scholarly journals Assessment of net primary productivity over India using Indian geostationary satellite (INSAT-3A) data

Author(s):  
S. K. Goroshi ◽  
R. P. Singh ◽  
R. Pradhan ◽  
J. S. Parihar

Polar orbiting satellites (MODIS and SPOT) have been commonly used to measure terrestrial Net Primary Productivity (NPP) at regional/global scale. Charge Coupled Device (CCD) instrument on geostationary INSAT-3A platform provides a unique opportunity for continuous monitoring of ecosystem pattern and process study. An <i>improved</i> Carnegie-Ames-Stanford Approach (<i>i</i>CASA) model is one of the most expedient and precise ecosystem models to estimate terrestrial NPP. In this paper, an assessment of terrestrial NPP over India was carried out using the iCASA ecosystem model based on the INSAT CCD derived Normalized Difference Vegetation Index (NDVI) with multisource meteorological data for the year 2009. NPP estimated from the INSAT CCD followed the characteristic growth profile of most of the vegetation types in the country. NPP attained maximum during August and September, while minimum in April. Annual NPP for different vegetation types varied from 1104.55 gC m<sup>&minus;2</sup> year<sup>&minus;1</sup> (evergreen broadleaf forest) to 231.9 gC m<sup>&minus;2</sup> year<sup>&minus;1</sup> (grassland) with an average NPP of 590 gC m<sup>&minus;2</sup> year<sup>&minus;1</sup>. We estimated 1.9 PgC of net carbon fixation over Indian landmass in 2009. Biome level comparison between INSAT derived NPP and MODIS NPP indicated a good agreement with the Willmott’s index of agreement (d) ranging from 0.61 (Mixed forest) to 0.99 (Open Shrubland). Our findings are consistent with the earlier NPP studies in India and indicate that INSAT derived NPP has the capability to detect spatial and temporal variability of terrestrial NPP over a wide range of terrestrial ecosystems in India. Thus INSAT-3A data can be used as one of the potential satellite data source for accurate biome level carbon estimation in India.

2019 ◽  
Vol 12 (1) ◽  
pp. 12
Author(s):  
Chaobin Zhang ◽  
Ying Zhang ◽  
Zhaoqi Wang ◽  
Jianlong Li ◽  
Inakwu Odeh

Both vegetation phenology and net primary productivity (NPP) are crucial topics under the background of global change, but the relationships between them are far from clear. In this study, we quantified the spatial-temporal vegetation start (SOS), end (EOS), and length (LOS) of the growing season and NPP for the temperate grasslands of China based on a 34-year time-series (1982–2015) normalized difference vegetation index (NDVI) derived from global inventory modeling and mapping studies (GIMMS) and meteorological data. Then, we demonstrated the relationships between NPP and phenology dynamics. The results showed that more than half of the grasslands experienced significant changes in their phenology and NPP. The rates of their changes exhibited spatial heterogeneity, but their phenological changes could be roughly divided into three different clustered trend regions, while NPP presented a polarized pattern that increased in the south and decreased in the north. Different trend zones’ analyses revealed that phenology trends accelerated after 1997, which was a turning point. Prolonged LOS did not necessarily increase the current year’s NPP. SOS correlated with the NPP most closely during the same year compared to EOS and LOS. Delayed SOS contributed to increasing the summer NPP, and vice versa. Thus, SOS could be a predictor for current year grass growth. In view of this result, we suggest that future studies should further explore the mechanisms of SOS and plant growth.


2021 ◽  
Vol 13 (13) ◽  
pp. 2522
Author(s):  
Lkhagvadorj Nanzad ◽  
Jiahua Zhang ◽  
Battsetseg Tuvdendorj ◽  
Shanshan Yang ◽  
Sonam Rinzin ◽  
...  

Drought has devastating impacts on agriculture and other ecosystems, and its occurrence is expected to increase in the future. However, its spatiotemporal impacts on net primary productivity (NPP) in Mongolia have remained uncertain. Hence, this paper focuses on the impact of drought on NPP in Mongolia. The drought events in Mongolia during 2003–2018 were identified using the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI). The Boreal Ecosystem Productivity Simulator (BEPS)-derived NPP was computed to assess changes in NPP during the 16 years, and the impacts of drought on the NPP of Mongolian terrestrial ecosystems was quantitatively analyzed. The results showed a slightly increasing trend of the growing season NPP during 2003–2018. However, a decreasing trend of NPP was observed during the six major drought events. A total of 60.55–87.75% of land in the entire country experienced drought, leading to a 75% drop in NPP. More specifically, NPP decline was prominent in severe drought areas than in mild and moderate drought areas. Moreover, this study revealed that drought had mostly affected the sparse vegetation NPP. In contrast, forest and shrubland were the least affected vegetation types.


