative SIF [which is normalized by incoming near-infrared (NIR) reflected radiance to account for structural and bidirectional reflectance effects of the signal (47)] (SI Appendix, Fig. S1). SIF showed a nearly fourfold decrease during the transition from summer to winter—which is much larger than expected using current SIF modeling paradigms (42). The residuals (daily averages) of the 5-d running means showed that SIF and GPP are significantly correlated (SI Appendix, Fig. S2), suggesting that SIF tracks not only the seasonal variation of GPP, but also day-to-day changes driven largely by incoming light, while NDVI was constant throughout the season (Fig. 1C). There was also a close correspondence between tower-based SIF (at the time of satellite overpass) and satellite-based SIF from TROPOMI (22) and OCO-2 (48) (target), the former of which was able to retrieve satellite SIF at a subweekly resolution and has a near 1:1 slope compared with tower-derived SIF (SI Appendix, Fig. S3). The correspondence between tower and satellite SIF is particularly encouraging given the relatively large single-footprint size of TROPOMI (3.5 × 7 km at nadir) and OCO-2 (1.3 × 2.25 km; SI Appendix, Fig. S4).

Fig. 1.

Seasonal dynamics of GPP, far-red SIF, NDVI, APAR, needle pigments, and fluorescence at Niwot Ridge, CO. (A) Phenocam (webcam) images of the canopy where the data were collected during different seasons. (B) Five-day running means of cumulative daily GPP (black) and true daily average SIF (dark red). (C) Five-day running means of NDVI (green) and APAR (gold). Shaded regions in B and C indicate 1 SEM. (D) Chlorophyll a + b concentration relative to dry mass (green), maximum quantum efficiency (F_v/F_m) measured with a fluorimeter (blue), and dark-adapted xanthophyll cycle conversion state (purple) ([Zeaxanthin + Antheraxanthin]/[Violaxanthin + Antheraxanthin + Zeaxanthin]) sampled at monthly intervals. All needleleaf measurements represent the mean and 1 SE of both Engelmann spruce and lodgepole pine samples during each 2- to 3-d sampling period.

Seasonal averages of hourly data are shown to highlight the dynamic nature of GPP, light-use efficiency (GPP/APAR), SIF, SIF yield (SIF/APAR), and relative SIF (SIF/NIR reflected radiance) across the seasons (Fig. 2). In deciduous forests, there is almost no APAR or chlorophyll in the winter; but in this case, only about a 30% decrease in APAR was observed on sunny days in the winter, with no significant change in needle chlorophyll concentration (Fig. 2F). Meanwhile, a near complete suppression of photosynthetic activity during the winter resulted in nominal (∼0) GPP and very little SIF (Fig. 2 A and B and SI Appendix, Fig. S5). Additionally, SIF yield, LUE, and relative SIF were significantly reduced during the summer-to-winter transition, with a similar diurnal pattern (Fig. 2 C–E). This suggests that most of the absorbed light in winter and spring was being dissipated as heat via NPQ mechanisms, largely reducing fluorescence and contributing to the shutdown of photosynthesis. However, there was still the potential for a small amount of electron transport happening within needles, albeit at a much-reduced level, as evidenced by the F_v/F_m measurements (Fig. 1D). The small residual SIF emissions in winter (while GPP approaches zero) may indicate electron transport to maintain a transmembrane ΔpH needed to sustain NPQ (29). Further, the slight increase in SIF preceding GPP in the spring of 2018 could be due to photorespiratory recycling of CO₂ before stomatal opening because water transport was still blocked by frozen boles early in the spring (27). Future research is needed at both needle and canopy scales to fully understand the slightly earlier increase in fluorescence compared with GPP in evergreen coniferous ecosystems.

Fig. 2.

(A–F) Seasonal hourly averages of (A) far-red SIF; (B) GPP; (C) far-red SIF yield (SIF/APAR); (D) LUE (GPP/APAR); (E) relative far-red SIF (SIF/reflected radiance in the NIR retrieval window); and (F) APAR. Summer data are from June 21, 2017 to August 30, 2017 and from June 1, 2018 to June 29, 2018. Fall data are from September 1, 2017 to November 15, 2017. Winter data are from November 15, 2017 to March 31, 2018. Spring data are from April 1, 2018 to May 23, 2018. Shaded regions represent 1 SE of the hourly mean. Green, summer; gold, fall; blue, winter; and purple, spring.

SIF Tracks Photosynthesis Across All Seasons and at Different Timescales.

