Terrestrial gross primary production: Using NIRV to scale from site to globe

Terrestrial photosynthesis is the largest and one of the most uncertain fluxes in the global carbon cycle. We find that near‐infrared reflectance of vegetation (NIR_V), a remotely sensed measure of canopy structure, accurately predicts photosynthesis at FLUXNET validation sites at monthly to annual timescales (R² = 0.68), without the need for difficult to acquire information about environmental factors that constrain photosynthesis at short timescales. Scaling the relationship between gross primary production (GPP) and NIR_V from FLUXNET eddy covariance sites, we estimate global annual terrestrial photosynthesis to be 147 Pg C/year (95% credible interval 131–163 Pg C/year), which falls between bottom‐up GPP estimates and the top‐down global constraint on GPP from oxygen isotopes. NIR_V‐derived estimates of GPP are systematically higher than existing bottom‐up estimates, especially throughout the midlatitudes. Progress in improving estimated GPP from NIR_V can come from improved cloud screening in satellite data and increased resolution of vegetation characteristics, especially details about plant photosynthetic pathway.     

The phenology of leaf quality and its within‐canopy variation is essential for accurate modeling of photosynthesis in tropical evergreen forests

Leaf quantity (i.e., canopy leaf area index, LAI), quality (i.e., per‐area photosynthetic capacity), and longevity all influence the photosynthetic seasonality of tropical evergreen forests. However, these components of tropical leaf phenology are poorly represented in most terrestrial biosphere models (TBMs). Here, we explored alternative options for the representation of leaf phenology effects in TBMs that employ the Farquahar, von Caemmerer & Berry (FvCB) representation of CO₂ assimilation. We developed a two‐fraction leaf (sun and shade), two‐layer canopy (upper and lower) photosynthesis model to evaluate different modeling approaches and assessed three components of phenological variations (i.e., leaf quantity, quality, and within‐canopy variation in leaf longevity). Our model was driven by the prescribed seasonality of leaf quantity and quality derived from ground‐based measurements within an Amazonian evergreen forest. Modeled photosynthetic seasonality was not sensitive to leaf quantity, but was highly sensitive to leaf quality and its vertical distribution within the canopy, with markedly more sensitivity to upper canopy leaf quality. This is because light absorption in tropical canopies is near maximal for the entire year, implying that seasonal changes in LAI have little impact on total canopy light absorption; and because leaf quality has a greater effect on photosynthesis of sunlit leaves than light limited, shade leaves and sunlit foliage are more abundant in the upper canopy. Our two‐fraction leaf, two‐layer canopy model, which accounted for all three phenological components, was able to simulate photosynthetic seasonality, explaining ~90% of the average seasonal variation in eddy covariance‐derived CO₂ assimilation. This work identifies a parsimonious approach for representing tropical evergreen forest photosynthetic seasonality in TBMs that utilize the FvCB model of CO₂ assimilation and highlights the importance of incorporating more realistic phenological mechanisms in models that seek to improve the projection of future carbon dynamics in tropical evergreen forests.     

Environmental variation is directly responsible for short- but not long-term variation in forest-atmosphere carbon exchange

