Productivity Of Terrestrial Ecosystems Research Articles

Estimation of Global Cropland Gross Primary Production from Satellite Observations by Integrating Water Availability Variable in Light-Use-Efficiency Model

Satellite-based models have been widely used to estimate gross primary production (GPP) of terrestrial ecosystems. Although they have many advantages for mapping spatiotemporal variations of regional or global GPP, the performance in agroecosystems is relatively poor. In this study, a light-use-efficiency model for cropland GPP estimation, named EF-LUE, driven by remote sensing data, was developed by integrating evaporative fraction (EF) as limiting factor accounting for soil water availability. Model parameters were optimized first using CO2 flux measurements by eddy covariance system from flux tower sites, and the optimized parameters were further spatially extrapolated according to climate zones for global cropland GPP estimation in 2001–2019. The major forcing datasets include the fraction of absorbed photosynthetically active radiation (FAPAR) data from the Copernicus Global Land Service System (CGLS) GEOV2 dataset, EF from the ETMonitor model, and meteorological forcing variables from ERA5 data. The EF-LUE model was first evaluated at flux tower site-level, and the results suggested that the proposed EF-LUE model and the LUE model without using water availability limiting factor, both driven by flux tower meteorology data, explained 82% and 74% of the temporal variations of GPP across crop sites, respectively. The overall KGE increased from 0.73 to 0.83, NSE increased from 0.73 to 0.81, and RMSE decreased from 2.87 to 2.39 g C m−2 d−1 in the estimated GPP after integrating EF in the LUE model. These improvements may be largely attributed to parameters optimized for different climatic zones and incorporating water availability limiting factor expressed by EF into the light-use-efficiency model. At global scale, the verification by GPP measurements from cropland flux tower sites showed that GPP estimated by the EF-LUE model driven by ERA5 reanalysis meteorological data and EF from ETMonitor had overall the highest R2, KGE, and NSE and the smallest RMSE over the four existing GPP datasets (MOD17 GPP, revised EC-LUE GPP, GOSIF GPP and PML-V2 GPP). The global GPP from the EF-LUE model could capture the significant negative GPP anomalies during drought or heat-wave events, indicating its ability to express the impacts of the water stress on cropland GPP.

Meta-analysis of diazotrophic signatures across terrestrial ecosystems at the continental scale.

Biological nitrogen fixation performed by diazotrophs forms a cornerstone of Earth's terrestrial ecosystem productivity. However, the composition, diversity and distribution of soil diazotrophs are poorly understood across different soil ecosystems. Furthermore, the biological potential of the key diazotroph species in relation to key environmental parameters is unknown. To address this, we used meta-analysis approach to merge together 39 independent diazotroph amplicon sequencing (nifH gene) datasets consisting of 1988 independent soil samples. We then employed multiple statistical analyses and machine-learning approaches to compare diazotroph community differences and indicator species between terrestrial ecosystems on a global scale. The distribution, composition and structure of diazotroph communities varied across seven different terrestrial ecosystems, with community composition exhibiting an especially clear effect. The Cyanobacteria were the most abundant taxa in crust ecosystems (accounting for ~45% of diazotrophs), while other terrestrial ecosystems were dominated by Proteobacteria, including Alpha-, Beta- and Gamma-Proteobacteria (accounting for ~70% of diazotrophs). Farmland ecosystems harboured the highest and crust ecosystems the lowest alpha and phylogenetic diversities. Azospirillum zeae, Skermanella aerolata and four Bradyrhizobium species were identified as key indicator species of potential diazotroph activity. Overall, diazotroph abundances and distribution were affected by multiple environmental parameters, including soil pH, nitrogen, organic carbon, C:N ratio and annual mean precipitation and temperature. Together, our findings suggest that based on the relative abundance and diversity of nifH marker gene, diazotrophs have adapted to a range of environmental niches globally.

