Evaluation of net primary productivity and its spatial and temporal patterns in southern China’s grasslands
Z. G. Sun A C , X. H. Long B , C. M. Sun A , W. Zhou A , W. M. Ju D and J. L. Li A E
+ Author Affiliations
- Author Affiliations
A School of Life Science, Nanjing University, Nanjing 210093, People’s Republic of China.
B Jiangsu Provincial Key Laboratory of Marine Biology, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, People’s Republic of China.
C College of Animal Sciences and Technology, Nanjing Agricultural University, Nanjing 210095, People’s Republic of China.
D International Institute for Earth System Science, Nanjing University, Nanjing 210093, P eople’s Republic of China.
E Corresponding author. Email: jianlongli@gmail.com
The Rangeland Journal 35(3) 331-338 https://doi.org/10.1071/RJ12061
Submitted: 19 August 2012 Accepted: 21 March 2013 Published: 20 May 2013
Abstract
The net primary productivity (NPP) of grassland ecosystems is an important indicator of the capacity for carbon (C) absorption. The Global Production Efficiency Model was adopted to simulate NPP in southern China’s grasslands and to analyse the temporal and spatial dynamics from 1981 to 2000. There was a high correlation between measured and simulated values (R2 = 0.84). Based on the data from 1981 to 2000, the mean annual NPP was 1082 g C m–2 year–1, and the highest value (1798 g C m–2 year–1) was in Hainan province, and the lowest value (500 g C m–2 year–1) was in south-western Tibet. The highest mean NPP values were in the permanent wetlands (1193 g C m–2 year–1) and savannas (1137 g C m–2 year–1); woody savannas had an intermediate value (1087 g C m–2 year–1), and the lowest NPP occurred in typical grasslands and open shrubs, the mean values were 709 and 689 g C m–2 year–1, respectively. Temporally, the total NPP in southern China’s grasslands slightly increased in the 20-year period, especially from 1981 to 1990. The mean annual total of NPP in the 20 years was 0.758 Pg C. Inter-annual variation in total NPP was driven mainly by mean annual temperature rather than mean annual precipitation. The results suggest that grassland ecosystems in southern China have a large C sink.
Additional keywords: climate-driven factors, global production efficiency model (GLO-PEM), grasslands, net primary productivity (NPP), temporal and spatial patterns, Southern China.
References
Bao, Y. H., Bao, G. G., Guo, L. B., and Hai, Q. S. (2009). Evaluation of vegetation net primary productivity using MODIS data in Inner Mongolia. PIAGENG. Intelligent Information, Control, and Communication Technology for Agricultural Engineering 7490, 26–34.| Evaluation of vegetation net primary productivity using MODIS data in Inner Mongolia. PIAGENG.Crossref | GoogleScholarGoogle Scholar |
Bayarjargal, Y., Karnieli, A., Bayasgalan, M., Khudulmurb, S., Gandush, C., and Tucker, C. J. (2006). A comparative study of NOAA–AVHRR derived drought indices using change vector analysis. Remote Sensing of Environment 105, 9–22.
| A comparative study of NOAA–AVHRR derived drought indices using change vector analysis.Crossref | GoogleScholarGoogle Scholar |
Cao, M. K., Prince, S. D., Small, J., and Goetz, S. J. (2004). Remotely sensed inter-annual variations and trends in terrestrial Net Primary Productivity 1981–2000. Ecosystems 7, 233–242.
| Remotely sensed inter-annual variations and trends in terrestrial Net Primary Productivity 1981–2000.Crossref | GoogleScholarGoogle Scholar |
Chen, L. F., Gao, Y. H., Li, L., Liu, Q. H., and Gu, X. H. (2008). Forest NPP estimation based on MODIS data under cloudless conditions. Science in China Series D: Earth Sciences 51, 331–338.
| Forest NPP estimation based on MODIS data under cloudless conditions.Crossref | GoogleScholarGoogle Scholar |
Chen, Z. Q., Shao, Q. Q., Liu, J. Y., and Wang, J. B. (2012). Analysis of net primary productivity of terrestrial vegetation on the Qinghai-Tibet Plateau, based on MODIS remote sensing data. Science in China Series D: Earth Sciences 55, 1306–1312.
| Analysis of net primary productivity of terrestrial vegetation on the Qinghai-Tibet Plateau, based on MODIS remote sensing data.Crossref | GoogleScholarGoogle Scholar |
Department of Animal Husbandry and Veterinary Medicine, and General Station of Animal Husbandry and Veterinary Medicine of the Ministry of Agriculture of China (1996). ‘Rangeland Resources of China.’ (China Agriculture Science and Technology Press: Beijing.) [In Chinese].
