Terrestrial Net Primary Productivity Research Articles

Climate warming accelerates carbon release from foliar litter-A global synthesis.

With over one-third of terrestrial net primary productivity transferring to the litter layer annually, the carbon release from litter serves as a crucial valve in atmospheric carbon dioxide concentrations. However, few quantitative global projections of litter carbon release rate in response to climate change exist. Here, we combined a global foliar litter carbon release dataset (8973 samples) to generate spatially explicitly estimates of the response of their residence time (τ) to climate change. Results show a global mean litter carbon release rate ( ) of 0.69 year-1 (ranging from 0.09-5.6 year-1). Under future climate scenarios, global mean τ is projected to decrease by a mean of 2.7% (SSP 1-2.6) and 5.9% (SSP 5-8.5) during 2071-2100 period. Locally, the alleviation of temperature and moisture restrictions corresponded to obvious decreases in τ in cold and arid regions, respectively. In contract, τ in tropical humid broadleaf forests increased by 4.6% under SSP 5-8.5. Our findings highlight the vegetation type as a powerful proxy for explaining global patterns in foliar litter carbon release rates and the role of climate conditions in predicting responses of carbon release to climate change. Our observation-based estimates could refine carbon cycle parameterization, improving projections of carbon cycle-climate feedbacks.

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.

Human activities significantly impact China’s net primary production variation from 2001 to 2020

Formulating ecological restoration strategies requires accurately quantifying how climate and anthropogenic factors influence net primary production (NPP). A Carnegie-Ames-Stanford approach (CASA) model was applied to estimate China’s terrestrial NPP from 2001 to 2020. We adopted a random forest (RF) method to identify the main driving forces for NPP change in China. Total NPP in China increased noticeably with a 24.91 Tg C/yr rate, as shown in our results. The significantly increased NPP was mainly attributed to human activities (64.29 ± 0.17%), chiefly due to human management and ecological projects (afforestation or other) fostered vegetation growth. The primary drivers of NPP variation varied in different geographic regions. Climate dominated the NPP dynamic in north China (52.38 ± 0.91%), where the main factor that restricted the increase of NPP was precipitation. Human activities strongly impacted the NPP variation in the remaining regions. Human management measures increased NPP in northwest and southwest China. In the northeast, east, and south-central China, the NPP change resulted from land use change, primarily grassland, cropland, and forest change. Collectively, our study expands the understanding of the driving forces of NPP change, informing different strategies for achieving ecological restoration and carbon neutrality.

A comparative study on the spatio-temporal patterns and drivers of net primary productivity in three basins across different climate gradients in China

The comparative study on terrestrial net primary productivity in regions across climate gradients may help to better understand ecosystem response to climate change, yet is relatively understudied. Therefore, in this study, we compared the spatio-temporal patterns of net primary productivity during 2010-2019 and identify the different controls in three basins with typical climates in China: the Heihe River Basin with arid and semi-arid climate, Weihe River Basin with semi-arid and semi-humid climate, and Lower Yangtze River Basin with humid climate. Results indicated that the net primary productivity followed the order: Lower Yangtze River Basin (480.3 g C m−2 yr−1) > Weihe River Basin (346.7 g C m−2 yr−1) > Heihe River Basin (98.1 g C m−2 yr−1). The vegetation in the Heihe River Basin had severel hydrothermal limitation as the greatest importance of temperature and precipitation to the net primary productivity. In contrast, land cover type instead of climate became the most important variable on net primary productivity in the Weihe River Basin, and topography and land cover type were critical controls in the Lower Yangtze River Basin. In addition, the annual net primary productivity in all three areas exhibited an increasing trend during 2010-2019. However, the increase of net primary productivity in the Heihe River Basin was primarily driven by the increase of both temperature and precipitation due to the warming and humification in the northwestern of China. In contrast, the increase of temperature (especially spring warming) dominated the increase of net primary productivity in the Weihe River Basin and Lower Yangtze River Basin, due to the relatively sufficient precipitation. Furthermore, monthly net primary productivity exhibited a unimodal curve throughout the year. However, the increasing trend nearly stopped in June and July in the Lower Yangtze River Basin. This is possibly due to the light deficiency with abundant precipitation for plant photosynthesis in the natural ecosystem like forest and shrubland, and the rotation from wheat harvesting to rice planting in the cropland in these months.

