基于信息技术的枫桥香榧生境特征分析与适宜性评价
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摘要
本文以我国特有的珍稀果树枫桥香榧为例,在充分掌握枫桥香榧野外分布及其生物生态学特性的基础上,依托研究区地学数据库,运用信息技术的强大功能,通过多样区的综合分析,提取出具有普遍性和代表性的枫桥香榧适生环境的生境特征及其关键性的限制因子,综合分析适生环境的形成机理,借助Logistic方法建立评价和决策模型,根据所建模型反演和预测枫桥香榧最佳适生区域。研究结果将有助于阐明枫桥香榧生境特征及其选择机制,为枫桥香榧种植规划决策提供科学依据。主要研究内容和结果概述如下：
(1)基于面向对象方法的IKONOS影像枫桥香榧分布信息提取
利用高分辨率IKONOS影像为遥感数据源,采用面向对象的信息提取方法,利用光谱、形状、纹理等构建特征空间,进行研究区枫桥香榧空间分布信息提取,并与常规监督分类结果进行比较。结果显示,应用面向对象方法进行信息提取的总体精度达到81.67%,其中枫桥香榧分类精度达到.74.32%,Kappa系数达到0.75,分别比监督分类精确度提高6%、15.65%和10.39%。研究表明,借助高分辨率的遥感影像和面向对象的分类方法进行枫桥香榧空间分布信息提取的精度能够满足研究区对于枫桥香榧资源调查和生境结构分析的要求。
(2)枫桥香榧分布区地质、土壤与小气候要素特征分析
在Arcgis9.0的支持下,通过对研究区枫桥香榧分布图与各种资源环境图件的空间叠加与计算,对研究区枫桥香榧分布与地质、土壤和小气候要素进行定量分析和统计,揭示枫桥香榧生境分布的环境特征。统计分析表明,枫桥香榧分布区母岩多数为流纹质晶屑、玻屑熔结凝灰岩,占总面积的88.9%。研究区内枫桥香榧70%以上分布在黄泥土和山地黄泥土,是研究区最适宜枫桥香榧生长的土壤类型。75.2%的分布区土壤有机质含量大于2%,61.6%的分布区土层厚度大于70cm,表明土壤肥力是影响枫桥香榧分布的重要因子之一。和对照区相比,枫桥香榧核心区具有明显的水分资源优势,表现为常年空气湿度大,夏季温凉多雨,2-3月份降水偏多,4-6月份降水偏少的降水分配模式。尤其是夏季高温干旱季节的降水量比对照区高出55.6mm,同期>35℃的高温天数比对照区少了32天,这种类型的降水和温度特征与枫桥香榧生长发育关键时期的气候需求相互匹配。
(3)基于数字地形分析的枫桥香榧生境结构空间特征研究
在研究区1：1万DEM的支持下,利用空间地形分析技术进行枫桥香榧空间分布与各地形因子的叠置分析。结果表明,与集水线距离的远近是影响枫桥香榧分布的重要因子之一,47.76%的枫桥香榧集中分布在距集水线50m以内,累计96.16%的枫桥香榧分布在距集水线150m的空间范围内。枫桥香榧分布对海拔、坡度、坡向和坡位等地形因子选择性较高。76.15%的枫桥香榧分布在400-600m高度带,97.52%的枫桥香榧分布坡度在30°以下,74.43%属于阳坡和半阳坡,95.55%的枫桥香榧分布在中坡和下坡位。综合分析可知,研究区400-600m高度带上距离集水线150m空间范围内坡度在30。以下的向阳坡地是枫桥香榧最适宜的空间分布区域。枫桥香榧幼苗期对环境因子特别是水分的高度选择性是枫桥香榧分布的海拔等地形因子分异的主要原因。
(4)枫桥香榧适生环境因子分析与生态适宜性评价
采用SPSS统计软件对与集水线距离、海拔、坡度、土壤湿润度、太阳直接辐射量、坡向、土壤质地和土壤有机质这8个指标进行主成分分析。结果表明,枫桥香榧生境选择的主要影响因素依次为水分、热量与土壤养分因子。枫桥香榧根系生理特性及其在开花结实过程对环境因子的独特需求表明,水分因子可能是影响枫桥香榧生境形成的最重要的生态因子之一。应用Logistic回归模型对研究区枫桥香榧空间分布与环境因子的关系进行建模和评价。经统计检验,这8个参数对模型均有显著性作用。其中,前3个因子(与集水线距离、年太阳辐射量和土壤有机质含量)对模型的影响是主要的。适宜性评价结果表明,研究区优质枫桥香榧生长的生态适宜程度较高,中、高度适宜面积占总面积的61.7%：枫桥香榧发展的后备土地资源潜力较大。
(5)枫桥香榧的产量和品质与生境因子的相关分析
回归分析表明,枫桥香榧产量与年太阳辐射量、海拔、坡向、土壤有机质和钾含量关系密切。土壤养分因子,特别是有机质含量和钾含量高低对于枫桥香榧产量影响较大。不同生境条件枫桥香榧种子营养成分分析表明,原产地枫桥香榧种仁不饱和脂肪酸含量、氨基酸含量和蛋白质含量、钾含量和硒含量均高于引种地枫桥香榧种子相应营养元素的含量,而原产地枫桥香榧种子的钙、铜、锌、铁、锰、镁等矿质元素含量则低于对照。和引种地相比,原产地的枫桥香榧种子营养成分丰富,营养元素含量高,枫桥香榧的综合品质显著高于引种地。
Taking the endemic Chinese torreya as an example the paper carried out researches on the relationship between habitat selection and environmental factors based on information technology. Firstly, spatial database was established based on remote sensing image, DEM, soil, geology and meteorological data. Secondly, the key factors affecting its spatial distribution and site selection was analyzed by spatial analysis