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A comprehensive analysis of phenological changes in forest vegetation of the Funiu Mountains, China

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Abstract

This paper reports the phenological response of forest vegetation to climate change (changes in temperature and precipitation) based on Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) time-series images from 2000 to 2015. The phenological parameters of forest vegetation in the Funiu Mountains during this period were determined from the temperature and precipitation data using the Savitzky–Golay filter method, dynamic threshold method, Mann-Kendall trend test, the Theil-Sen estimator, ANUSPLIN interpolation and correlation analyses. The results are summarized as follows: (1) The start of the growing season (SOS) of the forest vegetation mainly concentrated in day of year (DOY) 105–120, the end of the growing season (EOS) concentrated in DOY 285–315, and the growing season length (GSL) ranged between 165 and 195 days. There is an evident correlation between forest phenology and altitude. With increasing altitude, the SOS, EOS and GSL presented a significant delayed, advanced and shortening trend, respectively. (2) Both SOS and EOS of the forest vegetation displayed the delayed trend, the delayed pixels accounted for 76.57% and 83.81% of the total, respectively. The GSL of the forest vegetation was lengthened, and the lengthened pixels accounted for 61.21% of the total. The change in GSL was mainly caused by the decrease in spring temperature in the region. (3) The SOS of the forest vegetation was significantly partially correlated with the monthly average temperature in March, with most correlations being negative; that is, the delay in SOS was mainly attributed to the temperature decrease in March. The EOS was significantly partially correlated with precipitation in September, with most correlations being positive; that is, the EOS was clearly delayed with increasing precipitation in September. The GSL of the forest vegetation was influenced by both temperature and precipitation throughout the growing season. For most regions, GSL was most closely related to the monthly average temperature and precipitation in August.

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References

  • And D R H, Frans L M, 2006. Regional Kendall test for trend. Environmental Science & Technology, 40(13): 4066–4073.

    Article  Google Scholar 

  • Chen X, Yu R, 2007. Spatial and temporal variations of the vegetation growing season in warm-temperate eastern China during 1982 to 1999. Acta Geographica Sinica, 62(1): 41–51. (in Chinese)

    Google Scholar 

  • Cong N, Wang T, Nan H et al., 2013. Changes in satellite-derived spring vegetation green-up date and its linkage to climate in China from 1982 to 2010: A multi-method analysis. Global Change Biology, 19(3): 881–891.

    Article  Google Scholar 

  • Cui Y P, 2013. Preliminary estimation of the realistic optimum temperature for vegetation growth in China. Environmental Management, 52(1): 151–162.

    Article  Google Scholar 

  • Dai J, Wang H, Ge Q, 2013. The decreasing spring frost risks during the flowering period for woody plants in temperate area of eastern China over past 50 years. Journal of Geographical Sciences, 23(4): 641–652.

    Article  Google Scholar 

  • Ding S, Lu X, 2006. Comparison of plant flora of Funiu Mountain and Jigong Mountain natural reserves. Geographical Research, 25(1): 62–70. (in Chinese)

    Google Scholar 

  • Fan Y, Hu N, Ding S et al., 2008. A study on the classification of plant functional types based on the dominant herbaceous species in forest ecosystem at Funiu Mountain national natural reserve. Acta Ecologica Sinica, 28(7): 3092–3101. (in Chinese)

    Google Scholar 

  • Forkel M, Migliavacca M, Thonicke K et al., 2015. Codominant water control on global interannual variability and trends in land surface phenology and greenness. Global Change Biology, 21(9): 3414–3435.

    Article  Google Scholar 

  • Gill A L, Gallinat A S, Sanders-Demoot R et al., 2015. Changes in autumn senescence in northern hemisphere deciduous trees: A meta-analysis of autumn phenology studies. Annals of Botany, 116(6): 875–888.

    Article  Google Scholar 

  • Ivan N B, Alexander A M, Mikhail Y et al., 2018. Climate warming as a possible trigger of Keystone Mussel population decline in Oligotrophic Rivers at the continental scale. Scientific Reports, 8: 35. doi: 10.1038/s41598-017-18873-y

    Article  Google Scholar 

  • Ji J, Huang M, Liu Q, 2005. Modeling studies of response mechanism of steppe productivity to climate change in middle latitude semiarid regions in China. Acta Meteorologica Sinica, 63(3): 257–266. (in Chinese)

    Google Scholar 

  • Jordan R M, Nathan J S, Aimée T C et al., 2017. Elevation alters ecosystem properties across temperate treelines globally. Nature, 542: 91–95.

