impacts of climate warming on plants phenophases in china for the last 40 years

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1826 Chinese Science Bulletin Vol. 47 No. 21 November 2002

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, Chi-nese Academy of Sciences, Beijing 100101, China Correspondence should be addressed to Zheng Jingyun (e-mail: [email protected])

Abstract Based on plant phenology data from 26 stations of the Chinese Phenology Observation Network of the Chi-nese 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 distribu-tion models of phenophase in every decade are reconstructed, and the impact of climate warming on geographical distribu-tion 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 ampli-tude caused by temperature decrease is greater than pheno-phase advance amplitude caused by temperature increase; the rate of phenophase advance days decreases with tem-perature increase amplitude, and the rate of phenophase delay days increases with temperature decrease amplitude. ( ) The geographical distribution model between pheno-phase 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, pheno-phases 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, pheno-phase response to climate change, China.

Phenophase change is an important indicator of cli-mate and natural environmental changes[1,2]. Recently, several researches from Europe showed that many phenological events have changed obviously with the cli-mate warming after the 1980s[3 5]. Spring phenophase advanced, and autumn phenophase delayed, plants grow-ing 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 ad-vanced by one week, and autumn events were delayed by 10 days. Statistical analyses indicate that there is a statis-tically 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 tem-perature. At the beginning of 1960s, China starts the phenol-ogy study led by Prof. Zhu Kezhen, and the Chinese Academy of Sciences built the Chinese Phenological Ob-servation Network (CPON)[7]. From the 1980s to the 1990s, several researchers undertook some preliminary studies on relative phenological events and the relation-ship of phenophase and climatic change based on the col-lected 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 2000. 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 empha-size the mechanism of response and model of phenophase change to mean temperature. The impact of other envi-ronmental 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 se-lected 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. flower-ing, Prunus persica L. Batsch flowering, Prunus davidiana Franch flowering, Prunus armeniaca L. flowering, Prunus

Fig. 1. The location of selected stations from CPON used in this study.

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Chinese Science Bulletin Vol. 47 No. 21 November 2002 1827

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 difference/d a) Selected phenophase Series lengthb) Spring temperature

difference/ c) Harbin 4.1 Ulmus pumila L. flowering, Salix babylonica L. leaf unfolding, Syringa Oblata

Lindl flowering, Betula mandshurica N. leaf unfolding 1963 1991 0.7

Shenyang 2.2 Ulmus pumila L. flowering, Prunus persica L. Batsch flowering, Robinica pseu-doacacia L. flowering, Syringa Oblata Lindl flowering

1963 1996 0.5

Shanhaiguan 3.7 Ulmus pumila L. flowering, Syringa Oblata Lindl flowering 1963 1993 0.6 (Chaoyang) Hohhot 3.0 Robinica pseudoacacia L. flowering, Syringa Oblata Lindl flowering 1963 1996 0.3 Beijing 3.5 Prunus davidiana Franch flowering, Robinica pseudoacacia L. blossom, Salix Baby-

lonica L. catkins flying, Syringa Oblata Lindl flowering, Prunus armeniaca L. flowering, ice melting in Beihai Lake

1950 2000 1.2

Jinan 1.9 Salix babylonica L. leaf unfolding, Robinica pseudoacacia L. flowering, Syringa Oblata Lindl flowering

1963 1991 1.1

Taian 2.1 Salix babylonica L. leaf unfolding, Robinica pseudoacacia L. flowering, Syringa Oblata Lindl flowering

1963 1991 1.1 (Jinan)

Yancheng 3.7 Ulmus pumila L.flowering, Prunus persica L. Batsch flowering, Robinica pseu-doacacia L.flowering

1964 1996 0.4 (Qingjiang)

Yangzhou 2.5 Ulmus pumila L. flowering Prunus persica L. Batsch flowering Robinica pseu-doacacia L. flowering

1963 1996 0.1 (Nanjing)

