Decrease In Net Primary Productivity Research Articles

Climate change causes spatial shifts in the productivity of agricultural long-term field experiments

Long-term field experiments (LTE) are highly valuable infrastructures in agricultural- and soil sciences for understanding the long-term impacts of climate and management practices. While they are designed to run under constant conditions, climate change is expected to affect site conditions considerably. This needs to be quantified when interpreting experimental results and when redesigning the experimental setup. One way to achieve this is by utilizing vegetation growth and carbon dynamics, specifically the Net Primary Productivity (NPP), as a spatially explicit indicator. NPP facilitates the assessment and interpretation of yield performance in LTEs under future climatic conditions. Our study estimated the changes in NPP for 271 LTE sites in Germany, comparing a baseline (2000–2020) with two scenarios (2081–2100) that were based on the Shared Socioeconomic Pathways (SSPs) (SSP245) and SSP585) by the Intergovernmental Panel on Climate Change (IPCC). We used the NASA-CASA biogeochemical model to calculate NPP in baseline and IPCC scenarios using Germany as a test case. LTEs were grouped by land use (crop types) and soil information (soil type, texture), drawing on the geodata infrastructure “BonaRes Repository”. The total annual terrestrial NPP for the baseline was calculated as 202.4 Mt C (sum of forests, grasslands, and arable lands) in Germany, while total NPP was up to 56.0 Mt C for different land use types. For both scenarios, NPP was projected to increase in LTEs located in southern Germany, indicating increased crop productivity, while a decrease was projected for the central Germany. The decrease in NPP of numerous LTEs in central Germany was estimated to extend to the LTEs in the eastern part corresponding to the worst-case scenario SSP585. Explicitly, the use of the multi-model ensemble mean as the climate driver in modelling may overestimate projected NPP by reducing inter-annual variability, highlighting the importance of methodological choices for accurate future projections. Besides, the results indicated that poor soils are projected to experience a further decline in productivity, primarily attributed to escalating water scarcity. Conversely, soils with high quality are likely to witness enhanced productivity, largely driven by the extension of the growing seasons. The outcomes of this study provide a basis for considering the future conditions of German LTEs and facilitate distinguishing between the effects of climate change and the impact of agricultural management on productivity at the regional level. These outputs enable planning and developing research strategies for selecting future LTE sites and redesigning existing or newly planned experiments. Moreover, the integrated modelling framework presented here highlights the potential of LTE data for large-scale modelling studies of ecosystem functions.

Evaluation of five models for constructing forest NPP–age relationships in China based on 3121 field survey samples

Abstract. Forest net primary productivity (NPP), representing the net carbon gain from the atmosphere, varies significantly with forest age. Reliable forest NPP–age relationships are essential for forest carbon cycle modeling and prediction. These relationships can be derived from forest inventory or field survey data, but it is unclear which model is the most effective in simulating forest NPP variation with age. Here, we aim to establish NPP–age relationships for China's forests based on 3121 field survey samples. Five models, including the semi-empirical mathematical (SEM) function, the second-degree polynomial (SDP) function, the logarithmic (L) function, the Michaelis–Menten (M) function, and the Γ function, were compared against field data. Results of the comparison showed that the SEM and Γ functions performed much better than the other three models, but due to the limited field survey samples at old ages, the Γ function showed a sharp decrease in NPP (decreased to almost zero) at old ages when building some forest NPP–age curves, while SEM could capture the variations in forest NPP at old ages reasonably well. Considering the overall performance with currently available forest field survey samples, SEM was regarded as the optimal NPP–age model. The finalized forest NPP–age curves for five forest types in six regions of China can facilitate forest carbon cycle modeling and future projection by using the process-based Integrated Terrestrial Ecosystem Carbon (InTEC) model in China and may also be useful for other regions.

