Increase In Net Primary Productivity Research Articles

Optimizing nitrogen fertilization rate to enhance soil carbon storage and decrease nitrogen pollution in paddy ecosystems with simultaneous straw incorporation

Nitrogen fertilization (NF) is an important agricultural management practice that greatly affects soil carbon (C) storage through regulating the balance of soil C input (straw biomass) and output (ecosystem respiration), especially for agroecosystems with simultaneous straw incorporation (SI). However, little is known about how different NF rates affect soil C balance (net ecosystem carbon budget, NECB) in flooded paddy ecosystems with SI. We conducted a two-year field experiment in a typical rice–wheat cropping system in southern China to investigate the response of soil C input (net primary production (NPP) and SI), output (ecosystem respiration and methane emissions), and NECB and N losses under five different NF rates (0/0, 120/90, 180/135, 240/180 and 300/225 kg N ha−1 for the rice/wheat season). Straw harvested from previous cropping season was chopped and fully incorporated into the soil prior to the next season. Our results showed that all treatments had a positive NECB value ranged between 4057–14380 kg C ha−1 yr−1. Compared with the no NF, NF treatments clearly increased the annual NECB by 17.2 %–185 % depending on NF rate. A 20 % reduction relative to the local NF rate (525 kg N ha−1) increased annual crop yield by 4.1 %–6.7 % and NECB by 9.6 %–16.8 %, which was attributed to the increase in NPP (2.6 %–6.2 %) and straw C input (3.8 %–6.1 %), and the decrease in ecosystem respiration (1.8 %–2.1 %) and methane emissions (8.4 %–10.4 %). Moreover, total reactive N losses were significantly decreased by 21 %. However, further reducing the rate by 40 % from local NF rate significantly decreased crop yield by 12.7 %–14.9 % and NECB by 16.7 %–19 %, mainly due to the significant decrease in soil C input through NPP by 14 %–18 % and straw C input by 7.4 %–15.8 % as the inadequate N supply impaired crop growth. Our results suggest that optimizing NF rate is effective in further enhancing soil C storage, decreasing N pollution and sustaining food security in paddy ecosystems with simultaneous SI.

Climate effects on temporal and spatial dynamics of phytoplankton and zooplankton in the Barents Sea

Temporal and spatial dynamics of phytoplankton and zooplankton in the Barents Sea have been investigated during the last three decades using remote sensing and in situ observations. Satellite-derived sea surface temperatures increased in the period 1998–2017 by 1.0 °C as an average for the Barents Sea. We found significant positive relationships between ice-free conditions (open water area and duration) and satellite-based net primary production (NPP). The estimated annual NPP for the Barents Sea more than doubled over the 1998–2017 period, from around 40 to over 100 Tg C. The strong increase in NPP is the result of reduction of sea ice, extending both the area and period available for phytoplankton production. In areas where ice extent has decreased, satellite-derived chlorophyll a shows that the timing of the peak spring phytoplankton bloom has advanced by over a month. Our results reveal that phytoplankton dynamics in the ecosystem have been changing rapidly and that this change is driven mainly by bottom-up climatic processes. Autumn mesozooplankton biomass showed strong interannual variability in the 1990s, displaying an inverse relationship with capelin biomass, the most abundant planktivorous fish. In some regions, e.g. Central Bank, capelin biomass explained up to 50% of the mesozooplankton variability during 1989–2017. Though capelin biomass has varied considerably, mesozooplankton biomass has remained rather stable since the mid-2000s (6–8 g dry wt. m−2), resulting in a weakening of the negative relationship between capelin and mesozooplankton biomass in recent years. The stable zooplankton biomass indicates favorable conditions (prolonged/increased NPP) for mesozooplankton production, partly counteracting high predation levels. Overall, we observed trends in phytoplankton phenology that were strongly associated with changes in sea ice cover driven by fluctuations in temperature regime, a trend that may intensify should the ecosystem become even warmer due to climate change. Further reductions of sea ice and associated ice algae is expected to have adverse effects on sympagic fauna and ice dependent species in the Arctic food web. The ice-free conditions may promote further Atlantification (or borealization) of plankton and fish communities in the Barents Sea.

