Spatial heterogeneity in leaf coloring date and the phenological response to thermal environment variations of Beijing landscape trees
-
摘要:目的
城市化进程影响下，城市内部热环境的空间分布不均导致植物物候的空间异质性突出。秋色盛期作为落叶树种生长季的终点，其空间异质性对于城市植被的年周期固碳量及整个城市生态系统的初级生产力具有重要影响，同时会引起秋季季相景观的空间变化，是监测城市生态及景观动态的一个关键角度，值得深入探究。本研究以此为切入点，旨在揭示北京城市环境中秋色盛期的空间异质性特征及其对下垫面热环境的响应。
方法本研究以北京主城区西北城郊梯度上9处公园绿地中的5种秋色叶树种为研究对象，基于地面物候观测对2017—2019年的秋色盛期数据进行采集，基于MODIS地温反演对样地热环境数据进行采集，对秋色盛期空间差异及其与秋季热环境的相关性进行分析。
结果（1）北京主城区各树种的秋色盛期整体发生于10月中旬至12月上旬、集中于11月上中旬，由早到晚依次为洋白蜡、元宝枫、银杏、水杉、旱柳，且银杏雌株的秋色盛期显著早于雄株。（2）各树种秋色盛期整体上由二环—三环—五环—五环外逐渐提前，城郊物候天数差异达（10.1 ± 0.3） d；样地间物候期整体差异显著，尤其四环外样地的秋色盛期显著早于三环内。（3）各树种秋色盛期与样地秋季平均地温（LSTa）呈显著正相关（P < 0.01），表明北京主城区内秋季地表热量的大量积累会导致秋色盛期延后；各树种秋色盛期对LSTa空间差异的响应敏感度平均为（4.11 ± 0.83） d/℃，以洋白蜡和水杉响应最为敏感。
结论北京主城区的秋色盛期表现出对城市秋季热环境空间差异的显著响应，城市热岛效应是未来气候变化的一个缩影，城市环境中物候期对热环境空间差异的响应可反映未来气候变化对植物物候的潜在影响，即具有“空间代替时间”的研究价值。
Abstract:ObjectiveUnder the impact of urbanization, the spatial unevenness of thermal environment within urbanized area leads to more prominent spatial heterogeneity of urban plant phenology. The spatial unevenness of leaf coloring date (LCD), the end of deciduous trees’ growing season has a far-reaching influence on the annual carbon sequestration of urban vegetation and the primary productivity of urban ecosystem, also causes spatial variation in the autumn seasonal aspect. Therefore, the spatial heterogeneity of leaf senescence is one critical cut-in point for monitoring urban ecology and landscape dynamics, and deserves profound exploration. Regarding this point, this research aimed to explore the spatial heterogeneity characteristics of leaf coloring date (LCD) and the phenological response to thermal environment of underlying surface in the highly urbanized Beijing City.
MethodThis research selected five autumn-color tree species as the research objects that distributed in 9 green spaces along the urban-suburb gradient in Beijing’s northwestern urban area. We applied ground phenological observation to collect the LCD data during 2017−2019, and collected thermal environment data by retrieving MODIS land surface temperature (LST). Then, we analyzed the spatial difference of LCD and its correlation with the autumn thermal environment.
Result(1) the LCD of various tree species in Beijing’s urban area occurred during mid-October to early December and clustered in early and mid-November, with the species order of LCD ranked as follows: Fraxinus pennsylvanica, Acer truncatum, Ginkgo biloba, Metasequoia glyptostroboides, Salix matsudana. The LCD for female ginkgo trees occurred significantly earlier than male ones. (2) The LCD of various species gradually advanced from the central urban area in 2nd Ring to the outskirts beyond 5th Ring, with the spatial range of LCD reaching (10.1 ± 0.3) d in average. A significant phenological difference existed among different sample plots and the LCD outside of 4th Ring occurred significantly earlier than that within 3rd Ring. (3) The LCD of various species showed a significantly positive correlation with the mean LST in autumn-LSTa (P < 0.01), which means the high accumulation of surface heat in autumn can drive leaf senescence to delay in Beijing’s urban area. The response sensitivity of LCD to the spatial variation of LSTa was (4.11 ± 0.83) d/℃ with F. pennsylvanica and M. glyptostroboides as the most sensitive species.
ConclusionThe leaf coloring date shows a significant response to the spatial variation of surface thermal environment in Beijing’s urban area. UHI effect represents the microcosms of long-term climate change, and the phenological response to thermal environment variation in urban area can reflect the potential impact of future climate change on plant phenology, i.e., a space-time substitution.
-
-
![]()
图 2 各树种秋色盛期的植株形态
Figure 2. Plant morphology of various tree species during the leaf coloring date
![]()
图 3 MOD11A1产品日间和夜间地温（LST）波段遥感数据（2019年10月20日影像）
Figure 3. Satellite data of day and night land surface temperature(LST) in MOD11A1 product (image of October 20th, 2019)
![]()
图 4 银杏雌株与雄株的秋色盛期对比
Figure 4. Comparison in leaf coloring date between female andmale ginkgo trees
![]()
图 6 2017—2019年北京主城区各样地秋季平均地温
Figure 6. Mean LST of autumn (LSTa) in various sample plots of Beijing’s urban area during 2017−2019
![]()
图 7 2017—2019年各树种秋色盛期与样地秋季平均地温的相关性
**指在0.01水平上显著相关。** refers to significant correlation at 0.01 level.
Figure 7. Correlations between leaf coloring date of various tree species and average autumn ground temperature (LST) of the sample plots
表 1 2017—2019年各树种秋色盛期数据（日序）
Table 1 Data in leaf coloring date (DOY) of various species during 2017−2019
树种
Tree species年份
Year样地 Sample plot 北京植物园
Beijing Botanical
Garden颐和园
Summer
Palace奥森南园
South Olympic
Forest Park地坛公园
Ditan
Park玉渊潭公园
Yuyuantan
Park北海公园
Beihai
Park景山公园
Jingshan
Park陶然亭公园
Taoranting
Park龙潭公园
Longtan
Park洋白蜡
Fraxinus
pennsylvanica2017 287.5 289.5 290.0 297.2 297.5 297.5 296.0 295.1 298.0 2018 295.0 297.2 298.9 305.0 303.7 305.5 303.0 306.3 303.3 2019 299.3 300.5 302.1 308.0 304.7 307.0 306.5 307.0 306.5 3年平均
Mean of three years293.9 295.7 297.0 303.4 301.9 303.3 301.8 302.8 302.6 元宝枫
Acer truncatum2017 301.5 302.0 302.5 309.0 308.5 311.0 305.0 309.0 311.0 2018 299.3 301.5 302.3 305.1 308.2 311.0 310.0 310.7 311.0 2019 308.1 308.0 309.0 313.5 311.3 316.0 312.5 314.2 314.3 3年平均
Mean of three years303.0 303.8 304.6 309.2 309.3 312.7 309.2 311.3 312.1 水杉
Metasequoia
glyptostroboides2017 312.5 312.3 313.8 318.0 319.0 319.4 317.0 318.0 321.0 2018 311.0 308.0 308.8 318.0 317.8 322.0 321.0 319.5 321.5 2019 313.2 311.5 312.5 319.5 320.0 319.0 318.0 321.0 319.6 3年平均
Mean of three years312.2 310.6 311.7 318.5 318.9 320.1 318.7 319.5 320.7 旱柳
Salix matsudana2017 322.2 324.1 325.4 330.0 331.8 329.4 330.0 331.3 333.0 2018 319.7 323.9 323.3 328.5 327.5 327.6 329.0 330.8 329.6 2019 318.0 319.8 319.0 325.0 325.4 327.6 326.0 327.3 326.5 3年平均
Mean of three years320.0 322.6 322.5 327.8 328.2 328.2 328.3 329.8 329.7 银杏
Ginkgo biloba2017 302.6 305.5 306.8 308.3 311.9 312.8 311.2 309.4 312.4 2018 304.7 308.0 307.0 311.0 311.1 313.7 311.5 314.7 312.8 2019 306.0 305.1 307.5 311.0 314.6 314.4 312.8 313.2 313.1 3年平均
Mean of three years304.4 306.2 307.1 310.1 312.5 313.6 311.8 312.5 312.7 银杏雌株♀
Female
G. biloba2017 297.4 304.3 303.0 305.8 309.1 307.0 308.2 309.3 308.0 2018 299.7 302.5 300.0 304.8 308.4 308.5 307.4 309.3 309.0 2019 301.2 303.0 302.7 305.9 309.0 309.0 310.7 307.8 308.5 3年平均
Mean of three years299.4 303.3 301.9 305.5 308.8 308.2 308.8 308.8 308.5 银杏雄株♂Male
G. biloba2017 307.4 313.7 310.6 317.0 315.6 315.3 314.2 317.8 316.0 2018 310.5 313.5 313.0 315.7 318.0 317.5 315.4 318.2 317.6 2019 309.6 313.7 310.0 315.2 319.0 318.4 317.0 317.6 317.5 3年平均
Mean of three years309.2 313.6 311.2 315.9 317.5 317.1 315.5 317.9 317.0 注：表中各样地的物候值取自样地内多样株的物候期均值。Note: phenology value for each sample plot takes the average phenology of multiple sampling trees in the sample plot. 
下载: 导出CSV
-
[1] Wang S, Gong D. Enhancement of the warming trend in China[J]. Geophysical Research Letters, 2000, 27(16): 2581−2584. doi: 10.1029/1999GL010825
[2] Neil K, Wu J. Effects of urbanization on plant flowering phenology: A review[J]. Urban Ecosystems, 2006, 9: 243−257. doi: 10.1007/s11252-006-9354-2
[3] Visser M E, Both C. Shifts in phenology due to global climate change: the need for a yardstick[J]. Proceedings of the Royal Society B, 2005, 272(1581): 2561−2569. doi: 10.1098/rspb.2005.3356
[4] Miller-Rushing A J, Høye T T, Inouye D W, et al. The effects of phenological mismatches on demography[J]. Philosophical Transactions of the Royal Society B: Biological Sciences, 2010, 365: 3177−3186. doi: 10.1098/rstb.2010.0148
[5] Richardson A D, Black T A, Ciais P, et al. Influence of spring and autumn phenological transitions on forest ecosystem productivity[J]. Philosophical Transactions of the Royal Society B: Biological Sciences, 2010, 365: 3227−3246. doi: 10.1098/rstb.2010.0102
[6] Tang J, Körner C, Muraoka H, et al. Emerging opportunities and challenges in phenology: a review[J]. Ecosphere, 2016, 7(8): e01436. doi: 10.1002/ecs2.1436
[7] 叶清, 焦庚英, 许晓利, 等. 物候学在植物季相景观规划中的应用[C]// 中国气象学会农业气象与生态学委员会, 江西省气象学会. 全国农业气象与生态环境学术年会论文集. 北京: 中国气象学会农业气象与生态学委员会, 2006: 409−411. Ye Q, Jiao G Y, Xu X L, et al. Application of phenology in the landscape planning of plant seasonal aspects [C]// Agricultural Meteorology and Ecology Committee of the Chinese Meteorological Society, Jiangxi Meteorological Society. Annual Conference Proceeding of National Agrometeorology and Ecology Committee. Beijing: Agrometeorology and Ecology Committee of Chinese Meteorological Society, 2006: 409−411.
[8] Nagai S, Saitoh T, Yoshitake S. Cultural ecosystem services provided by flowering of cherry trees under climate change: a case study of the relationship between the periods of flowering and festivals[J]. International Journal of Biometeorology, 2019, 63(4): 1051−1058.
[9] World Health Organization. Phenology and Human Health: Allergic Disorders: report of WHO Regional Office for Europe (No. 108750) [R]. Rome: WHO, 2003.
[10] Grimm N B, Faeth S H, Golubiewski N E, et al. Global change and the ecology of cities[J]. Science, 2008, 319: 756−760. doi: 10.1126/science.1150195
[11] Zhao S, Liu S, Zhou D. Prevalent vegetation growth enhancement in urban environment[J]. Proceedings of the National Academy of Sciences, 2016, 113: 6313−6318. doi: 10.1073/pnas.1602312113
[12] Farrell C, Szota C, Arndt S K. Urban plantings: ‘Living Laboratories’ for climate change response[J]. Trends in Plant Science, 2015, 20: 597−599. doi: 10.1016/j.tplants.2015.08.006
[13] Jia W, Zhao S, Zhang X, et al. Urbanization imprint on land surface phenology: the urban-rural gradient analysis for Chinese cities[J]. Global Change Biology, 2021, 27(12): 2895−2904. doi: 10.1111/gcb.15602
[14] 王静. 北京市土地利用空间格局对城市热岛强度的影响研究[D]. 呼和浩特: 内蒙古师范大学, 2014. Wang J. Impacts of spatial pattern of land use on urban heat island intensity in Beijing [D]. Huhhot: Inner Mongolia Normal University, 2014.
[15] 陈朱. 城市化对春季开花植物物候的影响[D]. 上海: 华东师范大学, 2011. Chen Z. Effects of urbanization on phenology of spring-flowering plants[D]. Shanghai: East China Normal University, 2011.
[16] Qiu T, Song C H, Li J X. Impacts of urbanization on vegetation phenology over the past three decades in Shanghai, China[J]. Remote Sensing, 2017, 9(9): 970−985. doi: 10.3390/rs9090970
[17] Zhou D, Zhao S, Zhang L, et al. Remotely sensed assessment of urbanization effects on vegetation phenology in China’s 32 major cities[J]. Remote Sensing of Environment, 2016, 176: 272−281. doi: 10.1016/j.rse.2016.02.010
[18] Yang J, Luo X, Jin C, et al. Spatiotemporal patterns of vegetation phenology along the urban-rural gradient in coastal Dalian, China [J/OL]. Urban Forestry & Urban Greening, 2020, 54: 126784[2021−09−20]. https://doi.org/10.1016/j.ufug.2020.126784Get.
[19] Melaas E K, Wang J A, Miller D L, et al. Interactions between urban vegetation and surface urban heat islands: a case study in the Boston metropolitan region[J/OL]. Environmental Research Letters, 2016, 11(5): 054020[2021−09−20]. https://doi.org/10.1088/1748-9326/11/5/054020.
[20] Mimet A, Pellissier V, Quénol H, et al. Urbaniszation induces early flowering: evidence from Platanus acerifolia and Prunus cerasus[J]. International Journal of Biometeorology, 2009, 53(3): 287−298. doi: 10.1007/s00484-009-0214-7
[21] Parece T, Campbell J. Intra-urban microclimate effects on phenology[J]. Urban Science, 2018, 2(26): 1−22.
[22] 曹广真, 侯鹏, 毛显强. 北京市城市化对地表温度时空特征的影响[J]. 气象, 2010, 36(3): 19−26. doi: 10.7519/j.issn.1000-0526.2010.03.003 Cao G Z, Hou P, Mao X Q. Impacts f urbanization on temporal and spatial characteristics of land surface temperature in Beijing[J]. Meteorological Monthly, 2010, 36(3): 19−26. doi: 10.7519/j.issn.1000-0526.2010.03.003
[23] Neil K, Wu J G, Bang C, et al. Urbanization affects plant flowering phenology and pollinator community: effects of water availability and land cover[J]. Ecological Processes, 2014, 3(17): 1−12.
[24] Katz D S, Dzul A, Kendel A, et al. Effect of intra-urban temperature variation on tree flowering phenology, airborne pollen, and measurement error in epidemiological studies of allergenic pollen[J]. Science of the Total Environment, 2019, 653: 1213−1222. doi: 10.1016/j.scitotenv.2018.11.020
[25] 王静, 常青, 柳冬良. 早春草本植物开花物候期对城市化进程的响应−以北京市为例[J]. 生态学报, 2014, 34(22): 6701−6710. Wang J, Chang Q, Liu D L. The flowering phenophase response of early spring herb to the urbanization process in Beijing[J]. Acta Ecologica Sinica, 2014, 34(22): 6701−6710.
[26] Woo H R, Kim H J, Lim P O, et al. Leaf senescence: systems and dynamics aspects[J]. Annual Review of Plant Biology, 2019, 70: 347−376. doi: 10.1146/annurev-arplant-050718-095859
[27] Wu C, Chen J M, Black T A, et al. Interannual variability of net ecosystem productivity in forests is explained by carbon flux phenology in autumn[J]. Global Ecology and Biogeography, 2013, 22(8): 994−1006. doi: 10.1111/geb.12044
[28] 董丽, 邢小艺. 气候变化对城市植被的影响研究综述[J]. 风景园林, 2021, 28(11): 61−67. Dong L, Xing X Y. Review of researches on impacts of climate change on urban vegetation[J]. Landscape Architecture, 2021, 28(11): 61−67.
[29] 宛敏渭, 刘秀珍. 中国物候观测方法[M]. 北京: 科学出版社, 1979. Wan M W, Liu X Z. Chinese phenological observation method [M]. Beijing: Science Press, 1979.
[30] 田丽媛. 温湿度对北京5种秋色叶树种秋叶变色的影响[D]. 北京: 北京林业大学, 2012. Tian L Y. The impact of temperature and humidity on five kinds of fall-color trees’ color changing in autumn of Beijing [D]. Beijing: Beijing Forestry University, 2012.
[31] Shi D, Wei X, Chen G, et al. Changes in photosynthetic characteristics and antioxidative protection in male and female ginkgo during natural senescence[J]. Journal of the American Society for Horticultural Science, 2012, 137(5): 349−360. doi: 10.21273/JASHS.137.5.349
[32] Curtis A E, Smith T A, Ziganshin B A, et al. The mystery of the Z-score[J]. Aorta, 2016, 4(4): 124−130.
[33] Alqasemi A S, Hereher M E, Al-Quraishi A M F, et al. Retrieval of monthly maximum and minimum air temperature using MODIS aqua land surface temperature data over the United Arab Emirates[J]. Geocarto International, 2020, 37(10): 2996−3013.
[34] Prevéy J, Vellend M, Rüger N, et al. Greater temperature sensitivity of plant phenology at colder sites: implications for convergence across northern latitudes[J]. Global Change Biology, 2017, 23(7): 2660−2671. doi: 10.1111/gcb.13619
[35] 杨敏, 杨贵军, 王艳杰, 等. 北京城市热岛效应时空变化遥感分析[J]. 国土资源遥感, 2018, 30(3): 213−223. Yang M, Yang G J, Wang Y J, et al. Remote sensing analysis of temporal-spatial variations of urban heat island effect over Beijing[J]. Remote Sensing for Land and Resources, 2018, 30(3): 213−223.