methods. Finally, the Logistic regression model was introduced into the suitability evaluation and the most suitable distribution zone was successfully predicted using the model. The results would be beneficial for understanding the ecological requirements and would provide scientific basis for preferable site selection and sustainable use of this rare species. The main contents are summarized as follow:
(1)Extraction of distribution information of Chinese torreya based on object-oriented method from IKONOS imagery
Based on the IKONOS satellite images, the object-oriented technology was used to extract the Chinese torreya information by building feature space from spectrum, shape and texture characteristics. The accuracy assessment demonstrated that the overall accuracy reached 81.67%, the accuracy of Torreya classification reached 74.32% and KAPPA coefficient was 0.75, which was 6%, 15.65% and 10.39% higher than that using supervised classification method respectively. The results showed that the accuracy of classification results using IKONOS image and the object-oriented method could meet the requirements of inventory and habitat analysis of Chinese torreya in the study area.
(2) Analysis of geology, soil characteristics and microclimate factors
Quantitative analysis and statistics of environmental features of habitats including geology, soil and microclimate elements were carried out in the study area based on GIS.88.9% of Torreya trees were distributed in the acid tuff. This rare species demanded on soil fertility, and 70% were found to present on mountain yellow earth and yellow earth; 75.2% of Torreya distributed on areas with soil organic matter content greater than 2%; 61.6% were located at regions with soil thicontrol plotness greater than 70 cm. The results showed that the soil nutrient is one of the important factors affecting the distribution of Chinese torreya. Compared with controlled areas, the microclimate characteristics in original habitat are featured by higher relative humidity, cool and rainy in summer and precipitation periodic variation in its growth season. During July and September, The number of＞35℃days was 32 days less than control areas whereas the rainy days and the rainfall was 5 days and 55.6 mm more than control areas respectively. These results demonstrated that the meteorological features in the original habitat were highly agreed with the climatic requirements of Chinese torreya.
