Understanding the net primary productivity(NPP) of grassland is crucial to evaluate the terrestrial carbon cycle. In this study, we investigated the spatial distribution and the area of global grassland across the glo...Understanding the net primary productivity(NPP) of grassland is crucial to evaluate the terrestrial carbon cycle. In this study, we investigated the spatial distribution and the area of global grassland across the globe. Then, we used the Carnegie-Ames-Stanford Approach(CASA) model to estimate global grassland NPP and explore the spatio-temporal variations of grassland NPP in response to climate change from 1982 to 2008. Results showed that the largest area of grassland distribution during the study period was in Asia(1737.23 × 104 km^2), while the grassland area in Europe was relatively small(202.83 × 10~4 km^2). Temporally, the total NPP increased with fluctuations from 1982 to 2008, with an annual increase rate of 0.03 Pg C/yr. The total NPP experienced a significant increasing trend from 1982 to 1995, while a decreasing trend was observed from 1996 to 2008. Spatially, the grassland NPP in South America and Africa were higher than the other regions, largely as a result of these regions are under warm and wet climatic conditions. The highest mean NPP was recorded for savannas(560.10 g C/(m^2·yr)), whereas the lowest was observed in open shrublands with an average NPP of 162.53 g C/(m^2·yr). The relationship between grassland NPP and annual mean temperature and annual precipitation(AMT, AP, respectively) varies with changes in AP, which indicates that, grassland NPP is more sensitive to precipitation than temperature.展开更多
This research classified vegetation types and evaluated net primary productivity (NPP) of southern China's grasslands based on the improved comprehensive and sequential classification system (CSCS), and proposed ...This research classified vegetation types and evaluated net primary productivity (NPP) of southern China's grasslands based on the improved comprehensive and sequential classification system (CSCS), and proposed 5 thermal grades and 6 humidity grades. Four classes of grasslands vegetation were recognized by improved CSCS, namely, tundra grassland class, typical grassland class, mixed grassland class and alpine grassland class. At the type level, 14 types of vegetations (9 grasslands and 5 forests) were classified. The NPP had a trend to decrease from east to west and south to north, and the annual mean NPP was estimated to be 656.3 g C m-2 yr-1. The NPP value of alpine grassland class was relatively high, generally more than 1200 g C m2 yr-1. The NPP value of mixed grassland class was in a range from 1 000 to 1200 g C m-2 yr-1. Tundra grassland class was located in southeastern Tibet with high elevation, and its NPP value was the lowest (〈600 g C m'2yrl). The typical grassland class distributed in most of the area, and its NPP value was generally from 600 to 1000 g C m-2 yr-1. The total NPP value in the study area was 68.46 Tg C. The NPP value of typical grassland class was the highest (48.44 Tg C), and mixed grassland class was the second (16.54 Tg C), followed by alpine grassland class (3.22 Tg C), with tundra grassland class being the lowest (0.25 Tg C). For all the grasslands types, the total NPP of forest meadow was the highest (34.81 Tg C), followed by sparse forest brush (16.54 Tg C), and montane meadow was the lowest (0.01 Tg C).展开更多
Grazing is a main human activity in the grasslands of Xinjiang, China. It is vital to identify the effects of grazing on the sustainable utilization of local grasslands. However, the effects of grazing on net primary ...Grazing is a main human activity in the grasslands of Xinjiang, China. It is vital to identify the effects of grazing on the sustainable utilization of local grasslands. However, the effects of grazing on net primary productivity (NPP), evapotranspiration (ET) and water use efficiency (WUE) in this region remain unclear. Using the spatial Biome-BGC grazing model, we explored the effects of grazing on NPP, ET and WUE across the different regions and grassland types in Xinjiang during 1979-2012. NPP, ET and WUE under the grazed scenario were generally lower than those under the ungrazed scenario, and the differences showed increasing trends over time. The decreases in NPP, ET and WUE varied significantly among the regions and grassland types. NPP decreased as follows: among the regions, Northern Xinjiang (16.60 g C/(m2·a)), Tianshan Mountains (15.94 g C/(m2·a)) and Southern Xinjiang (-3.54 g C/(m2·a)); and among the grassland types, typical grasslands (25.70 g C/(m2·a)), swamp meadows (25.26 g C/(m2·a)), mid-mountain meadows (23.39 g C/(m2·a)), alpine meadows (6.33 g C/(m2·a)), desert grasslands (5.82 g C/(m2·a)) and saline meadows (2.90 g C/(me.a)). ET decreased as follows: among the regions, Tianshan Mountains (28.95 mm/a), Northern Xinjiang (8.11 mm/a) and Southern Xinjiang (7.57 mm/a); and among the grassland types, mid-mountain meadows (29.30 mm/a), swamp meadows (25.07 mm·a), typical grasslands (24.56 mm/a), alpine meadows (20.69 mm/a), desert grasslands (11.06 mm/a) and saline meadows (3.44 mm/a). WUE decreased as follows: among the regions, Northern Xinjiang (0.053 g C/kg H2O), Tianshan Mountains (0.034 g C/kg H2O) and Southern Xinjiang (0.012 g C/kg H2O); and among the grassland types, typical grasslands (0.0609 g C/kg H2O), swamp meadows (0.0548 g C/kg H2O), mid-mountain meadows (0.0501 g C/kg H2O), desert grasslands (0.0172 g C/kg H2O), alpine meadows (0.0121 g C/kg H2O) and saline meadows (0.0067 g C/kg H2O). In general, the decreases in NPP and WUE were more significant in the regions with relatively high levels of vegetation growth because of the high grazing intensity in these regions. The decreases in ET were significant in mountainous areas due to the terrain and high grazing intensity.展开更多
Using the large-scale thick 4# coal seam from the Mid-Jurassic in the southern Ordos Basin as an example, this paper studied the net primary productivity(NPP) level of the Mid-Jurassic peatland, and discussed its cont...Using the large-scale thick 4# coal seam from the Mid-Jurassic in the southern Ordos Basin as an example, this paper studied the net primary productivity(NPP) level of the Mid-Jurassic peatland, and discussed its control factors. Geophysical logging signals were used for a spectrum analysis to obtain the Milankovitch cycle parameters in coal seam. These were then used to calculate the accumulation rate of the residual carbon in 4# coal seam. The carbon loss can be calculated according to the density and residual carbon content of 4# coal seam. Then, the total carbon accumulation rate of the peatland was further derived, and the NPP of peatland was determined. The results show that the NPP of MidJurassic peatland is higher than that of Holocene at the same latitude. Comprehensive analysis indicates that the temperature, carbon dioxide and oxygen levels in atmosphere are the main control factors of the NPP of Mid-Jurassic peatland.展开更多
Background:Net primary productivity(NPP)in forests plays an important role in the global carbon cycle.However,it is not well known about the increase rate of China’s forest NPP,and there are different opinions about ...Background:Net primary productivity(NPP)in forests plays an important role in the global carbon cycle.However,it is not well known about the increase rate of China’s forest NPP,and there are different opinions about the key factors controlling the variability of forest NPP.Methods:This paper established a statistics-based multiple regression model to estimate forest NPP,using the observed NPP,meteorological and remote sensing data in five major forest ecosystems.The fluctuation values of NPP and environment variables were extracted to identify the key variables influencing the variation of forest NPP by correlation analysis.Results:The long-term trends and annual fluctuations of forest NPP between 2000 and 2018 were examined.The results showed a significant increase in forest NPP for all five forest ecosystems,with an average rise of 5.2 gC·m-2·year-1 over China.Over 90%of the forest area had an increasing NPP range of 0-161 gC·m-2·year-1.Forest NPP had an interannual fluctuation of 50-269 gC.m-2·year-1 for the five major forest ecosystems.The evergreen broadleaf forest had the largest fluctuation.The variability in forest NPP was caused mainly by variations in precipitation,then by temperature fluctuations.Conclusions:All five forest ecosystems in China exhibited a significant increasing NPP along with annual fluctuations evidently during 2000-2018.The variations in China’s forest NPP were controlled mainly by changes in precipitation.展开更多
