Mean Net Primary Productivity Research Articles

A meta-analysis reveals increases in soil organic carbon following the restoration and recovery of croplands in Southwest China.

In China, the Grain for Green Program (GGP) is an ambitious project to convert croplands into natural vegetation, but exactly how changes in vegetation translate into changes in soil organic carbon remains less clear. Here we conducted a meta-analysis using 734 observations to explore the effects of land recovery on soil organic carbon and nutrients in four provinces in Southwest China. Following GGP, the soil organic carbon content (SOCc) and soil organic carbon stock (SOCs) increased by 33.73% and 22.39%, respectively, compared with the surrounding croplands. Similarly, soil nitrogen increased, while phosphorus decreased. Outcomes were heterogeneous, but depended on variations in soil and environmental characteristics. Both the regional land use and cover change indicated by the landscape type transfer matrix and net primary production from 2000 to 2020 further confirmed that the GGP promoted the forest area and regional mean net primary production. Our findings suggest that the GGP could enhance soil and vegetation carbon sequestration in Southwest China and help to develop a carbon-neutral strategy.

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.

Spatiotemporal Distribution of Carbon Sink Indicators—NPP and Its Driving Analysis in Ordos City, China

Ordos City is an important energy supply city for Chinese provinces and cities, providing a secure energy supply for China while also generating corresponding environmental pollution. Examining the spatiotemporal patterns of net primary productivity (NPP) in Ordos City and its driving factors is relevant to the realization of the carbon emission policy in Inner Mongolia. This study was undertaken to analyze NPP and its driving factors in Ordos City from 2000 to 2019 using NPP data, CO2 spatial grid data, meteorological data and statistical yearbook data accordingly. The NPP in Ordos City increased significantly from 2000 to 2019, mainly showing low values of NPP in the northwest and high values in the southeast. The usable grassland area and annual mean precipitation had a significant positive correlation with NPP, whereas the other factors had a more significant negative correlation. The usable grassland area had the largest influence on NPP, and fixed asset investment had the smallest influence on NPP. The total NPP–anthropogenic factor regression model and the mean NPP–natural factor regression model constructed allow for the prediction of NPP. Anthropogenic carbon emissions, population growth and usable grassland area were the main causes of NPP changes. Planting and protecting green plants and scientific and effective energy extraction plans are measures that enhance the degree of carbon sequestration in Ordos City.

Above- and Belowground Biomass Carbon Stock and Net Primary Productivity Maps for Tidal Herbaceous Marshes of the United States

Accurate assessments of greenhouse gas emissions and carbon sequestration in natural ecosystems are necessary to develop climate mitigation strategies. Regional and national-level assessments of carbon sequestration require high-resolution data to be available for large areas, increasing the need for remote sensing products that quantify carbon stocks and fluxes. The Intergovernmental Panel on Climate Change (IPCC) provides guidelines on how to quantify carbon flux using land cover land change and biomass carbon stock information. Net primary productivity (NPP), carbon uptake, and storage in vegetation, can also be used to model net carbon sequestration and net carbon export from an ecosystem (net ecosystem carbon balance). While biomass and NPP map products for terrestrial ecosystems are available, there are currently no conterminous United States (CONUS) biomass carbon stock or NPP maps for tidal herbaceous marshes. In this study, we used peak soil adjusted vegetation index (SAVI) values, derived from Landsat 8 composites, and five other vegetation indices, plus a categorical variable for the CONUS region (Pacific Northwest, California, Northeast, Mid-Atlantic, South Atlantic-Gulf, or Everglades), to model spatially explicit aboveground peak biomass stocks in tidal marshes (i.e., tidal palustrine and estuarine herbaceous marshes) for the first time. Tidal marsh carbon conversion factors, root-to-shoot ratios, and vegetation turnover rates, were compiled from the literature and used to convert peak aboveground biomass to peak total (above- and belowground) biomass and NPP. An extensive literature search for aboveground turnover rates produced sparse and variable values; therefore, we used an informed assumption of a turnover rate of one crop per year for all CONUS tidal marshes. Due to the lack of turnover rate data, the NPP map is identical to the peak biomass carbon stock map. In reality, it is probable that turnover rate varies by region, given seasonal length differences; however, the NPP map provides the best available information on spatially explicit CONUS tidal marsh NPP. This study identifies gaps in the scientific knowledge, to support future studies in addressing this lack of turnover data. Across CONUS, average total peak biomass carbon stock in tidal marshes was 848 g C m−2 (871 g C m−2 in palustrine and 838 g C m−2 in estuarine marshes), and based on a median biomass turnover rate of 1, it is expected that the mean NPP annual flux for tidal marshes is similar (e.g., 848 g C m−2 y−1). Peak biomass carbon stocks in tidal marshes were lowest in the Florida Everglades region and highest in the California regions. These are the first fine-scale national maps of biomass carbon and NPP for tidal wetlands, spanning all of CONUS. These estimates of CONUS total peak biomass carbon stocks and NPP rates for tidal marshes can support regional- and national-scale assessments of greenhouse gas emissions, as well as natural resource management of coastal wetlands, as part of nature-based climate solution efforts.

