秦岭森林植被物候及其对气象因子的响应

doi:10.13866/j.azr.2021.04.18

摘要/Abstract

摘要：

研究山地过渡带植被物候格局以及植被物候变化的驱动机制具有重要意义。基于2000—2018年MODIS NDVI遥感数据,利用双Logistic曲线拟合法提取2000—2018年秦岭山地植被物候参数,结合气温和降水数据,运用趋势分析、相关分析、冗余分析等方法,研究秦岭山地不同物候期的时空变化特征和对气象因子的响应。结果表明:(1) 秦岭山地物候始期集中于60~102 d,物候末期主要集中在315~345 d,生长季长度集中在225~255 d,空间上看,具有明显的垂直地带分布特征,随海拔升高,物候始期、末期、生长期长度分别呈延迟、提前和缩短趋势。(2) 从植被物候的年际变化来看,物候始期62.25%的区域呈现提前趋势,53.42%的区域物候末期呈现推迟趋势,其中59.18%的区域植被生长期长度延长,仅有5.12%位于中东部中高海拔区的部分区域显著延长。(3) 植被物候始期大部分区域与2—5月平均气温和降水呈负相关关系,分别占总面积的50.29%和65.24%;物候末期与8—11月平均气温和月降水量主要呈正相关关系,分别占总区域的66.63%和59.77%;(4) 冗余分析(Redundancy analysis,RDA)结果表明秦岭山地植被物候受当季和前期气象因子的共同影响,春季物候受物候发生期的影响大于上年冬季,物候末期前期的气温和降水对秋季物候的影响强度大于秋季,不同坡向物候变化对气象因子的响应程度有所差异。

关键词: 物候变化, 气象因子, 冗余分析, 秦岭

Abstract:

It is important to investigate the vegetation phenology pattern and the driving mechanism of vegetation phenology change in a mountain transition zone. In this study, we used the double logistic curve fitting method to extract the phenological parameters of forest vegetation in the Qinling Mountains on the basis of the moderate resolution imaging spectro radiometer and normalized difference vegetation index time-series images from 2000 to 2018. Combining temperature and precipitation data, we performed trend analysis, correlation analysis, and redundancy analysis to study the characteristics of time and space changes in different phenological periods and the response to climate elements in the Qinling area. The following results were obtained: (1) The start and end of the growing season ranged from 60 days to 102 days and from 315 days to 345 days, respectively. The length of the growth season ranged from 225 days to 255 days. From a spatial perspective, it has evident vertical zone distribution characteristics. With an increase in altitude, the start, end, and growth periods of phenology were delayed, advanced, and shortened, respectively. (2) The beginning of phenology was advanced, whereas the end of phenology was postponed. The proportions of pixels in advance and delayed phenologies were 62.25% and 53.42%, respectively. The length of the growing season exhibited a lengthened trend of 59.18%. Of the significantly extended area, 5.12% area was mainly located in the middle and high altitude areas of the central and eastern regions. (3) The initial period of vegetation phenology was negatively correlated with the average temperature and precipitation from February to May, accounting for 50.29% and 65.24% of the total area, respectively. The end of phenology was positively correlated with the average temperature and precipitation from August to November, accounting for 66.63% and 59.77% of the total area, respectively. (4) Redundancy analysis results show that the vegetation phenology in the Qinling Mountains was affected by both the current season and the earlier period of meteorological factors. The spring phenology was more affected in the phenology occurrence period than in the winter of previous year. Compared with autumn weather factors, temperature and precipitation in the early period of phenology exhibit a more significant relationship with the end of phenology. The phenological changes of different slopes exhibit different responses to meteorological factors.

Key words: phenological change, meteorological factors, redundancy analys, Qinling

杨琪,李书恒,李家豪,王嘉川. 秦岭森林植被物候及其对气象因子的响应[J]. 干旱区研究, 2021, 38(4): 1065-1074.

YANG Qi,LI Shuheng,LI Jiahao,WANG Jiachuan. Phenology of forest vegetation and its response to climate change in the Qinling Mountains[J]. Arid Zone Research, 2021, 38(4): 1065-1074.