Scatterplots for hourly, daily, and weekly aggregated data shown in Figs. 1 and 2 are provided in Fig. 3. Here, we show that SIF corresponded more closely to changes in GPP than APAR at hourly (R² = 0.62 vs. R² = 0.37), daily (R² = 0.78 vs. R² = 0.29), and weekly (R² = 0.92 vs. R² = 0.33) timescales, clearly underlining that most variation was due to changes in fluorescence and photosynthetic efficiencies (Figs. 1 and 4). The stronger correlation between SIF and GPP was largely driven by more dramatic changes in the seasonality of SIF compared with APAR—i.e., photosynthesis approached zero, but absorbed light remained relatively high. Notably, the strength (R²) of these relationships improved when the averaging period increased, but there was little difference in the slope and intercept of the GPP vs. SIF relationships at increasing timescales (Fig. 3).

Fig. 3.

(A–F) Scatterplots of (A–C) far-red SIF against APAR and (D–F) GPP binned at hourly (A and D), daily (B and E), and weekly (C and F) time intervals. Points are colored by season, dictated by onset and suppression of photosynthesis. Shaded regions indicate a 95% confidence interval around the line of best fit. We report the coefficient of determination (R²), slope, and intercept of each line of best fit. All relationships are statistically significant at P < 0.05.

Fig. 4.

Correlation plots of weekly average far-red SIF against needle measurements of foliar pigment composition and PAM fluorescence. (A) Total xanthophyll cycle pigment pool (V+A+Z μmol·g⁻¹). (B) Sustained retention of zeaxanthin and antheraxanthin after dark adaptation represented by the xanthophyll cycle conversion state ([Z+A]/[V+A+Z]). (C) Maximum quantum efficiency in the dark (F_v/F_m) measured by a fluorimeter. (D) Photosystem II operating efficiency (θPSII) at a photosynthetically active radiation (PAR) level of 500 μmol·m⁻²·s⁻¹, derived during a light response curve. Shaded regions indicate a 95% confidence interval around the line of best fit. All relationships are statistically significant at P < 0.05.

Typically, the dynamic range of PSII yields at the leaf scale (under NPQ changes) is much larger than that of the SIF yield (34, 42); however, at the canopy scale, we observe a substantial reduction in SIF yield (decrease of ∼80%) in the winter due to sustained NPQ and deactivation of photosystems. Such dynamic changes in PSII yield and F_v/F_m have been shown in winter measurements of PAM fluorescence in a similar ecosystem located in Hyytiälä, Finland, which also suggests substantial suppression of photochemistry in PSII (49). We hypothesize that either the impact of sustained NPQ on SIF yields is currently underestimated or the canopy aggregation of SIF and GPP over all sunlit and shaded leaves represents a substantially more complex scenario than that in leaf-scale studies. Thus, temporal and spatial averaging of SIF data could provide credence for the consistently strong and positive relationships between SIF and GPP observed at longer (often monthly) timescales (31). Further, APAR was not associated with changes in GPP at our site as strongly as in some agricultural systems (39) (SI Appendix, Fig. S6). While all of the relationships shown in the main text used tower-based far-red SIF data (consistent with satellites), we also observed a close correspondence between red SIF and GPP, with no discernable difference between red and far-red SIF for tracking GPP (SI Appendix, Fig. S6: hourly R² = 0.50; daily R² = 0.67; and weekly R² = 0.87). We expect that red SIF will increase when chlorophyll concentration decreases (50, 51), but since no change in chlorophyll was observed, red SIF tracks far-red SIF closely (SI Appendix, Fig. S2). Taken together, we conclude that high-frequency daily satellite overpasses measuring red and far-red SIF (i.e., TROPOMI) will be adequate to characterize the seasonality of photosynthesis and that the SIF/GPP relationship can be extrapolated across varying timescales in a reproducible fashion. However, due to the rapid onset and cessation of photosynthesis in this forest, current satellite SIF products averaged at a monthly time resolution are not yet adequate to capture the phenological transition that influences GPP in this system (48). Ultimately, the near-daily return interval of TROPOMI will provide a great improvement in our ability to track dynamics of photosynthesis across a wide range of ecosystems (22).

SIF Responds to Changes in Needle Physiology.