Integrating Aquatic and Terrestrial Carbon Fluxes to Assess the Net Landscape Carbon Balance of a Highly Erodible Semiarid Catchment

AbstractThe magnitude of the carbon (C) sink due to terrestrial primary production may be overestimated if the C losses through fluvial networks are not properly accounted for. In this study, we hypothesize that terrestrial‐aquatic C transfers represent a major loss of the terrestrial C sink in semiarid catchments. To test the hypothesis, we assessed the net landscape carbon balance (NLCB) of a highly erodible catchment on the semiarid Chinese Loess Plateau by compiling terrestrial net ecosystem productivity (NEP) estimates and aquatic fluxes of downstream C export, emission of CO2 and CH4, and C burial. Our results showed that, despite the severe erosion and strong C mobilization, this catchment was a net C sink (NLCB = 48.3–54.8 Mg C km−2 year−1). Downstream C export at catchment outlet and evasion of CO2 and CH4 only offset terrestrial NEP by 7.7%–8.5% due largely to low flow discharge and small water surface area of the stream network. Furthermore, C burial in reservoirs played a considerable role, reducing an additional 7.5%–8.3% of the NEP. Altogether, approximately 84% of the net terrestrial C production was stored within the catchment. Our study reveals that semiarid catchments with widespread erosion and low terrestrial production remain a net C sink, although the magnitude is lower than those found in other climate zones. Our study further advocates the need to integrate terrestrial‐aquatic C transfer into a comprehensive net C balance accounting at the landscape scale. Ignoring the aquatic C loss will cause biased estimates of the overall C sink strength.

Does growing atmospheric CO2 explain increasing carbon sink in a boreal coniferous forest?

The terrestrial net ecosystem productivity (NEP) has increased during the past three decades, but the mechanisms responsible are still unclear. We analyzed 17 years (2001–2017) of eddy‐covariance measurements of NEP, evapotranspiration (ET) and light and water use efficiency from a boreal coniferous forest in Southern Finland for trends and inter‐annual variability (IAV). The forest was a mean annual carbon sink (252 [±42] gC m‐2 a‐1), and NEP increased at rate +6.4–7.0 gC m‐2 a‐1 (or ca. +2.5% a‐1) during the period. This was attributed to the increasing gross‐primary productivity GPP and occurred without detectable change in ET. The start of annual carbon uptake period was advanced by 0.7 d a‐1, and increase in GPP and NEP outside the main growing season contributed ca. one‐third and one‐fourth of the annual trend, respectively. Meteorological factors were responsible for the IAV of fluxes but did not explain the long‐term trends. The growing season GPP trend was strongest in ample light during the peak growing season. Using a multi‐layer ecosystem model, we showed that direct CO2 fertilization effect diminishes when moving from leaf to ecosystem, and only 30–40% of the observed ecosystem GPP increase could be attributed to CO2. The increasing trend in leaf‐area index (LAI), stimulated by forest thinning in 2002, was the main driver of the enhanced GPP and NEP of the mid‐rotation managed forest. It also compensated for the decrease of mean leaf stomatal conductance with increasing CO2 and LAI, explaining the apparent proportionality between observed GPP and CO2 trends. The results emphasize that attributing trends to their physical and physiological drivers is challenged by strong IAV, and uncertainty of LAI and species composition changes due to the dynamic flux footprint. The results enlighten the underlying mechanisms responsible for the increasing terrestrial carbon uptake in the boreal zone.

Inter-comparisons of mean, trend and interannual variability of global terrestrial gross primary production retrieved from remote sensing approach

Many models were established to estimate gross primary production (GPP) of terrestrial ecosystems based on vegetation light use efficiency (LUE). Analysing the spatial-temporal variations of global terrestrial GPP became capable with the increasing length of satellite data. Previous studies mainly focused on evaluating the model performance or investigating the mean, the temporal trend or the interannual variability (IAV) of global terrestrial GPP based on one single or multiple models, which is difficult to identify common merits of a same cluster of GPP models. This study compared eight satellite-based LEU-type GPP models in capturing the mean, temporal trend and IAV of global GPP concurrently. Our results showed that current common-used models based on LUE methodology estimated global mean GPP ranging from 128.5 to 158.3 Pg C year−1, and global mean IAV ranging from 0.1 to 0.35, but the trends ranging from −0.22 to 0.51 Pg C year−1. In the context of plant functional types (PFTs) and climate classifications, no consistent feature for either of the mean, trend or IAV of GPP are identified among eight models. Future studies should integrate the latest advances on the mechanisms and associated environmental factors into models and consolidate performance of models to better understand the evolutions of terrestrial ecosystem functioning.

