不同尺度下橡胶园土壤养分时空变异特性的研究
|
摘要
管理好土壤养分,合理进行施肥,是关系到我国农业可持续发展的重大技术问题。土壤养分不仅具有明显的空间变异,而且在时间是上也表现出一定的变化。海南省作为中国重要的植胶区之一,其土壤养分的状况不仅与海南省农业非点源污染等环境有关,更与橡胶胶乳产量和质量相关。因此,研究海南省胶园土壤养分的时空变异特性,不仅是推进精准农业实施的前提和基础,而且也可以控制农业面源污染,更能为实现橡胶园科学、平衡施肥提供理论依据。但长期以来,利用GIS和地统计学对橡胶园的研究几乎是空白.因此,本研究应用地统计学与GIS技术相结合的方法,选择1：250000海南省胶园、1：50000蓝洋镇胶园两个不同尺度研究区域,分析了橡胶园土壤养分的时空变异特性,并进行不同尺度管理分析模型探讨。主要研究结果如下：
1.海南省橡胶园土壤养分时空变异
2008年海南省胶园碱解氮、全氮、全磷、速效钾、pH,有机质的含量跟1984年的相比均有不同程度的下降,速效钾含量下降幅度最大；而速效磷和全钾含量则比1984年有所增加。
海南省橡胶园经过长期不同的人为耕作管理,其土壤碱解氮、全氮、全磷、速效钾、全钾、有机质含量已逐渐趋向均一,以上各养分变异系数均呈下降趋势。PH的变异系数也呈下降趋势,表明种植橡胶后海南省胶园土壤有朝均匀、全面酸化方向发展的趋势。而速效磷的变异系数则由1984年的117.81%上升到200.2%,属于强变异。
2008全氮的块基比值为83.12%,空间相关性很弱,说明人为因素对土壤全氮的空间变异影响很大,碱解氮、速效磷、全磷、速效钾、全钾、有机质和PH均具有中等程度的空间相关性,说明经过长时间的耕作、施肥、田间管理水平等人为因素在一定程度上削弱了它们受结构性因素的影响,从而削弱它们的空间相关性。海南省土壤养分时空分布图和时空时空变异图结果进一步解释了土壤全氮、速效磷、全磷、速效钾、全钾、有机质和pH在这20几年的变化情况。根据橡胶树养分丰缺指标,对2008年海南省橡胶园养分分布格局进行分区,碱解氮分为两个管理分区,全氮、全钾、速效钾、全磷、速效磷和有机质均分为三个管理分区,在以后的胶园土壤管理中,可以根据该管理分区进行因地制宜的科学管理。
2.蓝洋镇橡胶园土壤养分空间变异
从对土壤养分数据的描述性统计分析结果来看,蓝洋镇胶园土壤碱解氮、全氮、PH和有机质的数据符合正态分布,而速效磷、全磷、速效钾和全钾的数据符合对数正态分布；从变异系数来看,速效磷的变异系数最大,为231.9%,PH的变异系数最小,为5.97%,其他几种养分的变异系数在25.29%～74.16%之间,大小顺序为全钾>速效钾>全磷>碱解氮>全氮>有机质。
土壤速效钾和全钾的C0/(C0+C)值均小于25%,表现出强烈的空间相关性,结构性因素是其空间变异的主要影响因子,这与研究区内长期以来忽视钾肥的施用的现状基本吻合,由此导致钾素的变异与土壤母质和土壤类型等结构性因素密切相关。土壤碱解氮、全氮、速效磷、全磷、pH、有机质均具有中等空间相关性,这六种养分的空间变异是结构性因素和随机性因素的共同作用的结果。
土壤各养分的空间相关距离在2.43km-12.294km之间,均大于取样间距。其中相关距离较小的是土壤碱解氮,为2.43km；相关距离较大的是PH,为12.294km。
养分空间变异图可以看出,蓝洋镇胶园各养分的空间分布都表现一定的规律。空间变异图能直观地体现各养分的空间分布情况,为以后的胶园管理提供依据。
根据养分丰缺指标绘制各养分丰缺图,对蓝洋镇胶园养分分布格局进行分区,全氮、速效钾、有机质分为两个管理分区,全钾、全磷、速效磷均分为三个管理分区,在以后的胶园土壤管理中,可以根据该管理分区进行因地制宜的科学管理。
3、不同尺度下橡胶园土壤养分空间变异套合分析
对两个不同尺度下的胶园土壤养分变异进行套合分析表明,土壤碱解氮、全氮、全磷、速效钾、pH、有机质的变异系数随研究尺度的加大而增加；速效磷和全钾的变异系数则是蓝洋镇>海南省,这说明在小尺度范围内,土壤速效磷和全钾的空间随机性大,更易受人为因素的影响。
碱解氮、全氮、速效磷、全磷、pH、有机质在不同尺度上都表现为中等空间相关性,速效钾和全钾在大尺度下表现为中等空间变异性,但在小尺度下却表现为强烈的空间相关性。
全氮的空间分布在两个尺度上都呈现出明显的地理规律,且在两个尺度下能形成一个较好的套合结构。土壤碱解氮、速效磷、全磷、速效钾、全钾、有机质虽然在各个尺度上都有较明显的空间分布格局,但两个尺度的分布规律差别很大,不能形成好的套合结构。
Appropriate management of soil nutrients and reasonable fertilization are the key technological problems related to Chinese agriculture's sustainable development. What features soil nutrients is not only the special viability, but also the temporal viability to some extent. As one of the importance rubber plantation areas of China, the soil nutrients status is not only related to the environments such as non-point source pollution, etc., but also to the yield and quality of rubber latex. Therefore, studying on the soil nutrients'time-space variation characters of Hainan rubber plantation is the precondition and basis for promoting the precision agriculture; it could also control the agricultural non-point source pollution and provide the theoretical basis for the rubber plantations'scientific and balanced fertilization. However, it has been almost a blank for a long time to study the rubber