Tower‐based eddy covariance measurements of forest‐atmosphere carbon dioxide (CO₂) exchange from many sites around the world indicate that there is considerable year‐to‐year variation in net ecosystem exchange (NEE). Here, we use a statistical modeling approach to partition the interannual variability in NEE (and its component fluxes, ecosystem respiration, R_eco, and gross photosynthesis, P_gross) into two main effects: variation in environmental drivers (air and soil temperature, solar radiation, vapor pressure deficit, and soil water content) and variation in the biotic response to this environmental forcing (as characterized by the model parameters). The model is applied to a 9‐year data set from the Howland AmeriFlux site, a spruce‐dominated forest in Maine, USA. Gap‐filled flux measurements at this site indicate that the forest has been sequestering, on average, 190 g C m⁻² yr⁻¹, with a range from 130 to 270 g C m⁻² yr⁻¹. Our fitted model predicts somewhat more uptake (mean 270 g C m⁻² yr⁻¹), but interannual variation is similar, and wavelet variance analyses indicate good agreement between tower measurements and model predictions across a wide range of timescales (hours to years). Associated with the interannual variation in NEE are clear differences among years in model parameters for both R_eco and P_gross. Analysis of model predictions suggests that, at the annual time step, about 40% of the variance in modeled NEE can be attributed to variation in environmental drivers, and 55% to variation in the biotic response to this forcing. As model predictions are aggregated at longer timescales (from individual days to months to calendar year), variation in environmental drivers becomes progressively less important, and variation in the biotic response becomes progressively more important, in determining the modeled flux. There is a strong negative correlation between modeled annual P_gross and R_eco (r=−0.93, P≤0.001); two possible explanations for this correlation are discussed. The correlation promotes homeostasis of NEE: the interannual variation in modeled NEE is substantially less than that for either P_gross or R_eco     

Physiological and environmental regulation of interannual variability in CO2 exchange on rangelands in the western United States

For most ecosystems, net ecosystem exchange of CO₂ (NEE) varies within and among years in response to environmental change. We analyzed measurements of CO₂ exchange from eight native rangeland ecosystems in the western United States (58 site‐years of data) in order to determine the contributions of photosynthetic and respiratory (physiological) components of CO₂ exchange to environmentally caused variation in NEE. Rangelands included Great Plains grasslands, desert shrubland, desert grasslands, and sagebrush steppe. We predicted that (1) week‐to‐week change in NEE and among‐year variation in the response of NEE to temperature, net radiation, and other environmental drivers would be better explained by change in maximum rates of ecosystem photosynthesis (A_max) than by change in apparent light‐use efficiency (α) or ecosystem respiration at 10 °C (R₁₀) and (2) among‐year variation in the responses of NEE, A_max, and α to environmental drivers would be explained by changes in leaf area index (LAI). As predicted, NEE was better correlated with A_max than α or R₁₀ for six of the eight rangelands. Week‐to‐week variation in NEE and physiological parameters correlated mainly with time‐lagged indices of precipitation and water‐related environmental variables, like potential evapotranspiration, for desert sites and with net radiation and temperature for Great Plains grasslands. For most rangelands, the response of NEE to a given change in temperature, net radiation, or evaporative demand differed among years because the response of photosynthetic parameters (A_max, α) to environmental drivers differed among years. Differences in photosynthetic responses were not explained by variation in LAI alone. A better understanding of controls on canopy photosynthesis will be required to predict variation in NEE of rangeland ecosystems.     

Canopy photosynthesis of six major arable crops is enhanced under diffuse light due to canopy architecture

Diffuse radiation generally increases photosynthetic rates if total radiation is kept constant. Different hypotheses have been proposed to explain this enhancement of photosynthesis, but conclusive results over a wide range of diffuse conditions or about the effect of canopy architecture are lacking. Here, we show the response of canopy photosynthesis to different fractions of diffuse light conditions for five major arable crops (pea, potato, wheat, barley, rapeseed) and cover crops characterized by different canopy architecture. We used 13 years of flux and microclimate measurements over a field with a typical 4 year crop rotation scheme in Switzerland. We investigated the effect of diffuse light on photosynthesis over a gradient of diffuse light fractions ranging from 100% diffuse (overcast sky) to 11% diffuse light (clear‐sky conditions). Gross primary productivity (GPP) increased with diffuse fraction and thus was greater under diffuse than direct light conditions if the absolute photon flux density per unit surface area was kept constant. Mean leaf tilt angle (MTA) and canopy height were found to be the best predictors of the diffuse versus direct radiation effect on photosynthesis. Climatic factors, such as the drought index and growing degree days (GDD), had a significant influence on initial quantum yield under direct but not diffuse light conditions, which depended primarily on MTA. The maximum photosynthetic rate at 2,000 µmol m^?2 s^?1 photosynthetically active radiation under direct conditions strongly depended on GDD, MTA, leaf area index (LAI) and the interaction between MTA and LAI, while under diffuse conditions, this parameter depended mostly on MTA and only to a minor extent on canopy height and their interaction. The strongest photosynthesis enhancement under diffuse light was found for wheat, barley and rapeseed, whereas the lowest was for pea. Thus, we suggest that measuring canopy architecture and diffuse radiation will greatly improve GPP estimates of global cropping systems.     

