Net Primary Production Trends Research Articles

Analysis of spatiotemporal dynamics of forest Net Primary Productivity of Nepal during 2000–2015

ABSTRACTProper estimation and spatiotemporal trend analysis of net primary productivity (NPP) are very important for forest ecosystem monitoring and management. In this article, we investigate the spatiotemporal trend and variability of the Boreal Ecosystem Productivity Simulator (BEPS)-derived forest NPP over Nepal during the period 2000–2015. This study is the first attempt to simulate nation-wide NPP at 500 m spatial resolution at the daily step for the recent 16-year period. In our work, we use a process-based model BEPS, to estimate the NPP in the forest of Nepal. All the meteorological, forest cover, soil data, leaf area index (LAI), tree cover, biomass, and biophysical parameters, required for the model, were downloaded from different sources or prepared, pre-processed and used in the BEPS model to come up with the daily NPP. In spite of some fluctuations in NPP in some years, there is an overall positive change in the NPP throughout the study period. The annual average national NPP has been raised from 1.34 g m−2 day−1 to 1.74 g m−2 day−1 from 2000 to –2015. Examining the inter-annual variation, we found almost 87% of the total forested area has a positive inter-annual variation and 13% negative. The overall average daily NPP per m2 over the entire forest in the entire period ranges from 0.1 to 4.7 g m−2 day−1 with an average of 1.65 g m−2 day−1. Similarly, by physiographic regions, the average NPP in the plain was 2.43 g m−2 day−1, hills 1.83 g m−2 day−1, and mountain 1.41 g m−2 day−1. The total daily NPP for the entire forest area ranges from 3 to 257 tons with an average of 96 tons over the study period. NPP was found to be highly influenced by rainfall, solar radiation, and temperature. While in case of the variation of NPP on different forest types, broad-leaved forest was found to have almost 1.7 times more (NPP 1.97 g m−2 day−1) than that of needle-leaved forest (NPP 1.18 g m−2 day−1). The slope per cent of <15% is favourable (NPP 2.15 g m−2 day−1) for higher NPP among different slope per cent. We found that this method could be more convenient for estimation and studies of the NPP in Nepal. The result from this study gives us important information on intra and inter-annual spatiotemporal trends and variability of NPP in the forest of overall Nepal of different physiographic regions. It also gives us information on the variation in trends of NPP with the change in various climatic and vegetation parameters, which can be important for the proper forest ecosystem monitoring, management, and planning operations.

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.

Spatial-temporal changes in NPP and its relationship with climate factors based on sensitivity analysis in the Shiyang River Basin

As a typical inland river basin in China, the Shiyang River Basin is characterized by its special mountain-basin structure. The ecological health in the basin is related to the sustainable development of the economy and society. At present, there are few studies on net primary productivity (NPP) in the Shiyang River Basin, and the existing analysis of the relationship between NPP and climatic factors is lacking. The upper mountainous area and the middle and lower oasis areas in the Shiyang River Basin were selected as the study area. The NPP of the study area was estimated using the Thornthwaite Memorial Model. The spatial and temporal characteristics of NPP were analyzed by Sen’s slope method. Based on the sensitivity analysis, the correlation of the main climate factors to NPP was estimated. According to the aforementioned work, the variation trend of the future NPP was predicted. The results showed that NPP in the study area increased from 1981 to 2015 with the increase in temperature and precipitation. The spatial heterogeneity of the change trend of NPP was not significant, but the spatial heterogeneity of the rangeability was strong. The NPP was highly sensitive to precipitation, relative humidity and net solar radiation. By integrating the changes in climatic elements, the temperature, precipitation and relative humidity contributed the main parts of the change in NPP. The NPP is predicted to increase by 4.9–8.1% by 2050 according to the amplitude of climate change over the past 35 yrs.

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.