plantations by utilizing GIS and geostatistics. Therefore, the study applies the method coming GIS and geostatistics, adopts two study areas under different scales:Hainan rubber plantations in 1:250000 and Lanyang rubber plantations in 1:50000, analyzes the soil nutrients'time-space variation characters of rubber plantations, and discusses the management analysis models in different scales. The main study results obtained are summarized as follows:
1. Soil Nutrients'Time-space Variation of Hainan Rubber Plantations
Compared with those of 1984, the contents of hydrolyzable nitrogen, total nitrogen, total pHospHor, available potassium, PH, and organic in Hainan rubber plantations decreased to different degrees in 2008, the descent range of available potassium was the largest; however, the contents of available pHospHor and total potassium increased compared with those of 1984.
After years of different artificial cultivation management, the contents of hydrolyzable nitrogen, total nitrogen, total pHospHor, available potassium, and organic in Hainan rubber plantations'soil gradually presented the uniform trend, and the variation coefficients of these contents above presented the downtrend. The PH's variation coefficient also presented the downtrend, which meant Hainan rubber plantations'soil had the developing trend of uniformity and overall acidification. However, the available pHospHor's variation coefficient increased from 117.81% in 1984 to 200.2%, which belonged to obvious variation.
In 2008 the total nitrogen's ratio was 83.12%, spatial correlation was rather weak, which meant artificial factors obviously influenced the total nitrogen's spatial variation; and the hydrolyzable nitrogen, available pHospHor, total pHospHor, available potassium, total potassium, organic and pH all presented medium spatial correlation, which meant the artificial factors such as years of cultivation, fertilization, field management, etc. had reduced the structural factors' influenced on these contents, and consequently weakened their spatial correlation. Hainan soil's time-space distribution grapH and space-time difference grapH further explained the changing status of total nitrogen, available pHospHor, total pHospHor, available potassium, total potassium, organic and PH during more than 20 years. According to the plentiful-lack indexes of rubber trees'nutrients, we divided the nutrient distribution pattern of 2008 Hainan rubber plantations, hydrolyzable nitrogen was divided into two management sub-areas, total nitrogen, total pHospHor, available potassium, available potassium, and organic had been divided into three management sub-areas; then in the future rubber plantation management, we could implement scientific management according to these sub-areas adjusting to the local conditions.
