Spatiotemporal changes of gross primary productivity and its response to drought in the Mongolian Plateau under climate change

Gross primary productivity(GPP)of vegetation is an important constituent of the terrestrial carbon sinks and is significantly influenced by drought.Understanding the impact of droughts on different types of vegetation GPP provides insight into the spatiotemporal variation of terrestrial carbon sinks,aiding efforts to mitigate the detrimental effects of climate change.In this study,we utilized the precipitation and temperature data from the Climatic Research Unit,the standardized precipitation evapotranspiration index(SPEI),the standardized precipitation index(SPI),and the simulated vegetation GPP using the eddy covariance-light use efficiency(EC-LUE)model to analyze the spatiotemporal change of GPP and its response to different drought indices in the Mongolian Plateau during 1982-2018.The main findings indicated that vegetation GPP decreased in 50.53% of the plateau,mainly in its northern and northeastern parts,while it increased in the remaining 49.47%area.Specifically,meadow steppe(78.92%)and deciduous forest(79.46%)witnessed a significant decrease in vegetation GPP,while alpine steppe(75.08%),cropland(76.27%),and sandy vegetation(87.88%)recovered well.Warming aridification areas accounted for 71.39% of the affected areas,while 28.53% of the areas underwent severe aridification,mainly located in the south and central regions.Notably,the warming aridification areas of desert steppe(92.68%)and sandy vegetation(90.24%)were significant.Climate warming was found to amplify the sensitivity of coniferous forest,deciduous forest,meadow steppe,and alpine steppe GPP to drought.Additionally,the drought sensitivity of vegetation GPP in the Mongolian Plateau gradually decreased as altitude increased.The cumulative effect of drought on vegetation GPP persisted for 3.00-8.00 months.The findings of this study will improve the understanding of how drought influences vegetation in arid and semi-arid areas.

How forest age impacts on net primary productivity: Insights from future multi-scenarios

Forest net primary productivity(NPP)constitutes a key flux within the terrestrial ecosystem carbon cycle and serves as a significant indicator of the forests carbon sequestration capacity,which is closely related to forest age.Despite its significance,the impact of forest age on NPP is often ignored in future NPP projections.Here,we mapped forest age in Hunan Province at a 30-m resolution utilizing a combination of Landsat time series stack(LTSS),national forest inventory(NFI)data,and the relationships between height and age.Subsequently,NPP was derived from NFI data and the relationships between NPP and age was built for various forest types.Then forest NPP was predicted based on the NPP-age relationships under three future scenarios,assessing the impact of forest age on NPP.Our findings reveal substantial variations in forest NPP in Hunan Province under three future scenarios:under the age-only scenario,NPP peaks in 2041(133.56TgC·yr^(−1)),while NPP peaks three years later in 2044(141.14TgC·yr^(−1))under the natural development scenario.The maximum afforestation scenario exhibits the most rapid increase in NPP,with peaking in 2049(197.95TgC·yr^(−1)).However,with the aging of the forest,NPP is projected to then decrease by 7.54%,6.07%,and 7.47%in 2060,and 20.05%,19.74%,and 28.38%in 2100,respectively,compared to their peaks under the three scenarios.This indicates that forest NPP will continue to decline soon.Controlling the age structure of forests through selective logging,afforestation and reforestation,and encouraging natural regeneration after disturbance could mitigate this declining trend in forest NPP,but implications of these measures on the full forest carbon balance remain to be studied.Insights from the future multi-scenarios are expected to provide data to support sustainable forest management and national policy development,which will inform the achievement of carbon neutrality goals by 2060.