[36] Jeong S J, Park H, Ho C H, et al. Impact of urbanization on spring and autumn phenology of deciduous trees in the Seoul capital area, South Korea[J]. International Journal of Biometeorology, 2019, 63(5): 627−637. doi: 10.1007/s00484-018-1610-7
[37] Estiarte M, Peñuelas J. Alteration of the phenology of leaf senescence and fall in winter deciduous species by climate change: effects on nutrient proficiency[J]. Global Change Biology, 2015, 21(3): 1005−1017. doi: 10.1111/gcb.12804
[38] Yan H, Fan S, Guo C, et al. Assessing the effects of landscape design parameters on intra-urban air temperature variability: the case of Beijing, China[J]. Building and Environment, 2014, 76: 44−53. doi: 10.1016/j.buildenv.2014.03.007
[39] 陈睿智. 城市公园景观要素的微气候相关性分析[J]. 风景园林, 2020, 27(7): 94−99. Chen R Z. Microclimate correlation analysis of landscape elements in city parks[J]. Landscape Architecture, 2020, 27(7): 94−99.
[40] 游晓婕, 李琼, 孟庆林. 城市热岛空间格局及形态差异化调控策略研究: 以广州市中心城区为例[J]. 风景园林, 2021, 28(5): 74−79. You X J, Li Q, Meng Q L. Research on spatial patterns and morphological differentiation control strategy of urban heat islands: a case study of downtown area of Guangzhou City[J]. Landscape Architecture, 2021, 28(5): 74−79.
[41] 李膨利, Muhammad Amir Siddique, 樊柏青, 等. 下垫面覆盖类型变化对城市热岛的影响: 以北京市朝阳区为例[J]. 北京林业大学学报, 2020, 42(3): 99−109. Li P L, Siddique M A, Fan B Q, et al. Effects of land surface type changes on urban heat island: a case study of Chaoyang District, Beijing[J]. Journal of Beijing Forestry University, 2020, 42(3): 99−109.
[42] 范舒欣, 李坤, 张梦园, 等. 城市居住区绿地小微尺度下垫面构成对环境微气候的影响: 以北京地区为例[J]. 北京林业大学学报, 2021, 43(10): 100−109. Fan S X, Li K, Zhang M Y, et al. Effects of micro scale underlying surface type and pattern of urban residential area on microclimate: taking Beijing as a case study[J]. Journal of Beijing Forestry University, 2021, 43(10): 100−109.
[43] 王爱霞, 任光淳, 秦亚楠. 半干旱区城市广场树木形态对微气候的影响研究[J]. 风景园林, 2020, 27(7): 100−107. Wang A X, Ren G C, Qin Y N. Research on influence of tree shape of city squares on microclimate in semi-arid areas[J]. Landscape Architecture, 2020, 27(7): 100−107.
[44] 乔治, 黄宁钰, 徐新良, 等. 2003-2017 年北京市地表热力景观时空分异特征及演变规律[J]. 地理学报, 2019, 74(3): 475−489. Qiao Z, Huang N Y, Xu X L, et al. Spatio-temporal pattern and evolution of the urban thermal landscape in metropolitan Beijing between 2003 and 2017[J]. Acta Geographica Sinica, 2019, 74(3): 475−489.
[45] Fracheboud Y, Luquez V, Björkén L, et al. The control of autumn senescence in European aspen[J]. Plant Physiology, 2009, 149(4): 1982−1991. doi: 10.1104/pp.108.133249
[46] Way D A, Montgomery R A. Photoperiod constraints on tree phenology, performance and migration in a warming world[J]. Plant Cell & Environment, 2015, 38(9): 1725−1736.
[47] Estrella N, Menzel A. Responses of leaf coloring in four deciduous tree species to climate and weather in Germany[J]. Climate Research, 2006, 32(3): 253−267.
[48] Dai J, Wang H, Ge Q. Multiple phenological responses to climate change among 42 plant species in Xi’an, China[J]. International Journal of Biometeorology, 2012, 57(5): 749−758.
[49] Dai J, Wang H, Ge Q. The spatial pattern of leaf phenology and its response to climate change in China[J]. International Journal of Biometeorology, 2013, 58(4): 521−528.