Divergent long‐term trends and interannual variation in ecosystem resource use efficiencies of a southern boreal old black spruce forest 1999–2017

Long‐term trends in ecosystem resource use efficiencies (RUEs) and their controlling factors are key pieces of information for understanding how an ecosystem responds to climate change. We used continuous eddy covariance and microclimate data over the period 1999–2017 from a 120‐year‐old black spruce stand in central Saskatchewan, Canada, to assess interannual variability, long‐term trends, and key controlling factors of gross ecosystem production (GEP) and the RUEs of carbon (CUE = net primary production [NPP]/GEP), light (LUE = GEP/absorbed photosynthetic radiation [APAR]), and water (WUE = GEP/evapotranspiration [E]). At this site, annual GEP has shown an increasing trend over the 19 years (p < 0.01), which may be attributed to rising atmospheric CO₂ concentration. Interannual variability in GEP, aside from its increasing trend, was most strongly related to spring temperatures. Associated with the significant increase in annual GEP were relatively small changes in NPP, APAR, and E, so that annual CUE showed a decreasing trend and annual LUE and WUE showed increasing trends over the 19 years. The long‐term trends in the RUEs were related to the increasing CO₂ concentration. Further analysis of detrended RUEs showed that their interannual variation was impacted most strongly by air temperature. Two‐factor linear models combining CO₂ concentration and air temperature performed well (R²~0.60) in simulating annual RUEs. LUE and WUE were positively correlated both annually and seasonally, while LUE and CUE were mostly negatively correlated. Our results showed divergent long‐term trends among CUE, LUE, and WUE and highlighted the need to account for the combined effects of climatic controls and the ‘CO₂ fertilization effect’ on long‐term variations in RUEs. Since most RUE‐based models rely primarily on one resource limitation, the observed patterns of relative change among the three RUEs may have important implications for RUE‐based modeling of C fluxes.     

Scaling gross ecosystem production at Harvard Forest with remote sensing: a comparison of estimates from a constrained quantum-use efficiency model and eddy correlation

Two independent methods of estimating gross ecosystem production (GEP) were compared over a period of 2 years at monthly integrals for a mixed forest of conifers and deciduous hardwoods at Harvard Forest in central Massachusetts. Continuous eddy flux measurements of net ecosystem exchange (NEE) provided one estimate of GEP by taking day to night temperature differences into account to estimate autotrophic and heterotrophic respiration. GEP was also estimated with a quantum efficiency model based on measurements of maximum quantum efficiency (Qmax), seasonal variation in canopy phenology and chlorophyll content, incident PAR, and the constraints of freezing temperatures and vapour pressure deficits on stomatal conductance. Quantum efficiency model estimates of GEP and those derived from eddy flux measurements compared well at monthly integrals over two consecutive years (R²= 0–98). Remotely sensed data were acquired seasonally with an ultralight aircraft to provide a means of scaling the leaf area and leaf pigmentation changes that affected the light absorption of photosynthetically active radiation to larger areas. A linear correlation between chlorophyll concentrations in the upper canopy leaves of four hardwood species and their quantum efficiencies (R²= 0–99) suggested that seasonal changes in quantum efficiency for the entire canopy can be quantified with remotely sensed indices of chlorophyll. Analysis of video data collected from the ultralight aircraft indicated that the fraction of conifer cover varied from < 7% near the instrument tower to about 25% for a larger sized area. At 25% conifer cover, the quantum efficiency model predicted an increase in the estimate of annual GEP of < 5% because unfavourable environmental conditions limited conifer photosynthesis in much of the non-growing season when hardwoods lacked leaves.     