Impacts of Ocean Deoxygenation on Marine Benthos in the Gulf of Mexico

Ocean deoxygenation is a growing concern globally. Oxygen is less soluble in warm water, and warming temperatures also result in the slowdown of ocean circulation which limits oxygen delivery to deeper waters. Anthropogenic eutrophication has also contributed to the development of hypoxic conditions in many coastal areas. Here we investigate biodiversity structure along an environmental gradient in the Gulf of Mexico to see how patterns of spatiotemporal turnover can inform future biotic response of benthos to ocean deoxygenation. Live and dead assemblages of bivalve mollusks were collected at 15 stations offshore Louisiana, Alabama, and Florida. Abundance and body size data were collected, and specimens were classified functionally using information about feeding, attachment, life position, and body size. Environmental conditions were characterized using multi-decadal mean sea surface temperature (SST), dissolved oxygen (DO), and net primary productivity (NPP), and grain size data from our field samples. Stations in the north-central Gulf affected by Mississippi River discharge are characterized by higher NPP, lower DO, and higher percentages of silt and clay than stations in the northeastern Gulf. Both taxonomic and functional diversity significantly covary with this environmental gradient, with the lowest diversities observed at stations in the core of Louisiana’s “dead zone.” Analyses of spatiotemporal turnover patterns reveal shifts in the dominant feeding mode, with hypoxic environments containing a greater abundance of deposit and mixed feeders, compared with more oxygenated environments that host an abundance of suspension feeders and are characterized by a greater variety of feeding ecologies. Live-dead analyses reveal a shift in taxonomic and functional diversity in coastal Louisiana, that appears to coincide with the onset of anthropogenic eutrophication in these coastal settings.

Modeling carbon uptake by vegetation of grassland ecosystems and its associated factors in China based on remote sensing

In order to reveal the spatial variation characteristics and influencing factors of grassland net primary productivity (NPP) in China, this paper uses remote sensing data, land use data and meteorological data to simulate and estimate China’s grassland net primary productivity from 2001 to 2019 using the Carnegie-Ames-Stanford Approach (CASA). The trend analysis and complex correlation analysis were used to analyze the relationship with the temporal and spatial changes of grassland NPP from the perspectives of climate factors, topography, longitude and latitude. The results show that: 1) In the past 19 years, the China’s grassland NPP has generally shown a fluctuating upward trend, the spatial distribution of NPP variation shows a characteristic of low in the west and high in the east, with the increased area accounting for 70.39% of the total grassland area, and the low NPP values are mainly distributed in the northwestern part of Tibet and Qinghai and the central part of Inner Mongolia, the average annual NPP is 257.13 g C·m−2·a−1. 2) The change of mean NPP value of grassland in China is more dependent on precipitation (p) than air temperature (T). 3) Grassland NPP showed a decreasing trend with the increase of altitude, and the NPP on the gradient with DEM between 200 m and 500 m was the highest (483.86 g·C·m−2·a−1); The maximum annual mean value (448.42 g C·m−2·a−1) is fallen over the sharp slope of 35°–45°; the NPP of grassland increases with the slope (from shade to sunny), and the NPP of grassland on the semi-sunny slope increases. The annual average NPP is the highest (270.87 g C·m−2·a−1). 4) The mean value of grassland NPP was negatively correlated with the change of latitude, and showed a “wave-like” downward trend from south to north; the mean value of grassland NPP was positively related to the change of longitude. The correlation relationship shows a “stepped” upward trend from west to east.