    Article  Google Scholar 

  • Jong R D, Bruin S D, Wit A D et al., 2011. Analysis of monotonic greening and browning trends from global NDVI time-series. Remote Sensing of Environment, 115(2): 692–702.

    Article  Google Scholar 

  • Jönsson P, Eklundh L, 2002. Seasonality extraction by function fitting to time-series of satellite sensor data. IEEE Transactions on Geoscience and Remote Sensing, 40(8): 1824–1832.

    Article  Google Scholar 

  • Jönsson P, Eklundh L, 2004. Timesat: A program for analyzing time-series of satellite sensor data. Computers & Geosciences, 30(8): 833–845.

    Article  Google Scholar 

  • Julien Y, Sobrino J A, 2009. Global land surface phenology trends from GIMMS database. International Journal of Remote Sensing, 30(13): 3495–3513.

    Article  Google Scholar 

  • King D A, 2004. Environment-climate change science: Adapt, mitigate, or ignore? Science, 303(5655): 176–177.

    Article  Google Scholar 

  • Kong D, Zhang Q, Huang W et al., 2017. Vegetation phenology change in Tibetan Plateau from 1982 to 2013 and its related meteorological factors. Acta Geographica Sinica, 72(1): 39–52. (in Chinese)

    Google Scholar 

  • Liu F, 2015. Temporal-spatial variations of temperature in Chinese inland based on GIS and multivariate statistical method [D]. Lanzhou: Lanzhou University.

  • Liu Z, Li L, Mc Vicar T R et al., 2008. Introduction of the professional interpolation software for meteorology data: ANUSPLINN. Meteorological Monthly, 34(2): 92–100. (in Chinese)

    Google Scholar 

  • Luo Z, Yu S, 2017. Spatiotemporal variability of land surface phenology in China from 2001–2014. Remote Sens., 9: 65. doi: 10.3390/rs9010065.

    Article  Google Scholar 

  • Ma J, 2004. Laws of soil vertical variations on southern slope of Funiu Mt.: Simultaneous study on north boundary of subtropical zone. Acta Geographica Sinica, 59(6): 998–1011. (in Chinese)

    Google Scholar 

  • Ma X, Chen S, Deng J et al., 2016. Vegetation phenology dynamics and its response to climate change on the Tibetan Plateau. Acta Prataculturae Sinica, 25(1): 13–21. (in Chinese)

    Google Scholar 

  • Mu S, Li J, Chen Y et al., 2012. Spatial differences of variations of vegetation coverage in Inner Mongolia during 2001–2010. Acta Geographica Sinica, 67(9): 1255–1268. (in Chinese)

    Google Scholar 

  • Nemani R, Keeling C D, Hashimoto H et al., 2003. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science, 300(5625): 1560–1563.

    Article  Google Scholar 

  • Pau S, Wolkovich E M, Cook B I et al., 2011. Predicting phenology by integrating ecology, evolution and climate science. Global Change Biology, 17(12): 3633–3643.

    Article  Google Scholar 

  • Richardson A D, Keenan T F, Migliavacca M et al., 2013. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agricultural and Forest Meteorology, 169(3): 156–173.

    Article  Google Scholar 

  • Sen P K, 1968. Estimates of the regression coefficient based on Kendall's Tau. Journal of the American Statistical Association, 63(324): 1379–1389.

    Article  Google Scholar 

  • Song C, 1994. Scientific Survey of the Funiu Mountain Nature Reserve. Beijing: China Forestry Publishing House. (in Chinese)

    Google Scholar 

  • Tan J, Li A, Lei G, 2016. Contrast on Anusplin and Cokriging meteorological spatial interpolation in southeastern margin of Qinghai-Xizang Plateau. Plateau Meteorology, 35(4): 875–886. (in Chinese)

    Google Scholar 

  • Tao Z, Wang H, Liu Y, 2017. Phenological response of different vegetation types to temperature and precipitation variations in northern China during 1982–2012. International Journal of Remote Sensing, 38(11): 3236–3252.