Quantifying the contributions of climatic and human factors to vegetation net primary productivity dynamics in East Africa

As an important part of the terrestrial ecosystem, vegetation dynamics are subject to impacts from both climate change and human activities. Clarifying the driving mechanisms of vegetation variation is of great significance for regional ecological protection and achieving sustainable development goals. Here, net primary productivity (NPP) was used to investigate the spatiotemporal variability of vegetation dynamics from 2000 to 2020 in East Africa, and its correlations with climate factors. Furthermore, we utilized partial derivatives analysis and set up different scenarios to distinguish the relative contributions of climatic and human factors to NPP changes. The results revealed that NPP exhibited a significant increase with 4.16 g C/m2/a from 2000 to 2020 in East Africa, and an upward trend was detected across 71.06% of the study area. The average contributions of precipitation, temperature, and solar radiation to the NPP inter-annual variations in East Africa were 2.02, −1.09, and 0.31 gC⋅m–2⋅a–1, respectively. Precipitation made the greatest positive contribution among all of the climatic factors, while temperature made strong negative contributions. The contributions of climate change and human activities to NPP changes were 1.24 and 2.34 gC⋅m–2⋅a–1, respectively. Moreover, the contribution rate of human activities to NPP increase was larger than that of climate change, while the role of climate change in NPP decrease was larger than that of human activities. The findings of the study can provide new evidence for a deeper understanding of ecosystem stability and carbon cycling in East Africa, as well as a reference for decision-making and scientific support for ecological environmental protection.

Adverse Effects of Ozone Pollution on Net Primary Productivity in the North China Plain

AbstractTropospheric ozone significantly damages vegetation and reduces net primary productivity (NPP). We developed a stable linear NPP response model based on accumulated ozone exposure over a threshold of 40 parts per billion (ppb) (AOT40). We then estimated the effects of regional ozone damage on NPP for different vegetation types. The study suggests an average decrease in NPP of 24.7% due to ozone pollution in the North China Plain, similar to previous estimates ranging from 10.1% to 24.7%, with a maximum reduction exceeding 200 [g C m‐2 yr‐1] and more than 50%. Vegetation types such as broadleaf forests, needleleaf forest, crops, and grasses showed significant NPP decreases of 47.1%, 37.8%, 36.7%, and 44.6%, respectively. Declining NPP also had negative impacts on several Chinese crop species. Our work highlights the need for urgent and effective action to mitigate ozone pollution's substantial detrimental effects on ecosystem health and productivity.

Warming inhibits increases in vegetation net primary productivity despite greening in India

India is the second-highest contributor to the post-2000 global greening. However, with satellite data, here we show that this 18.51% increase in Leaf Area Index (LAI) during 2001–2019 fails to translate into increased carbon uptake due to warming constraints. Our analysis further shows 6.19% decrease in Net Primary Productivity (NPP) during 2001–2019 over the temporally consistent forests in India despite 6.75% increase in LAI. We identify hotspots of statistically significant decreasing trends in NPP over the key forested regions of Northeast India, Peninsular India, and the Western Ghats. Together, these areas contribute to more than 31% of the NPP of India (1274.8 TgC.year−1). These three regions are also the warming hotspots in India. Granger Causality analysis confirms that temperature causes the changes in net-photosynthesis of vegetation. Decreasing photosynthesis and stable respiration, above a threshold temperature, over these regions, as seen in observations, are the key reasons behind the declining NPP. Our analysis shows that warming has already started affecting carbon uptake in Indian forests and calls for improved climate resilient forest management practices in a warming world.

Marine heatwaves during the pre-monsoon season and their impact on Chlorophyll-a in the north Indian Ocean in 1982–2021

Indian Ocean has been undergoing rapid warming in recent years, which increases the likelihood of Marine heatwave (MHW). MHWs are extreme warm ocean surface conditions in which temperature exceeds the 95th percentile for three or more consecutive days. We investigate MHW events occurred in Arabian Sea (AS) and Bay of Bengal (BoB) during pre-monsoon for 1982–2021 period, their impact on Chlorophyll-a (Chl-a) and net primary productivity (NPP). There were 42 (68) MHW events with a significant trend of 8.1 (6.3) MHW days dec−1 in AS (BoB). There is a distinct decrease in Chl-a concentration associated with MHW, especially in medium and long duration events. In general, AS and BoB have witnessed more frequent and long-lasting MHWs in the 2002–2021 period, which reduce NPP of north Indian Ocean. A decrease in Chl-a and NPP, 10 % in AS and 2 % in BoB, is estimated, but only severe MHWs inflict a notable reduction.