Changes in the sizes of precipitation events in the context of global climate change may have profound impacts on ecosystem productivity in arid and semiarid grasslands. However, we still have little knowledge about t...Changes in the sizes of precipitation events in the context of global climate change may have profound impacts on ecosystem productivity in arid and semiarid grasslands. However, we still have little knowledge about to what extent grassland productivity will respond to an individual precipitation event. In this study, we quantified the duration, the maximum, and the time-integrated amount of the response of daily gross primary productivity (GPP) to an individual precipitation event and their variations with different sizes of precipitation events in a typical temperate steppe in Inner Mongolia, China. Results showed that the duration of GPP-response (τ<sub>R</sub>) and the maximum absolute GPP-response (GPP<sub>max</sub>) increased linearly with the sizes of precipitation events (P<sub>es</sub>), driving a corresponding increase in time-integrated amount of the GPP-response (GPP<sub>total</sub>) because variations of GPPtotal were largely explained by τ<sub>R</sub> and GPP<sub>max</sub>. The relative contributions of these two parameters to GPP<sub>total</sub> were strongly P<sub>es</sub>-dependent. The GPP<sub>max</sub> contributed more to the variations of GPP<sub>total</sub> when P<sub>es</sub> was relatively small (<20 mm), whereas τ<sub>R</sub> was the main driver to the variations of GPP<sub>total</sub> when P<sub>es</sub> was relatively large. In addition, a threshold size of at least 5 mm of precipitation was required to induce a GPP-response for the temperate steppe in this study. Our work has important implications for the modeling community to obtain an advanced understanding of productivity-response of grassland ecosystems to altered precipitation regimes.展开更多
It is necessary to quantitatively study the relationship between climate and human factors on net primary productivity(NPP)inorder to understand the driving mechanism of NPP and prevent desertification.This study inve...It is necessary to quantitatively study the relationship between climate and human factors on net primary productivity(NPP)inorder to understand the driving mechanism of NPP and prevent desertification.This study investigated the spatial and temporal differentiation features of actual net primary productivity(ANPP)in the Ili River Basin,a transboundary river between China and Kazakhstan,as well as the proportional contributions of climate and human causes to ANPP variation.Additionally,we analyzed the pixel-scale relationship between ANPP and significant climatic parameters.ANPP in the Ili River Basin increased from 2001 to 2020 and was lower in the northeast and higher in the southwest;furthermore,it was distributed in a ring around the Tianshan Mountains.In the vegetation improvement zone,human activities were the dominant driving force,whereas in the degraded zone,climate change was the primary major driving force.The correlation coefficients of ANPP with precipitation and temperature were 0.322 and 0.098,respectively.In most areas,there was a positive relationship between vegetation change,temperature and precipitation.During 2001 to 2020,the basin’s climatic change trend was warm and humid,which promoted vegetation growth.One of the driving factors in the vegetation improvement area was moderate grazing by livestock.展开更多
Individual coal seams formed in paleo-peatlands represent sustained periods of terrestrial carbon accumulation and a key environmental indicator attributed to this record is the rate of carbon accumulation.Determining...Individual coal seams formed in paleo-peatlands represent sustained periods of terrestrial carbon accumulation and a key environmental indicator attributed to this record is the rate of carbon accumulation.Determining the rate of carbon accumulation requires a measure of time contained within the coal.This study aimed to determine this rate via the identification of Milankovitch orbital cycles in the coals.The geophysical log is an ideal paleoclimate proxy and has been widely used in the study of sedimentary records using spectral analysis.Spectral analyses of geophysical log from thick coal seams can be used to identify the Milankovitch cycles and to calculate the period of the coal deposition.By considering the carbon loss during coalification,the long-term average carbon accumulation rate and net primary productivity(NPP)of paleo-peatlands in coal seams can be obtained.This review paper presents the procedures of analysis,assessment of results and interpretation of geophysical logs in determining the NPP of paleo-peatlands.展开更多
In recent years, with the constant change in the global climate, the effect of climate factors on net primary productivity(NPP) has become a hot research topic. However, two opposing views have been presented in this ...In recent years, with the constant change in the global climate, the effect of climate factors on net primary productivity(NPP) has become a hot research topic. However, two opposing views have been presented in this research area: global NPP increases with global warming, and global NPP decreases with global warming. The main reasons for these two opposite results are the tremendous differences among seasonal and annual climate variables, and the growth of plants in accordance with these climate variables. Therefore, it will fail to fully clarify the relation between vegetation growth and climate changes by research that relies solely on annual data. With seasonal climate variables, we may clarify the relation between vegetation growth and climate changes more accurately. Our research examined the arid and semiarid areas in China(ASAC), which account for one quarter of the total area of China. The ecological environment of these areas is fragile and easily affected by human activities. We analyzed the influence of climate changes, especially the changes in seasonal climate variables, on NPP, with Climatic Research Unit(CRU) climatic data and Moderate Resolution Imaging Spectroradiometer(MODIS) satellite remote data, for the years 2000–2010. The results indicate that: for annual climatic data, the percentage of the ASAC in which NPP is positively correlated with temperature is 66.11%, and 91.47% of the ASAC demonstrates a positive correlation between NPP and precipitation. Precipitation is more positively correlated with NPP than temperature in the ASAC. For seasonal climatic data, the correlation between NPP and spring temperature shows significant regional differences. Positive correlation areas are concentrated in the eastern portion of the ASAC, while the western section of the ASAC generally shows a negative correlation. However, in summer, most areas in the ASAC show a negative correlation between NPP and temperature. In autumn, precipitation is less important in the west, as opposed to the east, in which it is critically important. Temperatures in winter are a limiting factor for NPP throughout the region. The findings of this research not only underline the importance of seasonal climate variables for vegetation growth, but also suggest that the effects of seasonal climate variables on NPP should be explored further in related research in the future.展开更多