Phosphorus is the key soil indicator controlling productivity in planted Masson pine forests across subtropical China

Soil physiochemical properties are critical to understanding forest productivity and carbon (C) finance schemes in terrestrial ecosystems. However, few studies have focused on the effects of the soil physiochemical properties on the productivity in planted forests. This study was therefore conducted at 113 sampling plots located in planted Masson pine forests across subtropical China to test what and how the aboveground net primary productivity (ANPP) would be explained by the soil physiochemical properties, stand attributes, and functional traits using regression analysis and structural equation modelling (SEM). Across subtropical China, the ANPP ranged from 1.79 to 14.04 Mg ha−1 year−1 among the plots, with an average value of 6.05 Mg ha−1 year−1. The variations in ANPP were positively related to the stand density, root phosphorus (P) content and soil total P content but were negatively related to the stand age, root C:P and N:P ratios. Among these factors, the combined effects of stand density, stand age and soil total P content explained 35% of the ANPP variations. The SEM results showed the indirect effect of the soil total P content via the root P content and C:P ratio on the ANPP and indirect effects of other soil properties (e.g., pH, clay, and bulk density) via the soil total P content and root functional traits (e.g., root P, C:P, and N:P) on the ANPP. By considering all possible variables and paths, the best-fitting SEM explained only 11–13% of the ANPP variations, which suggested that other factors may be more important in determining the productivity in planted forests. Overall, this study highlights that soil total P content should be used as a key soil indicator for determining the ANPP in planted Masson pine forests across subtropical China, and suggests that the root functional traits mediate the effects of soil properties on the ANPP.

Contrasting responses of woody and grassland ecosystems to increased CO2 as water supply varies.

Experiments show that elevated atmospheric CO2 (eCO2) often enhances plant photosynthesis and productivity, yet this effect varies substantially and may be climate sensitive. Understanding if, where and how water supply regulates CO2 enhancement is critical for projecting terrestrial responses to increasing atmospheric CO2 and climate change. Here, using data from 14 long-term ecosystem-scale CO2 experiments, we show that the eCO2 enhancement of annual aboveground net primary productivity is sensitive to annual precipitation and that this sensitivity differs between woody and grassland ecosystems. During wetter years, CO2 enhancement increases in woody ecosystems but declines in grass-dominated systems. Consistent with this difference, woody ecosystems can increase leaf area index in wetter years more effectively under eCO2 than can grassland ecosystems. Overall, and across different precipitation regimes, woody systems had markedly stronger CO2 enhancement (24%) than grasslands (13%). We developed an empirical relationship to quantify aboveground net primary productivity enhancement on the basis of changes in leaf area index, providing a new approach for evaluating eCO2 impacts on the productivity of terrestrial ecosystems.

Divergent responses of terrestrial carbon use efficiency to climate variation from 2000 to 2018