Simulation of climate change and thinning effects on productivity of Larix olgensis plantations in northeast China using 3-PGmix model

Understanding the effects of thinning on forest productivity under climate change is vital to adaptive forest management. In the present study, the 3-PGmix model was applied to simulate the thinning effects on productivity of Larix olgensis plantations under climate change using 164 sample plots collected from the 6th, 7th and 8th National Forest Inventories in Jilin Province, northeast China. Climate scenarios of RCP 4.5 and RCP 8.5 were adopted from 2011 to 2100 with corresponding reference years (1981–2010). We simulated four cutting intensities: no-thinning, NT; low intensity thinning with 10% stem removal, LT; moderate thinning with 20% stem removal, MT and heavy thinning with 30% stem removal, HT for three times with 5- and 10-year thinning intervals. The results indicated that the mean net primary productivity (NPP) during the simulated 90 years was increased under RCP 4.5 and RCP 8.5. The LT and MT had positive but HT had negative effects on the mean NPP for the same climate scenario. Increased thinning intensity facilitated the positive effects of climate change on NPP but without a significant interaction effect. During the simulation, LT had the highest NPP value and HT had the biggest NPP increase under future climate change. We also discussed the management of larch plantations under climate change and advocated low intensity thinning with 10-year thinning interval to gain maximum NPP for mitigating climate change.

Changes in the food supply capacity of alpine grassland ecosystem: A dialectic synthesis of natural and anthropogenic drivers

Grassland-based animal husbandry and livestock production is the main contributor to livelihood creation for herdsmen. By using the structural dynamics method, this study quantified the changes in the food supply capacity (FSC) of alpine grassland ecosystem and sensitivity to significant variables. The findings indicated that: i) Natural factors were the dominated forces affecting FSC, and their contribution was 71.3%. Of these natural elements, the net primary productivity (NPP) and precipitation were the largest contributors, accounting for approximately 35%. The sensitivity index of the FSC to NPP and precipitation during grassland growing season were 4.1 and 1.9 respectively. On the contrary, human factors like warm shed area, density of road, capacity for access to information, contributed to 28.7% of the total FSC. ii) More intense snow disaster had a larger negative impact on FSC. Snow disaster can cause dramatic reduction in FSC, with a loss rate of 27.6% and with none intense disaster more negative impacts. iii) The continuing increase of FSC in the past 30 years from 1984 to 2014 was due to the significant increase of precipitation and NPP in the growing season of alpine grassland. Evidently, successful adaptation to climate change was critical to combat the climatic adversely impact on FSC. Typically, strengthening information dissemination, road accessibility and knowledge popularization of local residents' disaster reduction should be place high priority for improving FSC.

Afforestation promotes the enhancement of forest LAI and NPP in China

Recent national wide afforestation in China are playing an increasingly significant role in the global greening trend and CO2 mitigation. However, the long term knowledge of spatiotemporal pattern of plantation forests (PF) is essential to understand the continuability and sustainability of the PF contribution and its spatiotemporal pattern comparing to nature forests (NF). Here we combined an inventory based map of PF, three up-to-date remote sensing leaf area index (LAI) datasets, and a process-based terrestrial biogeochemical model to investigate the interannual variabilities (IAVs) and trends of LAI and net primary productivity (NPP) of natural and plantation forests in China, from 1982 to 2014. We found that PF possessed similar spatiotemporal patterns as those of NF, while they exhibited a greater enhancement of both LAI and NPP since 2000. The total proportions of LAI and NPP in the plantation areas increased from 22% to 23.4%, and 22% to 22.8% from 1982 to 2014, respectively. Although different datasets provided diverse rates, an increasing trend was in agreement. The spatially-explicit analysis also illustrated that the increasing proportions were primarily contributed by the Southern sub-regions, particularly the Southwest and South sub-regions, while the PF in Northern sub-regions (e.g., Inner Mongolia and Northeast) even showed a decreasing contribution trend. The quantitative outputs from this study supported that PF promoted the greening trend in China since the 21st century. However, we also argued that the swift increase in LAI and NPP by PF should mainly result from the growing number of tree plantations and the rapid growth of newly planted forests. The proper management of PF is, therefore, an essential task for the maintenance and long-term improvement of their ecosystem services.