Northeast China has experienced frequent droughts over the past fifteen years. However, the effects of droughts on net primary productivity(NPP) in Northeast China remain unclear. In this paper, the droughts that occu...Northeast China has experienced frequent droughts over the past fifteen years. However, the effects of droughts on net primary productivity(NPP) in Northeast China remain unclear. In this paper, the droughts that occurred in Northeast China between 1999 and 2013 were identified using the Standardized Precipitation Evapotranspiration Index(SPEI). The NPP standardized anomaly index(NPP-SAI) was used to evaluate NPP anomalies. The years of 1999, 2000, 2001, and 2007 were further investigated in order to explore the influence of droughts on NPP at different time scales(3, 6, and 12 months). Based on the NPP-SAI of normal areas, we found droughts overall decreased NPP by 112.06 Tg C between 1999 and 2013. Lower temperatures at the beginning of the growing season could cause declines in NPP by shortening the length of the growing season. Mild drought or short-term drought with higher temperatures might increase NPP, and weak intensity droughts intensified the lag effects of droughts on NPP.展开更多
Forest net primary productivity(NPP) is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-A...Forest net primary productivity(NPP) is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach(CASA) model with normalized difference vegetation index(NDVI) sequences derived from Advanced Very High Resolution Radiometer(AVHRR) Global Inventory Modeling and Mapping Studies(GIMMS) and Terra Moderate Resolution Imaging Spectroradiometer(MODIS) products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regression model based on least squares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China increased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and autumn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPP. In autumn, precipitation acted as the most important factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportranspiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional regions. In addition to climatic change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.展开更多
Net primary productivity(NPP), a metric used to define and identify changes in plant communities, is greatly affected by climate change, human activities and other factors. Here, we used the Carnegie-Ames-Stanford App...Net primary productivity(NPP), a metric used to define and identify changes in plant communities, is greatly affected by climate change, human activities and other factors. Here, we used the Carnegie-Ames-Stanford Approach(CASA) model to estimate the NPP of plant communities in Hengduan Mountains area of China, and to explore the relationship between NPP and altitude in this region. We examined the mechanisms underlying vegetation growth responses to climate change and quantitatively assessed the effects of ecological protection measures by partitioning the contributions of climate change and human activities to NPP changes. The results demonstrated that: 1) the average total and annual NPP values over the years were 209.15 Tg C and 468.06 g C/(m2·yr), respectively. Their trend increasingly fluctuated, with spatial distribution strongly linked to altitude(i.e., lower and higher NPP in high altitude and low altitude areas, respectively) and 2400 m represented the marginal altitude for vegetation differentiation; 2) areas where climate was the main factor affecting NPP accounted for 18.2% of the total research area, whereas human activities were the primary factor influencing NPP in 81.8% of the total research area, which indicated that human activity was the main force driving changes in NPP. Areas where climatic factors(i.e., temperature and precipitation) were the main driving factors occupied 13.6%(temperature) and 6.0%(precipitation) of the total research area, respectively. Therefore, the effect of temperature on NPP changes was stronger than that of precipitation; and 3) the majority of NPP residuals from 2001 to 2014 were positive, with human activities playing an active role in determining regional vegetation growth, possibly due to the return of farmland back to forest and natural forest protection. However, this positive trend is decreasing. This clearly shows the periodical nature of ecological projects and a lack of long-term effectiveness.展开更多
Vegetation growth status is an important indicator of ecological security.The Tarim River Basin is located in the inland arid region of Northwest China and has a highly fragile ecological environment.Assessing the veg...Vegetation growth status is an important indicator of ecological security.The Tarim River Basin is located in the inland arid region of Northwest China and has a highly fragile ecological environment.Assessing the vegetation net primary productivity(NPP)of the Tarim River Basin can provide insights into the vegetation growth variations in the region.Therefore,based on the Google Earth Engine(GEE)cloud platform,we studied the spatiotemporal variation of vegetation NPP in the Tarim River Basin(except for the eastern Gobi and Kumutag deserts)from 2001 to 2020 and analyzed the correlations between vegetation NPP and meteorological factors(air temperature and precipitation)using the Sen slope estimation method,coefficient of variation,and rescaled range analysis method.In terms of temporal characteristics,vegetation NPP in the Tarim River Basin showed an overall fluctuating upward trend from 2001 to 2020,with the smallest value of 118.99 g C/(m2•a)in 2001 and the largest value of 155.07 g C/(m2•a)in 2017.Regarding the spatial characteristics,vegetation NPP in the Tarim River Basin showed a downward trend from northwest to southeast along the outer edge of the study area.The annual average value of vegetation NPP was 133.35 g C/(m2•a),and the area with annual average vegetation NPP values greater than 100.00 g C/(m2•a)was 82,638.75 km2,accounting for 57.76%of the basin.The future trend of vegetation NPP was dominated by anti-continuity characteristic;the percentage of the area with anti-continuity characteristic was 63.57%.The area with a significant positive correlation between vegetation NPP and air temperature accounted for 53.74%of the regions that passed the significance test,while the area with a significant positive correlation between vegetation NPP and precipitation occupied 98.68%of the regions that passed the significance test.Hence,the effect of precipitation on vegetation NPP was greater than that of air temperature.The results of this study improve the understanding on the spatiotemporal variation of vegetation NPP in the Tarim River Basin and the impact of meteorological factors on vegetation NPP.展开更多