Dynamic of Grassland Degradation and Its Driving Forces from Climate Variation and Human Activities in Central Asia

Central Asia is one of the most sensitive regions to climate changes in the world and the grassland degradation of this region has attracted considerable concern. Quantifying the driving force of grassland degradation is important for understanding the effects of climate variation and human activities on grassland. In this study, net primary productivity (NPP) was selected as an indicator to quantitatively evaluate the relative role of climate variation and human activities in Central Asia from 2000 to 2020. This study used the global NPP product MOD17A3 as actual NPP and estimated the potential NPP using the Thornthwaite memorial model. The potential NPP and the difference between the potential NPP and actual NPP were used to represent the influence of climate variation and human activities. The grassland degradation or restoration can be demonstrated by the slope of actual NPP (SA). A positive slope value (SA) suggested that restoration occurs, whereas a negative slope value suggested that degradation occurred. The results showed that 23.08% of the total grassland area experienced grassland degradation, whereas 2.51% of the whole grassland underwent grassland restoration. Furthermore, 53.8% of the degraded grassland areas were influenced by climate variation, and 14.5% were caused by human activities. By contrast, the relative roles of climate variation and human activities in grassland restoration were 25% and 47.9%, respectively. The NPP variation also could be calculated by assessing the effects of these factors and the results showed that 55.7% of the NPP decrease was caused by climate variation, whereas 9.6% was a result of human activities. On the contrary, climate variation and human activities resulted in 19.8% and 37.3% of grassland restoration, respectively. Therefore, climate variation was the dominant factor of grassland degradation, and human activities were the main driver of grassland restoration in Central Asia.

Climate seasonality and extremes influence net primary productivity across California’s grasslands, shrublands, and woodlands

Terrestrial vegetation is a substantial carbon sink and plays a foundational role in regional and global climate change mitigation strategies. The state of California, USA, commits to achieving carbon neutrality by 2045 in part by managing terrestrial ecosystems to sequester more than 80 MMT of CO2. We used a 35-year net primary productivity (NPP) remote sensing product with gridded climate, soil, topography, and vegetation data to evaluate spatiotemporal drivers of NPP variation and identify drivers of NPP response to extremes in water availability in California’s major grasslands, shrublands, and woodlands. We used generalized boosted models (GBMs) and linear mixed effects models (LMMs) to identify influential predictors of NPP and characterize their relationships with NPP across seven major vegetation cover types: annual grasslands, blue oak, chamise-redshank chaparral, coastal scrub, coastal oak woodland, mixed chaparral, and montane hardwood. Climate seasonality, specifically greater precipitation and warmer minimum temperatures in early spring and winter, was associated with greater NPP across space, particularly in chaparral, blue oak, and grassland systems. Maximum annual temperature and climatic water deficit (CWD) showed a negative relationship with NPP in most vegetation cover types, particularly chaparral and coastal scrub. We found a significant decrease in NPP over time in most vegetation types, appearing to coincide with the 2012–2016 California mega-drought. However, response to water availability extremes differed by vegetation type. In most vegetation types, especially grasslands, increases in NPP in extreme wet years were greater than declines in NPP in dry years. Our analysis characterizes several climate risks and conservation opportunities in using California’s natural lands to store carbon. Namely, shifts in climate seasonality and water availability extremes threaten these systems’ ability to fix carbon, yet hotspots of NPP resilience may exist and could be enhanced through conservation and restoration. Additional mechanistic work can help illuminate these opportunities and prioritize conservation decision making.

