Impacts of climate warming on plants phenophases in China for the last 40 years

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1 Impacts of climate warming on plants phenophases in China for the last 40 years ZHENG Jingyun, GE Quansheng & HAO Zhixin Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing , China Correspondence should be addressed to Zheng Jingyun ( Abstract Based on plant phenology data from 26 stations of the Chinese Phenology Observation Network of the Chinese Academy of Sciences and the climate data, the change of plant phenophase in spring and the impact of climate warming on the plant phenophase in China for the last 40 years are analyzed. Furthermore, the geographical distribution models of phenophase in every decade are reconstructed, and the impact of climate warming on geographical distribution model of phenophase is studied as well. The results show that ( ) the response of phenophase advance or delay to temperature change is nonlinear. Since the 1980s, at the same amplitude of temperature change, phenophase delay amplitude caused by temperature decrease is greater than phenophase advance amplitude caused by temperature increase; the rate of phenophase advance days decreases with temperature increase amplitude, and the rate of phenophase delay days increases with temperature decrease amplitude. ( ) The geographical distribution model between phenophase and geographical location is unstable. Since the 1980s, with the spring temperature increasing in the most of China and decreasing in the south of Qinling Mountains, phenophases have advanced in northeastern China, North China and the lower reaches of the Changjiang River, and have delayed in the eastern part of southwestern China and the middle reaches of the Changjiang River; while the rate of the phenophase difference with latitude becomes smaller. Keywords: climate warming, phenophase change, impact, phenophase response to climate change, China. Phenophase change is an important indicator of climate and natural environmental changes [1,2]. Recently, several researches from Europe showed that many phenological events have changed obviously with the climate warming after the 1980s [3 5]. Spring phenophase advanced, and autumn phenophase delayed, plants growing season has been lengthened, even egg-laying dates of birds in the United Kingdom have advanced. Analyses on Normalized Difference Vegetation Index (NDVI) data also suggest that the growing season has become nearly 18 days longer in Eurasia, including spring phenophase advanced by one week, and autumn events were delayed by 10 days. Statistical analyses indicate that there is a statistically meaningful relation between inter-annual changes in NDVI and land surface temperature for vegetated areas between 40 N and 70 N [6]. Currently, there are many studies focused on revealing the change of phenophase and its causes, but only a few studies focused on the mechanism and model of phenophase response to temperature. At the beginning of 1960s, China starts the phenology study led by Prof. Zhu Kezhen, and the Chinese Academy of Sciences built the Chinese Phenological Observation Network (CPON) [7]. From the 1980s to the 1990s, several researchers undertook some preliminary studies on relative phenological events and the relationship of phenophase and climatic change based on the collected data [8,9]. Only a few studies focus on the response of phenophase to climatic change. In this study, the impact of climate change on plant phenophase change will be analyzed based on the plant phenophase data observed by CPON of the Chinese Academy of Sciences from 1963 to As a result that the temperature is the key factor to control phenophase change among those of environmental factors [2], moreover there is a strong relation between mean temperature and coldest month temperature as well as extreme minimum temperature, this note will emphasize the mechanism of response and model of phenophase change to mean temperature. The impact of other environmental factors (such as light, water, etc.) and their change on phenophase change will be addressed in future study. 1 Brief about source data The phenophase data from CPON were used in this study. Although there are 67 stations in CPON, where covered the most of China and the systematic observation that started from 1963, there are only 26 stations data selected in this study according to the length, continuity and coverage. The distribution of observational stations is shown in fig. 1 and the length of the data in every station is listed in table 1. The selected phenophase include Salix babylonica L. leaf unfolding, Salix babylonica L., Prunus persica L. Batsch, Prunus davidiana Franch, Prunus armeniaca L., Prunus Fig. 1. The location of selected stations from CPON used in this study Chinese Science Bulletin Vol. 47 No. 21 November 2002