Fan, J. W., Shao, Q. Q., Liu, J. Y., Wang, J. B., Harris, W., Chen, Z. Q., Zhong, H. P., Xu, X. L., and Liu, R. G. (2010). Assessment of effects of climate change and grazing activity on grassland yield in the Three Rivers Headwaters Region of Qinghai–Tibet Plateau, China. Environmental Monitoring and Assessment 170, 571–584.
| Assessment of effects of climate change and grazing activity on grassland yield in the Three Rivers Headwaters Region of Qinghai–Tibet Plateau, China.Crossref | GoogleScholarGoogle Scholar | 20041346PubMed |
Goulden, M. L., Mcmillan, A. M. S., Winston, G. C., Rocha, A. V., Manies, K. L., Harden, J. W., and Bond-Lamberty, B. P. (2011). Patterns of NPP, GPP, respiration, and NEP during boreal forest succession. Global Change Biology 17, 855–871.
| Patterns of NPP, GPP, respiration, and NEP during boreal forest succession.Crossref | GoogleScholarGoogle Scholar |
Hein, L., Ridder, N. D., Hiernaux, P., Leemans, R., de Wit, A., and Schaepman, M. (2011). Desertification in the Sahel: towards better accounting for ecosystem dynamics in the interpretation of remote sensing images. Journal of Arid Environments 75, 1164–1172.
| Desertification in the Sahel: towards better accounting for ecosystem dynamics in the interpretation of remote sensing images.Crossref | GoogleScholarGoogle Scholar |
Hik, D. S., and Jefferies, R. L. (1990). Increases in the net above-ground primary production of a salt-marsh forage grass: a test of the predictions of the herbivore-optimization model. Journal of Ecology 78, 180–195.
| Increases in the net above-ground primary production of a salt-marsh forage grass: a test of the predictions of the herbivore-optimization model.Crossref | GoogleScholarGoogle Scholar |
Huang, Y., Zhang, W., Sun, W. J., and Zheng, X. H. (2007). Net primary production of Chinese croplands from 1950 to 1999. Ecological Applications 17, 692–701.
| Net primary production of Chinese croplands from 1950 to 1999.Crossref | GoogleScholarGoogle Scholar | 17494389PubMed |
Huang, Y. H., Zhou, G. Y., Tang, X. L., Jiang, H., Zhang, D. Q., and Zhang, Q. M. (2011). Estimated soil respiration rates decreased with long-term soil microclimate changes in successional forests in Southern China. Environmental Management 48, 1189–1197.
| Estimated soil respiration rates decreased with long-term soil microclimate changes in successional forests in Southern China.Crossref | GoogleScholarGoogle Scholar |
IPCC (2001). ‘Climate Change 2001: The Scientific Basis.’ (Cambridge University Press: Cambridge, UK.)
IPCC (2007). ‘Climate Change 2007: the Physical Science Basis.’ (Cambridge University Press: Cambridge, UK.)
Liu, J., Chen, J. M., Cihlar, J., and Park, W. M. (1997). A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sensing of Environment 62, 158–175.
| A process-based boreal ecosystem productivity simulator using remote sensing inputs.Crossref | GoogleScholarGoogle Scholar |
Lobell, D. B., Hicke, J. A., Asner, G. P., Field, C. B., Tucker, C. J., and Los, S. O. (2002). Satellite estimates of productivity and light use efficiency in United States agriculture, 1982–98. Global Change Biology 8, 722–735.
| Satellite estimates of productivity and light use efficiency in United States agriculture, 1982–98.Crossref | GoogleScholarGoogle Scholar |
Ma, W. H., Fang, J. Y., Yang, Y. H., and Mohammat, A. (2010). Biomass carbon stocks and their changes in northern China’s grasslands during 1982–2006. Science China Life Science 53, 841–850.
| Biomass carbon stocks and their changes in northern China’s grasslands during 1982–2006.Crossref | GoogleScholarGoogle Scholar |
Melillo, J. M., Mcguire, A. D., Kicklighter, D. W., Moore, B., Vorosmarty, C. J., and Schloss, A. L. (1993). Global climate change and terrestrial net primary production. Nature 363, 234–240.
| Global climate change and terrestrial net primary production.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK3sXksFeiu78%3D&md5=ec6af10fc1468d3897daf50233ef1ef4CAS |
Meng, J. H., Wu, B. F., and Zhou, Y. M. (2005). Monitoring terrestrial net primary productivity of China using BIOME-BGC model based on remote sensing. IGARSS ‘05: 25th IEEE International Geoscience and Remote Sensing Symposium 5, 3105–3108.
Myneni, R. B., Keeling, C. D., Tucker, C. J., Asrar, G., and Nemani, R. R. (1997). Increased plant growth in the northern high latitudes from 1981 to 1991. Nature 386, 698–702.
| Increased plant growth in the northern high latitudes from 1981 to 1991.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK2sXislOgurw%3D&md5=fc8e6b16a54f0da9f3eb50509fb4c3b7CAS |
Nayak, A. K., Patel, N. R., and Dadhwal, V. K. (2010). Estimation and analysis of terrestrial net primary productivity over India by remote-sensing-driven terrestrial biosphere model. Environmental Monitoring and Assessment 170, 195–213.
| Estimation and analysis of terrestrial net primary productivity over India by remote-sensing-driven terrestrial biosphere model.Crossref | GoogleScholarGoogle Scholar |
Ni, J. (2004). Estimating net primary productivity of grasslands from field biomass measurements in temperate northern China. Plant Ecology 174, 217–234.