Seasonal influence of freshwater discharge on spatio-temporal variations in primary productivity, sea surface temperature, and euphotic zone depth in the northern Bay of Bengal

Ocean productivity is the foundation of marine food web,which continuously removes atmospheric carbon dioxide and supports life at sea and on land.Spatio-temporal variability of net primary productivity(NPP),sea surface temperature(SST),sea surface salinity(SSS),mixed layer depth(MLD),and euphotic zone depth(EZD) in the northern B ay of Bengal(BoB) during three monsoon seasons were examined in this study based on remote sensing data for the period 2005 to 2020.To compare the NPP distribution between the coastal zones and open BoB,the study area was divided into five zones(Z1-Z5).Results suggest that most productive zones Z2 and Zl are located at the head bay area and are directly influenced by freshwater discharge together with riverine sediment and nutrient loads.Across Z1-Z5,the NPP ranges from 5 315.38 mg/(m^(2)·d) to 346.7 mg/(m^(2)·d)(carbon,since then the same).The highest monthly average NPP of 5 315.38 mg/(m^(2)·d) in February and 5 039.36 mg/(m^(2)·d) in June were observed from Z2,while the lowest monthly average of 346.72 mg/(m^(2)·d) was observed in March from Z4,which is an oceanic zone.EZD values vary from 6-154 m for the study area,and it has an inverse correlation with NPP concentration.EZD is deeper during the summer season and shallower during the wintertime,with a corresponding increase in productivity.Throughout the year,monthly SST shows slight fluctuation for the entire study area,and statistical analysis shows a significant correlation among NPP,and EZD,overall positive between NPP and MLD,whereas no significant correlation among SSS,and SST for the northern BoB.Long-term trends in SST and productivity were significantly po sitive in head bay zones but negatively productive in the open ocean.The findings in this study on the distribution of NPP,SST,SSS,MLD,and EZD and their seasonal variability in five different zones of BoB can be used to further improve the management of marine resources and overall environmental condition in response to climate changes in BoB as they are of utmost relevance to the fisheries for the three bordering countries.

Assessing the uncertainties of phytoplankton absorption-based model estimates of marine net primary productivity

Satellite-derived phytoplankton pigment absorption （aph） has been used as a key predictor of phytoplankton photosynthetic efficiency to estimate global ocean net primary production （NPP）. In this study, an aph-based NPP model （AbPM） with four input parameters including the photosynthetically available radiation （PAR）, diffuse attenuation at 490 nm （Ka（490））, euphotic zone depth （Zeu） and the phytoplankton pigment absorption coefficient （aph） is compared with the chlorophyll-based model and carbon-based model. It is found that the AbPM has significant advantages on the ocean NPP estimation compared with the chlorophyll-based model and carbon- based model. For example, AbPM greatly outperformed the other two models at most monitoring sites and had the best accuracy, including the smallest values of RMSD and bias for the NPP estimate, and the best correlation between the observations and the modeled NPPs. In order to ensure the robustness of the model, the uncertainty in NPP estimates of the AbPM was assessed using a Monte Carlo simulation. At first, the frequency histograms of simple difference （fi）, and logarithmic difference （~LOG） between model estimates and in situ data confirm that the two input parameters （Zeu and PAR） approximate the Normal Distribution, and another two input parameters （aph and Ka（490）） approximate the logarithmic Normal Distribution. Second, the uncertainty in NPP estimates in the AbPM was assessed by using the Monte Carlo simulation. Here both the PB （percentage bias）, defined as the ratio of ANPP to the retrieved NPP, and the CV （coefficient of variation）, defined as the ratio of the standard deviation to the mean are used to indicate the uncertainty in the NPP brought by input parameter to AbPM model. The uncertainty related to magnitude is denoted by PB and the uncertainty related to scatter range is denoted by CV. Our investigations demonstrate that PB of NPP uncertainty brought by all parameters with an annual mean of 5.5% covered a range of -5%-15% for the global ocean. The PB uncertainty of AbPM model was mainly caused by aph; the PB of NPP uncertainty brought by aph had an annual mean of 4.1% for the global ocean. The CV brought by all the parameters with an annual mean of 105% covered a range of 98%-134% for global ocean. For the coastal zone of Antarctica with higher productivity, the PB and CV of NPP uncertainty brought by all parameters had annual means of 7.1% and 121%, respectively, which are significantly larger than those obtained in the global ocean. This study suggests that the NPPs estimated by AbPM model are more accurate than others, but the magnitude and scatter range of NPP errors brought by input parameter to AbPM model could not be neglected, especially in the coastal area with high productivity. So the improving accuracy of satellite retrieval of input parameters should be necessary. The investigation also confirmed that the SST related correction is effective for improving the model accuracy in low temperature condition.

