Many studies have shown that solar-induced fluorescence (SIF) has a good potential to predict gross primary production (GPP) of vegetation. What we measured by remote sensing or near-surface ...platforms is top-of-canopy (TOC) SIF (SIFtoc), which is not necessarily equal or proportional to total emitted SIF (SIFtot) from the entire canopy due to the (re)absorption and scattering effects. However, photosynthesis, the process that plants use to fix carbon from the atmosphere, occurs at the entire vertical canopy. Here, by using the recollision theory, we calculated SIFtot at 760 nm from the measured SIFtoc, hyperspectral reflectance (R), canopy interception (i) and leaf albedo (ωl). Among them, both SIFtoc and R can be obtained from concurrent TOC spectral measurements; i and ωl in the near-infrared region can be estimated from the open access datasets with a good accuracy. Our result confirms that the measured SIFtoc only accounts for a small fraction of SIFtot: the above-the-canopy sensor can only “see” on average 22.9% of SIFtot at Harvard Forest. SIFtot has the following advantages over SIFtoc in estimating GPP: (1) SIFtot improves the diurnal estimate of canopy GPP, especially capable to capture the midday depression of photosynthesis which may cause the large discrepancies between SIFtoc and GPP on a diurnal basis, (2) SIFtot produces a stronger correlation with GPP from plants with complex canopy structure or under sky conditions with more diffuse irradiance, and (3) the SIFtot-GPP relationship shows a stronger resilience to environmental stresses. The fluorescence escape ratio (fesc), the ratio between SIFtoc multiplied by π and SIFtot, is mostly determined by the sun-canopy-sensor geometry and leaf inclination distribution. The effect of LAI and the leaf chlorophyll concentration on fesc is marginal at the 760 nm wavelength. Our results suggest that converting SIFtoc into SIFtot provides a better tool to understand and estimate GPP.
Display omitted
•Total emitted SIF (SIFtot) can be estimated from top-of-canopy SIF (SIFtoc).•The sensor only received on average 22.9% of total emitted SIF.•SIFtot improves the diurnal estimate of canopy GPP.•SIFtot produced a stronger correlation with GPP for plants with complex structure.•The SIFtot-GPP relationship shows a stronger resilience to environmental stresses.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
In this study, we used the remotely-sensed data from the Moderate Resolution Imaging Spectrometer (MODIS), meteorological and eddy flux data and an artificial neural networks (ANNs) technique to ...develop a daily evapotranspiration
(ET) product for the period of 2004–2005 for the conterminous U.S. We then estimated and analyzed the regional water-use efficiency (WUE) based on the developed ET and MODIS gross primary production (GPP) for the region. We first trained the ANNs to predict evapotranspiration fraction (EF) based on the data at 28 AmeriFlux sites between 2003 and 2005. Five remotely-sensed variables including land surface temperature (LST), normalized difference vegetation index (NDVI), normalized difference water index (NDWI), leaf area index (LAI) and photosynthetically active radiation (PAR) and ground-measured air temperature and wind velocity were used. The daily ET was calculated by multiplying net radiation flux derived from remote sensing products with EF. We then evaluated the model performance by comparing modeled ET with the data at 24 AmeriFlux sites in 2006. We found that the ANNs predicted daily ET well (
R
2
=
0.52–0.86). The ANNs were applied to predict the spatial and temporal distributions of daily ET for the conterminous U.S. in 2004 and 2005. The ecosystem WUE for the conterminous U.S. from 2004 to 2005 was calculated using MODIS GPP products (MOD17) and the estimated ET. We found that all ecosystems' WUE-drought relationships showed a two-stage pattern. Specifically, WUE increased when the intensity of drought was moderate; WUE tended to decrease under severe drought. These findings are consistent with the observations that WUE does not monotonously increase in response to water stress. Our study suggests a new water-use efficiency mechanism should be considered in ecosystem modeling. In addition, this study provides a high spatial and temporal resolution ET dataset, an important product for climate change and hydrological cycling studies for the MODIS era.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Coastal wetlands are large reservoirs of soil carbon (C). However, the annual C accumulation rates contributing to the C storage in these systems have yet to be spatially estimated on a large scale. ...We synthesized C accumulation rate (CAR) in tidal wetlands of the conterminous United States (US), upscaled the CAR to national scale, and predicted trends based on climate change scenarios. Here, we show that the mean CAR is 161.8 ± 6 g Cm
yr
, and the conterminous US tidal wetlands sequestrate 4.2-5.0 Tg C yr
. Relative sea level rise (RSLR) largely regulates the CAR. The tidal wetland CAR is projected to increase in this century and continue their C sequestration capacity in all climate change scenarios, suggesting a strong resilience to sea level rise. These results serve as a baseline assessment of C accumulation in tidal wetlands of US, and indicate a significant C sink throughout this century.
