Abstract
Fluctuations of the climate variables have increased in the recent years. These fluctuations are different in each climatic region. Net primary production (NPP) indicating the plant growth and carbon stabilization over period of time is influenced by these fluctuations. Investigation of the variations in the NPP and analysis of its relationship with the climatic and environmental variables can play a key role in determining the effects of fluctuations of climatic variables on the NPP. Therefore, the present study was conducted to investigate the spatiotemporal changes in the NPP and its correlation with precipitation rate and temperature during 2000–2014 based on the annual NPP estimates determined by the moderate resolution imaging spectroradiometer (MODIS) sensor and precipitation and temperature data of the synoptic stations in eight climate regions in Iran. The slope of variations in the NPP was calculated in these climatic regions, and then, the changes in the NPP trend at two confidence levels of 95 and 99% were investigated based on the pixel-based method using the Mann–Kendall test. The sensitivity of NPP to climatic variables of temperature and precipitation was also estimated by calculating the correlation. The results showed the significant spatial distribution of NPP in the whole region under study indicating a declining trend from north to south and from west to east directions. The results also indicated the nonlinear variations in the temporal distribution of NPP. The annual mean NPP was found to follow the climatic boundaries in the climatic regions except for climate region 2, and region with the higher annual mean precipitation had higher annual mean NPP. Analysis of the trend by the Mann–Kendall method revealed that 3.2% of the pixels in the whole region followed a certain trend. Among the pixels, 70% of them followed a negative trend and the remaining 30% followed a positive trend. The greatest number of pixels with a certain trend was found in the Gulf of Oman coast climate region so that 93% of the pixels had a positive trend. The lowest number of pixels with a certain trend was observed in eastern Alborz foothills so that 87% of the pixels showed a negative trend. Slope variations of the NPP in the whole region varied from − 35 to 46 gC m2 year−1. The eastern plateau had the highest negative slope variations among the climate regions, and the highest positive slope variation of 42% was observed in the highlands climate region. In general, the precipitation rate and temperature showed a mean partial coefficient of 0.22 and 0.02, respectively, and the correlation between the NPP and temperature and precipitation was different in each climatic region. The temperature was negatively correlated with the NPP in four climatic regions with higher annual mean temperatures and in other climatic regions; it had a weak positive correlation. Therefore, the sensitivity of NPP to precipitation and temperature was different in each climatic region.
Similar content being viewed by others
Abbreviations
- NPP:
-
net primary production
- ANPP:
-
annual NPP
- MODIS:
-
moderate resolution imaging spectroradiometer
- CASA:
-
the Carnegie-Ames-Stanford approach
- P:
-
precipitation
- E:
-
evapotranspiration
- PET:
-
potential evapotranspiration
- GIS:
-
geography information system
- GPP:
-
gross primary production
- LAI:
-
leaf area index
- NDVI:
-
normalized difference vegetation index
- FRWO:
-
Forests, Range, and Watershed Management Organization
- km2 :
-
square kilometer
- ha:
-
hectare
- GPP:
-
gross primary production
- Rm:
-
maintenance respiration
- Rg:
-
respiration rate
- LAI:
-
leaf area index
- S:
-
variance
- α :
-
significance level
- Z :
-
standard normal distribution
- θ slope :
-
slope of variations
- R x,y :
-
correlation of NPP with the temperature and precipitation rate
- gC m2 year−1 :
-
gram carbon square meters per year
References
Abbaspour, A. C., Faramarzi, M., Ghasemi, S., & Yang, H. (2009). Assessing the impact of climate change on water resources in Iran. Water Resources Research, 45(10), W10434. https://doi.org/10.1029/2008WR007615.
Azhdari, Z., Rafeie Sardooi, E., Bazrafshan, O., Zamani, H., Singh, V. P., Mohseni Saravi, M., & Ramezani, M. (2020). Impact of climate change on net primary production (NPP) in south Iran. Environmental Monitoring and Assessment, 192, 409. https://doi.org/10.1007/s10661-020-08389-w.
Balling, R. C., Keikhosravi Kiany, M. S., & Sen Roy, S. H. (2015). Anthropogenic signals in Iranian extreme temperature indices. Atmospheric Research, 169(1), 96–101. https://doi.org/10.1016/j.atmosres.2015.09.030.