Growth Suitability Evaluation of Larix principis-rupprechtii Mayr Based on Potential NPP under Different Climate Scenarios

Larch (Larix principis-rupprechtii Mayr) is a major coniferous tree species in northern China, and climate change has serious impacts on larch growth. However, the impact of future climate change on net primary productivity (NPP) and the growth suitability of larch is unclear. Based on forest inventory data, spatially continuous environmental factor data (climate, topography, soil), and NPP from the Carnegie-Ames-Stanford approach (CASA) model in the study area, the random forest (RF) model was used to simulate the potential NPP and growth suitability of larch under different shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) for current and future (2041–2060, 2080–2100). The correlation between potential NPP and determinants under different climate scenarios was analyzed at the pixel scale. The results showed that: (1) RF showed excellent performance in predicting the potential NPP of the region (R2 = 0.80, MAE = 15.61 gC·m−2·a−1, RMSE = 29.68 gC·m−2·a−1). (2) Under current climatic conditions, the mean potential NPP of larch was 324.9 gC·m−2·a−1. Low growth suitability of larch occurred in most parts of the study area, and high growth suitability only existed in the Bashang area and the high-elevation mountains. (3) The total area of high and medium growth suitable areas were projected to be 76.0%, 66.7%, 78.2%, and 80.8% by the end of this century under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 climate scenarios, respectively. (4) Under the SSP1-2.6 and SSP2-4.5 climate scenarios, the temperature had a significant contribution to the accumulation of the larch’s NPP, whereas precipitation had less effect on the larch’s growth. The results provided a theoretical basis for the adaptive management of larch forests under global climate change.

Investigating the Impacts of Urbanization on Vegetation Net Primary Productivity: A Case Study of Chengdu–Chongqing Urban Agglomeration from the Perspective of Townships

As an emerging national strategic urban agglomeration in China, the changing trend of vegetation net primary productivity (NPP) and the impact of the urbanization level (UL) on carbon cycle functions in the Chengdu–Chongqing urban agglomeration (CUA) have received increasing attention. Previous studies have largely overlooked externalities and the heterogeneity of urbanization effects, and urbanization has also been analyzed in isolation (with focus being on land and population urbanization). In this study, the spatial evolution of NPP was evaluated from 2000 to 2020 at the township level (3859) using multivariate remote sensing data and a comprehensive index (UL) that included population urbanization, land urbanization, and economic urbanization. Bivariate spatial autocorrelation, spatial Durbin models, and geographically weighted regression models were used to analyze the spatial externalities of urbanization impacts and assess the global and local effects. The results show that the region’s mean NPP increased by 177.25 g*c/m2 (annual growth of 1.59%), exhibiting a distribution of “low in the middle and high in the periphery” and low-value clustering along major traffic arteries and rivers. Low-value-NPP areas were mainly located in urban centers, while the high-level areas were in the mountainous region (in the southwest and southeast) and significantly expanded over time. Negative correlation clusters were the main clustering types between the UL and NPP; the “High-Low” negative correlation clusters accelerated outward from the urban centers of Chengdu and Chongqing. Overall, urbanization had negative direct and spillover effects on NPP, exhibiting spatial non-stationarity of the negative driving effect within the urban agglomeration. The results indicate the need to strengthen regional ecological joint governance and adopt more place-based urbanization optimization strategies. This study offers new insights to help to reduce the constraining effects of urbanization on vegetation productivity and ecological functions from the perspectives of population agglomeration, land expansion, and industrial construction.

Net Primary Productivity Variations Associated with Climate Change and Human Activities in Nanjing Metropolitan Area of China.

