Quantitative Assessment of the Relative Contributions of Climate and Human Factors to Net Primary Productivity in the Ili River Basin of China and Kazakhstan

It is necessary to quantitatively study the relationship between climate and human factors on net primary productivity(NPP)inorder to understand the driving mechanism of NPP and prevent desertification.This study investigated the spatial and temporal differentiation features of actual net primary productivity(ANPP)in the Ili River Basin,a transboundary river between China and Kazakhstan,as well as the proportional contributions of climate and human causes to ANPP variation.Additionally,we analyzed the pixel-scale relationship between ANPP and significant climatic parameters.ANPP in the Ili River Basin increased from 2001 to 2020 and was lower in the northeast and higher in the southwest;furthermore,it was distributed in a ring around the Tianshan Mountains.In the vegetation improvement zone,human activities were the dominant driving force,whereas in the degraded zone,climate change was the primary major driving force.The correlation coefficients of ANPP with precipitation and temperature were 0.322 and 0.098,respectively.In most areas,there was a positive relationship between vegetation change,temperature and precipitation.During 2001 to 2020,the basin’s climatic change trend was warm and humid,which promoted vegetation growth.One of the driving factors in the vegetation improvement area was moderate grazing by livestock.

Temporal and spatial variations of net primary productivity and its response to groundwater of a typical oasis in the Tarim Basin, China

Net primary productivity (NPP) of the vegetation in an oasis can reflect the productivity capacity of a plant community under natural environmental conditions. Owing to the extreme arid climate conditions and scarce precipitation in the arid oasis regions, groundwater plays a key role in restricting the development of the vegetation. The Qira Oasis is located on the southern margin of the Taklimakan Desert (Tarim Basin, China) that is one of the most vulnerable regions regarding vegetation growth and water scarcity in the world. Based on remote sensing images of the Qira Oasis and daily meteorological data measured by the ground stations during the period 2006-2019, this study analyzed the temporal and spatial patterns of NPP in the oasis as well as its relation with the variation of groundwater depth using a modified Carnegie Ames Stanford Approach (CASA) model. At the spatial scale, NPP of the vegetation decreased from the interior of the Qira Oasis to the margin;at the temporal scale, NPP of the vegetation in the oasis fluctuated significantly (ranging from 29.80 to 50.07 g C/(m2•month)) but generally showed an increasing trend, with the average increase rate of 0.07 g C/(m2•month). The regions with decreasing NPP occupied 64% of the total area of the oasis. During the study period, NPP of both farmland and grassland showed an increasing trend, while that of forest showed a decreasing trend. The depth of groundwater was deep in the south of the oasis and shallow in the north, showing a gradual increasing trend from south to north. Groundwater, as one of the key factors in the surface change and evolution of the arid oasis, determines the succession direction of the vegetation in the Qira Oasis. With the increase of groundwater depth, grassland coverage and vegetation NPP decreased. During the period 2008-2015, with the recovery of groundwater level, NPP values of all types of vegetation with different coverages increased. This study will provide a scientific basis for the rational utilization and sustainable management of groundwater resources in the oasis.

Seasonal Responses of Net Primary Productivity of Vegetation to Phenological Dynamics in the Loess Plateau, China

With global warming, the great changes in the patterns of plant growth have occurred. The conditions in early spring and late autumn have changed the process of vegetation photosynthesis, which are expected to have a significant impact on net primary productivity(NPP) and affect the global carbon cycle. Currently, the seasonal response characteristics of NPP to phenological changes in dryland ecosystems are still not well defined. This article calibrated and analyzed the normalized difference vegetation index(NDVI)time series of Advanced Very-High-Resolution Radiometer(AVHRR) data from 1982 to 2015 in the Loess Plateau, China. The spatial and temporal distributions of vegetation phenology and NPP in the Loess Plateau under semihumid and semiarid conditions were investigated. The seasonal variation in the NPP response to vegetation phenology under the climate change was also analyzed. The results showed that, different from the northern forest, there was distinct spatial heterogeneity in the effect of climate change on the dynamic change in vegetation growth in the Loess Plateau: 1) an advance of the start of the growing season(SOS) and a delay of the end of the growing season(EOS) significantly increased the NPP in spring and autumn, respectively, in the humid southeast;2) in the arid northwest, the NPP did not significantly increase in spring and autumn but significantly decreased in summer.