| Estimating net primary productivity of grasslands from field biomass measurements in temperate northern China.Crossref | GoogleScholarGoogle Scholar |
Pan, Y. D., Mcguire, A. D., Kicklighter, D. W., and Melillo, J. M. (1996). The importance of climate and soils for estimates of net primary production: a sensitivity analysis with the terrestrial ecosystem models. Global Change Biology 2, 5–23.
| The importance of climate and soils for estimates of net primary production: a sensitivity analysis with the terrestrial ecosystem models.Crossref | GoogleScholarGoogle Scholar |
Piao, S. L., Fang, J. Y., and Guo, Q. H. (2001). Application of CASA model to the estimation of Chinese terrestrial net primary productivity. Acta Phytoecologica Sinica 25, 603–608.
Potter, C. S., Randerson, J., Field, C. B., Matson, P. A., Vitousek, P. M., Mooney, H. A., and Klooster, S. A. (1993). Terrestrial eco-system production: a process model based on global satellite and surface data. Global Biogeochemical Cycles 7, 811–841.
| Terrestrial eco-system production: a process model based on global satellite and surface data.Crossref | GoogleScholarGoogle Scholar |
Prince, S. D., and Goward, S. N. (1995). Global primary production: a remote sensing approach. Journal of Biogeography 22, 815–835.
| Global primary production: a remote sensing approach.Crossref | GoogleScholarGoogle Scholar |
Riedo, M., Gyalistras, D., and Fuhrer, J. (2000). Net primary production and carbon stocks in differently managed grasslands: simulation of site-specific sensitivity to an increase in atmospheric CO2 and to climate change. Ecological Modelling 134, 207–227.
| Net primary production and carbon stocks in differently managed grasslands: simulation of site-specific sensitivity to an increase in atmospheric CO2 and to climate change.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3cXntFyis7w%3D&md5=c6cc11fd7a773a520358cac13026d420CAS |
Ruimy, A., Saugier, B., and Dedieu, G. (1994). Methodology for the estimation of terrestrial net primary production from remotely sensed data. Journal of Geophysical Research 99, 5263–5283.
| Methodology for the estimation of terrestrial net primary production from remotely sensed data.Crossref | GoogleScholarGoogle Scholar |
Schimel, D. S., Emanuel, W., and Rizzo, B. (1997). Continental scale variability in ecosystem processes: models, data, and the role of disturbance. Ecological Monographs 67, 251–271.
| Continental scale variability in ecosystem processes: models, data, and the role of disturbance.Crossref | GoogleScholarGoogle Scholar |
Silva, J. M. N., Sá, A. C. L., and Pereira, J. M. C. (2005). Comparison of burned area estimates derived from SPOT-VEGETATION and Landsat ETM+ data in Africa: influence of spatial pattern and vegetation type. Remote Sensing of Environment 96, 188–201.
| Comparison of burned area estimates derived from SPOT-VEGETATION and Landsat ETM+ data in Africa: influence of spatial pattern and vegetation type.Crossref | GoogleScholarGoogle Scholar |
Sims, D. A., Luo, H. Y., Hastings, S., Oechelb, W. C., Rahmanc, A. F., and Gamona, J. A. (2006). Parallel adjustments in vegetation greenness and ecosystem CO2 exchange in response to drought in a Southern California chaparral ecosystem. Remote Sensing of Environment 103, 289–303.
| Parallel adjustments in vegetation greenness and ecosystem CO2 exchange in response to drought in a Southern California chaparral ecosystem.Crossref | GoogleScholarGoogle Scholar |
SPSS (1999). ‘SPSS Based 10.0 User’s Guide.’ (SPSS Inc.: Chicago. IL.)
Sui, X., and Zhou, G. (2013). Carbon dynamics of temperate grassland ecosystems in China from 1951 to 2007: an analysis with a process-based biogeochemistry model. Environmental Earth Sciences 68, 521–533.
| Carbon dynamics of temperate grassland ecosystems in China from 1951 to 2007: an analysis with a process-based biogeochemistry model.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXjs1Kruw%3D%3D&md5=015e81cfabb9391a4f578faf9f5e23a4CAS |
Tarnavsky, E., Garrigues, S., and Brown, M. E. (2008). Multi-scale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products. Remote Sensing of Environment 112, 535–549.
| Multi-scale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products.Crossref | GoogleScholarGoogle Scholar |
Yang, Y. H., Fang, J. Y., Ji, C. J., and Han, W. X. (2009). Above- and below-ground biomass allocation in Tibetan grasslands. Journal of Vegetation Science 20, 177–184.
| Above- and below-ground biomass allocation in Tibetan grasslands.Crossref | GoogleScholarGoogle Scholar |
Zhao, M. S., and Runnings, S. W. (2006). Sensitivity of moderate resolution imaging spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses. Journal of Geophysical Research 111, G01002.
| Sensitivity of moderate resolution imaging spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses.Crossref | GoogleScholarGoogle Scholar |