Measurements of xanthophyll cycle conversion state and the quantum efficiency of photosystem II from active PAM fluorescence exhibited statistically significant relationships with weekly averages of tower-based SIF during periods of in situ sampling (Fig. 4). This confirms that the strong seasonality of GPP in this subalpine evergreen forest is modulated by changes in photosynthetic efficiency and the acclimation of photoprotective pigments in needles across two of the dominant species (P. contorta and P. engelmannii) at Niwot Ridge (27). The total xanthophyll cycle pool size (Fig. 4A) and retention of zeaxanthin and antheraxanthin (Figs. 1D and 4B) are representative of sustained winter photoprotection in the light-harvesting complexes (29). Our data suggest that these pools can change over the course of 2 wk in the spring (Fig. 1D) and that these changes coincide with increases in SIF.

It is important to note that while we draw linkages between decreasing photosynthesis, decreasing SIF, and increasing xanthophyll cycle activity, there are many other coinciding potential drivers of ecosystem productivity. At Niwot Ridge, the spring onset of photosynthesis is associated with increasing temperature, hydraulic system recovery, and an increase in carboxylation capacity (27, 52, 53). We expect not only that winter acclimation corresponds to changes in the xanthophyll cycle, but also that a variety of carotenoids, such as lutein and beta-carotene, may play a photoprotective role during the transition seasons and winter (30, 54). A continued long-term dataset of tower-based SIF and needle physiology measurements at Niwot Ridge will improve our ability to understand how SIF might respond to different controls on ecosystem carbon uptake including temperature, water availability, and evaporative demand.

Discussion

In this winter-dormant confiner forest, remotely sensed SIF reflects dynamic changes in photosynthesis at the needle (Fig. 4) and canopy scales (Figs. 1–3)—in stark contrast with traditional vegetation indexes (NDVI), which remain relatively insensitive to seasonal changes in evergreen photosynthesis. In this forest, xanthophyll cycle pigments play a significant role during winter acclimation of photosynthesis. In northern hemisphere evergreen forests, an increase in xanthophyll cycle pigments during winter is often accompanied by a decrease in chlorophyll concentration (55–57); however, we observed little seasonal change in chlorophyll concentration—coincident with previous reports at Niwot Ridge (27). An alternative measure of seasonal acclimation of leaf pigment composition is the chlorophyll:carotenoid index (CCI)—which can be detected by satellites such as MODIS—and tends to track changes in xanthophyll cycle pigments associated with winter acclimation (58). While CCI is an especially promising proxy of photosynthetic dynamics in evergreen forests, SIF has an advantage in that it is not directly impacted by fine-scale surface heterogeneity, which can bias reflectance-based indexes that are also sensitive to nonphotosynthesizing landscape features within a pixel (soil background, standing water, etc.). Additionally, SIF retrievals are less affected by clouds (59) and are not prone to saturation when leaf area is high (SI Appendix, Fig. S7). We report strong, statistically significant relationships between SIF and GPP at hourly, daily, and weekly timescales under both clear and diffuse sky conditions (SI Appendix, Fig. S7); however, it is worth noting that the slope of the relationship is lower under diffuse sky conditions, potentially because GPP can remain high even under cloudy conditions in this evergreen forest (60), and when all data are pooled together it weakens the relationship slightly (Fig. 3). The choice of a remotely sensed GPP proxy must be weighed against the available spatial and temporal resolution of the data product. Most satellite SIF data are sparse (long revisit time) and often come at a coarser spatial resolution than satellite reflectance products. OCO-2 “target mode” data provided only five observations during our study period. TROPOMI, on the other hand, will provide an order of magnitude increase in revisit frequency at high spatial resolution and retrieval precision (22), enabling a much more finely resolved time series of SIF data (22) (SI Appendix, Fig. S3) and improved assessment of longer-term records from GOME-2.

Previous research has highlighted the importance of understanding the nonlinear relationships between photosynthesis, fluorescence, and NPQ and how they manifest at increasing scales before interpreting SIF from space (26, 34, 42). However, our results suggest that satellite SIF from TROPOMI might be sufficient to track dynamics in photosynthesis in evergreen systems, albeit at a coarser spatial resolution (3.5 × 7 km at nadir) than that observed from tower-based observations. This is particularly relevant as state-of-the-art global terrestrial biosphere models fail to capture the seasonality of GPP in evergreen systems, often predicting an early spring uptake of CO₂ (7, 16). A potential explanation could be that global model predictions of GPP are overly sensitive to air temperature, which increases above freezing before GPP onset at Niwot Ridge (SI Appendix, Fig. S1). Some site-specific models have been able to circumvent these issues by providing a more detailed analysis of the timing and magnitude of GPP (45, 61, 62). To improve measuring and modeling of GPP seasonality, there is a growing network of flux towers (8) in evergreen systems that are capable of hosting tower-mounted spectrometers which could be used to further test the potential and limitations of SIF and reflectance indexes in monitoring ecosystem photosynthesis. The present study provides strong evidence for the ability of SIF to capture changes in photosynthetic capacity directly at a range of temporal scales. While greenness indexes and global models have failed to represent the magnitude and timing of GPP in winter-dormant coniferous forests, we have shown that SIF is a critical asset for improved monitoring of carbon cycle dynamics in evergreen forests. Given that higher latitudes experience amplified warming, such observations will be crucial to understand changes in carbon cycling of evergreens in the context of climate change.