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 Fq’/Fm’, 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 (GPPSIF) were strongly correlated to leaf‐level biochemistry and canopy structure, including chlorophyll content (R2 = 0.65 for canopy GPPSIF and chlorophyll content; P < 0.0001), leaf area index (LAI) (R2 = 0.35 for canopy GPPSIF and LAI; P < 0.0001), and normalized difference vegetation index (NDVI) (R2 = 0.36 for canopy GPPSIF 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.
We studied the relationship between fluorescence and photosynthesis at the leaf, canopy, and larger scales using both field‐based and satellite remote sensing data across the entire growing season. We found that fluorescence captured the seasonal variations of photosynthesis with a linear relationship over different spatial scales. Our results suggest that fluorescence is a useful proxy to monitor photosynthesis at leaf, canopy, and ecosystem scales.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
•SIF has a good potential to predict transpiration (T).•The combinations of SIF bands has better performance in estimating T.•The relation between SIF and T appears non-linear under stressful ...conditions.•Observation time has no clear impact on the SIF-T relationships.•Temporal aggregation to daily scales can further enhance the SIF-T correlations.
By utilizing continuous measurements of water fluxes and solar-induced chlorophyll fluorescence (SIF) over the entire growing season, we exploit the potential of broadband SIF in predicting plant transpiration (T) in a temperate forest. After reconstructing the full SIF spectrum from the selected absorption lines and simulations from the SCOPE (Soil Canopy Observation Photochemistry and Energy fluxes) model, linear regression (LR) and Gaussian processes regression (GPR) models are used to analyze the relation between T and combinations of different SIF bands. We find that SIF emissions in the near-infrared spectrum (at 720 nm, 740 nm and 760 nm) are more sensitive to T than SIF emissions in the red spectrum (at 685 nm and 687 nm). While conditions such as light and heat stress decouple the relationship between single-band SIF and T, the combination of different SIF bands allows the retrieval of reliable T estimates even in these conditions. Overall, we find that the use of SIF as a proxy for T yields estimates that are at least as accurate as those from traditional transpiration models such as the Penman-Monteith equation, which are input demanding and complex to apply to in situ and satellite data. Specifically, we find that (1) the SIF-T relationship deteriorates when Photosynthetically Active Radiation (PAR), vapor pressure deficit and air temperature exceed biological optimal thresholds; (2) a high leaf area index exerts a negative impact on the SIF-T correlation due to increasing scattering and (re)absorption of the SIF signal; (3) the SIF-T relationship does not change depending on the observation time during the day; and (4) temporal aggregation to days further enhanced the SIF-T correlations. Altogether, our results provide the first ground-based evidence that SIF emission has potential to be a close predictor of plant transpiration, especially when a combination of different SIF bands is considered.