Spatial variation of carbon turnover time and carbon uptake in a Chinese desert steppe ecosystem

• The average whole-ecosystem C turnover time was 37.65 years in the desert steppe. • The net primary productivity averaged 131.93 g C m −2 yr −1 from 2000 to 2018. • The potential ecosystem C uptake averaged 28.86 g C m −2 yr −1 in the desert steppe. • The contribution of soil C uptake to total ecosystem C uptake averaged 92.6%. • CTTE value increases from north to south with precipitation and latitude. Quantifying the carbon dynamics in arid and semi-arid ecosystems is a key issue in determining the global carbon budget. Carbon turnover time (CTT) and carbon uptake are the key indicators that determine the C dynamics and the potential C sequestration, but it has not been well quantified in a specific ecosystem. Our study combined a field inventory in a desert steppe ecosystem with data synthesis and the Terrestrial Ecosystem Regional model (TECO-R) for desert steppes to invert the key parameters of the ecosystem’s carbon cycle. The average CTT in the leaf, root, and soil carbon pools (to a depth of 50 cm) and for the whole ecosystem was 1.43, 10.1, 76.96, and 37.65 years, respectively. The study area’s net primary productivity (NPP) averaged 131.93 g C m −2 yr −1 from 2000 to 2018 based on the Carnegie-Ames-Stanford approach, and the ecosystem C uptake averaged 28.86 g C m −2 yr −1 , driven by an increasing NPP trend. The whole-ecosystem CTT ( CTTE ) increased significantly, by about 6 years per 25-mm increase in precipitation, 0.45° increase in latitude, 1000-g increase in SOC, and 50-g C m −2 yr −1 increase in NPP. The threshold temperature for CTT in the desert steppe was around 6 °C. CTTE was significantly negatively correlated with temperature above this temperature, but below this value is the opposite. However, the pattern of ecosystem potential C uptake was affected by climate, NPP, and the intensity of human activities, with no clearly dominant factor. These analyses of the desert steppe’s carbon cycle will help to improve the assessment of dryland carbon dynamics and global carbon budgets.

The effects of climate factors and human activities on net primary productivity in Xinjiang.

Net primary productivity (NPP) is an index of the increase in plant biomass. Plant biomass is an important component of the global carbon cycle that indicates the health of an ecosystem. Environmental restoration has recently received much attention in Xinjiang, and it is thus important to quantify the dynamic effects of the drivers of NPP in the region. NPP was calculated for the annual growing season from 1982 to 2013 using the Carnegie-Ames-Stanford Approach (CASA) model. The effects of climate factors on NPP were analyzed, and the relationships between NPP and climate factors as well as human activity were quantified. Additionally, an innovative method based on partial derivatives and residual error was proposed to calculate the contributions of climate factors and human activities. The results show that average annual NPP in Xinjiang was 57.45gCm-2 from 1982 to 2013 and that the average increase in annual NPP was 0.23gCm-2year-1. The average increases in annual NPP due to temperature, precipitation, and solar radiation were 0.0095, 0.2679, and 0.2541gCm-2year-1; the average decreases were respectively - 0.0133, - 0.0521, and - 0.0725gCm-2year-1. Precipitation and solar radiation influence NPP more than temperature. Precipitation had the greatest effect on NPP in the first 19years, but solar radiation became more influential after 2000. Climate conditions were favorable for increase in NPP before 2000. The environmental restoration also occurred in Xinjiang during that period, and human activity slightly decreased NPP. Human activity increased and had a greater effect on NPP after 2000.

Spatial and temporal change patterns of net primary productivity and its response to climate change in the Qinghai-Tibet Plateau of China from 2000 to 2015

The vegetation ecosystem of the Qinghai-Tibet Plateau in China, considered to be the “natural laboratory” of climate change in the world, has undergone profound changes under the stress of global change. Herein, we analyzed and discussed the spatial-temporal change patterns and the driving mechanisms of net primary productivity (NPP) in the Qinghai-Tibet Plateau from 2000 to 2015 based on the gravity center and correlation coefficient models. Subsequently, we quantitatively distinguished the relative effects of climate change (such as precipitation, temperature and evapotranspiration) and human activities (such as grazing and ecological construction) on the NPP changes using scenario analysis and Miami model based on the MOD17A3 and meteorological data. The average annual NPP in the Qinghai-Tibet Plateau showed a decreasing trend from the southeast to the northwest during 2000–2015. With respect to the inter-annual changes, the average annual NPP exhibited a fluctuating upward trend from 2000 to 2015, with a steep increase observed in 2005 and a high fluctuation observed from 2005 to 2015. In the Qinghai-Tibet Plateau, the regions with the increase in NPP (change rate higher than 10%) were mainly concentrated in the Three-River Source Region, the northern Hengduan Mountains, the middle and lower reaches of the Yarlung Zangbo River, and the eastern parts of the North Tibet Plateau, whereas the regions with the decrease in NPP (change rate lower than −10%) were mainly concentrated in the upper reaches of the Yarlung Zangbo River and the Ali Plateau. The gravity center of NPP in the Qinghai-Tibet Plateau has moved southwestward during 2000–2015, indicating that the increment and growth rate of NPP in the southwestern part is greater than those of NPP in the northeastern part. Further, a significant correlation was observed between NPP and climate factors in the Qinghai-Tibet Plateau. The regions exhibiting a significant correlation between NPP and precipitation were mainly located in the central and eastern Qinghai-Tibet Plateau, and the regions exhibiting a significant correlation between NPP and temperature were mainly located in the southern and eastern Qinghai-Tibet Plateau. Furthermore, the relative effects of climate change and human activities on the NPP changes in the Qinghai-Tibet Plateau exhibited significant spatial differences in three types of zones, i.e., the climate change-dominant zone, the human activity-dominant zone, and the climate change and human activity interaction zone. These research results can provide theoretical and methodological supports to reveal the driving mechanisms of the regional ecosystems to the global change in the Qinghai-Tibet Plateau.