    Article  Google Scholar 

  • Wang G, Deng W, Yang Y et al., 2011. The advances, priority and developing trend of alpine ecology. Journal of Mountain Science, 29(2): 129–140. (in Chinese)

    Google Scholar 

  • Wang Y, Tian Q, Huang Y, 2013. NDVI difference rate recognition model of deciduous broad-leaved forest based on HJ-CCD remote sensing data. Spectroscopy and Spectral Analysis, 33(4): 1018–1022. (in Chinese)

    Google Scholar 

  • Xia H, Li A, Zhao W et al., 2015. Spatiotemporal variations of forest phenology in the Qinling zone based on remote sensing monitoring, 2001–2010. Progress in Geography, 34(10): 1297–1305. (in Chinese)

    Article  Google Scholar 

  • Xia J, Chen J, Piao S et al., 2014. Terrestrial carbon cycle affected by non-uniform climate warming. Nature Geoscience, 7(3): 173–180.

    Article  Google Scholar 

  • Xia J Y, Wan S Q, 2013. Independent effects of warming and nitrogen addition on plant phenology in the Inner Mongolian steppe. Annals of Botany, 111(6): 1207–1217.

    Article  Google Scholar 

  • Xu Y, Dai J, Wang H et al., 2015. Variation characteristics of main phenophases of natural calendar and analysis of responses to climate change in Harbin in 1985–2012. Geographical Research, 34(9): 1662–1674. (in Chinese)

    Google Scholar 

  • Yu F, Zheng X, Gu X et al., 2008. Comparative study on spatial interpolation of climate elements precision in complex mountainous environment. Journal of Guizhou Meteorology, 32(3): 3–6. (in Chinese)

    Google Scholar 

  • Zhang B, Yao Y, 2016. Implications of mass elevation effect for the altitudinal patterns of global ecology. Journal of Geographical Sciences, 26(7): 871–877.

    Article  Google Scholar 

  • Zhang C, Nan Y, Zhao Y, 2016. Study on vegetation classification based on multi-temporal HJ-1 CCD data: The Changbai Mountain area as a case. Geography and Geo-Information Science, 29(5): 41–44. (in Chinese)

    Google Scholar 

  • Zhang J, Wang Y, Zhu L et al., 2016. Study on change of northern subtropical border in mountainous regions in western Henan province. Journal of Henan University: Natural Science, 46(1): 40–49. (in Chinese)

    Google Scholar 

  • Zhang X, Friedl M C, Strahler A, 2004. Climate controls on vegetation phenological patterns in northern mid- and high latitudes inferred from MODIS data. Global Change Biology, 10(7): 1133–1145.

    Article  Google Scholar 

  • Zhang X, Zhu W, Cui Y et al., 2016. The response of forest dynamics to hydro-thermal change in Funiu Mountain. Geographical Research, 35(6): 1029–1040. (in Chinese)

    Google Scholar 

  • Zheng J, Ge Q, Hao Z et al., 2012. Changes of spring phenodate in Yangtze River Delta region in the past 150 years. Acta Geographica Sinica, 67(1): 45–52. (in Chinese)

    Google Scholar 

  • Zhou L, Tucker C J, Kaufmann R K et al., 2001. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. Journal of Geophysical Research Atmospheres, 106(D17): 20069–20084.

    Article  Google Scholar 

  • Zhu K, Wan M, 1999. Phenology. Changsha: Hunan Education Publishing House. (in Chinese)

    Google Scholar 

  • Zhu L, Xu L, 2011. Analysis of effects of global change on terrestrial ecosystem. Areal Research and Development, 30(2): 161–164. (in Chinese)

    Google Scholar 

  • Zhu Z, Piao S, Myneni R B et al., 2016. Greening of the earth and its drivers. Nature Climate Change, 6(8): 791–796.

    Article  Google Scholar 

  • Zu J, Yang J, 2016. Temporal variation of vegetation phenology in northeastern China. Acta Ecologica Sinica, 36(7): 2015–2023. (in Chinese)

    Google Scholar 

Download references

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Correspondence to Wenbo Zhu.

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Foundation: National Natural Science Foundation of China, No.41671090; National Basic Research Program (973 Program), No.2015CB452702

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Zhu, W., Zhang, X., Zhang, J. et al. A comprehensive analysis of phenological changes in forest vegetation of the Funiu Mountains, China. J. Geogr. Sci. 29, 131–145 (2019). https://doi.org/10.1007/s11442-019-1588-z

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  • DOI: https://doi.org/10.1007/s11442-019-1588-z

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