Materials and Methods

Study Location.

This study was conducted at a subalpine conifer forest in Colorado [the Niwot Ridge AmeriFlux Core Site US-NR1 (63), 40.03°N, 105.55°W, 3050 m elevation], over the period from June 21, 2017 to June 29, 2018. The forest is composed of three dominant evergreen needleleaf species: lodgepole pine (P. contorta Douglas ex Loudon), Engelmann spruce (P. engelmannii Parry ex Engelm.), and subalpine fir [A. lasiocarpa (Hook.) Nutt.]. The climate at this forest includes cold winters with a persistent snowpack from October/November to May/June. Extensive site details are available in earlier publications (27, 60, 64). An image of the US-NR1 flux tower and PhotoSpec telescope unit is provided in SI Appendix, Fig. S8.

Tower-Based Solar-Induced Chlorophyll Fluorescence.

Data from a scanning spectrometer (PhotoSpec) atop the 26-m tall tower were used for the canopy-scale analysis (43). Data gaps were the result of power loss to our PhotoSpec system from September 7, 2017 to October 19, 2017. The detection of SIF is based on measuring the change in the optical density of a well-known narrow spectral feature in the presence of a fluorescence signal, a solar Fraunhofer line (65–67). The instrument setup is described in detail in Grossmann et al. (43).

The PhotoSpec instrument consists of a 2D scanning telescope unit which can be pointed to any location on a canopy at user-selectable azimuth and elevation angles. Light reaching the telescope is distributed into three thermally stabilized commercial spectrometers via optical fiber bundles. These spectrometers cover wavelength ranges at high spectral resolution to retrieve SIF in the red and far-red wavelength range, as well as at moderate resolution to retrieve vegetation indices such as the NDVI. Far-red and red SIF are retrieved in the 745- to 758-nm and 680- to 686-nm wavelength windows, respectively (43). The telescope unit also includes a commercial photosynthetically active radiation (PAR) sensor (LI-COR LI-190R). A typical measurement sequence in the field started with the measurement of a solar reference spectrum using an upward-looking opal glass diffuser, followed by a scan from nadir to the horizon in 0.7° steps at two different azimuth directions, with a time resolution of ∼20 s per measurement (integration time). Diffuser spectra are recorded approximately every 3 min throughout the scanning routine. The PhotoSpec has a 0.7° field of view (FOV), resulting in an ∼20-cm diameter footprint (at nadir) on the top of the canopy. A conservative filter was applied to the SIF retrievals to ensure we were measuring data from vegetation and that measurements were not taken at unreasonably low solar or viewing zenith angles, which result in high retrieval errors. We filtered SIF data to include measurements when the solar zenith angle was less than 90°, the viewing zenith angle was less than 30°, and NDVI was greater than 0.6. The return interval for a complete scan was around 20 min, but we averaged data from all scans on an hourly time resolution to match the temporal resolution of flux tower data.

Needle Physiology.

To determine seasonality of photosynthetic performance at the needle scale, physiological measurements (pigment extraction and PAM fluorescence) were performed on sun-exposed foliage from two canopy-access towers near the main flux tower and in the laboratory on branches collected from those trees, every 4–8 wk over the annual cycle. Samples came from pine and spruce trees that were in the field of view of the spectrometer. Due to canopy structure, a limited number of trees were accessible from the towers, preventing more extensive replication. This also limited sampling to P. contorta ad P. engelmannii needles. Two branches were measured/sampled from each tree during each visit (n = 6 branches on three trees for pine, and n = 4 branches on two trees for spruce, in the upper canopy at 10–12 m height above ground). We pooled species together to better match the FOV of tower- and satellite-based SIF retrievals; however, we note that no significant difference was observed between the two species at any time during the season.

Needle-Scale Chlorophyll Fluorescence.