Arid and semi-arid ecosystems exhibit a spatially complex biogeophysical structure. According to arid western special climate-vegetation characters, the fractional cover of photosynthetic vegetation (PV), non-photos...Arid and semi-arid ecosystems exhibit a spatially complex biogeophysical structure. According to arid western special climate-vegetation characters, the fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), bare soil and water are unmixed, using the remote sensing spectral mixture analysis. We try the method to unmix the canopy funation structure of arid land cover in order to avoid the differentiation of regional vegetation system and the disturbance of environmental background. We developed a modified production efficiency model NPP-PEM appropriate for the arid area at regional scale based on the concept of radiation use efficiency. This model refer to the GLO-PEM and CASA model was driven with remotely sensed observations, and calculates not just the conversion efficiency of absorbed photosynthetically active radiation but also the carbon fluxes that determine net primary productivity (NPP). We apply and validate the model in the Kaxger and Yarkant river basins in arid western China. The NPP of the study area in 1992 and 1998 was estimated based on the NPP-PEM model. The results show that the improved PEM model, considering the photosynthetical activation of heterogeneous functional vegetation, is in good agreement with field measurements and the existing literature. An accurate agreement (R2= 0.85, P〈0.001) between the estimates and the ground-based measurement was obtained. The spatial distribution of mountain-oasis-desert ecosystem shows an obvious heterogeneous carbon uptake. The results are applicable to arid ecosystem studies ranging from characterizing carbon cycle, carbon flux over arid areas to monitoring change in mountain-oasis-desert productivity, stress and management.展开更多
Vegetation net primary productivity(NPP)is a sensitive indicator to characterize the response of terrestrial ecosystems to the climate change.Projections of the NPP changes of the Loess Plateau under future climate sc...Vegetation net primary productivity(NPP)is a sensitive indicator to characterize the response of terrestrial ecosystems to the climate change.Projections of the NPP changes of the Loess Plateau under future climate scenarios have great significances in revealing the interactions among terrestrial ecosystems and climatic systems,as well as instructing future vegetation construction of this region.Here,we carried out a case study on the Yangou watershed in the Loess Plateau.Using the vegetation-producing process model(VPP)established for such small watersheds,we simulated the NPP of the Yangou watershed under different scenarios of climate changes.The results showed that the NPP significandy increased with the precipitation increasing and evidently decreased with the temperature increasing where the climate change occurred in the whole year or in the summer half year.However,where the climate change occurred in the winter half year,the increased precipitation had little effect on the NPP,and the increased temperature significantly reduced the NPP.There were clear differences among the response sensitivities of different vegetation types with trees and shrubs were more sensitive to the changes in temperature and precipitation than crops and grasses.Currently,the most favourable climate change scenario to the NPP in the Yangou watershed was T0P15 under which the precipitation increased by 15%and the temperature did not changed,in the whole year;in the meantime,the most unfavourable climate change scenarios was T2P-15 under which the precipitation declined by 15%and the temperature increased by 2℃,in the whole year.展开更多
Based on monthly data of precipitation,temperature,sunshine duration,wind speed,relative humidity and other climatic factors in Youyang County during 1956-2013,net primary productivity(NPP)in the county was calculated...Based on monthly data of precipitation,temperature,sunshine duration,wind speed,relative humidity and other climatic factors in Youyang County during 1956-2013,net primary productivity(NPP)in the county was calculated by using a climate productivity model,and effects of changes in climatic factors on NPP in the county were studied.The results show that annual average NPP in Youyang County during 1956-2013was 11.137 t/(hm^2·a),but there were no significant changes over the past 58 years.There was a significantly positive correlation between NPP and annual precipitation or annual mean relative humidity.Under the background of global warming,NPP in Youyang County will face greater pressure,thereby putting pressure on local ecological environment.The research can provide scientific reference for the construction of Youyang County and ecological protection zones in the southeast of Chongqing.展开更多
Net Primary Productivity (NPP) is the basis of the material and energy transport calculation in ecosystem studies. NPP directly reflects the production capacity of plant communities under natural conditions. Ecosystem...Net Primary Productivity (NPP) is the basis of the material and energy transport calculation in ecosystem studies. NPP directly reflects the production capacity of plant communities under natural conditions. Ecosystem services are hot topics in the field of ecology. Many studies calculate ecosystem service value based on NPP. Taking Guanshanhu District of Guiyang City, Guizhou Province as the research object, using TM, ETM<sup>+</sup>, Gaofen2 and MOD17A3HGF.006 as data sources, this paper analyzed the change of ecosystem service value based on NPP in 2000, 2010 and 2020. The results showed that the area of forest ecosystem increased during 2000-2010 and decreased during 2010-2020. The artificial surface grew rapidly from 1146.82 hm<sup>2</sup> to 7544.29 hm<sup>2</sup> during 2000-2020. The farmland ecosystem decreased from 13308.29 hm<sup>2</sup> to 6342.33 hm<sup>2</sup> during 2000-2020. With the dynamic changes in ecosystem spatial distribution and component structure, the total NPP in 2000, 2010 and 2020 was 12.58 × 10<sup>4</sup> t, 11.90 × 10<sup>4</sup> t and 11.78 × 10<sup>4</sup> t, respectively, showing a decreasing trend. The total value of natural and semi-natural ecosystems services based on NPP showed an increasing trend, which was ¥ 6.938 × 10<sup>8</sup> in 2000, ¥ 8.052 × 10<sup>8</sup> in 2010 and ¥ 10.306 × 10<sup>8</sup> in 2020 respectively. The ecosystem contributed the most to the ecological service value in 2000 was farmland, but in 2010 and 2020, it was the forest ecosystem. The ecological service value of grassland and wetland was relatively small, while the ratio of the wetland ecological service value displayed a decreasing trend. In the future, it is necessary to establish a strict pretrial system for land use, so as to effectively protect the natural and semi-natural ecosystems and fulfill the growing ecological demands of residents.展开更多
基金Under the auspices of Asia Pacific Network for Global Change Research(APN)Global Change Fund Project(No.ARCP2015-03CMY-Li)+2 种基金National Natural Science Foundation of China(No.41271361,41501575)National Key Research and Development Project(No.2018YFD0800201)Key Project of Chinese National Programs for Fundamental Research and Development(No.2010CB950702)
文摘Understanding the net primary productivity(NPP) of grassland is crucial to evaluate the terrestrial carbon cycle. In this study, we investigated the spatial distribution and the area of global grassland across the globe. Then, we used the Carnegie-Ames-Stanford Approach(CASA) model to estimate global grassland NPP and explore the spatio-temporal variations of grassland NPP in response to climate change from 1982 to 2008. Results showed that the largest area of grassland distribution during the study period was in Asia(1737.23 × 104 km^2), while the grassland area in Europe was relatively small(202.83 × 10~4 km^2). Temporally, the total NPP increased with fluctuations from 1982 to 2008, with an annual increase rate of 0.03 Pg C/yr. The total NPP experienced a significant increasing trend from 1982 to 1995, while a decreasing trend was observed from 1996 to 2008. Spatially, the grassland NPP in South America and Africa were higher than the other regions, largely as a result of these regions are under warm and wet climatic conditions. The highest mean NPP was recorded for savannas(560.10 g C/(m^2·yr)), whereas the lowest was observed in open shrublands with an average NPP of 162.53 g C/(m^2·yr). The relationship between grassland NPP and annual mean temperature and annual precipitation(AMT, AP, respectively) varies with changes in AP, which indicates that, grassland NPP is more sensitive to precipitation than temperature.