Carbon use efficiency (CUE) refers to the allocation of photosynthesized products by plants and is commonly used to measure primary production in terrestrial ecosystems. Despite the fact that the effects of climate variation on vegetation CUE have been studied at various spatial scales, there is still a lack of consensus as to how vegetation CUE responds to climate factors. The objective of this study was to evaluate the spatiotemporal dynamics of terrestrial CUE based on the latest versions of Moderate Resolution Imaging Spectroradiometer (MODIS) products during 2000–2018, and to reveal the dominant climate factor that controls vegetation CUE in different regions by using path analysis (PA). The results showed that global vegetation CUE increased significantly due to a more rapid increase in net primary productivity (NPP) than in gross primary productivity (GPP) over this period. Central Africa and South America are the two areas that experienced clear increases in CUE, and Amazon and northeastern India experienced decreases in vegetation CUE due to reduced precipitation. CUE increased significantly in the north frigid, the torrid, and the south temperate zones over this period. The largest areas showing vegetation CUE increases and decreases occurred in the north temperate zone. Rising precipitation lowered the vegetation CUE in the north frigid zone, but promoted CUE increase in the torrid and south temperate zones. Higher temperatures led to higher CUE in the north frigid and south temperate zones. Reduced CUE due to higher temperature mostly occurred in the arid zones. CUE in the cold/boreal zone remained relatively stable due to the synchronized variation of GPP and NPP. The divergent responses of terrestrial CUE to climate variations call for flexible ecosystem management to adapt to the future warming climate in different regions. The results also highlighted that a dynamic parameterization scheme of vegetation carbon allocation should be considered in simulating the terrestrial C cycle in Earth System Models.

ВЛИЯНИЕ ИЗМЕНЕНИЙ КЛИМАТА НА БИОПРОДУКТИВНОСТЬ НАЗЕМНЫХ ЭКОСИСТЕМ В БЕЛОРУССКО-УКРАИНСКОМ ПОЛЕСЬЕ

The influence of interannual and long-term climate change impacts on net primary production (NPP) of terrestrial ecosystems in the central part of the Belarusian-Ukrainian Polesie region (50.7°-53° N, 25.5°-31.5° E) are investigated using satellite observations and reanalysis data. The results show that nowadays Polesie belongs to the zone of excessive heat and solar radiation resources and insufficient moisture resources. The interannual variations in NPP in Polesie are 2-3 times higher than in the other parts of Eastern Europe. Climate change in the recent 50 years led to the reduction of the total carbon stock in the vegetation cover of the region (at the rate of ~750000 t/year). However, a number of natural and anthropogenic processes not related to the climate compensate the climate-related carbon loss in the terrestrial biomass. Moreover, these processes cause a slow growth of carbon at the rate of 140000 t/year in the region.

Increasing Causal Effects of El Niño–Southern Oscillation on the Future Carbon Cycle of Terrestrial Ecosystems

AbstractHere we examine the causal effects of El Niño–Southern Oscillation (ENSO) on the global carbon cycle over historical and future periods utilizing datasets from the Coupled Modeling Intercomparison Project Phase 6 models. Our results show that ENSO exhibits impact on terrestrial carbon fluxes and carbon storage over numerous regions of Asia, Oceania, and America. High consensus is found between models for the influences of ENSO over these regions. The results demonstrate that the effects of ENSO on carbon cycling over subtropics and high‐latitude regions may be more significant than previously understood. In historical simulation, the regions affected by ENSO account for approximately 8.5% land‐area and this proportion rises to approximately 11.7% in the future simulation, indicating an increase in ENSO influences on the gross primary productivity of terrestrial ecosystems. In addition, the results emphasize stronger response of seasonal carbon stocks to ENSO compared to that of seasonal carbon fluxes.

Large contribution of recent photosynthate to soil respiration in tropical dipterocarp forest revealed by girdling

Abstract Tropical forests are the most productive terrestrial ecosystems, fixing over 40 Pg of carbon from the atmosphere each year. A substantial portion of this carbon is allocated below‐ground to roots and root‐associated micro‐organisms. However, there have been very few empirical studies on the dynamics of this below ground transfer, especially in tropical forests where carbon allocation processes are influenced by high plant species diversity. We used a whole‐stand girdling experiment to halt the below‐ground transfer of recent photosynthates in a lowland tropical forest in Borneo. By girdling 209 large trees in a 0.48 ha plot, we determined: (a) the contribution of recent photosynthate to root‐rhizosphere respiration and; (b) the relationships among the disruption of this below‐ground carbon supply, tree species composition and mortality. Mortality of the 209 trees was 62% after 370 days, with large variation among species and particularly high mortality within the Dipterocarpaceae (99%) and Fagaceae (100%) families. We also observed a higher risk of mortality following girdling for species with lower wood density. Soil CO2 emissions declined markedly (36 ± 5%) over ~50 days following girdling in three of six monitored subplots. In the other three subplots there was either a marginal decline or no response of soil CO2 emissions to girdling. The decrease in soil CO2 efflux was larger in subplots with dominance of Dipterocarpaceae. Synthesis. Our results indicate high spatial variation in the coupling of below‐ground carbon allocation and root‐rhizosphere respiration in this tropical forest, with a closer coupling in forest dominated by Dipterocarpaceae. Our findings highlight the implications of tree species composition of tropical forests in affecting the dynamics of below‐ground carbon transfer and its release to the atmosphere.