Natural Vegetation Succession Under Climate Change and the Combined Effects on Net Primary Productivity

AbstractClimate change and the resulting natural vegetation succession can alter vegetation productivity. However, the mechanisms underlying future productivity changes under the two influences remain unclear. Here, we used the comprehensive sequence classification system to simulate changes in global potential natural vegetation under different climate scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5), and combined the Carnegie–Ames–Stanford Approach model with random forest to assess the response of net primary productivity (NPP) to climate change and vegetation succession from 2020 to 2100. Except for SSP126, terrestrial NPP in 2100 decreased by 0.86, 2.39, and 2.54 Pg C·a−1 versus 2020 under SSP2‐4.5, SSP5‐8.5, and SSP3‐7.0, respectively. Forest was the primary contributor to terrestrial NPP changes. The total forest area was projected to increase under all scenarios, with SSP2‐4.5 showing the largest increase (358.57 × 104 km2). However, expanding forest regions exhibited a relatively low mean NPP, while stable regions demonstrated a declining pattern. Consequently, forest NPP increased under SSP1‐2.6 but decreased by 4.03, 3.43, and 0.82 Pg C·a−1 in 2100 versus 2020 under SSP5‐8.5, SSP3‐7.0, and SSP2‐4.5, respectively. In comparison, grassland and desert exerted minor influence on terrestrial NPP changes, their total NPP decreased only under the SSP1‐2.6 scenario. The grassland area decreased, but the mean NPP increased, whereas the desert area expanded, resulting in consistent changes in both total and mean NPP. Our results analyzed the effects of climate change and vegetation distribution under its influence on the change of NPP, which can deepen our understanding of their relationship.

Spatial and temporal variation of vegetation NPP and analysis of influencing factors in Heilongjiang Province, China

Vegetation net primary productivity (NPP) plays an important role in investigating carbon cycle and NPP provided by forest constitutes the main component of terrestrial vegetation NPP. Since late 1990s, a series of policies for protecting forest have been implemented in Heilongjiang Province, China, directly leading to the continuous change of forest area and growth environment. As a result, analysis of spatiotemporal characteristics of NPP after the implementation of protection policies was conducted in this study, and influencing factors leading to the distribution and spatiotemporal heterogeneity of NPP was also compared quantitatively, aiming to reveal the changing characteristics and influencing factors of NPP in a large area over a longer time span. In this study, multi-source data including MOD17A3 NPP product, meteorological data, topographic data and land-use data was selected, and then the spatiotemporal characteristics of NPP from 2001 to 2020 were analyzed through commonly-used spatiotemporal analysis indices and methods. Finally, influencing factors leading to the distribution and spatiotemporal heterogeneity of NPP in the study area were quantitatively compared and analyzed. Results show that the total amount of NPP in Heilongjiang Province has a fluctuating trend with an increasing rate of 23.47% over the past twenty years, and the increase/decrease scenarios of NPP usually can be found in forest regions with high forest coverage and urban regions experiencing dramatic urbanization processes, respectively. Meanwhile, this study also finds that there is no absolute dominant factor can be responsible for the difference in spatial distribution of NPP, but the conversion between forest and other land-use types are the main factors leading to the spatiotemporal heterogeneity of NPP in the study area. The conclusions in this study may provide guiding significance for formulating forestry protection policies in forest regions and designing land-use plans in the future, aiming to achieve the balance between ecological protection and urban development.

Effects of different rangeland management practices on vegetation metrics and wildlife abundance in a semi-closed ecosystem in north-central Kenya

