Abstract
Understanding the seasonal behaviour of a subtropical forest and its inter-annual variation is crucial to understanding and monitoring its ecosystem function in the context of global warming. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index dataset, a wavelet transform method was used to investigate the inter-annual variations of vegetation phenology in a subtropical mountain and hill region in Fujian, China, during 2001–2010. The results show a distinct inter-annual variation of vegetation phenology related to climate variability even if most areas presented non-significant trends. The start dates significantly advanced and end dates delayed in 2003 and 2008, due to anomalously warm conditions. There was generally a gradient of increasing start dates, and earlier end dates of vegetation growing season, due to colder temperatures at higher altitudes. However, the altitudinal phenology relationship also depends on its corresponding rainfall conditions. Earlier start dates were observed at higher altitudes during rainfall deficit years such as 2008, which coincides with relatively abundant rainfall at higher altitudes. This paper reveals that vegetation phenology was coupled with altitudinal gradient, with distinct responses at different combinations of alternate temperature and precipitation conditions variability.
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Horion S, Cornet Y, Erpicum M, et al. Studying interactions between climate variability and vegetation dynamic using a phenology based approach. Int J Appl Earth Obs Geoinf, 2013, 20: 20–32
Allen C D, Breshears D D. Drought-induced shift of a forest-wood-land ecotone: rapid landscape response to climate variation. Proc Natl Acda Sci USA, 1998, 95: 14839
Wang H L, Gan Y T, Wang R Y, et al. Phenological trends in winter wheat and spring cotton in response to climate changes in northwest China. Agric For Meteorol, 2008, 148: 1242–1251
Pennec A, Gond V, Sabatier D. Tropical forest phenology in French Guiana from MODIS time series. Remote Sens Lett, 2011, 2: 337–345
Julien Y, Sobrino J A. Global land surface phenology trends from GIMMS database. Int J Remote Sens, 2009, 30: 3495–3513
Ding M J, Zhang Y L, Sun X M, et al. Spatiotemporal variation in alpine grassland phenology in the Qinghai-Tibetan Plateau from 1999 to 2009. Chin Sci Bull, 2013, 58: 396–405
Chen X Q, Hu B, Yu R. Spatial and temporal variation of phenological growing season and climate change impacts in temperate eastern China. Glob Change Biol, 2005, 11: 1118–1130
Busetto L, Colombo R, Migliavacca M, et al. Remote sensing of larch phenological cycle and analysis of relationships with climate in the Alpine region. Glob Change Biol, 2010, 16: 2504–2517
Jeong S J, Ho C H, Gim H J, et al. Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008. Glob Change Biol, 2011, 17: 2385–2399
Bradley B A, Jacob R W, Hermance J F, et al. A curve fitting procedure to derive inter-annual phenologies from time series of noisy satellite NDVI data. Remote Sens Environ, 2007, 106: 137–145
Sobrino J A, Julien Y, Morales L. Changes in vegetation spring dates in the second half of the twentieth century. Int J Remote Sens, 2011, 32: 5247–5265
Ivits E, Cherlet M, Toth G, et al. Combining satellite derived phenology with climate data for climate change impact assessment. Glob Planet Change, 2012, 85–86: 85–97
Jeganathan C, Dash J, Atkinson P M. Mapping the phenology of natural vegetation in India using a remote sensing-derived chlorophyll index. Int J Remote Sens, 2011, 31: 5777–5796
Chang C T, Lin T C, Wang S F, et al. Assessing growing season be ginning and end dates and their relation to climate in Taiwan using satellite data. Int J Remote Sens, 2011, 32: 5035–5058
Kramer K, Leinonen I, Loustau D. The importance of phenology for the evaluation of impact of climate change on growth of boreal, temperate and Mediterranean forests ecosystems: An overview. Int J Biometeorol, 2000, 44: 67–75
Penuelas J, Rutishauser T, Filella I. Phenology feedbacks on climate change. Science, 2009, 324: 887–888
Jentsch A, Kreyling J, Boettcher-Treschkow J, et al. Beyond gradual warming: extreme weather events alter flower phenology of European grassland and heath species. Glob Change Biol, 2009, 15: 837–849
Crimmins T M, Crimmins M A, David B C. Complex responses to climate drivers in onset of spring flowering across a semiarid elevation gradient. J Eeol, 2010, 98: 1042–1051
Jenerette G D, Scott R L, Huete A R. Functional differences between summer and winter season rain assessed with MODIS-derived phenology in a semi-arid region. J Veg Sci, 2010, 21: 16–30
Lloyd A H, Bunn A G, Berner L. A latitudinal gradient in tree growth response to climate warming in the Siberian taiga. Glob Change Biol, 2011, 17: 1935–1945
