毛乌素沙地乌审旗境内NDVI与环境因子的尺度响应
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摘要
尺度是正确理解格局与过程相互作用的关键。格局、过程与尺度间的依赖关系是景观生态学研究中的核心问题之一。格局和过程对不同尺度上干扰的响应,是自然系统内在的复杂时空异质性的主要来源。
毛乌素沙地处于荒漠、荒漠草原向森林草原的生态过渡带,荒漠化过程在不同时间和空间尺度显著作用于沙地生态系统的格局变化,是开展不同时空尺度下荒漠化进展过程和驱动机制研究的理想地区。系统地研究毛乌素沙地景观、植被格局空间异质性及其对不同时空尺度下气候、地形因子的响应,有助于理解探索荒漠化的进展过程和驱动机制,为科学监测评价荒漠化动态变化、合理制定防治荒漠化策略提供依据。
本文以地处毛乌素沙地腹地的乌审旗为研究对象,筛选出适宜当地的气候因子空间化插值方法并分析其年际变化的周期性振荡特征；在生态学、应用数学的理论和3S技术支持下,分别在南北和东西走向设置5条重采样样带共17328个像元,获得1990年、2005年和2009年毛乌素沙地植被指数(-1≤NDVI≤1)、植被覆盖(NDVI≥0)、主要气候因子和基本地形因子数据,采用原始尺度、小波多尺度细节系数相关分析、多元逐步回归分析等分析方法,分析植被—气候—地形空间格局特征及其不同尺度下响应规律,得出如下结论：
(1)在现有数据密度的条件下,内蒙古地区降水和相对湿度适宜采用以原始数据四球球面模型和合理二次模型为半变异函数模型模拟数据空间变化趋势的普通克里格法进行空间数据插值,以幂指数取3时的反距离加权法作为气温适宜的空间化插值算法。
(2)近40年来内蒙古毛乌素沙地年平均气温上升0.401℃/10a,年降水和年平均相对湿度的变化趋势不明显。气候年际变化的周期性振荡存在多重时间尺度上的复杂嵌套结构。
(3)植被指数(-1≤NDVI≤1)、植被覆盖、主要气候因子和基本地形因子小波多分辨率分析的特征尺度规律为：植被指数(-1≤NDVI≤1)、植被覆盖、主要气候因子和基本地形因子的空间异质性随尺度上推增大,并倾向于大尺度水平表达。植被指数(-1≤NDVI≤1)和植被覆盖(NDVI≥0)空间格局具复杂的非线性特征,研究区气候因子和海拔高度在研究尺度范围内不存在特征尺度,坡度和坡向的特征尺度具有复杂的空间分布特征。
(4)在原始尺度下,植被覆盖与气候、地形因子的多元逐步回归分析结果表明：在降水大的年份,降水、相对湿度、气温对植被覆盖的影响作用要强于地形因子,而在降水少,气候干旱的年份,坡度、海拔高度等局部地形因素对于植被的覆盖影响要强于气候因子。
(5)植被指数(-1≤NDVI≤1)、植被覆盖与气候、地形因子间具复杂的尺度相关特征,最大相关尺度多出现在中高尺度,表明气候和地形的作用均倾向于表现在宏观水平。气温与植被指数(-1≤NDVI≤1)、植被覆盖的敏感尺度较少,降水与植被指数(-1≤NDVI≤1)、植被覆盖具多重尺度的显著、极显著相关,坡度、坡向与植被指数(-1≤NDVI≤1)存在宏观和微观尺度的制约关系,海拔高度、坡向与植被覆盖具多重尺度的制约关系。多尺度相关分析有利于揭示格局和过程中的尺度响应,了解格局形成过程中,各因子在不同尺度上的作用。
(6)荒漠化过程与尺度、格局密切相关。荒漠化过程存在着时空尺度差异,这种差异表现在荒漠化敏感尺度与驱动因素的变化上。就毛乌素沙地而言,固定、半固定沙地,梁滩、河谷的荒漠化过程及驱动机制在风蚀、水蚀、盐渍化的交替作用下难以用统—尺度来度量,因此应从多重尺度对荒漠化过程进行监测和评价,为科学合理地制定防治策略提供依据。
Scale is the key to correctly understand the interaction between patterns and processes. Dependencies relationship between pattern, process and scale is one of the core issues in landscape ecology. The patterns and processes in response to disturbances in different scales is the main source of the inherent and complex heterogeneity of natural systems in time and space.