2. Nutrients'Spatial Variation of Lanyang Town Rubber Plantation
From the descriptive statistical results of soil nutrients data it could be seen that the data of Lanyang Town rubber plantations'hydrolyzable nitrogen, total nitrogen and organic conformed to normal distribution, and the data of available pHospHor, total pHospHor, available potassium, and total potassium conformed to lognormal distribution; from the aspect of variation coefficients, the available pHospHor's variation coefficient reached the maximum:231.9%, while that of PH was the minimum,5.97%; the variation coefficients lay between 25.29% and 74.16%, with the order of total potassium>available potassium>total pHospHor> hydrolyzable nitrogen>total nitrogen>organic.
The Co/(Co+C) values of available and total pHospHor were less than 25%, and presented strong spatial correlation; structural variation was the main influential factor of spatial correlation, which basically conformed to the study areas'potassium fertilization current status that had been ignored for a long time; and the corresponding potassium variation was closely related to the soil parent materials and patterns. The hydrolyzable nitrogen,、total nitrogen, available pHospHor, total pHospHor, PH, and organic had all presented medium correlation, the spatial variation of these six nutrients was the results of mutual effect between the structural factors and random factors.
The correlation distance of every nutrients lay between 2.43km and 12.294km, which were larger than their intervals. The relatively shorter interval belonged to hydrolyzable nitrogen:2.43km, and the larger one belonged to PH,12.294km.
From the spatial variation grapH it could been seen that the nutrients distribution of Lanyang Town had all presented certain rules. The spatial variation grapH could intuitionally presented the spatial distribution status, which would provide the theoretical evidence for rubber plantations'management in the future.
According to the nutrients plentiful-lack grapH drawn through plentiful-lack indexes, we divided the nutrients distribution patterns of Lanyang Town rubber plantations into sub-areas, total nitrogen, available potassium and organic were divided into two management sub-areas; total potassium, total pHospHor, and available pHospHor were divided into three management sub-areas; then in the future rubber plantation management, we could implement scientific management according to these sub-areas adjusting to the local conditions.
3. Nested Analysis on Rubber Plantations'Nutrients Spatial Variation in Different Scales
Nested analysis on rubber plantations'nutrients spatial variation in two scales was carried out, the results showed that the variation coefficients of hydrolyzable nitrogen, total nitrogen, total pHospHor, available potassium, pH, organic increased as the studying scale increased; the variation coefficients of available pHospHor and total potassium showed that those of Lanyang Town>Hainan Province, which meant that in the small scale, the randomness of available pHospHor and total potassium were large, which was easily influenced by artificial factors.
Hydrolyzable nitrogen, total nitrogen, available pHospHor, total pHospHor, PH and organic showed medium correlation in different scales, available and total potassium showed medium spatial correlation in large scales, but they showed strong correlations in small scales.
The total nitrogen's spatial distribution presented obvious geograpHic rules in two scales, and could form a relatively good nested structure. Although hydrolyzable nitrogen, available pHospHor, total pHospHor, available potassium, total potassium and organic presented obvious spatial distribution patterns in two scales, the rules of the two scales are obviously different, which meant good nested structure could not be formed.