Bao, G., Bao, Y., Qin, Z., Xin, X., Bao, Y., Bayarsaikan, S., Zhou, Y., & Chuntai, B. (2016). Modeling net primary productivity of terrestrial ecosystems in the semi-arid climate of the Mongolian plateau using LSWI-based CASA ecosystem model. International Journal of Applied Earth Observation and Geoinformation, 46(2016), 84–93. https://doi.org/10.1016/j.jag.2015.12.001.
Bao, G., Tuyaa, A., Bayarsaikhanc, S., Dorjsurenc, A., Mandakhc, U., Baoa, Y., Lid, C. H., & Vanchindorje, B. (2019). Variations and climate constraints of terrestrial net primary productivity over Mongolia. Journal of Quaternary International. https://doi.org/10.1016/j.quaint.2019.06.017.
Chen, Z., Yu, G. R., Zhu, X. J., Wang, Q. F., Niu, S. L., & Hu, Z. M. (2015). Covariation between gross primary production and ecosystem respiration across space and the underlying mechanisms: a global synthesis. Agricultural and Forest Meteorology, 203, 180–190. https://doi.org/10.1016/j.agrformet.2015.01.012.
Chen, S., Jiang, H., Chen, Y., & Cai, Z. (2019). Spatial-temporal patterns of net primary production in Anji (China) between 1984 and 2014. Journal of Ecological Indicators, 110(2020), 105954. https://doi.org/10.1016/j.ecolind.2019.105954.
Eisfelder, C. H., Klein, I., Niklaus, M., & Kuenzer, C. (2013). Net primary productivity in Kazakhstan, its spatio-temporal patterns and relation to meteorological variables. Journal of Arid Environments, 103, 17–30. https://doi.org/10.1016/j.jaridenv.2013.12.005.
Fang, O., Wang, Y., & Shao, X. (2015). The effect of climate on the net primary productivity (NPP) of Pinus koraiensis in the Changbai Mountains over the past 50 years. Trees., 30, 281–294. https://doi.org/10.1007/s00468-015-1300-6.
Fensholt, R., Sandholt, I., Rasmussen, S. M., Stisen, S., & Diouf, A. (2006). Evaluation of satellite based primary production modelling in the semi-arid Sahel. Remote Sensing of Environment, 105, 173–188. https://doi.org/10.1016/j.rse.2006.06.011.
FRWO. (2019). Iranian forests, range and watershed management Organization website. http://www.frw.org.ir/02/fa/staticpages/page.aspx?tid=1499. Accessed Jun 2019.
Fu, Z., Stoy, P. C., Luo, Y., Chen, J., Sun, J., Montagnani, L., et al. (2017). Climate controls over the net carbon uptake period and amplitude of net ecosystem production in temperate and boreal ecosystems. Agricultural and Forest Meteorology, 243, 9–18. https://doi.org/10.1016/j.agrformet.2017.05.009.
Guo, X., Black, S., & He, Y. (2011). Estimation of leaf CO2 exchange rates using a SPOT image. International Journal of Remote Sensing, 32, 353–366. https://doi.org/10.1080/01431160903464161.
Hadian, F., Jafari, R., Bashiri, H., Tartesh, M., & Clarke, K. C. (2018). Estimation of spatial and temporal changes in net primary production based on Carnegie Ames Stanford Approach (CASA) model in semi-arid rangelands of Semirom County, Iran. Journal of Arid Land. https://doi.org/10.1007/s40333-019-0060-3.
Haghdoust, N., Akbarinia, M., Safaie, N., Yousefzadeh, H., & Balint, M. (2017). Community analysis of Persian oak fungal micro biome under dust storm conditions. Fungal Ecology, 29, 1–9. https://doi.org/10.1016/j.funeco.2017.05.002.
Hao, W., Guohua, L., Zhongshan, L., Xin, Y., Meng, W., & Li, G. (2017). Impacts of climate change on net primary productivity in arid and semiarid regions of China. Chinese Geographical Science, 26, 35–47. https://doi.org/10.1007/s11769-015-0762-1.