Impact assessment of urbanization on vegetation net primary productivity: A case study of the core development area in central plains urban agglomeration, China

Rapid urbanization process has a negative or positive impact on vegetation growth. Net primary productivity (NPP) is an effective indicator to characterize vegetation growth status. Taking the core development area of the Central Plains urban agglomeration as the study area, we estimated the NPP and its change trend in the past four decades using the Carnegie-Ames-Stanford Approach (CASA) model and statistical analysis based on meteorological and multi-source remote sensing data. Meanwhile, combined with the urbanization impact framework, we further analyzed urbanization's direct and indirect impact on NPP. The results showed that the urban area increased by 2688 km2 during a high-speed urbanization process from 1983 to 2019. As a result of the intense urbanization process, a continuous NPP decrease (direct impact) can be seen, which aggravated along with the acceleration of the urban expansion, and the mean value of direct impact was 130.84 g C·m−2·a−1. Meanwhile, urbanization also had a positive impact on NPP (indirect impact). The indirect impact showed an increasing trend during urbanization with a mean value of 10.91 g C·m−2·a−1. The indirect impact was mainly related to temperature in climatic factors. The indirect impact has a seasonal heterogeneity, and high-temperature environments of urban areas are more effective in promoting vegetation growth in autumn and winter than in summer. Among different cities, high-speed development cities have higher indirect impact values than medium's and low's because of better ecological construction. This study is of great significance for understanding the impact of urbanization on vegetation growth in the Central Plains urban agglomeration area, supporting urban greening plans, and building sustainable and resilient urban agglomerations.

South American mountain ecosystems and global change – a case study for integrating theory and field observations for land surface modelling and ecosystem management

ABSTRACT Background Plot-based monitoring has yielded much information on the taxonomic diversity and carbon (C) storage in tropical lowland forests of the Amazon basin. This has resulted in an improved understanding of the relationship between lowland forest biomass dynamics and global change drivers, such as climate change and atmospheric CO2 concentration. Much less attention has been paid to the mountain ecosystems of South America that comprise montane forests and alpine vegetation (páramo, puna, high Andean grasslands, wetlands, and alpine heath). This vegetation complex provides a variety of ecosystem services and forms a natural laboratory along various physiographic, geological and evolutionary history/biogeography, and land use history gradients. Aims Here, we review existing empirical understanding and model-based approaches to quantify the contribution of mountain ecosystems to ecosystem service provision in the rapidly changing socioecological setting of the South American mountains. The objective of this paper is to outline a broad road map for the implementation of mountain vegetation into dynamic global vegetation models (DGVM) for use in Earth System Models (ESM), based on our current understanding of their structure and function and of their responsiveness to global change drivers. We also identify treeline processes, critical in mountain ecosystems, as key missing elements in DGVMs/ESMs, and thus explore in addition a treeline model. Methods Stocktaking of the availability of empirical data was undertaken from eight research sites along the Andes and in south-eastern Brazil. Out of eight sites, two (one each in Venezuela and Brazil) had some climate, ecological and ecophysiological data potentially suitable to parametrise a DGVM. Tree biomass data were available for six sites. A preliminary assessment of the Joint UK Land Environment Simulator (JULES) DGVM was made to identify gaps in available data and their impacts on model parametrisation and calibration. Additionally, the potential climate-determined elevation of the treeline was modelled to check the DGVM for its ability to identify the transition between the montane forest and alpine vegetation. Results Outcomes of the evaluation of the JULES land surface model identified the following key processes in montane forests: temperature-related decrease in net primary production, respiration, and allocation to above-ground biomass and increase in soil C stocks with elevation. There was a variable agreement between simulated biomass and those derived from field measurements via allometric equations. Conclusions We identified major gaps between data availability and the needs for process-based modelling of South American mountain vegetation and its dynamics in DGVMs. To bridge this gap, we propose a transdisciplinary network, composed of members of the theoretical/modelling and empirical scientific communities, to study the natural dynamics of mountain ecosystems and their responses to global change drivers locally, regionally and at the continental scale, within a social-ecological system framework. The work presented here forms the basis for the design of data collection from field measurements and instrumental monitoring stations to parametrise and verify DGVMs. The network is designed to collaborate with and complement existing long-term research initiatives in the region and will adopt existing standard field protocols. Complementary protocols will ensure compatibility between field data collection and data needed for process-based and empirical models.