Rapid economic development has changed land use and population density, which in turn affects the stability and carbon sequestration capacity of regional ecosystems. Net primary productivity (NPP) can reflect the carbon sequestration capacity of ecosystems and is affected by both climate change and human activities. Therefore, quantifying the relative contributions of climate change and human activities on NPP can help us understand the impact of climate change and human activities on the carbon sequestration capacity of ecosystems. At present, researchers have paid more attention to the impact of climate change and land use change on NPP. However, few studies have analyzed the response of the NPP to gross domestic product (GDP) and population density variations on a pixel scale. Therefore, this paper analyzes the impact of climate change and human activities to NPP on a pixel scale in the Nanjing metropolitan area. During the period 2000-2019, the annual mean NPP was 494.89 g C·m-2·year-1, and the NPP in the south of the Nanjing metropolitan area was higher than that in the north. The NPP was higher in the forest, followed by unused land, grassland, and cropland. In the past 20 years, the annual mean NPP showed a significant upward trend, with a growth rate of 3.78 g C·m-2·year-1. The increase in temperature and precipitation has led to an increasing trend of regional NPP, and the impact of precipitation on NPP was more significant than that of temperature. The transformation of land use from low-NPP type to high-NPP type also led to an increase in NPP. Land use change from high-NPP type to low-NPP type was the main cause of regional NPP decline. Residual analysis was used to analyze the impact of human activities on NPP. Over the last 20 years, the NPP affected by human activities (NPPhum) showed a high spatial pattern in the south and a low spatial pattern in the north, and the annual mean NPPhum also showed a fluctuating upward trend, with a growth rate of 2.00 g C·m-2·year-1. The NPPhum was influenced by both GDP and population density, and the impact of population density on NPP was greater than that of GDP.

Temporal and spatial variation of vegetation net primary productivity and its driving factors in Ningxia, China from 2000 to 2019

Ningxia is an important agriculture-pastoral area in China. Research on the temporal and spatial variations of net primary productivity (NPP) in this area and its driving factors would help understand the trends and leading factors of NPP variations, and reveal vegetation restoration status and causes. Based on the NPP data of MODIS, we used Theil-Sen Median trend analysis, correlation analysis, overlay analysis and other methods to analyze the spatiotemporal variations and driving factors of NPP in Ningxia. The results showed that NPP of Ningxia vegetation showed a fluctuating upward trend during 2000-2019, with a linear growth rate of 5.46 g C·m-2·a-1. The NPP presented a spatial characteristics of "two high and two low", with the highest in the southern mountain area, followed by the Yellow River irrigation area, and the lowest in the hilly area of the central arid zone and Helan Mountain. 84.2% of the NPP in the study area was under significant restoration, mainly distributed in the central and southern mountainous and hilly areas. The NPP varied significantly with altitude and was significantly affected by the terrain. NPP center of gravity had generally moved to the south, with the increase and growth rate of NPP of vegetation in the south being greater than that in the north. The annual precipitation in Ningxia had shown an increasing trend, while the average annual temperature had slightly decreased. The NPP was significantly affec-ted by precipitation (R2=0.291), whereas the correlation between mean annual temperature and NPP was weak. 96.9% of the study area was at a state of vegetation restoration, which was promoted by both climate change and human activities.

The impact of climate change on growth and drought-induced mortality risk of Robinia pseudoacacia plantations along a precipitation gradient on the Chinese Loess Plateau

Robinia pseudoacacia has been widely planted on the Chinese Loess Plateau for soil and water conservation. Declining growth of R. pseudoacacia plantations has become a recently emerging challenge for revegetation and sustainable forest management in this region. In the suitable area of R. pseudoacacia, we selected four representative study sites along a precipitation gradient (aridity indexes of 1.3 at Fufeng, 1.5 at Changwu, 1.9 at Ansai, and 2.4 at Mizhi) and used an integrated Biome BioGeochemistry-plant hydraulic traits model (BBGC-SPERRY) to assess the climate change impacts on net primary productivity (NPP), maximum leaf area index (LAImax), actual evapotranspiration (AET), and annual average percentage loss of whole-plant hydraulic conductance (APLK) for R. pseudoacacia. We adopted climate scenario data derived from five downscaled Global Circulation Models under three Representative Concentration Pathways (RCPs2.6, RCP4.5 and RCP8.5) and set baseline (1981–2020), near future (2021–2060, NFP) and far future (2061–2099, FFP) periods. Our projections show annual precipitation will significantly increase during the NFP and FFP at the Ansai and Mizhi sites and increase slightly at the Fufeng and Changwu sites during the FFP; annual maximum and minimum temperatures will increase under all RCPs. The mean NPP and LAImax of R. pseudoacacia will significantly decrease by 9.9% (RCP4.5) to 49.1% (RCP2.6) during the NFP and by 7.4% (RCP4.5) to 50.1% (RCP2.6) during the FFP at the Changwu, Ansai, and Mizhi sites; however, both measures will significantly increase during the NFP and FFP at the Fufeng site. The AET will significantly increase during the NFP and FFP at all sites. The maximum APLK will increase from south to north along the precipitation gradient, with values greater than 60% at the Changwu, Ansai, and Mizhi sites during the NFP and FFP. These results indicate the drought-induced mortality risk of R. pseudoacacia will increase under future climate change.