基金the National Basic Research Program of China(2010CB950702)the National High-Technology Reaearch and Development Program of China(2007AA10Z231)the Asia-Pacific Network for Global Change Research Project(ARCP201106CMY-Li)
文摘This research classified vegetation types and evaluated net primary productivity (NPP) of southern China's grasslands based on the improved comprehensive and sequential classification system (CSCS), and proposed 5 thermal grades and 6 humidity grades. Four classes of grasslands vegetation were recognized by improved CSCS, namely, tundra grassland class, typical grassland class, mixed grassland class and alpine grassland class. At the type level, 14 types of vegetations (9 grasslands and 5 forests) were classified. The NPP had a trend to decrease from east to west and south to north, and the annual mean NPP was estimated to be 656.3 g C m-2 yr-1. The NPP value of alpine grassland class was relatively high, generally more than 1200 g C m2 yr-1. The NPP value of mixed grassland class was in a range from 1 000 to 1200 g C m-2 yr-1. Tundra grassland class was located in southeastern Tibet with high elevation, and its NPP value was the lowest (〈600 g C m'2yrl). The typical grassland class distributed in most of the area, and its NPP value was generally from 600 to 1000 g C m-2 yr-1. The total NPP value in the study area was 68.46 Tg C. The NPP value of typical grassland class was the highest (48.44 Tg C), and mixed grassland class was the second (16.54 Tg C), followed by alpine grassland class (3.22 Tg C), with tundra grassland class being the lowest (0.25 Tg C). For all the grasslands types, the total NPP of forest meadow was the highest (34.81 Tg C), followed by sparse forest brush (16.54 Tg C), and montane meadow was the lowest (0.01 Tg C).
基金supported financially by the National Natural Science Foundation of China(41361140361,41271126)the Project of State Key Laboratory of Desert and Oasis Ecology(Y471163)
文摘Grazing is a main human activity in the grasslands of Xinjiang, China. It is vital to identify the effects of grazing on the sustainable utilization of local grasslands. However, the effects of grazing on net primary productivity (NPP), evapotranspiration (ET) and water use efficiency (WUE) in this region remain unclear. Using the spatial Biome-BGC grazing model, we explored the effects of grazing on NPP, ET and WUE across the different regions and grassland types in Xinjiang during 1979-2012. NPP, ET and WUE under the grazed scenario were generally lower than those under the ungrazed scenario, and the differences showed increasing trends over time. The decreases in NPP, ET and WUE varied significantly among the regions and grassland types. NPP decreased as follows: among the regions, Northern Xinjiang (16.60 g C/(m2·a)), Tianshan Mountains (15.94 g C/(m2·a)) and Southern Xinjiang (-3.54 g C/(m2·a)); and among the grassland types, typical grasslands (25.70 g C/(m2·a)), swamp meadows (25.26 g C/(m2·a)), mid-mountain meadows (23.39 g C/(m2·a)), alpine meadows (6.33 g C/(m2·a)), desert grasslands (5.82 g C/(m2·a)) and saline meadows (2.90 g C/(me.a)). ET decreased as follows: among the regions, Tianshan Mountains (28.95 mm/a), Northern Xinjiang (8.11 mm/a) and Southern Xinjiang (7.57 mm/a); and among the grassland types, mid-mountain meadows (29.30 mm/a), swamp meadows (25.07 mm·a), typical grasslands (24.56 mm/a), alpine meadows (20.69 mm/a), desert grasslands (11.06 mm/a) and saline meadows (3.44 mm/a). WUE decreased as follows: among the regions, Northern Xinjiang (0.053 g C/kg H2O), Tianshan Mountains (0.034 g C/kg H2O) and Southern Xinjiang (0.012 g C/kg H2O); and among the grassland types, typical grasslands (0.0609 g C/kg H2O), swamp meadows (0.0548 g C/kg H2O), mid-mountain meadows (0.0501 g C/kg H2O), desert grasslands (0.0172 g C/kg H2O), alpine meadows (0.0121 g C/kg H2O) and saline meadows (0.0067 g C/kg H2O). In general, the decreases in NPP and WUE were more significant in the regions with relatively high levels of vegetation growth because of the high grazing intensity in these regions. The decreases in ET were significant in mountainous areas due to the terrain and high grazing intensity.
基金provided by the National Natural Science Foundation of China (No. 41402086)the Colleges Scientific Research Projects of Shandong Province (No. J14LH06)+1 种基金the provincial excellent young talents in colleges and universities in Shandong Province natural science foundation of the mutual funds (No. ZR2015JL016)State key research and development plan (No. 2017YFC0601400)
文摘Using the large-scale thick 4# coal seam from the Mid-Jurassic in the southern Ordos Basin as an example, this paper studied the net primary productivity(NPP) level of the Mid-Jurassic peatland, and discussed its control factors. Geophysical logging signals were used for a spectrum analysis to obtain the Milankovitch cycle parameters in coal seam. These were then used to calculate the accumulation rate of the residual carbon in 4# coal seam. The carbon loss can be calculated according to the density and residual carbon content of 4# coal seam. Then, the total carbon accumulation rate of the peatland was further derived, and the NPP of peatland was determined. The results show that the NPP of MidJurassic peatland is higher than that of Holocene at the same latitude. Comprehensive analysis indicates that the temperature, carbon dioxide and oxygen levels in atmosphere are the main control factors of the NPP of Mid-Jurassic peatland.
