Deforestation in Latin America in the 2000s predominantly occurred outside of typical mature forests.

The role of tropical forests in the global carbon budget remains controversial, as carbon emissions from deforestation are highly uncertain. This high uncertainty arises from the use of either fixed forest carbon stock density or maps generated from satellite-based optical reflectance with limited sensitivity to biomass to generate accurate estimates of emissions from deforestation. New space missions aiming to accurately map the carbon stock density rely on direct measurements of the spatial structures of forests using lidar and radar. We found that lost forests are special cases, and their spatial structures can be directly measured by combining archived data acquired before and after deforestation by space missions principally aimed at measuring topography. Thus, using biomass mapping, we obtained new estimates of carbon loss from deforestation ahead of forthcoming space missions. Here, using a high-resolution map of forest loss and the synergy of radar and lidar to estimate the aboveground biomass density of forests, we found that deforestation in the 2000s in Latin America, one of the severely deforested regions, mainly occurred in forests with a significantly lower carbon stock density than typical mature forests. Deforestation areas with carbon stock densities lower than 20.0, 50.0, and 100.0 Mg C/ha accounted for 42.1%, 62.0%, and 83.3% of the entire deforested area, respectively. The average carbon stock density of lost forests was only 49.13 Mg C/ha, which challenges the current knowledge on the carbon stock density of lost forests (with a default value 100 Mg C/ha according to the Intergovernmental Panel on Climate Change Tier 1 estimates, or approximately 112 Mg C/ha used in other studies). This is demonstrated over both the entire region and the footprints of the spaceborne lidar. Consequently, our estimate of carbon loss from deforestation in Latin America in the 2000s was 253.0 ± 21.5 Tg C/year, which was considerably less than existing remote-sensing-based estimates, namely 400-600 Tg C/year. This indicates that forests in Latin America were most likely not a net carbon source in the 2000s compared to established carbon sinks. In previous studies, considerable effort has been devoted to rectify the underestimation of carbon sinks; thus, the overestimation of carbon emissions should be given sufficient consideration in global carbon budgets. Our results also provide solid evidence for the necessity of renewing knowledge on the role of tropical forests in the global carbon budget in the future using observations from new space missions.

Global annual wetland dataset at 30 m with a fine classification system from 2000 to 2022.

Wetlands play a key role in maintaining ecological balance and climate regulation. However, due to the complex and variable spectral characteristics of wetlands, there are no publicly available global 30-meter time-series wetland dynamic datasets at present. In this study, we present novel global 30 m annual wetland maps (GWL_FCS30D) using time-series Landsat imagery on the Google Earth Engine platform, covering the period of 2000-2022 and containing eight wetland subcategories. Specifically, we make full use of our prior globally distributed wetland training sample pool, and adopt the local adaptive classification and spatiotemporal consistency checking algorithm to generate annual wetland maps. The GWL_FCS30D maps were found to achieve an overall accuracy and Kappa coefficient of 86.95 ± 0.44% and 0.822, respectively, in 2020, and show great temporal variability in the United States and the European Union. We expect the dataset would provide vital support for wetland ecosystems protection and sustainable development.

Enhancing Leaf Area Index Estimation for Maize with Tower-Based Multi-Angular Spectral Observations.

The leaf area index (LAI) played a crucial role in ecological, hydrological, and climate models. The normalized difference vegetation index (NDVI) has been a widely used tool for LAI estimation. However, the NDVI quickly saturates in dense vegetation and is susceptible to soil background interference in sparse vegetation. We proposed a multi-angular NDVI (MAVI) to enhance LAI estimation using tower-based multi-angular observations, aiming to minimize the interference of soil background and saturation effects. Our methodology involved collecting continuous tower-based multi-angular reflectance and the LAI over a three-year period in maize cropland. Then we proposed the MAVI based on an analysis of how canopy reflectance varies with solar zenith angle (SZA). Finally, we quantitatively evaluated the MAVI's performance in LAI retrieval by comparing it to eight other vegetation indices (VIs). Statistical tests revealed that the MAVI exhibited an improved curvilinear relationship with the LAI when the NDVI is corrected using multi-angular observations (R2 = 0.945, RMSE = 0.345, rRMSE = 0.147). Furthermore, the MAVI-based model effectively mitigated soil background effects in sparse vegetation (R2 = 0.934, RMSE = 0.155, rRMSE = 0.157). Our findings demonstrated the utility of tower-based multi-angular spectral observations in LAI retrieval, having the potential to provide continuous data for validating space-borne LAI products. This research significantly expanded the potential applications of multi-angular observations.