Rangelands contribute at least 30% of terrestrial net primary productivity, making them an important part of natural ecosystems despite low and unpredictable rainfall regimes. Rangelands are sensitive to anthropogenic activities, making management interventions key to maintaining forage quality and quantity for wildlife. This study explored the effects of mowing of grasslands and carrying away (MO), prescribed grazing (PG), and unprescribed grazing (UG) on above-ground biomass, basal gaps, and wildlife abundance at Lewa Wildlife Conservancy in Meru, Kenya. Data collection was done 18 months after treatment for PG and MO, while UG was continuous. Treated blocks were selected in a systematic and random way, while adjacent untreated plots acted as controls. Blocks were divided into 100 m × 100 m grid cells using ArcMap 10.8.1, where sampling plots were drawn. T-statistics and analysis of variance (ANOVA) tests were used to test statistical significance. We found a significant reduction in the aboveground biomass between MO and its control (t = 4.886, p = 0.003) and between UG and its control (t =5.487, p = 0.007). No significant change was observed between PG and its control (t = 1.192, p = 0.287). MO increased wildlife abundance (t = -4.670, p = 0.003), while PG (t = 0.589, p = 0.583) and UG (t = -0.262, p = 0.803) showed no difference compared to their controls. The mean length of basal gaps between MO and its control decreased (t = 7.069, p = 0.001), while those between UG and its control increased (t = -4.053, p = 0.001), with no effect observed between PG and its control (t = 1.882, p = 0.061). This study recommends the use of mowing of grasslands and carrying away on rangelands as it positively influence the metrics under investigation.

Reducing spatial resolution increased net primary productivity prediction of terrestrial ecosystems: A Random Forest approach

Net primary production (NPP) is a pivotal component of the terrestrial carbon dynamic, as it directly contributes to the sequestration of atmospheric carbon by vegetation. However, significant variations and uncertainties persist in both the total amount and spatiotemporal patterns of terrestrial NPP, primarily stemming from discrepancies among datasets, modeling approaches, and spatial resolutions. In order to assess the influence of different spatial resolutions on global NPP, we employed a random forest (RF) model using a global observational dataset to predict NPP at 0.05°, 0.25°, and 0.5° resolutions. Our results showed that (1) the RF model performed satisfactorily with modeling efficiencies of 0.53–0.55 for the three respective resolutions; (2) NPP exhibited similar spatial patterns and interannual variation trends at different resolutions; (3) intriguingly, total global NPP varied greatly across different spatial resolutions, amounting 57.3 ± 3.07 for 0.05°, 61.46 ± 3.27 for 0.25°, and 66.5 ± 3.42 Pg C yr−1 for 0.5°. Such differences may be associated with the resolution transformation of the input variables when resampling from finer to coarser resolution, which significantly increased the spatial and temporal variation characteristics, particularly in regions within the southern hemisphere such as Africa, South America, and Australia. Therefore, our study introduces a new concept emphasizing the importance of selecting an appropriate spatial resolution when modeling carbon fluxes, with potential applications in establishing benchmarks for global biogeochemical models.

Modeling the impact of urbanization and climate changes on terrestrial vegetation productivity in China by a neighborhood substitution analysis

Vegetation plays a vital role in global carbon sink in terrestrial ecosystems and could be affected by climate changes and human activities. In the current context of rapid urban expansion, understanding the impacts of urbanization and climate changes on net primary productivity (NPP) is helpful to sequester more atmospheric carbon and achieve carbon neutrality. We explored the terrestrial spatio-temporal NPP dynamics in China during the years 2000–2010 and 2010–2020, respectively, using the Carnegie-Ames-Stanford Approach (CASA) model based on multi-source remote sensing data. We then proposed a neighborhood substitution model to isolate the effects of urbanization and climate changes on NPP and examined the driving forces for the NPP update. The results revealed that while urbanization was likely to reduce NPP, averagely by 48.57 Tg C and 50.13 Tg C in the two stages, climate changes improved NPP by 97.71 Tg C and 92.46 Tg C, respectively, indicating that the climate changes offset the reduced vegetation productivity from rapid urbanization. The results highlighted that the rapidly urbanizing process reduced vegetation productivity due to the lost vegetated land and degraded vegetation productivity. In addition, the residual effect other than urbanization and the climate changes also played a part on the degraded vegetation carbon sequestration, reducing NPP by an average of 4.29 Tg C year−1 and 3.94 Tg C year−1 in the two stages, which could be related to other human activities. We recommend protecting vegetation cover and making informed land use plan as means to improve carbon sequestration in the context of rapid urban expansion and climate changes.