基金supported by the National Natural Science Fundation of China(No.41571175,31661143028)the special funds for basic research and operation from the Chinese Academy of Meteorological Science(2017Y003)。
文摘Background:Net primary productivity(NPP)in forests plays an important role in the global carbon cycle.However,it is not well known about the increase rate of China’s forest NPP,and there are different opinions about the key factors controlling the variability of forest NPP.Methods:This paper established a statistics-based multiple regression model to estimate forest NPP,using the observed NPP,meteorological and remote sensing data in five major forest ecosystems.The fluctuation values of NPP and environment variables were extracted to identify the key variables influencing the variation of forest NPP by correlation analysis.Results:The long-term trends and annual fluctuations of forest NPP between 2000 and 2018 were examined.The results showed a significant increase in forest NPP for all five forest ecosystems,with an average rise of 5.2 gC·m-2·year-1 over China.Over 90%of the forest area had an increasing NPP range of 0-161 gC·m-2·year-1.Forest NPP had an interannual fluctuation of 50-269 gC.m-2·year-1 for the five major forest ecosystems.The evergreen broadleaf forest had the largest fluctuation.The variability in forest NPP was caused mainly by variations in precipitation,then by temperature fluctuations.Conclusions:All five forest ecosystems in China exhibited a significant increasing NPP along with annual fluctuations evidently during 2000-2018.The variations in China’s forest NPP were controlled mainly by changes in precipitation.
基金jointly supported by the National Natural Science Foundation of China(31400425,31570437,41301043,31420103917)the National Key Project of Scientific and Technical Supporting Program(2013BAC03B03)+1 种基金the Funding for Talented Young Scientists of IGSNRR(2013RC203)the Social Foundation of Beijing Academy of Social Sciences(154005)
文摘Changes in the sizes of precipitation events in the context of global climate change may have profound impacts on ecosystem productivity in arid and semiarid grasslands. However, we still have little knowledge about to what extent grassland productivity will respond to an individual precipitation event. In this study, we quantified the duration, the maximum, and the time-integrated amount of the response of daily gross primary productivity (GPP) to an individual precipitation event and their variations with different sizes of precipitation events in a typical temperate steppe in Inner Mongolia, China. Results showed that the duration of GPP-response (τ<sub>R</sub>) and the maximum absolute GPP-response (GPP<sub>max</sub>) increased linearly with the sizes of precipitation events (P<sub>es</sub>), driving a corresponding increase in time-integrated amount of the GPP-response (GPP<sub>total</sub>) because variations of GPPtotal were largely explained by τ<sub>R</sub> and GPP<sub>max</sub>. The relative contributions of these two parameters to GPP<sub>total</sub> were strongly P<sub>es</sub>-dependent. The GPP<sub>max</sub> contributed more to the variations of GPP<sub>total</sub> when P<sub>es</sub> was relatively small (<20 mm), whereas τ<sub>R</sub> was the main driver to the variations of GPP<sub>total</sub> when P<sub>es</sub> was relatively large. In addition, a threshold size of at least 5 mm of precipitation was required to induce a GPP-response for the temperate steppe in this study. Our work has important implications for the modeling community to obtain an advanced understanding of productivity-response of grassland ecosystems to altered precipitation regimes.
基金Under the auspices of the Key Laboratory of Xinjiang Science and Technology Department(No.2022D04009)National Social Science Foundation of China’s Major Program(No.17ZDA064)。
文摘It is necessary to quantitatively study the relationship between climate and human factors on net primary productivity(NPP)inorder to understand the driving mechanism of NPP and prevent desertification.This study investigated the spatial and temporal differentiation features of actual net primary productivity(ANPP)in the Ili River Basin,a transboundary river between China and Kazakhstan,as well as the proportional contributions of climate and human causes to ANPP variation.Additionally,we analyzed the pixel-scale relationship between ANPP and significant climatic parameters.ANPP in the Ili River Basin increased from 2001 to 2020 and was lower in the northeast and higher in the southwest;furthermore,it was distributed in a ring around the Tianshan Mountains.In the vegetation improvement zone,human activities were the dominant driving force,whereas in the degraded zone,climate change was the primary major driving force.The correlation coefficients of ANPP with precipitation and temperature were 0.322 and 0.098,respectively.In most areas,there was a positive relationship between vegetation change,temperature and precipitation.During 2001 to 2020,the basin’s climatic change trend was warm and humid,which promoted vegetation growth.One of the driving factors in the vegetation improvement area was moderate grazing by livestock.
基金supported by the National Natural Science Foundation of China(Grant Nos.41030213 and 41572090)the Fundamental Research Funds for the Central Universities(Grant No.2022YJSDC05)the Yue Qi Scholar Project of China University of Mining and Technology(Beijing).
文摘Individual coal seams formed in paleo-peatlands represent sustained periods of terrestrial carbon accumulation and a key environmental indicator attributed to this record is the rate of carbon accumulation.Determining the rate of carbon accumulation requires a measure of time contained within the coal.This study aimed to determine this rate via the identification of Milankovitch orbital cycles in the coals.The geophysical log is an ideal paleoclimate proxy and has been widely used in the study of sedimentary records using spectral analysis.Spectral analyses of geophysical log from thick coal seams can be used to identify the Milankovitch cycles and to calculate the period of the coal deposition.By considering the carbon loss during coalification,the long-term average carbon accumulation rate and net primary productivity(NPP)of paleo-peatlands in coal seams can be obtained.This review paper presents the procedures of analysis,assessment of results and interpretation of geophysical logs in determining the NPP of paleo-peatlands.