Analysis of Changes in Vegetation Carbon Storage and Net Primary Productivity as Influenced by Land-Cover Change in Inner Mongolia, China

Exploring the influence of vegetation carbon stocks over land-cover change and the relationship between land-cover change and net primary production (NPP) is of great practical importance for achieving China’s carbon neutrality target. Therefore, this paper analyses the spatio-temporal distribution of land-cover change and NPP change in Inner Mongolia from 2000 to 2020 and explores the vegetation carbon stock change caused by land-cover change, the relationship between land cover and NPP, and the relationship between land-cover change and NPP change. The results show that the main land-cover change in Inner Mongolia during 2000–2020 was the conversion from other land-cover types to grassland, with the conversion of bare land to grassland from 2000 to 2010 covering an area of 20,634.87 km2. During the period of 2000–2020, the high values of NPP were mainly located in northeastern Inner Mongolia, and the low values were mainly distributed in southwestern Inner Mongolia. The total carbon storage changes in vegetation affected by land-cover change during 2000–2010 and 2010–2020 were 10,736,986.11 t and 3,894,272.41 t. The mean values of NPP for different land covers were, in descending order, forest > cultivated land > wetland > grassland > artificial surfaces > shrubland > water bodies > bare land. Between 2000 and 2010, the change in land-cover type to water bodies was the main cause of the decrease in NPP, and the increase in NPP was mainly due to the conversion of other land-cover types to cultivated land, forest, and grassland. The implementation of appropriate conservation and management measures (e.g., the construction of forest and grass ecological protection), planting, and the protection of high-vegetation carbon storage plants and other means can improve the level of vegetation carbon sequestration and protect the ecological environment of Inner Mongolia.

Simulating diverse forest management options in a changing climate on a Pinus nigra subsp. laricio plantation in Southern Italy.

Mediterranean pine plantations provide several ecosystem services but are vulnerable to climate change. Forest management might play a strategic role in the adaptation of Mediterranean forests, but the joint effect of climate change and diverse management options have seldom been investigated together. Here, we simulated the development of a Laricio pine (Pinus nigra subsp. laricio) stand in the Bonis watershed (southern Italy) from its establishment in 1958 up to 2095 using a state-of-the-science process-based forest model. The model was run under three climate scenarios corresponding to increasing levels of atmospheric CO2 concentration and warming, and six management options with different goals, including wood production and renaturalization. We analysed the effect of climate change on annual carbon fluxes (i.e., gross and net primary production) and stocks (i.e., basal area, standing and harvested carbon woody stocks) of the autotrophic compartment, as well as the impact of different management options compared to a no management baseline. Results show that higher temperatures (+3 to +5 °C) and lower precipitation (-20 % to -22 %) will trigger a decrease in net primary productivity in the second half of the century. Compared to no management, the other options had a moderate effect on carbon fluxes over the whole simulation (between -14 % and +11 %). While standing woody biomass was reduced by thinning interventions and the shelterwood system (between -5 % and -41 %), overall carbon stocks including the harvested wood were maximized (between +41 % and +56 %). Results highlight that management exerts greater effects on the carbon budget of Laricio pine plantations than climate change alone, and that climate change and management are largely independent (i.e., no strong interaction effects). Therefore, appropriate silvicultural strategies might enhance potential carbon stocks and improve forest conditions, with cascading positive effects on the provision of ecosystem services in Mediterranean pine plantations.