2 Table 1 The difference between the mean phenophase and temperature in spring for the period before the 1980s and that since the 1980s for 26 stations Station Phenophase Spring temperature Selected phenophase Series length difference/d a) b) difference/ c) Harbin 4.1 Ulmus pumila L., Salix babylonica L. leaf unfolding, Syringa Oblata Lindl, Betula mandshurica N. leaf unfolding Shenyang 2.2 Ulmus pumila L., Prunus persica L. Batsch, Robinica pseudoacacia L., Syringa Oblata Lindl Shanhaiguan 3.7 Ulmus pumila L., Syringa Oblata Lindl (Chaoyang) Hohhot 3.0 Robinica pseudoacacia L., Syringa Oblata Lindl Beijing 3.5 Prunus davidiana Franch, Robinica pseudoacacia L. blossom, Salix Babylonica L. catkins flying, Syringa Oblata Lindl, Prunus armeniaca L., ice melting in Beihai Lake Jinan 1.9 Salix babylonica L. leaf unfolding, Robinica pseudoacacia L., Syringa Oblata Lindl Taian 2.1 Salix babylonica L. leaf unfolding, Robinica pseudoacacia L., Syringa Oblata Lindl (Jinan) Yancheng 3.7 Ulmus pumila L., Prunus persica L. Batsch, Robinica pseudoacacia L (Qingjiang) Yangzhou 2.5 Ulmus pumila L. Prunus persica L. Batsch Robinica (Nanjing) pseudoacacia L. Yinxian 0.6 Salix babylonica L. budding, Ulmaus Pumila leaf unfolding, Melia azedarach L (Ningbo) Xiamen 2.9 Magnolia denudata Desr, Gossampinus malabarica (DC.) Merr, Melia azedarach L. Luoyang 2.2 Ulmus pumila L., Salix babylonica L. leaf unfolding, Robinica pseudoacacia L., Syringa Oblata Lindl, Ginkgo biloba L. budding (Zhengzhou) Wuhan 3.0 Magnolia denudata Desr, Melia azedarach L Changde 4.4 Robinica pseudoacacia L., Melia azedarach L Changsha 5.0 Robinica pseudoacacia L., Melia azedarach L Guangzhou 3.2 Melia azedarach L., Gossampinus malabarica (DC.) Merr leaf unfolding Xi an 0.2 Ulmus pumila L., Salix babylonica L. leaf unfolding, Robinica pseudoacacia L., Syringa Oblata Lindl, Prunus davidiana Franch Minqin 0.4 Salix matsudana leaf unfolding, Ulmus pumila L., Murus acbal, Prunus armeniaca L (Wuwei) Shihezi 0.4 Prunus armeniaca L., Robinica pseudoacacia L (Wusu) 1.0 (Urumqi) Beibei 9.3 Prunus persica L. Batsch, Robinica pseudoacacia L., Cercis chinensis Bge (Shapingba) Renshou 6.8 Prunus persica L. Batsch, Robinica pseudoacacia L (Chengdu), Firmiana simplex W. F. Wight. leaf unfolding Guiyang 5.8 Ulmus pumila L., Salix babylonica L. leaf unfolding, Prunus persica L. Batsch, Robinica pseudoacacia L., Cercis chinensis Bge Guilin 7.2 Salix babylonica L. leaf unfolding, Prunus persica L. Batsch Mengla 4.5 Broussonetia papyrifera (L.) Vent leaf unfolding, Melia toosendan Sieb. et Zucc (Jinghong) Shanghai There are no data available before the 1980s. During the period of , the phenophases in the early spring have advanced trends, but have no obvious trends in the late spring. Kunming There are no data after the 1980s. During the period of , the phenophases in spring have little advanced trends. a) Positive indicates phenophase delay and negative indicates phase advance since the 1980s; b) except that Beijing has continuous records, the other stations lack observation data from 1968 to 1970; c) positive indicates spring temperature increase and negative indicates spring temperature decrease since the 1980s. salicina Lindl, Ulmus pumila L., Syringa Oblata Lindl, Morus alba L., Robinica pseudoacacia L. leaf unfolding, Robinica pseudoacacia L., Melia azedarach L., etc. These phenophases are characterized by spring natural phenology in China with wide distribution and easy observation. The meteorological data used in this study are mean monthly temperature in the same period. 2 Impact of climate warming on phenophase The difference between the mean phenophase and temperature in spring for the period before the 1980s and that since the 1980s for 26 stations (or neighbor station) are listed in table 1. It is suggested that there exist 3 kinds of changes in spring phenophase and temperature: advance, constant variation and delay for the spring pheno- Chinese Science Bulletin Vol. 47 No. 21 November