Mu Us Sandland located in ecological transition zone from desert or desert steppe to forest steppe. The process of desertification plays a significant role in pattern changes of sand ecosystems in different time and space scale, which is an ideal site to carry out the research of desertification processes and its driving mechanism with different spatial and temporal scales. The landscape, vegetation patterns of spatial heterogeneity and its response to climate and the topographic factor of Mu Us Sandland under different spatial and temporal scales would be systematicly studied, which would help to understand and explore the progress of desertification process and driving mechanism, to scientificly monitor and evaluate the dynamic of desertification and to provide the basis for the formulation strategy of desertification prevention.
Taken Wushen County in the hinterland of Mu Us Sandland as objects, screened out the suitable spatial interpolation method of climatic factors of local area and analyzed it's periodic oscillation characteristics of interannual variability, based on the theory of ecological and applied mathematics and on the3S technology, set five re-sampling transects from north to south and from east to west (totally17328pixel), data about vegetation index (-1≤NDVI≤1) with vegetation coverage (NDVI>0) and the principal climate factor with basic topographic factor in1990,2005and2009in Mu Us Sandland was get. Using analysis methods of the detail coefficients of wavelet multi-scale correlation and stepwise multiple regression at original scale, spatial patterns of vegetation-climate-topography and response law at different scales were analyzed. The following conclusions were getting:
(1) Under the conditions of the existing data density, data about precipitation and relative humidity of Inner Mongolia was appropriate to adopt the Ordinary Kriging with tetraspherical and rational quadratic as semivariogram model of the raw data for optimal spatial data interpolation method, Inverse Distance Weighting with p=3is optimal spatial interpolation method about average annual atmospheric temperature.
(2) The annual average temperature of Mu Us Sandland in Inner Mongolia in the past41years increased by0.401℃/10a, the trends of annual precipitation and annual mean relative humidity are not obvious. Complex nested structure was existed in periodic oscillation of climate change at multiple time scales.
(3) The characteristic scales of regularity in vegetation index (-1≤NDVI<1) with vegetation cover and the principal climate factors with basic topographic factors getting by the wavelet multi-resolution analysis was shown as follow: vegetation index (-1≤NDVI≤1), vegetation cover, the spatial heterogeneity of the major climatic factors and basic topographic factors increased with scale-up and tend to express at large-scale. The spatial patterns of the vegetation index (-1≤NDVI≤1) and vegetation cover (NDVI≥0) were of a complex non-linear characteristics. No characteristic scale was found with climatic factors and elevation of the study area in the research scales. The characteristic scale of the slope and aspect were complex in spatial distribution.
(4) In the original scale, the results of multiple stepwise regression analysis of vegetation cover and climate with topographic factors showed that: in the year with high yield of precipitation, the effects of precipitation, relative humidity, temperature on the vegetation cover were stronger than the effect of the topographic factor. While in the year with low yield of rainfall, the effects of local topographic factors of slope and elevation on the vegetation cover were stronger than the effect of climatic factors.
(5) There are complex characteristics in scale between vegetation index (-1≤NDVI≤1) with the vegetation cover and climate with topographic factors. The maximum correlation scale was often observed in middle and large scale. This indicates that the role of meteorological and topographic tend to show at the macroscopical level. The sensitive scale of temperature and vegetation index (-1≤NDVI≤1) with vegetation cover was small. Precipitation and vegetation index (-1≤NDVI≤1) with vegetation cover were significantly or extremely related with each other at multi-scale. Vegetation index (-1≤NDVI≤1) was related with slope and aspect at macro-and micro-scale. There are multiple relationships in scales between vegetation cover and elevation with aspect, which is helpful to reveal the patterns and processes in response to scales, to understand the role of various factors at different scales during the process of pattern formation.
(6) The process of desertification was closely related with scale and pattern. There were differences in the process of desertification in spatial and temporal scales. This difference was indicated in the changes of desertification in sensitive scale and in the driving factors. To Mu Us Sandland, it is difficult to measure the desertification process and driving mechanism under a unified scale in fixed or semi-fixed sandland and bottomla- nd with the valley since which is impacted by wind or water erosion and salinization. So the desertification monitoring and evaluation should be done in multiple scales, which would provide a basis for drafting the control strategies scientifically and rationally.