Monitoring the impact of climate change and human activities on grassland vegetation dynamics in the northeastern Qinghai-Tibet Plateau of China during 2000–2015

Climate change and human activities can influence vegetation net primary productivity (NPP), a key component of natural ecosystems. The Qinghai-Tibet Plateau of China, in spite of its significant natural and cultural values, is one of the most susceptible regions to climate change and human disturbances in the world. To assess the impact of climate change and human activities on vegetation dynamics in the grassland ecosystems of the northeastern Qinghai-Tibet Plateau, we applied a time-series trend analysis to normalized difference vegetation index (NDVI) datasets from 2000 to 2015 and compared these spatiotemporal variations with trends in climatic variables over the same time period. The constrained ordination approach (redundancy analysis) was used to determine which climatic variables or human-related factors mostly influenced the variation of NDVI. Furthermore, in order to determine whether current conservation measures and programs are effective in ecological protection and reconstruction, we divided the northeastern Qinghai-Tibet Plateau into two parts: the Three-River Headwater conservation area (TRH zone) in the south and the non-conservation area (NTRH zone) in the north. The results indicated an overall (73.32%) increasing trend of vegetation NPP in grasslands throughout the study area. During the period 2000–2015, NDVI in the TRH and NTRH zones increased at the rates of 0.0015/a and 0.0020/a, respectively. Specifically, precipitation accounted for 9.2% of the total variation in NDVI, while temperature accounted for 13.4%. In addition, variation in vegetation NPP of grasslands responded not only to long- and short-term changes in climate, as conceptualized in non-equilibrium theory, but also to the impact of human activities and their associated perturbations. The redundancy analysis successfully separated the relative contributions of climate change and human activities, of which village population and agricultural gross domestic product were the two most important contributors to the NDVI changes, explaining 17.8% and 17.1% of the total variation of NDVI (with the total contribution >30.0%), respectively. The total contribution percentages of climate change and human activities to the NDVI variation were 27.5% and 34.9%, respectively, in the northeastern Qinghai-Tibet Plateau. Finally, our study shows that the grassland restoration in the study area was enhanced by protection measures and programs in the TRH zone, which explained 7.6% of the total variation in NDVI.

Identification and assessment of the factors driving vegetation degradation/regeneration in drylands using synthetic high spatiotemporal remote sensing Data—A case study in Zhenglanqi, Inner Mongolia, China

Abstract Vegetation degradation is a direct distinguishing feature of land degradation in drylands and seriously affects the ecological balance and sustainable development of drylands. Existing assessment methods of vegetation degradation at the regional scale based on long-time-series data have many shortcomings, including coarse resolution and a diversity of vegetation indicators that are typically complex. In the present study, net primary productivity (NPP) was selected as a primary vegetation indicator. Taking Zhenglanqi in the Inner Mongolia Autonomous Region as the study area, a technical process for the assessment of vegetation degradation/regeneration and analysis of the associated driving forces was proposed at a medium–high resolution scale. First, integrating the high spatial resolution advantage of Landsat data and the high temporal resolution advantage of moderate resolution imaging spectroradiometer (MODIS) data, a time series annual NPP dataset from 2001 to 2016 at 30 m resolution was constructed by applying the spatial and temporal adaptive reflectance fusion model (STARFM) and improved Carnegie–Ames–Stanford Approach (CASA) model. Then, the areas of vegetation degradation and regeneration from 2001 to 2016 were identified and determined by annual NPP trend analysis using the Sen + Mann-Kendall method. Overall, vegetation in Zhenglanqi was generally characterized by regeneration, with the degraded and recovered areas being 0.8% and 11.4%, respectively. Nearly 20% of the areas covered by sandy land showed a significant trend of vegetation regeneration, which indicated that the sand-drifting control measures introduced in the Otindag sandy land and its surroundings had achieved significant results. Next, the driving forces of vegetation degradation and regeneration in Zhenglanqi were distinguished over the past 16 years through proposed multiple and partial regression methods. Human activities were the main driver of vegetation degradation and regeneration (68.6% for degradation, 59.9% for regeneration), and the combination of human activities and climate variation also played an important role in vegetation degradation and regeneration (29.3% for degradation, 39.4% for regeneration), which indicated that the significant improvement of vegetation was related to the implemented eco-restoration projects, and visually proved by comparison of high resolution satellite images taking in different years. This research is expected to provide technical support and scientific reference data for ecological protection and land management in the study area, as well as the development of ecological engineering strategies in the drylands of northern China.