Downstream carbon transport and surface CO2 evasion in the Hanjiang River Network and their implications for regional carbon budget

Fluvial carbon fluxes have been increasingly recognized as important components of the global carbon budget. However, it is challenging to accurately quantify carbon fluxes in river networks; therefore, the role of carbon fluxes in the regional carbon budget remains poorly understood. The Hanjiang River Network (HRN) is located in a subtropical monsoon climate zone, and its material transport has a notable impact on the Changjiang River. In this study, it was hypothesized that the total fluvial carbon fluxes from the river network in the subtropical monsoon climate zone are dominated by vertical CO2 evasion and account for a large fraction of terrestrial net primary productivity (NPP) (e.g., 10 %) and fossil CO2 emissions (e.g., 30 %), which is roughly equivalent to the global average. Therefore, the downstream export of three carbon fractions and CO2 evasion were estimated in the HRN over the last two decades and the findings were compared with NPP and fossil CO2 emissions in the basin. The results suggest that approximately 2.14–6.02 Tg C year−1 (1 Tg = 1012 g) of carbon is exported in the HRN. Vertical CO2 evasion represents the largest destination at 1.22–5.34 Tg C year−1 or 68 % of the total fluvial carbon flux component, corresponding to 1.5 %–11 % of the fossil CO2 emissions. Downstream export of dissolved inorganic carbon is the second largest destination with a magnitude of 0.56–1.92 Tg C year−1. Downstream organic carbon export plays a relatively small role with a magnitude of 0.04–0.28 Tg C year−1. The findings also indicate that the offset of total fluvial carbon fluxes from terrestrial NPP is unexpectedly small (2.0 %–5.4 %). Data availability and the simplification of carbon processes introduced uncertainty; therefore, future research should incorporate a fuller representation of fluvial carbon processes and fractions to improve regional-scale carbon accounting.

Estimation of aerosol and cloud radiative effects on terrestrial net primary productivity over northeast Qinghai-Tibet plateau

Processes of plant growth are affected by solar radiation reaching the surface, which is regulated by atmospheric components such as aerosols and clouds. However, there are still large uncertainties in evaluating the impact of aerosol radiative effects (ARE) and cloud radiative effects (CRE) on ecosystems. This study estimated the ARE and CRE on vegetation productivity from 2001 to 2020 over the Northeast Qinghai-Tibet Plateau (QTP) based on MODIS satellite data coupled with the validated Radiative Transfer model (RTM) libRadtran and CASA (Carnegie-Ames-Stanford Approach)model. The results showed that both ARE and CRE have restrained vegetation growth in the last 20 years. The net primary productivity (NPP) of vegetation attenuation by ARE was strongest in summer with an increase of temperature and humidity which caused enhanced air particle transformation and hygroscopic growth, followed by spring and autumn, which were extremely affected by dust, and NPP attenuation by ARE was weakest in winter, accounting for 5.2% of the annual NPP. CRE plays an attenuating role on NPP with increasing cloudiness. The ARE reduced NPP by 18.8 g C/m2/yr, and CRE reduced NPP by 406.9 g C/m2/yr. NPP attenuation by CRE was more than ten times that of NPP attenuation by ARE, which indicated that the CRE has a much stronger weakening of NPP than ARE. The area where the trend of NPP at all-sky conditions increases/decreases had a good match with the areas where the trend of NPP by CRE increases/decreases with R2 being 0.89, indicating that CRE plays a dominant role in attenuating NPP. The increase in NPP is mainly attributed to the decrease in NPP attenuation by CRE over the past two decades. The study results could help to comprehensively understand the ARE and CRE on the terrestrial carbon cycle, and to further access and analyze vegetation ecosystem conditions.

The inverted forest: Aboveground and notably large belowground carbon stocks and their drivers in Brazilian savannas