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参考文献 26

[1]	陆佩玲, 于强, 贺庆棠. 植物物候对气候变化的响应[J]. 生态学报, 2006, 26(3):923-929.
	[ Lu Peiling, Yu Qiang, He Qingtang. Responses of plant phenology to climatic change[J]. Acta Ecologica Sinica, 2006, 26(3):923-929. ]
[2]	Noormets A, Chen J, Gu L, et al. The phenology of gross ecosystem productivity and ecosystem respiration in temperate hardwood and conifer chronosequences[J]. Phenology of Ecosystem Processes, 2009, 59-85. DOI 10.1007/978-1-4419-0026-5_3.
[3]	Richardson A D, Keenan T F, Migliavacca M, et al. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system[J]. Agricultural and Forest Meteorology, 2013, 169(3):156-173. doi: 10.1016/j.agrformet.2012.09.012
[4]	Delbart N, Toan T L, Kergoat L, et al. Remote sensing of spring phenology in boreal region: A free of snow-effect method using NOAA-AVHRR and SPOT-VGT data (1982-2004)[J]. Remote Sensing of Environment, 2006, 101(1):52-62. doi: 10.1016/j.rse.2005.11.012
[5]	胡召玲, 戴慧, 侯飞, 等. 中国东北城乡植被物候时空变化及其对地表温度的响应[J]. 生态学报, 2020, 40(12):4137-4145.
	[ Hu Zhaoling, Dai Hui, Hou Fei, et al. Spatio-temporal change of urban-rural vegetation phenology and its response to land surface temperature in Northeast[J]. Acta Ecologica Sinica, 2020, 40(12):4137-4145. ]
[6]	杨光, 宋戈, 韦振锋, 等. 基于时序指数西北植被物候时空变化特征[J]. 水土保持研究, 2015, 22(6):213-218.
	[ Yang Guang, Song Ge, Wei Zhenfeng, et al. Characteristics of vegetation phenology in Northwest China based on sequential vegetation index[J]. Research of Soil and Water Conservation, 2015, 22(6):213-218. ]
[7]	孔冬冬, 张强, 黄文琳, 等. 1982-2013年青藏高原植被物候变化及气象因素影响[J]. 地理学报, 2017, 72(1):39-52. doi: 10.11821/dlxb201701004
	[ Kong Dongdong, Zhang Qiang, Huang Wenlin, et al. Vegetation phenology change in Tibetan Plateau from 1982 to 2013 and its related meteorological factors[J]. Acta Geographica Sinica, 2017, 72(1):39-52. ] doi: 10.11821/dlxb201701004
[8]	Xiao X, Hagen S, Zhang Q, et al. Detecting leaf phenology of seasonally moist tropical forests in South America with multi-temporal MODIS images[J]. Remote Sensing of Environment, 2006, 103(4):465-473. doi: 10.1016/j.rse.2006.04.013
[9]	俎佳星, 杨健. 东北地区植被物候时序变化[J]. 生态学报, 2016, 36(7):2015-2023.
	[ Zu Jiaxing, Yang Jian. Temporal variation of vegetation phenology in northeastern China[J]. Acta Ecologica Sinica, 2016, 36(7):2015-2023. ]
[10]	张百平. 中国南北过渡带研究的十大科学问题[J]. 地理科学进展, 2019, 38(3):305-311. doi: 10.18306/dlkxjz.2019.03.001
	[ Zhang Baiping. Ten major scientific issues concerning the study of China’s north-south transitional zone[J]. Progress in Geography, 2019, 38(3):305-311. ] doi: 10.18306/dlkxjz.2019.03.001
[11]	康慕谊, 朱源. 秦岭山地生态分界线的论证[J]. 生态学报, 2007, 27(7):2774-2784.
	[ Kang Muyi, Zhu Yuan. Discussionand analysis on the geo-ecological boundary in Qinling range[J]. Acta Ecologica Sinica, 2007, 27(7):2774-2784. ]
[12]	李双双, 延军平, 万佳. 全球气候变化下秦岭南北气温变化特征[J]. 地理科学, 2012, 32(7):853-858. doi: 10.13249/j.cnki.sgs.2012.07.853
	[ Li Shuangshuang, Yan Junping, Wan Jia. The characteristics of temperature change in Qinling Mountains[J]. Scientia Geographica Sinica, 2012, 32(7):853-858. ] doi: 10.13249/j.cnki.sgs.2012.07.853
[13]	李英杰, 延军平, 刘永林. 秦岭南北气候干湿变化与降水非均匀性的关系[J]. 干旱区研究, 2016, 33(3):619-627.
	[ Li Yingjie, Yan Junping, Liu Yonglin. Relationship between dryness wetness and precipitation heterogeneity in the North and South of the Qinling Mountains[J]. Arid Zone Research, 2016, 33(3):619-627. ]
[14]	Cong N, Piao S L, Chen A P, et al. Spring vegetation green-up date in China inferred from SPOT NDVI data: A multiple model analysis[J]. Agricultural and Forest Meteorology, 2012, 165:104-113. doi: 10.1016/j.agrformet.2012.06.009
[15]	于健, 徐倩倩, 刘文慧, 等. 长白山东坡不同海拔长白落叶松径向生长对气候变化的响应[J]. 植物生态学报, 2016, 40(1):24-35. doi: 10.17521/cjpe.2015.0216