Remote sensing of heterogeneity in photosynthetic efficiency, electron transport and dissipation of excess light in Populus deltoides stands under ambient and elevated CO2 concentrations, and in a tropical forest canopy, using a new laser-induced fluorescence transient device

Determining the spatial and temporal diversity of photosynthetic processes in forest canopies presents a challenge to the evaluation of biological feedbacks needed for improvement of carbon and climate models. Limited access with portable instrumentation, especially in the outer canopy, makes remote sensing of these processes a priority in experimental ecosystem and climate change research. Here, we describe the application of a new, active, chlorophyll fluorescence measurement system for remote sensing of light use efficiency, based on analysis of laser‐induced fluorescence transients (LIFT). We used mature stands of Populus grown at ambient (380 ppm) and elevated CO₂ (1220 ppm) in the enclosed agriforests of the Biosphere 2 Laboratory (B2L) to compare parameters of photosynthetic efficiency, photosynthetic electron transport, and dissipation of excess light measured by LIFT and by standard on‐the‐leaf saturating flash methods using a commercially available pulse‐modulated chlorophyll fluorescence instrument (Mini‐PAM). We also used LIFT to observe the diel courses of these parameters in leaves of two tropical forest dominants, Inga and Pterocarpus, growing in the enclosed model tropical forest of B2L. Midcanopy leaves of both trees showed the expected relationships among chlorophyll fluorescence‐derived photosynthetic parameters in response to sun exposure, but, unusually, both displayed an afternoon increase in nonphotochemical quenching in the shade, which was ascribed to reversible inhibition of photosynthesis at high leaf temperatures in the enclosed canopy. Inga generally showed higher rates of photosynthetic electron transport, but greater afternoon reduction in photosynthetic efficiency. The potential for estimation of the contribution of outer canopy photosynthesis to forest CO₂ assimilation, and assessment of its response to environmental stress using remote sensing devices such as LIFT, is briefly discussed.     

Can exploiting natural genetic variation in leaf photosynthesis contribute to increasing rice productivity? A simulation analysis

Rice productivity can be limited by available photosynthetic assimilates from leaves. However, the lack of significant correlation between crop yield and leaf photosynthetic rate (A) is noted frequently. Engineering for improved leaf photosynthesis has been argued to yield little increase in crop productivity because of complicated constraints and feedback mechanisms when moving up from leaf to crop level. Here we examined the extent to which natural genetic variation in A can contribute to increasing rice productivity. Using the mechanistic model GECROS, we analysed the impact of genetic variation in A on crop biomass production, based on the quantitative trait loci for various photosynthetic components within a rice introgression line population. We showed that genetic variation in A of 25% can be scaled up equally to crop level, resulting in an increase in biomass of 22–29% across different locations and years. This was probably because the genetic variation in A resulted not only from Rubisco (ribulose 1,5‐bisphosphate carboxylase/oxygenase)‐limited photosynthesis but also from electron transport‐limited photosynthesis; as a result, photosynthetic rates could be improved for both light‐saturated and light‐limited leaves in the canopy. Rice productivity could be significantly improved by mining the natural variation in existing germ‐plasm, especially the variation in parameters determining light‐limited photosynthesis.     

Estimating photosynthetic rate and annual carbon gain in conifers from specific leaf weight and leaf biomass

Summary Canopy photosynthesis is difficult to measure directly or to predict with complex models demanding knowledge of seasonal variation in environmental and physiological properties of the canopy. Trees in particular offer a challenge with their large, aerodynamically rough and seasonally-changing canopy properties. In this paper we assess the possibility of using specific leaf weight to predict seasonal and annual net photosynthetic rate in deciduous (Larix sp.) and evergreen (Picea abies) conifers.Annual photosynthetic rate and specific leaf weight of different positions of the crown in both species were highly correlated (r ²=0.930). Annual carbon uptake by different segments in a mature P. abies crown was closely related to leaf biomass. The relationship was improved by adjusting the leaf biomass of each segment in regard to its specific leaf weight relative to the maximum found in the canopy. The adjustment accounted for associated differences in photosynthetic activity. This combined structural index (leaf biomassxrelative specific leaf weight) could, when calibrated, predict the total annual carbon uptake by different parts of the crown. If direct measurements of photosynthesis are not available, the combined structural index may still serve as a comparative estimator of annual carbon uptake.     