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.

Spatial Distribution of Optimal Plant Cover and Its Influencing Factors for Populus simonii Carr. on the Bashang Plateau, China

The Bashang Plateau is the core zone of the agro-pastoral ecotone in northern China and represents an ecological barrier for preventing the invasion of wind-blown sand in the Beijing–Tianjin–Hebei region. Increasing plant cover to control soil erosion is an effective measure to address land degradation; however, plant cover is different from climatic conditions. In this study, we determined the optimal spatial distribution of Populus simonii Carr., which is a widely planted species used for revegetation on the Bashang Plateau. A modified Biome-BGC model was used to simulate the dynamics of the net primary productivity (NPP), actual evapotranspiration (AET), and leaf-area index (LAI). The model was validated using field-observed tree-ring and MODIS AET and NPP data. The dynamics of AET, NPP and LAI for P. simonii at 122 representative sites in the study area for the period 1980–2019 were simulated by the validated model. The results showed that the spatial distributions of mean AET, NPP, and LAI generally decreased from southeast to northwest. The ranges of optimal plant cover in terms of maximum LAI for P. simonii were 3.3 in the Fengning–Weichang area, 1.9 in the Shangyi–Zhangbei–Guyuan area and 1.3 in the Kangbao area. Mean annual precipitation (MAP), elevation, soil texture and mean annual temperature were the main factors influencing the distribution of AET, NPP and LAI. As the MAP decreased, the correlations between AET, NPP, LAI and precipitation gradually decreased. In different subregions, the factors influencing optimal-plant-cover distribution varied significantly. These quantitative findings provide the optimal plant cover for the dominant tree in different subregions and provide useful information for land degradation management on the Bashang Plateau.

Global Sensitivity Analysis of the LPJ Model for Larix olgensis Henry Forests NPP in Jilin Province, China

Parameter sensitivity analysis can determine the influence of the input parameters on the model output. Identification and calibration of critical parameters are the crucial points of the process model optimization. Based on the Extended Fourier Amplitude Sensitivity Test (EFAST) and the Morris method, this paper analyzes and compares the parameter sensitivity of the annual mean net primary productivity (NPP) of Larix olgensis Henry forests in Jilin Province simulated by the Lund–Potsdam–Jena dynamic global vegetation model (LPJ model) in 2009–2014 and 2000–2019, and deeply examines the sensitivity and influence of the two methods to each parameter and their respective influence on the model’s output. Moreover, it optimizes some selected parameters and re-simulates the NPP of Larix olgensis forests in Jilin Province from 2010 to 2019. The conclusions are the following: (1) For the LPJ model, the sensitive and non-influential parameters could be identified, which could guide the optimization order of the model and was valuable for model area applications. (2) The results of the two methods were similar but not identical. The sensitivity parameters were significantly correlated (p < 0.05); parameter krp was the most sensitive parameter, followed by parameters αm, αa and gm. These sensitive parameters were mainly found in the photosynthesis, water balance, and allometric growth modules. (3) The EFAST method had a higher precision than the Morris method, which could calculate quantitatively the contribution rate of each parameter to the variances of the model results; however, the Morris method involved fewer model running times and higher efficiency. (4) The mean relative error (MRE) and mean absolute error (MAE) of the simulated value of LPJ model after parameter optimization decreases. The optimized annual mean value of NPP from 2010 to 2019 was 580 g C m−2 a−1, with a mean annual growth rate of 2.13%, exhibiting a fluctuating growth trend. The MAE of the simulated value of LPJ model after parameter optimization decreases.

