Site Characteristics Mediate the Relationship Between Forest Productivity and Satellite Measured Solar Induced Fluorescence

Abstract

Solar-Induced Chlorophyll Fluorescence (SIF) can provide key information about the state of photosynthesis and offers the prospect of defining remote sensing-based estimation of Gross Primary Production (GPP). There is strong theoretical support for the link between SIF and GPP and this relationship has been empirically demonstrated using ground-based, airborne, and satellite-based SIF observations, as well as modeling. However, most evaluations have been based on monthly and annual scales, yet the GPP:SIF relations can be strongly influenced by both vegetation structure and physiology. At the monthly timescales, the structural response often dominates but short-term physiological variations can strongly impact the GPP:SIF relations. Here, we test how well SIF can predict the inter-daily variation of GPP during the growing season and under stress conditions, while taking into account the local effect of sites and abiotic conditions. We compare the accuracy of GPP predictions from SIF at different timescales (half-hourly, daily, and weekly), while evaluating effect of adding environmental variables to the relationship. We utilize observations for years 2018–2019 at 31 mid-latitudes, forested, eddy covariance (EC) flux sites in North America and Europe and use TROPOMI satellite data for SIF. Our results show that SIF is a good predictor of GPP, when accounting for inter-site variation, probably due to differences in canopy structure. Seasonally averaged leaf area index, fraction of absorbed photosynthetically active radiation (fPAR) and canopy conductance provide a predictor to the site-level effect. We show that fPAR is the main factor driving errors in the linear model at high temporal resolution. Adding water stress indicators, namely canopy conductance, to a multi-linear SIF-based GPP model provides the best improvement in the model precision at the three considered timescales, showing the importance of accounting for water stress in GPP predictions, independent of the SIF signal. SIF is a promising predictor for GPP among other remote sensing variables, but more focus should be placed on including canopy structure, and water stress effects in the relationship, especially when considering intra-seasonal, and inter- and intra-daily resolutions.

Accounting for Changes in Radiation Improves the Ability of SIF to Track Water Stress‐Induced Losses in Summer GPP in a Temperate Deciduous Forest

“…Furthermore, Yazbeck et al. (2021) demonstrated that SIF did not reliably capture daily‐scale reductions in GPP due to water stress at multiple flux tower sites. Wohlfahrt et al.…”

“…Despite the strong correlations reported between SIF and GPP at seasonal and diurnal timescales, uncertainties remain in the mechanistic relationship between SIF and GPP (Ryu et al, 2019), and in how that relationship changes across different ecosystems and spatiotemporal scales. Several studies have found that SIF over cropland is more closely tied to absorbed PAR (APAR) than to GPP (Miao et al, 2018;Yazbeck et al, 2021), and Zeng et al (2019) broadly demonstrated that SIF is strongly influenced by canopy structure and changes in f esc . SIF is also dependent on the fluorescence yield of the photosystems, which can itself be influenced by light and biological conditions (Baker, 2008), further complicating its relationship with GPP.…”

“…Several satellite-based studies have used SIF to observe the impacts of moderate to severe drought in both temperate (Li et al, 2020;Smith et al, 2020;Song et al, 2018;Sun et al, 2015;Yoshida et al, 2015) and tropical regions (Koren et al, 2018;Liu et al, 2017); nonetheless, observations of SIF tend to be less sensitive to interannual variability in GPP during summer and may not show the impacts of mild stress (Butterfield et al, 2020). Furthermore, Yazbeck et al (2021) demonstrated that SIF did not reliably capture daily-scale reductions in GPP due to water stress at multiple flux tower sites. Wohlfahrt et al (2018) showed that local scale observations of SIF over a Mediterranean pine forest decoupled from GPP under environmental stress and suggested that much of the strong correlation between SIF and GPP in this ecosystem was driven by a shared dependence on APAR, calling into question the detectability of stress-induced changes in GPP from SIF observations.…”

Accounting for Changes in Radiation Improves the Ability of SIF to Track Water Stress-Induced Losses in Summer GPP in a Temperate Deciduous Forest

“…Despite the strong correlations reported between SIF and GPP at seasonal and diurnal timescales, uncertainties remain in the mechanistic relationship between SIF and GPP , and in how that relationship changes across different ecosystems and spatiotemporal scales. Several studies have found that SIF over cropland is more closely tied to absorbed PAR (APAR) than to GPP (Miao et al, 2018;Yazbeck et al, 2021), andZeng et al (2019) broadly demonstrated that SIF is strongly influenced by canopy structure and changes in fesc. SIF is also dependent on the fluorescence yield of the photosystems.…”

“…Several satellite-based studies have used SIF to observe the impacts of moderate to severe drought (Li et al, 2020;Song et al, 2018;Yoshida et al, 2015); nonetheless, observations of SIF tend to be less sensitive to interannual variability in GPP during summer and may not show the impacts of mild stress (Butterfield et al, 2020). Furthermore, Yazbeck et al (2021) demonstrated that SIF did not reliably capture daily-scale reductions in GPP due to water stress at multiple flux tower sites. Wohlfahrt et al (2018) showed that local scale observations of SIF over a Mediterranean pine forest decoupled from GPP under environmental stress and suggested that much of the strong correlation between SIF and GPP in this ecosystem was driven by a shared dependence on APAR, calling into question the detectability of stress-induced changes in GPP from SIF observations.…”