1.海南省橡胶园土壤养分时空变异
2008年海南省胶园碱解氮、全氮、全磷、速效钾、pH,有机质的含量跟1984年的相比均有不同程度的下降,速效钾含量下降幅度最大；而速效磷和全钾含量则比1984年有所增加。
海南省橡胶园经过长期不同的人为耕作管理,其土壤碱解氮、全氮、全磷、速效钾、全钾、有机质含量已逐渐趋向均一,以上各养分变异系数均呈下降趋势。PH的变异系数也呈下降趋势,表明种植橡胶后海南省胶园土壤有朝均匀、全面酸化方向发展的趋势。而速效磷的变异系数则由1984年的117.81%上升到200.2%,属于强变异。
2008全氮的块基比值为83.12%,空间相关性很弱,说明人为因素对土壤全氮的空间变异影响很大,碱解氮、速效磷、全磷、速效钾、全钾、有机质和PH均具有中等程度的空间相关性,说明经过长时间的耕作、施肥、田间管理水平等人为因素在一定程度上削弱了它们受结构性因素的影响,从而削弱它们的空间相关性。海南省土壤养分时空分布图和时空时空变异图结果进一步解释了土壤全氮、速效磷、全磷、速效钾、全钾、有机质和pH在这20几年的变化情况。根据橡胶树养分丰缺指标,对2008年海南省橡胶园养分分布格局进行分区,碱解氮分为两个管理分区,全氮、全钾、速效钾、全磷、速效磷和有机质均分为三个管理分区,在以后的胶园土壤管理中,可以根据该管理分区进行因地制宜的科学管理。
2.蓝洋镇橡胶园土壤养分空间变异
从对土壤养分数据的描述性统计分析结果来看,蓝洋镇胶园土壤碱解氮、全氮、PH和有机质的数据符合正态分布,而速效磷、全磷、速效钾和全钾的数据符合对数正态分布；从变异系数来看,速效磷的变异系数最大,为231.9%,PH的变异系数最小,为5.97%,其他几种养分的变异系数在25.29%～74.16%之间,大小顺序为全钾>速效钾>全磷>碱解氮>全氮>有机质。
土壤速效钾和全钾的C0/(C0+C)值均小于25%,表现出强烈的空间相关性,结构性因素是其空间变异的主要影响因子,这与研究区内长期以来忽视钾肥的施用的现状基本吻合,由此导致钾素的变异与土壤母质和土壤类型等结构性因素密切相关。土壤碱解氮、全氮、速效磷、全磷、pH、有机质均具有中等空间相关性,这六种养分的空间变异是结构性因素和随机性因素的共同作用的结果。
土壤各养分的空间相关距离在2.43km-12.294km之间,均大于取样间距。其中相关距离较小的是土壤碱解氮,为2.43km；相关距离较大的是PH,为12.294km。
养分空间变异图可以看出,蓝洋镇胶园各养分的空间分布都表现一定的规律。空间变异图能直观地体现各养分的空间分布情况,为以后的胶园管理提供依据。
根据养分丰缺指标绘制各养分丰缺图,对蓝洋镇胶园养分分布格局进行分区,全氮、速效钾、有机质分为两个管理分区,全钾、全磷、速效磷均分为三个管理分区,在以后的胶园土壤管理中,可以根据该管理分区进行因地制宜的科学管理。
3、不同尺度下橡胶园土壤养分空间变异套合分析
对两个不同尺度下的胶园土壤养分变异进行套合分析表明,土壤碱解氮、全氮、全磷、速效钾、pH、有机质的变异系数随研究尺度的加大而增加；速效磷和全钾的变异系数则是蓝洋镇>海南省,这说明在小尺度范围内,土壤速效磷和全钾的空间随机性大,更易受人为因素的影响。
碱解氮、全氮、速效磷、全磷、pH、有机质在不同尺度上都表现为中等空间相关性,速效钾和全钾在大尺度下表现为中等空间变异性,但在小尺度下却表现为强烈的空间相关性。
全氮的空间分布在两个尺度上都呈现出明显的地理规律,且在两个尺度下能形成一个较好的套合结构。土壤碱解氮、速效磷、全磷、速效钾、全钾、有机质虽然在各个尺度上都有较明显的空间分布格局,但两个尺度的分布规律差别很大,不能形成好的套合结构。
Appropriate management of soil nutrients and reasonable fertilization are the key technological problems related to Chinese agriculture's sustainable development. What features soil nutrients is not only the special viability, but also the temporal viability to some extent. As one of the importance rubber plantation areas of China, the soil nutrients status is not only related to the environments such as non-point source pollution, etc., but also to the yield and quality of rubber latex. Therefore, studying on the soil nutrients'time-space variation characters of Hainan rubber plantation is the precondition and basis for promoting the precision agriculture; it could also control the agricultural non-point source pollution and provide the theoretical basis for the rubber plantations'scientific and balanced fertilization. However, it has been almost a blank for a long time to study the rubber plantations by utilizing GIS and geostatistics. Therefore, the study applies the method coming GIS and geostatistics, adopts two study areas under different scales:Hainan rubber plantations in 1:250000 and Lanyang rubber plantations in 1:50000, analyzes the soil nutrients'time-space variation characters of rubber plantations, and discusses the management analysis models in different scales. The main study results obtained are summarized as follows:
1. Soil Nutrients'Time-space Variation of Hainan Rubber Plantations
Compared with those of 1984, the contents of hydrolyzable nitrogen, total nitrogen, total pHospHor, available potassium, PH, and organic in Hainan rubber plantations decreased to different degrees in 2008, the descent range of available potassium was the largest; however, the contents of available pHospHor and total potassium increased compared with those of 1984.