Simulation of the Ecosystem Productivity Responses to Aerosol Diffuse Radiation Fertilization Effects over the Pan-Arctic during 2001–19

The pan-Arctic is confronted with air pollution transported from lower latitudes.Observations have shown that aerosols help increase plant photosynthesis through the diffuse radiation fertilization effects(DRFEs).While such DRFEs have been explored at low to middle latitudes,the aerosol impacts on pan-Arctic ecosystems and the contributions by anthropogenic and natural emission sources remain less quantified.Here,we perform regional simulations at 0.2o×0.2ousing a well-validated vegetation model(Yale Interactive terrestrial Biosphere,YIBs)in combination with multi-source of observations to quantify the impacts of aerosol DRFEs on the net primary productivity(NPP)in the pan-Arctic during 2001-19.Results show that aerosol DRFEs increase pan-Arctic NPP by 2.19 Pg C(12.8%)yr^(-1)under clear-sky conditions,in which natural and anthropogenic sources contribute to 8.9% and 3.9%,respectively.Under all-sky conditions,such DRFEs are largely dampened by cloud to only 0.26 Pg C(1.24%)yr^(-1),with contributions of 0.65% by natural and 0.59% by anthropogenic species.Natural aerosols cause a positive NPP trend of 0.022% yr^(-1)following the increased fire activities in the pan-Arctic.In contrast,anthropogenic aerosols induce a negative trend of-0.01% yr^(-1)due to reduced emissions from the middle latitudes.Such trends in aerosol DRFEs show a turning point in the year of 2007 with more positive NPP trends by natural aerosols but negative NPP trends by anthropogenic aerosols thereafter.Though affected by modeling uncertainties,this study suggests a likely increasing impact of aerosols on terrestrial ecosystems in the pan-Arctic under global warming.

Submarine groundwater discharge enhances primary productivity in the Yellow Sea, China: Insight from the separation of fresh and recirculated components

Submarine groundwater discharge(SGD)is being increasingly recognized as a significant source of nutrient into coastal waters,and generally comprises two components:submarine fresh groundwater discharge(SFGD)and recirculated saline groundwater discharge(RSGD).The separate evaluation of SFGD and RSGD is extremely limited as compared to the conventional estimation of total SGD and associated nutrient fluxes,especially in marginal-scale regions.In this study,new high-resolution radium isotopes data in seawater and coastal groundwater enabled an estimation of SGD flux in a typical marginal sea of the Yellow Sea.By establishing 226Ra and 228Ra mass balance models,we obtained the SGD-derived radium fluxes,and then estimated the SFGD and RSGD fluxes through a two end-member model.The results showed that the total SGD flux into the Yellow Sea was equivalent to approximately 6.6 times the total freshwater discharge of surrounding rivers,and the SFGD flux accounted for only 5.2%–8.8%of the total SGD.Considering the nutrient concentrations in coastal fresh and saline groundwater,we obtained the dissolved inorganic nutrient fluxes(mmol m^(-2) yr^(-1))to be 52–353 for nitrogen(DIN),0.21–1.4 for phosphorus(DIP),34–226 for silicon(DSi)via SFGD,and 69–262 for DIN,1.0–3.9 for DIP,70–368 for DSi via RSGD,with the sum of nutrient fluxes equaling to(1.8–9.3)-fold,(1.3–5.6)-fold and(2.0–9.5)-fold of the riverine inputs.Compared to the conventional estimation of the total SGD flux,the nutrient fluxes derived from the separation of SFGD and RSGD were(1.6–2.1),(1.6–1.8)and(4.0–4.9)times lower for DIN,DIP and DSi,respectively,indicating that the estimates by separating SFGD and RSGD could be conservative and representative results of the Yellow Sea.Furthermore,we suggested that SGD played an important role in nutrient sources among all the traditional nutrient inputs sources,providing 15%–48%,33%–68%and 14%–43%of the total DIN,DIP and DSi input fluxes into the Yellow Sea,and the high nutrient stoichiometric ratios(i.e.,DIN/DIP)in SGD probably contributed to the increasing ratios in the Yellow Sea.In addition delivering large amounts of nutrient into the Yellow Sea,SGD would create primary productivity of 10–49,1.6–6.8 and 8.8–42 g C m^(-2)yr^(-1) based on N,P and Si,which were equivalent to 5.2%–27%,0.9%–3.7%and 4.7%–23%of the total primary productivity,respectively.In particular,the SFGD-derived DIN flux can be converted to primary productivity of 4.2–28 g C m^(-2)yr^(-1) thus demonstrating the disproportionately large role of SFGD in ecological environment of the Yellow Sea relative to its flux.Therefore,we conclude that SGD,particularly SFGD,plays an important role as a nutrient source for the Yellow Sea,and not only affects nutrient budgets and structures but also enhances the primary productivity.