Changes in the trends of vegetation net primary productivity in China between 1982 and 2015

China has been experiencing significant climate and land use changes over the past decades. The way in which these changes, particularly a warming hiatus and national ecological restoration projects that occurred almost concurrently in the late 1990s, have influenced vegetation net primary productivity (NPP), is not well documented. Here, we estimated annual and seasonal changes in China’s NPP between 1982 and 2015 using the Carnegie-Ames-Stanford Approach model and examined their shifting years (SHYs) caused by the switch in climatic factors and the restoration projects. Our analyses revealed that the growth of annual, spring and summer NPP stalled in 1997 or 1998, while the trend of autumn NPP increased in 1992 at the national scale. We also showed that the changes in the NPP trends were more sensitive to the warming hiatus in spring and autumn, as well as in the temperate monsoonal region and the Tibetan Plateau, while the larger trend of autumn NPP in eastern China after the SHY was strongly coupled with increased monsoonal precipitation. Although the starting years of the restoration projects were partially consistent with the SHYs of the NPP trends, the projects were likely playing minor roles in enhancing NPP increase. Our findings can be applied for ecological risk assessment and future management of ecological restoration projects in the context of global change.

Contrasting policy shifts influence the pattern of vegetation production and C sequestration over pasture systems: A regional-scale comparison in Temperate Eurasian Steppe

Socio-economical conditions profoundly influence terrestrial ecosystems, especially the agroecosystems. However, the effects of large-scale “top-down” socio-economical changes on patterns of vegetation production and C sequestration in pastures remain largely unclear. The contrasting institutional and policy shifts in 1990s over the two sub-region of Temperate Eurasian Steppe (TES), i.e., the Kazakh Steppe (KS) and the Mongol Steppe (MS), provide a unique opportunity to illustrate the human and natural interactions. Combining multiple information from remote sensing, land model, climate and inventory data, this study investigated how the regional trend and inter-annual variability (IAV) of leaf area index (LAI), net primary productivity (NPP), net ecosystem productivity (NEP) were associated with different institutional and policy shifts. From 1997 to 2016, climate is the primary control factor to the IAV of the ecosystem indexes (EIs, i.e., LAI, NPP, NEP) at a regional view. Highly contrasting impacts of human appropriation indexes (HAIs, i.e., livestock number and agricultural GDP) to the EIs were found for the two sub-region. The effect of HAIs on EIs was weak in the MS, but significant negative correlations between HAIs and EIs were found in the KS. Further decomposition into administrative divisions showed that the swift rise of human appropriation in China was accompanied with increases in grassland NPP and NEP, owing to the policy shift to sustainable management. But the institutional shift to market-driven economy and increasing human appropriation generally acted as a negative factor to EIs in various countries over the KS, especially in Uzbekistan and Turkmenistan. Regional evidences revealed the importance of large-scale socio-economic shifts in shaping the pattern of important ecosystem properties of grasslands and emphasized the importance of sustainability development in managing pasture systems.