基金the Strategic Priority Research Program-Climate Change:Carbon Budget and Relevant Issues of Chinese Academy of Sciences(No.XDA05060104)
文摘In recent years, with the constant change in the global climate, the effect of climate factors on net primary productivity(NPP) has become a hot research topic. However, two opposing views have been presented in this research area: global NPP increases with global warming, and global NPP decreases with global warming. The main reasons for these two opposite results are the tremendous differences among seasonal and annual climate variables, and the growth of plants in accordance with these climate variables. Therefore, it will fail to fully clarify the relation between vegetation growth and climate changes by research that relies solely on annual data. With seasonal climate variables, we may clarify the relation between vegetation growth and climate changes more accurately. Our research examined the arid and semiarid areas in China(ASAC), which account for one quarter of the total area of China. The ecological environment of these areas is fragile and easily affected by human activities. We analyzed the influence of climate changes, especially the changes in seasonal climate variables, on NPP, with Climatic Research Unit(CRU) climatic data and Moderate Resolution Imaging Spectroradiometer(MODIS) satellite remote data, for the years 2000–2010. The results indicate that: for annual climatic data, the percentage of the ASAC in which NPP is positively correlated with temperature is 66.11%, and 91.47% of the ASAC demonstrates a positive correlation between NPP and precipitation. Precipitation is more positively correlated with NPP than temperature in the ASAC. For seasonal climatic data, the correlation between NPP and spring temperature shows significant regional differences. Positive correlation areas are concentrated in the eastern portion of the ASAC, while the western section of the ASAC generally shows a negative correlation. However, in summer, most areas in the ASAC show a negative correlation between NPP and temperature. In autumn, precipitation is less important in the west, as opposed to the east, in which it is critically important. Temperatures in winter are a limiting factor for NPP throughout the region. The findings of this research not only underline the importance of seasonal climate variables for vegetation growth, but also suggest that the effects of seasonal climate variables on NPP should be explored further in related research in the future.
基金Under the auspices of Special Issue of National Remote Sensing Survey and Assessment of Eco-Environment Change Between 2000 and 2010(No.STSN-09-03)
文摘Northeast China has experienced frequent droughts over the past fifteen years. However, the effects of droughts on net primary productivity(NPP) in Northeast China remain unclear. In this paper, the droughts that occurred in Northeast China between 1999 and 2013 were identified using the Standardized Precipitation Evapotranspiration Index(SPEI). The NPP standardized anomaly index(NPP-SAI) was used to evaluate NPP anomalies. The years of 1999, 2000, 2001, and 2007 were further investigated in order to explore the influence of droughts on NPP at different time scales(3, 6, and 12 months). Based on the NPP-SAI of normal areas, we found droughts overall decreased NPP by 112.06 Tg C between 1999 and 2013. Lower temperatures at the beginning of the growing season could cause declines in NPP by shortening the length of the growing season. Mild drought or short-term drought with higher temperatures might increase NPP, and weak intensity droughts intensified the lag effects of droughts on NPP.
基金Under the auspices of Key Program of Chinese Academy of Sciences(No.KZZD-EW-08-02)CAS/SAFEA(Chinese Academy of Science/State Administration of Foreign Experts Affairs)International Partnership Program for Creative Research Teams(No.KZZD-EW-TZ-07)Strategic Frontier Program of Chinese Academy of Sciences-Climate Change:Carbon Budget and Relevant Issues(No.XDA05050101)
文摘Forest net primary productivity(NPP) is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach(CASA) model with normalized difference vegetation index(NDVI) sequences derived from Advanced Very High Resolution Radiometer(AVHRR) Global Inventory Modeling and Mapping Studies(GIMMS) and Terra Moderate Resolution Imaging Spectroradiometer(MODIS) products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regression model based on least squares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China increased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and autumn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPP. In autumn, precipitation acted as the most important factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportranspiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional regions. In addition to climatic change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.
基金Under the auspices of National Key Basic Research Program of China(No.2015CB452706)National Natural Science Foundation of China(No.41401198,41571527)+1 种基金Youth Talent Team Program of the Institute of Mountain Hazards and Environment,Chinese Academy of Sciences(No.SDSQB-2015-01)Youth Innovation Promotion Association,Chinese Academy of Sciences(No.2016332)
文摘Net primary productivity(NPP), a metric used to define and identify changes in plant communities, is greatly affected by climate change, human activities and other factors. Here, we used the Carnegie-Ames-Stanford Approach(CASA) model to estimate the NPP of plant communities in Hengduan Mountains area of China, and to explore the relationship between NPP and altitude in this region. We examined the mechanisms underlying vegetation growth responses to climate change and quantitatively assessed the effects of ecological protection measures by partitioning the contributions of climate change and human activities to NPP changes. The results demonstrated that: 1) the average total and annual NPP values over the years were 209.15 Tg C and 468.06 g C/(m2·yr), respectively. Their trend increasingly fluctuated, with spatial distribution strongly linked to altitude(i.e., lower and higher NPP in high altitude and low altitude areas, respectively) and 2400 m represented the marginal altitude for vegetation differentiation; 2) areas where climate was the main factor affecting NPP accounted for 18.2% of the total research area, whereas human activities were the primary factor influencing NPP in 81.8% of the total research area, which indicated that human activity was the main force driving changes in NPP. Areas where climatic factors(i.e., temperature and precipitation) were the main driving factors occupied 13.6%(temperature) and 6.0%(precipitation) of the total research area, respectively. Therefore, the effect of temperature on NPP changes was stronger than that of precipitation; and 3) the majority of NPP residuals from 2001 to 2014 were positive, with human activities playing an active role in determining regional vegetation growth, possibly due to the return of farmland back to forest and natural forest protection. However, this positive trend is decreasing. This clearly shows the periodical nature of ecological projects and a lack of long-term effectiveness.
基金funded by the National Natural Science Foundation of China(42161049,41761019,41061052)the Special Project for Talent Development in the Western Region(201408655089).
文摘Vegetation growth status is an important indicator of ecological security.The Tarim River Basin is located in the inland arid region of Northwest China and has a highly fragile ecological environment.Assessing the vegetation net primary productivity(NPP)of the Tarim River Basin can provide insights into the vegetation growth variations in the region.Therefore,based on the Google Earth Engine(GEE)cloud platform,we studied the spatiotemporal variation of vegetation NPP in the Tarim River Basin(except for the eastern Gobi and Kumutag deserts)from 2001 to 2020 and analyzed the correlations between vegetation NPP and meteorological factors(air temperature and precipitation)using the Sen slope estimation method,coefficient of variation,and rescaled range analysis method.In terms of temporal characteristics,vegetation NPP in the Tarim River Basin showed an overall fluctuating upward trend from 2001 to 2020,with the smallest value of 118.99 g C/(m2•a)in 2001 and the largest value of 155.07 g C/(m2•a)in 2017.Regarding the spatial characteristics,vegetation NPP in the Tarim River Basin showed a downward trend from northwest to southeast along the outer edge of the study area.The annual average value of vegetation NPP was 133.35 g C/(m2•a),and the area with annual average vegetation NPP values greater than 100.00 g C/(m2•a)was 82,638.75 km2,accounting for 57.76%of the basin.The future trend of vegetation NPP was dominated by anti-continuity characteristic;the percentage of the area with anti-continuity characteristic was 63.57%.The area with a significant positive correlation between vegetation NPP and air temperature accounted for 53.74%of the regions that passed the significance test,while the area with a significant positive correlation between vegetation NPP and precipitation occupied 98.68%of the regions that passed the significance test.Hence,the effect of precipitation on vegetation NPP was greater than that of air temperature.The results of this study improve the understanding on the spatiotemporal variation of vegetation NPP in the Tarim River Basin and the impact of meteorological factors on vegetation NPP.