Heshmati, G. A. (2007). Vegetation characteristics of four ecological zones of Iran. International Journal of Plant Production., 1, 215–224. https://doi.org/10.22069/IJPP.2012.538.
John, J., Chithra N. R, Thampi, S.G, (2019), Prediction of land use/cover change in the Bharathapuzha.
Khalyani, A. H., & Mayer, A. L. (2013). Spatial and temporal deforestation dynamics of Zagros forests (Iran) from 1972 to 2009. Landscape and Urban Planning, 117(1–12). https://doi.org/10.1016/J.LANDURBPLAN.2013.04.014.
Knorr, W., & Heimann, M. (2001). Uncertainties in global terrestrial biosphere modeling 1. A comprehensive sensitivity analysis with a new photosynthesis and energy balance scheme. Global Biogeochemical Cycles, 15, 207–255. https://doi.org/10.1029/1998GB001059.
Leeuw, J.D., Rizayeva, A., Namazov, E., Bayramov, E,. Marshall, M, T., Etzolde, J., Neudertf, R., (2019). Application of the MODIS MOD 17 net primary production product in grassland carrying capacity assessment. International Journal of Applied Earth Observation and Geoinformation. 78, 66–76. https://doi.org/10.1016/j.jag.2018.09.014.
Li, Z., Huffman, T., McConkey, B., & Townley-Smith, L. (2013). Monitoring and modeling spatial and temporal patterns of grassland dynamics using time-series MODIS NDVI with climate and stocking data. Remote Sensing of Environment, 138, 232–244. https://doi.org/10.1016/j.rse.2013.07.020.
Li, G., Hana, H., Dub, Y., Huic, D., Xiad, J., Niue, S., Lia, X., & Wana, S. (2017). Effects of warming and increased precipitation on net ecosystem productivity: a long-term manipulative experiment in a semi-arid grassland. Agricultural and Forest Meteorology, 232, 359–366. https://doi.org/10.1016/j.agrformet.2016.09.004.
Li, W., Li, C., Liu, X., He, D., Bao, A., Yi, Q., Wang, B., & Liu, T. (2018). Analysis of spatial-temporal variation in NPP based on hydrothermal conditions in the Lancang-Mekong River Basin from 2000 to 2014. Environmental Monitoring and Assessment, 190(6), 2–15. https://doi.org/10.1007/s10661-018-6690-7.
Liang, W., Yang, Y., Fan, D., Guan, H., Zhang, T., Long, D., Zhou, Y., & Bai, D. (2015). Analysis of spatial and temporal patterns of net primary production and their climate controls in China from 1982 to 2010. Agricultural and Forest Meteorology, 204, 22–36. https://doi.org/10.1016/j.agrformet.2015.01.015.
Liu, C., Dong, X., & Liu, Y. (2015). Changes of NPP and their relationship to climate factors based on the transformation of different scales in Gansu, China. CATENA., 125, 190–199. https://doi.org/10.1016/j.catena.2014.10.027.
Liu, Y., Yang, Y., Wang, Q., Du, X., Li, J., Gang, C. H., Zhou, W., & Wang, Z. H. (2019). Evaluating the responses of net primary productivity and carbon use efficiency of global grassland to climate variability along an aridity gradient. The Science of the Total Environment, 652, 671–682. https://doi.org/10.1016/j.scitotenv.2018.10.295.
Luo, Y. Q., Gerten, D., Le Maire, G., Parton, W. J., Weng, E. S., Zhou, X. H., Keough, C., Beier, C., Ciais, P., Cramer, W., Dukes, J. S., Emmett, B., Janson, P. J., Alan, K., Linder, S., Nepstad, D., & Rustad, L. (2008). Modeled interactive effects of precipitation, temperature, and CO2 on ecosystem carbon and water dynamics in different climatic zones. Global Change Biology, 14, 1986–1999. https://doi.org/10.1111/j.1365-2486.2008.01629.x.
Masoodian, S. A. (2011). Climatology of Iran. Isfahan: University of Isfahan Press (In Persian).
Modarres, R., Sarhadi, A., & Burn, D. H. (2016). Changes of extreme drought and flood events in Iran. Global and Planetary Change, 144, 67–81. https://doi.org/10.1016/j.gloplacha.2016.07.008.
