Land Surface Temperature May Have a Greater Impact than Air Temperature on the Autumn Phenology in the Tibetan Plateau
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data
2.3. Methods
2.3.1. Preprocessing of NDVI Data
2.3.2. Dynamic Threshold Method
2.3.3. Theil-Sen Trend Analysis and Mann-Kendall (MK) Test
2.3.4. Rescaled Range Analysis
- Mean sequence:
- Cumulative deviation:
- Extreme deviation:
- Standard deviation:
2.3.5. Partial Correlation Analysis
3. Results
3.1. Spatial Patterns of Autumn Phenology
3.2. Spatiotemporal Variation of Autumn Phenology
3.3. Consistency of Autumn Phenology Trends
3.4. Relationship between Altitude and Autumn Phenology
3.5. Response of Autumn Phenology to Climatic Factors
4. Discussion
4.1. Indirect Validation of the EOS
4.2. Temporal and Spatial Pattern of Autumn Phenology
4.3. Response of Autumn Vegetation to Climate Change
4.4. Analysis of Dominant Factors Affecting Autumn Phenology
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- IPCC. Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; IPCC: Geneva, Switzerland, 2022. [Google Scholar]
- United Nations Environment Programme. Emissions Gap Report 2023: Broken Record: Temperatures Hit New Highs, Yet World Fails to Cut Emissions (Again); United Nations Environment Programme: Nairobi, Kenya, 2023. [Google Scholar]
- Zhai, P.M.; Yu, R.; Zhou, B.Q.; Chen, Y.; Guo, J.; Lu, Y. Research Progress in Impact of 1.5 °C Global Warming on Global and Regional Scales. Adv. Clim. Chang. Res. 2022, 13, 465–472. [Google Scholar] [CrossRef]
- Piao, S.; Liu, Q.; Chen, A.; Janssens, I.A.; Fu, Y.; Dai, J.; Liu, L.; Lian, X.; Shen, M.; Zhu, X. Plant phenology and global climate change: Current progresses and challenges. Global Chang. Biol. 2019, 25, 1922–1940. [Google Scholar] [CrossRef] [PubMed]
- Gao, X.; Zhao, D.S. Impacts of climate change on vegetation phenology over the Great Lakes Region of Central Asia from 1982 to 2014. Sci. Total Environ. 2022, 845, 157227. [Google Scholar] [CrossRef]
- Wang, Z.; Fu, B.; Wu, X.; Li, Y.; Feng, Y.; Wang, S.; Wei, F.; Zhang, L. Vegetation resilience does not increase consistently with greening in China’s Loess Plateau. Commun. Earth Environ. 2023, 4, 336. [Google Scholar] [CrossRef]
- Xu, X.; Riley, W.J.; Koven, C.D.; Jia, G.; Zhang, X. Earlier leaf-out warms air in the north. Nat. Clim. Chang. 2020, 10, 370–375. [Google Scholar] [CrossRef]
- Richardson, A.D.; Keenan, T.F.; Migliavacca, M.; Ryu, Y.; Sonnentaf, O.; Toomey, M. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agric. For. Meteorol. 2013, 169, 156–173. [Google Scholar] [CrossRef]
- Wang, M.; Luo, Y.; Zhang, Z.; Xie, Q.; Wu, X.; Ma, X. Recent advances in remote sensing of vegetation phenology: Retrieval algorithm and validation strategy. Natl. Remote Sens. Bull. 2022, 26, 431–455. [Google Scholar] [CrossRef]
- Peng, D.; Zhang, X.; Zhang, B.; Liu, L.; Liu, X.; Huete, A.; Huang, W.; Wang, S.; Luo, S.; Zhang, X.; et al. Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States. ISPRS J. Photogramm. Remote Sens. 2017, 132, 185–198. [Google Scholar] [CrossRef]
- Xi, X.; Zhao, G.X. Chlorophyll content in winter wheat: Inversion and monitoring based on UAV multi-spectral remote sensing. Chin. Agric. Sci. Bull. 2020, 36, 119–126. [Google Scholar] [CrossRef]