After years of different artificial cultivation management, the contents of hydrolyzable nitrogen, total nitrogen, total pHospHor, available potassium, and organic in Hainan rubber plantations'soil gradually presented the uniform trend, and the variation coefficients of these contents above presented the downtrend. The PH's variation coefficient also presented the downtrend, which meant Hainan rubber plantations'soil had the developing trend of uniformity and overall acidification. However, the available pHospHor's variation coefficient increased from 117.81% in 1984 to 200.2%, which belonged to obvious variation.
In 2008 the total nitrogen's ratio was 83.12%, spatial correlation was rather weak, which meant artificial factors obviously influenced the total nitrogen's spatial variation; and the hydrolyzable nitrogen, available pHospHor, total pHospHor, available potassium, total potassium, organic and pH all presented medium spatial correlation, which meant the artificial factors such as years of cultivation, fertilization, field management, etc. had reduced the structural factors' influenced on these contents, and consequently weakened their spatial correlation. Hainan soil's time-space distribution grapH and space-time difference grapH further explained the changing status of total nitrogen, available pHospHor, total pHospHor, available potassium, total potassium, organic and PH during more than 20 years. According to the plentiful-lack indexes of rubber trees'nutrients, we divided the nutrient distribution pattern of 2008 Hainan rubber plantations, hydrolyzable nitrogen was divided into two management sub-areas, total nitrogen, total pHospHor, available potassium, available potassium, and organic had been divided into three management sub-areas; then in the future rubber plantation management, we could implement scientific management according to these sub-areas adjusting to the local conditions.
2. Nutrients'Spatial Variation of Lanyang Town Rubber Plantation
From the descriptive statistical results of soil nutrients data it could be seen that the data of Lanyang Town rubber plantations'hydrolyzable nitrogen, total nitrogen and organic conformed to normal distribution, and the data of available pHospHor, total pHospHor, available potassium, and total potassium conformed to lognormal distribution; from the aspect of variation coefficients, the available pHospHor's variation coefficient reached the maximum:231.9%, while that of PH was the minimum,5.97%; the variation coefficients lay between 25.29% and 74.16%, with the order of total potassium>available potassium>total pHospHor> hydrolyzable nitrogen>total nitrogen>organic.
The Co/(Co+C) values of available and total pHospHor were less than 25%, and presented strong spatial correlation; structural variation was the main influential factor of spatial correlation, which basically conformed to the study areas'potassium fertilization current status that had been ignored for a long time; and the corresponding potassium variation was closely related to the soil parent materials and patterns. The hydrolyzable nitrogen,、total nitrogen, available pHospHor, total pHospHor, PH, and organic had all presented medium correlation, the spatial variation of these six nutrients was the results of mutual effect between the structural factors and random factors.
The correlation distance of every nutrients lay between 2.43km and 12.294km, which were larger than their intervals. The relatively shorter interval belonged to hydrolyzable nitrogen:2.43km, and the larger one belonged to PH,12.294km.
From the spatial variation grapH it could been seen that the nutrients distribution of Lanyang Town had all presented certain rules. The spatial variation grapH could intuitionally presented the spatial distribution status, which would provide the theoretical evidence for rubber plantations'management in the future.
According to the nutrients plentiful-lack grapH drawn through plentiful-lack indexes, we divided the nutrients distribution patterns of Lanyang Town rubber plantations into sub-areas, total nitrogen, available potassium and organic were divided into two management sub-areas; total potassium, total pHospHor, and available pHospHor were divided into three management sub-areas; then in the future rubber plantation management, we could implement scientific management according to these sub-areas adjusting to the local conditions.