(3) Habitat structure characteristics of Chinese torreya based on digital terrain analysis
The spatial distribution map of rare Chinese torreya from IKONOS image is over-lapped with 8 topographical factors derived from Digital Elevation Models using digital terrain analysis method. The results showed that 47.76% of the rare plant records occur in areas within 50 m to valley line, and 96.16% were restricted in areas less than 150 meters away from the valley line. The spatial pattern of Chinese torreya exhibited high selectivity of topographical factors such as elevation, slope, aspect and slope position.76.15% occurred at the elevation belts between 400-600m,97.52% grew on the slopes less than 30°74.43% belonged to sunny or half-sunny slope, and 95.55% occurred on the midslope and downslope. Those areas less than 150 m to valley line with slopes less than 30°, altitudes between 400-600 m, and concave surfaces could be identified as the most suitable region for this rare plant. The main cause of topographic differentiation may be highly correlated with the high selectivity of environmental factors during its seedling growth stage.
(4) Habitat factor analysis and ecological suitability evaluation
The special habitat factors for Chinese torreya were analyzed with Principal Component Analysis (PCA) and a series of environmental factors including distance to valley line, elevation, slope, topographical wetness index, solar radiation index, soil texture and soil organic matter. The results of PCA analysis indicated that the main environmental factors of affecting habitat of Chinese torreya were in order of importance:moisture, heat and soil nutrient. And moisture might be one of the most important ecological factors for Chinese torreya due to its unique biological and ecological characteristics. A Logistic regression was used to calculate a model for the relationship using topographical attributes. It is concluded that 8 explanatory variables are noted to be significant and 3 topographical factors (distance to valley line, solar radiation index and soil organic matter) may be the important factors influencing its habitat selection. The results from Logistic model evaluation showed that the acreage of the high and moderate suitable zone for Chinese torreya planting accounted for 61.7% of the total area. This result indicated that the study area showed great potential for cultivation of Chinese torreya.
(5) Relationship of yield and quality of Chinese torreya with environmental factors
Regression analysis showed that the yield of Chinese torreya highly related with solar radiation, altitude, slope, soil organic matter and potassium content. Soil nutrient factors, especially organic matter content and potassium content influenced its yield significantly. Nutrient analysis of Chinese torreya from different habitats showed that unsaturated fatty acids, amino acids and protein content, potassium content and selenium of dry seeds in origin habitat were higher than that in introduction area. Whereas the contents of calcium, copper, zinc, iron, manganese, magnesium and other mineral elements were lower than that in introduction area. Those torreya trees in origin habitat were rich in nutrients compared to that in introduction area, and their comprehensive quality was significantly higher than that from introduction area.