- Julien, Y.; Sobrino, J.A. Global land surface phenology trends from GIMMS database. Int. J. Remote Sens. 2009, 30, 3495–3513. [Google Scholar] [CrossRef]
- Wu, L.Z.; Ma, X.F.; Dou, X.; Zhu, J.T.; Zhao, C.Y. Impacts of climate change on vegetation phenology and net primary productivity in arid Central Asia. Sci. Total Environ. 2021, 796, 149055. [Google Scholar] [CrossRef]
- Doussoulin-Guzmán, M.A.; Pérez-Porras, F.J.; Triviño-Tarradas, P.; Rios-Mesa, A.; Garcia-Ferrer, P.; Mesas-Carrascosa, F.J. Grassland Phenology Response to Climate Conditions in Biobio, Chile from 2001 to 2020. Remote Sens. 2022, 14, 475. [Google Scholar] [CrossRef]
- Bradley, A.V.; Gerard, F.F.; Barbier, N.; Weedon, G.P.; Anderson, L.O.; Huntingford, C.; Aragao, L.; Zelazowski, P.; Arai, E. Relationships between phenology, radiation and precipitation in the Amazon region. Glob. Chang. Biol. 2011, 17, 2245–2260. [Google Scholar] [CrossRef]
- Duarte, L.; Teodoro, A.C.; Monteiro, A.T.; Cunha, M.; Goncalves, H. QPhenoMetrics: An open source software application to assess vegetation phenology metrics. Comput. Electron. Agric. 2018, 148, 82–94. [Google Scholar] [CrossRef]
- Gao, B.C.; Li, R.R. Quantitative improvement in the estimates of NDVI values from remotely sensed data by correcting thin cirrus scattering effects. Remote Sens. Environ. 2000, 74, 494–502. [Google Scholar] [CrossRef]
- Skakun, S.; Franch, B.; Vermote, E.; Roger, J.C.; Becker-Reshef, I.; Justice, C.; Kussul, N. Early season large-area winter crop mapping using MODIS NDVI data, growing degree days information and a Gaussian mixture model. Remote Sens. Environ. 2017, 195, 244–258. [Google Scholar] [CrossRef]
- Liu, Q.; Fu, Y.H.; Zhu, Z.; Liu, Y.; Liu, Z.; Huang, M.; Janssens, I.A.; Piao, S. Delayed autumn phenology in the Northern Hemisphere is related to change in both climate and spring phenology. Glob. Chang. Biol. 2016, 22, 3702–3711. [Google Scholar] [CrossRef] [PubMed]
- Garonna, I.; de Jong, R.; Schaepman, M.E. Variability and evolution of global land surface phenology over the past three decades (1982–2012). Glob. Chang. Biol. 2016, 22, 1456–1468. [Google Scholar] [CrossRef] [PubMed]
- Linderholm, H.W. Growing season changes in the last century. Agric. For. Meteorol. 2006, 137, 1–14. [Google Scholar] [CrossRef]
- Piao, S.; Fang, J.; Zhou, L.; Ciais, P.; Zhu, B. Variations in satellite-derived phenology in China’s temperate vegetation. Glob. Chang. Biol. 2006, 12, 672–685. [Google Scholar] [CrossRef]
- Yun, J.; Jeong, S.J.; Ho, C.H.; Park, C.E.; Park, H.; Kin, J. Influence of winter precipitation on spring phenology in boreal forests. Glob. Chang. Biol. 2018, 24, 5176–5187. [Google Scholar] [CrossRef] [PubMed]
- Ren, S.L.; Li, Y.T.; Peichl, M. Diverse effects of climate at different times on grassland phenology in mid-latitude of the Northern Hemisphere. Ecol. Indic. 2020, 113, 106260. [Google Scholar] [CrossRef]
- Li, P.; Peng, C.; Wang, M.; Luo, Y.; Li, M.; Zhangg, K.; Zhan, D.; Zhu, Q. dynamics of vegetation autumn phenology and its response to multiple environmental factors from 1982 to 2012 on Qinghai-Tibetan Plateau in China. Sci. Total Environ. 2018, 637, 855–864. [Google Scholar] [CrossRef] [PubMed]
- Chen, X.; Li, B.; Li, Q.; Li, J.; Abdulla, S. Spatio-temporal pattern and changes of evapotranspiration in arid Central Asia and Xinjiang of China. J. Arid. Land 2012, 4, 105–112. [Google Scholar] [CrossRef]
- Jiang, W.; Niu, Z.; Wang, L.; Yao, R.; Gui, X.; Xiang, F.; Ji, Y. Impacts of Drought and Climatic Factors on Vegetation Dynamics in the Yellow River Basin and Yangtze River Basin, China. Remote Sens. 2022, 14, 930. [Google Scholar] [CrossRef]
- Gou, Y.; Jin, Z.; Kou, P.; Tao, Y.; Xu, Q.; Zhu, W.; Tian, H. Mechanisms of climate change impacts on vegetation and prediction of changes on the Loess Plateau, China. Environ. Earth Sci. 2024, 83, 234. [Google Scholar] [CrossRef]
- Chen, X.; An, S.; Inouye, D.W.; Schwartz, M.D. Temperature and snowfall trigger alpine vegetation green-up on the world’s roof. Glob. Chang. Biol. 2015, 21, 3635–3646. [Google Scholar] [CrossRef] [PubMed]
- Sun, H.; Chen, Y.; Xiong, J.; Ye, C.; Yong, Z.; Wang, Y.; He, D.; Xu, S. Relationships between climate change, phenology, edaphic factors, and net primary productivity across the Tibetan Plateau. Int. J. Appl. Earth Obs. Geoinf. 2022, 107, 102708. [Google Scholar] [CrossRef]
- Fu, B.J.; Ouyang, Z.Y.; Shi, P. Current Condition and Protection Strategies of Qinghai-Tibet Plateau Ecological Security Barrier. Bull. Chin. Acad. Sci. 2021, 36, 1298–1306. [Google Scholar] [CrossRef]
- Zhang, Q.; Kong, D.D.; Shi, P.J.; Singh, V.P.; Sun, P. Vegetation phenology on the Qinghai-Tibetan Plateau and its response to climate change (1982–2013). Agric. For. Meteorol. 2018, 248, 408–417. [Google Scholar] [CrossRef]
- Mo, S.G.; Zhang, B.P.; Cheng, W.M. Major Environmental Effects of the Tibetan Plateau. Prog. Geogr. 2004, 23, 88–96. [Google Scholar] [CrossRef]
- Yao, T.D.; Zhu, L.P. The response of environmental changes on Tibetan Plateau to global changes and adaptation strategy. Adv. Earth Sci. 2006, 21, 459–464. [Google Scholar] [CrossRef]
- Piao, S.L.; Cui, M.D.; Chen, A.P.; Wang, X.; Ciais, P.; Liu, J.; Tang, Y. 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. 2011, 151, 1599–1608. [Google Scholar] [CrossRef]
- Chen, D.; Xu, B.; Yao, T.; Guo, Z.; Cui, P.; Chen, F.; Zhang, T. Assessment of past, present and future environmental changes on the Tibetan Plateau. Chin. Sci. Bull. 2015, 60, 3025–3035. [Google Scholar] [CrossRef]
- Ding, Y.H.; Ren, G.Y.; Shi, G.Y. National assessment report of climate change (l): Climate change in China and its future trend. Adv. Clim. Chang. Res. 2006, 2, 3–8. [Google Scholar]
- Wang, X.Y.; Wu, C.Y.; Peng, D.L.; Gonsamo, A.; Liu, Z.J. Snow cover phenology affects alpine vegetation growth dynamics on the Tibetan Plateau: Satellite observed evidence, impacts of different biomes, and climate drivers. Agric. For. Meteorol. 2018, 256–257, 61–74. [Google Scholar] [CrossRef]
- Zu, J.; Zhang, Y.; Huang, K.; Liu, Y.; Chen, N.; Cong, N. Biological and climate factors co-regulated spatial-temporal dynamics of vegetation autumn phenology on the Tibetan Plateau. Int. J. Appl. Earth Obs. Geoinf. 2018, 69, 198–205. [Google Scholar] [CrossRef]
- Chen, X.; Wang, L. Progress in remote sensing phenological research. Prog. Geog. 2009, 28, 33–40. [Google Scholar] [CrossRef]
- Shao, Z.; Zhou, W.; Li, F.; Zhou, X.; Yang, F. Spatiotemporal variation of vegetation phenophase and its response to climate change in Micang Mountains from 2003 to 2018. Acta Ecol. Sin. 2021, 41, 3701–3712. [Google Scholar] [CrossRef]
- Shen, M.; Tang, Y.; Jin, C.; Zhu, X.; Zheng, Y. Influences of temperature and precipitation before the growingseason on spring phenology in grasslands of the central and eastern Qinghai-Tibetan Plateau. Agric. For. Meteorol. 2011, 151, 1711–1722. [Google Scholar] [CrossRef]
- Ding, M.; Zhang, Y.; Sun, X.; Liu, L.; Wang, Z. Spatiotemporal variation in alpine grassland phenology in the Qinghai-Tibetan Plateau from 1999 to 2009. Chin. Sci. Bull. 2012, 57, 3185–3194. [Google Scholar] [CrossRef]
- Jonsson, P.; Eklundh, L. Seasonality extraction by function fitting to time-series of satellite sensor data. IEEE Trans. Geosci. Remote Sens. 2002, 40, 1824–1832. [Google Scholar] [CrossRef]
- Su, Y.; Zhang, F.; Liu, B. Response of forest vegetation phenology to climate change in Xiaoxing’an Mountains of northeastern China. J. Beijing For. Univ. 2023, 45, 34–47. [Google Scholar] [CrossRef]
- Ying, H.; Zhang, H.Y.; Zhao, J.J.; Shan, Y.; Zhang, Z.; Guo, X.; Rihan, W.; Deng, G. Effects of spring and summer extreme climate events on the autumn phenology of different vegetation types of Inner Mongolia, China, from 1982 to 2015. Ecol. Indic. 2020, 111, 105974. [Google Scholar] [CrossRef]
- Piao, S.; Liu, Z.; Wang, T.; Peng, S.; Ciais, P.; Huang, M.; Ahlstrom, A.; Burkhart, J.F.; Chevallier, F.; Janssens, I.A.; et al. Weakening temperature control on the interannual variations of spring carbon uptake across northern lands. Nat. Clim. Chang. 2017, 7, 359–363. [Google Scholar] [CrossRef]
- Liu, M.; Li, Y.; He, B.; Zhao, W. Spatiotemporal Dynamics of Grassland Phenology and Sensitivity to Extreme Precipitation in Autumn in Qinghai-Tibetan Plateau. Res. Soil Water Conserv. 2023, 30, 353–363. [Google Scholar] [CrossRef]
- Yuan, M.; Zhao, L.; Lin, A.; Li, Q.; She, D.; Qu, S. How do climatic and non-climatic factors contribute to the dynamics of vegetation autumn phenology in the Yellow River Basin, China? Ecol. Indic. 2020, 112, 106112. [Google Scholar] [CrossRef]
- Ma, R.; Shen, X.; Zhang, J.; Xia, C.; Liu, Y.; Wu, L.; Wang, Y.; Jiang, M.; Lu, X. Variation of vegetation autumn phenology and its climatic drivers in temperate grasslands of China. Int. J. Appl. Earth Obs. Geoinf. 2022, 114, 103064. [Google Scholar] [CrossRef]
- Yang, X.; Fan, F. Land surface phenology and its response to climate change in the Guangdong-Hong Kong-Macao Greater Bay Area during 2001–2020. Ecol. Indic. 2023, 154, 10728. [Google Scholar] [CrossRef]
- Xie, B.N.; Qin, Z.F.; Wang, Y.; Chang, Q.R. Monitoring vegetation phenology and their response to climate change on Chinese Loess Plateau based on remote sensing. Trans. Chin. Soc. Agric. Eng. 2015, 31, 153–160. [Google Scholar] [CrossRef]
- Jiao, K.; Gao, J.; Wu, S. Climatic determinants impacting the distribution of greenness in China: Regional differentiation and spatial variability. Int. J. Biometeorol. 2019, 63, 523–533. [Google Scholar] [CrossRef]
- Shen, X.; Jiang, M.; Lu, X.; Liu, X.; Liu, B.; Zhang, J.; Wang, X.; Tong, S.; Lei, G.; Wang, S.; et al. Aboveground biomass and its spatial distribution pattern of herbaceous marsh vegetation in China. Sci. China Earth Sci. 2021, 64, 1115–1125. [Google Scholar] [CrossRef]
- Fang, W.; Huang, S.; Huang, Q.; Huang, G.; Wang, H.; Leng, G.; Wang, L. Probabilistic assessment of remote sensing-based terrestrial vegetation vulnerability to drought stress of the Loess Plateau in China. Remote Sens Environ. 2019, 232, 111290. [Google Scholar] [CrossRef]
- Yue, P.; Zhang, Q.; Ren, X.; Ren, X.; Yang, Z.; Li, H.; Yang, Y. Environmental and biophysical effects of evapotranspiration in semiarid grassland and maize cropland ecosystems over the summer monsoon transition zone of China. Agric. Water Manag. 2022, 264, 107462. [Google Scholar] [CrossRef]
- Shen, X.; Liu, B.; Li, G.; Zhou, D. lmpact of Climate Change on Temperate and Alpine Grasslands in China during 1982–2006. Adv. Meteorol. 2015, 10, 180614. [Google Scholar] [CrossRef]
- Wang, Y.; Shen, X.; Jiang, M.; Lu, X. Vegetation Change and Its Response to Climate Change between 2000 and 2016 in Marshes of the Songnen Plain, Northeast China. Sustainability 2020, 12, 3569. [Google Scholar] [CrossRef]
- Peng, S.; Piao, S.; Ciais, P.; Myneni, R.B.; Chen, A.; Chevallier, F.; Dolman, J.A.; Janssens, I.A.; Peñuelas, J.; Zhang, G.; et al. Asymmetric effects of daytime and night-time warming on Northern Hemisphere vegetation. Nature 2013, 501, 88–92. [Google Scholar] [CrossRef]
- Xia, H.; Li, A.; Feng, G. The Effects of Asymmetric Diurnal Warming on Vegetation Growth of the Tibetan Plateau over the Past Three Decades. Sustainability 2018, 10, 1103. [Google Scholar] [CrossRef]
- Shen, X.; Liu, Y.; Zhang, J.; Wang, Y.; Ma, R.; Liu, B.; Lu, X.; Jiang, M. Asymmetric impacts of diurnal warming on vegetation carbon sequestration of marshes in the Qinghai Tibet Plateau. Glob. Biogeochem. Cycles 2022, 36, e2022GB007396. [Google Scholar] [CrossRef]
- Huang, P.; Li, Z.; Guo, H. New Advances in the regulation of leaf Senescence by classical and peptide hormones. Front. Plant Sci. 2022, 13, 923136. [Google Scholar] [CrossRef] [PubMed]
- Thomas, P.; Janave, M.T. Effect of temperature on chlorophyllase activity, chlorophyll degradation and carotenoids of Cavendish bananas during ripening. Int. J. Food Sci. Technol. 1992, 27, 57–63. [Google Scholar] [CrossRef]
- Shi, C.; Sun, G.; Zhang, H.; Xiao, B.; Ze, B.; Zhang, N.; Wu, N. Effects of warming on chlorophyll degradation and carbohydrate accumulation of Alpine herbaceous species during plant senescence on the Tibetan Plateau. PLoS ONE 2014, 9, e107874. [Google Scholar] [CrossRef]
- Moore, C.E.; Meacham-Hensold, K.; Lemonnier, P.; Slattery, R.A.; Benjamin, C.; Bernacchi, C.J.; Lawson, T.; Cavanagh, A.P. The effect of increasing temperature on crop photosynthesis: From enzymes to ecosystems. J. Exp. Bot. 2021, 72, 2822–2844. [Google Scholar] [CrossRef]
- Li, X.; Guo, W.; Li, S.; Zhang, J.; Ni, X. The different impacts of the daytime and nighttime land surface temperatures on the alpine grassland phenology. Ecosphere 2021, 12, e03578. [Google Scholar] [CrossRef]
- He, T.; Wu, M.X.; Jia, J.F. Research advances in morphology and anatomy of alpine plants growing in the Qinghai-Tibet Plateau and their adaptations to environment. Acta Ecol. Sin. 2007, 27, 2574–2583. [Google Scholar] [CrossRef]
- Ernakovich, J.G.; Hopping, K.A.; Berdanier, A.B.; Simpson, R.T.; Kachergis, E.J.; Steltzer, H.; Wallenstein, M.D. Predicted responses of arctic and alpine ecosystems to altered seasonality under climate change. Glob. Chang. Biol. 2014, 20, 3256–3269. [Google Scholar] [CrossRef]
- Onwuka, B.; Mang, B. Effects of soil temperature on some soil properties and plant growth. Adv. Plants Agric. Res. 2018, 8, 34–37. [Google Scholar] [CrossRef]
- Reichardt, K.; Timm, L.C. How Plants Absorb Nutrients from the Soil. In Soil, Plant and Atmosphere; Springer Nature: Cham, Switzerland, 2020. [Google Scholar] [CrossRef]
- Pregitzer, K.; King, J. Effects of Soil Temperature on Nutrient Uptake. In Nutrient Acquisition by Plants; BassiriRad, H., Ed.; Ecological Studies; Springer: Berlin/Heidelberg, Germany, 2005; Volume 181, pp. 277–310. [Google Scholar] [CrossRef]
- Shen, X.; Liu, B.; Henderson, M.; Wang, L.; Wu, Z.; Wu, H.; Jiang, M.; Lu, X. Asymmetric effects of daytime and nighttime warming on spring phenology in the temperate grasslands of China. Agric. For. Meteorol. 2018, 259, 240–249. [Google Scholar] [CrossRef]
Remote Sensing Phenological Parameter | Definition | Corresponding Agricultural Phenological Stage | Definition |
---|---|---|---|
Start of the Growing Season (SOS) | The period when photosynthesis begins and green leaf area starts to increase | Emergence/Leaf Out/ Green-up Stage | The period around seedling emergence |
End of the Growing Season (EOS) | The period when photosynthesis approaches zero and green leaf area decreases to its minimum | Senescence/Dormancy Stage | The period when chlorophyll content stabilizes at a lower level compared to other periods |
Vegetation Type | Tmax | Tmin | Precipitation | Daytime LST | Nighttime LST |
---|---|---|---|---|---|
forest | 12.10 | 22.55 | 20.72 | 25.62 | 19.01 |
meadow | 16.02 | 18.88 | 16.66 | 27.78 | 20.66 |
shrub | 14.60 | 19.38 | 17.86 | 28.36 | 19.79 |
steppe | 14.93 | 24.08 | 22.77 | 20.60 | 17.62 |
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Tang, H.; Sun, X.; Zhou, X.; Li, C.; Ma, L.; Liu, J.; Ding, Z.; Liu, S.; Yu, P.; Jia, L.; et al. Land Surface Temperature May Have a Greater Impact than Air Temperature on the Autumn Phenology in the Tibetan Plateau. Forests 2024, 15, 1476. https://doi.org/10.3390/f15081476
Tang H, Sun X, Zhou X, Li C, Ma L, Liu J, Ding Z, Liu S, Yu P, Jia L, et al. Land Surface Temperature May Have a Greater Impact than Air Temperature on the Autumn Phenology in the Tibetan Plateau. Forests. 2024; 15(8):1476. https://doi.org/10.3390/f15081476
Chicago/Turabian StyleTang, Hanya, Xizao Sun, Xuelin Zhou, Cheng Li, Lei Ma, Jinlian Liu, Zhi Ding, Shiwei Liu, Pujia Yu, Luyao Jia, and et al. 2024. "Land Surface Temperature May Have a Greater Impact than Air Temperature on the Autumn Phenology in the Tibetan Plateau" Forests 15, no. 8: 1476. https://doi.org/10.3390/f15081476