3. Nested Analysis on Rubber Plantations'Nutrients Spatial Variation in Different Scales
Nested analysis on rubber plantations'nutrients spatial variation in two scales was carried out, the results showed that the variation coefficients of hydrolyzable nitrogen, total nitrogen, total pHospHor, available potassium, pH, organic increased as the studying scale increased; the variation coefficients of available pHospHor and total potassium showed that those of Lanyang Town>Hainan Province, which meant that in the small scale, the randomness of available pHospHor and total potassium were large, which was easily influenced by artificial factors.
Hydrolyzable nitrogen, total nitrogen, available pHospHor, total pHospHor, PH and organic showed medium correlation in different scales, available and total potassium showed medium spatial correlation in large scales, but they showed strong correlations in small scales.
The total nitrogen's spatial distribution presented obvious geograpHic rules in two scales, and could form a relatively good nested structure. Although hydrolyzable nitrogen, available pHospHor, total pHospHor, available potassium, total potassium and organic presented obvious spatial distribution patterns in two scales, the rules of the two scales are obviously different, which meant good nested structure could not be formed.
引文
[1]鲍全盛,王华东,毛显强,我国水环境非点源污染研究进展.环境科学进展,1995,3(3)：31-36.
[2]陈浮,蹼励杰等.近20年太湖流域典型区土壤养分时空变化及驱动机理[J].土壤学报,2002.39(2)：23-44.
[3]陈志雄,VuaClniM,封丘地区土壤水分平衡研究工.田间土壤湿度的空间变异.土壤学报,1999.16(3)：35-42.
[4]丁瑞兴,黄骁.茶园—土壤系统铝和氟的生物地球化学循环及其对土壤酸化的影响.土壤学报,1991；28(3)：229-236.
[5]郭旭东,傅伯杰,马克明,陈利顶等.基于GIS和地统计学的土壤养分空间变异特征研究—以河北省遵化市为例[J].应用生态学报,2000,11(4)：557-563.
[6]海南省农业厅土肥站.海南土壤[M].海口：海南出版社,1993.
[7]韩江波服务“三农”产业重点选择研究及相关对策——以海南天然橡胶产业为例[J]农村金融研究2008(01)：74-77
[8]何鹏,吴敏,韦家少.海南省胶园土壤肥力质量指标的时空变异特性研究.中国农学通报,2008,24(10)：310-316.
[9]何向东,陆行正,吴小平.海南岛胶园土壤肥力区划及其利用的研究[J].热带农业科学,1991,(01)：40-48.
[10]何向东,吴小平.海南恳区胶园土壤肥力演变探研[J].热带农业科学,1997,(04)：16-22.
[11]何向东,吴小平等.海南垦区胶园肥力演变探研.热带农业科学,2002,22(1)：16-22
[12]侯景儒,尹镇南,等.实用地质统计学.北京：地质出版社,1998.
[13]黄绍文,金继运,杨俐苹等.乡镇级土壤养分空间变异与分区管理技术研究.精准农业与土壤养分管理.北京：大地出版社,2001.248-259.
[14]蒋菊生,王如松著.海南橡胶产业生态[M].北京：中国科学技术出版社，2004：1-34.
[15]雷志栋,杨诗秀,许志荣等,土壤特性空间变异性初步研究。水利学报, 1989,26(4)：309-315.
[16]雷志栋,杨诗秀,许志荣等.土壤特性空间变异特性初步研究.水利学报,1985,(9)：10-21.
[17]李菊梅,李生秀.几种营养元素在土壤中的分布类型[J].干早地区农业研究,1998,16(1)：69-75.
[18]李荣刚,农业污染的由来、危害与内涵.当代生态农业,1999(3-4)：63-64.
[19]林钊沐,黎仕聪,茶正早,等.中国热带土壤植胶后肥力变化与胶树平衡施肥[J].农田养分平衡与管理[C].南京：河海大学出版社,2000：407-414.
[20]刘杏梅,徐建明等.太湖流域土壤养分空间变异特征分析—以浙江省平湖市为例,浙江大学学报,2005.