Full text
Available for:
GEOZS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
We assess the performance of optical images, reflectance-based vegetation indices and solar induced chlorophyll fluorescence (SIF) datasets with various spatial and temporal resolutions in monitoring ...the GPP-based phenology in a temperate deciduous forest. If negative impacts due to coarse spatial and temporal resolutions are effectively reduced, we find that all these data can serve as good indicators of phenological metrics in the spring that are derived from GPP time series. However, the autumn phenological metrics derived from all reflectance-based datasets are later than the tower-based GPP estimates. This is because the reflectance-based observations estimate phenology by tracking physiological properties including leaf area index (LAI) and leaf chlorophyll content (Chl), which does not reflect instantaneous changes in phenophase transitions, and thus the estimated fall phenological events may be later than GPP-based phenology. In contrast, we find that SIF has a good potential to track seasonal transition of photosynthetic activities in both spring and fall seasons. The advantage of SIF in estimating the GPP-based phenology lies in its inherent link to photosynthesis activities such that SIF can respond quickly to all factors regulating phenological events. Despite uncertainties in phenological metrics estimated from current spaceborne SIF observations due to their coarse spatial and temporal resolutions, dates of the middle spring and autumn – the two most important metrics, can still be reasonably estimated from satellite SIF. Our study reveals that SIF provides a better way to monitor GPP-based phenological metrics.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Much progress has been made in methane modeling for the Arctic. However, there is still large uncertainty in emissions estimates due to the spatial variability in water table depth resulting from ...complex topographic gradients, and due to variations in methane production and oxidation due to complex freezing and thawing processes. Here we extended an extant methane emission module within a biogeochemistry model, the Terrestrial Ecosystem Model (TEM), to include a large‐scale hydrology model, the variable infiltration capacity (VIC) model. The VIC model provides the required inputs, including freezing and thawing fronts, soil temperature and moisture, to the methane module. The effect of topography on the redistribution of soil moisture and water table depth was explicitly modeled using the TOPMODEL approach. The coupled modeling framework was applied to the Yukon River basin at a spatial resolution of 1 km from 1986 to 2005. The simulations show that the average annual net emissions of CH4 from the region are 4.01 Tg CH4 yr−1. El Niño phenomena usually lead to positive emission anomalies, while decreases in net CH4 emissions may be associated with strong La Niña events. Precipitation was found to be more closely related to CH4 dynamics than to soil temperature and active layer depth during the study period. This study suggests that the effects of soil freezing and thawing processes and the effects of microtopography on hydrology should be considered in the quantification of CH4 emissions.
Key Points
Water table information is explicitly addressed in the methane modeling
The effect of freezing and thawing processes is also explicitly considered
Methane emissions in the Yukon River basin from 1986 to 2005
Globally, 15.5 million km² of land are currently identified as protected areas, which provide society with many ecosystem services including climate-change mitigation. Combining a global database of ...protected areas, a reconstruction of global land-use history, and a global biogeochemistry model, we estimate that protected areas currently sequester 0.5 Pg C annually, which is about one fifth of the carbon sequestered by all land ecosystems annually. Using an integrated earth systems model to generate climate and land-use scenarios for the twenty-first century, we project that rapid climate change, similar to high-end projections in IPCC's Fifth Assessment Report, would cause the annual carbon sequestration rate in protected areas to drop to about 0.3 Pg C by 2100. For the scenario with both rapid climate change and extensive landuse change driven by population and economic pressures, 5.6 million km² of protected areas would be converted to other uses, and carbon sequestration in the remaining protected areas would drop to near zero by 2100.
The escape probability of Solar-induced chlorophyll fluorescence (SIF) can be remotely estimated using reflectance measurements based on spectral invariants theory. This can then be used to correct ...the effects of canopy structure on canopy-leaving SIF. However, the feasibility of these estimation methods is untested in heterogeneous vegetation such as the discontinuous forest canopy layer under evaluation here. In this study, the Discrete Anisotropic Radiative Transfer (DART) model is used to simulate canopy-leaving SIF, canopy total emitted SIF, canopy interceptance, and the fraction of absorbed photosynthetically active radiation (fAPAR) in order to evaluate the estimation methods of SIF escape probability in discontinuous forest canopies. Our simulation results show that the normalized difference vegetation index (NDVI) can be used to partly eliminate the effects of background reflectance on the estimation of SIF escape probability in most cases, but fails to produce accurate estimations if the background is partly or totally covered by vegetation. We also found that SIF escape probabilities estimated at a high solar zenith angle have better estimation accuracy than those estimated at a lower solar zenith angle. Our results show that additional errors will be introduced to the estimation of SIF escape probability with the use of satellite products, especially when the product of leaf area index (LAI) and clumping index (CI) was underestimated. In other results, fAPAR has comparable estimation accuracy of SIF escape probability when compared to canopy interceptance. Additionally, fAPAR for the entire canopy has better estimation accuracy of SIF escape probability than fPAR for leaf only in sparse forest canopies. These results help us to better understand the current estimation results of SIF escape probability based on spectral invariants theory, and to improve its estimation accuracy in discontinuous forest canopies.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
PDF