China's current forest age structure will lead to weakened carbon sinks in the near future.

Forests are chiefly responsible for the terrestrial carbon sink that greatly reduces the buildup of CO2 concentrations in the atmosphere and alleviates climate change. Current predictions of terrestrial carbon sinks in the future have so far ignored the variation of forest carbon uptake with forest age. Here, we predict the role of China's current forest age in future carbon sink capacity by generating a high-resolution (30 m) forest age map in 2019 over China's landmass using satellite and forest inventory data and deriving forest growth curves using measurements of forest biomass and age in 3,121 plots. As China's forests currently have large proportions of young and middle-age stands, we project that China's forests will maintain high growth rates for about 15 years. However, as the forests grow older, their net primary productivity will decline by 5.0% ± 1.4% in 2050, 8.4% ± 1.6% in 2060, and 16.6% ± 2.8% in 2100, indicating weakened carbon sinks in the near future. The weakening of forest carbon sinks can be potentially mitigated by optimizing forest age structure through selective logging and implementing new or improved afforestation. This finding is important not only for the global carbon cycle and climate projections but also for developing forest management strategies to enhance land sinks by alleviating the age effect.

Solar-induced chlorophyll fluorescence imperfectly tracks the temperature response of photosynthesis in winter wheat.

Solar-induced fluorescence (SIF) is a promising proxy for photosynthesis, but it is unclear whether it performs well in tracking the gross primary productivity (GPP) under different environmental conditions. In this study, we investigated the dynamics of the two parameters from October 2020 to June 2021 in field-grown winter wheat (Triticum aestivum) and found that the ability of SIF to track GPP was weakened at low temperatures. Accounting for the coupling of light and temperature at a seasonal scale, we found that SIF yield showed a lower temperature sensitivity and had a lower but broader optimal temperature range compared with light-use efficiency (LUE), although both SIF yield and LUE decreased in low-temperature conditions. The discrepancy between the temperature responses of SIF yield and GPP caused an increase in the ratio of SIF/GPP in winter, which indicated the variation in the relationship between them during this period. The results of our study highlight the impact of low temperature on the relationship between SIF and GPP and show the necessity of reconsidering the dynamics of energy distribution inside plants under changing environments.

Residues of Culinary-Medicinal Winter Mushroom, Flammulina velutipes (Agaricomycetes), Cultivation as a Potential Source of Functional Skin Substitute with Multiple Bioactivities.

Residues generated during the cultivation of edible mushroom Flammulina velutipes are abundant and utilized with low efficiency. In this study, the composition and bioactivities of a skin substitute named TG05 obtained from residues of the F. velutipes cultivation process were investigated. The main composition of TG05 was considered to be chitin and it inhibited growth of Gram-positive Staphylococcus aureus and Gram-negative Pseudomonas aeruginosa. TG05 also suppressed the inflammatory response through the inducible nitric oxide synthase signaling pathway. Inflammation was attenuated by reducing the expression of tumor necrosis factor-α, interleukin (IL)-1ß, IL-6, and prostaglandin E2 at the transcription level. Furthermore, TG05 exhibited antioxidant activities based on hydroxyl, 2,2-diphenyl-1-picryl-hydrazy, 2,2'-azobis-(3-ethylbenzothiazoline-6-sulfonic acid), superoxide anion radical scavenging activity, and reducing power assays. However, the effect of TG05 was independent of hyaluronidase inhibitory activity. Taken together, specific mechanisms related to the notable wound-healing-promoting activity of TG05 were demonstrated, mainly attributable to its antimicrobial, anti-inflammatory, and antioxidant activities. Therefore, TG05 may have potential for use as a functional biomaterial in various applications.

Structural characterization of two Hericium erinaceus polysaccharides and their protective effects on the alcohol-induced gastric mucosal injury.