[21]鲁如昆.土壤农业化学分析方法[M].中国农业科技出版社,2000.
[22]陆正行,吴小平,何向东等,海南岛胶园土壤的钾素状况,热带作物学报,1989,10(1)：17-23.
[23]麦全法.我国主要植胶区胶园生态系统养分变化趋势的研究[D].华南热带农业大学,2006.
[24]漆智平,余让水.海南主要土壤钾素状况与热带农业[J].热带农业科学,1997,(04)：48-54.
[25]全国土壤普查办公室.中国土壤普查数据.中国农业出版社,1997.
[26]石锦芹,丁瑞兴,刘友兆。尿素和茶树落叶对土壤的酸化作用.茶叶科学,1999,19(1)：7-12.
[27]孙羲.植物营养原理.中国农业出版社.1995,13-416
[28]王巧环 刘志崴 王甲因,海南农垦胶园土壤养分现状及平衡施肥,热带农科.1999,5：8-14..,
[29]王学锋,章衡.土壤有机质的空间变异性研究[J].土壤,1995,27(2)：85-89.
[30]王政权.地统计学及其在生态学中的应用.北京,科学出版社.1999.
[31]徐吉炎,土壤调查数据地域统计的最佳估值研究：彰武县表层土全氮量的半方差图和块状Kriging估值.土壤学报,1983,20(4)：419-430.
[32]严昶升,土壤肥力研究方法[M].北京：农业出版社,1988
[33]杨玉玲,文启凯,田长彦,等.土壤空间变异研究现状及展望.干旱区研 究.2001,18(2)：50-55.
[34]袁可能.植物营养元素的土壤化学.北京：科学出版设,1983.
[35]张文渊,水环境中的氮污染特征与影响因素.黑龙江环境通报,2000,24(5)1：27-28
[36]张焱华,何鹏等.橡胶园土壤酶活性与土壤肥力的关系.中国农学通报,2007,23(11)：375-379
[37]周慧珍,龚子同.土壤空间变异性研究[J].土壤学报.1996,33(3)：232-241.
[38]朱兆良,我国土壤供氮和化肥氮去向研究的进展.土壤,1985,17(4)1：2-9
[39]Azimi-Zonooz A,Krajewski W F,Bowles D S and Seo D J.Spatial rainfall estimation by linear and non-linear cokriging of radar-rainfall and raingage data.Stochastic ydrol. Hydraul.1989,3:51-67.
[40]Bedient P B and Huber W C.Hydrology and Floodplain Analysis:Second Edition. Addison-Wesley,New York.NY, 1992.
[41]Bogres R and MallarinoAP.Field-seale variability of pHospHorus and Potassium uptake by no -till com and soybean.Soil Sci.Soc.Am.J. 1997,61:846-853.。
[42]Borga M and Vizzaccaro A.On the interpolation of hydrologic variables:formal equivalence of multiquadratic surface fitting and kriging.Hydrol,1997,195(1-4):160~171.
[43]Boyer DG, Wrihgt RJ, Feldhake CM and Bligh DP.Soil spatial variability in steeply sloping acid soil environment.5011Sei. 1991,161:278-287.
[44]Burrough P A.Soil variability:a late 20th, century view.[J].Soil and fertilizers. 1993 56(5):529~562.
[45]Cahn MD,Hummel JW and Brouer BH. Spatial analysis of soil fertility for sitespecific crop management.soil Sci.Am.J. 1994,58:1240-1248.
[46]Chien YL, DY Lee, HY Guo, KH Houng.Geostatistical analysis of soil properties of mid-west Taiwan soils.Soil Science. 1997,162:291-297.
[47]Clark I.Practical geostatistics.Applied Science Publishers LTD.London,1981.
[48]Dane JH, Reed RB and Hopmans JW.Estimating Soil Parameters and sample site by bootstrapping.Soil Sci.Soc.Am.J.1986,5:283-287.
[49]David M J.Geostatistical ore reserve estimation.Amsterdam Elsevier,1997.
[50]Deutsch C V and Journel A G.GSLIB:Geostatistical Software Library and User's Guide:