The impact of extreme weather on the phenology of rubber plantations in Hainan Island, China

LIANG Yuehua; WANG Yichen; WANG Ziqin; CUI Wei; WU Lan; SUN Zhongyi

doi:10.15886/j.cnki.rdswxb.20240055

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Volume 15 Issue 5

Sep. 2024

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Article Navigation > Journal of Tropical Biology > 2024 > 15(5): 547-557

LIANG Yuehua, WANG Yichen, WANG Ziqin, CUI Wei, WU Lan, SUN Zhongyi. The impact of extreme weather on the phenology of rubber plantations in Hainan Island, China[J]. Journal of Tropical Biology, 2024, 15(5): 547-557. doi: 10.15886/j.cnki.rdswxb.20240055

Citation:

LIANG Yuehua, WANG Yichen, WANG Ziqin, CUI Wei, WU Lan, SUN Zhongyi. The impact of extreme weather on the phenology of rubber plantations in Hainan Island, China[J]. Journal of Tropical Biology, 2024, 15(5): 547-557. doi: 10.15886/j.cnki.rdswxb.20240055

The impact of extreme weather on the phenology of rubber plantations in Hainan Island, China

doi: 10.15886/j.cnki.rdswxb.20240055

1. School of Ecology, Hainan University, Haikou, Hainan 570203;
2. Development Research Center of State Forestry and Grassland Administration, Beijing 100714;
3. Hainan Key Laboratory of Environmental Processes and Ecological Regulation in Agriculture and Forestry, Haikou, Hainan 570228, China

Received Date: 2024-04-02
Rev Recd Date: 2024-05-13

Abstract

With the intensification of climate change, the frequency and intensity of extreme weather events have increased, and their impacts on ecosystem structure and function far exceeds those of gradual trend changes. As an important component of terrestrial ecosystems, the phenological response of tropical forests to climate change has always been a research hotspot. However, due to their high plant diversity and evergreen characteristics, scientific findings have not been consolidated. This study focuses on monoculture rubber plantations with distinct phenological characteristics as an entry point. Extreme weather events sensitive to phenological responses were selected by fitting multi-curves pixel-by-pixel to rubber plantations phenology and employing machine learning techniques to reveal the spatiotemporal distribution patterns of spring phenology（Start of growing Season, SOS）, autumn phenology（End of growing Season, EOS）, and extreme weather events during 2003—2018. The impacts of climate extreme indices on phenology were analyzed based on partial correlation analysis. The results show that the SOS of rubber plantations in Hainan Island advanced by an average of 0.73 d·a-1, while the EOS was delayed by 0.60 d·a-1. A few extreme cold events showed an increasing trend, while extremely hot events showed the opposite trend. The days of extreme daytime and night-time temperatures were the main factors affecting SOS and EOS; the number of days with low day-time temperature（TN10p） and the number of days with low night-time temperature（TX10p） were positively correlated with SOS, while the number of days with warm day-time temperature（TN90p） and the number of days with warm night-time temperature（TX90p） were negatively correlated with SOS; TN10p, TN90p, and TX90p were positively correlated with EOS, but TX10p was negatively correlated with EOS. The responses of SOS and EOS to extreme weather events with different intensities and frequencies exhibited obvious east-west differences in space. All these findings showed that it can enhance our understanding of the response of tropical forest structure and function to climate change when extreme weather factors are considered.
- extreme temperature,
- extreme precipitation,
- spatiotemporal distribution,
- MODIS EVI,
- plantation management