Spatially Varying in CO2 Concentrations Regulates Carbon Uptake in the Northern Hemisphere

AbstractAgainst the current climate change background, the mid–high latitudes (>23.7°N) of the Northern Hemisphere have experienced an increase in atmospheric CO2 concentrations, which is higher than the global average. An Beijing Normal University–Earth System Model was used in this study to estimate the carbon uptake in the mid–high latitudes from 2031 to 2060 under the SSP5‐8.5 future emissions scenario. Results showed that, in the high latitudes, non‐uniform CO2 led to a reduction in net ecosystem productivity (NEP) by −0.1 Pg C yr−1. This mainly resulted from a 1.5‐fold greater increase in heterotrophic respiration than in net primary productivity (NPP). In the mid‐latitudes, meanwhile, the decrease in carbon uptake was generally due to a two‐fold greater decrease in NPP than heterotrophic respiration. The decrease in precipitation was closely correlated with local carbon uptake, which could explain this decrease in NPP. It was further found that, in East Asia, changes in atmospheric circulation induced by the non‐uniform CO2 might have reduced the amount of large‐scale precipitation by −9 mm yr−1. This reduction was the primary contributor (98%) to the decrease in overall precipitation, possibly strengthening the limitation of water on plant growth, which would cause a decline in NEP. In the future, it is suggested that such spatially varying CO2 concentrations should be assessed for possible impacts on local carbon uptake.

Spatiotemporal variation of net primary productivity influenced by climatic variables in the karst area of China

Karst area is one of the most ecologically fragile regions. Monitoring spatial and temporal variation of net primary productivity (NPP) and its response to climate change are essential for vegetation restoration. In this study, we used the CASA (Carnegie-Ames-Stanford Approach) model to estimate the NPP in the karst area of China during 2001 to 2019. We analyzed the response of multi-scale NPP to climate change by using Theil-Sen Median trend analysis, partial correlation analysis and time lag analysis. The results showed that the average NPP was 399.06 gC·m−2, decreased from southeast to northwest, with an annual increase rate of 1.93 gC·m−2 from 2001 to 2019. The broadleaf forest had the highest NPP, and summer NPP accounted for 48.12% of annual NPP. Climate change significantly promotes the increase of NPP in the early growing season. Partial correlation analysis showed that NPP was more correlated with precipitation (0.20) than temperature (0.12), this phenomenon was more pronounced in some arid regions. Where precipitation caused a decrease in NPP during the rainy season. The time lag of NPP to temperature change was shorter than precipitation, indicating that NPP is more sensitive to temperature in most regions. The time lag of NPP to temperature changes was very short in spring. Whereas, even in arid regions, the time lag of NPP to precipitation changes was still long. This study can deepen our knowledge of the response of NPP to climate change in karst ecosystems.

Response of terrestrial net primary production to climate change associated with the quadrupling CO2 forcing in CMIP6 models

AbstractTerrestrial net primary production (NPP) has shown remarkable changes in response to increasing atmospheric CO2 and associated climate change. Many studies have investigated and emphasized the CO2 fertilization effects, while the climatic effects remain uncertain in magnitude and spatial pattern. This study investigates these climatic effects and underlying causes by using outputs of the simulation abruptly quadrupled CO2 from 23 CMIP6 models. We find that tropical terrestrial NPP decreases but extratropical terrestrial NPP increases in response to the CO2‐induced climate change. The decreased tropical terrestrial NPP is significantly correlated with the warmer and drier climate anomalies, while the increased extratropical terrestrial NPP is significantly correlated with the warmer and wetter climate anomalies. These results emphasize the climatic effects on terrestrial NPP and reveal the differences among different terrestrial ecosystems, which is favorable for a better understanding of the terrestrial carbon cycle and its coupling with climate.