	[ Yu Jian, Xu Qianqian, Liu Wenhui, et al. Response of radial growth to climate change for Larix olgensis along an altitudinal gradient on the eastern slope of Changbai Mountain[J]. Chinese Journal of Plant Ecology, 2016, 40(1):24-35. ] doi: 10.17521/cjpe.2015.0216
[16]	侯朝伟, 孙西艳, 刘永亮, 等. 烟台近海浮游动物优势种空间生态位研究[J]. 生态学报, 2020, 40(16):5822-5833.
	[ Hou Chaowei, Sun Xiyan, Liu Yongliang, et al. Spatial niches of dominant zooplankton species in the Yantai offshore waters[J]. Acta Ecologica Sinica, 2020, 40(16):5822-5833. ]
[17]	马源, 杨洁, 张德罡, 等. 高寒草甸退化对祁连山土壤微生物生物量和氮矿化速率的影响[J]. 生态学报, 2020, 40(8):2680-2690.
	[ Ma Yuan, Yang Jie, Zhang Degang, et al. Effects of alpine meadow degradation on soil microbial biomass and nitrogen mineralization rate in the Qilian Mountains[J]. Acta Ecologica Sinica, 2020, 40(8):2680-2690. ]
[18]	王小平, 杨雪, 杨楠, 等. 凋落物多样性及组成对凋落物分解及土壤微生物群落的影响——二氧化碳倍增条件下[J]. 生态学报, 2020, 40(17):6171-6178.
	[ Wang Xiaoping, Yang Xue, Yang Nan, et al. Effects of litter diversity and composition on litter decomposition characteristics and soil microbial community: Under the conditions of doubling ambient atmospheric CO₂ concentration[J]. Acta Ecologica Sinica, 2020, 40(17):6171-6178. ]
[19]	仲舒颖, 葛全胜, 郑景云, 等. 近30年北京自然历的主要物候期、物候季节变化及归因[J]. 植物生态学报, 2012, 36(12):1217-1225. doi: 10.3724/SP.J.1258.2012.01217
	[ Zhong Shuying, Ge Quansheng, Zheng Jingyun, et al. Changes of main phenophases of natural calendar and phenological seasons in Beijing for the last 30 years[J]. Chinese Journal of Plant Ecology, 2012, 36(12):1217-1225. ] doi: 10.3724/SP.J.1258.2012.01217
[20]	邓晨晖, 白红英, 马新萍, 等. 2000-2017年秦岭山地植被物候变化特征及其南北差异[J]. 生态学报, 2021, 41(3):1068-1080.
	[ Deng Chenhui, Bai Hongying, Ma Xinping, et al. Variation characteristics and its north-south differences of the vegetation phenology by remote sensing monitoring in the Qinling Mountains during 2000-2017[J]. Acta Ecologica Sinica, 2021, 41(3):1068-1080. ]
[21]	夏浩铭, 李爱农, 赵伟, 等. 2001-2010年秦岭森林物候时空变化遥感监测[J]. 地理科学进展, 2015, 34(10):1297-1305. doi: 10.18306/dlkxjz.2015.10.010
	[ Xia Haoming, Li Ainong, Zhao Wei, et al. Spatiotemporal variations of forest phenology in the Qinling zone based on remote sensing monitoring 2001-2010[J]. Progress in Geography, 2015, 34(10):1297-1305. ] doi: 10.18306/dlkxjz.2015.10.010
[22]	郭少壮, 白红英, 黄晓月, 等. 秦岭太白红杉林遥感物候提取及对气候变化的响应[J]. 生态学杂志, 2019, 38(4):1123-1132.
	[ Guo Shaozhuang, Bai Hongying, Huang Xiaoyue, et al. Remote sensing phenology of Larix chinensis forest in response to climate change in Qinling Mountains[J]. Chinese Journal of Ecology, 2019, 38(4):1123-1132. ]
[23]	马新萍, 白红英, 贺映娜, 等. 基于NDVI的秦岭山地植被遥感物候及其与气温的响应关系——以陕西境内为例[J]. 地理科学, 2015, 35(12):1616-1621. doi: 10.13249/j.cnki.sgs.2015.012.1616
	[ Ma Xinping, Bai Hongying, He Yingna, et al. The vegetation remote sensing phenology of Qinling Mountains based on NDVI and it’s response to temperature: Taking within the territory of Shaanxi as an example[J]. Scientia Geographica Sinica, 2015, 35(12):1616-1621. ] doi: 10.13249/j.cnki.sgs.2015.012.1616
[24]	李登科, 王钊. 基于MCD12Q2的秦岭植被物候时空变化及对气候的响应[J]. 生态环境学报, 2020, 29(1):11-22.
	[ Li Dengke, Wang Zhao. Spatiotemporal variation of vegetation phenology and its response to climate in Qinling Mountains based on MCD12Q2[J]. Ecology and Environmental sciences, 2020, 29(1):11-22. ]
[25]	王连喜, 陈怀亮, 李琪, 等. 植物物候与气候研究进展[J]. 生态学报, 2010, 30(2):447-454.
	[ Wang Lianxi, Chen Huailiang, Li Qi, et al. Research advances in plant phenology and climate[J]. Acta Ecologica Sinica, 2010, 30(2):447-454. ]
[26]	顾润源, 周伟灿, 白美兰, 等. 气候变化对内蒙古草原典型植物物候的影响[J]. 生态学报, 2012, 32(3):767-776.
	[ Gu Runyuan, Zhou Weican, Bai Meilan, et al. Impacts of climate change on phenological phase of herb in the main grassland in Inner Mongolia[J]. Acta Ecologica Sinica, 2012, 32(3):767-776. ]

月份	北坡气温		北坡降水		南坡气温		南坡降水
月份	第1轴排序	第2轴排序	第1轴排序	第2轴排序	第1轴排序	第2轴排序	第1轴排序	第2轴排序
10	-0.30	0.00	-0.04	0.00	0.39	0.00	0.50	0.00
11	0.49	0.00	0.26	0.00	-0.14	0.00	-0.82^*	0.00
12	0.29	0.00	0.69^*	0.00	0.30	0.00	0.03	0.00
1	-0.01	0.00	-0.04	0.00	0.20	0.00	0.61	0.00
2	-0.14	0.00	-0.53	0.00	-0.03	0.00	0.05	0.00
3	-0.29	0.00	0.01	0.00	-0.71^*	0.00	-0.19	0.00
4	0.78^*	0.00	-0.56	0.00	-0.49^*	0.00	0.34	0.00
5	0.15	0.00	-0.12	0.00	0.20	0.00	0.11	0.00

月份	北坡气温		北坡降水		南坡气温		南坡降水
月份	第1轴排序	第2轴排序	第1轴排序	第2轴排序	第1轴排序	第2轴排序	第1轴排序	第2轴排序
4	0.52	0.00	0.82^*	0.00	0.13	0.00	0.03	0.00
5	0.47	0.00	0.20	0.00	0.16	0.00	0.80^*	0.00
6	0.41	0.00	0.06	0.00	-0.01	0.00	-0.61	0.00
7	-0.29	0.00	-0.38	0.00	0.27^*	0.00	0.15	0.00
8	-0.26	0.00	-0.20	0.00	0.15	0.00	0.23	0.00
9	-0.41	0.00	0.10	0.00	-0.27	0.00	-0.04	0.00
10	-0.53	0.00	-0.18	0.00	-0.64^*	0.00	-0.27	0.00
11	0.03	0.00	0.46	0.00	0.01	0.00	0.40	0.00