(1)基于面向对象方法的IKONOS影像枫桥香榧分布信息提取
利用高分辨率IKONOS影像为遥感数据源,采用面向对象的信息提取方法,利用光谱、形状、纹理等构建特征空间,进行研究区枫桥香榧空间分布信息提取,并与常规监督分类结果进行比较。结果显示,应用面向对象方法进行信息提取的总体精度达到81.67%,其中枫桥香榧分类精度达到.74.32%,Kappa系数达到0.75,分别比监督分类精确度提高6%、15.65%和10.39%。研究表明,借助高分辨率的遥感影像和面向对象的分类方法进行枫桥香榧空间分布信息提取的精度能够满足研究区对于枫桥香榧资源调查和生境结构分析的要求。
(2)枫桥香榧分布区地质、土壤与小气候要素特征分析
在Arcgis9.0的支持下,通过对研究区枫桥香榧分布图与各种资源环境图件的空间叠加与计算,对研究区枫桥香榧分布与地质、土壤和小气候要素进行定量分析和统计,揭示枫桥香榧生境分布的环境特征。统计分析表明,枫桥香榧分布区母岩多数为流纹质晶屑、玻屑熔结凝灰岩,占总面积的88.9%。研究区内枫桥香榧70%以上分布在黄泥土和山地黄泥土,是研究区最适宜枫桥香榧生长的土壤类型。75.2%的分布区土壤有机质含量大于2%,61.6%的分布区土层厚度大于70cm,表明土壤肥力是影响枫桥香榧分布的重要因子之一。和对照区相比,枫桥香榧核心区具有明显的水分资源优势,表现为常年空气湿度大,夏季温凉多雨,2-3月份降水偏多,4-6月份降水偏少的降水分配模式。尤其是夏季高温干旱季节的降水量比对照区高出55.6mm,同期>35℃的高温天数比对照区少了32天,这种类型的降水和温度特征与枫桥香榧生长发育关键时期的气候需求相互匹配。
(3)基于数字地形分析的枫桥香榧生境结构空间特征研究
在研究区1：1万DEM的支持下,利用空间地形分析技术进行枫桥香榧空间分布与各地形因子的叠置分析。结果表明,与集水线距离的远近是影响枫桥香榧分布的重要因子之一,47.76%的枫桥香榧集中分布在距集水线50m以内,累计96.16%的枫桥香榧分布在距集水线150m的空间范围内。枫桥香榧分布对海拔、坡度、坡向和坡位等地形因子选择性较高。76.15%的枫桥香榧分布在400-600m高度带,97.52%的枫桥香榧分布坡度在30°以下,74.43%属于阳坡和半阳坡,95.55%的枫桥香榧分布在中坡和下坡位。综合分析可知,研究区400-600m高度带上距离集水线150m空间范围内坡度在30。以下的向阳坡地是枫桥香榧最适宜的空间分布区域。枫桥香榧幼苗期对环境因子特别是水分的高度选择性是枫桥香榧分布的海拔等地形因子分异的主要原因。
(4)枫桥香榧适生环境因子分析与生态适宜性评价
采用SPSS统计软件对与集水线距离、海拔、坡度、土壤湿润度、太阳直接辐射量、坡向、土壤质地和土壤有机质这8个指标进行主成分分析。结果表明,枫桥香榧生境选择的主要影响因素依次为水分、热量与土壤养分因子。枫桥香榧根系生理特性及其在开花结实过程对环境因子的独特需求表明,水分因子可能是影响枫桥香榧生境形成的最重要的生态因子之一。应用Logistic回归模型对研究区枫桥香榧空间分布与环境因子的关系进行建模和评价。经统计检验,这8个参数对模型均有显著性作用。其中,前3个因子(与集水线距离、年太阳辐射量和土壤有机质含量)对模型的影响是主要的。适宜性评价结果表明,研究区优质枫桥香榧生长的生态适宜程度较高,中、高度适宜面积占总面积的61.7%：枫桥香榧发展的后备土地资源潜力较大。
(5)枫桥香榧的产量和品质与生境因子的相关分析
回归分析表明,枫桥香榧产量与年太阳辐射量、海拔、坡向、土壤有机质和钾含量关系密切。土壤养分因子,特别是有机质含量和钾含量高低对于枫桥香榧产量影响较大。不同生境条件枫桥香榧种子营养成分分析表明,原产地枫桥香榧种仁不饱和脂肪酸含量、氨基酸含量和蛋白质含量、钾含量和硒含量均高于引种地枫桥香榧种子相应营养元素的含量,而原产地枫桥香榧种子的钙、铜、锌、铁、锰、镁等矿质元素含量则低于对照。和引种地相比,原产地的枫桥香榧种子营养成分丰富,营养元素含量高,枫桥香榧的综合品质显著高于引种地。
Taking the endemic Chinese torreya as an example the paper carried out researches on the relationship between habitat selection and environmental factors based on information technology. Firstly, spatial database was established based on remote sensing image, DEM, soil, geology and meteorological data. Secondly, the key factors affecting its spatial distribution and site selection was analyzed by spatial analysis methods. Finally, the Logistic regression model was introduced into the suitability evaluation and the most suitable distribution zone was successfully predicted using the model. The results would be beneficial for understanding the ecological requirements and would provide scientific basis for preferable site selection and sustainable use of this rare species. The main contents are summarized as follow:
(1)Extraction of distribution information of Chinese torreya based on object-oriented method from IKONOS imagery
Based on the IKONOS satellite images, the object-oriented technology was used to extract the Chinese torreya information by building feature space from spectrum, shape and texture characteristics. The accuracy assessment demonstrated that the overall accuracy reached 81.67%, the accuracy of Torreya classification reached 74.32% and KAPPA coefficient was 0.75, which was 6%, 15.65% and 10.39% higher than that using supervised classification method respectively. The results showed that the accuracy of classification results using IKONOS image and the object-oriented method could meet the requirements of inventory and habitat analysis of Chinese torreya in the study area.