Potential impacts of climate change on vegetation dynamics and ecosystem function in a mountain watershed on the Qinghai-Tibet Plateau

The Qinghai-Tibet Plateau constitutes unique mountain ecosystems that can be used for early detection of the impacts of climate change on ecosystem functions. We use the MAPSS-CENTURY 2 (MC2), a dynamic global vegetation model, to examine the potential responses of terrestrial ecosystems to climate change in the past (1961–2010) and future (2011–2080) under one medium-low warming scenario (RCP4.5) at a 1-km spatial resolution in the Upper Heihe River Basin (UHRB), northwestern China. Results showed that 21.4% of the watershed area has experienced changes in potential natural vegetation types in the past and that 42.6% of the land would undergo changes by the 2070s, characterized by a sharp increase in alpine tundra at the cost of cold barren land. Net primary productivity (NPP) and heterotrophic respiration (RH) have increased sharply since the mid-1980s and are projected to remain at reduced rates in the future. Overall, UHRB switched from carbon neutral to a carbon sink in 1961–2010, and the sink strength is projected to decline after 2040. Additionally, future climate change is projected to drive a decrease in water yield due to a slight decrease in precipitation and an increase in evapotranspiration (ET). Furthermore, we find large spatial variations in simulated ecosystem dynamics, including an upward trend of NPP, RH, and ET in the alpine zone, but a downward trend in the mid-elevation forest zone. These results underscore the complexity of potential impacts of climate change on mountain watersheds that represent the headwaters of inland river systems in an arid environment.

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.

Climatic Changes Dominant Interannual Trend in Net Primary Productivity of Alpine Vulnerable Ecosystems

The Three-River Headwaters (TRH), which is the source area of Yangtze River, Yellow River and Lancang River, is vulnerable and sensitive, and its alpine ecosystem is considered an important barrier for China's ecological security. Understanding the impact of climate changes is essential for determining suitable measures for ecological environmental protection and restoration against the background of global climatic changes. However, different explanations of the interannual trends in complex alpine ecosystems have been proposed due to limited availability of reliable data and the uncertainty of the model itself. In this study, the remote sensing-process coupled model (GLOPEM-CEVSA) was used to estimate the net primary productivity (NPP) of vegetation in the TRH region from 2000 to 2012. The estimated NPP significantly and linearly correlated with the above-ground biomass sampled in the field (the multiple correlative coefficient R2 = 0.45, significant level P < 0.01) and showed better performance than the MODIS productivity product, i.e. MOD17A3, (R2 = 0.21). The climate of TRH became warmer and wetter during 1990-2012, and the years 2000 to 2012 were warmer and wetter than the years1990–2000. Responding to the warmer and wetter climate, the NPP had an increasing trend of 13.7 g m–2 (10 yr)–1 with a statistical confidence of 86% (P = 0.14). Among the three basins, the NPP of the Yellow River basin increased at the fastest rate of 17.44 g m–2 (10 yr)–1 (P = 0.158), followed by the Yangtze River basin, and the Lancang River, which was the slowest with a rate of 12.2 g m–2 (10 yr)–1 and a statistical confidence level of only 67%. A multivariate linear regression with temperature and precipitation as the independent variables and NPP as the dependent variable at the pixel level was used to analyze the impacts of climatic changes on the trend of NPP. Both temperature and precipitation can explain the interannual variability of 83% in grassland NPP in the whole region, and can explain high, medium and low coverage of 78%, 84% and 83%, respectively, for grassland in the whole region. The results indicate that climate changes play a dominant role in the interannual trend of vegetation productivity in the alpine ecosystems on Qinghai-Tibetan Plateau. This has important implications for the formulation of ecological protection and restoration policies for vulnerable ecosystems against the background of global climate changes.

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.

Dominant control of climate variations over land-use change on net primary productivity under different urbanization intensities in Beijing, China