Roles of Climate Change and Increasing CO2 in Driving Changes of Net Primary Productivity in China Simulated Using a Dynamic Global Vegetation Model

Net primary productivity (NPP) is the key component of the terrestrial carbon cycle, and terrestrial NPP trends under increasing CO2 and climate change in the past and future are of great significance in the study of the global carbon budget. Here, the LPJ-DGVM was employed to simulate the magnitude and pattern of China’s terrestrial NPP using long-term series data to understand the response of terrestrial NPP to increasing CO2 concentration and climate change. The results showed that total NPP of China’s terrestrial ecosystem increased from 2.8 to 3.6 Pg C yr−1 over the period of 1961–2016, with an annual average of 3.1 Pg C yr−1. The average NPP showed a gradient decrease from the southeast to northwest. Southwest China and Northwest China, comprising mostly arid and semi-arid regions, exhibited the largest increase rate in total NPP among the six geographical regions of China. Additionally, large interannual variability around the NPP trends was presented, and NPP anomalies in China’s terrestrial ecosystem are strongly associated with the El Niño-Southern Oscillation (ENSO). Southwest China made the largest contribution to the interannual variability of national total NPP. The total NPP of China’s terrestrial ecosystem continuously increased with the concurrent increase in the CO2 concentration and climate change under different scenarios in the future. During the period from 2091 to 2100, the average total NPP under the A2 and RCP85 scenarios would reach 4.9 and 5.1 Pg C yr−1 respectively, higher than 4.2 and 3.9 Pg C yr−1 under the B1 and RCP45 scenarios. Forests, especially temperate forests, make the largest contribution to the future increase in NPP. The increase in CO2 concentration would play a dominant role in driving further NPP increase in China’s terrestrial ecosystems, and climate change may slightly attenuate the fertilization effect of CO2 on NPP.

Dynamic trend of land degradation/restoration along Indira Gandhi Canal command area in Jaisalmer District, Rajasthan, India: a case study

Land cover is a crucial component in assessment of biodiversity and ecosystem services. In arid regions, land cover is mostly composed of aeolian structures which exhibit fragile environmental scenario. The major challenge in this highly dynamic landscape was conversion of desertic land to intensive land use such as agricultural farmlands. To overcome this challenge Indira Gandhi Canal (IGC) and its branches were extended over this district. The main interest of this research was to investigate net primary productivity (NPP) changes using multi-temporal satellite imagery and meteorological datasets within the timeframe of 30 years from 1982 to 2012 over this region. This study was taken up to assess the impact of canal in and around IGC command area in Jaisalmer District to understand the consequence on desertic environment. Analysis of three decades terrestrial NPP over IGC command area in Jaisalmer District, India, shows significant increase in NPP. The satellite data-based analysis of NPP as well as validation with the optical data in the study region revealed that this increasing trend in NPP is basically associated to increase in canal networks. The water supply from the canal gradually led to expansion of irrigation in the agricultural fields leading to change in dynamics of the area. This systematic and long-term NPP analysis will be useful to strengthen our understanding for the role of regional land cover types and impact of their change in the national and global carbon cycle for understanding land degradation and desertification scenario in the study area.

Response of net primary productivity to vegetation restoration in Chinese Loess Plateau during 1986-2015.

Land use and land cover change induced by large scale ecological restoration programs has a significant impact on the terrestrial ecosystem carbon cycle, especially on the net primary productivity (NPP) in arid and semi-arid regions. This study investigated the change in NPP caused by the large-scale ecological restoration in the Chinese Loess Plateau (LPR) region from 1986 to 2015 based on land cover datasets and NPP calculated using the Carnegie-Ames-Stanford Approach model. The results indicated that the annual total NPP exhibited a significant uptrend (P < 0.01) throughout the whole vegetation restoration region during the last 30 years, with an annual increase of 0.137 Tg C. A significant abrupt change was detected in 2006 for the annual total NPP series. Over half of the restoration region showed an increase in NPP in the past three decades, however, about 30~40% of the vegetation restoration region exhibited NPP loss before 2006, but subsequently NPP loss was found in only approximately 20% of the study region. Overall, the increase in NPP attributed to the vegetation restoration reached 51.14 Tg C in the past three decades, indicating that these large-scale vegetation restoration programs increased the carbon sequestration capacity of terrestrial ecosystems in the Loess Plateau. The findings of this study improve our understanding of the effects of the green campaign on terrestrial ecosystems.

Measured estimates of semi-natural terrestrial NPP in Great Britain: comparison with modelled values, and dependence on atmospheric nitrogen deposition