Hericium erinaceus, a traditional edible mushroom, is known as a medicine food homology to ameliorate gastrointestinal diseases. However, the relationship between the structural characteristics of Hericium erinaceus and its stomach-protecting activity remains unclear. Here, the structural properties of two polysaccharides from Hericium erinaceus, mycelium polysaccharide (HMP) and fruiting body polysaccharide (HFP) were investigated by spectral approaches. The results showed that the distribution of HMP was more uniform compared to HFP. Both HMP and HFP have triple helix structures, but the HMP conformation showed greater stability. Subsequently, the preventive effect of HMP and HFP on ethanol-induced gastric mucosal injury was also evaluated in rats and GES-1 cells, and it showed that both HMP and HFP had significant protective activity against gastric mucosal injury, but HMP showed better activity than HFP. These results suggested that conformational stability polysaccharide in Hericium erinaceus is more related to its gastric-protecting activity.

Study on the interaction of Hericium erinaceus mycelium polysaccharides and its degradation products with food additive silica nanoparticles.

Gastric mucosal injury is a common gastrointestinal disorder. Hericium erinaceus polysaccharide, the major active ingredient in Hericium erinaceus, can reduce gastric mucosal damage to some extent. In this study, two different products HMP-Vc and HMP-Ce were obtained by Vitamin C and cellulase degradation of Hericium erinaceus mycelium polysaccharide (HMP). The gastroprotective activity of polysaccharides and its interaction products with food additives silica nanoparticles (nSiO2) were studied in GES-1 cells. It was found that gastroprotective activity of HMP was significantly higher than that of degradation products, and the addition of nSiO2 could enhance this activity of HMP. The greatest difference between the degradation products and HMP was the reduction of the triple helix structure, which might be the reason of the gastroprotective activity was less than that of HMP. Moreover, nSiO2 might interact with HMP through hydrogen bonding to enhance its activity.

ValLAI_Crop, a validation dataset for coarse-resolution satellite LAI products over Chinese cropland.

Numerous validation efforts have been conducted over the last decade to assess the accuracy of global leaf area index (LAI) products. However, such efforts continue to face obstacles due to the lack of sufficient high-quality field measurements. In this study, a fine-resolution LAI dataset consisting of 80 reference maps was generated during 2003-2017. The direct destructive method was used to measure the field LAI, and fine-resolution LAI images were derived from Landsat images using semiempirical inversion models. Eighty reference LAI maps, each with an area of 3 km × 3 km and a percentage of cropland larger than 75%, were selected as the fine-resolution validation dataset. The uncertainty associated with the spatial scale effect was also provided. Ultimately, the fine-resolution reference LAI dataset was used to validate the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI product. The results indicate that the fine-resolution reference LAI dataset builds a bridge to link small sampling plots and coarse-resolution pixels, which is extremely important in validating coarse-resolution LAI products.

Optimizing the Empirical Parameters of the Data-Driven Algorithm for SIF Retrieval for SIFIS Onboard TECIS-1 Satellite.

Space-based solar-induced chlorophyll fluorescence (SIF) has been widely demonstrated as a great proxy for monitoring terrestrial photosynthesis and has been successfully retrieved from satellite-based hyperspectral observations using a data-driven algorithm. As a semi-empirical algorithm, the data-driven algorithm is strongly affected by the empirical parameters in the model. Here, the influence of the data-driven algorithm's empirical parameters, including the polynomial order (np), the number of feature vectors (nSV), the fluorescence emission spectrum function, and the fitting window used in the retrieval model, were quantitatively investigated based on the simulations of the SIF Imaging Spectrometer (SIFIS) onboard the First Terrestrial Ecosystem Carbon Inventory Satellite (TECIS-1). The results showed that the fitting window, np, and nSV were the three main factors that influenced the accuracy of retrieval. The retrieval accuracy was relatively higher for a wider fitting window; the root mean square error (RMSE) was lower than 0.7 mW m-2 sr-1 nm-1 with fitting windows wider than 735-758 nm and 682-691 nm for the far-red band and the red band, respectively. The RMSE decreased first and then increased with increases in np range from 1 to 5 and increased in nSV range from 2 to 20. According to the specifications of SIFIS onboard TECIS-1, a fitting window of 735-758 nm, a second-order polynomial, and four feature vectors are the optimal parameters for far-red SIF retrieval, resulting in an RMSE of 0.63 mW m-2 sr-1 nm-1. As for red SIF retrieval, using second-order polynomial and seven feature vectors in the fitting window of 682-697 nm was the optimal choice and resulted in an RMSE of 0.53 mW m-2 sr-1 nm-1. The optimized parameters of the data-driven algorithm can guide the retrieval of satellite-based SIF and are valuable for generating an accurate SIF product of the TECIS-1 satellite after its launch.