Lu S J. Fujian Climate (in Chinese). Beijing: China Meteorological Press, 1999. 45–54
Gao Z W. Research on Forest Resource Management (in Chinese). Fuzhou: The Cartographic Publisher of Fujian, 2004. 372
The People’s Government of Fujian. Fujian Yearbook (in Chinese). Fuzhou: The People’s Publisher of Fujian, 2010
Justice C O, Vermote E, Townshend J R G, et al. The Moderate Resolution Imaging Spectroradiometer (MODIS): Land remote sensing for global change research. IEEE Trans Geosci Remote Sens, 1998, 36: 1228–1249
Waring R H, Coops N C, Fan W, et al. MODIS enhanced vegetation index predicts tree species richness across forested ecoregions in the contiguous USA. Remote Sens Environ, 2006, 103: 218–226
Sakamoto T, Yokozawa M, Toritani H, et al. A crop phenology detection method using time-series MODIS data. Remote Sens Environ, 2005, 96: 366–374
Galford G L, Mustard J F, Melillo J, et al. Wavelet analysis of MODIS time series to detect expansion and intensification of row-crop agriculture in Brazil. Remote Sens Environ, 2008, 112: 576–587
Setiawan Y D, Yoshino K, Philpot W D. Characterizing temporal vegetation dynamics of land use in regional scale of Java Island, Indonesia. J Land Use Sci, 2011: 1–30
Alados C L, Puigdefábregas, Martínez-Fernández J. Ecological and socio-economical thresholds of land and plant-community degradation in semi-arid Mediterranean areas of southeastern Spain. J Arid Environ, 2011, 75: 1368–1376
Martínez B, Gilabert M A. Vegetation dynamics from NDVI time series analysis using the wavelet transform. Remote Sens Environ, 2009, 113: 1823–1842
Singh A, Dutta R, Stein A, et al. A wavelet-based approach for monitoring plantation crops (tea: Camellia sinensis) in North East India. Int J Remote Sens, 2012, 33: 4982–5008
White M A, Thornton P E, Running S W. A continental phenology model for monitoring vegetation responses to interannual climatic variability. Glob Biogeochem Cycles, 1997, 11: 217–234
Fisher J I, Mustard J F, Vadeboncoeur M A. Green leaf phenology at Landsat resolution: Scaling from the field to the satellite. Remote Sens Environ, 2006, 100: 265–279
Sen P K. Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc, 1968, 324: 1379–1389
Japan Meteorological Agency. Annual Report on the Climate System 2008. 2008
Zhang F, Gao H, Cui X. Frequency of extreme high temperature days in China, 1961–2003. Weather, 2008, 2: 46–49
Walther G R, Post E, Convey P, et al. Ecological responses to recent climate change. Nature, 2002, 416: 389–395
Menzel A, Sparks T H, Estrella N, et al. European phenological response to climate change matches the warming pattern. Glob Change Biol, 2006, 12: 1969–1976
Cleland E E, Chuine I, Menzel A, et al. Shifting plant phenology in response to global change. Trends Ecol Evol, 2007, 22: 357–365
Siebert S, Ewert F. Spatiotemporal patterns of phenological development in Germany in relation to temperature and day length. Agric For Meteorol, 2011, 152: 44–57
Dinis L T, Peixoto F, Pinto T, et al. Study of morphological and phenological diversity in chestnut trees (“Judia” variety) as a function of temperature sum. Environ Exp Bot, 2011, 70: 110–120
Van Oort P A J, Zhang T Y, de Vries M E, et al. Correlation between temperature and phenology prediction error in rice (Oryza sativa L.). Agric For Meteorol, 2011, 151: 1545–1555
Piao S L, Fang J Y, Zhou L M, et al. Variations in satellite-derived phenology in China’s temperate vegetation. Glob Change Biol, 2006, 12: 672–685
Zhang X, Friedl M A, Schaaf C B, et al. Climate controls on vegetation phenological patterns in northern mid- and high latitudes inferred from MODIS data. Glob Change Biol, 2004, 10: 1133–1145
Piao S L, Cui M D, Chen A P, et al. Altitude and temperature dependence of change in the spring vegetation green-up date from 1982 to 2006 in the Qinghai-Xizang Plateau. Agric For Meteorol, 2012, 151: 1599–1608
Elmore A J, Guinn S M, Minsley B J, et al. Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests. Glob Change Biol, 2012, 18: 656–674
Iversen M, Bråthen K A, Yoccoz Nigel G, et al. Predictors of plant phenology in a diverse high-latitude alpine landscape: Growth forms and topography. J Veg Sci, 2009, 20: 903–915
Beurs K M, Henebry G M. Phenological Research. Dordrecht: Springer Netherlands, 2010. 177–208
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Qiu, B., Zhong, M., Tang, Z. et al. Spatiotemporal variability of vegetation phenology with reference to altitude and climate in the subtropical mountain and hill region, China. Chin. Sci. Bull. 58, 2883–2892 (2013). https://doi.org/10.1007/s11434-013-5847-6
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DOI: https://doi.org/10.1007/s11434-013-5847-6