Savannas contribute to ca. 30 % of the total terrestrial net primary productivity and are responsible for significant carbon storage. Savannas in South America are mostly found within the Cerrado Domain, which is very threatened and presents remarkable carbon pools. Herein, we used a unique dataset of 21 Cerrado sites spanning 144 permanent field plots in Southeastern Brazil to assess the general patterns of above and belowground carbon stocks. We identified the main environmental and tree diversity drivers of aboveground wood carbon and productivity, belowground carbon stocks (roots and soil), carbon ratios (root:shoot and above:below) and total carbon stocks in the Cerrado through a combination of climatic estimates, fire frequency data, field measurements of vegetation, roots, soil carbon, nutrients and texture, and assessment of different components of diversity (species, functional and phylogenetic). Our findings reveal average aboveground, root, and soil carbon stocks of 20.4, 14.24, and 123.13 Mg.ha−1, respectively. Average Root:Shoot and Above:Below confirm the “inverted forest” concept with values of 1.58 and 0.21, respectively. Total carbon was 145.62 Mg.ha−1, reinforcing the great amount of carbon storage in the Cerrado and its role in the carbon cycle and dynamics. Tree diversity variables (mainly species diversity and functional composition variables) had more significant effects over aboveground variables, whereas environmental variables had more significant effects over belowground variables. Ratios and total carbon mixed up these effects. The impressive values of carbon storage, especially belowground, point out the need to better manage and protect the Cerrado. Moreover, our findings might be particularly relevant for discussions on restoration programs focused on the trees-for‑carbon idea that do not consider species diversity and belowground carbon stocks.

Assessing the Effects of Human Activities on Terrestrial Net Primary Productivity of Grasslands in Typical Ecologically Fragile Areas.

Global enhanced human activities have deeply influenced grassland ecosystems. Quantifying the impact of human activities on grasslands is crucial to understanding the grassland dynamic change mechanism, such as grassland degradation, and to establishing ecosystem protection measures. In this study, potential net primary productivity (PNPP), actual NPP (ANPP), and the forage harvest NPP (HNPP) were employed to establish the human activities index (HAI) to reveal the spatiotemporal changes of the effects of human activities on grassland ecosystems in eastern Inner Mongolia from 2000 to 2017, and to further explore the relationship between human activities and grassland degradation. The results showed that the total average PNPP, ANPP, and HNPP of grasslands in eastern Inner Mongolia were 187.2 Tg C yr-1, 152.3 Tg C yr-1, and 8.9 Tg C yr-1, respectively, during the period of 2000 to 2017. The HAI exhibited a clear decreasing trend during the study period, with annual mean values ranging from 0.75 to 0.47, which indicates that the NPP loss induced by human activities is weakening, and this trend is dominated by the difference between potential NPP and actual NPP. About 42.4% of the study area was non-degraded grassland, and the declining grassland degradation index (GDI) indicated that the degradation grade in eastern Inner Mongolia improved from moderate to light degradation. A positive relationship was found between HAI and GDI. This relationship was more significant in Xilingol League, which is a typical ecologically fragile area, than that in Xing'an League and Hulunbuir City.

Response of Terrestrial Net Primary Production to Quadrupled CO2 Forcing: A Comparison between the CAS-ESM2 and CMIP6 Models.

Terrestrial net primary production (NPP) is a key carbon flux that changes with rising atmospheric CO2 and CO2-induced climate change. Earth system models are commonly used to investigate these NPP changes because of their fundamentally trustworthy ability to simulate physical climate systems and terrestrial biogeochemical processes. However, many uncertainties remain in projecting NPP responses, due to their complex processes and divergent model characteristics. This study estimated NPP responses to elevated CO2 and CO2-induced climate change using the Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM2), as well as 22 CMIP6 models. Based on CMIP6 pre-industrial and abruptly quadrupled CO2 experiments, the analysis focused on a comparison of the CAS-ESM2 with the multi-model ensemble (MME), and on a detection of underlying causes of their differences. We found that all of the models showed an overall enhancement in NPP, and that CAS-ESM2 projected a slightly weaker NPP enhancement than MME. This weaker NPP enhancement was the net result of much weaker NPP enhancement over the tropics, and a little stronger NPP enhancement over northern high latitudes. We further report that these differences in NPP responses between the CAS-ESM2 and MME resulted from their different behaviors in simulating NPP trends with modeling time, and are attributed to their different projections of CO2-induced climatic anomalies and different climate sensitivities. These results are favorable for understanding and further improving the performance of the CAS-ESM2 in projecting the terrestrial carbon cycle, and point towards a need for greater understanding and improvements for both physical climatic processes and the terrestrial carbon cycle.

Identification of factors influencing net primary productivity of terrestrial ecosystems based on interpretable machine learning --evidence from the county-level administrative districts in China

Global climate change is rooted in the imbalance between carbon sources and sinks, and net-zero greenhouse gas emissions should focus not only on the source-side drivers but also on the sink-side influencing factors. Taking the county-level administrative districts in China as the sample, this study uses machine learning models to fit the relationship between socioeconomic development (SED) and net primary productivity (NPP) of terrestrial ecosystems. Moreover, it identifies key influencing factors and their effects based on the SHapley Additive exPlanations (SHAP) algorithm. The results show that the districts with low terrestrial NPP show the characteristics of agglomeration distribution. The eight key factors, in order, are as follows: agricultural development level, latitude, population size, longitude, animal husbandry development level, economic scale, time trend and industrialization level. In this study, via SHAP interaction plots, we found that the effects of population, economic growth, and industrialization on terrestrial NPP are regionally heterogeneous; via cluster analysis, we found the stage characteristics of the mode of SED affecting terrestrial NPP. Therefore, the conservation of terrestrial NPP needs to be combined with the stage changes of SED, as well as inter-regional differences, to develop a regionally coordinated and time-coherent ecological carbon sink conservation plan.

Regional Response of Land Hydrology and Carbon Uptake to Different Amounts of Solar Radiation Modification

AbstractSolar radiation modification (SRM) is a proposed method to cool the Earth by intentionally perturbing the Earth's energy balance. One concern about the effect of SRM is disparities in the regional climate response. In this study, we use the Community Earth System Model (CESM1.2) to analyze the regional response of land hydrology and terrestrial carbon uptake to different amounts of SRM. The SRM is implemented by a uniform increase in volcanic‐size sulfate aerosols in the stratosphere under a doubling of atmospheric CO2. Our results show that different amounts of SRM could either moderate or exacerbate CO2‐induced changes in land hydrology including precipitation, precipitation minus evapotranspiration, and soil moisture (SM), but the effect varies widely across regions and specific variables. An “optimal” amount of SRM that moderates land hydrology changes for one region might exacerbate changes for other regions (or vice versa). Also, our study shows that for quite a few regions, partial SRM moderates CO2‐induced change in precipitation minus evaporation but exacerbates changes in CO2‐induced SM. The response of terrestrial Net primary productivity (NPP) to different amounts of SRM shows large regional disparities, depending on whether temperature or water availability constrains NPP more. Our study also shows that the effect of CO2 physiological forcing plays a key role in regulating land hydrology response to SRM, especially at the regional scale.

GLOBAL ARIDIFICATION AND THE DECLINE OF NPP: A COMMENTARY on Projected increases in global terrestrial net primary productivity loss caused by drought under climate change by Dan Cao, Jiahua Zhang, Jiaqi Han, Tian Zhang, Shanshan Yang, Jingwen Wang, Foyez Ahmed Prodhan, and Fengmei Yao

AbstractNet primary production (NPP) is an important metric of the global carbon cycle, critical for monitoring climate stabilization and for societal economic products. Global NPP should be monitored continuously to adapt societal policy to emerging declines.

Spatiotemporal patterns and drivers of net primary production in the terrestrial ecosystem of the Dajiuhu Basin, China, between 1990 and 2018

Net primary production (NPP) plays a vital role in both the evolution of ecosystems and the terrestrial carbon cycle and is influenced by geographical conditions and climate change. Understanding the terrestrial carbon balance requires an in-depth knowledge of the relationships between NPP and geographical and climatic conditions. This study aimed to simulate and map the daily spatiotemporal features of terrestrial NPP in the Dajiuhu Basin (DB), China, using the BEPS-TerrainLab V2.0 model. This area is highly sensitive to climate change and is a water source in the central path of the South-to-North Water Transfer Project. Changes in the distribution of daily and seasonal NPP between 1990 and 2018 were examined using the Mann-Kendall (MK) test, the moving t-test (MTT), and multiple regression analyses. It was found that: 1) The model explained 79% of the variation in eddy covariance (EC)-tower-measured NPP, and could thus be applied to the DB; 2) The mean annual NPP in the DB between 1990 and 2018 was 705 g C/m2/yr, with the terrestrial NPP decreasing before 1999 (−31.8 g C/m2/yr) and increasing after 1999 (0.87 g C/m2/yr); 3) The NPP first increased and then decreased with increasing altitude, with higher NPP values mainly found in the mountains on the periphery of the basin and lower NPP values in the central basin;4) Changes in NPP during autumn and summer contributed the most to the annual NPP trend. Temperature and NPP were positively correlated in summer and autumn, whereas they were negatively correlated in spring and winter. Precipitation and NPP were positively correlated in spring, autumn, and winter; 5) The sensitivities of NPP to temperature and precipitation differed across the different seasons. The sensitivities of the annual NPP to temperature and precipitation decreased and increased, respectively, compared with those before 1999. Although the contribution of precipitation to the NPP trend became more significant after 1999, that of temperature decreased. This study proposes an approach for a detailed study of daily changes in NPP and for examining the link between environmental factors, climatic conditions, and NPP distribution.