Spatiotemporal variation in vegetation net primary productivity and its relationship with meteorological factors in the Tarim River Basin of China from 2001 to 2020 based on the Google Earth Engine

Vegetation growth status is an important indicator of ecological security.The Tarim River Basin is located in the inland arid region of Northwest China and has a highly fragile ecological environment.Assessing the vegetation net primary productivity(NPP)of the Tarim River Basin can provide insights into the vegetation growth variations in the region.Therefore,based on the Google Earth Engine(GEE)cloud platform,we studied the spatiotemporal variation of vegetation NPP in the Tarim River Basin(except for the eastern Gobi and Kumutag deserts)from 2001 to 2020 and analyzed the correlations between vegetation NPP and meteorological factors(air temperature and precipitation)using the Sen slope estimation method,coefficient of variation,and rescaled range analysis method.In terms of temporal characteristics,vegetation NPP in the Tarim River Basin showed an overall fluctuating upward trend from 2001 to 2020,with the smallest value of 118.99 g C/(m2•a)in 2001 and the largest value of 155.07 g C/(m2•a)in 2017.Regarding the spatial characteristics,vegetation NPP in the Tarim River Basin showed a downward trend from northwest to southeast along the outer edge of the study area.The annual average value of vegetation NPP was 133.35 g C/(m2•a),and the area with annual average vegetation NPP values greater than 100.00 g C/(m2•a)was 82,638.75 km2,accounting for 57.76%of the basin.The future trend of vegetation NPP was dominated by anti-continuity characteristic;the percentage of the area with anti-continuity characteristic was 63.57%.The area with a significant positive correlation between vegetation NPP and air temperature accounted for 53.74%of the regions that passed the significance test,while the area with a significant positive correlation between vegetation NPP and precipitation occupied 98.68%of the regions that passed the significance test.Hence,the effect of precipitation on vegetation NPP was greater than that of air temperature.The results of this study improve the understanding on the spatiotemporal variation of vegetation NPP in the Tarim River Basin and the impact of meteorological factors on vegetation NPP.

Identification of Milankovitch Cycles and Calculation of Net Primary Productivity of Paleo-peatlands using Geophysical Logs of Coal Seams

Individual coal seams formed in paleo-peatlands represent sustained periods of terrestrial carbon accumulation and a key environmental indicator attributed to this record is the rate of carbon accumulation.Determining the rate of carbon accumulation requires a measure of time contained within the coal.This study aimed to determine this rate via the identification of Milankovitch orbital cycles in the coals.The geophysical log is an ideal paleoclimate proxy and has been widely used in the study of sedimentary records using spectral analysis.Spectral analyses of geophysical log from thick coal seams can be used to identify the Milankovitch cycles and to calculate the period of the coal deposition.By considering the carbon loss during coalification,the long-term average carbon accumulation rate and net primary productivity(NPP)of paleo-peatlands in coal seams can be obtained.This review paper presents the procedures of analysis,assessment of results and interpretation of geophysical logs in determining the NPP of paleo-peatlands.

Research Advances in Net Primary Productivity of Terrestrial Ecosystem

The net primary productivity of vegetation reflects the total amount of carbon fixed by plants through photosynthesis each year. The study of vegetation net primary productivity is one of the core contents of global change and terrestrial ecosystems. This article reviews the current research status of net primary productivity of terrestrial vegetation, and comprehensively analyzes the advantages and disadvantages of three types of productivity estimation models, climate relative models, biogeochemical models, and light energy utilization models. The light energy utilization models have become the mainstream method for estimating vegetation net primary productivity because they can directly use remote sensing data. However, there are still many deficiencies in the estimation of vegetation net primary productivity, which need to be further improved and tested.

Net Primary Productivity and Management Potential of Artificial Pinus tabulaeformis Forest in Shanxi Province

The dynamic variation of net primary productivity of artificial Pinus tabulaeformis forest was studied in Shanxi Province,and potential productivity of artificial forest was predicted to provide reference for improving quality of regional forest stand. The regression equation was established by using the stratification and harvesting method with the relative growth model. Cumulative method and Thornthwaite Memorial model was used to estimate the actual and potential productivity of the forest. The productivity of P. tabulaeformis forest increased with the increase of age and started decrease with the mature period. The actual productivity of P. tabulaeformis forest was 4. 462 t/( ha·year); the contribution rate of trees was 72. 17% of the total productivity,and with the increase of age,the total biomass increased but productivity decreased at late near-mature forest; the contribution rate of herb layer was 21. 16% in the young forest stage,and then decreased gradually. On the contrary,the contribution rate of shrub layer increased gradually,and the contribution rate of the grassland was more than that of the herb layer,so as the key period of structural management; the average potential productivity of forest was 8. 422 t/( ha·year),and the potential space of P. tabulaeformis was at least 32% in Shanxi Province. In conclusion,the potential space of productivity of P. tabulaeformis was at least 32%,and the primary limiting factor of P. tabulaeformis forest productivity in Shanxi Province was rainfall.

Response of vegetation net primary productivity to climate change scenarios in the Loess Plateau of China--A case study of the Yangou watershed

Vegetation net primary productivity(NPP)is a sensitive indicator to characterize the response of terrestrial ecosystems to the climate change.Projections of the NPP changes of the Loess Plateau under future climate scenarios have great significances in revealing the interactions among terrestrial ecosystems and climatic systems,as well as instructing future vegetation construction of this region.Here,we carried out a case study on the Yangou watershed in the Loess Plateau.Using the vegetation-producing process model(VPP)established for such small watersheds,we simulated the NPP of the Yangou watershed under different scenarios of climate changes.The results showed that the NPP significandy increased with the precipitation increasing and evidently decreased with the temperature increasing where the climate change occurred in the whole year or in the summer half year.However,where the climate change occurred in the winter half year,the increased precipitation had little effect on the NPP,and the increased temperature significantly reduced the NPP.There were clear differences among the response sensitivities of different vegetation types with trees and shrubs were more sensitive to the changes in temperature and precipitation than crops and grasses.Currently,the most favourable climate change scenario to the NPP in the Yangou watershed was T0P15 under which the precipitation increased by 15%and the temperature did not changed,in the whole year;in the meantime,the most unfavourable climate change scenarios was T2P-15 under which the precipitation declined by 15%and the temperature increased by 2℃,in the whole year.

Ecosystem Services Evaluation of Karst New Urban Areas Based on Net Primary Productivity of Guanshanhu District, Guiyang, Guizhou Province, China

Net Primary Productivity (NPP) is the basis of the material and energy transport calculation in ecosystem studies. NPP directly reflects the production capacity of plant communities under natural conditions. Ecosystem services are hot topics in the field of ecology. Many studies calculate ecosystem service value based on NPP. Taking Guanshanhu District of Guiyang City, Guizhou Province as the research object, using TM, ETM+, Gaofen2 and MOD17A3HGF.006 as data sources, this paper analyzed the change of ecosystem service value based on NPP in 2000, 2010 and 2020. The results showed that the area of forest ecosystem increased during 2000-2010 and decreased during 2010-2020. The artificial surface grew rapidly from 1146.82 hm2 to 7544.29 hm2 during 2000-2020. The farmland ecosystem decreased from 13308.29 hm2 to 6342.33 hm2 during 2000-2020. With the dynamic changes in ecosystem spatial distribution and component structure, the total NPP in 2000, 2010 and 2020 was 12.58 × 104 t, 11.90 × 104 t and 11.78 × 104 t, respectively, showing a decreasing trend. The total value of natural and semi-natural ecosystems services based on NPP showed an increasing trend, which was ￥ 6.938 × 108 in 2000, ￥ 8.052 × 108 in 2010 and ￥ 10.306 × 108 in 2020 respectively. The ecosystem contributed the most to the ecological service value in 2000 was farmland, but in 2010 and 2020, it was the forest ecosystem. The ecological service value of grassland and wetland was relatively small, while the ratio of the wetland ecological service value displayed a decreasing trend. In the future, it is necessary to establish a strict pretrial system for land use, so as to effectively protect the natural and semi-natural ecosystems and fulfill the growing ecological demands of residents.

Variation of net primary productivity and its drivers in China’s forests during 2000-2018

Background:Net primary productivity(NPP)in forests plays an important role in the global carbon cycle.However,it is not well known about the increase rate of China’s forest NPP,and there are different opinions about the key factors controlling the variability of forest NPP.Methods:This paper established a statistics-based multiple regression model to estimate forest NPP,using the observed NPP,meteorological and remote sensing data in five major forest ecosystems.The fluctuation values of NPP and environment variables were extracted to identify the key variables influencing the variation of forest NPP by correlation analysis.Results:The long-term trends and annual fluctuations of forest NPP between 2000 and 2018 were examined.The results showed a significant increase in forest NPP for all five forest ecosystems,with an average rise of 5.2 gC·m-2·year-1 over China.Over 90%of the forest area had an increasing NPP range of 0-161 gC·m-2·year-1.Forest NPP had an interannual fluctuation of 50-269 gC.m-2·year-1 for the five major forest ecosystems.The evergreen broadleaf forest had the largest fluctuation.The variability in forest NPP was caused mainly by variations in precipitation,then by temperature fluctuations.Conclusions:All five forest ecosystems in China exhibited a significant increasing NPP along with annual fluctuations evidently during 2000-2018.The variations in China’s forest NPP were controlled mainly by changes in precipitation.

Elevation response of above-ground net primary productivity for Picea crassifolia to climate change in Qilian Mountains of Northwest China based on tree rings

Current ecosystem models used to simulate global terrestrial carbon balance generally suggest that terrestrial landscapes are stable and mature,but terrestrial net primary productivity(NPP)data estimated without accounting for disturbances in species composition,environment,structure,and ecological characteristics will reduce the accuracy of the global carbon budget.Therefore,the steady-state assumption and neglect of elevation-related changes in forest NPP is a concern.The Qilian Mountains are located in continental climate zone,and vegetation is highly sensitive to climate change.We quantified aboveground biomass(AGB)and aboveground net primary productivity(ANPP)sequences at three elevations using field-collected tree rings of Picea crassifolia in Qilian Mountains of Northwest China.The results showed that(1)There were significant differences between AGB and ANPP at the three elevations,and the growth rate of AGB was the highest at the low elevation(55.99 t ha^(–1)10a^(–1)).(2)There are differences in the response relationship between the ANPP and climate factors at the three elevations,and drought stress is the main climate signal affecting the change of ANPP.(3)Under the future climate scenario,drought stress intensifies,and the predicted decline trend of ANPP at the three elevations from mid-century to the end of this century is–0.025 t ha^(–1)10a^(–1),respectively;–0.022 t ha^(–1)10a^(–1);At–0.246 t ha^(–1)10a^(–1),the level of forest productivity was significantly degraded.The results reveal the elevation gradient differences in forest productivity levels and provide key information for studying the carbon sink potential of boreal forests.

The biomass and aboveground net primary productivity of Schima superba-Castanopsis carlesii forests in east China

The biomass and productivity of Schima superba-Castanopsis carlesii forests in Tiantong,Zhejiang Province,were determined using overlapping quadrants and stem analyses.The total community biomass was(225.3±30.1) t hm-2,of which the aboveground parts accounted for 72.0% and the underground parts accounted for 28.0%.About 87.2% of biomass existed in the tree layer.The resprouting biomass was small,of which over 95.0% occurred in the shrub layer.The productivity of the aboveground parts of the community was(386.8±98.9) g m-2a-1,in which more than 96.0% was present at the tree level.The trunk's contribution to productivity was the greatest,while that of leaves was the smallest.In China,the community biomass of subtropical evergreen broadleaved forests differs significantly with the age of the forest.The community biomass of the 52-year-old S.superba-C.carlesii forests in this study was lower than the average biomass of subtropical evergreen broadleaved forests in China,and was lower than the biomass of other subtropical evergreen broadleaved forests elsewhere in the world.Moreover,its productivity was lower than the model estimate,indicating that without disturbance,this community has great developmental potential in terms of community biomass and productivity.

Impacts of land conversion and management measures on net primary productivity in semi-arid grassland

Ecological restoration measures implemented in China have profoundly impacted vegetation NPP.This study aimed to estimate the effects of the land conversion and management measures on the grassland ecosystem in semi-arid regions.Land use data were employed from 2000 to 2015 to compare land conversion and coverage changes in Xilingol grassland.Then,the contributions of land conversion and management policies were quantified by assessing the difference between actual NPP and climate-induced NPP changes.The results indicated that the grassland area had a net loss of 534.42 km^(2),and the net area of increased vegetation coverage was 74,683.05 km^(2).Furthermore,the total NPP increased by 8,010.73 Gg C·yr^(−1)(1 Gg=10^(9)g),of which the human activities,including grazing management measures(+6,809.40 Gg C·yr^(−1))and land conversion(45.72 Gg C·yr^(−1))contributed to 85.58%of the increase in NPP.Transformation from desert and farmland dominated grassland expansion and NPP increase,while urbanization and desertification caused large grassland reduction and NPP loss.The grazing management increased vegetation NPP in most regions except for some regions in the desert steppe and the farming-pastoral zone.Related policies should be further adjusted to strengthen the management of the desert steppe and farming-pastoral regions.

Estimation of Terrestrial Net Primary Productivity in China from Fengyun-3D Satellite Data

Currently,the satellite data used to estimate terrestrial net primary productivity(NPP)in China are predominantly from foreign satellites,and very few studies have based their estimates on data from China’s Fengyun satellites.Moreover,despite their importance,the influence of land cover types and the normalized difference vegetation index(NDVI)on NPP estimation has not been clarified.This study employs the Carnegie–Ames–Stanford approach(CASA)model to compute the fraction of absorbed photosynthetically active radiation and the maximum light use efficiency suitable for the main vegetation types in China in accordance with the finer resolution observation and monitoring-global land cover(FROM-GLC)classification product.Then,the NPP is estimated from the Fengyun-3D(FY-3D)data and compared with the Moderate Resolution Imaging Spectroradiometer(MODIS)NPP product.The FY-3D NPP is also validated with existing research results and historical field-measured NPP data.In addition,the effects of land cover types and the NDVI on NPP estimation are analyzed.The results show that the CASA model and the FY-3D satellite data estimate an average NPP of 441.2 g C m^(−2) yr^(−1) in 2019 for China’s terrestrial vegetation,while the total NPP is 3.19 Pg C yr^(−1).Compared with the MODIS NPP,the FY-3D NPP is overestimated in areas of low vegetation productivity and is underestimated in high-productivity areas.These discrepancies are largely due to the differences between the FY-3D NDVI and MODIS NDVI.Compared with historical field-measured data,the FY-3D NPP estimation results outperformed the MODIS NPP results,although the deviation between the FY-3D NPP estimate and the in-situ measurement was large and may exceed 20%at the pixel scale.The land cover types and the NDVI significantly affected the spatial distribution of NPP and accounted for NPP deviations of 17.0%and 18.1%,respectively.Additionally,the total deviation resulting from the two factors reached 29.5%.These results show that accurate NDVI products and land cover types are important prerequisites for NPP estimation.

Global patterns and climatic drivers of above-and belowground net primary productivity in grasslands

Understanding patterns and determinants of net primary productivity(NPP)in global grasslands is ongoing challenges,especially for belowground NPP(BNPP)and its fraction(fBNPP).By developing a comprehensive field-based dataset,we revealed that,along with gradients of mean annual precipitation,actual evapotranspiration,and aridity,aboveground NPP(ANPP),BNPP,and total NPP(TNPP)exhibited hump-shaped patterns,whereas fBNPPshowed an opposite trend.ANPP and TNPP showed positive correlations with mean annual temperature,but fBNPPwas negatively correlated with it.The relationship between BNPP and climatic factors was considerably weak,indicating that BNPP was relatively stable regardless of the climate conditions.We also observed that the sensitivities of ANPP and BNPP to interannual temperature variability and those of BNPP to interannual precipitation fluctuations exhibited large variations among different study sites,and differed from those at the spatial scale.In contrast,the temporal sensitivities of ANPP to interannual precipitation variability were highly similar across all the individual sites and much smaller than those at the spatial scale.Overall,these results highlight that precipitation,temperature and evapotranspiration all play vital roles in shaping ANPP pattern and its partitioning to belowground and that the patterns of BNPP along climatic gradients do not mirror those of the ANPP.

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.

Global patterns in above-ground net primary production and precipitation-use efficiency in grasslands

The above-ground net primary production(ANPP) and the precipitation-use efficiency(PUE) regulate the carbon and water cycles in grassland ecosystems, but the relationships among the ANPP, PUE and precipitation are still controversial. We selected 717 grassland sites with ANPP and mean annual precipitation(MAP) data from 40 publications to characterize the relationships ANPP–MAP and PUE–MAP across different grassland types. The MAP and ANPP showed large variations across all grassland types, ranging from 69 to 2335 mm and 4.3 to 1706 g m^(-2), respectively. The global maximum PUE ranged from 0.19 to 1.49 g m^(-2) mm^(-1) with a unimodal pattern. Analysis using the sigmoid function explained the ANPP–MAP relationship best at the global scale. The gradient of the ANPP–MAP graph was small for arid and semi-arid sites(MAP <400 mm). This study improves our understanding of the relationship between ANPP and MAP across dry grassland ecosystems. It provides new perspectives on the prediction and modeling of variations in the ANPP for different grassland types along precipitation gradients.

Assessing Net Primary Production in Montane Wetlands from Proximal, Airborne, and Satellite Remote Sensing

In this study, several vegetation indices were examined in order to determine the most sensitive vegetation index for monitoring southern Appalachian wetlands. Three levels of platforms (in situ, airborne, and satellite) for sensors were also examined in conjunction with vegetation indices. Net primary production (NPP) data were gathered to use as a measure of wetland function. Along with the in situ radiometers, National Agricultural Imagery Program (NAIP) data and Landsat 8 Operational Land Imager (OLI) data were gathered in order to calculate vegetation indices at three platforms. At the in situ level, VARI700 was the most sensitive vegetation index in terms of NPP (r2 = 0.65, p < 0.05). At the airborne level, the NDVI was the most sensitive vegetation index to NPP (r2 = 0.35, p = 0.11). At the satellite level, the DVI appeared to have a positive relationship with NPP. For most indices there was a drop in the coefficient of determination with NPP when the platform altitude increased, with the exception of NDVI when increasing altitude from in situ to airborne. This study provides a novel methodology comparing reflectance and vegetation indices at three platform levels.

Effects of drip and flood irrigation on carbon dioxide exchange and crop growth in the maize ecosystem in the Hetao Irrigation District,China

Drip irrigation and flood irrigation are major irrigation methods for maize crops in the Hetao Irrigation District,Inner Mongolia Autonomous Region,China.This research delves into the effects of these irrigation methods on carbon dioxide(CO_(2))exchange and crop growth in this region.The experimental site was divided into drip and flood irrigation zones.The irrigation schedules of this study aligned with the local commonly used irrigation schedule.We employed a developed chamber system to measure the diurnal CO_(2)exchange of maize plants during various growth stages under both drip and flood irrigation methods.From May to September in 2020 and 2021,two sets of repeated experiments were conducted.In each experiment,a total of nine measurements of CO_(2)exchange were performed to obtain carbon exchange data at different growth stages of maize crop.During each CO_(2)exchange measurement event,CO_(2)flux data were collected every two hours over a day-long period to capture the diurnal variations in CO_(2)exchange.During each CO_(2)exchange measurement event,the biological parameters(aboveground biomass and crop growth rate)of maize and environmental parameters(including air humidity,air temperature,precipitation,soil water content,and photosynthetically active radiation)were measured.The results indicated a V-shaped trend in net ecosystem CO_(2)exchange in daytime,reducing slowly at night,while the net assimilation rate(net primary productivity)exhibited a contrasting trend.Notably,compared with flood irrigation,drip irrigation demonstrated significantly higher average daily soil CO_(2)emission and greater average daily CO_(2)absorption by maize plants.Consequently,within the maize ecosystem,drip irrigation appeared more conducive to absorbing atmospheric CO_(2).Furthermore,drip irrigation demonstrated a faster crop growth rate and increased aboveground biomass compared with flood irrigation.A strong linear relationship existed between leaf area index and light utilization efficiency,irrespective of the irrigation method.Notably,drip irrigation displayed superior light use efficiency compared with flood irrigation.The final yield results corroborated these findings,indicating that drip irrigation yielded higher harvest index and overall yield than flood irrigation.The results of this study provide a basis for the selection of optimal irrigation methods commonly used in the Hetao Irrigation District.This research also serves as a reference for future irrigation studies that consider measurements of both carbon emissions and yield simultaneously.

Decoupling between Plant Productivity and Growing Season Length under a Warming Climate in Canada’s Arctic

Given the short duration of growing season in the Arctic, a strong correlation between plant productivity and growing season length (GSL) is conventionally assumed. Will this assumption hold true under a warming climate? In this study, we addressed the question by investigating the relationship between net primary productivity of leaves (NPPleaf) and GSL for various tundra ecosystems. We quantified NPPleaf and GSL using long-term satellite data and field measurements. Our results indicated that the relationship was not significant (i.e., decoupled) for 44% to 64% of tundra classes in the southern Canadian Arctic, but significant for all classes in the northern Canadian Arctic. To better understand the causes of the decoupling, we further decomposed the relationship into two components: the correspondence of interannual variations and the agreement of long- term trends. We found that the longer the mean GSL for a tundra class, the poorer the correspondence between their interannual variations. Soil moisture limitation further decoupled the relationship by deteriorating the agreement of long-term trends. Consequently, the decoupling between NPPleaf and GSL would be more likely to occur under a warming climate if the tundra class had a mean GSL > 116 (or 123) days with a dry (or moist) soil moisture regime.