Biogenic silica concentration as a marine primary productivity proxy in the Holsteinsborg Dyb, West Greenland, during the last millennium

We analyzed the biogenic silica(BSi)content and produced a diatom-based summer sea-surface temperature(SST)reconstruction for sediment core GC4 from the Holsteinsborg Dyb,West Greenland.Our aim was to reconstruct marine productivity and climatic fluctuations during the last millennium.Increased BSi content and diatom abundance suggest relatively high marine productively during the interval of AD 1000–1400,corresponding in time to the Medieval Warm Period(MWP).The summer SST reconstruction indicates relatively warm conditions during AD 900–1100,followed by cooling after AD 1100.An extended cooling period during AD 1400–1900 is characterized by prolonged low in reconstructed SST and high sea-ice concentration.The BSi values fluctuated during this period,suggesting varying marine productivity during the Little Ice Age(LIA).There is no significant correlation between the BSi content and SST during the last millennium,suggesting that the summer SST has little influence on marine productively in the Holsteinsborg Dyb.A good correspondence between the BSi content and the element Ti counts in core GC4 suggests that silicate-rich meltwater from the Greenland ice sheet was likely responsible for changes in marine productively in the Holsteinsborg Dyb.

Recent Advances of Bioactive Marine Natural Products in Drug Discovery

Marine natural products(MNPs)are valuable resources for drug development.To date,17 drugs from marine sources are in clinical use,and 33 pharmaceutical compounds are in clinical trials.Presently the success of drug development from the marine resources is higher than the industry average.It is a feasible strategy to conduct the discovery of druglead compounds based on marine chemical ecology by fully exploiting the pharmacological potential of marine chemical defense matters.In the search for bioactive MNPs,our group has constructed a biological resources library including more than 1500 strains of fungi.Focusing on the strategy of Blue Drug Library,we have discovered a series of novel MNPs with abundant biological functions.Highly efficient and scalable total synthesis of(+)-aniduquinolone A(44)and pesimquinolone I(48)have been completed,which will facilitate access to sufficient quantities of candidates for in vivo pharmacological and toxicological studies.As a nucleoprotein(NP)inhibitor,QLA(75)possesses significant anti-influenza A virus(IAV)activities both in vitro and in vivo.CHNQD-00803(76)is a potent and selective AMP-activated kinase(AMPK)activator that can effectively inhibit metabolic disorders and metabolic dysfunction-associated steatohepatitis(MASH)progression.Moreover,we identified two new candidate molecules with potent anti-hepatocellular carcinoma effects.Particularly,as a natural guanine-nucleotide exchange factors for ADP-ribosylation factor GTPases(Arf-GEFs)inhibitor prodrug,CHNQD-01255(78)is qualified to be developed as a targeted candidate anticancer drug,which may be promising to apply for cancer immunotherapy.Hence,it is evident that MNPs play an important role in drug development.