Yinxian 0.6 Salix babylonica L. budding, Ulmaus Pumila leaf unfolding, Melia azedarach L. flowering

1968 1996 0.4 (Ningbo)

Xiamen 2.9 Magnolia denudata Desr flowering, Gossampinus malabarica (DC.) Merr flower-ing, Melia azedarach L. flowering

1964 1988 0.9

Luoyang 2.2 Ulmus pumila L. flowering, Salix babylonica L. leaf unfolding, Robinica pseu-doacacia L. flowering, Syringa Oblata Lindl flowering, Ginkgo biloba L. budding

1964 1996 0.04 (Zhengzhou)

Wuhan 3.0 Magnolia denudata Desr flowering, Melia azedarach L. flowering 1963 1996 0.1 Changde 4.4 Robinica pseudoacacia L. flowering, Melia azedarach L. flowering 1965 1991 0.4 Changsha 5.0 Robinica pseudoacacia L. flowering, Melia azedarach L. flowering 1963 1991 0.5 Guangzhou 3.2 Melia azedarach L. flowering, Gossampinus malabarica (DC.) Merr leaf unfolding 1963 1990 0.03 Xi’an 0.2 Ulmus pumila L. flowering, Salix babylonica L. leaf unfolding, Robinica pseu-

doacacia L. flowering, Syringa Oblata Lindl flowering, Prunus davidiana Franchflowering

1963 1996 0.3

Minqin 0.4 Salix matsudana leaf unfolding, Ulmus pumila L. flowering, Murus acbal flower-ing, Prunus armeniaca L. flowering

1974 1996 0.4 (Wuwei)

Shihezi 0.4 Prunus armeniaca L. flowering, Robinica pseudoacacia L. flowering 1963 1996 0.2 (Wusu) 1.0 (Urumqi)

Beibei 9.3 Prunus persica L. Batsch flowering, Robinica pseudoacacia L. flowering, Cercis chinensis Bge flowering

1963 1996 0.6 (Shapingba)

Renshou 6.8 Prunus persica L. Batsch flowering, Robinica pseudoacacia L. flowering 1964 1994 0.6 (Chengdu) Guiyang 5.8 Ulmus pumila L. flowering, Salix babylonica L. leaf unfolding, Prunus persica L.

Batsch flowering, Robinica pseudoacacia L. flowering, Cercis chinensis Bgeflowering, Firmiana simplex W. F. Wight. leaf unfolding

1963 1995 0.8

Guilin 7.2 Salix babylonica L. leaf unfolding, Prunus persica L. Batsch flowering 1963 1993 0.4 Mengla 4.5 Broussonetia papyrifera (L.) Vent leaf unfolding, Melia toosendan Sieb. et Zucc.

flowering 1963 1996 0.3 (Jinghong)

Shanghai There are no data available before the 1980s. During the period of 1981 1996, 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 1963 1975, 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 flowering, Ulmus pumila L. flowering, Sy-ringa Oblata Lindl flowering, Morus alba L. flowering, Robinica pseudoacacia L. leaf unfolding, Robinica pseu-doacacia L. flowering, Melia azedarach L. flowering, etc. These phenophases are characterized by spring natural phenology in China with wide distribution and easy ob-servation. 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: ad-vance, constant variation and delay for the spring pheno-

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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 tem-perature 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 be-fore the 1980s and that since the 1980s listed in table 1 is drawn in fig. 2, and the best fitting equation is

y = 2.05x2 6.08x + 0.69, where y is the mean phenophase difference, x is the spring temperature difference. The sample numbers is 24, coeffi-cient is 0.827, passed = 0.0001 significance level. This result shows that in the region where the spring tempera-ture 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 pheno-phase 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 tempera-ture decrease is greater than phenophase advance ampli-tude 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 in-creases with temperature decrease amplitude. The relationship between the spring temperature and the phenophase on the inter-annual variation for 10 sta-tions 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 pheno-phases 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 pheno-phase 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 sig-nificance level totally. 3 Impact of climate warming on geographical distribution models of phenophase The relationship between phenophase and geo-graphical location is a fundamental scientific issue in the research field of phenology. The general relationship be-tween 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 lati-tude 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 dif-ference advances by 3 4 days with 1˚ decline in the lati-tude. 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 statis-tic 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 Chinafor the period of 1960s 1990s (see the 4th column intable 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

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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 flowering; solid: temperature from April to May, bold line: linear fitting. (b) Shenyang, dot-dash: Ulmus pumila L. flower-ing in Shanhaiguan, dash: Syringa Oblata Lindl flowering, solid: temperature from April to May, bold line: linear fitting. (c) Beijing, dot-dash: Prunus davidiana Franch flowering, dash: Robinica pseudoacacia L. blossom, solid: temperature from March to May, bold line: linear fitting. (d)Yancheng, Ji-angsu, dot-dash: Prunus persica L. Batsch flowering, dash: Robinica pseudoacacia L. flowering, 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. flowering, solid: tem-perature from March to May (Zhengzhou), bold line: linear fitting. (f) Xi’an, dot-dash: Prunus davidiana Franch flowering, dash: Syringa Oblata Lindl flowering, solid: temperature from March to May, bold line: linear fitting. (g) Changde, Hunan, dot-dash: Robinica pseudoacacia L. leaf unfolding, dash: Melia azedarach L. flowering, solid: temperature from March to May, bold line: linear fitting. (h) Beibei, Chongqing, dot-dash: Cercis chinensis Bge flowering, dash: Robinica pseudoacacia L. flowering, solid: temperature from Feb. to April (Shapingba, Chongqing), bold line: linear fitting. (i) Guiyang, dot-dash: Cercis chinensis Bge flowering, dash: Firmiana simplex W. F. Wight leaf unfolding, solid: temperature from March to April. (j) Guangzhou, dot-dash: Melia azedarach L. flowering, dash: Gossampinus malabarica (DC.) Merr leaf unfolding, solid: temperature from Feb. to April.

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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 pheno-phase is in different values. In spring (from the end of February to early May), the average rate of the pheno-phase 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 dif-ference with latitude, longitude and altitude difference corresponds to the response of environmental factors dif-ference (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 pheno-phase 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 and geographical locationa)

Sample No.

Multiple correlation coefficient

1960s 1990s Y = 2.974 + 0.562 + 1.21 h – 98.173 11 0.942 1980s Y = 2.355 + 0.428 + 0.846 h – 56.294 11 0.827

Ulmus pumila L. flowering

1990s Y = 3.376 + 0.507 + 1.514 h – 107.012 12 0.860 1960s 1990s Y = 3.292 + 0.414 + 1.26 h – 84.429 11 0.950

1980s Y = 2.517 + 0.626 + 0.402 h – 77.518 14 0.891 Salix babylonica L. leaf unfolding

1990s Y = 3.982 + 0.604 + 1.514 h – 134.021 11 0.912 1960s 1990s Y = 2.981 + 0.289 + 0.380 h – 51.675 11 0.966

1980s Y = 2.033 + 0.842 + 1.437 h – 82.332 12 0.983 Salix babylonica L. flowering

1990s Y = 2.531 + 0.312 + 2.168 h – 40.458 12 0.964 1960s 1990s Y = 2.644 + 1.067 + 0.269 h – 122.515 9 0.955

1980s Y = 2.252 + 1.404 + 0.7212 h – 145.825 9 0.978 Prunus persica L. Batsch flowering

1990s Y = 2.171 + 0.614 + 0.4358 h 57.397 10 0.855 1980s 1990s Y = 3.238 + 0.518 + 1.156 h – 90.59 8 0.925

1980s Y = 4.026 + 0.114 + 0.129 h – 66.181 8 0.960 Magoolia grandifloral L. flowering

1990s Y = 2.520 + 1.039 + 1.927 h – 130.247 8 0.933 1960s 1980s Y = 3.743 + 0.182 + 2.333 h – 85.54 9 0.998 Prunus armeniaca L.