3 phase corresponding to the increase, unobvious change, and decline for the spring temperature respectively since the 1960s. The spring temperature has increased, and the phenophase has advanced in northeastern China, North China and the lower reaches of the Changjiang River since the 1980s. The stations in Weihe Plain and the west of Henan Province, such as Xi an, Luoyang, etc., have no noticeable spring temperature change and phenophase change trends since the 1980s. However, the spring temperature decreased and phenophase delayed in the stations in the eastern part of southwestern China, the middle reaches of the Changjiang River and South China. The diagram of the difference between the mean phenophase and temperature in spring for the period before the 1980s and that since the 1980s listed in table 1 is drawn in fig. 2, and the best fitting equation is y = 2.05x x , where y is the mean phenophase difference, x is the spring temperature difference. The sample numbers is 24, coefficient is 0.827, passed α = significance level. This result shows that in the region where the spring temperature increased by 0.5, the spring phenophase advanced by 2 days since the 1980s; while in the region of the spring temperature increased by 1, the spring phenophase advanced by 3.5 days. However, in the regions where the spring temperature decreased by 0.5, the spring phenophase delayed by 4 days; while in the regions where the spring temperature decreased by 1, the spring phenophase delayed by 8.8 days. It is suggested that the response of the phenophase advance and delay to the temperature increase and decrease is nonlinear, namely, since the 1980s, at the same amplitude of temperature change, phenophase delay amplitude caused by temperature decrease is greater than phenophase advance amplitude caused by temperature increase; the rate of pheno- Fig. 2. The diagram of the difference between the mean phenophase and temperature in spring for the period before the 1980s and that since the 1980s (solid dot: observation, curve: polynomial fitting). phase advance days decreases with temperature increase amplitude, and the rate of phenophase delay days increases with temperature decrease amplitude. The relationship between the spring temperature and the phenophase on the inter-annual variation for 10 stations is displayed in fig. 3. Harbin and Shenyang stand for northeastern China, Beijing stands for North China, Yancheng stands for the lower reaches of the Changjiang River, Changde stands for the middle reaches of the Changjiang River, Luoyang and Xi an stand for western Henan Province and Weihe Plain respectively, Beibei and Guiyang stand for the eastern part of southwestern China, Guangzhou stands for South China. There are 2 phenophases selected from each station, which stand for the early spring and the late spring separately. Statistical analyses indicate that there is a statistically meaningful relation between inter-annual changes in the spring phenophase and the spring temperature for every station. The coefficient between the early and late spring phenophase series and the spring temperature series passed 0.01 significance level totally. 3 Impact of climate warming on geographical distribution models of phenophase The relationship between phenophase and geographical location is a fundamental scientific issue in the research field of phenology. The general relationship between phenophase and geographical location had been discussed and their statistic model had been built by many scholars, such as Hopokins [2]. Gong et al. had also built the statistic model between phenophase and geographical location for main plant phenophase in China. The statistic model suggested that the latitude is a key factor to control the plant phenophase geographical distribution in China. The phenophase difference gradually declines with latitude difference from the early spring to summer. Before the end of February, the phenophase difference advances by 4 5 days with 1 decline in the latitude. From the beginning of May to the end of April, the phenophase difference advances by 3 4 days with 1 decline in the latitude. The phenophase difference advances by 2 3 days with 1 decline in latitude from the end of April to mid-june. Meanwhile, from the end of June to mid-july, the phenophase difference advances by less than 1 day only with 1 decline in the latitude [10]. However, the statistic model between the phenophase and the geographical location should be changed with the climate change, and this is another key issue needed to further discuss. The statistic models between phenophase and geographical location for main plant phenophase in China for the period of 1960s 1990s (see the 4th column in table 1 for series length) and for the two decades, 1980s and 1990s, are listed in table 2. The mean date since the 1980s in Xi an, the central location of China, and the rate of the phenophase difference for 2 periods, before the 1828 Chinese Science Bulletin Vol. 47 No. 21 November 2002