Spatio-temporal distribution of net primary productivity along the northeast China transect and its response to climatic change

An improved Carnegie Ames Stanford Approach model （CASA model） was used to estimate the net primary productivity （NPP） of the Northeast China Transect （NECT） every month from 1982 to 2000. The spatial-temporal distribution of NPP along NECT and its response to climatic change were also analyzed. Results showed that the change tendency of NPP spatial distribution in NECT is quite similar to that of precipitation and their spatial correlation coefficient is up to 0.84 （P 〈 0.01）. The inter-annual variation of NPP in NECT is mainly affected by the change of the aestival NPP every year, which accounts for 67.6% of the inter-annual increase in NPP and their spatial correlation coefficient is 0.95 （P 〈 0.01）. The NPP in NECT is mainly cumulated between May and September, which accounts for 89.8% of the annual NPP. The NPP in summer （June to August） accounts for 65.9% of the annual NPP and is the lowest in winter. Recent climate changes have enhanced plant growth in NECT. The mean NPP increased 14.3% from 1980s to 1990s. The inter-annual linear trend of NPP is 4.6 gC·m^-2·a^-1, and the relative trend is 1.17%, which owns mainly to the increasing temperature.

Estimation of Net Primary Productivity of Terrestrial Vegetation in China by Remote Sensing

Among the many approaches for studying the net primary productivity (NPP), a new method by using remote sensing was introduced in this paper. With spectral information source (the visible band, near infrared band and thermal infrared band) of NOAA-AVHRR, we can get the relative index and parameters, which can be used for estimating NPP of terrestrial vegetation. By means of remote sensing, the estimation of biomass and NPP is mainly based on the models of light energy utilization. In other words, the biomass and NPP can be calculated from the relation among NPP, absorbed photosynthetical active radiation (APAR) and the rate (epsilon) of transformation of APAR to organic matter, thus: NPP = ( FPAR x PAR) x [epsilon * x sigma (T) x sigma (E) x sigma (S) x (1 - Y-m) x (1 - Y-g)]. Based upon remote sensing ( RS) and geographic information system (GIS), the NPP of terrestrial vegetation in China in every ten days was calculated, and the annual NPP was integrated. The result showed that the total NPP of terrestrial vegetation in China was 6.13 x 10(9) t C . a(-1) in 1990 and the maximum NPP was 1 812.9 g C/m(2). According to this result, the spatio-temporal distribution of NPP was analyzed. Comparing to the statistical models, the RS model, using area object other than point one, can better reflect the distribution of NPP, and match the geographic distribution of vegetation in China.

Storage of biomass and net primary productivity in desert shrubland of Artemisia ordosica on Ordos Plateau of Inner Mongolia, China

Biomass and net primary productivity （NPP） are two important parameters in determining ecosystem carbon pool and carbon sequestration. The biomass storage and NPP in desert shrubland of Artemisia ordosica on Ordos Plateau were investigated with method of harvesting standard size shrub in the growing season （June-October） of 2006. Results indicated that above- and belowground biomass of the same size shrubs showed no significant variation in the growing season （p〉0.1）, but annual biomass varied significantly （p〈 0.01）. In the A. ordosica community, shrub biomass storage was 699.76-1246.40 g.m^-2 and annual aboveground NPP was 224.09 g-m^-2·a^-1. Moreover, shrub biomass and NPP were closely related with shrub dimensions （cover and height） and could be well predicted by shrub volume using power regression.

Assessing the Dynamics of Grassland Net Primary Productivity in Response to Climate Change at the Global Scale