Analysis the alteration of systemic inflammation in old and young APP/PS1 mouse.

The impairment of cognitive function was considered as a major clinic feature in Alzheimer's disease (AD) patients. Thus, a number of researches related to AD were focused on the changes in brain. However, as a neurodegenerative disorder with systemic inflammation, the periphery organs may also play a key role in AD pathology. Here, we pose the hypothesis that histopathology and inflammatory response of periphery organs may alter with aging in APP/PS1 mouse model. Therefore, we performed immunohistochemical staining technology to double label Aß plaques and microglia cells in brain. The H&E staining was performed in periphery tissues and the mRNA expression of inflammatory factors IL-6, IL-10 and TNF-α were also determined. Next, the index of oxidative stress was measured. Consequently, the level of inflammatory factors was significantly increased in 24 months APP/PS1 mice. Furthermore, the enzyme activity of SOD, CAT and GSH were significantly decreased in colon and other organs. Our results demonstrated the increased inflammation response and declined antioxidative capacity of periphery organs in aged APP/PS1 mice, which suggesting that a more comprehensive perspective to study AD were necessary.

Integrating SIF and Clearness Index to Improve Maize GPP Estimation Using Continuous Tower-Based Observations.

Solar-induced chlorophyll fluorescence (SIF) has been proven to be well correlated with vegetation photosynthesis. Although multiple studies have found that SIF demonstrates a strong correlation with gross primary production (GPP), SIF-based GPP estimation at different temporal scales has not been well explored. In this study, we aimed to investigate the quality of GPP estimates produced using the far-red SIF retrieved at 760 nm (SIF760) based on continuous tower-based observations of a maize field made during 2017 and 2018, and to explore the responses of GPP and SIF to different meteorological conditions, such as the amount of photosynthetically active radiation (PAR), the clearness index (CI, representing the weather condition), the air temperature (AT), and the vapor pressure deficit (VPD). Firstly, our results showed that the SIF760 tracked GPP well at both diurnal and seasonal scales, and that SIF760 was more linearly correlated to PAR than GPP was. Therefore, the SIF760-GPP relationship was clearly a hyperbolic relationship. For instantaneous observations made within a period of half an hour, the R2 value was 0.66 in 2017 and 2018. Based on daily mean observations, the R2 value was 0.82 and 0.76 in 2017 and 2018, respectively. and had an R2 value of 0.66 (2017) and 0.66 (2018) for instantaneous observations made within a period of half an hour and 0.82 (2017) and 0.76 (2018) for daily mean observations. Secondly, it was found that the SIF760-GPP relationship varied with the environmental conditions, with the CI being the dominant factor. At both diurnal and seasonal scales, the ratio of GPP to SIF760 decreased noticeably as the CI increased. Finally, the SIF760-based GPP models with and without the inclusion of CI were trained using 70% of daily observations from 2017 and 2018 and the models were validated using the remaining 30% of the dataset. For both linear and non-linear models, the inclusion of the CI greatly improved the SIF760-based GPP estimates based on daily mean observations: the value of R2 increased from 0.71 to 0.82 for the linear model and from 0.82 to 0.87 for the non-linear model. The validation results confirmed that the SIF760-based GPP estimation was improved greatly by including the CI, giving a higher R2 and a lower RMSE. These values improved from R2 = 0.66 and RMSE = 7.02 mw/m2/nm/sr to R2 = 0.76 and RMSE = 6.36 mw/m2/nm/sr for the linear model, and from R2 = 0.71 and RMSE = 4.76 mw/m2/nm/sr to R2 = 0.78 and RMSE = 3.50 mw/m2/nm/sr for the non-linear model. Therefore, our results demonstrated that SIF760 is a reliable proxy for GPP and that SIF760-based GPP estimation can be greatly improved by integrating the CI with SIF760. These findings will be useful in the remote sensing of vegetation GPP using satellite, airborne, and tower-based SIF data because the CI is usually an easily accessible meteorological variable.