References

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[24]	CHEN S, FU Y H, HAO F, et al. Vegetation phenology and its ecohydrological implications from individual to global scales[J]. Geography and Sustainability, 2022,3(4):334-338.
[25]	BUITENWERF R, ROSE L, HIGGINS S I. Three decades of multi-dimensional change in global leaf phenology[J]. Nature Climate Change, 2015, 5:364-368.
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[27]	代武君,金慧颖,张玉红,等.植物物候学研究进展[J].生态学报, 2020, 40(19):6705-6719.
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[31]	包青格乐,张润卿,王艺宸,等. 2000-2020年海南岛天然橡胶人工林分布变化数据集[J].中国科学数据,2023, 8(4):364-375.
[32]	KONG D, ZHANG Y, WANG D, et al. Photoperiod explains the asynchronization between vegetation carbon phenology and vegetation greenness phenology[J]. Journal of Geophysical Research:Biogeosciences, 2020, 125(8):e2020JG005636.
[33]	KONG D, MCVICAR T R, XIAO M, et al. phenofit:an R package for extracting vegetation phenology from time series remote sensing[J]. Methods in Ecology and Evolution, 2022, 13(7):1508-1527.
[34]	LI X, DU H, ZHOU G, et al. Spatiotemporal patterns of remotely sensed phenology and their response to climate change and topography in subtropical bamboo forests during2001-2017:a case study in Zhejiang Province, China[J].GIScience&Remote Sensing, 2023, 60(1):2163575.
[35]	WANG M, LI P, PENG C, et al. Divergent responses of autumn vegetation phenology to climate extremes over northern middle and high latitudes[J]. Global Ecology and Biogeography, 2022, 31(11):2281-2296.
[36]	WANG M, ZHANG S, GUO X, et al. Responses of soil organic carbon to climate extremes under warming across global biomes[J]. Nature Climate Change, 2024, 14:98-105.
[37]	MEERAN K, VERBRIGGHE N, INGRISCH J, et al.Individual and interactive effects of warming and nitrogen supply on CO₂ fluxes and carbon allocation in subarctic grassland[J]. Global Change Biology, 2023, 29(18):5276-5291.
[38]	BYRNE M P. Amplified warming of extreme temperatures over tropical land[J]. Nature Geoscience, 2021, 14:837-841.
[39]	CAO Y, GUO W, GE J, et al. Greening vegetation cools mean and extreme near-surface air temperature in China[J].Environmental Research Letters, 2024, 19(1):014040.
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The impact of extreme weather on the phenology of rubber plantations in Hainan Island, China

1. School of Ecology, Hainan University, Haikou, Hainan 570203;

2. Development Research Center of State Forestry and Grassland Administration, Beijing 100714;

3. Hainan Key Laboratory of Environmental Processes and Ecological Regulation in Agriculture and Forestry, Haikou, Hainan 570228, China

Received Date: 2024-04-02

Rev Recd Date: 2024-05-13

Key words:

Abstract: With the intensification of climate change, the frequency and intensity of extreme weather events have increased, and their impacts on ecosystem structure and function far exceeds those of gradual trend changes. As an important component of terrestrial ecosystems, the phenological response of tropical forests to climate change has always been a research hotspot. However, due to their high plant diversity and evergreen characteristics, scientific findings have not been consolidated. This study focuses on monoculture rubber plantations with distinct phenological characteristics as an entry point. Extreme weather events sensitive to phenological responses were selected by fitting multi-curves pixel-by-pixel to rubber plantations phenology and employing machine learning techniques to reveal the spatiotemporal distribution patterns of spring phenology（Start of growing Season, SOS）, autumn phenology（End of growing Season, EOS）, and extreme weather events during 2003—2018. The impacts of climate extreme indices on phenology were analyzed based on partial correlation analysis. The results show that the SOS of rubber plantations in Hainan Island advanced by an average of 0.73 d·a-1, while the EOS was delayed by 0.60 d·a-1. A few extreme cold events showed an increasing trend, while extremely hot events showed the opposite trend. The days of extreme daytime and night-time temperatures were the main factors affecting SOS and EOS; the number of days with low day-time temperature（TN10p） and the number of days with low night-time temperature（TX10p） were positively correlated with SOS, while the number of days with warm day-time temperature（TN90p） and the number of days with warm night-time temperature（TX90p） were negatively correlated with SOS; TN10p, TN90p, and TX90p were positively correlated with EOS, but TX10p was negatively correlated with EOS. The responses of SOS and EOS to extreme weather events with different intensities and frequencies exhibited obvious east-west differences in space. All these findings showed that it can enhance our understanding of the response of tropical forest structure and function to climate change when extreme weather factors are considered.

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Reference (56)

[1]	XU Y, LI X, DU H, et al. Improving extraction phenology accuracy using SIF coupled with the vegetation index and mapping the spatiotemporal pattern of bamboo forest phenology[J]. Remote Sensing of Environment, 2023, 297:113785.
[2]	LI Q, CHEN X, YUAN W, et al. Remote sensing of seasonal climatic constraints on leaf phenology across pantropical evergreen forest biome[J]. Earth's Future, 2021,9(9):e2021EF002160.
[3]	WOLKOVICH E M, COOK B I, ALLEN J M, et al. Warming experiments underpredict plant phenological responses to climate change[J]. Nature, 2012, 485(7399):494-497.
[4]	PIAO S, LIU Z, WANG T, et al. Weakening temperature control on the interannual variations of spring carbon uptake across northern lands[J]. Nature Climate Change,2017(7):359-363.
[5]	徐波.全球变暖对植物物候的影响[J].大众科技,2018, 20(9):22-25.
[6]	WANG M, WANG S, ZHAO J, et al. Global positive gross primary productivity extremes and climate contributions during 1982-2016[J]. The Science of the Total Environment, 2021, 774:145703.
[7]	ZHOU G Y, ZHOU L Y, SHAO J J, et al. Effects of extreme drought on terrestrial ecosystems:review and prospects[J]. Chinese Journal of Plant Ecology, 2020,44(5):515-525.
[8]	Intergovernmental Panel on Climate Change (IPCC). AR6Climate Change 2021:The Physical Science Basis[M].Cambridge:Cambridge University Press, 2021.
[9]	Intergovernmental Panel on Climate Change (IPCC).Global Warming of 1.5℃:IPCC Special Report on Impacts of Global Warming of 1.5℃ above Pre-Industrial Levels in Context of Strengthening Response to Climate Change, Sustainable Development, and Efforts to Eradicate Poverty[M]. Cambridge:Cambridge University Press;2022.
[10]	LI P, LIU Z, ZHOU X, et al. Combined control of multiple extreme climate stressors on autumn vegetation phenology on the Tibetan Plateau under past and future climate change[J]. Agricultural and Forest Meteorology,2021, 308/309:108571.
[11]	MULDER C P H, ILES D T, ROCKWELL R F.Increased variance in temperature and lag effects alter phenological responses to rapid warming in a subarctic plant community[J]. Global Change Biology, 2017,23(2):801-814.
[12]	LI Y, ZHANG W, SCHWALM C R, et al. Widespread spring phenology effects on drought recovery of Northern Hemisphere ecosystems[J]. Nature Climate Change,2023, 13:182-188.
[13]	HE L, WANG J, CIAIS P, et al. Non-symmetric responses of leaf onset date to natural warming and cooling in northern ecosystems[J]. PNAS Nexus, 2023, 2(9):pgad308.
[14]	MENG F, ZHANG L, ZHANG Z, et al. Opposite effects of winter day and night temperature changes on early phenophases[J]. Ecology, 2019, 100(9):e02775.
[15]	PIAO S, ZHANG X, CHEN A, et al. The impacts of climate extremes on the terrestrial carbon cycle:a review[J].Science China Earth Sciences, 2019, 62(10):1551-1563.
[16]	SONG G, WU S, LEE C K F, et al. Monitoring leaf phenology in moist tropical forests by applying a superpixelbased deep learning method to time-series images of tree canopies[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2022, 183:19-33.
[17]	WANG J, SONG G, LIDDELL M, et al. An ecologicallyconstrained deep learning model for tropical leaf phenology monitoring using PlanetScope satellites[J]. Remote Sensing of Environment, 2023, 286:113429.
[18]	MEDINA-VEGA J A, WRIGHT S J, BONGERS F, et al.Vegetative phenologies of lianas and trees in two Neotropical forests with contrasting rainfall regimes[J]. The New Phytologist, 2022, 235(2):457-471.
[19]	ITIOKA T, YAMAUTI M. Severe drought, leafing phenology, leaf damage and lepidopteran abundance in the canopy of a Bornean aseasonal tropical rain forest[J].Journal of Tropical Ecology, 2004, 20(4):479-482.
[20]	SUN H, YAN L, LI Z, et al. Drought shortens subtropical understory growing season by advancing leaf senescence[J].Global Change Biology, 2024, 30(5):e17304.
[21]	WANG F, ZHANG R, LIN J, et al. High autumn temperatures increase the depth of bud dormancy in the subtropical Torreya grandis and Carya illinoinensis and delay leaf senescence in the deciduous Carya[J]. Trees, 2022,36(3):1053-1065.
[22]	LI X, FU Y H, CHEN S, et al. Increasing importance of precipitation in spring phenology with decreasing latitudes in subtropical forest area in China[J]. Agricultural and Forest Meteorology, 2021108427.
[23]	BENNETT A C, RODRIGUES DE SOUSA T,MONTEAGUDO-MENDOZA A, et al. Sensitivity of South American tropical forests to an extreme climate anomaly[J]. Nature Climate Change, 2023(13):967-974.
[24]	CHEN S, FU Y H, HAO F, et al. Vegetation phenology and its ecohydrological implications from individual to global scales[J]. Geography and Sustainability, 2022,3(4):334-338.