Patterns of nitrogen and phosphorus pools in terrestrial ecosystems in China

Abstract. Recent increases in atmospheric carbon dioxide (CO2) and temperature relieve their limitations on terrestrial ecosystem productivity, while nutrient availability constrains the increasing plant photosynthesis more intensively. Nitrogen (N) and phosphorus (P) are critical for plant physiological activities and consequently regulate ecosystem productivity. Here, for the first time, we mapped N and P densities and concentrations of leaves, woody stems, roots, litter, and soil in forest, shrubland, and grassland ecosystems across China based on an intensive investigation at 4868 sites, covering species composition, biomass, and nutrient concentrations of different tissues of living plants, litter, and soil. Forest, shrubland, and grassland ecosystems in China stored 6803.6 Tg N, with 6635.2 Tg N (97.5 %) fixed in soil (to a depth of 1 m) and 27.7 (0.4 %), 57.8 (0.8 %), 71.2 (1 %), and 11.7 Tg N (0.2 %) in leaves, stems, roots, and litter, respectively. The forest, shrubland, and grassland ecosystems in China stored 2806.0 Tg P, with 2786.1 Tg P (99.3 %) fixed in soil (to a depth of 1 m) and 2.7 (0.1 %), 9.4 (0.3 %), 6.7 (0.2 %), and 1.0 Tg P (< 0.1 %) in leaves, stems, roots, and litter, respectively. Our estimation showed that N pools were low in northern China, except in the Changbai Mountains, Mount Tianshan, and Mount Alta, while relatively higher values existed in the eastern Qinghai–Tibetan Plateau and Yunnan. P densities in vegetation were higher towards the southern and north-eastern part of China, while soil P density was higher towards the northern and western part of China. The estimated N and P density and concentration datasets, “Patterns of nitrogen and phosphorus pools in terrestrial ecosystems in China” (https://doi.org/10.5061/dryad.6hdr7sqzx), are available from the Dryad digital repository (Zhang et al., 2021). These patterns of N and P densities could potentially improve existing earth system models and large-scale research on ecosystem nutrients.

The response of litter decomposition to phosphorus addition in typical temperate grassland in Inner Mongolia

The productivity of terrestrial ecosystems is limited by soil fertility, such assoil phosphorus (P). The decomposition of litter is the main process that affects nutrient cycling. To understand the characteristics of litter decomposition and nutrient release under P addition, we conducted a 2-year litter bag experiment at P addition rates (0–12.5 g P m−2 yr−1). All litter decomposed faster during the second growing season due to highly concentrated precipitation, and Stipa grandis litter decomposed faster (1.02–1.63 times) than Leymus chinensis under P treatments. The decomposition of L. chinensis and mixed litter was more thoroughly at 1 g P m−2 yr−1, while S. grandis decomposed more under 5 g P m−2 yr−1. P addition promoted nitrogen (N) and P immobilization and all litter reached its maximum at 12.5 g P m−2 yr−1. Phosphorus addition increased β-glucosidase production at 5 g P m−2 yr−1, but leucine aminopeptidase production was promoted at high P. The ratio of leucine aminopeptidase to phosphatase increased over time, indicating the N deficiency and P saturation during late stages of decomposition. Our results show that Inner Mongolia's grasslands was limited by P availability and that precipitation was important in the region's decomposition processes.