The Solar-Induced Chlorophyll Fluorescence Imaging Spectrometer (SIFIS) Onboard the First Terrestrial Ecosystem Carbon Inventory Satellite (TECIS-1): Specifications and Prospects.

The global monitoring of solar-induced chlorophyll fluorescence (SIF) using satellite-based observations provides a new way of monitoring the status of terrestrial vegetation photosynthesis on a global scale. Several global SIF products that make use of atmospheric satellite data have been successfully developed in recent decades. The Terrestrial Ecosystem Carbon Inventory Satellite (TECIS-1), the first Chinese terrestrial ecosystem carbon inventory satellite, which is due to be launched in 2021, will carry an imaging spectrometer specifically designed for SIF monitoring. Here, we use an extensive set of simulated data derived from the MODerate resolution atmospheric TRANsmission 5 (MODTRAN 5) and Soil Canopy Observation Photosynthesis and Energy (SCOPE) models to evaluate and optimize the specifications of the SIF Imaging Spectrometer (SIFIS) onboard TECIS for accurate SIF retrievals. The wide spectral range of 670-780 nm was recommended to obtain the SIF at both the red and far-red bands. The results illustrate that the combination of a spectral resolution (SR) of 0.1 nm and a signal-to-noise ratio (SNR) of 127 performs better than an SR of 0.3 nm and SNR of 322 or an SR of 0.5 nm and SNR of 472 nm. The resulting SIF retrievals have a root-mean-squared (RMS) diff* value of 0.15 mW m-2 sr-1 nm-1 at the far-red band and 0.43 mW m-2 sr-1 nm-1 at the red band. This compares with 0.20 and 0.26 mW m-2 sr-1 nm-1 at the far-red band and 0.62 and 1.30 mW m-2 sr-1 nm-1 at the red band for the other two configurations described above. Given an SR of 0.3 nm, the increase in the SNR can also improve the SIF retrieval at both bands. If the SNR is improved to 450, the RMS diff* will be 0.17 mW m-2 sr-1 nm-1 at the far-red band and 0.47 mW m-2 sr-1 nm-1 at the red band. Therefore, the SIFIS onboard TECIS-1 will provide another set of observations dedicated to monitoring SIF at the global scale, which will benefit investigations of terrestrial vegetation photosynthesis from space.

Triterpenes from Poria cocos are revealed as potential retinoid X receptor selective agonists based on cell and in silico evidence.

Poria cocos is an edible and medicinal fungus that is widely used in Traditional Chinese Medicines as well as in modern applications. Retinoid X receptor (RXR) occupies a central place in nuclear receptor signaling, and a pharmacological RXR-dependent pathway is involved in myeloid cell function. Here, structural information for 82 triterpenes from P. cocos and 17 known RXR agonists was collected in a compound library and retrieved for a molecular docking study. Three triterpenes, 16α-hydroxytrametenolic acid (HTA), pachymic acid (PA), and polyporenic acid C (PPAC), were identified as novel RXR-specific agonists based on luciferase reporter assays and in silico evidence. Treatment with HTA, PA, and PPAC significantly induced differentiation of the human promyelocytic leukemia cell line HL-60 with EC50 values of 21.0 ± 0.52, 6.7 ± 0.37, and 9.4 ± 0.65 µM, respectively. These effects were partly blocked by the RXR antagonist UVI3003, suggesting that an RXR-dependent pathway may play an important role in their anti-acute promyelocytic leukemia (APL) effects. Taken together, triterpenes from P. cocos are revealed as naturally occurring RXR selective agonists with the potential for anti-cancer activity. These results suggest a novel approach to the treatment or prevention of APL.

Wound Healing Activity of a Skin Substitute from Residues of Culinary-Medicinal Winter Mushroom Flammulina velutipes (Agaricomycetes) Cultivation.