毛乌素沙地处于荒漠、荒漠草原向森林草原的生态过渡带,荒漠化过程在不同时间和空间尺度显著作用于沙地生态系统的格局变化,是开展不同时空尺度下荒漠化进展过程和驱动机制研究的理想地区。系统地研究毛乌素沙地景观、植被格局空间异质性及其对不同时空尺度下气候、地形因子的响应,有助于理解探索荒漠化的进展过程和驱动机制,为科学监测评价荒漠化动态变化、合理制定防治荒漠化策略提供依据。
本文以地处毛乌素沙地腹地的乌审旗为研究对象,筛选出适宜当地的气候因子空间化插值方法并分析其年际变化的周期性振荡特征；在生态学、应用数学的理论和3S技术支持下,分别在南北和东西走向设置5条重采样样带共17328个像元,获得1990年、2005年和2009年毛乌素沙地植被指数(-1≤NDVI≤1)、植被覆盖(NDVI≥0)、主要气候因子和基本地形因子数据,采用原始尺度、小波多尺度细节系数相关分析、多元逐步回归分析等分析方法,分析植被—气候—地形空间格局特征及其不同尺度下响应规律,得出如下结论：
(1)在现有数据密度的条件下,内蒙古地区降水和相对湿度适宜采用以原始数据四球球面模型和合理二次模型为半变异函数模型模拟数据空间变化趋势的普通克里格法进行空间数据插值,以幂指数取3时的反距离加权法作为气温适宜的空间化插值算法。
(2)近40年来内蒙古毛乌素沙地年平均气温上升0.401℃/10a,年降水和年平均相对湿度的变化趋势不明显。气候年际变化的周期性振荡存在多重时间尺度上的复杂嵌套结构。
(3)植被指数(-1≤NDVI≤1)、植被覆盖、主要气候因子和基本地形因子小波多分辨率分析的特征尺度规律为：植被指数(-1≤NDVI≤1)、植被覆盖、主要气候因子和基本地形因子的空间异质性随尺度上推增大,并倾向于大尺度水平表达。植被指数(-1≤NDVI≤1)和植被覆盖(NDVI≥0)空间格局具复杂的非线性特征,研究区气候因子和海拔高度在研究尺度范围内不存在特征尺度,坡度和坡向的特征尺度具有复杂的空间分布特征。
(4)在原始尺度下,植被覆盖与气候、地形因子的多元逐步回归分析结果表明：在降水大的年份,降水、相对湿度、气温对植被覆盖的影响作用要强于地形因子,而在降水少,气候干旱的年份,坡度、海拔高度等局部地形因素对于植被的覆盖影响要强于气候因子。
(5)植被指数(-1≤NDVI≤1)、植被覆盖与气候、地形因子间具复杂的尺度相关特征,最大相关尺度多出现在中高尺度,表明气候和地形的作用均倾向于表现在宏观水平。气温与植被指数(-1≤NDVI≤1)、植被覆盖的敏感尺度较少,降水与植被指数(-1≤NDVI≤1)、植被覆盖具多重尺度的显著、极显著相关,坡度、坡向与植被指数(-1≤NDVI≤1)存在宏观和微观尺度的制约关系,海拔高度、坡向与植被覆盖具多重尺度的制约关系。多尺度相关分析有利于揭示格局和过程中的尺度响应,了解格局形成过程中,各因子在不同尺度上的作用。
(6)荒漠化过程与尺度、格局密切相关。荒漠化过程存在着时空尺度差异,这种差异表现在荒漠化敏感尺度与驱动因素的变化上。就毛乌素沙地而言,固定、半固定沙地,梁滩、河谷的荒漠化过程及驱动机制在风蚀、水蚀、盐渍化的交替作用下难以用统—尺度来度量,因此应从多重尺度对荒漠化过程进行监测和评价,为科学合理地制定防治策略提供依据。
Scale is the key to correctly understand the interaction between patterns and processes. Dependencies relationship between pattern, process and scale is one of the core issues in landscape ecology. The patterns and processes in response to disturbances in different scales is the main source of the inherent and complex heterogeneity of natural systems in time and space.