[25]	BUITENWERF R, ROSE L, HIGGINS S I. Three decades of multi-dimensional change in global leaf phenology[J]. Nature Climate Change, 2015, 5:364-368.
[26]	范德芹,赵学胜,朱文泉,等.植物物候遥感监测精度影响因素研究综述[J].地理科学进展, 2016, 35(3):304-319.
[27]	代武君,金慧颖,张玉红,等.植物物候学研究进展[J].生态学报, 2020, 40(19):6705-6719.
[28]	YANG X, WU J, CHEN X, et al. A comprehensive framework for seasonal controls of leaf abscission and productivity in evergreen broadleaved tropical and subtropical forests[J]. Innovation (Cambridge (Mass)), 2021, 2(4):100154.
[29]	PARK D S, LYRA G M, ELLISON A M, et al. Herbarium records provide reliable phenology estimates in the understudied tropics[J]. Journal of Ecology, 2023, 111(2):327-337.
[30]	代奎,曾秀,王鑫洋,等.春季增温对亚热带木本植物物候和生长的影响[J].生态学杂志, 2021, 40(12):3881-3889.
[31]	包青格乐,张润卿,王艺宸,等. 2000-2020年海南岛天然橡胶人工林分布变化数据集[J].中国科学数据,2023, 8(4):364-375.
[32]	KONG D, ZHANG Y, WANG D, et al. Photoperiod explains the asynchronization between vegetation carbon phenology and vegetation greenness phenology[J]. Journal of Geophysical Research:Biogeosciences, 2020, 125(8):e2020JG005636.
[33]	KONG D, MCVICAR T R, XIAO M, et al. phenofit:an R package for extracting vegetation phenology from time series remote sensing[J]. Methods in Ecology and Evolution, 2022, 13(7):1508-1527.
[34]	LI X, DU H, ZHOU G, et al. Spatiotemporal patterns of remotely sensed phenology and their response to climate change and topography in subtropical bamboo forests during2001-2017:a case study in Zhejiang Province, China[J].GIScience&Remote Sensing, 2023, 60(1):2163575.
[35]	WANG M, LI P, PENG C, et al. Divergent responses of autumn vegetation phenology to climate extremes over northern middle and high latitudes[J]. Global Ecology and Biogeography, 2022, 31(11):2281-2296.
[36]	WANG M, ZHANG S, GUO X, et al. Responses of soil organic carbon to climate extremes under warming across global biomes[J]. Nature Climate Change, 2024, 14:98-105.
[37]	MEERAN K, VERBRIGGHE N, INGRISCH J, et al.Individual and interactive effects of warming and nitrogen supply on CO₂ fluxes and carbon allocation in subarctic grassland[J]. Global Change Biology, 2023, 29(18):5276-5291.
[38]	BYRNE M P. Amplified warming of extreme temperatures over tropical land[J]. Nature Geoscience, 2021, 14:837-841.
[39]	CAO Y, GUO W, GE J, et al. Greening vegetation cools mean and extreme near-surface air temperature in China[J].Environmental Research Letters, 2024, 19(1):014040.
[40]	王顿,杨秀玖,李习文,等.基于AHP的海南岛生态地质环境质量综合评价与分析[J].环境生态学, 2024,6(3):33-43.
[41]	MA Q Q, HUANG J G, HÄNNINEN H, et al. Climate warming prolongs the time interval between leaf-out and flowering in temperate trees:Effects of chilling, forcing and photoperiod[J]. Journal of Ecology, 2021, 109(3):1319-1330.
[42]	YANG X, WU J, CHEN X, et al. A comprehensive framework for seasonal controls of leaf abscission and productivity in evergreen broadleaved tropical and subtropical forests[J]. Innovation (Cambridge (Mass)), 2021, 2(4):100154.
[43]	ZHANG J, CHEN S, WU Z, et al. Review of vegetation phenology trends in China in a changing climate[J].Progress in Physical Geography:Earth and Environment,2022, 46(6):829-845.
[44]	JEWARIA P K, HÄNNINEN H, LI X, et al. A hundred years after:endodormancy and the chilling requirement in subtropical trees[J]. The New Phytologist, 2021, 231(2):565-570.
[45]	CHEN X, WANG L, INOUYE D. Delayed response of spring phenology to global warming in subtropics and tropics[J]. Agricultural and Forest Meteorology, 2017,234:222-235.
[46]	PAN Y Q, ZENG X, CHEN W D, et al. Chilling rather than photoperiod controls budburst for gymnosperm species in subtropical China[J]. Journal of Plant Ecology,2022, 15(1):100-110.
[47]	GUO J, MA Q, XU H, et al. Meta-analytic and experimental evidence that warmer climate leads to shift from advanced to delayed spring phenology[J]. Agricultural and Forest Meteorology, 2023, 342:109721.
[48]	ZHANG L, ZHENG J, HÄNNINEN H, et al. Differences between four sympatric subtropical tree species in the interactive effects of three environmental cues on leaf-out phenology[J]. Agricultural and Forest Meteorology,2022, 327:109227.
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Message Board

The impact of extreme weather on the phenology of rubber plantations in Hainan Island, China

doi: 10.15886/j.cnki.rdswxb.20240055

Abstract

References

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通讯作者: 陈斌, bchen63@163.com

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