Chlorophyll fluorescence was measured on pine and spruce trees using PAM fluorimetry from a portable photosynthesis system (LI-6800F; LI-COR) equipped with the standard broadleaf chamber and control of temperature, humidity, and incident light. Two types of measurements were made, the PSII operating efficiency in the light (θPSII at 500 PAR) and the maximum quantum efficiency of PSII photochemistry (F_v/F_m on dark-acclimated tissues). Nomenclature is consistent with the review of Baker (68), except that we refer to F_q′/F_m′ as θPSII. To measure F_v/F_m, the distal 10–15 cm of branches were cut, wrapped in aluminum foil with a moistened paper towel, and transported to the laboratory for several hours of dark acclimation. Measurements were performed using the LI-COR 6800, after which needles were immediately flash-frozen in liquid N₂ for leaf pigment analysis.

Measurements of θPSII were made from the canopy access towers as follows. For P. contorta, one to two fascicles were inserted into the chamber while attached to the branch. P. engelmannii branch/needle geometry prevented measurements with this chamber on intact branches, so 8–10 needles were detached from the branch and affixed to adhesive tape before placing in the leaf chamber. We did not control for the orientation of the needles in the chamber (adaxial vs. abaxial). Before a measurement, ambient air temperature and light level were measured, and leaf temperature and incident light in the leaf chamber were set to match air temperature and 40% relative humidity. This was repeated for incident PAR at a light intensity of 500 µmol photons⋅m⁻²⋅s⁻¹ to determine θPSII during illumination.

Needle Chlorophyll and Carotenoid Composition.

Needle pigment composition was measured to evaluate seasonal acclimation associated with the decrease in photosynthesis due to winter acclimation. Following the measurements of F_v/F_m adjacent foliage was collected and immediately flash-frozen in liquid nitrogen (LN₂) for leaf pigment analysis. Needles were stored frozen in LN₂, dry ice, or a −80 °C freezer until analysis. Pigments were extracted in acetone and analyzed by HPLC as described in Bowling et al. (27). Needle pigment contents are expressed as moles per unit fresh mass and as molar ratios (i.e., [Z + A]/[V + A + Z]). Pigments from both species during each measurement campaign were averaged, and variation was reported as 1 SD.

Meteorological Parameters and Carbon Fluxes.

Weather and environmental parameters were monitored to assess their influence on forest carbon cycling. These included a wide variety of AmeriFlux Core Site observations, and the vertical exchange of CO₂, including storage, was measured at a height of 21.5 m by eddy covariance using a sonic anemometer (model CSAT3; Campbell Scientific) coupled with a closed-path infrared gas analyzer (model LI-6262; LI-COR Biosciences)—details are available in Burns et al. (60). The fluxes of GPP and ecosystem respiration were partitioned from net ecosystem exchange using air temperature following the method of Reichstein et al. (11) via the R package REddyProc (69).

The fraction of PAR absorbed by the vegetation canopy (fPAR) was computed using arrays of upward- and downward-oriented PAR sensors above and below the canopy. Full-spectrum quantum sensors (SQ-500-SS; Apogee Instruments) were new and factory-calibrated together just before installation. Above-canopy sensors (one up and one down) were mounted on the main flux tower, and below-canopy sensors (six up and six down) were mounted at 2 m height above ground via the canopy-access towers. The fPAR was calculated for each pair of below-canopy relative to above-canopy sensors, and these were averaged over daylight hours for each day to produce the seasonal pattern of APAR (fPAR_canopy × PAR_{top of canopy}). Additionally, we tested the ability of our SIF retrievals to track GPP under clear and diffuse sky conditions using a threshold (0.5, top-of-canopy/top-of-atmosphere shortwave radiation) similar to that used in (39, 70).

Satellite Data.

OCO-2 target mode observations at Niwot Ridge started in April 2017 and we used the official SIF products v8. Target collections consist of repeating backward and forward scans as the instrument flies overhead, with eight independent across-track measurements along a 10-km-wide swath and a nominal OCO-2 footprint of 1.3 km × 2.25 km. Targets are typically centered on TCCON stations for calibration of XCO₂ but centered here on the eddy covariance tower for analysis against PhotoSpec. Five targets were collected (SI Appendix, Fig. S3) during our sampling period and one was discarded (in June) due to excessive cloud cover. Only scenes identified as evergreen needleleaf forest were retained. Otherwise, data are quality controlled following Sun et al. (48). TROPOMI satellite data were processed according to Köhler et al. (22).

Data Availability.

The datasets generated and/or analyzed for the current study are available at a data repository hosted at the California Institute of Technology (https://data.caltech.edu/records/1231). The doi associated with this dataset is 10.22002/D1.1231 (71).