Plant growth in nitrogen (N)-limited, unfertilised terrestrial ecosystems should respond to additional N inputs from atmospheric deposition (Ndep). We investigated this for sites in Great Britain (GB) by compiling 796 estimates of net primary productivity (NPP) from measured biomass production over the period 1932–2014, although the great majority were for 1990 onwards. The sites were largely vegetated with shrubs, grass and bracken, and had a wide range of Ndep (0.5–3.3 gN m−2 a−1 in 2000). The measured NPP estimates were compared with calculated values from the biogeochemical ecosystem model N14CP, which predicts that NPP depends strongly upon Ndep. The measured and modelled average total NPP values (gC m−2 a−1) from all data were 387 (standard deviation, SD = 193) and 377 (SD = 72) respectively. Measured and modelled averages for vegetation classes followed the sequence: broadleaved trees ~ needle-leaved trees > herbs (rough grassland + bracken) ~ shrubs. After averaging measured values for sites in individual model grid cells (5 km × 5 km) with 10 or more replicates, the measured and modelled NPP values were correlated (n = 26, r2 = 0.22, p = 0.011), with a slope close to unity. Significant linear relationships were found between measured ln NPP and cumulative Ndep for both herbs (n = 298, p = 0.021) and shrubs (n = 473, p = 0.006), with slopes comparable to those predicted with the model. The results suggest that semi-natural NPP in GB depends positively upon Ndep, in a manner that agrees quantitatively with N14CP predictions. Calculations with the model, using modelled temporal variation in Ndep, indicate that fertilisation by Ndep caused average increases in semi-natural NPP over the period 1800 to 2010 of 30% for shrubs, 71% for herbs, and 91% for broadleaved trees. Combined with previous published results for forests, our findings suggest a general and widespread vegetation response to fertilisation by Ndep.

Changes in vegetation and surface water balance at basin-scale in Central China with rising atmospheric CO2

Elevated atmospheric CO2 concentration alters vegetation growth and composition, increases plant water use efficiency (WUE), and changes surface water balance. These changes and their differences between wet and dry climate are studied at a mid-latitude experiment site in the Loess Plateau of China. The study site, the Jinghe River basin (JRB), covers an area of 43,216 km2 and has a semiarid climate in the north and a semi-humid climate in the south. Two simulations from 1965 to 2012 are made using a site-calibrated Lund–Potsdam–Jena dynamic global vegetation model: one with the observed rise of the atmospheric CO2 from 319.7–391.2 ppmv, and the other with a fixed CO2 at the level of 1964 (318.9 ppmv). Analyses of the model results show that the elevated atmospheric CO2 promotes growth of woody vegetation (trees) and causes a 6.0% increase in basin-wide net primary production (NPP). The NPP increase uses little extra water however because of higher WUE. Further examination of the surface water budget reveals opposite CO2 effects between semiarid and semi-humid climates in the JRB. In the semiarid climate, plants sustain growth in higher CO2 because of the higher level of intracellular CO2 and therefore WUE, thus consuming more water and causing a greater decrease of surface runoff than in the fixed-lower CO2 case. In the semi-humid climate, NPP also increases but by a smaller amount than in the semiarid climate. Plant transpiration (ET) and total evapotranspiration (E) decrease in the elevated CO2 environment, yielding the increase of runoff. This asymmetry of the effects of elevated atmospheric CO2 exacerbates drying in the semiarid climate and enhances wetness in the semi-humid climate. Furthermore, plant WUE (=NPP/ET) is found to be nearly invariant to climate but primarily a function of the atmospheric CO2 concentration, a result suggesting a strong constraint of atmospheric CO2 on biophysical properties of the Earth system.

Global vegetation distribution driving factors in two Dynamic Global Vegetation Models of contrasting complexities

Abstract This study compares the dynamic vegetation response in two Dynamic Global Vegetation Models (DGVMs) with contrasting processes complexity to changes in climate and atmospheric CO2. We consider observed pre-industrial climates and four different simulated climate change states relative to preindustrial conditions: the mid-Holocene (6 ka), the pre-industrial state with halved CO2 levels (140 ppm), doubled CO2 (560 ppm), and quadrupled CO2 (1120 ppm). The two DVGMs are LPJ-GUESS and VECODE. The input climate is derived from an earth system model of intermediate complexity (iLOVECLIM). We evaluate the sensitivities of these two DGVMs to changing climate and CO2 levels and assess the impact of their respective complexity on these sensitivities. Our results show that both DGVMs yield results consistent with the broad features of pre-industrial vegetation dynamics and changes in vegetation from mid-Holocene to pre-industrial. They also agree with the patterns of vegetation responses to the more extreme varying CO2 scenarios, yet with stronger magnitudes in LPJ-GUESS than in VECODE; in particular, large uncertainties are associated with the response of tropical vegetation to varying CO2 levels. LPJ-GUESS simulates stronger positive responses of global net primary production (NPP) to elevated CO2 levels than VECODE, particularly in tropical regions. The increase in global NPP differs by 8% between the two DGVMs under 2*CO2 scenarios. Also, LPJ-GUESS simulates tropical vegetation sensitivities, defined here as the changes in tree-cover per degree of temperature anomaly, varying from 0.5 (°C−1), 0.25 (°C−1) to 0.15 (°C−1) under ½*CO2, 2*CO2, and 4*CO2 scenarios. In VECODE these values are around 0.05 (°C−1) for all scenarios. The higher sensitivity of LPJ-GUESS to CO2 concentration levels is likely related to the inclusion of more detailed ecophysiological processes. The two DGVMs' different complexity of eco-physiological processes also impacts on vegetation requirements for rainfall due to the physiological effects that more efficient water use of vegetation is facilitated under elevated atmospheric CO2 concentration. The sensitivity of global Leaf Area Index (LAI) in the two DGVMs decreases with the increasing atmospheric CO2 from pre-industrial level to 4*CO2 scenario. The uncertainties of vegetation simulations are mainly contributed by the tropical vegetation response to climate and CO2 concentration due to the inclusion of ecosystem processes in both DGVMs and the scheme of vegetation classification. Based on our results, we recommend to use a standard set of vegetation types and to set up systematic simulations detecting the range of vegetation sensitivity to varying CO2 and climate forcing when inter-comparing different DGVMs.