Understanding the net primary productivity(NPP) of grassland is crucial to evaluate the terrestrial carbon cycle. In this study, we investigated the spatial distribution and the area of global grassland across the globe. Then, we used the Carnegie-Ames-Stanford Approach(CASA) model to estimate global grassland NPP and explore the spatio-temporal variations of grassland NPP in response to climate change from 1982 to 2008. Results showed that the largest area of grassland distribution during the study period was in Asia(1737.23 × 104 km^2), while the grassland area in Europe was relatively small(202.83 × 10~4 km^2). Temporally, the total NPP increased with fluctuations from 1982 to 2008, with an annual increase rate of 0.03 Pg C/yr. The total NPP experienced a significant increasing trend from 1982 to 1995, while a decreasing trend was observed from 1996 to 2008. Spatially, the grassland NPP in South America and Africa were higher than the other regions, largely as a result of these regions are under warm and wet climatic conditions. The highest mean NPP was recorded for savannas(560.10 g C/(m^2·yr)), whereas the lowest was observed in open shrublands with an average NPP of 162.53 g C/(m^2·yr). The relationship between grassland NPP and annual mean temperature and annual precipitation(AMT, AP, respectively) varies with changes in AP, which indicates that, grassland NPP is more sensitive to precipitation than temperature.

Estimation of net primary productivity in China using remote sensing data

It is significant to estimate terrestrial net primary productivity (NPP) accurately not only for global change research, but also for natural resources management to achieve sustainable development. Remote sensing data can describe spatial distribution of plant resources better. So, in this paper an NPP model based on remote sensing data and climate data is developed. And 1km resolution AVHRR NDVI data are used to estimate the spatial distribution and seasonal change of NPP in China. The results show that NPP estimated using remote sensing data are more close to truth. Total annual NPP in China is 2.645X109 tC. The spatial distribution of NPP in China is mainly affected by precipitation and has the trend of decreasing from southeast to northwest.

The net primary productivity of Mid-Jurassic peatland and its control factors: Evidenced by the Ordos Basin

Using the large-scale thick 4# coal seam from the Mid-Jurassic in the southern Ordos Basin as an example, this paper studied the net primary productivity(NPP) level of the Mid-Jurassic peatland, and discussed its control factors. Geophysical logging signals were used for a spectrum analysis to obtain the Milankovitch cycle parameters in coal seam. These were then used to calculate the accumulation rate of the residual carbon in 4# coal seam. The carbon loss can be calculated according to the density and residual carbon content of 4# coal seam. Then, the total carbon accumulation rate of the peatland was further derived, and the NPP of peatland was determined. The results show that the NPP of MidJurassic peatland is higher than that of Holocene at the same latitude. Comprehensive analysis indicates that the temperature, carbon dioxide and oxygen levels in atmosphere are the main control factors of the NPP of Mid-Jurassic peatland.

Effects of climate change on phenology and primary productivity in the desert steppe of Inner Mongolia

Variations in temperature and precipitation affect local ecosystems. Considerable spatial and temporal heterogeneity exists in arid ecosystems such as desert steppes. In this study, we analyzed the spatiotemporal dy- namics of climate and vegetation phenology in the desert steppe of Inner Mongolia, China using meteorological data （1961-2010） from 11 stations and phenology data （2004-2012） from 6 ecological observation stations. We also estimated the gross primary production for the period of 1982-2009 and found that the annual mean tem- perature increased at a rate of 0.47~C/decade during 1961-2010, with the last 10 years being consistently warmer than the 50 years as an average. The most significant warming occurred in winters. Annual precipitation slightly decreased during the 50-year period, with summer precipitation experiencing the highest drop in the last 10 years, and spring precipitation, a rise. Spatially, annual precipitation increased significantly in the northeastern and eastern central areas next to the typical steppe. From 2004 to 2012, vegetation green-up and senescence date advanced in the study area, shortening the growing season. Consequently, the primary productivity of the desert steppe de- creased along the precipitation gradient from southeast to northwest. Temporally, productivity increased during the period of 1982-1999 and significantly decreased after 2000. Overall, the Last decade witnessed the most dramatic climatic changes that were likely to negatively affect the desert steppe ecosystem. The decreased primary produc- tivity, in particular, decreases ecosystem resilience and impairs the livelihood of local farmers and herdsmen.