Nitrogen use efficiency of terrestrial plants in China: geographic patterns, evolution, and determinants

BackgroundPlant nitrogen use efficiency (NUE) is an important ecological indicator that reflects the capacity of a plant to transform nitrogen into production, which is essential for further elucidating plant growth and terrestrial ecosystem productivity. Although there are a growing number of studies that address NUE changes at local scales, the variations of NUE over large spatial scales remain unclear. In this study, we analyzed the geographic patterns of NUE and explored its phylogenic and environmental drivers across 1452 species at 1102 sites in China.ResultsNUE tended to decrease with latitude (r = − 0.56), whereas it increased with longitude (r = 0.54), and varied widely in different ecosystems and plant life forms. Furthermore, NUE was negatively correlated with plant foliar phosphorus concentration (r = − 0.53), soil pH (r = − 0.10), soil total phosphorus (r = − 0.13) and available phosphorus (r = − 0.05), but positively with the mean annual temperature (r = 0.32), annual precipitation (r = 0.27), and aridity index (r = 0.26). NUE was significantly altered with phylogeny and evolved toward a lower value (r = − 0.28), which may have been due to increasing nitrogen deposition and fixation in biogeochemical evolution. Overall, the combination of foliar phosphorus concentration, phylogeny, climate, and soil properties accounted for 52.7% of the total variations of NUE. In particular, foliar phosphorus concentration was the most important factor, whereas plant evolutionary history was second in contributing to NUE variations.ConclusionsOur study emphasizes the pivotal role of plant stoichiometry and phylogeny in nitrogen cycling and suggests incorporating them into earth system models to better understanding plant growth and nitrogen cycling in the context of environmental changes.

Climate Change Decreased Net Ecosystem Productivity in the Arid Region of Central Asia

Numerous studies have confirmed that climate change leads to a decrease in the net ecosystem productivity (NEP) of terrestrial ecosystems and alters regional carbon source/sink patterns. However, the response mechanism of NEP to climate change in the arid regions of Central Asia remains unclear. Therefore, this study combined the Carnegie–Ames–Stanford approach (CASA) and empirical models to estimate the NEP in Central Asia and quantitatively evaluate the sensitivity of the NEP to climate factors. The results show that although the net primary productivity (NPP) in Central Asia exhibits an increasing trend, it is not significant. Soil heterotrophic respiration (RH) has increased significantly, while the NEP has decreased at a rate of 6.1 g C·m−2·10 a−1. Spatially, the regional distribution of the significant increase in RH is consistent with that of the significant decrease in the NEP, which is concentrated in western and southern Central Asia. Specifically, the NPP is more sensitive to precipitation than temperature, whereas RH and NEP are more sensitive to temperature than precipitation. The annual contribution rates of temperature and precipitation to the NEP are 28.79% and 23.23%, respectively. Additionally, drought has an important impact on the carbon source/sink in Central Asia. Drought intensified from 2001 to 2008, leading to a significant expansion of the carbon source area in Central Asia. Therefore, since the start of the 21st century, climate change has damaged the NEP of the Central Asian ecosystem. Varying degrees of warming under different climate scenarios will further aggravate the expansion of carbon source areas in Central Asia. An improved understanding of climate change impacts in Central Asia is critically required for sustainable development of the regional economy and protection of its natural environment. Our results provide a scientific reference for the construction of the Silk Road Economic Belt and global emissions reduction.