4 Fig. 3. The inter-annual phenophase and spring temperature variations for 10 stations. (a) Harbin, dot-dash: Betula mandshurica N. leaf unfolding, dash: Syringa Oblata Lindl ; solid: temperature from April to May, bold line: linear fitting. (b) Shenyang, dot-dash: Ulmus pumila L. in Shanhaiguan, dash: Syringa Oblata Lindl, solid: temperature from April to May, bold line: linear fitting. (c) Beijing, dot-dash: Prunus davidiana Franch, dash: Robinica pseudoacacia L. blossom, solid: temperature from March to May, bold line: linear fitting. (d)yancheng, Jiangsu, dot-dash: Prunus persica L. Batsch, dash: Robinica pseudoacacia L., solid: temperature from March to May (Qingjiang, Jiangsu), bold line: linear fitting. (e) Luoyang, dot-dash: Salix babylonica L. Leaf unfolding, dash: Robinica pseudoacacia L., solid: temperature from March to May (Zhengzhou), bold line: linear fitting. (f) Xi an, dot-dash: Prunus davidiana Franch, dash: Syringa Oblata Lindl, solid: temperature from March to May, bold line: linear fitting. (g) Changde, Hunan, dot-dash: Robinica pseudoacacia L. leaf unfolding, dash: Melia azedarach L., solid: temperature from March to May, bold line: linear fitting. (h) Beibei, Chongqing, dot-dash: Cercis chinensis Bge, dash: Robinica pseudoacacia L., solid: temperature from Feb. to April (Shapingba, Chongqing), bold line: linear fitting. (i) Guiyang, dot-dash: Cercis chinensis Bge, dash: Firmiana simplex W. F. Wight leaf unfolding, solid: temperature from March to April. (j) Guangzhou, dot-dash: Melia azedarach L., dash: Gossampinus malabarica (DC.) Merr leaf unfolding, solid: temperature from Feb. to April. Chinese Science Bulletin Vol. 47 No. 21 November

5 1980s and since the 1980s, with the latitude, longitude and altitude difference are given in table 3. In contrast to the previous result [10], table 3 also shows that the rate of the phenophase difference with the geographical location has changed since the 1980s, even though every plant phenophase is in different values. In spring (from the end of February to early May), the average rate of the phenophase difference advances by 2.7 days with 1 decline in the latitude, advances by 0.65 days with 1 decline in the longitude, and delays by 1.2 days with 100 m increase in the altitude since the 1980s. In fact, the phenophase difference with latitude, longitude and altitude difference corresponds to the response of environmental factors difference (such as temperature, light, water, soil, etc.) caused by different geographical locations, in which the phenophase difference with latitude difference mainly corresponds to the impact of temperature difference on phenophase caused by different latitudes. Compared with the change rate before the 1980s, the rate of the phenophase difference in spring with latitude difference during Table 2 The statistic model between phenophase and geographical location for main plant phenophase in China Phenophase Duration Statistic model between phenophase Sample Multiple correlation and geographical location a) No. coefficient Ulmus pumila L. 1960s 1990s Y = 2.974φ λ h s Y = φ λ h s Y = φ λ h Salix babylonica L. leaf 1960s 1990s Y = φ λ h unfolding 1980s Y = φ λ h Salix babylonica L. Prunus persica L. Batsch Magoolia grandifloral L. 1990s Y = φ λ h s 1990s Y = φ λ h s Y = φ λ h s Y = φ λ h s 1990s Y = φ λ h s Y = φ λ h s Y = φ λ h s 1990s Y = φ λ h s Y = φ λ h s Y = φ λ h s 1980s Y = φ λ h Prunus armeniaca L. 1980s Y = φ λ h Syringa Oblata Lindl 1960s 1990s Y = φ λ h s Y = φ λ h s Y = φ λ h Cercis chinensis Bge 1970s 1990s Y = φ λ h s Y = φ λ h Morus alba L. Robinica pseudoacacia L. Melia azedarach L. 1990s Y = φ λ h s 1990s Y = φ λ h s Y = φ λ h s Y = φ λ h s 1990s Y = φ λ h s Y = φ λ h s Y = φ λ h s 1990s Y = φ λ h s Y = φ λ h s Y = φ λ h a) Y, Phenophase /days from Jan. 1; φ, latitude/degree; λ, longitude/degree; h, altitude/100 m. ` Table 3 The mean date of the main phenophase since the 1980s in Xi an and the rate of the date difference with the latitude, longitude and altitude for the periods before the 1980s and since the 1980s Phenophase Mean date in Xi an Rate with latitude Rate with longitude Rate with altitude (d/degree) (d/degree) (d/100 m) Ulmus pumila L. February (+3.55) (+0.37) (+0.90) Magoolia grandifloral L. March Salix babylonica L. unfold March Prunus armeniaca L. March (+3.74) (+0.78) (+1.54) Salix babylonica L. March (+3.62) (+0.71) (+0.38) Prunus persica L. Batsch April (+3.98) (+0.71) (+1.36) Syringa Oblata Lindl April Morus alba L. April (+3.09) (+0.36) (+0.72) Robinica pseudoacacia L. May Average (+3.60) (+0.59) (+1.00) The rate is mean value of phenophases in the 1980s and the 1990s, and the value in the bracket indicates the rate before the 1980s from ref. [10] Chinese Science Bulletin Vol. 47 No. 21 November 2002

6 the period since the 1980s is less than that in the period before the 1980s. This is caused by the spring temperature increase un-homogeneous to the different latitudes, in respect that the spring temperature difference is usually parallel to latitude, whereas the rate of spring temperature with latitude (from south to north) is a key factor to control the date of phenophase with latitude. Since the 1980s, many parts of northern China have a great temperature increase rate, particularly in northeastern China where temperature increases by more than 1, however, in southern China, the temperature increase rate is less, and even declines in the south of Qinling Mountains. It led to the spring temperature difference with latitude, namely, the temperature difference from north to south becomes smaller, so that the rate of the phenophase difference with latitude becomes smaller too. These results indicate that the geographical distribution model between the phenophase and geographical location is unstable, and the statistical parameter must be changed when the climate changes. The result of the rate of the phenophase difference in spring with latitude difference during the period since the 1980s is less than that in the period before the 1980s, which indicates that the rate of the phenophase difference with latitude difference in the warm period is less than that in the cold period. It is implicated that the reconstruction of climate during historical times by using the phenology approach should use the different rates of the phenophase difference with latitude in the cold and warm periods respectively. 4 Conclusive remarks There is a statistically meaningful relation between inter-annual changes in the spring phenophase and the spring temperature in China for the last 40 years. Since the 1980s, the spring temperature increases, the phenophase advances in the northeast of China and North China as well as the lower reaches of the Changjiang River; in the regions of Weihe Plain and the west of Henan Province, such as Xi an, Luoyang, etc., the spring temperature change is unobvious, the trend of change of phenophase cannot be identified clearly; while in the regions of the eastern part of southwestern China, the middle reaches of the Changjiang River and South China, the spring temperature decreases, and the phenophase delays. The response of phenophase advance or delay to temperature change is nonlinear. ( ) Under the condition of the same amplitude of the temperature change, phenophase delay amplitude caused by the temperature decrease is greater than phenophase advance amplitude caused by temperature increase; ( ) the rate of phenophase advance days decreases with temperature increase amplitude, and the rate of phenophase delay days increases with temperature decrease amplitude. Since the 1980s, in the region where the spring temperature increased by 0.5, the spring phenophase advanced by 2 days; while in the region where the spring temperature increased by 1, the spring phenophase advanced by 3.5 days. However, in the regions where the spring temperature decreased by 0.5, the spring phenophase delayed by 4 days; while in the regions where the spring temperature decreased by 1, the spring phenophase delayed by 8.8 days. The geographical distribution model between phenophase and geographical locations is unstable when the climate changes, and the rate of the phenophase difference in spring with latitude difference during the period since the 1980s is less than that in the period before the 1980s. This is caused by the spring temperature increase unhomogeneous to the different latitudes, many parts of northern China have a great temperature increase rate, and in southern China, the temperature increase rate has been less or has decreased since the 1980s. It leads to the spring temperature difference with latitude, namely, the temperature difference from north to south becomes smaller, so that the rate of the phenophase difference with latitude becomes smaller too. This study is not only a regional case on the impact of global warming on plant phenophase and vegetation change, but also reveals the nonlinear response of phenophase change to temperature change, and the characteristic of unstable geographical distribution model between phenophase and the geographical location with the climate change by statistics, which provides a new phenophase change pattern to the phenology. Meanwhile, it also implicates that the reconstruction of climate during historical times by using the phenology approach should use the different rates of the phenophase difference with latitude in the cold and warm periods respectively. Acknowledgements This work was supported by the Chinese Academy of Sciences (Grant No. KZCX2-314), the National Natural Science Foundation of China (Grant No ), and Institute of Geographic Sciences and Natural Resources Research, the Chinese Academy of Sciences (Grant No. CXIOG-A00-02). References 1. 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