Carbon storage and net primary productivity in Canadian boreal mixedwood stands

Canadian boreal mixedwood forests are extensive,with large potential for carbon sequestration and storage;thus,knowledge of their carbon stocks at different stand ages is needed to adapt forest management practices to help meet climate-change mitigation goals.Carbon stocks were quantified at three Ontario boreal mixedwood sites.A harvested stand,a juvenile stand replanted with spruce seedlings and a mature stand had total carbon stocks(±SE)of 133±13 at age 2,130±13 at age 25,and 207±15 Mg C ha^-1 at age 81 years.At the clear-cut site,stocks were reduced by about 40%or 90 Mg C ha^-1 at harvest.Vegetation held 27,34 and 62%of stocks,while detritus held 34,29 and 13%of stocks at age 2,25 and 81,respectively.Mineral soil carbon stocks averaged 51 Mg C ha^-1,and held 38,37 and 25%of stocks.Aboveground net primary productivity(±SE)in the harvested and juvenile stand was 2.1±0.2 and 3.7±0.3 Mg C ha^-1 per annum(p.a.),compared to 2.6±2.5 Mg C ha^-1 p.a.in the mature stand.The mature canopies studied had typical boreal mixedwood composition and mean carbon densities of 208 Mg C ha^-1,which is above average for managed Canadian boreal forest ecosystems.A comparison of published results from Canadian boreal forest ecosystems showed that carbon stocks in mixedwood stands are typically higher than coniferous stands at all ages,which was also true for stocks in vegetation and detritus.Also,aboveground net primary productivity was typically found to be higher in mixedwood than in coniferous boreal forest stands over a range of ages.Measurements from this study,together with those published from the other boreal forest stands demonstrate the potential for enhanced carbon sequestration through modified forest management practices to take advantage of Canadian boreal mixedwood stand characteristics.

Estimation of net primary productivity and its driving factors in the Ili River Valley,China

Net primary productivity（NPP）, as an important variable and ecological indicator in grassland ecosystems, can reflect environmental change and the carbon budget level. The Ili River Valley is a wetland nestled in the hinterland of the Eurasian continent, which responds sensitively to the global climate change. Understanding carbon budget and their responses to climate change in the ecosystem of Ili River Valley has a significant effect on the adaptability of future climate change and sustainable development. In this study, we calculated the NPP and analyzed its spatio-temporal pattern of the Ili River Valley during the period 2000–2014 using the normalized difference vegetation index（NDVI） and an improved Carnegie-Ames-Stanford（CASA） model. Results indicate that validation showed a good performance of CASA over the study region, with an overall coefficient of determination（R2） of 0.65 and root mean square error（RMSE） of 20.86 g C/（m^2·a）. Temporally, annual NPP of the Ili River Valley was 599.19 g C/（m^2·a） and showed a decreasing trend from 2000 to 2014, with an annual decrease rate of –3.51 g C/（m^2·a）. However, the spatial variation was not consistent, in which 55.69% of the areas showed a decreasing tendency, 12.60% of the areas remained relatively stable and 31.71% appeared an increasing tendency. In addition, the decreasing trends in NPP were not continuous throughout the 15-year period, which was likely being caused by a shift in climate conditions. Precipitation was found to be the dominant climatic factor that controlled the inter-annual variability in NPP. Furthermore, the correlations between NPP and climate factors differed along the vertical zonal. In the medium-high altitudes of the Ili River Valley, the NPP was positively correlated to precipitation and negatively correlated to temperature and net radiation. In the low-altitude valley and high-altitude mountain areas, the NPP showed a negative correlation with precipitation and a weakly positive correlation with temperature and net radiation. The results suggested that the vegetation of the Ili River Valley degraded in recent years, and there was a more complex mechanism of local hydrothermal redistribution that controlled the growth of vegetation in this valley ecosystem.

Effects of grazing on net primary productivity,evapotranspiration and water use efficiency in the grasslands of Xinjiang,China

Grazing is a main human activity in the grasslands of Xinjiang, China. It is vital to identify the effects of grazing on the sustainable utilization of local grasslands. However, the effects of grazing on net primary productivity （NPP）, evapotranspiration （ET） and water use efficiency （WUE） in this region remain unclear. Using the spatial Biome-BGC grazing model, we explored the effects of grazing on NPP, ET and WUE across the different regions and grassland types in Xinjiang during 1979-2012. NPP, ET and WUE under the grazed scenario were generally lower than those under the ungrazed scenario, and the differences showed increasing trends over time. The decreases in NPP, ET and WUE varied significantly among the regions and grassland types. NPP decreased as follows： among the regions, Northern Xinjiang （16.60 g C/（m2·a））, Tianshan Mountains （15.94 g C/（m2·a）） and Southern Xinjiang （-3.54 g C/（m2·a））; and among the grassland types, typical grasslands （25.70 g C/（m2·a））, swamp meadows （25.26 g C/（m2·a））, mid-mountain meadows （23.39 g C/（m2·a））, alpine meadows （6.33 g C/（m2·a））, desert grasslands （5.82 g C/（m2·a）） and saline meadows （2.90 g C/（me.a））. ET decreased as follows： among the regions, Tianshan Mountains （28.95 mm/a）, Northern Xinjiang （8.11 mm/a） and Southern Xinjiang （7.57 mm/a）; and among the grassland types, mid-mountain meadows （29.30 mm/a）, swamp meadows （25.07 mm·a）, typical grasslands （24.56 mm/a）, alpine meadows （20.69 mm/a）, desert grasslands （11.06 mm/a） and saline meadows （3.44 mm/a）. WUE decreased as follows： among the regions, Northern Xinjiang （0.053 g C/kg H2O）, Tianshan Mountains （0.034 g C/kg H2O） and Southern Xinjiang （0.012 g C/kg H2O）; and among the grassland types, typical grasslands （0.0609 g C/kg H2O）, swamp meadows （0.0548 g C/kg H2O）, mid-mountain meadows （0.0501 g C/kg H2O）, desert grasslands （0.0172 g C/kg H2O）, alpine meadows （0.0121 g C/kg H2O） and saline meadows （0.0067 g C/kg H2O）. In general, the decreases in NPP and WUE were more significant in the regions with relatively high levels of vegetation growth because of the high grazing intensity in these regions. The decreases in ET were significant in mountainous areas due to the terrain and high grazing intensity.

Spatial-temporal variations in net primary productivity in the Arctic from 2003 to 2016

The area of Arctic sea ice has dramatically decreased, and the length of the open water season has increased;these patterns have been observed by satellite remote sensing since the 1970 s. In this paper, we calculate the net primary productivity(NPP, calculated by carbon) from 2003 to 2016 based on sea ice concentration products,chlorophyll a(Chl a) concentration, photosynthetically active radiation(PAR), sea surface temperature(SST), and sunshine duration data. We then analyse the spatiotemporal changes in the Chl a concentration and NPP and further investigate the relations among NPP, the open water area, and the length of the open water season. The results indicate that(1) the Chl a concentration increased by 0.025 mg/m^3 per year;(2) the NPP increased by 4.29 mg/(m^2·d) per year, reaching a maximum of 525.74 mg/(m^2·d) in 2016;and(3) the Arctic open water area increased by 57.23×10^3 km^2/a, with a growth rate of 1.53 d/a for the length of the open water season. The annual NPP was significantly positively related to the open water area, the length of the open water season and the SST.The daily NPP was also found to have a lag correlation with the open water area, with a lag time of two months.With global warming, NPP has maintained an increasing trend, with the most significant increase occurring in the Kara Sea. In summary, this study provides a macroscopic understanding of the distribution of phytoplankton in the Arctic, which is valuable information for the evaluation and management of marine ecological environments.

Dynamic change of net primary productivity and fractional vegetation cover in the Yellow River Basin using multi-temporal AVHRR NDVI Data

An exponential relationship between net primary productivity (NPP) and integrated NDVI has been found in this paper. Based on the relationship and using multi-temporal 8 km resolution NOAA AVHRR-NDVI data, the spatial distribution and dynamic change of NPP and fractional vegetation cover in the Yellow River Basin from 1982 to 1999 are analyzed. Finally, the effect of rainfall on NDVI is examined. Results show that mean NPP and fractional vegetation cover have an inclining trend for the whole basin, and rainfall in flood season influences vegetation cover most.