Unique characteristics of ecosystem CO2 exchange in Sundarban mangrove forest and their relationship with environmental factors

Sundarban mangroves, known to be the largest single block of tidal halophytic mangrove forest globally, covers a significant portion of the world's mangroves and contributes substantially to the global mangrove carbon budget. Nevertheless, there is still a lack of long-term continuous monitoring of CO2 fluxes over this crucial ecosystem and their dynamics in response to climatic variations. This study presents the carbon balance and seasonal dynamics of this oldest and undisturbed mangrove ecosystem using quasi-continuous eddy covariance measurements from April 2012 to March 2016. These tidal forests are found to be net C sink with a mean net primary production (NEP) of 276 g C m−2 yr−1 (±35; ±1 Standard deviation amongst the four years). The NEP is partitioned into gross primary production (GPP) and ecosystem respiration indicate gross sequestration of 1581 (±152) g C m−2 yr−1 with a respiratory loss of 1305 (±184) g C m−2 yr−1. We have observed that inter- and intra-annual variations in CO2 fluxes are primarily controlled by environmental factors such as temperature, vapour pressure deficit (VPD), rainfall and photosynthetic active radiation. At the study site, the photosynthetic activity and light use efficiency decreased with an increase in temperature and VPD. Though minimal seasonal fluctuations in CO2 fluxes were observed, a strong linkage has been observed between C fluxes and satellite-derived enhanced vegetation index (MODIS EVI) during the study period. Further, the carbon assimilation rates were found to be higher under diffused sky than normal conditions due to the increased photosynthetic activity by penetration of diffused radiation within the mangrove canopies. Additionally, ecosystem productivity during the study period was higher during the wet periods than dry periods. Our findings show that ecosystem productivity rates are strongly related to temperature, vapour pressure deficit, rainfall, and radiation, implying that global warming could have a significant impact on these environmental factors and other underlying parameters (such as salinity, tidal inundation patterns etc.) and potentially reduce the C sequestration potential of these tropical mangroves of India.

土地利用转变与海拔高度协同作用黄土高原植被固碳变化特征

PDF HTML阅读 XML下载 导出引用 引用提醒 土地利用转变与海拔高度协同作用黄土高原植被固碳变化特征 DOI: 10.5846/stxb202106211643 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 陕西省自然科学基础研究计划项目（2017JZ008） Vegetation carbon sequestration in the Loess Plateau under the synergistic effects of land cover change and elevations Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:全球固碳释碳问题一直是近年来关乎民生的热点话题，区域碳源/碳汇对生态环境的重要性不言而喻。基于CASA模型估算黄土高原1990-2015年植被净初级生产力的年际变化，并分析土地利用变化、海拔高度及两者协同作用对其综合影响，结果表明：（1）黄土高原1990-2015年植被NPP与植被固碳总体呈增加趋势，年均NPP增速2.74 gC m-2 a-1，年均固碳增速1.13 TgC/a，研究区林地年均NPP （619.5 gC m-2 a-1）远超其他用地类型，固碳效果理想；（2）黄土高原年均NPP随高程的增加先降低后升高，年总NPP和固碳量随高程增加变化趋势相反；（3）研究区土地利用转变类型中退耕还林的植被固碳效果最好；而林地变为耕地或草地均不能达到固碳目的，此外，更推荐在研究区海拔低于1500 m变草为耕，海拔高于1500 m退耕还草，海拔高于3000 m变耕、草为林。以期为区域尺度的生态环境建设提供一定的参考和科学依据。 Abstract:Global carbon sequestration and release has been a hotspot issue concerning people's livelihood in recent years. The importance of regional carbon sequestration and release to the ecological environment was self-evident. It is of great theoretical and practical significance to use remote sensing data and appropriate estimation model to quantitatively estimate NPP (Net Primary Productivity) and analyze spatio-temporal pattern of vegetation carbon sequestration and carbon release in the Loess Plateau. Based on the CASA (Carnegie Ames Stanford Approach) model, this paper estimated the annual change of the NPP on the loess plateau from 1990 to 2015, and analyzed the comprehensive effects in the process of Land Use/Land Cover Change (LUCC), elevations and their synergistic effects. It found that:(1) vegetation NPP and carbon sequestration showed an increasing trend in the Loess Plateau from 1990 to 2015. The annual average growth rate of NPP was 2.74 gC m-2 a-1 and the annual average growth rate of carbon sequestration was 1.13 TgC/a. The average annual NPP (619.5 gC m-2 a-1) of forest land in the study area was much higher than that of other land types, which was an ideal means of carbon sequestration. (2) The annual mean NPP of the Loess Plateau increased year by year, but the annual mean annual NPP decreased first and then increased with the increase of elevation, while the annual total NPP and carbon sequestration showed opposite trends with the increase of elevation. (3) In the study area, conversion of cropland to forest contributed the most to vegetation carbon sequestration among all land use changes types, meanwhile, the conversion of forest into cropland or grassland could not achieve carbon sequestration. In addition, it is recommended to convert grassland to cropland when the elevation is lower than 1500 m, return cropland to grassland when the elevation is higher than 1500 m, and convert cropland and grassland to forest when the elevation is higher than 3000 m in the study area. The study focuses on the effect of carbon sequestration under the synergistic effect of land use change and elevations. It is concluded that the development and utilization of land in the study area leads to the increase of carbon sequestration, while the ecological return of land leads to the increase of carbon sequestration; Moreover, it is more suitable to convert cropland to forest at low and high altitude regions than at middle altitude in the study area, in order to provide reference and guidance for the ecological environment in the regional scale. 参考文献 相似文献 引证文献