A skin substitute TG05 obtained from residues of the culinary-medicinal mushroom Flammulina velutipes cultivation process was developed in this study for the first time. Pre-column derivatization high-performance liquid chromatography fingerprints analysis revealed that TG05 was composed of water-insoluble fibers containing xylose (57%), glucose (19.5%), and arabinose (16.3%) as major monomers. Porous and opaque structure of TG05 was demonstrated by scanning electron microscopy. Animal experiments conducted on mice and rats indicated that TG05 notably accelerated the wound-healing process. In addition, TG05 induced proliferation and migration of human keratinocytes time- and dose-dependently. Taken together, the skin substitute TG05 with new structure promotes wound healing in vitro and in vivo. This study provided a novel method to produce functional biomaterial from abundant and low-cost agricultural residues generated during edible mushroom cultivation.

SIFSpec: Measuring Solar-Induced Chlorophyll Fluorescence Observations for Remote Sensing of Photosynthesis.

Solar-induced chlorophyll fluorescence (SIF) is regarded as a proxy for photosynthesis in terrestrial vegetation. Tower-based long-term observations of SIF are very important for gaining further insight into the ecosystem-specific seasonal dynamics of photosynthetic activity, including gross primary production (GPP). Here, we present the design and operation of the tower-based automated SIF measurement (SIFSpec) system. This system was developed with the aim of obtaining synchronous SIF observations and flux measurements across different terrestrial ecosystems, as well as to validate the increasing number of satellite SIF products using in situ measurements. Details of the system components, instrument installation, calibration, data collection, and processing are introduced. Atmospheric correction is also included in the data processing chain, which is important, but usually ignored for tower-based SIF measurements. Continuous measurements made across two growing cycles over maize at a Daman (DM) flux site (in Gansu province, China) demonstrate the reliable performance of SIF as an indicator for tracking the diurnal variations in photosynthetically active radiation (PAR) and seasonal variations in GPP. For the O2-A band in particular, a high correlation coefficient value of 0.81 is found between the SIF and seasonal variations of GPP. It is thus concluded that, in coordination with continuous eddy covariance (EC) flux measurements, automated and continuous SIF observations can provide a reliable approach for understanding the photosynthetic activity of the terrestrial ecosystem, and are also able to bridge the link between ground-based optical measurements and airborne or satellite remote sensing data.

Retrieval of global terrestrial solar-induced chlorophyll fluorescence from TanSat satellite.

The first Chinese Carbon Dioxide Observation Satellite Mission (TanSat), which was launched on December 21, 2016, is intended to measure atmospheric CO2 concentration. The high spectral resolution (0.044 nm) and high SNR (360 at 15.2 mW m-1 sr-1 nm-1) measurements in the region of the O2-A band of the Atmospheric Carbon dioxide Grating Spectroradiometer (AGCS) module onboard TanSat make it possible to retrieve solar-induced chlorophyll fluorescence (SIF) from TanSat observations at the global scale. This paper aims to explore the potential of the TanSat data for global SIF retrieval. A singular vector decomposition (SVD) statistical method was employed to retrieve SIF using radiance over a micro spectral window (∼2 nm) around the Fe Fraunhofer lines (centered at 758.8 nm). The global SIF at 758.8 nm was successfully retrieved with a low residual error of 0.03 mW m-1 sr-1 nm-1. The results show that the spatial and temporal patterns of the retrieved SIF agree well with the global terrestrial vegetation pattern. The monthly SIF products retrieved from the TanSat data were compared with other remote sensing datasets, including OCO-2 SIF, MODIS NDVI, EVI and GPP. The overall consistency between TanSat and OCO-2 SIF products (R2 = 0.86) and the consistency of the spatial patterns and temporal variations between the TanSat SIF and MODIS vegetation indices and GPP enhance our confidence in the potential and feasibility of TanSat data for SIF retrieval. TanSat, therefore, provides a new opportunity for global sampling of SIF at fine spatial resolution (2 km × 2 km), thus improving photosynthesis observations from space.

Modeling the Footprint and Equivalent Radiance Transfer Path Length for Tower-Based Hemispherical Observations of Chlorophyll Fluorescence.