Climate variations and land-use change induced by rapid urbanization can lead to crucial impacts on ecosystem Net Primary Productivity (NPP), especially in regions with intensive human activity. However, the relative contributions of land-use change and climate variations to NPP changes under different urbanization intensities are still a topic of debate. This study reports on a case study in Beijing, which is undergoing rapid urbanization, to estimate the effects of land-use change and climate variations on NPP in regions with diverse urbanization intensities in recent decades using remote-sensing data and the Carnegie-Ames-Stanford Approach (CASA) model. The results reveal obvious land-use changes in Beijing, showing an increase in both built-up and forested areas in the two inner, highly urbanized regions and a dramatic conversion from built-up area and grassy bush to forest in the two outer, less urbanized regions. Factorial experiments were performed to estimate the contributions of land-use change and climate variations to NPP changes for different regions and land-use types. An increasing trend in regional NPP was observed with decreasing urbanization intensity in all experiments. However, the increment in NPP between 2002 and 2009 tended to decrease with decreasing urbanization intensity in most experiments. Climate variation was the dominant factor in increasing NPP in the study region during 2002–2009, with a mean contribution of ∼89.5% over different regions and land-use types. However, land-use change contributed to a certain extent to NPP changes for specific land-use types (e.g., ∼28.1% for forests) in regions of intensive urbanization. Eco-engineering approaches such as increasing vegetation cover, especially forest, in built-up areas and reforestation and afforestation in non-built-up areas may be useful in mitigating the impacts of urbanization on NPP, especially in intensively urbanized regions.

Variations and climate constraints of terrestrial net primary productivity over Mongolia

The ecosystems of Mongolia are among the most sensitive to global climate change because they are located in the circumpolar boreal zone, with its arid and semiarid climate. This study used the Carnegie-Ames-Stanford Approach (CASA) model parameterized by meteorological and remote-sensing data to quantify vegetation net primary productivity (NPP) for Mongolia for 1982–2011 and further constructed a map of the relative contributions of climatic constraints to NPP. The results showed that 30-year average NPP in Mongolia varied spatially from 18.1 to 662.8 g C/m2, with an average of 228.2 g C/m2. From the map of climatic constraints on NPP, it was estimated that temperature constrains NPP variation over about 3.9% of Mongolia's land area, whereas precipitation constraints are dominant over about 77.5%. NPP in temperature-constrained regions has continuously increased from 1982 to 2011, with an annual increment of 2.18 g C/m2 (R = 0.61, p < 0.01) with continuous climate warming (0.07 °C/year, R = 0.73, p < 0.01). In contrast, the NPP trend in precipitation-constrained regions has changed from increasing (R = 0.68, p = 0.01) to decreasing (R = -0.38, p = 0.12) since 1994, which can be attributed to a reversal of precipitation trends in 1994. At national scale, NPP appeared stable during 1982–2011, due primarily to the high proportion of precipitation-constrained area in Mongolia, which obscured NPP trends in the temperature-constrained regions. Given that NPP trends clearly varied with different climatic constraints, the importance of differentiating climatic constraints on NPP for exploring NPP trends under different climatic drivers should be emphasized. The seasonal-scale analysis further showed that summer climate and associated vegetation productivity is an important factor regulating NPP over the entire growing season, due primarily to the high proportion of summer NPP and precipitation for the entire growing season, and warmer temperatures in summer relative to those in spring and autumn. In addition to temperature and precipitation, radiation is an important factor responsible for the NPP variations, and the shape of the correlations between radiation and NPP with changing precipitation gradient suggests that the impact process of radiation on NPP with changing water stress is similar to that of temperature, but its impact is weaker than that of temperature.

A long-term and comprehensive assessment of the urbanization-induced impacts on vegetation net primary productivity

Urbanization not only directly alters the regional ecosystem net primary productivity (NPP) through land-cover replacement, but it is also accompanied by huge indirect impacts due to the associated climate change and anthropogenic activities. However, to date, limited efforts have been made to quantitatively separate the two types of urbanization impacts, and the continuous variations over a long-time span are not well understood. In this study, both the long-term direct and indirect impacts of urbanization on NPP were established and analyzed based on multi-source remote sensing data, taking the city of Kunming in China as a case study area. The results indicated that the intense urbanization process has led to a continuous decrease in NPP from 1990 to 2014, due to the direct impact of land-cover replacement. Nevertheless, the urbanization has also resulted in an apparently positive indirect impact on NPP, which has offset about 30% of the direct impact in recent years. The increasing trend of the indirect impact was found to be higher than the NPP trend in the surrounding forest areas, which proves that vegetation growth has been promoted by the urban environment. The indirect impact has also shown great spatial and temporal heterogeneity, with generally higher values in the old city area and winter season. This can mostly be attributed to the distribution of temperature, i.e., the urban heat island effect, which has shown a significantly positive correlation with the indirect impact. However, the correlations between NPP and climatic factors were found to be completely different, which confirmed the need to separate the direct and indirect impacts. Overall, this study has demonstrated that urbanization has reduced the total NPP over the region, but has promoted some vegetation growth, and the knowledge of the indirect impact will help to support urban greening planning.

Tree-ring isotopes capture interannual vegetation productivity dynamics at the biome scale

Historical and future trends in net primary productivity (NPP) and its sensitivity to global change are largely unknown because of the lack of long-term, high-resolution data. Here we test whether annually resolved tree-ring stable carbon (δ13C) and oxygen (δ18O) isotopes can be used as proxies for reconstructing past NPP. Stable isotope chronologies from four sites within three distinct hydroclimatic environments in the eastern United States (US) were compared in time and space against satellite-derived NPP products, including the long-term Global Inventory Modeling and Mapping Studies (GIMMS3g) NPP (1982–2011), the newest high-resolution Landsat NPP (1986–2015), and the Moderate Resolution Imaging Spectroradiometer (MODIS, 2001–2015) NPP. We show that tree-ring isotopes, in particular δ18O, correlate strongly with satellite NPP estimates at both local and large geographical scales in the eastern US. These findings represent an important breakthrough for estimating interannual variability and long-term changes in terrestrial productivity at the biome scale.

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

2000-2015年宁夏草地净初级生产力时空特征及其气候响应

PDF HTML阅读 XML下载 导出引用 引用提醒 2000-2015年宁夏草地净初级生产力时空特征及其气候响应 DOI: 10.5846/stxb201801220171 作者: 作者单位: 宁夏大学西北土地退化与生态系统恢复省部共建国家重点实验室培育基地,宁夏大学西北土地退化与生态系统恢复省部共建国家重点实验室培育基地,宁夏大学西北土地退化与生态系统恢复省部共建国家重点实验室培育基地,宁夏大学西北土地退化与生态系统恢复省部共建国家重点实验室培育基地,宁夏大学西北土地退化与生态系统恢复省部共建国家重点实验室培育基地,宁夏大学西北土地退化与生态系统恢复省部共建国家重点实验室培育基地,宁夏大学西北土地退化与生态系统恢复省部共建国家重点实验室培育基地,宁夏大学西北土地退化与生态系统恢复省部共建国家重点实验室培育基地 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（41661003）；宁夏高等学校一流学科（生态学）建设项目（NXYLXK2017B06）；中国科学院西部之光人才计划项目（XAB2017AW01） Spatiotemporal characteristics of grassland net primary production in Ningxia Province from 2000 to 2015 and its response to climate change Author: Affiliation: Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwest China,Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwest China,Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwest China,Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwest China,Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwest China,Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwest China,Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwest China,Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwest China Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:草地是宁夏陆地生态系统的重要组成部分，估算其净初级生产力（NPP）对宁夏草地可持续利用与管理至关重要。采用MODIS数据和CASA模型对2000-2015年间宁夏草地生态系统NPP进行了估算，通过一元线性回归趋势分析、Hurst指数等方法研究草地NPP的时空变化规律及未来演变趋势，并分析草地NPP与气象因子的相关性。结果表明：（1）基于CASA模型的宁夏草地NPP模拟精度高，其估算值与实测多年草地NPP均值具有良好的线性关系（R=0.93，P < 0.01），与MOD17产品的草地NPP空间分布基本一致。（2）近16 a宁夏草地年均NPP为148.28 g C m-2 a-1，且存在波动上升的趋势，其线性增长率为3.84 g C m-2 a-1（P < 0.01）。（3）宁夏草地NPP整体处于上升趋势，草地NPP增长的草地面积达98%，且其增率自南向北递减；宁夏草地NPP的Hurst指数在0.27-0.81之间，均值为0.53，大部分草地的NPP变化趋势具有较强同向持续性。（4）在年时间尺度上，宁夏草地NPP主要受降水量的影响，与气温的相关性较弱；在月时间尺度上，生长季草地NPP与月总降水量的相关性高，且不存在时间滞后响应现象，而与月均温的响应则存在1个月的时间滞后性，宁夏大面积分布的干草原与荒漠草原NPP对气温响应滞后是导致这一现象发生的主要原因。 Abstract:Net primary productivity (NPP) is an important indicator of terrestrial ecosystems and accurately estimating NPP is fundamental in terrestrial carbon cycle research. Ningxia Province is dominated by grassland and the estimation of grassland NPP can provide a scientific basis for the sustainable use of grassland resources and the improvement of grassland management. In this study, the grassland ecosystem NPP in Ningxia Province was estimated using a Carnegie-Ames-Stanford Approach (CASA) model and Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2000 to 2015. To study the spatiotemporal characteristics and future evolution trend of grassland NPP, the correlation between the grassland NPP and meteorological factors was analyzed using a simple linear regression model and the Hurst index. The results showed that the CASA model accurately simulated the grassland NPP in Ningxia Province. The correlation coefficient between estimated NPP by the CASA model and measured NPP was 0.93 (P < 0.01), and the spatial characteristics of the estimated NPP image were similar to that of the NPP image of MOD17. In the whole province, the average annual grassland NPP estimated by the CASA model was 148.28 g C m-2 a-1 during 2000-2015. Meanwhile, the average annual grassland NPP increased with fluctuations during the past 16 years and the linear growth rate was 3.84 g C m-2 a-1 (P < 0.01). Regarding the spatial variation of grassland NPP in Ningxia Province, the NPP in 98% of the grassland increased during the past 16 years and this increasing rate decreased from South to North. The Hurst index of grassland NPP in the past 16 years ranged from 0.27 to 0.81 and the mean value was 0.53, which indicated the grassland NPP will maintain the same trend of change in the future. At an annual scale, the average grassland NPP in Ningxia Province was mainly affected by annual precipitation, and had a weak correlation with the average annual temperature. At a monthly scale, there was also a weak relationship between the grassland NPP and temperature in the growing season; however, the monthly total precipitation exerted an important influence on the grassland NPP accumulation. Furthermore, there was a one-month time lag in the monthly NPP response to mean temperature, but this phenomenon did not exist between the monthly NPP and total precipitation. The main reason for this phenomenon was possibly the hysteresis response to temperature in the steppe and desert grasslands, which were the main types of grassland in Ningxia Province. 参考文献 相似文献 引证文献

