Response Of Net Primary Productivity Research Articles

Untangling the impacts of socioeconomic and climatic changes on vegetation greenness and productivity in Kazakhstan

Studies examining the joint interactions and impacts of social-environmental system (SES) drivers on vegetation dynamics in Central Asia are scarce. We investigated seasonal trends and anomalies in drivers and their impacts on ecosystem structure and function (ESF). We explored the response of net primary production, evapotranspiration and normalized difference vegetation index (NDVI) to various SES drivers—climate, human influence, heat stress, water storage, and water content—and their latent relationships in Kazakhstan. We employed 13 predictor drivers from 2000 to 2016 to identify the interactions and impacts on ESF variables that reflect vegetation growth and productivity. We developed 12 models with different predictor–response variable combinations and separated them into two approaches. First, we considered the winter percent snow cover (SNOWc) and spring rainfall (P_MAM) as drivers and then as moderators in a structural equation model (SEM). SNOWc variability (SNOWcSD) as an SEM moderator exhibited superior model accuracy and explained the interactions between various predictor–response combinations. Winter SNOWcSD did not have a strong direct positive influence on summer vegetation growth and productivity; however, it was an important moderator between human influence and the ESF variables. Spring rainfall had a stronger impact on ESF variability than summer rainfall. We also found strong positive feedback between soil moisture (SM) and NDVI, as well as a strong positive influence of vegetation optical depth (VOD) and terrestrial water storage (TWS) on ESF. Livestock density (LSKD) exhibited a strong negative influence on ESF. Our results also showed a strong positive influence of socioeconomic drivers, including crop yield per hectare (CROPh), gross domestic product per capita (GDPca), and population density (POPD) on vegetation productivity. Finally, we found that vegetation dynamics were more sensitive to SM, VOD, LSKD and POPD than climatic drivers, suggesting that water content and human influence drivers were more critical in Kazakhstan.

Responses of net primary productivity to phenological dynamics based on a data fusion algorithm in the northern Qinghai-Tibet Plateau

Phenology is a key measure of how well an ecosystem functions and is pivotal in revealing vegetation productivity. Net Primary Productivity (NPP) and phenology have profound implications for the exploration of regional ecosystem processes. Several studies have investigated the effects of phenological indicators on NPP. However, these studies were carried out at a coarse resolution, making it difficult to obtain sufficient information on vegetation structure and dynamics; they also, potentially underestimate how productivity is influenced by phenology. This work uses fused NDVI images employing the ESTARFM model to determine how vegetation NPP reacts to phenology in the northern Qinghai-Tibet Plateau. The results showed that NPP was only 59.93 gC·m−2·year -1. The start of the growing season (SGS) was concentrated from March to May, whereas the end of the growing season (EGS) spanned from late September to early November. The length of the growing season (LGS) spanned 4–8 months during 2000–2020, NPP showed an increasing trend, SGS and EGS advanced, and LGS showed a prolonged trend. SGS and EGS were negatively correlated with NPP and seasonal temperature, however NPP was positively correlated with seasonal precipitation. LGS was positively correlated with NPP and interannual temperature, whereas it was negatively correlated with interannual precipitation. This study will aid in providing an accurate understanding of how NPP responds to phenological dynamics. Concurrently, collective understanding of terrestrial ecosystem responses to changes on a global scale will be advanced.

Spatial-Temporal Correlations between Soil pH and NPP of Grassland Ecosystems in the Yellow River Source Area, China.