基金National Project for Basic Research, No.2002CB412507 National key project of fundamental research, No.G1999043500 National Natural Science Foundation of China, No.90202002
文摘Arid and semi-arid ecosystems exhibit a spatially complex biogeophysical structure. According to arid western special climate-vegetation characters, the fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), bare soil and water are unmixed, using the remote sensing spectral mixture analysis. We try the method to unmix the canopy funation structure of arid land cover in order to avoid the differentiation of regional vegetation system and the disturbance of environmental background. We developed a modified production efficiency model NPP-PEM appropriate for the arid area at regional scale based on the concept of radiation use efficiency. This model refer to the GLO-PEM and CASA model was driven with remotely sensed observations, and calculates not just the conversion efficiency of absorbed photosynthetically active radiation but also the carbon fluxes that determine net primary productivity (NPP). We apply and validate the model in the Kaxger and Yarkant river basins in arid western China. The NPP of the study area in 1992 and 1998 was estimated based on the NPP-PEM model. The results show that the improved PEM model, considering the photosynthetical activation of heterogeneous functional vegetation, is in good agreement with field measurements and the existing literature. An accurate agreement (R2= 0.85, P〈0.001) between the estimates and the ground-based measurement was obtained. The spatial distribution of mountain-oasis-desert ecosystem shows an obvious heterogeneous carbon uptake. The results are applicable to arid ecosystem studies ranging from characterizing carbon cycle, carbon flux over arid areas to monitoring change in mountain-oasis-desert productivity, stress and management.
基金Key Research Program of the Chinese Academy of Sciences(KZZD-EW-04)West Light Foundation of the Chinese Academy of Sciences and Funds of State Key Laboratory of Loess and Quaternary Geology,Chinese Academy of Sciences(SKLLQG1123)
文摘Vegetation net primary productivity(NPP)is a sensitive indicator to characterize the response of terrestrial ecosystems to the climate change.Projections of the NPP changes of the Loess Plateau under future climate scenarios have great significances in revealing the interactions among terrestrial ecosystems and climatic systems,as well as instructing future vegetation construction of this region.Here,we carried out a case study on the Yangou watershed in the Loess Plateau.Using the vegetation-producing process model(VPP)established for such small watersheds,we simulated the NPP of the Yangou watershed under different scenarios of climate changes.The results showed that the NPP significandy increased with the precipitation increasing and evidently decreased with the temperature increasing where the climate change occurred in the whole year or in the summer half year.However,where the climate change occurred in the winter half year,the increased precipitation had little effect on the NPP,and the increased temperature significantly reduced the NPP.There were clear differences among the response sensitivities of different vegetation types with trees and shrubs were more sensitive to the changes in temperature and precipitation than crops and grasses.Currently,the most favourable climate change scenario to the NPP in the Yangou watershed was T0P15 under which the precipitation increased by 15%and the temperature did not changed,in the whole year;in the meantime,the most unfavourable climate change scenarios was T2P-15 under which the precipitation declined by 15%and the temperature increased by 2℃,in the whole year.
基金Supported by Chongqing Social Science Planning Project(2015YBGL119)Chongqing Education Commission Humanities and Social Sciences Project(15SKG157)Chongqing Three Georges University Project(14ZD15)
文摘Based on monthly data of precipitation,temperature,sunshine duration,wind speed,relative humidity and other climatic factors in Youyang County during 1956-2013,net primary productivity(NPP)in the county was calculated by using a climate productivity model,and effects of changes in climatic factors on NPP in the county were studied.The results show that annual average NPP in Youyang County during 1956-2013was 11.137 t/(hm^2·a),but there were no significant changes over the past 58 years.There was a significantly positive correlation between NPP and annual precipitation or annual mean relative humidity.Under the background of global warming,NPP in Youyang County will face greater pressure,thereby putting pressure on local ecological environment.The research can provide scientific reference for the construction of Youyang County and ecological protection zones in the southeast of Chongqing.
文摘Net Primary Productivity (NPP) is the basis of the material and energy transport calculation in ecosystem studies. NPP directly reflects the production capacity of plant communities under natural conditions. Ecosystem services are hot topics in the field of ecology. Many studies calculate ecosystem service value based on NPP. Taking Guanshanhu District of Guiyang City, Guizhou Province as the research object, using TM, ETM<sup>+</sup>, Gaofen2 and MOD17A3HGF.006 as data sources, this paper analyzed the change of ecosystem service value based on NPP in 2000, 2010 and 2020. The results showed that the area of forest ecosystem increased during 2000-2010 and decreased during 2010-2020. The artificial surface grew rapidly from 1146.82 hm<sup>2</sup> to 7544.29 hm<sup>2</sup> during 2000-2020. The farmland ecosystem decreased from 13308.29 hm<sup>2</sup> to 6342.33 hm<sup>2</sup> during 2000-2020. With the dynamic changes in ecosystem spatial distribution and component structure, the total NPP in 2000, 2010 and 2020 was 12.58 × 10<sup>4</sup> t, 11.90 × 10<sup>4</sup> t and 11.78 × 10<sup>4</sup> t, respectively, showing a decreasing trend. The total value of natural and semi-natural ecosystems services based on NPP showed an increasing trend, which was ¥ 6.938 × 10<sup>8</sup> in 2000, ¥ 8.052 × 10<sup>8</sup> in 2010 and ¥ 10.306 × 10<sup>8</sup> in 2020 respectively. The ecosystem contributed the most to the ecological service value in 2000 was farmland, but in 2010 and 2020, it was the forest ecosystem. The ecological service value of grassland and wetland was relatively small, while the ratio of the wetland ecological service value displayed a decreasing trend. In the future, it is necessary to establish a strict pretrial system for land use, so as to effectively protect the natural and semi-natural ecosystems and fulfill the growing ecological demands of residents.