Evaluating carbon use efficiency in forest types and ecoregions of Turkey

The total amount of carbon deposited by forests is gross primary productivity (GPP), and the net amount remaining after respiration is net primary productivity (NPP). The carbon storage effectiveness of forests is determined by the NPP:GPP ratio. This ratio is carbon use efficiency (CUE), and it is important for understanding the dynamics of carbon exchange between the biosphere and atmosphere. The aim of this study is to evaluate the variation of CUE, which is commonly used as a constant value in terrestrial carbon models, in different forest types and ecoregions of Turkey. The distribution of forest types in different ecoregions of Turkey was determined and, NPP, GPP, and CUE values were calculated for the different forest types in each region in this study. Moderate Resolution Imaging Spectroradiometer (MODIS) satellite image was obtained for NPP and GPP content of forest types. In addition that the CORINE land use classification system was used for the spatial distribution of coniferous, broad-leaved and mixed forests in Turkey. The highest mean NPP (640 gC / m-2 y-1) and GPP (856 gC / m-2 y-1) were found in coniferous forests. The lowest NPP (267 gC / m-2 y-1) and GPP (493 gC / m-2 y-1) were detected in mixed forests in the Southeastern Anatolian Transitional Region. The highest CUE value was found in the Black Sea Climatic Region (0.89). Our results showed that the CUE was not a constant value. Although the mean CUE values among forest types were close to each other, significant differences were found between ecoregions. With the findings obtained, it is recommended that the CUE value should be determined under different environmental conditions

The importance of permafrost in the steady and fast increase in net primary production of the grassland on the Qinghai–Tibet Plateau

Permafrost affects soil water and soil temperature regimes; however, its effects on net primary production (NPP) remain unknown. Here, we examined temporal-spatial changes in grassland NPP during 2000–2018 in permafrost and permafrost-free areas on the Qinghai–Tibetan Plateau using the random forest (RF) and radial basis function artificial neural network (RBF-ANN). Our results indicated that the areas that showed increasing, decreasing, and non-significant trends for NPP accounted for 13.88%, 1.90%, and 84.22% of the permafrost area, respectively. For the permafrost-free areas, these NPP trends accounted for 22.25%, 2.68%, and 75.07% of the permafrost-free area, respectively. The mean NPP in the permafrost regions showed a faster and steadier (1.520 g C/m2/yr, p < 0.05) increase than in non-permafrost regions (1.224 g C/m2/yr, p < 0.05). The Biome-BGC model confirmed that these spatial NPP patterns could be attributed to differences in soil water and soil temperature between permafrost and permafrost-free areas. Both the soil temperature and soil water content in permafrost sites exhibited relatively lower variance than in permafrost-free sites. Although many factors may be attributed to these patterns, our results suggest that there is a possibility that the relatively stable change in permafrost NPP can be explained by the fact that permafrost can regulate soil water and temperature regimes. Therefore, climate warming can increase NPP in cold regions, and permafrost degradation may destabilize the grassland ecosystem, which may cause NPP values to exhibit greater interannual changes in the future.