Effects of photoinhibition on whole-plant carbon gain assessed with a photosynthesis model

A canopy photosynthesis model was modified to assess the effect of photoinhibition on whole‐plant carbon gain. Photoinhibitory changes in maximum quantum yield of photosystem II (F_v/F_m) could be explained solely from a parameter (Lflux) calculated from the light micro‐environment of the leaves. This relationship between F_v/F_m and the intercepted cumulative light dose, integrated and equally weighted over several hours was incorporated into the model. The effect of photoinhibition on net photosynthesis was described through relationships between photoinhibition and the shaping parameters of the photosynthetic light‐response curve (quantum use efficiency, convexity, and maximum capacity). This new aspect of the model was then validated by comparing measured field data (diurnal courses of F_v/F_m) with simulation results. Sensitivity analyses revealed that the extent of photoinhibitory reduction of whole‐plant photosynthesis was strongly dependent on the structural parameters (LAI and leaf angle). Simulations for a Mediterranean evergreen oak, Quercus coccifera, under climatic conditions which cause mild photoinhibition revealed a daily loss of 7·5–8·5% of potential carbon gain in the upper sunlit canopy layers, a 3% loss in the bottom canopy, and an overall loss of 6·1%. Thus, this canopy photoinhibition model (CANO‐PI) allows the quantitative evaluation of photoinhibition effects on primary production.     

Canopy photosynthetic production in a Japanese larch forest. II. Estimation of the canopy photosynthetic production

Seasonal changes and yearly gross canopy photosynthetic production were estimated for an 18 year old Japanese larch (Larix leptolepis) forest between 1982 and 1984. A canopy photosynthesis model was applied for the estimation, which took into account the effect of light interception by the non-photosynthetic organs. Seasonal changes in photosynthetic ability, amount of canopy leaf area and light environment within the canopy were also taken into account. Amount of leaf area was estimated by the leaf area growth of a single leaf. The change of light environment within the canopy during the growing season was estimated with a light penetration model and the leaf increment within the canopy. Canopy respiration and surplus production were calculated as seasonal and yearly values for the three years studied. Mean yearly estimates of canopy photosynthesis, canopy respiration and surplus production were 37, 13 and 23 tCO₂ ha⁻¹ year⁻¹, respectively. Vertical trend, seasonal changes and yearly values of the estimates were analyzed in relation to environmental and stand factors.     

The response of stomatal conductance to seasonal drought in tropical forests

Stomata regulate CO₂ uptake for photosynthesis and water loss through transpiration. The approaches used to represent stomatal conductance (g_s) in models vary. In particular, current understanding of drivers of the variation in a key parameter in those models, the slope parameter (i.e. a measure of intrinsic plant water‐use‐efficiency), is still limited, particularly in the tropics. Here we collected diurnal measurements of leaf gas exchange and leaf water potential (Ψ_leaf), and a suite of plant traits from the upper canopy of 15 tropical trees in two contrasting Panamanian forests throughout the dry season of the 2016 El Niño. The plant traits included wood density, leaf‐mass‐per‐area (LMA), leaf carboxylation capacity (V_c,max), leaf water content, the degree of isohydry, and predawn Ψ_leaf. We first investigated how the choice of four commonly used leaf‐level g_s models with and without the inclusion of Ψ_leaf as an additional predictor variable influence the ability to predict g_s, and then explored the abiotic (i.e. month, site‐month interaction) and biotic (i.e. tree‐species‐specific characteristics) drivers of slope parameter variation. Our results show that the inclusion of Ψ_leaf did not improve model performance and that the models that represent the response of g_s to vapor pressure deficit performed better than corresponding models that respond to relative humidity. Within each g_s model, we found large variation in the slope parameter, and this variation was attributable to the biotic driver, rather than abiotic drivers. We further investigated potential relationships between the slope parameter and the six available plant traits mentioned above, and found that only one trait, LMA, had a significant correlation with the slope parameter (R² = 0.66, n = 15), highlighting a potential path towards improved model parameterization. This study advances understanding of g_s dynamics over seasonal drought, and identifies a practical, trait‐based approach to improve modeling of carbon and water exchange in tropical forests.     

Can light-saturated photosynthesis in lowland tropical forests be estimated by one light level?

Leaf-level net photosynthesis (A_n) estimates and associated photosynthetic parameters are crucial for accurately parameterizing photosynthesis models. For tropical forests, such data are poorly available and collected at variable light conditions. To avoid over- or underestimation of modeled photosynthesis, it is critical to know at which photosynthetic photon flux density (PPFD) photosynthesis becomes light-saturated. We studied the dependence of A_n on PPFD in two tropical forests in French Guiana. We estimated the light saturation range, including the lowest PPFD level at which A_sat (A_n at light saturation) is reached, as well as the PPFD range at which A_sat remained unaltered. The light saturation range was derived from photosynthetic light-response curves, and within-canopy and interspecific differences were studied. We observed wide light saturation ranges of A_n. Light saturation ranges differed among canopy heights, but a PPFD level of 1,000 µmol m⁻² s⁻¹ was common across all heights, except for pioneer trees species that did not reach light saturation below 2,000 µmol m⁻² s⁻¹. A light intensity of 1,000 µmol m⁻² s⁻¹ sufficed for measuring A_sat of climax species at our study sites, independent of the species or the canopy height. Because of the wide light saturation ranges, results from studies measuring A_sat at higher PPFD levels (for upper canopy leaves up to 1,600 µmol m⁻² s⁻¹) are comparable with studies measuring at 1,000 µmol m⁻² s⁻¹.     

PHOTOACCLIMATION OF PHOTOSYNTHESIS IRRADIANCE RESPONSE CURVES AND PHOTOSYNTHETIC PIGMENTS IN MICROALGAE AND CYANOBACTERIA1

The photosynthesis‐irradiance response (PE) curve, in which mass‐specific photosynthetic rates are plotted versus irradiance, is commonly used to characterize photoacclimation. The interpretation of PE curves depends critically on the currency in which mass is expressed. Normalizing the light‐limited rate to chl a yields the chl a‐specific initial slope (α^chl). This is proportional to the light absorption coefficient (a^chl), the proportionality factor being the photon efficiency of photosynthesis (φ_m). Thus, α^chl is the product of a^chl and φ_m. In microalgae α^chl typically shows little (<20%) phenotypic variability because declines of φ_m under conditions of high‐light stress are accompanied by increases of a^chl. The variation of α^chl among species is dominated by changes in a^chl due to differences in pigment complement and pigment packaging. In contrast to the microalgae, α^chl declines as irradiance increases in the cyanobacteria where phycobiliproteins dominate light absorption because of plasticity in the phycobiliprotein:chl a ratio. By definition, light‐saturated photosynthesis (P_m) is limited by a factor other than the rate of light absorption. Normalizing P_m to organic carbon concentration to obtain P_m^C allows a direct comparison with growth rates. Within species, P_m^C is independent of growth irradiance. Among species, P_m^C covaries with the resource‐saturated growth rate. The chl a:C ratio is a key physiological variable because the appropriate currencies for normalizing light‐limited and light‐saturated photosynthetic rates are, respectively, chl a and carbon. Typically, chl a:C is reduced to about 40% of its maximum value at an irradiance that supports 50% of the species‐specific maximum growth rate and light‐harvesting accessory pigments show similar or greater declines. In the steady state, this down‐regulation of pigment content prevents microalgae and cyanobacteria from maximizing photosynthetic rates throughout the light‐limited region for growth. The reason for down‐regulation of light harvesting, and therefore loss of potential photosynthetic gain at moderately limiting irradiances, is unknown. However, it is clear that maximizing the rate of photosynthetic carbon assimilation is not the only criterion governing photoacclimation.     