Author(s):  
Y. R. Cai ◽  
J. H. Zheng ◽  
M. J. Du ◽  
C. Mu ◽  
J. Peng

Vegetation is an important part of the terrestrial ecosystem. It plays an important role in the energy and material exchange of the ground-atmosphere system and is a key part of the global carbon cycle process.Climate change has an important influence on the carbon cycle of terrestrial ecosystems. Net Primary Productivity (Net Primary Productivity)is an important parameter for evaluating global terrestrial ecosystems. For the Xinjiang region, the study of grassland NPP has gradually become a hot issue in the ecological environment.Increasing the estimation accuracy of NPP is of great significance to the development of the ecosystem in Xinjiang. Based on the third-generation GIMMS AVHRR NDVI global vegetation dataset and the MODIS NDVI (MOD13A3) collected each month by the United States Atmospheric and Oceanic Administration (NOAA),combining the advantages of different remotely sensed datasets, this paper obtained the maximum synthesis fusion for New normalized vegetation index (NDVI) time series in 2006&amp;ndash;2015.Analysis of Net Primary Productivity of Grassland Vegetation in Xinjiang Using Improved CASA Model The method described in this article proves the feasibility of applying data processing, and the accuracy of the NPP calculation using the fusion processed NDVI has been greatly improved. The results show that: (1) The NPP calculated from the new normalized vegetation index (NDVI) obtained from the fusion of GIMMS AVHRR NDVI and MODIS NDVI is significantly higher than the NPP calculated from these two raw data; (2) The grassland NPP in Xinjiang Interannual changes show an overall increase trend; interannual changes in NPP have a certain relationship with precipitation.


2021 ◽  
Vol 9 ◽  
Author(s):  
Tarun K. Thakur ◽  
Digvesh K. Patel ◽  
Anita Thakur ◽  
Anirudh Kumar ◽  
Arvind Bijalwan ◽  
...  

In recent decades, degradation and loss of the world’s forest ecosystems have been key contributors to biodiversity loss and future climate change. This article analyzes plant diversity, biomass, carbon sequestration potential (CSP), and the net primary productivity (NPP) of four vegetation types viz., Dense mixed forest (DMF); Open mixed forest (OMF); Teak plantation (TP), and Sal mixed forest (SMF) in the dry tropical forest ecosystem of central India through remote sensing techniques together with physical ground observations during 2013–2018. The total C storage in trees varied from 16.02 to 47.15 Mg ha−1 in studied vegetation types with the highest in DMF and lowest in OMF. The total C storage in stem wood, branches, and foliage falls in the range of 52.93–78.30%, 9.49–22.99%, and 3.31–12.89% respectively. The total standing biomass varied from 83.77 to 111.21 Mg ha−1 and these variations are due to different vegetation types, with the highest in DMF followed by TP, SMF while the lowest was estimated in OMF. The net primary productivity (NPP) [aboveground (AG) + belowground (BG)] varied from 7.61 to 9.94 Mg ha−1 yr−1 with mean values of 8.74 Mg ha−1 yr−1 where AG shares a maximum contribution of 77.66%. The total biomass production was distributed from 64.09 to 82.91% in AG and 17.08–35.91% in BG components. The present study outlines that the studied forest ecosystem has the substantial potential of carbon sequestration and a great possibility of mitigating local and global climate change.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhe Yuan ◽  
Yongqiang Wang ◽  
Jijun Xu ◽  
Zhiguang Wu

AbstractThe ecosystem of the Source Region of Yangtze River (SRYR) is highly susceptible to climate change. In this study, the spatial–temporal variation of NPP from 2000 to 2014 was analyzed, using outputs of Carnegie–Ames–Stanford Approach model. Then the correlation characteristics of NPP and climatic factors were evaluated. The results indicate that: (1) The average NPP in the SRYR is 100.0 gC/m2 from 2000 to 2014, and it shows an increasing trend from northwest to southeast. The responses of NPP to altitude varied among the regions with the altitude below 3500 m, between 3500 to 4500 m and above 4500 m, which could be attributed to the altitude associated variations of climatic factors and vegetation types; (2) The total NPP of SRYR increased by 0.18 TgC per year in the context of the warmer and wetter climate during 2000–2014. The NPP was significantly and positively correlated with annual temperature and precipitation at interannual time scales. Temperature in February, March, May and September make greater contribution to NPP than that in other months. And precipitation in July played a more crucial role in influencing NPP than that in other months; (3) Climatic factors caused the NPP to increase in most of the SRYR. Impacts of human activities were concentrated mainly in downstream region and is the primary reason for declines in NPP.