Spatiotemporal variation and driving factors of vegetation net primary productivity in a typical karst area in China from 2000 to 2010

Exploring the spatiotemporal variation in vegetation net primary productivity (NPP) and evaluating the impact of different drivers on NPP are vital for vegetation protection and restoration in Guizhou Province, which is a typical karst area in China. In this study, Cox–Stuart test, linear regression and spatial statistics were used to analyze the spatiotemporal variation in vegetation NPP in Guizhou. Random Forest combined with local spatial autocorrelation analysis was applied to quantify the effects of eight drivers from climate, topography, human activities and vegetation growth status on the NPP from different clusters in different years based on the NPP product from the Global Production Efficiency Model (GLO-PEM). The following results were obtained. (1) The average annual NPP in Guizhou during 2000–2010 showed no significant increasing or decreasing trend. (2) The annual mean NPP in the west was the lowest in the period, but the NPP per year had a rising tendency in the west and a declining one in the east from 2000 to 2010. (3) The NPP in Guizhou showed a significant clustering trend across each year in the period, whereas the clustering degree reflected a downward trend over time. The statistically significant clusters of high values (HH) and clusters of low values (LL) of NPP were mainly distributed in the east and west, respectively, in 2000, 2005 and 2010. (4) The accuracy of the driver analysis of the three NPP cluster types combined (HH + LL, HL + LH, and HH + HL + LH + LL) was higher than that of the other cluster types in Guizhou in 2000, 2005 and 2010. Vegetation growth and human activities show greater effect on the NPP of the three combined types than climate and topography. These findings are valuable in refining the results of the driver analysis and improving their accuracy. This study provides a deeper insight into the effect of different drivers on the NPP from different spatial clusters in Guizhou. Our results indicate that implementing appropriate silvicultural measures and formulating effective management policies are essential to improve the NPP and reduce the adverse effects of human activities on NPP in Guizhou.

The effects of ecological rehabilitation projects on the resilience of an extremely drought-prone desert riparian forest ecosystem in the Tarim River Basin, Xinjiang, China

The Tarim River Basin in Xinjiang, China, has a typical desert riparian forest ecosystem. Analysis of the resilience of this type of ecosystem under extreme drought conditions and ecological rehabilitation projects could provide a theoretical basis for understanding ecosystem stability and resistance, and provide new ecological rehabilitation measures to improve ecosystem resilience. We employed a quantitative framework to assess net primary productivity (NPP) resilience, emphasizing four aspects of NPP dynamics: NPP, NPP stability, NPP resistance, and maximum NPP potential. We compared ecosystem resilience across four time periods: before the implementation of ecological rehabilitation projects (1990–2000), during construction and partial implementation of ecological rehabilitation projects (2001–2012), during the initial project stage of ecological rehabilitation (2013–2015), and during the late project stage of ecological rehabilitation (2016–2018). There are three main finding of this research. (1) Mean NPP was increased significantly from 2013 and was decreased from 2016, especially in the main stream of the Tarim River and in the basins of eight of its nine tributary rivers. (2) Ecosystem resilience in 2013–2018 was greater than in 1990–2012, with the greatest NPP stability, mean NPP and NPP resistance, especially in part one of the river basin (the Aksu River, the Weigan-Kuche River, the Dina River, the Kaidu-Konqi River, and the main stream of the Tarim River). Ecosystem resilience in 2001–2012 was lowest when compared to 1990–2000 and 2013–2018, with lowest mean NPP, NPP stability, NPP resistance and maximum NPP potential, particularly in part two of the river basin (the Kashigr River, the Yarkand River and the Hotan River basins). Therefore, part one was most affected by ecological restoration projects. When 2013–2018 was divided into two distinct stages, 2013–2015 and 2016–2018, resilience in the latter stage was the lowest, with lowest mean NPP, NPP resistance and maximum NPP potential, especially in the main stream of the Tarim River. This may be due to unreasonable water conveyance in 2014–2015. (3) Ecological resilience has increased significantly in 2013–2015 after the implementation of ecological water transfer projects, river regulation, and natural vegetation enclosure projects. Ecosystem resilience could continue to increase even more in the future with the continued implementation of reasonable ecological water transfer projects.