Chlorophyll fluorescence tracks seasonal variations of photosynthesis from leaf to canopy in a temperate forest

Accurate estimation of terrestrial gross primary productivity (GPP) remains a challenge despite its importance in the global carbon cycle. Chlorophyll fluorescence (ChlF) has been recently adopted to understand photosynthesis and its response to the environment, particularly with remote sensing data. However, it remains unclear how ChlF and photosynthesis are linked at different spatial scales across the growing season. We examined seasonal relationships between ChlF and photosynthesis at the leaf, canopy, and ecosystem scales and explored how leaf‐level ChlF was linked with canopy‐scale solar‐induced chlorophyll fluorescence (SIF) in a temperate deciduous forest at Harvard Forest, Massachusetts, USA. Our results show that ChlF captured the seasonal variations of photosynthesis with significant linear relationships between ChlF and photosynthesis across the growing season over different spatial scales (R² = 0.73, 0.77, and 0.86 at leaf, canopy, and satellite scales, respectively; P < 0.0001). We developed a model to estimate GPP from the tower‐based measurement of SIF and leaf‐level ChlF parameters. The estimation of GPP from this model agreed well with flux tower observations of GPP (R² = 0.68; P < 0.0001), demonstrating the potential of SIF for modeling GPP. At the leaf scale, we found that leaf F_q’/F_m’, the fraction of absorbed photons that are used for photochemistry for a light‐adapted measurement from a pulse amplitude modulation fluorometer, was the best leaf fluorescence parameter to correlate with canopy SIF yield (SIF/APAR, R² = 0.79; P < 0.0001). We also found that canopy SIF and SIF‐derived GPP (GPP_SIF) were strongly correlated to leaf‐level biochemistry and canopy structure, including chlorophyll content (R² = 0.65 for canopy GPP_SIF and chlorophyll content; P < 0.0001), leaf area index (LAI) (R² = 0.35 for canopy GPP_SIF and LAI; P < 0.0001), and normalized difference vegetation index (NDVI) (R² = 0.36 for canopy GPP_SIF and NDVI; P < 0.0001). Our results suggest that ChlF can be a powerful tool to track photosynthetic rates at leaf, canopy, and ecosystem scales.     

Do all chlorophyll fluorescence emission wavelengths capture the spring recovery of photosynthesis in boreal evergreen foliage?

Chlorophyll a fluorescence (ChlF) is closely related to photosynthesis and can be measured remotely using multiple spectral features as solar‐induced fluorescence (SIF). In boreal regions, SIF shows particular promise as an indicator of photosynthesis, in part because of the limited variation of seasonal light absorption in these ecosystems. Seasonal spectral changes in ChlF could yield new information on processes such as sustained nonphotochemical quenching (NPQ_S) but also disrupt the relationship between SIF and photosynthesis. We followed ChlF and functional and biochemical properties of Pinus sylvestris needles during the photosynthetic spring recovery period to answer the following: (a) How ChlF spectra change over seasonal timescales? (b) How pigments, NPQ_S, and total photosynthetically active radiation (PAR) absorption drive changes of ChlF spectra? (c) Do all ChlF wavelengths track photosynthetic seasonality? We found seasonal ChlF variation in the red and far‐red wavelengths, which was strongly correlated with NPQ_S, carotenoid content, and photosynthesis (enhanced in the red), but not with PAR absorption. Furthermore, a rapid decrease in red/far‐red ChlF ratio occurred in response to a cold spell, potentially relating to the structural reorganization of the photosystems. We conclude that all current SIF retrieval features can track seasonal photosynthetic dynamics in boreal evergreens, but the full SIF spectra provides additional insight.     