[50] Liu Q, Piao S, Campioli M, et al. Modeling leaf senescence of deciduous tree species in Europe[J]. Global Change Biology, 2020, 26(7): 4104−4118. doi: 10.1111/gcb.15132
[51] Archetti M, Richardson A D, O’Keefe J, et al. Predicting climate change impacts on the amount and duration of autumn colors in a New England forest[J/OL]. PLoS One, 2013, 8(3): e57373[2022−02−22]. https://doi.org/10.1371/journal.pone.0057373.
[52] Lang W, Chen X, Qian S, et al. A new process-based model for predicting autumn phenology: How is leaf senescence controlled by photoperiod and temperature coupling?[J]. Agricultural and Forest Meteorology, 2019, 268: 124−135. doi: 10.1016/j.agrformet.2019.01.006
[53] Wu C, Wang J, Ciais P, et al. Widespread decline in winds delayed autumn foliar senescence over high latitudes[J/OL]. Proceedings of the National Academy of Sciences, 2021, 118(16): e2015821118[2022−02−22]. https://doi.org/10.1073/pnas.2015821118.
[54] Cook B I, Wolkovich E M, Davies T J, et al. Sensitivity of spring phenology to warming across temporal and spatial climate gradients in two independent databases[J]. Ecosystems, 2012, 15(8): 1283−1294. doi: 10.1007/s10021-012-9584-5
[55] Wilson K B, Baldocci D D. Seasonal and interannual variability of energy fluxes over a broadleaved temperate deciduous forest in North America[J]. Agricultural and Forest Meteorology, 2000, 100(1): 1−18. doi: 10.1016/S0168-1923(99)00088-X
[56] Xing X Y, Dong L, Konijnendijk C, et al. The Impact of microclimate on the reproductive phenology of female Populus tomentosa in a micro-scale urban green space in Beijing[J/OL]. Sustainability, 2021, 13(6): 3518[2022−03−23]. https://doi.org/10.3390/su13063518.
[57] Rosique-Esplugas C, Cottrell J E, Cavers S, et al. Clinal genetic variation and phenotypic plasticity in leaf phenology, growth and stem form in common ash ( Fraxinus excelsior L.)[J]. Forestry, 2021, 95(1): 83−94.
[58] Keskitalo J, Bergquist G, Gardestrom P, et al. A cellular timetable of autumn senescence[J]. Plant Physiology, 2005, 139(4): 1635−1648. doi: 10.1104/pp.105.066845
[59] Alberto F J, Aitken S N, Alía R, et al. Potential for evolutionary responses to climate change: evidence from tree populations[J]. Global Change Biology, 2013, 19: 1645−1661. doi: 10.1111/gcb.12181
-
期刊类型引用(6)
1. 张友谊，李松柏，钟磊. 基于地形因子的震后泥石流降雨阈值分析. 科学技术与工程. 2024(32): 13708-13717 . 
百度学术
2. 曹永强，张若凝，范帅邦. 辽宁省降雨型泥石流环境特征及分类预警. 华北水利水电大学学报(自然科学版). 2022(02): 60-68 . 百度学术
3. 曹永强，张若凝，李玲慧，路洁，宁月. 辽宁省泥石流与不同时间尺度下降水因子的关系研究. 灾害学. 2021(03): 51-56 . 百度学术
4. 乔建平. 降雨型滑坡泥石流灾害预警原理及系统结构. 人民长江. 2020(01): 50-55+74 . 百度学术
5. 胡凯衡，魏丽，刘双，李秀珍. 横断山区泥石流空间格局和激发雨量分异性研究. 地理学报. 2019(11): 2303-2313 . 百度学术
6. 凌訸，陶蓉，白晓华. 平凉鸭儿沟泥石流形成过程及特征分析. 甘肃水利水电技术. 2017(01): 18-21 . 百度学术
其他类型引用(3)
计量
- 文章访问数: 385
- HTML全文浏览量: 68
- PDF下载量: 49
- 被引次数: 9