The measurement of solar-induced chlorophyll fluorescence (SIF) is a new tool for estimating gross primary production (GPP). Continuous tower-based spectral observations together with flux measurements are an efficient way of linking the SIF to the GPP. Compared to conical observations, hemispherical observations made with cosine-corrected foreoptic have a much larger field of view and can better match the footprint of the tower-based flux measurements. However, estimating the equivalent radiation transfer path length (ERTPL) for hemispherical observations is more complex than for conical observations and this is a key problem that needs to be addressed before accurate retrieval of SIF can be made. In this paper, we first modeled the footprint of hemispherical spectral measurements and found that, under convective conditions with light winds, 90% of the total radiation came from an FOV of width 72°, which in turn covered 75.68% of the source area of the flux measurements. In contrast, conical spectral observations covered only 1.93% of the flux footprint. Secondly, using theoretical considerations, we modeled the ERTPL of the hemispherical spectral observations made with cosine-corrected foreoptic and found that the ERTPL was approximately equal to twice the sensor height above the canopy. Finally, the modeled ERTPL was evaluated using a simulated dataset. The ERTPL calculated using the simulated data was about 1.89 times the sensor's height above the target surface, which was quite close to the results for the modeled ERTPL. Furthermore, the SIF retrieved from atmospherically corrected spectra using the modeled ERTPL fitted well with the reference values, giving a relative root mean square error of 18.22%. These results show that the modeled ERTPL was reasonable and that this method is applicable to tower-based hemispherical observations of SIF.

The Influences of Drought and Land-Cover Conversion on Inter-Annual Variation of NPP in the Three-North Shelterbelt Program Zone of China Based on MODIS Data.

Terrestrial ecosystems greatly contribute to carbon (C) emission reduction targets through photosynthetic C uptake.Net primary production (NPP) represents the amount of atmospheric C fixed by plants and accumulated as biomass. The Three-North Shelterbelt Program (TNSP) zone accounts for more than 40% of China's landmass. This zone has been the scene of several large-scale ecological restoration efforts since the late 1990s, and has witnessed significant changes in climate and human activities.Assessing the relative roles of different causal factors on NPP variability in TNSP zone is very important for establishing reasonable local policies to realize the emission reduction targets for central government. In this study, we examined the relative roles of drought and land cover conversion(LCC) on inter-annual changes of TNSP zone for 2001-2010. We applied integrated correlation and decomposition analyses to a Standardized Evapotranspiration Index (SPEI) and MODIS land cover dataset. Our results show that the 10-year average NPP within this region was about 420 Tg C. We found that about 60% of total annual NPP over the study area was significantly correlated with SPEI (p<0.05). The LCC-NPP relationship, which is especially evident for forests in the south-central area, indicates that ecological programs have a positive impact on C sequestration in the TNSP zone. Decomposition analysis generally indicated that the contributions of LCC, drought, and other Natural or Anthropogenic activities (ONA) to changes in NPP generally had a consistent distribution pattern for consecutive years. Drought and ONA contributed about 74% and 23% to the total changes in NPP, respectively, and the remaining 3% was attributed to LCC. Our results highlight the importance of rainfall supply on NPP variability in the TNSP zone.

Improving artificial forest biomass estimates using afforestation age information from time series Landsat stacks.

China maintains the largest artificial forest area in the world. Studying the dynamic variation of forest biomass and carbon stock is important to the sustainable use of forest resources and understanding of the artificial forest carbon budget in China. In this study, we investigated the potential of Landsat time series stacks for aboveground biomass (AGB) estimation in Yulin District, a key region of the Three-North Shelter region of China. Firstly, the afforestation age was successfully retrieved from the Landsat time series stacks in the last 40 years (from 1974 to 2013) and shown to be consistent with the surveyed tree ages, with a root-mean-square error (RMSE) value of 4.32 years and a determination coefficient (R (2)) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R (2) values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in seven counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360 %. For the persistent forest area since 1974, the forest AGB density increased from 15.72 t/ha in 1986 to 44.53 t/ha in 2013, with an annual rate of about 0.98 t/ha. For the artificial forest planted after 1974, the AGB density increased about 1.03 t/ha a year from 1974 to 2013. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades.