不同地形梯度上的植被变化趋势及原因分析
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摘要
植被变化趋势的地形分异规律对于理解其驱动因素具有重要意义。为了探索植被变化趋势的地形梯度分异规律和原因,以MODISNDVI为数据源,利用Mann-kendall方法分析2000-2015年贵州省植被的变化趋势,通过地形位指数(TNI)和分布指数分析植被变化趋势的地形梯度分异规律,并结合气候、土地利用和扰动类型数据分析其形成原因。结果表明,(1)在空间分布上,NDVI呈极显著降低趋势(Z≤-2.32,P≤0.01)的栅格占研究区总面积的3.8%,主要分布在北部、东北和东南部区域;极显著增加趋势(Z≥2.32,P≤0.01)的栅格占研究区总面积的3.7%,主要分布在西部、西南和东北部地区。(2)低(1-4)和高(9-12)地形位是NDVI呈显著减少趋势的栅格的优势分布区,而中(5-8)地形位是NDVI显著增加趋势的栅格的优势分布区。(3)低地形位上NDVI显著降低的栅格中,49.2%存在NDVI变化趋势的突变,其中33.5%是由于建设开发和林地退化等原因导致。(4)中地形位上NDVI显著增加的栅格中,扰动后修复的比例达到30.7%,主要是由于生态修复促使NDVI显著增加。(5)高地形位上NDVI显著增加的栅格中86.2%在研究时段内未发生植被扰动。这部分栅格中,NDVI与夏季气温呈负相关的比例分别占东部和中部地貌区总面积的97%和96.5%。综上,人为活动是导致低地形位NDVI显著减少和中地形位NDVI显著增加的主要原因;高地形位内NDVI值的显著下降与春季和夏季气温升高有关。植被变化趋势的地形梯度分异规律能够反映出植被变化的直接驱动因素。在生态环境保护过程中,针对不同地形梯度上的植被应该采取不同的保护措施:低地形位区重点关注人为活动对植被的扰动;中地形位区重点关注生态工程的治理成效和不合理的土地利用方式,避免植被恢复与退化的同时发生;高地形位上通过实地监测密切关注植被对全球气候变暖的响应。
Topographic variation of vegetation dynamics is critical for understanding the responds of vegetation changes to drivers.Taking satellite-derived normalized difference vegetation index(NDVI) as the proxy of vegetation growth, the trend of vegetation change in 2000-2015 was calculated by using MODIS NDVI data and Mann-kendall method; the topographic variation of vegetation change trend was analyzed with the terrain niche index(TNI) and terrain niche distribution index, and its main driving factors were investigated with forest disturbances, land use and climate data. The results showed that:(1) the grids with an extremely significant decreasing trend of NDVI(Z≤-2.32, P≤0.01) accounted for 3.8% of the study area, and distributed mainly in the northwest, northeast and southeast regions. The grids with an extremely significant increasing trend(Z≥2.32, P≤0.01) accounted for 3.7% of the study area, mainly distributed in the western, southwestern and northeastern regions.(2) Grids of significantly reduced NDVI were dominated by areas with low(1-4) and high(9-12) TNI, while grids of remarkably increased NDVI were dominated by areas with middle TNI(5-8).(3) Inside the regions with significantly decrease NDVI and low TNI, 49.2% of the pixels showed sudden change of NDVI change rate, and 33.5% of which was induced by construction and forest degradation.(4) Inside the regions of significantly increased NDVI and middle TNI, the percent of restored after disturbance accounted for 30.7%, mainly due to the significant increase of NDVI caused by ecological restoration. And(5) the 86.2% of pixels with significantly increased NDVI showed no vegetation disturbance, in which the pixels had negative relationship between NDVI and summer temperature accounted for 97% and 96.5% in the east and central geomorphic regions, respectively. To sum up, human activities is the main cause for the significant NDVI decrease in the low terrain niche areas and remarkable NDVI increase in the middle terrain niche region. A significant NDVI decrease in the high terrain niche area may relate to temperature increase in spring and summer. Different vegetation protection methods should be applied according to the level of TNI: the vegetation disturbance caused by human activities should be emphasized in the low TNI area; the effect of ecological engineering and unsuitable land use needs to be paid attention in the middle TNI region to prevent the dual track effect of vegetation restoration and degradation; the response of vegetation to global warming needs to be monitored in high TNI region.
Topographic variation of vegetation dynamics is critical for understanding the responds of vegetation changes to drivers.Taking satellite-derived normalized difference vegetation index(NDVI) as the proxy of vegetation growth, the trend of vegetation change in 2000-2015 was calculated by using MODIS NDVI data and Mann-kendall method; the topographic variation of vegetation change trend was analyzed with the terrain niche index(TNI) and terrain niche distribution index, and its main driving factors were investigated with forest disturbances, land use and climate data. The results showed that:(1) the grids with an extremely significant decreasing trend of NDVI(Z≤-2.32, P≤0.01) accounted for 3.8% of the study area, and distributed mainly in the northwest, northeast and southeast regions. The grids with an extremely significant increasing trend(Z≥2.32, P≤0.01) accounted for 3.7% of the study area, mainly distributed in the western, southwestern and northeastern regions.(2) Grids of significantly reduced NDVI were dominated by areas with low(1-4) and high(9-12) TNI, while grids of remarkably increased NDVI were dominated by areas with middle TNI(5-8).(3) Inside the regions with significantly decrease NDVI and low TNI, 49.2% of the pixels showed sudden change of NDVI change rate, and 33.5% of which was induced by construction and forest degradation.(4) Inside the regions of significantly increased NDVI and middle TNI, the percent of restored after disturbance accounted for 30.7%, mainly due to the significant increase of NDVI caused by ecological restoration. And(5) the 86.2% of pixels with significantly increased NDVI showed no vegetation disturbance, in which the pixels had negative relationship between NDVI and summer temperature accounted for 97% and 96.5% in the east and central geomorphic regions, respectively. To sum up, human activities is the main cause for the significant NDVI decrease in the low terrain niche areas and remarkable NDVI increase in the middle terrain niche region. A significant NDVI decrease in the high terrain niche area may relate to temperature increase in spring and summer. Different vegetation protection methods should be applied according to the level of TNI: the vegetation disturbance caused by human activities should be emphasized in the low TNI area; the effect of ecological engineering and unsuitable land use needs to be paid attention in the middle TNI region to prevent the dual track effect of vegetation restoration and degradation; the response of vegetation to global warming needs to be monitored in high TNI region.
引文
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SWEETING M M,1995.Karst in China:it’s geomorphology and environment[M].New York:Springer.
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TONG X W,WANG K L,BRANDT M,et al.,2016.Assessing future vegetation trends and restoration prospects in the Karst regions of southwest China[J].Remote Sensing,8(5):357.
TUCKER C J,SELLERS P J,1986.Satellite remote sensing of primary production[J].International Journal of Remote Sensing,7(11):1395-1416.
VERBESSELT J,HYNDMAN R,NEWNHAM G,et al.,2010.Detecting trend and seasonal changes in satellite image time series[J].Remote Sensing of Environment,114(1):106-115.
WANG S J,ZHANG D F,LI R L,2002.Mechanism of rocky desertification in the Karst mountain Areas of Guizhou province,southwest China[J].International Review for Environmental Strategies,3(1):123-135.
YANG Q Y,JIANG Z C,YUAN D X,et al.,2014.Temporal and spatial changes of karst rocky desertification in ecological reconstruction region of Southwest China[J].Environmental Earth Sciences,72(11):4483-4489.
YANG S T,WANG B,CHENG H G,et al.,2004.The vegetation cover over last 20 years in karst region of Guizhou province using AVHRRdata[C]//Alaska:Anchorage.2004 IEEE International Geoscience and Remote Sensing Symposium:3456-3459.
郜红娟,张朝琼,张凤太,2015.基于地形梯度的贵州省土地利用时空变化分析[J].四川农业大学学报,33(1):62-70.GAO H J,ZHANG C Q,ZHANG F T,2015.Spatio-temporal patterns of land use change in Guizhou province base on terrain gradient[J].Journal of Sichuan Agricultural University,33(1):62-70.
贵州省农业地貌区划编委会,1989.贵州省农业地貌区划(省级卷)[M].贵阳:贵州人民出版社:62-63.Guizhou agricultural landform zoning editorial committee,1989.Agriculture landform division in Guizhou province[M].Guiyang:Guizhou People’s Publishing House:62-63.
马士彬,安裕伦,2008.喀斯特地区土地利用与坡度因子关系分析:以贵州省都匀市为例[J].贵州师范大学学报(自然科学版),26(1):18-21.MA S B,AN Y L,2008.Relationship between terrain slope and land-use in Karst areas:A case study of Duyun city in Guizhou province[J].Journal of Guizhou Normal University(Natural Sciences),26(1):18-21.
马士彬,张勇荣,安裕伦,2012.山区城市土地利用动态空间分布特征:以贵州省六盘水市为例[J].自然资源学报,27(3):489-496.MA S B,ZHANG Y R,AN Y L,2012.Spatial pattern of urban land use in the mountain area:A case study of Liupanshui in Guizhou province[J].Journal of Natural Resources,27(3):489-496.
欧阳志云,王桥,郑华,等,2014.全国生态环境十年变化(2000-2010年)遥感调查评估[J].中国科学院院刊,29(4):462-466.OUYANG Z Y,WANG Q,ZHENG H,et al.,2014.National Ecosystem Survey and Assessment of China(2000-2010)[J].Bulletin of Chinese Academy of Sciences,29(4):462-466.
熊康宁,黎平,周忠发,等,2002.喀斯特石漠化的遥感:GIS典型研究[M].北京:地质出版社:26-28.XIONG K N,LI P,ZHOU Z F,et al.,2002.Remote sensing:GISstudy of Karst rocky desertification[M].Beijing:Geological Publishing House:26-28.
喻红,曾辉,江子瀛,2001.快速城市化地区景观组分在地形梯度上的分布特征研究[J].地理科学,21(1):64-69.YU H,ZENG H,JIANG Z Y,2001.Study on distribution characteristics of landscape elements along the terrain gradient[J].Scientia Geogr Aphica Sinica,21(1):64-69.
周忠发,朱昌丽,谭玮颐,等,2019.基于空间开发适宜性评价的石漠化地区可持续发展研究:以贵州省盘州市为例[J].贵州师范大学学报(自然科学版),37(1):1-9.ZHOU Z F,ZHU C L,TAN W Y,et al.,2019.Research on sustainable development of rocky desertification region based on spatial development suitability:A case of Panzhou city,Guizhou province[J].Journal of Guizhou Normal University(Natural Sciences),37(1):1-9.
CAI S S,LIU D S,2015.Detecting change dates from dense satellite time series using a sub-annual change detection algorithm[J].Remote Sensing,7(7):8705-8727.
DE JONG R,VERBESSELT J,SCHAEPMAN M E,et al.,2012.Trend changes in global greening and browning:contribution of short-term trends to longer-term change[J].Global Change Biology,18(2):642-655.
FORKEL M,CARVALHAIS N,VERBESSELT J,et al.,2013.Trend change detection in NDVI time series:Effects of inter-annual variability and methodology[J].Remote Sensing,5:2113-2144.
HOU W J,GAO J B,WU S H,et al.,2015.Interannual variations in growing-season NDVI and its correlation with climate variables in the southwestern Karst region of China[J].Remote Sensing,7(9):11105-11124.
KENDALL M G,1970.Rank Correlation Methods[M].London:Griffin:19-33.
KENNEDY R E,YANG Z Q,COHEN W B,2010.Detecting trends in forest disturbance and recovery using yearly landsat time series:1.landtrendr-temporal segmentation algorithms[J].Remote Sensing of Environment,114(12):2897-2910.
MANN H B,1945.Nonparametric tests against trend[J].Econometrica,13(3):245-259.
PAN N Q,FENG X M,FU B J,et al.,2018.Increasing global vegetation browning hidden in overall vegetation greening:Insights from time-varying trends[J].Remote Sensing of Environment,214:59-72.
RODRIGUEZ-ITUR I,PORPORATO A,LAION F,et al.,2001.Intensive or extensive use of soil moisture:plant strategies to cope with stochastic water availability[J].Geophysical Research Letters,28(23):4495-4497.
SWEETING M M,1995.Karst in China:it’s geomorphology and environment[M].New York:Springer.
TIAN Y C,BAI X Y,WANG S J,et al.,2017.Spatial-temporal changes of vegetation cover in Guizhou province,southern China[J].Chinese Geographical Science,27(1):25-38.
TONG X W,WANG K L,BRANDT M,et al.,2016.Assessing future vegetation trends and restoration prospects in the Karst regions of southwest China[J].Remote Sensing,8(5):357.
TUCKER C J,SELLERS P J,1986.Satellite remote sensing of primary production[J].International Journal of Remote Sensing,7(11):1395-1416.
VERBESSELT J,HYNDMAN R,NEWNHAM G,et al.,2010.Detecting trend and seasonal changes in satellite image time series[J].Remote Sensing of Environment,114(1):106-115.
WANG S J,ZHANG D F,LI R L,2002.Mechanism of rocky desertification in the Karst mountain Areas of Guizhou province,southwest China[J].International Review for Environmental Strategies,3(1):123-135.
YANG Q Y,JIANG Z C,YUAN D X,et al.,2014.Temporal and spatial changes of karst rocky desertification in ecological reconstruction region of Southwest China[J].Environmental Earth Sciences,72(11):4483-4489.
YANG S T,WANG B,CHENG H G,et al.,2004.The vegetation cover over last 20 years in karst region of Guizhou province using AVHRRdata[C]//Alaska:Anchorage.2004 IEEE International Geoscience and Remote Sensing Symposium:3456-3459.
郜红娟,张朝琼,张凤太,2015.基于地形梯度的贵州省土地利用时空变化分析[J].四川农业大学学报,33(1):62-70.GAO H J,ZHANG C Q,ZHANG F T,2015.Spatio-temporal patterns of land use change in Guizhou province base on terrain gradient[J].Journal of Sichuan Agricultural University,33(1):62-70.
贵州省农业地貌区划编委会,1989.贵州省农业地貌区划(省级卷)[M].贵阳:贵州人民出版社:62-63.Guizhou agricultural landform zoning editorial committee,1989.Agriculture landform division in Guizhou province[M].Guiyang:Guizhou People’s Publishing House:62-63.
马士彬,安裕伦,2008.喀斯特地区土地利用与坡度因子关系分析:以贵州省都匀市为例[J].贵州师范大学学报(自然科学版),26(1):18-21.MA S B,AN Y L,2008.Relationship between terrain slope and land-use in Karst areas:A case study of Duyun city in Guizhou province[J].Journal of Guizhou Normal University(Natural Sciences),26(1):18-21.
马士彬,张勇荣,安裕伦,2012.山区城市土地利用动态空间分布特征:以贵州省六盘水市为例[J].自然资源学报,27(3):489-496.MA S B,ZHANG Y R,AN Y L,2012.Spatial pattern of urban land use in the mountain area:A case study of Liupanshui in Guizhou province[J].Journal of Natural Resources,27(3):489-496.
欧阳志云,王桥,郑华,等,2014.全国生态环境十年变化(2000-2010年)遥感调查评估[J].中国科学院院刊,29(4):462-466.OUYANG Z Y,WANG Q,ZHENG H,et al.,2014.National Ecosystem Survey and Assessment of China(2000-2010)[J].Bulletin of Chinese Academy of Sciences,29(4):462-466.
熊康宁,黎平,周忠发,等,2002.喀斯特石漠化的遥感:GIS典型研究[M].北京:地质出版社:26-28.XIONG K N,LI P,ZHOU Z F,et al.,2002.Remote sensing:GISstudy of Karst rocky desertification[M].Beijing:Geological Publishing House:26-28.
喻红,曾辉,江子瀛,2001.快速城市化地区景观组分在地形梯度上的分布特征研究[J].地理科学,21(1):64-69.YU H,ZENG H,JIANG Z Y,2001.Study on distribution characteristics of landscape elements along the terrain gradient[J].Scientia Geogr Aphica Sinica,21(1):64-69.
周忠发,朱昌丽,谭玮颐,等,2019.基于空间开发适宜性评价的石漠化地区可持续发展研究:以贵州省盘州市为例[J].贵州师范大学学报(自然科学版),37(1):1-9.ZHOU Z F,ZHU C L,TAN W Y,et al.,2019.Research on sustainable development of rocky desertification region based on spatial development suitability:A case of Panzhou city,Guizhou province[J].Journal of Guizhou Normal University(Natural Sciences),37(1):1-9.