Projected Increases in Global Terrestrial Net Primary Productivity Loss Caused by Drought Under Climate Change

AbstractUnderstanding present and future impacts of drought on the terrestrial carbon budget is of great significance to the evaluation of terrestrial ecosystem disturbance and terrestrial carbon sink. Here, we evaluate the effect of vegetation net primary productivity (NPP) associated with drought through the difference between the mean NPP in the drought and normal years during a specific time period (30 years). Then, the NPP effects in different vegetation types and climatic zones under baseline stage (1981–2010) and future climate scenarios (RCP2.6, RCP4.5, and RCP8.5) is assessed. The results indicate that the negative NPP extremes are captured in most regions, except for the high‐latitude in the Northern Hemisphere. The NPP loss caused by extreme droughts in 2071–2100 is largest under RCPs, followed by the effects of severe and moderate droughts. Regionally, central United States, southern Africa, central Asia, India, Amazon tropical rainforest, and Australia are projected to experience a significant increase in negative NPP extremes and most of these regions are in arid and semi‐arid and tropical rain forest areas. In contrast, tropical Asia suffers little drought effects. For different vegetation, Evergreen Broadleaf Forest, Closed Shrubland, Open Shrubland, Croplands, and Grassland are the most affected by drought. The largest NPP loss occurs in most part of regions under RCP4.5 scenario, not RCP8.5. Climate change is projected to play the largest role in aggravating the risk of drought‐induced NPP reduction. And meanwhile, the adverse effects of drought on vegetation may be resisted through rational fertilizer utilization and land management in future.

Estimation of Terrestrial Net Primary Productivity in the Yellow River Basin of China Using Light Use Efficiency Model

The net primary productivity (NPP) of vegetation is an essential factor of ecosystem functions, including the biological geochemical carbon cycle, which is often impacted by climate change and human activities. It plays a significant role in comprehending the nature of carbon balance in an ecosystem and demonstrates the global and regional carbon cycle dynamics. The present study used an upgraded CASA model to calculate the NPP in the Yellow River Basin (YRB), China. The model’s simulation ability was improved by changing the model parameters. Further, the CASA model was validated by comparing with MODIS-NPP and in situ observed NPP, wherein the accuracy of the CASA model estimation was found satisfactory to estimate NPP changes in the study area. The simulated results of the improved CASA model showed that the mean annual NPP value of vegetation in the YRB was 283.4 gC m–2 a–1 from 2001 to 2020, with a declining trend in spatial distribution from south to north. In contrast, the NPP appeared as an increasing trend in the YRB temporally from 212 gC m–2 a–1 in 2001 to 342 gC m–2 a–1 in 2020, with a mean annual growth rate of 4.6 gC m–2 a–1. The total NPP in the YRB increased by 40,088.3 GgC between 2001 and 2020, from 226.06 TgC to 266.15 TgC. This rise can be attributed to the increase in forests. The average grassland area has reduced by 4651 km2 during the last two decades, significantly impacting the total NPP of grasslands. Although the increase in NPP in wetlands was minimal, accounting for 815.53 GgC, the highest change percentage of 79.78%, could be observed among the six vegetation types due to the anthropogenic influences and climate change. The conditions favorable for vegetation growth and a sustained environment were enhanced by the increased precipitation and temperature and the reinforced ecological protection by the government.