Spatiotemporal variation of productivity and carbon use efficiency of forests in Northeast China from 2000 to 2015.

Understanding changes in vegetation productivity and carbon use efficiency and their responses to climate change is significant to accurately assess and predict regional carbon budget in Northeast forest area, a region being an important carbon sink and sensitive to global change. Based on MODIS monitoring data and vegetation type distribution data, I analyzed the spatiotemporal varia-tions of ecosystem productivity (net primary productivity (NPP), gross primary productivity (GPP)) and carbon use efficiency (NPP/GPP) of Northeast forest from 2000 to 2015. Results showed that the average NPP and GPP were 346.4 and 773 g C·m-2·a-1, respectively, and the average NPP/GPP was 0.45 during 2000 and 2015. NPP and GPP of different forest types were following the order: coniferous and broad-leaved mixed forests > deciduous broad-leaved forests > coniferous forests, while the difference in NPP/GPP was not significant among different forest types. NPP and GPP were high in Southeast part and low in Northwest part. From 2000 to 2015, the NPP, GPP and NPP/GPP of Northeast forest showed a fluctuating increase, suggesting the carbon sequestration capacity was gradually enhanced. However, the trends and rates of NPP, GPP and NPP/GPP showed spatial variation. NPP, GPP and NPP/GPP increased significantly in the southern part of the Daxing'anling while decreased significantly in the northern part of the Daxing'anling, and showed a weak increasing trend in the rest of Northeast forest. The increase of annual precipitation was the main factor driving the fluctuating increase of NPP, GPP and NPP/GPP in Northeast forest.

Response of net primary production to land use and climate changes in the middle-reaches of the Heihe River Basin.

Net primary production (NPP) supplies matter, energy, and services to facilitate the sustainable development of human society and ecosystem. The response mechanism of NPP to land use and climate changes is essential for food security and biodiversity conservation but lacks a comprehensive understanding, especially in arid and semi‐arid regions. To this end, taking the middle‐reaches of the Heihe River Basin (MHRB) as an example, we uncovered the NPP responses to land use and climate changes by integrating multisource data (e.g., MOD17A3 NPP, land use, temperature, and precipitation) and multiple methods. The results showed that (a) land use intensity (LUI) increased, and climate warming and wetting promoted NPP. From 2000 to 2014, the LUI, temperature, and precipitation of MHRB increased by 1.46, 0.58°C, and 15.76 mm, respectively, resulting in an increase of 14.62 gC/m2 in annual average NPP. (b) The conversion of low‐yield cropland to forest and grassland increased NPP. Although the widespread conversion of unused land and grassland to cropland boosted both LUI and NPP, it was not conducive to ecosystem sustainability and stability due to huge water consumption and human‐appropriated NPP. Urban sprawl occupied cropland, forest, and grassland and reduced NPP. (c) Increase in temperature and precipitation generally improved NPP. The temperature decreasing <1.2°C also promoted the NPP of hardy vegetation due to the simultaneous precipitation increase. However, warming‐induced water stress compromised the NPP in arid sparse grassland and deserts. Cropland had greater NPP and NPP increase than natural vegetation due to the irrigation, fertilizers, and other artificial inputs it received. The decrease in both temperature and precipitation generally reduced NPP, but the NPP in the well‐protection or less‐disturbance areas still increased slightly.