Mu Us Sandland located in ecological transition zone from desert or desert steppe to forest steppe. The process of desertification plays a significant role in pattern changes of sand ecosystems in different time and space scale, which is an ideal site to carry out the research of desertification processes and its driving mechanism with different spatial and temporal scales. The landscape, vegetation patterns of spatial heterogeneity and its response to climate and the topographic factor of Mu Us Sandland under different spatial and temporal scales would be systematicly studied, which would help to understand and explore the progress of desertification process and driving mechanism, to scientificly monitor and evaluate the dynamic of desertification and to provide the basis for the formulation strategy of desertification prevention.
Taken Wushen County in the hinterland of Mu Us Sandland as objects, screened out the suitable spatial interpolation method of climatic factors of local area and analyzed it's periodic oscillation characteristics of interannual variability, based on the theory of ecological and applied mathematics and on the3S technology, set five re-sampling transects from north to south and from east to west (totally17328pixel), data about vegetation index (-1≤NDVI≤1) with vegetation coverage (NDVI>0) and the principal climate factor with basic topographic factor in1990,2005and2009in Mu Us Sandland was get. Using analysis methods of the detail coefficients of wavelet multi-scale correlation and stepwise multiple regression at original scale, spatial patterns of vegetation-climate-topography and response law at different scales were analyzed. The following conclusions were getting:
(1) Under the conditions of the existing data density, data about precipitation and relative humidity of Inner Mongolia was appropriate to adopt the Ordinary Kriging with tetraspherical and rational quadratic as semivariogram model of the raw data for optimal spatial data interpolation method, Inverse Distance Weighting with p=3is optimal spatial interpolation method about average annual atmospheric temperature.
(2) The annual average temperature of Mu Us Sandland in Inner Mongolia in the past41years increased by0.401℃/10a, the trends of annual precipitation and annual mean relative humidity are not obvious. Complex nested structure was existed in periodic oscillation of climate change at multiple time scales.
(3) The characteristic scales of regularity in vegetation index (-1≤NDVI<1) with vegetation cover and the principal climate factors with basic topographic factors getting by the wavelet multi-resolution analysis was shown as follow: vegetation index (-1≤NDVI≤1), vegetation cover, the spatial heterogeneity of the major climatic factors and basic topographic factors increased with scale-up and tend to express at large-scale. The spatial patterns of the vegetation index (-1≤NDVI≤1) and vegetation cover (NDVI≥0) were of a complex non-linear characteristics. No characteristic scale was found with climatic factors and elevation of the study area in the research scales. The characteristic scale of the slope and aspect were complex in spatial distribution.
(4) In the original scale, the results of multiple stepwise regression analysis of vegetation cover and climate with topographic factors showed that: in the year with high yield of precipitation, the effects of precipitation, relative humidity, temperature on the vegetation cover were stronger than the effect of the topographic factor. While in the year with low yield of rainfall, the effects of local topographic factors of slope and elevation on the vegetation cover were stronger than the effect of climatic factors.
(5) There are complex characteristics in scale between vegetation index (-1≤NDVI≤1) with the vegetation cover and climate with topographic factors. The maximum correlation scale was often observed in middle and large scale. This indicates that the role of meteorological and topographic tend to show at the macroscopical level. The sensitive scale of temperature and vegetation index (-1≤NDVI≤1) with vegetation cover was small. Precipitation and vegetation index (-1≤NDVI≤1) with vegetation cover were significantly or extremely related with each other at multi-scale. Vegetation index (-1≤NDVI≤1) was related with slope and aspect at macro-and micro-scale. There are multiple relationships in scales between vegetation cover and elevation with aspect, which is helpful to reveal the patterns and processes in response to scales, to understand the role of various factors at different scales during the process of pattern formation.
(6) The process of desertification was closely related with scale and pattern. There were differences in the process of desertification in spatial and temporal scales. This difference was indicated in the changes of desertification in sensitive scale and in the driving factors. To Mu Us Sandland, it is difficult to measure the desertification process and driving mechanism under a unified scale in fixed or semi-fixed sandland and bottomla- nd with the valley since which is impacted by wind or water erosion and salinization. So the desertification monitoring and evaluation should be done in multiple scales, which would provide a basis for drafting the control strategies scientifically and rationally.
引文
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