Broad Consistency Between Satellite and Vegetation Model Estimates of Net Primary Productivity Across Global and Regional Scales

AbstractDrought has the potential to significantly decrease net primary production (NPP). However, the drought sensitivity of NPP remains unclear globally. Here we investigated the response of NPP to drought for the period 1982–2011 using NPP derived from satellite models, eight dynamic global vegetation models (DGVMs), and several drought indices. Our results indicate that the sign of drought response of NPP is consistent across satellites and DGVMs globally. Both the model and satellite data show a unimodal distribution of drought sensitivity across climatic gradients and indicate that semiarid regions are the most drought‐sensitive areas. In addition, a decreasing drought trend was significantly correlated with an increasing trend in satellite‐derived NPP or DGVM‐derived NPP globally. However, the DGVM‐derived NPP is more sensitive to drought than the satellite‐derived NPP over most vegetated land areas and presents a stronger correlation with drought, higher drought sensitivity, and larger slopes between NPP and drought trends. The overresponse of the DGVM‐derived NPP to drought relative to the satellite‐derived NPP could be attributed to the higher drought sensitivity of the simulated leaf area index and overresponse of the DGVM‐derived NPP to the vapor pressure deficit. Overall, large uncertainties remain in the response of NPP to drought and additional long‐term observations are required to better represent NPP responses to water stress in DGVM models.

Assessing vulnerability of forest ecosystem in the Indian Western Himalayan region using trends of net primary productivity