In recent years, ecological concerns such as vegetation destruction, permafrost deterioration, and river drying have been paid much more attention to on the Yellow River Basin in China. Soil pH is regarded to be the fundamental variable among soil properties for vegetation growth, while net primary productivity (NPP) is also an essential indicator to reflect the healthy growth of vegetation. Due to the limitation of on-site samples, the spatial–temporal variations in soil pH and NPP, as well as their intrinsic mechanisms, remain unknown, especially in the Yellow River source area, China. Therefore, it is imperative to investigate the coupling relationship between soil pH and NPP of the area. The study coupled MODIS reflectance data (MOD09A1) with on-site soil pH to estimate spatial–temporal variations in soil pH, explore the response of NPP to soil pH, and assess the extent to which they contribute to grassland ecosystems, thus helping to fill knowledge gaps. Results indicated that the surface spectral reflectance for seven bands could express the geographic pattern of soil pH by applying a multiple linear regression equation; NPP exhibited an increasing trend while soil pH was the contrary in summer from 2000 to 2021. In summer, NPP was negatively correlated with soil pH and there was a lag effect in the response of NPP to soil pH, revealing a correlation between temperate steppes > montane meadows > alpine meadows > swamps in different grassland ecosystems. In addition, contribution indices for temperate steppes and montane meadows were positive whereas they were negative for swamps and alpine meadows, which are apparent findings. The contribution index of montane and alpine meadows was greater than that of temperate steppes and swamps. The approach of the study can enable managers to easily identify and rehabilitate alkaline soil and provides an important reference and practical value for ecological restoration and sustainable development of grassland ecosystems in alpine regions.

Time-Lag Effect of Climate Conditions on Vegetation Productivity in a Temperate Forest–Grassland Ecotone

Climate conditions can significantly alter the vegetation net primary productivity (NPP) in many of Earth’s ecosystems, although specifics of NPP–climate condition interactions, especially time-lag responses on seasonal scales, remain unclear in ecologically sensitive forest–grassland ecotones. Based on the Moderate-Resolution Imaging Spectroradiometer (MODIS) and meteorological datasets, we analyzed the relationship between NPP and precipitation, temperature, and drought during the growing season (April–August), considering the time-lag effect (0–5 months) at the seasonal scale in Hulunbuir, Inner Mongolia, China from 2000 to 2018. The results revealed a delayed NPP response to precipitation and drought throughout the growing season. In April, the precipitation in the 4 months before (i.e., the winter of the previous year) explained the variation in NPP. In August, the NPP in some areas was influenced by the preceding 1~2 months of drought. The time-lag effect varied with vegetation type and soil texture at different spatial patterns. Compared to grass and crop, broadleaf forest and meadow exhibited a longer legacy of precipitation during the growing season. The length of the time-lag effects of drought on NPP increased with increasing soil clay content during the growing season. The interaction of vegetation types and soil textures can explain 37% of the change in the time-lag effect of the NPP response to PPT on spatial pattern. Our findings suggested that preceding precipitation influences vegetation growth at the early stages of growth, while preceding drought influences vegetation growth in the later stages of growth. The spatial pattern of the time lag was significantly influenced by interaction between vegetation type and soil texture factors. This study highlights the importance of considering the time-lag effects of climate conditions and underlying drivers in further improving the prediction accuracy of NPP and carbon sinks in temperate semiarid forest–grassland ecotones.

Presence of the Herbaceous Marsh Species Schoenoplectus americanus Enhances Surface Elevation Gain in Transitional Coastal Wetland Communities Exposed to Elevated CO2 and Sediment Deposition Events.

Coastal wetlands are dynamic ecosystems that exist along a landscape continuum that can range from freshwater forested wetlands to tidal marsh to mudflat communities. Climate-driven stressors, such as sea-level rise, can cause shifts among these communities, resulting in changes to ecological functions and services. While a growing body of research has characterized the landscape-scale impacts of individual climate-driven stressors, little is known about how multiple stressors and their potential interactions will affect ecological functioning of these ecosystems. How will coastal wetlands respond to discrete climate disturbances, such as hurricane sediment deposition events, under future conditions of elevated atmospheric CO2? Will these responses vary among the different wetland communities? We conducted experimental greenhouse manipulations to simulate sediment deposition from a land-falling hurricane under future elevated atmospheric CO2 concentrations (720 ppm CO2). We measured responses of net primary production, decomposition, and elevation change in mesocosms representing four communities along a coastal wetland landscape gradient: freshwater forested wetland, forest/marsh mix, marsh, and mudflat. When Schoenoplectus americanus was present, above- and belowground biomass production was highest, decomposition rates were lowest, and wetland elevation gain was greatest, regardless of CO2 and sediment deposition treatments. Sediment addition initially increased elevation capital in all communities, but post-deposition rates of elevation gain were lower than in mesocosms without added sediment. Together these results indicate that encroachment of oligohaline marshes into freshwater forested wetlands can enhance belowground biomass accumulation and resilience to sea-level rise, and these plant-mediated ecosystem services will be augmented by periodic sediment pulses from storms and restoration efforts.

Projections of the Net Primary Production of Terrestrial Ecosystem and Spatiotemporal Responses to Climate Change in the Yangtze River Economic Belt

Evaluating the responses of net primary productivity (NPP) to climate change is essential for regional ecosystem management and adaptations to climate change. The Yangtze River Economic Belt (YREB) is a key ecological functional area and hotspot of carbon sequestration in China due to the high degree of forest coverage. We used a process-based ecosystem model to project terrestrial NPP and analyzed the response to climate change over the 21st century in the YREB under two representative concentration pathway (RCP) scenarios using the regional climate model. The results show that the projection of NPP generally increased by 13.5% under RCP4.5 and 16.4% under RCP8.5 in the middle of the century, by 23% under RCP4.5, and by 35% under RCP8.5 in the late term of the century compared with that from a reference period of current climate conditions (1985–2006). The rate of NPP change under the RCP8.5 scenario is higher than that under the RCP4.5 scenario. Similarly, the NPP is also projected to increase both with 1.5 and 2 °C global warming targets in the YREB. The magnitudes of NPP increment are approximately 14.7% with 1.5 °C and 21% with 2 °C warming targets compared with the current climate, which are higher than the average increments of China. Although NPP is projected to increase under the two scenarios, the tendency of NPP increasingly exhibits a slowdown after the 2060 s under the RCP4.5 scenario, and the growth rate of NPP is projected to drop in more than 31% of regional areas with the additional 0.5 °C warming. In contrast, under the RCP8.5 scenario, the trend in NPP keeps rising substantially, even above 2 °C global warming. However, the NPP in some provinces, including Jiangxi and Hunan, is projected to reduce at the end of the 21st century, probably because of temperature rises, precipitation decreases, and water demand increases. Generally, the NPP is projected to increase due to climate change, particularly temperature increase. However, temperature rising does not always show a positive effect on NPP increasing; the growth rate of NPP will slow down under the RCP4.5 scenario in the mid-late 21st century, and NPP will also reduce by the end of this century under the RCP8.5 scenario in some places, probably presenting some risks to terrestrial ecosystems in these areas, in terms of reduced functions and service decline, a weakened capacity of carbon sequestration, and reduced agricultural production.

How precipitation legacies affect broad-scale patterns of primary productivity: Evidence from the Inner Mongolia grassland

The legacy effects of precipitation, defined as the impact of precipitation from previous years on current-year net primary productivity (NPP), have been well recognized in field experiments and site-level observational studies. However, it remains unclear how consecutive dry or wet years influence the directions and magnitude of legacies and broad-scale patterns of NPP. Here, we quantified the spatial and temporal patterns of legacy effect across different numbers of consecutive wet and dry years from 2000 to 2020 in the Inner Mongolia grassland. Spatially, the response of legacies to precipitation transitions was asymmetric along the mean annual precipitation gradient. The positive response of legacies to precipitation decrease was found for desert steppe and typical steppe after preceding wetness. In contrast, the response of legacies to precipitation increase was negative for desert steppe and meadow steppe after preceding drought. Moreover, legacies were more sensitive in desert steppe than that in typical steppe and meadow steppe for both the preceding wetness and preceding drought. However, the meadow steppe showed the highest response to the inter-annual precipitation change among the three grassland types. Furthermore, the legacies responded more strongly to precipitation decrease (preceding consecutive wet years) than the increase (preceding consecutive dry years) for meadow steppe and typical steppe. Yet, the desert steppe showed the opposite response to precipitation change. Temporally, the legacy effects lasted for only one year and could be transmitted year by year. Our findings highlight that consecutive wet and dry years play essential roles in controlling the NPP responses to climate fluctuations in arid and semi-arid grasslands. Understanding ecosystem responses to climatic periods can provide insights into the effects of directional changes in rainfall associated with climate change.

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

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

Response of grassland net primary productivity to climate change in China

To protect the grassland ecosystem’s security, and coordinate the utilisation of grassland resources, explicitly estimating the response of Net Primary Productivity (NPP) of 10 grassland groups to future climate change is necessary. Based on the Comprehensive and Sequential Classification System (CSCS) and modified Carnegie Ames Stanford Approach (CASA) model, in conjunction with four Representative Concentration Pathways (RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5) of the Intergovernmental Panel on Climate Change (IPCC), the response of China’s grassland NPP to climate change was simulated and estimated. Results showed that: (1) the simulation accuracy of modified CASA model (R2 = 0.65) is 34% higher than that of CASA model, indicating that the modified CASA was suitable for estimating grassland NPP in China; (2) annual mean NPP and total NPP (2001–18) were 138.4 g C m−2 year−1 and 495.7 T g C, respectively; compared with the period 2001–18, NPP during the 2050 under RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 were predicted with increases of 34.8%, 35.9%, 34.9% and 35.8%, respectively; and (3) from the present-day to the 2050, the NPP of Warm desert exhibited the largest increase (73.2–76.3%), while that of Tundra and alpine grassland the smallest (1.3–1.6%). These differences in NPP increase likely lead to differences in grassland carrying capacity. To respond to the impact of future climate change on grassland, grassland classification management strategies according to different groups should be implemented as grassland NPP changes differently in different grassland groups.

Warmer and wetter climate promotes net primary production in C4 grassland with additional enhancement by hay harvesting

AbstractGrassland ecosystems provide essential services to society. To maintain ecosystem functions and services of grasslands under changing environments, it is critical to understand how grasslands respond and feedback to climate change. Here, we present results from a long‐term (16 years) warming and clipping (to mimic hay harvesting or grazing) experiment conducted in a grassland ecosystem dominated by C4 grasses in the Great Plains, USA. We analyzed responses of net primary production (NPP), aboveground NPP (ANPP), and belowground NPP (BNPP) to the expanded ranges of climate conditions observed in the experiment. NPP, ANPP, and BNPP all responded to the climatic variables nonlinearly, with higher degrees of nonlinearity for BNPP than that for ANPP. BNPP peaked at the optimum air temperature of 17.5–18.5°C while ANPP peaked at the optimum air temperature of 18.5–20.0°C. The optimum air temperatures for both ANPP and BNPP were higher than mean annual temperature (16.3°C) at the site. The optimum precipitation for BNPP was intermediate levels (775–1250 mm) while ANPP was maximized in wetter conditions (1250–1605 mm) compared with BNPP. Clipping significantly reduced ANPP and shifted the optimum conditions for BNPP to warmer and wetter conditions. In summary, C4‐grass dominant ecosystems have the potential to increase NPP in future warmer and wetter conditions, and clipping may amplify this positive effect in this grassland ecosystem.

Spatiotemporal heterogeneity of net primary productivity and response to climate change in the mountain regions of southwest China

Monitoring changes in the net primary productivity (NPP) of vegetation and its response to climatic changes is integral to gain insight into the carbon cycle mechanism and facilitate human well-being. Nonetheless, past studies lacked a month-scaled exploration and largely ignored spatial heterogeneity of the time lag effect. In this study, we focused on the Hengduan Mountain region situated in southwest China and analyzed the variation of NPP and its main driving mechanisms during 2000–2016. Our results revealed that: (1) The annual NPP signified a slightly increasing trend. On the grid-scale, the variation region of NPP was mainly characterized by increasing trends in most of the growth stages, except for July. (2) The response of NPP to climate change presented obvious spatial heterogeneity and complexity. The increasing NPP of the growing season in the northeast part and areas around Xichang can be attributed to temperature rising, while the increase of temperature in the central valleys led to a decline in NPP. Furthermore, decreasing precipitation led to the decrease in NPP in the western valleys. Thus, adequate water should be provided for the vegetation in western valley, and drought-tolerant plants should be choice in the central valley. (3) Changes in NPP were more influenced by temperature than precipitation, which was more evident on monthly scale, especially during April and May, and for the southeast and northeast part in June and August. (4) The lag time of NPP variation in relation to temperature changes was shorter than that of precipitation in most growth stages, indicating that NPP is more sensitive to temperature. In the colder region or growth stages, the lagged time of the response of NPP to temperature was shorter, which was more obvious on the monthly scale. This research will have important implications for ecosystem management.

Response of grassland net primary productivity to dry and wet climatic events in four grassland types in Inner Mongolia.

Increasing frequency and intensity of climate extremes have profound impacts on grassland biodiversity functioning and stability. Using Moderate Resolution Imaging Spectroradiometer (MODIS) net primary productivity (NPP) data and standardized precipitation evapotranspiration index, we assessed the response of NPP to growing-season and annual climate extremes and time-lag of climatic conditions across four grassland types (meadow steppe, typical steppe, steppe desert, and desert steppe) in Inner Mongolia, China from the period 2000 to 2019. Results showed that annual NPP varied significantly across four grassland types, with the highest NPP in meadow steppe and the lowest in desert steppe. Annual NPP of all grassland types increased over the past 20years, but NPP in meadow steppe and typical steppe decreased for the period 2012-2019. Irrespective of grassland type, the 1- and 2-month time-lag of climatic conditions showed significant effects on annual NPP. Growing-season climate was found the better predictor of annual NPP in all grassland types than the annual climate. Compared with growing-season normal climates, annual NPP was lowest in extreme dry events in all grasslands, while highest in extreme wet events in meadow steppe and typical steppe, and in moderate wet events in steppe desert and desert steppe. Typical steppe and steppe desert are highly vulnerable to the increasing intensity of climate extremes, as we found that the losses of NPP in these grasslands in extreme dry were almost double than that of moderate dry events. Surprisingly, for meadow steppe and desert steppe, the losses of NPP for both moderate and extreme dry events were almost the same, which highlights that a low-intensity drought may have profound impacts on the annual NPP of these grasslands. The study provides the key insight in scientific basis to improve our understanding of the effects of climate extremes on grassland NPP, which is critical to sustainable management of grassland and maintain ecosystem stability.

Relationship between net primary productivity and soil water content in the Shule River Basin

Soil water content (SWC) is the basic condition for the survival of terrestrial vegetation. Net primary productivity (NPP) directly reflects the status of vegetation growth. Therefore, studying the coupling relationship between NPP and SWC in the arid region of Northwest China is of great significance for vegetation restoration and the protection of fragile ecosystems. Based on remote sensing and SWC measured data, the CASA model and statistical downscaling methods were used to calculate the NPP and SWC, analyze the spatial and temporal evolution of them, and to explore their coupling relationship in the Shule River Basin (SRB) in China. Our results indicate that (1) an upward trend in NPP and SWC during the summers of 2001–2015. (2)The NPP and SWC were mainly positively correlated. There was a lag effect in the response of vegetation NPP to SWC in most areas of the basin. However, NPP had a greater impact on SWC in desert areas than in other regions. (3) Based on changes to SWC, two scenarios analyses of NPP were conducted to reveal how NPP responded to SWC. In scenario 1 (the SWC change only), as SWC increases, NPP gradually increases. Scenario 2 (increase of 1 °C temperature and 2% precipitation), compared with scenario 1, as SWC increases, the increase in NPP decreases. Based on the results, in scenario 2, the beneficial effect of SWC on vegetation growth was weakened. Thus, under future climate change, only by timely supplementing SWC can we better promote the growth of NPP, improve vegetation productivity, and effectively restore and protect the ecological environment of SRB. This study deepens our understanding of the coupling relationship between the ecological environment and water resources of the SRB and provides a scientific basis for formulating rational allocation of water resources and ecological environment restoration and protection measures in the arid regions of China.

Absolute Contribution of the Non-Uniform Spatial Distribution of Atmospheric CO2 to Net Primary Production through CO2-Radiative Forcing

Atmospheric concentrations of CO2 are the most important driver of the Earth’s climate and ecosystems through CO2-radiative forcing, fueling the surface temperature and latent heat flux on half-century timescales. We used FGOALS-s2 coupled with AVIM2 to estimate the response of net primary production (NPP) to spatial variations in CO2 during the time period 1956–2005. We investigated how the induced variations in surface temperature and soil moisture influence NPP and the feedback of the oceans and sea ice on changes in NPP. The spatial variations in the concentrations of CO2 resulted in a decrease in NPP from 1956 to 2005 when we included ocean and sea ice dynamics, but a slight increase in NPP without ocean and sea ice dynamics. One of the reasons is that the positive feedback of sea temperature to the surface temperature leads to a significant decrease in tropical NPP. Globally, the non-uniform spatial distribution of CO2 absolutely contributed about 14.3% ± 2.2% to the terrestrial NPP when we included ocean and sea ice dynamics or about 11.5% ± 1.1% without ocean and sea ice dynamics. Our findings suggest that more attention should be paid to the response of NPP to spatial variations in atmospheric CO2 through CO2-radiative forcing, particularly at low latitudes, to better constrain the predicted carbon flux under current and future conditions. We also highlight the fundamental importance of changes in soil moisture in determining the pattern, response and magnitude of NPP to the non-uniform spatial distribution of CO2 under a warming climate.

The response of net primary productivity to climate change and its impact on hydrology in a water-limited agricultural basin.

Climate change has remarkably altered growing-season vegetation growth, but the impacts of vegetation variability on the regional hydrological cycle remain poorly understood. Exploring the relationships between climate change, vegetation dynamics, and hydrologic factors would contribute to the sustainable management of ecosystems. Here, we investigated the response of vegetation dynamics to climate change and its impact on hydrologic factors in a traditional agricultural basin with limited water resources in China, Nansi Lake Basin (NLB). To this end, CASA (Carnegie-Ames-Stanford Approach) model and the SWAT (Soil and Water Assessment Tool) model were applied to simulate the net primary productivity (NPP), evapotranspiration (ET), and soil water in the growing season (April-October) from 2000 to 2016. Results showed that the mean growing-season NPP (NPPGS) exhibited an ascending trend at a rate of 2.93 g C/m2/year during the 17-year period. The intra-annual variation of NPPGS displayed two peaks in May and July, respectively. The first peak in May was accompanied by relative deficits in soil water, which might inhibit vegetation productivity. Precipitation was the principal climatic factor controlling NPPGS dynamics in the water-limited NLB. The positive influence of temperature on NPPGS was relatively weak, and even future warming could negatively affect ecosystem productivity in the south-central regions of the NLB. Furthermore, a strongly positive relationship between NPPGS and ET was detected, suggesting that increasing NPP in the future might stimulate the rise in ET and then exacerbate drought at the watershed scale. This study provides an integrated model for a comprehensive understanding of the interaction between vegetation, climate, and hydrological cycle, and highlights the importance of water-saving agriculture for future food security.

Global and Regional Estimation of Carbon Uptake Using CMIP6 ESM Compared With TRENDY Ensembles at the Centennial Scale

AbstractTo evaluate the ability of CMIP6 Earth System Models to simulate net biome production (NBP) changes caused by natural and man‐made forcing, the simulated NBP during the period 1901–2010 at global, hemispheric and regional scales was compared with the estimated NBP of the TRENDY ensemble. The annual NBP, globally and over the Northern Hemisphere and tropics, from the CMIP6 ensemble reflected well the TRENDY ensemble annual values from 1901 to 2010, and the correlation coefficient passed the 0.05 significance level. The annual NBP estimated by CMIP6 over the globe, Northern Hemisphere and tropics was 0.20 ± 0.46, 0.25 ± 0.34, and −0.02 ± 0.14 Pg C yr−1, respectively; while from the TRENDY ensemble it was 1.04 ± 0.41, 0.55 ± 0.24, and 0.43 ± 0.20 Pg C yr−1, respectively. The main weaknesses of the CMIP6 multi‐model ensemble simulation was the lower strength of NBP, especially at low latitudes. The simulated results showed higher soil respiration estimated by CMIP6 for these regions, especially in the Amazon Basin, than that by the TRENDY ensemble, which produced the greater NPB estimated by TRENDY. The CMIP6 ensemble exaggerated the increasing trend of carbon sinks between 30° and 60°N in the Northern Hemisphere after 1961, due to the stronger positive response of NPP (net primary production) in the high‐latitude Northern Hemisphere to global warming. The NBP during 1901–2010 could not be reproduced well by the CMIP6 ensemble in most sub‐regions, as evidenced by the failure to pass the statistical test at the 5% significance level in 70% of the sub‐regions in terms of the correlation coefficients with the TRENDY ensemble. In eastern Asia, for example, NBP was poorly estimated by the CMIP6 ensemble, as evidenced by negative correlation coefficients with the TRENDY ensemble.

The effect of water stress on net primary productivity in northwest China.

Net primary productivity (NPP) has been widely used as the indicator of vegetation function and exhibits large spatial and temporal variations caused by numerous factors. Northwest China (NWC) is one of the driest regions in China, and water supply is the key determinant of NPP here. However, studies on the effects of water stress on NPP in NWC at the regional scale are still relatively lacking. Thus, in this study, based on a set of Moderate-Resolution Imaging Spectroradiometer (MODIS) NPP and evapotranspiration (ET) datasets, we quantified the response of NPP to water stress, which is indicated by crop water stress index (CWSI). Regional average of annual NPP in NWC showed an increasing trend during the study period, at a rate of 0.84 g C m-2 yr-1. At the province level, the NPP increase rates increased in the order of Ningxia (7.7%), Shaanxi (6.5%), Gansu (4.5%), Qinghai (3.8%), and Xinjiang (1.7%). NPP was negatively correlated with CWSI (p<0.05) in 73% of areas, indicating the key role of water stress in constraining NPP over this arid region. The effect of water stress on NPP changes with elevation. Water stress has the strongest negative impact on NPP in areas with elevations around 2000 m. In elevations above 5000 m, NPP is not limited by water stress, mostly positively correlated with CWSI. Our findings further clarify the importance of water stress in dryland ecosystems, while highlighting that elevation gradients can significantly affect the correlation between NPP and water stress.

Precipitation manipulation and terrestrial carbon cycling: The roles of treatment magnitude, experimental duration and local climate

AbstractAimPrecipitation manipulation experiments have shown diverse terrestrial carbon (C) cycling responses when the ecosystem is subjected to different magnitudes of altered precipitation, various experimental durations or heterogeneity in local climate. However, how these factors combine to affect C cycle responses to changes in precipitation remains unclear.LocationGlobal.Time period1990–2019.Major taxa studiedTerrestrial ecosystems.MethodsUsing observations from 230 published studies in which precipitation was manipulated and terrestrial C cycling variables were measured, we conducted a global meta‐analysis to investigate responses of diverse C cycle processes to altered precipitation, including gross ecosystem productivity, ecosystem respiration, net ecosystem productivity, ecosystem carbon use efficiency, net primary productivity (NPP), aboveground and belowground NPP, aboveground and belowground biomass, shoot‐to‐root ratio, soil respiration and soil microbial biomass C.ResultsWe found that C cycling responses were correlated linearly and positively with the magnitude of precipitation treatments. We also detected that the responses of NPP and its aboveground component (ANPP) to altered precipitation weakened with experimental duration. Furthermore, gross ecosystem productivity, ecosystem respiration and net ecosystem productivity showed larger responses to precipitation treatments of greater magnitude over shorter time periods. The response of soil respiration, a key component of the C budget in most terrestrial ecosystems, depended in particular on the local climate. Local temperature and precipitation not only influenced the magnitude of the response of soil respiration to altered precipitation but also affected its sensitivity to the magnitude of the precipitation treatments, with higher sensitivities in the response of soil respiration to treatment magnitude at drier and colder sites.Main conclusionsOur findings highlight the importance of the interactions between the magnitude of precipitation treatments, their duration and the local climate in the response of ecosystem C cycling to altered precipitation, which is crucial to a better understanding of ecosystem C processes and functioning and projecting them under changing precipitation regimes.

Response of net primary productivity to grassland phenological changes in Xinjiang, China.

Determining the relationship between net primary productivity (NPP) and grassland phenology is important for an in-depth understanding of the impact of climate change on ecosystems. In this study, the NPP of grassland in Xinjiang, China, was simulated using the Carnegie-Ames-Stanford approach (CASA) model with Moderate Resolution Imaging Spectroradiometer (MODIS) grassland phenological (MCD12Q2) data to study trends in phenological metrics, grassland NPP, and the relations between these factors from 2001–2014. The results revealed advancement of the start of the growing season (SOS) for grassland in most regions (55.2%) in Xinjiang. The percentage of grassland area in which the end of the growing season (EOS) was delayed (50.9%) was generally the same as that in which the EOS was advanced (49.1%). The percentage of grassland area with an increase in the length of the growing season (LOS) for the grassland area (54.6%) was greater than that with a decrease in the LOS (45.4%). The percentage of grassland area with an increase in NPP (61.6%) was greater than that with a decrease in NPP (38.4%). Warmer regions featured an earlier SOS and a later EOS and thus a longer LOS. Regions with higher precipitation exhibited a later SOS and an earlier EOS and thus a shorter LOS. In most regions, the SOS was earlier, and spring NPP was higher. A linear statistical analysis showed that at various humidity (K) levels, grassland NPP in all regions initially increased but then decreased with increasing LOS. At higher levels of K, when NPP gradually increased, the LOS gradually decreased.

A Decade's Change in Vegetation Productivity and Its Response to Climate Change over Northeast China.

In this study, we simulated vegetation net primary productivity (NPP) using the boreal ecosystem productivity simulator (BEPS) between 2003 and 2012 over Northeast China, a region that is significantly affected by climate change. The NPP was then validated against the measurements that were calculated from tree ring data, with a determination coefficient (R2) = 0.84 and the root mean square error (RMSE) = 42.73 gC/m2·a. Overall, the NPP showed an increasing trend over Northeast China, with the average rate being 4.48 gC/m2·a. Subsequently, partial correlation and lag analysis were conducted between the NPP and climatic factors. The partial correlation analysis suggested that temperature was the predominant factor that accounted for changes in the forest NPP. Solar radiation was the main factor that affected the forest NPP, and the grass NPP was the most closely associated with precipitation. The relative humidity substantially affected the annual variability of the shrub and crop NPPs. The lag time of the NPP related to precipitation increased with the vegetation growth, and it was found that the lag period of the forest was longer than that of grass and crops, whereas the cumulative lag month of the forest was shorter. This comprehensive analysis of the response of the vegetation NPP to climate change can provide scientific references for the managing departments that oversee relevant resources.