Diffuse solar radiation and canopy photosynthesis in a changing environment

The sunlight received by plants is affected by cloudiness and pollution. Future changes in cloud cover will differ among regions, while aerosol concentrations are expected to continue increasing globally as a result of wildfires, fossil fuel combustion, and industrial pollution. Clouds and aerosols increase the diffuse fraction and modify the spectral composition of incident solar radiation, and both will affect photosynthesis and terrestrial ecosystem productivity. Thus, an assessment of how canopy and leaf-level processes respond to these changes is needed as part of accurately forecasting future global carbon assimilation. To review these processes and their implications: first, we discuss the physical basis of the effect of clouds and aerosols on solar radiation as it penetrates the atmosphere; second, we consider how direct and diffuse radiation are absorbed and transmitted by plant canopies and their leaves; and finally, we assess the consequences for photosynthesis at the canopy and ecosystem levels. Photobiology will be affected at the atmospheric level by a shift in spectral composition toward shorter or longer wavelengths under clouds or aerosols, respectively, due to different scattering. Changes in the microclimate and spectral composition of radiation due to an enhanced diffuse fraction also depend on the acclimation of canopy architectural and physiological traits, such as leaf area index, orientation, and clumping. Together with an enhancement of light-use efficiency, this makes the effect of diffuse solar radiation on canopy photosynthesis a multilayered phenomenon, requiring experimental testing to capture those complex interactions that will determine whether it produces the persistent enhancement in carbon assimilation that land-surface models currently predict.

Temporal Pattern Analysis of Cropland Phenology in Shandong Province of China Based on Two Long-Sequence Remote Sensing Data

Vegetation phenology dynamics have attracted worldwide attention due to its direct response to global climate change and the great influence on terrestrial carbon budgets and ecosystem productivity in the past several decades. However, most studies have focused on phenology investigation on natural vegetation, and only a few have explored phenology variation of cropland. In this study, taking the typical cropland in the Shandong province of China as the target, we analyzed the temporal pattern of the Normalized Difference Vegetation Index (NDVI) and phenology metrics (growing season start (SOS) and end (EOS)) derived from the Global Inventory Monitoring and Modeling System (GIMMS) 3-generation version 1 (1982–2015) and the Vegetation Index and Phenology (VIP) version 4 (1981–2016), and then investigated the influence of climate factors and Net Primary Production (NPP, only for EOS) on SOS/EOS. Results show a consistent seasonal profile and interannual variation trend of NDVI for the two products. Annual average NDVI has significantly increased since 1980s, and hugely augmentations of NDVI were detected from March to June for both NDVI products (p < 0.01), which indicates a consistent greening tendency of the study region. SOSs from both products are correlated well with the ground-observed wheat elongation and spike date and have significantly advanced since the 1980s, with almost the same changing rate (0.65/0.64 days yr-1, p < 0.01). EOS also exhibits an earlier but weak advancing trend. Due to the significant advance of SOS, the growing season duration has significantly lengthened. Spring precipitation has a relatively stronger influence on SOS than temperature and shortwave radiation, while a greater correlation coefficient was diagnosed between EOS and autumn temperature/shortwave radiation than precipitation/NDVI. Autumn NPP exhibits a nonlinear effect on EOS, which is first earlier and then later with the increase of autumn NPP. Overall, we highlight the similar capacity of the two NDVI products in characterizing the temporal patterns of cropland phenology.

Daily estimation of gross primary production under all sky using a light use efficiency model coupled with satellite passive microwave measurements

Although satellite-based light use efficiency (LUE) model is widely used to estimate gross primary production (GPP) of terrestrial ecosystems, microwave observations have not been integrated into LUE models. This study developed a new LUE model coupled with a passive microwave vegetation index (Emissivity Difference Vegetation Index, EDVI) for daily GPP estimation. Normalized EDVI (nEDVI), an indicator of canopy-scale leaf development and biomass change, was used as a proxy of fraction of photosynthetically active radiation (FPAR). EDVI-based evaporative fraction (EDVI-EF) under all sky was used to indicate synoptic-scale water stress on LUE. 8-year in-situ measurements from seven flux tower sites (four forests, two grasslands and one croplands) of ChinaFLUX network were used to evaluate the model. We found that nEDVI-based FPAR better captured the short-term variations in daily in-situ GPP (GPPobs) than other optic-based FPAR schemes. This capability of nEDVI was more noticeable under moderate and heavy cloud cover (Frc) conditions. Validations against daily GPPobs at all sites showed that EDVI-based GPP (GPPEDVI) generated an overall small bias of −0.47 gC m−2 day−1 (−8.1%) and good Taylor score (S) of 0.86 at the daily scale. Better accuracy of GPPEDVI was found at forests sites with R2 of 0.43 to 0.73, bias of-5.29% to 3.03% and S of 0.58 to 0.78, respectively. At a tropical forest site with most frequent cloud cover, the model also well captured the variation in GPPobs from clear sky to cloudy sky (R2 of 0.93) with stable accuracies. Furthermore, the accuracy of daily GPPEDVI was found to be comparable with global satellite optic MOD17 GPP (GPPMOD17) and EC-LUE GPP (GPPECLUE) from 8-day to yearly scales across the sites. In particular, GPPEDVI performed generally smaller bias at evergreen broadleaf forests, while both of GPPMOD17 and GPPECLUE were overestimated, suggesting that there could be less saturation for microwave-based LUE model over dense vegetation. Although all three satellite LUE models severely underestimated GPP of crop, GPPEDVI generated lower bias (−29.8%) than GPPMOD17 (−66.8%) and GPPECLUE (−59.5%). Overall, this study is the first attempt toward the integration of microwave-derived variables into LUE model for daily GPP estimation. The microwave-based LUE model has a potential of mapping spatiotemporally continues daily GPP under various clouds.