The Himalayan ecosystem is one of the sensitive and fragile ecosystems with rich biodiversity that provides major ecosystem services. The study was conducted to measure the extent of vulnerability across forested grids of Uttarakhand—one of the States of Indian Western Himalayan (IWH) region. The forests of the state are exposed to various anthropogenic and natural climatic pressures, thus making them vulnerable. In this paper, we demonstrate how to map vulnerability of forest ecosystem by analyzing variability and trends of net primary productivity (NPP). The vulnerability of the forest ecosystem was evaluated through trends of sensitivity and adaptability of NPP. The sensitivity of a system was considered as the response degree of the system to climatic variability whereas adaptability was considered as the ability to maintain, recover or improve its structure in the face of climatic stresses. In our study, NPP was considered as the receptor of shock and stresses of climatic variability and human disturbances. We discuss the method and results with reference to productivity changes under the influence of changing climate for the forested landscape of a mountainous region. The results have been summarized to rank vulnerability at the level of administrative boundary of governance, i.e. district. Average value of vulnerability for all NPP pixels of forests grids in a district was used to compute the vulnerability at district level. The study will help forest managers in decision making for efficiently allocating resources and to prioritize management options in the identified regions to improve productivity in coming times.

The effects of air temperature and precipitation on the net primary productivity in China during the early 21st century

Research on how terrestrial ecosystems respond to climate change can reveal the complex interactions between vegetation and climate. net primary productivity (NPP), an important vegetation parameter and ecological indicator, fluctuates within any given ecological environment or regional carbon budget. In this study, spatial interpolation was used to generate a spatial dataset, with 1-km spatial resolution, with meteorological data from 736 observation stations across China. An improved CASA model was used to simulate NPP over the period of 2001–2013 by taking into account land-cover change in every year during the same period. We propose the gridbased spatial patterns and dynamics of annual NPP, annual average temperature, and annual total precipitation based on the model. We also used the model to demonstrate the spatial correlation between NPP, temperature, and precipitation in the study area with special focus on the impact of climate change in the early 21st century. Results showed that the spatial pattern of NPP over all of China is characterized by higher values in the southeast and lower values in the northwest. The spatial pattern of temperature indicates substantial latitudinal differences across the country, and the spatial pattern of precipitation shows a ribbon of decline from the southeast coast to the northwest inland. Most areas show an upward trend in NPP. Temperatures appear to decrease across the country during the global warming hiatus (1998–2008), and are accompanied by an increase in precipitation over most regions. The correlation between NPP and annual average temperature is weak. Alternatively, NPP and annual total precipitation are positively correlated in northern and central China at a coefficient above 0.64 (p<0.01) yet negatively correlated in the eastern parts of the Qinghai- Tibet Plateau and Sichuan Basin. Results can provide useful information for improving parameters for calibration of the terrestrial ecosystem process model.

Estimation of net primary productivity and its driving factors in the Ili River Valley, China

Net primary productivity (NPP), as an important variable and ecological indicator in grassland ecosystems, can reflect environmental change and the carbon budget level. The Ili River Valley is a wetland nestled in the hinterland of the Eurasian continent, which responds sensitively to the global climate change. Understanding carbon budget and their responses to climate change in the ecosystem of Ili River Valley has a significant effect on the adaptability of future climate change and sustainable development. In this study, we calculated the NPP and analyzed its spatio-temporal pattern of the Ili River Valley during the period 2000–2014 using the normalized difference vegetation index (NDVI) and an improved Carnegie-Ames-Stanford (CASA) model. Results indicate that validation showed a good performance of CASA over the study region, with an overall coefficient of determination (R2) of 0.65 and root mean square error (RMSE) of 20.86 g C/(m2•a). Temporally, annual NPP of the Ili River Valley was 599.19 g C/(m2•a) and showed a decreasing trend from 2000 to 2014, with an annual decrease rate of–3.51 g C/(m2•a). However, the spatial variation was not consistent, in which 55.69% of the areas showed a decreasing tendency, 12.60% of the areas remained relatively stable and 31.71% appeared an increasing tendency. In addition, the decreasing trends in NPP were not continuous throughout the 15-year period, which was likely being caused by a shift in climate conditions. Precipitation was found to be the dominant climatic factor that controlled the inter-annual variability in NPP. Furthermore, the correlations between NPP and climate factors differed along the vertical zonal. In the medium-high altitudes of the Ili River Valley, the NPP was positively correlated to precipitation and negatively correlated to temperature and net radiation. In the low-altitude valley and high-altitude mountain areas, the NPP showed a negative correlation with precipitation and a weakly positive correlation with temperature and net radiation. The results suggested that the vegetation of the Ili River Valley degraded in recent years, and there was a more complex mechanism of local hydrothermal redistribution that controlled the growth of vegetation in this valley ecosystem.