Monteith, J. L. (1972). Solar radiation and productivity in Tropical ecosystem. Journal of Applied Ecology, 9, 747–766. https://doi.org/10.2307/2401901.
Mowll, W., Blumenthal, D. M., Cherwin, K., Smith, A., Symstad, A. J., Vermeire, T., Collin, S. L., Smith, M. D., & Knapp, A. K. (2015). Climatic controls of aboveground net primary production in semi-arid grasslands along a latitudinal gradient portend low sensitivity to warming. Oecologia, 177, 959–969. https://doi.org/10.1007/s00442-015-3232-7.
Neeti, N., & Eastman, J. R. (2011). A contextual Mann-Kendall approach for the assessment of trend significance in image time series. Transactions in GIS, 15, 599–611. https://doi.org/10.1111/j.1467-9671.2011.01280.x.
Rezaei, M., Farajzadeh, M., Mielonenb, T., & Ghavidel, Y. (2019). Analysis of spatio-temporal dust aerosol frequency over Iran based on satellite data. Atmospheric Pollution Research, 10, 508–519. https://doi.org/10.1016/j.apr.2018.10.002.
Running, S.W., Zhao, M., (2015). User’s guide, daily GPP and annual NPP (MOD17A2/A3) products NASA Earth Observing System MODIS Land Algorithm. Version 3.0 for Collection 6 October 7. https://www.ntsg.umt.edu/files/modis/MOD17UsersGuide2015_v3.pdf
Running, S. W., Thornton, P. E., Nemani, R. R., & Glassy, J. M. (2000). Global terrestrial gross and net primary productivity from the earth observing system. In O. Sala, R. Jackson, & H. Mooney (Eds.), Methods in ecosystem science (pp. 44–57). New York: Springer. https://doi.org/10.1007/978-1-4612-1224-9_4.
Saki, M., Soltani Koupaei, S., Tarkesh Esfahani, M., Jafari R., (2018). Spatial and temporal changes of net primary production (NPP) and their relationship with climatic factors from 2000 to 2014 in Isfahan Province. Iranian Journal of Applied Ecology (IJAE). 7, 27-40. http://ijae.iut.ac.ir/article-1-850-en.html (In Persian)
Schubert, P., Lagergren, F., Aurelia, M., Christensen, M., Grelle, A., Heliasz, M., Klemedtsson, L., Lindroth, A., Pilegaard, M., Vesala, M., & Eklundh, L. (2012). Modeling GPP in the Nordic forest landscape with MODIS time series data—comparison with the MODIS GPP product. Remote Sensing of Environment, 126, 136–147. https://doi.org/10.1016/j.rse.2012.08.005.
Sharafati, A., Nabaei, S., & Shahi, D. S. H. (2019). Spatial assessment of meteorological drought features over different climate regions in Iran. International Jornal of Climatology, 2019, 1–21. https://doi.org/10.1002/joc.6307.
Soleimani, A., Hosseini, S. M., Massah Bavani, A. R., Jafari, M., & Francaviglia, R. (2019). Influence of land use and land cover change on soil organic carbon and microbial activity in the forests of northern Iran. Catena, 177, 227–237. https://doi.org/10.1016/j.catena.2019.02.018
Twine, T. E., & Kucharik, C. J. (2009). Climate impacts on net primary productivity trends in natural and managed ecosystems of the central and eastern United States. Agricultural and Forest Meteorology, 149, 2143–2161. https://doi.org/10.1016/j.agrformet.2009.05.012.
Vase, V. K., Dash, G., Sreenath, K. R., Temkar, G., Shailendra, R., Mohammed Koya, K., Divu, D., Dash, S., Pradhan, R. K., Sukhdhane, K. S., & Jayasankar, J. (2018). Spatio-temporal variability of physico-chemical variables,chlorophyll a, and primary productivity in the northern Arabian Sea along India coast. Environmental Monitoring and Assessment, 190(3), 148.2–148.14814. https://doi.org/10.1007/s10661-018-6490-0.
Verbesselt, J., Hyndman, R., Newnham, G., & Culvenor, D. (2009). Detecting trend and seasonal changes in satellite image time series. Remote Sensing of Environment, 114, 106–115. https://doi.org/10.1016/j.rse.2009.08.014.