flowering 1980s Y = 3.386 + 0.336 + 1.416 h – 79.061 9 0.996 1960s 1990s Y = 2.751 + 0.410 + 0.982 h – 47.73 9 0.969

1980s Y = 2.379 + 0.353 + 0.877 h – 25.636 9 0.961 Syringa Oblata Lindl flowering

1990s Y = 2.494 + 0.331 + 1.101 h – 29.902 10 0.964 1970s 1990s Y = 3.367 + 0.560 + 0.526 h – 76.733 8 0.964

1980s Y = 2.397 + 1.553 + 0.669 h – 160.894 10 0.954 Cercis chinensis Bge flowering

1990s Y = 3.037 + 0.960 + 0.634 h – 113.486 10 0.914 1960s 1990s Y = 2.581 + 1.332 + 2.347 h – 139.4 10 0.963

1980s Y = 2.286 + 1.881 + 2.934 h – 191.296 10 0.953 Morus alba L. flowering

1990s Y = 2.485 + 0.662 + 1.723 h – 55.316 10 0.926 1960s 1990s Y = 2.427 + 0.586 + 0.761 h – 31.437 11 0.953

1980s Y = 2.019 + 0.568 + 0.825 h – 13.262 16 0.916 Robinica pseudoacacia L. flowering

1990s Y = 2.444 + 0.615 + 1.170 h – 36.339 11 0.953 1970s 1990s Y = 3.263 +0.581 + 1.469 h – 73.703 10 0.977

1980s Y = 2.968 +0.523 + 1.91 h – 24.9 12 0.906 Melia azedarach L. flowering

1990s Y = 3.116 +0.580 + 1.11 h – 36.2 10 0.941 a) Y, Phenophase /days from Jan. 1; , latitude/degree; , 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 (d/degree)

Rate with longitude (d/degree)

Rate with altitude (d/100 m)

Ulmus pumila L. flowering February 27 +2.89 (+3.55) +0.47 (+0.37) +1.19 (+0.90) Magoolia grandifloral L. flowering March 20 +3.27 +0.58 +1.03 Salix babylonica L. unfold March 21 +3.25 +0.62 +0.95 Prunus armeniaca L. flowering March 22 +3.39 (+3.74) +0.34 (+0.78) +1.42 (+1.54) Salix babylonica L. flowering March 30 +2.30 (+3.62) +0.61 (+0.71) +1.70 (+0.38) Prunus persica L. Batsch flowering April 2 +2.21 (+3.98) +1.01 (+0.71) +0.58 (+1.36) Syringa Oblata Lindl flowering April 7 +2.43 +0.34 +0.99 Morus alba L. flowering April 17 +2.39 (+3.09) +1.27 (+0.36) +2.33 (+0.72) Robinica pseudoacacia L. flowering May 1 +2.23 +0.59 +1.00 Average +2.71 (+3.60) +0.65 (+0.59) +1.24 (+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].

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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 con-trol 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 pheno-phase and geographical location is unstable, and the sta-tistical parameter must be changed when the climate changes. The result of the rate of the phenophase differ-ence 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 pheno-phase 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 Prov-ince, 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 tem-perature 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, pheno-phase 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 tem-perature decrease amplitude. Since the 1980s, in the re-gion where the spring temperature increased by 0.5 , the spring phenophase advanced by 2 days; while in the re-gion 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 pheno-phase 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 un- homogeneous 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 tem-perature 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 pheno-phase change to temperature change, and the characteris-tic 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 im-plicates 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 Acad-emy of Sciences (Grant No. KZCX2-314), the National Natural Science Foundation of China (Grant No. 49901001), and Institute of Geographic Sciences and Natural Resources Research, the Chinese Academy of Sciences (Grant No. CXIOG-A00-02).

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(Received May 23, 2002)

impacts of climate warming on plants phenophases in china for the last 40 years

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