2021 ◽  
Vol 118 (52) ◽  
pp. e2115283118
Author(s):  
Heng Huang ◽  
Salvatore Calabrese ◽  
Ignacio Rodriguez-Iturbe

Soil heterotrophic respiration (Rh) represents an important component of the terrestrial carbon cycle that affects whether ecosystems function as carbon sources or sinks. Due to the complex interactions between biological and physical factors controlling microbial growth, Rh is uncertain and difficult to predict, limiting our ability to anticipate future climate trajectories. Here we analyze the global FLUXNET 2015 database aided by a probabilistic model of microbial growth to examine the ecosystem-scale dynamics of Rh and identify primary predictors of its variability. We find that the temporal variability in Rh is consistently distributed according to a Gamma distribution, with shape and scale parameters controlled only by rainfall characteristics and vegetation productivity. This distribution originates from the propagation of fast hydrologic fluctuations on the slower biological dynamics of microbial growth and is independent of biome, soil type, and microbial physiology. This finding allows us to readily provide accurate estimates of the mean Rh and its variance, as confirmed by a comparison with an independent global dataset. Our results suggest that future changes in rainfall regime and net primary productivity will significantly alter the dynamics of Rh and the global carbon budget. In regions that are becoming wetter, Rh may increase faster than net primary productivity, thereby reducing the carbon storage capacity of terrestrial ecosystems.


2019 ◽  
Vol 41 (4) ◽  
pp. 335
Author(s):  
Z. G. Sun ◽  
J. S. Wu ◽  
F. Liu ◽  
T. Y. Shao ◽  
X. B. Liu ◽  
...  

Identifying the effects of climate change and human activities on the degradation and restoration of terrestrial ecosystems is essential for sustainable management of these ecosystems. However, our knowledge of methodology on this topic is limited. To assess the relative contribution of climate change and human activities, actual and potential net primary productivity (NPPa and NPPp respectively), and human appropriation of net primary productivity (HANPP) were calculated and applied to the monitoring of forest, grassland, and cropland ecosystems in Yunnan–Guizhou–Sichuan Provinces, southwest China. We determined annual means of 476 g C m–2 year–1 for NPPa, 1314 g C m–2 year–1 for NPPp, and 849 g C m–2 year–1 for HANPP during the period between 2007 and 2016. Furthermore, the area with an increasing NPPa accounted for 75.12% of the total area of the three ecosystems. Similarly, the areas with increasing NPPp and HANPP accounted for 77.60 and 57.58% of the study area respectively. Furthermore, we found that ~57.58% of areas with ecosystem restored was due to climate change, 23.39% due to human activities, and 19.03% due to the combined effects of human activities and climate change. In contrast, climate change and human activities contributed to 19.47 and 76.36%, respectively, of the areas of degraded ecosystem. Only 4.17% of degraded ecosystem could be attributed to the combined influences of climate change and human activities. We conclude that human activities were mainly responsible for ecosystem degradation, whereas climate change benefitted ecosystem restoration in southwest China in the past decade.


1993 ◽  
Vol 23 (1) ◽  
pp. 81-88 ◽  
Author(s):  
Tatyana P. Kolchugina ◽  
Ted S. Vinson

Natural processes in ocean and terrestrial ecosystems together with human activities have caused a measurable increase in the atmospheric concentration of CO2. It is predicted that an increase in the concentration of CO2 will cause the Earth's temperatures to rise and will accelerate rates of plant respiration and the decay of organic matter, disrupting the equilibrium of the terrestrial carbon cycle. Forests are an important component of the biosphere, and sequestration of carbon in boreal forests may represent one of the few realistic alternatives to ameliorate changes in atmospheric chemistry. The former Soviet Union has the greatest expanse of boreal forests in the world; however, the role of Soviet forests in the terrestrial carbon cycle is not fully understood because the carbon budget of the Soviet forest sector has not been established. In recognition of the need to determine the role of Soviet forests in the global carbon cycle, the carbon budget of forest biomes in the former Soviet Union was assessed based on an equilibrium analysis of carbon cycle pools and fluxes. Net primary productivity was used to identify the rate of carbon turnover in the forest biomes. Net primary productivity was estimated at 4360 Mt of carbon, the vegetation carbon pool was estimated at 110 255 Mt, the litter carbon pool was estimated at 17 525 Mt, and the soil carbon pool was estimated at 319 100 Mt. Net primary productivity of Soviet forest biomes exceeded industrial CO2 emissions in the former Soviet Union by a factor of four and represented approximately 7% of the global terrestrial carbon turnover. Carbon stores in the phytomass and soils of forest biomes of the former Soviet Union represented 16% of the carbon concentrated in the biomass and soils of the world's terrestrial ecosystems. All carbon pools of Soviet forest biomes represented approximately one-seventh of the world's terrestrial carbon pool.


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