Wang, X., Li, F., Gao, R., Luo, Y., & Liu, T. (2014, 104). Predicted NPP spatiotemporal variations in a semiari steppe watershed for historical and trending. Journal of Arid Environments, 67–79. https://doi.org/10.1016/j.jaridenv.2014.02.003.
Wang, X., Tan, K., Chen, B., & Du, P. (2017). Assessing the spatiotemporal variation and impact factors of net primary productivity in China. Scientific Reports, 7, 44415. https://doi.org/10.1038/srep44415.
Wen, Y., Liu, X., Baic, Y., Sund, Y., Yang, J., Lin, K., Pei, F., & Yan, Y. (2019). Determining the impacts of climate change and urban expansion on terrestrial net primary production in China. Journal of Environmental Management, 240, 75–83. https://doi.org/10.1016/j.jenvman.2019.03.071.
Wu, S., Zhou, S., Chen, D., Wei, Z., Liang, D., & Li, X. (2014). Determining the contributions of urbanization and climate change to NPP variations over the last decade in the Yangtze River Delta, China. Science Total Environmental, 427, 397–406. https://doi.org/10.1016/j.scitotenv.2013.10.128.
Yang, J., Zhang, X. C., Hui, L. Z., & Yu, J. U. (2017). Nonlinear variations of net primary productivity and its relationship with climate and vegetation phenology, China. Forests, 8, 361, 2-21. https://doi.org/10.3390/f8100361.
Zhang, C., & Ren, W. (2017). Complex climatic and CO2 controls on net primary productivity of temperate dry land ecosystems over central Asia during 1980–2014. Journal of Geophysical Research – Biogeosciences, 122, 2356–2374. https://doi.org/10.1002/2017JG003781.
Zhang, G., Kang, Y., Han, G., & Sakurai, K. (2011). Effect of climate change over the past century on the distribution, extent, and NPP of ecosystems of Inner Mongolia. Global Change Biology, 17, 377–389. https://doi.org/10.1111/j.1365-2486.2010.02237.x.
Zhang, M., Lin, H., Sun, H., & Cai, Y. (2019). Estimation of vegetation productivity using Landsat 8 time series in a heavily urbanized area, Central China. Remote Sensing, 11(2), 133. https://doi.org/10.3390/rs11020133.
Zhang, R., & Zhou, y., Luo, H., Wang, F., & Wang, S. (2017). Estimation and analysis of spatiotemporal dynamics of the net primary productivity integrating efficiency model with process model in karst area. Remote Sensing, 9(5), 477. https://doi.org/10.3390/rs9050477
Zhao, M. S., & Running, S. W. (2010). Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science., 329, 940–943. https://doi.org/10.1126/science.1192666.
Zhao, M., Heinsch, F. A., Nemani, R. R., & Running, S. W. (2005). Improvements of the MODIS terrestrial gross and net primary production global data set. Remote Sensing of Environment, 95, 164–176. https://doi.org/10.1016/j.rse.2004.12.011.
Zhao, N., Currit, N., & Samson, E. (2011). Net primary production and gross domestic product in China derived from satellite imagery. Ecological Economics, 70, 921–928. https://doi.org/10.1016/j.ecolecon.2010.12.023.
Zhao, F., Wu, Y., Sivakumar, B., Long, A., Qiu, L., Chen, J., Wang, L., Liu, S., & Hu, H. (2019). Climatic and hydrologic controls on net primary production in a semiarid loess watershed. Journal of Hydrology, 568, 803–815. https://doi.org/10.1016/j.jhydrol.2018.11.031.
Websites:
IRIMO (2019). Iran meteorological organization website. http://irimo.ir/eng/index.php. Accessed Jun 2019.
National Aeronautics and Space Administration. https://search.earthdata.nasa.gov/search
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Kamali, A., Khosravi, M. & Hamidianpour, M. Spatial–temporal analysis of net primary production (NPP) and its relationship with climatic factors in Iran. Environ Monit Assess 192, 718 (2020). https://doi.org/10.1007/s10661-020-08667-7
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10661-020-08667-7