(2) Analysis of geology, soil characteristics and microclimate factors
Quantitative analysis and statistics of environmental features of habitats including geology, soil and microclimate elements were carried out in the study area based on GIS.88.9% of Torreya trees were distributed in the acid tuff. This rare species demanded on soil fertility, and 70% were found to present on mountain yellow earth and yellow earth; 75.2% of Torreya distributed on areas with soil organic matter content greater than 2%; 61.6% were located at regions with soil thicontrol plotness greater than 70 cm. The results showed that the soil nutrient is one of the important factors affecting the distribution of Chinese torreya. Compared with controlled areas, the microclimate characteristics in original habitat are featured by higher relative humidity, cool and rainy in summer and precipitation periodic variation in its growth season. During July and September, The number of＞35℃days was 32 days less than control areas whereas the rainy days and the rainfall was 5 days and 55.6 mm more than control areas respectively. These results demonstrated that the meteorological features in the original habitat were highly agreed with the climatic requirements of Chinese torreya.
(3) Habitat structure characteristics of Chinese torreya based on digital terrain analysis
The spatial distribution map of rare Chinese torreya from IKONOS image is over-lapped with 8 topographical factors derived from Digital Elevation Models using digital terrain analysis method. The results showed that 47.76% of the rare plant records occur in areas within 50 m to valley line, and 96.16% were restricted in areas less than 150 meters away from the valley line. The spatial pattern of Chinese torreya exhibited high selectivity of topographical factors such as elevation, slope, aspect and slope position.76.15% occurred at the elevation belts between 400-600m,97.52% grew on the slopes less than 30°74.43% belonged to sunny or half-sunny slope, and 95.55% occurred on the midslope and downslope. Those areas less than 150 m to valley line with slopes less than 30°, altitudes between 400-600 m, and concave surfaces could be identified as the most suitable region for this rare plant. The main cause of topographic differentiation may be highly correlated with the high selectivity of environmental factors during its seedling growth stage.
(4) Habitat factor analysis and ecological suitability evaluation
The special habitat factors for Chinese torreya were analyzed with Principal Component Analysis (PCA) and a series of environmental factors including distance to valley line, elevation, slope, topographical wetness index, solar radiation index, soil texture and soil organic matter. The results of PCA analysis indicated that the main environmental factors of affecting habitat of Chinese torreya were in order of importance:moisture, heat and soil nutrient. And moisture might be one of the most important ecological factors for Chinese torreya due to its unique biological and ecological characteristics. A Logistic regression was used to calculate a model for the relationship using topographical attributes. It is concluded that 8 explanatory variables are noted to be significant and 3 topographical factors (distance to valley line, solar radiation index and soil organic matter) may be the important factors influencing its habitat selection. The results from Logistic model evaluation showed that the acreage of the high and moderate suitable zone for Chinese torreya planting accounted for 61.7% of the total area. This result indicated that the study area showed great potential for cultivation of Chinese torreya.
(5) Relationship of yield and quality of Chinese torreya with environmental factors
Regression analysis showed that the yield of Chinese torreya highly related with solar radiation, altitude, slope, soil organic matter and potassium content. Soil nutrient factors, especially organic matter content and potassium content influenced its yield significantly. Nutrient analysis of Chinese torreya from different habitats showed that unsaturated fatty acids, amino acids and protein content, potassium content and selenium of dry seeds in origin habitat were higher than that in introduction area. Whereas the contents of calcium, copper, zinc, iron, manganese, magnesium and other mineral elements were lower than that in introduction area. Those torreya trees in origin habitat were rich in nutrients compared to that in introduction area, and their comprehensive quality was significantly higher than that from introduction area.
引文
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