Determining the impacts of climate change and urban expansion on terrestrial net primary production in China

Climate change and urbanization strongly affect the variations of terrestrial net primary production (NPP), but the relative contributions of these two factors to NPP changes have not been determined yet (especially on a macroscale). In this study, spatial-temporal variations of NPP in China from 2000 to 2010 were estimated using the Carnegie−Ames−Stanford Approach model, and the effects induced by urbanization and climate change were quantified. The obtained results showed that during the study period, the NPP in China exhibited an annual increase of 0.03 Pg C accompanied by large spatial heterogeneities. During the whole study period, the urban area in China increased by 16.44 × 103 km2, and the corresponding NPP losses amounted to 11.60 × 10−3 Pg C. Urban expansion significantly offset the climate change-induced NPP increases and worsened NPP decreases (the offsetting ratio calculated for China was 5.42%, and its exact magnitudes varied by province). The largest NPP variations were observed over the regions with rapid urban expansion, whose contribution ratio was 32.20% for China and exceeded 30% for most provinces. Climate change contributed considerably to the NPP variations in both the newly urbanized (30.45%) and purely vegetated (46.92%) areas, but its contribution ratios were slightly lower than those of residual factors. Moreover, climate change strongly affected the NPP levels over the arid and semi-arid regions as well as over the Tibet Plateau; however, residual factors dominated the NPP variations over the central and southeast China. Our study highlights a significant role of urbanization in driving terrestrial NPP variations on a macroscale and provides a new perspective on disentangling the impacts of external factors on NPP values.

近16年青海高原植被NPP时空格局变化及气候与人为因素的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 近16年青海高原植被NPP时空格局变化及气候与人为因素的影响 DOI: 10.5846/stxb201707151286 作者: 作者单位: 中南大学地球科学与信息物理学院,中南大学地球科学与信息物理学院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41171326，41201386） Spatial-temporal change in vegetation Net Primary Productivity and its response to climate and human activities in Qinghai Plateau in the past 16 years Author: Affiliation: School of Geosciences and Info-physics in Central South University,School of Geosciences and Info-physics in Central South University Fund Project: National Natural Science Foundation of China, No. 41171326 ; No. 41201386 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:采用2000-2015年MOD13Q1-16天合成的250 m分辨率NDVI时序数据，基于CASA改进模型估算了青海高原植被NPP，分析了近16年来植被NPP时空变化的特征与规律及其对气候因素变化的响应，并探讨不同区域生态保护工程建设的成效。研究结果表明：①青海高原植被NPP多年平均值242.50 gC m-2 a-1，空间上呈东高西低，南高北低，由西北向东南逐渐递增分布趋势；②2000-2015年，研究区年NPP分布在53.24-96.56 TgC，呈平稳增加，年增长率1.32 TgC/a；③气候的暖湿化是植被NPP增加的主要因素，降水、气温的耦合作用是青海高原植被NPP年际波动的重要因素，不同区域植被NPP受控因子存在差异；④不同生态保护工程的实施，对区域NPP时空格局及变化趋势存在不同程度的影响。其中，三江源地区年NPP上升趋势最为明显，环青海湖地区、东部地区次之，柴达木地区是最缓慢的地区。 Abstract:Based on MOD13Q1-250-m resolution-16-day synthesis NDVI data for the Qinghai Plateau from 2000 to 2015, by using the improved CASA model, we estimated the vegetation net primary productivity (NPP) of the Qinghai Plateau, analyzed the characteristics and regularities of NPP spatial-temporal variation, evaluated the correlation between NPP and meteorological factors, and explored the ecological effect of ecological protection project in different regions. The results indicate the following:① The average annual NPP in the Qinghai Plateau is 242.50 g C m-2 a-1, which is high in the east and south and increases from northwest to southeast. ② During 2000-2015, the annual amount of NPP increased stably from 53.24 to 96.56 Tg C, with an annual growth rate of 1.32 Tg C/a. ③ The warm and humid climate is the main factor affecting the increase in vegetation NPP, and precipitation and temperature are significant factors in the inter-annual fluctuation of NPP in the Qinghai Plateau. Additionally, in different areas, the factors controlling NPP growth differed. ④ The implementation of different ecological protection projects has a varying influence on spatial-temporal patterns and inter-annual trends in regional NPP. Among them, the annual increasing trend in NPP in the Sanjiangyuan region was the most obvious, followed by the Qinghai Lake area, Eastern region, and Qaidam region. 参考文献 相似文献 引证文献