Nitrogen effects on plant productivity change at decadal time‐scales

AbstractAimAlthough some long‐term studies have been conducted to quantify the impacts of nitrogen (N) on plant productivity, uncertainties remain regarding whether these impacts change over time and the underlying mechanisms. By overlooking this, we might over‐ or underestimate the impacts of N on terrestrial ecosystems. Our goal was to determine whether the impacts of N on plant productivity change in the long term and what controls these dynamics.LocationGlobal.Time period1999–2018.Major taxa studiedEffects of N on plant productivity.MethodsWe synthesized 63 N addition studies with duration ≥ 8 years in natural terrestrial ecosystems.ResultsOur results showed temporally dynamic impacts of N on plant productivity in terrestrial ecosystems. The interannual coefficient of variation (CV) of N impacts ranged from 19 to 768% across 63 studies, with higher variability in acidic soils. Moreover, a substantial proportion (44%) of studies showed evidence of a consistent directional change in the strength of the impacts of N over time. The direction of change varied with biome type (forests, decrease; grasslands and shrublands, increase). The temporal pattern of the impacts of N was mostly responsive to mean annual precipitation (MAP), mean annual temperature (MAT) and initial soil pH, which accounted for 24%, 19% and 19% of the variation, respectively.Main conclusionsOur findings indicate that temporally dynamic impacts of long‐term N addition on plant productivity and large fluctuations of the impacts of N between years are generally observed among studies in terrestrial ecosystems. Therefore, not only the magnitude of N impacts on plant productivity, but also their temporal pattern and variability should be considered in future experimental and model research.

Effect of atmospheric nitrogen deposition and its components on carbon flux in terrestrial ecosystems in China

Long-term atmospheric nitrogen (N) deposition increases bioavailable N in terrestrial ecosystems, thereby influencing ecosystem productivity. However, how N deposition and its components (i.e., NO3−–N and NH4+–N) influence the spatial pattern of productivity in terrestrial ecosystems in China remains unknown. Here, we utilize published data including carbon (C) fluxes from eddy flux tower (gross ecosystem productivity, ecosystem respiration, and net ecosystem productivity) and the corresponding climate and N deposition data for 60 typical ecosystems in China. The objective was to investigate the effect of N deposition on ecosystem productivity and explore the variations of N use efficiency (NUE). Our results reveal that atmospheric total N deposition is significantly correlated with C fluxes of terrestrial ecosystems in China. Ecosystems respond variably to different components of N deposition. In detail, forest ecosystem marginally correlated with NO3−–N and wet deposition, while grassland ecosystem significantly correlated with NH4+–N and dry deposition. NUE of productivity induced by N deposition in Chinese terrestrial ecosystems was 53.95 ± 40.30 g C g−1 N, and it was influenced by precipitation and aridity index. This study quantifies the contribution of total N deposition and its associated components to productivity in terrestrial ecosystems in China, offering vital information for regional C and N management.