Combining meteorology, eddy fluxes, isotope measurements, and modeling to understand environmental controls of carbon isotope discrimination at the canopy scale

Estimates of terrestrial carbon isotope discrimination are useful to quantify the terrestrial carbon sink. Carbon isotope discrimination by terrestrial ecosystems may vary on seasonal and interannual time frames, because it is affected by processes (e.g. photosynthesis, stomatal conductance, and respiration) that respond to variable environmental conditions (e.g. air humidity, temperature, light). In this study, we report simulations of the temporal variability of canopy‐scale C₃ photosynthetic carbon isotope discrimination obtained with an ecophysiologically based model (ISOLSM) designed for inclusion in global models. ISOLSM was driven by half‐hourly meteorology, and parameterized with eddy covariance measurements of carbon and energy fluxes and foliar carbon isotope ratios from a pine forest in Metolius (OR). Comparing simulated carbon and energy fluxes with observations provided a range of parameter values that optimized the simulated fluxes. We found that the sensitivity of photosynthetic carbon isotope discrimination to the slope of the stomatal conductance equation (m, Ball–Berry constant) provided an additional constraint to the model, reducing the wide parameter space obtained from the fluxes alone. We selected values of m that resulted in similar simulated long‐term discrimination as foliar isotope ratios measured at the site. The model was tested with ¹³C measurements of ecosystem (δ_R) and foliar (δ_f) respiration. The daily variability of simulated ¹³C values of assimilated carbon (δ_A) was similar to that of observed δ_f, and higher than that of observed and simulated δ_R. We also found similar relationships between environmental factors (i.e. vapor pressure deficit) and simulated δ_R as measured in ecosystem surveys of δ_R. Therefore, ISOLSM reasonably simulated the short‐term variability of δ_A controlled by atmospheric conditions at the canopy scale, which can be useful to estimate the variability of terrestrial isotope discrimination. Our study also shows that including the capacity to simulate carbon isotope discrimination, together with simple ecosystem isotope measurements, can provide a useful constraint to land surface and carbon balance models.     

Carbon sequestration in boreal jack pine stands following harvesting

A large area of boreal jack pine (Pinus banksiana Lamb.) forest in Canada is recovering from clear‐cut harvesting, and the carbon (C) balance of these regenerating forests remains uncertain. Net ecosystem CO₂ exchange was measured using the eddy‐covariance technique at four jack pine sites representing different stages of stand development: three postharvest sites (HJP02, HJP94, and HJP75) and one preharvest site (OJP). The four sites, located in the southern Canadian boreal forest, Saskatchewan, Canada, are typical of low productivity jack pine stands and were 2, 10, 29, and 90 years old in 2004, respectively. Mean annual net ecosystem production (NEP) for 2004 and 2005 was ?137±11, 19±16, 73±28, and 22±30 g C m^?2 yr^?1 at HJP02, HJP94, HJP75 and OJP, respectively, showing the postharvest jack pine stands to be moderate C sources immediately after harvesting, weak sinks at 10 years, moderate C sinks at 30 years, then weak C sinks at 90 years. Mean annual gross ecosystem photosynthesis (GEP) for the 2 years was 96±10, 347±20, 576±34, and 583±35 g C m^?2 yr^?1 at HJP02, HJP94, HJP75, and OJP, respectively. The ratio of annual ecosystem respiration (R) to annual GEP was 2.51±0.15, 0.95±0.04, 0.87±0.03, and 0.96±0.03. Seasonally, NEP peaked in May or June at all four sites but GEP and R were highest in July. R at a reference soil temperature of 10 °C, ecosystem quantum yield and photosynthetic capacity were lowest for the 2‐year‐old stand. R was most sensitive to soil temperature for the 90‐year‐old stand. The primary source of variability in NEP over the course of succession of the jack pine ecosystem following harvesting was stand age due to the changes in leaf area index. Intersite variability in GEP and R was an order of magnitude greater than interannual variability at OJP. For both young and old stands, GEP had greater interannual variability than R and played a more important role than R in interannual variation in NEP. Based on year‐round flux measurements from 2000 to 2005, the 10‐year stand had larger interannual variability in GEP and R than the 90‐year stand. Interannual variability in NEP was driven primarily by early‐growing‐season temperature and growing‐season length. Photosynthesis played a dominant role in the rapid rise in NEP early in stand development. Late in stand development, however, the subtle decrease in NEP resulted primarily from increasing respiration.