Carbon variation of dry grasslands in Central Asia in response to climate controls and grazing appropriation

Quantification of grassland carbon (C) variations is necessary for understanding how grazing and climate change interact to regulate carbon capture and release. Central Asia (CA) has the largest temperate grassland belt in the world and unique temperate dryland ecosystems, which experienced severe climate change and grazing-induced disturbances. However, the impact of grazing on C dynamics is highly uncertain owing to climate variations. Here, an arid ecosystem model (AEM) supplemented with a grazing module that specifically addressed physiological and ecological characteristics of dryland vegetation was developed to quantitatively simulate grassland C dynamics in response to changes in precipitation, temperature, grazing intensity, and CO2 level in the past decades. The regional simulation results showed that net primary productivity (NPP) was affected mainly by precipitation (in 59% of the studied area). Grazing had a negative effect on NPP and C stocks, whereas overcompensation occurred in 25.71% of the studied area, mainly in the dry western parts. The complex interaction effects of climate, CO2, and grazing negatively affected productivity, with a grassland NPP decrease of − 1.14 g C/m2/a and high interannual variability. We found that the temporal pattern of cumulative C sequestration, especially total C and vegetation C (VEGC), closely followed the annual fluctuations of precipitation. VEGC stocks decreased from 182.22 to 177.82 g C/m2, with a very low value between 1998 and 2008, when precipitation significantly decreased. The results indicate that southern Xinjiang and the Turgay Plateau of Kazakhstan are ecologically fragile areas due to grassland degradation.

Contributions of climate change and human activities to vegetation dynamics in Qilian Mountain National Park, northwest China

A series of policies have been implicated in the Qilian Mountain National Park (QLMNP) to combat climate change (CC). Distinguishing the impacts of CC and human activities (HA) on vegetation dynamics in QLMNP is crucial for policies implementation and ecological conservation. Here, we quantify the contributions of CC and HA to net primary productivity (NPP) using partial derivatives and dividing them into six different scenarios. The results indicated that the average annual NPP over the whole park significantly increased (2.14 g C m−2 yr−1) and a major portion of QLMNP (74.39%) exhibited a significant vegetation restoration; only 0.14% of the park underwent significant degradation during 2000–2019. Precipitation was the dominant climatic factor that influenced vegetation dynamics in QLMNP (56.66%), while the influences of temperature and solar radiation account for 28.92% and 14.42%, respectively. The climatic factors were positively correlated with NPP in most regions of the QLMNP. The relative contributions of CC and HA to the increase in NPP were 39.70% and 60.30%, respectively. The HA-dominated (NPP) areas contained most ecological restoration projects. In addition, substantial differences were observed in the CC-dominated and HA-dominated areas; 70.73% of the CC-dominated areas and 29.27% of the HA-dominated areas showed the decrease in NPP. Moreover, CC-dominated areas were mainly distributed in low-value NPP areas, and the precipitation was negatively correlated with NPP in this area. In general, CC and the ecological restoration projects made a positive contribution to the eco-environment of QLMNP.

Dynamics of Vegetation Net Primary Productivity and Its Response to Drought in the Mongolian Plateau

Vegetation net primary productivity (NPP) is an important aspect of the global carbon cycle, and its change is closely related to climate change. This study analyzed the spatial-temporal variation of the standardized precipitation evapotranspiration index (SPEI) and NPP in the Mongolian Plateau, and investigated the effect of drought on NPP. To this end, NPP was simulated using the Carnegie-Ames-Stanford Approach (CASA) model. The results showed that from 1982 to 2014, NPP exhibited an upward trend in different seasons, and a significant increasing trend in most areas in the growing season and spring. The degree of drought also showed an increasing trend in each season. Moreover, the decrease in NPP and SPEI in Mongolia was larger than that in Inner Mongolia. Vegetation showed a positive correlation with SPEI in the growing season and summer, but a negative correlation in the other seasons. Moreover, the impact of drought on vegetation in the growing season showed a lag effect, whereas the lag response was inconspicuous during the early stages of the growing season. Different vegetation NPP responded strongly to the SPEI of the current month and the previous month.

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.

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.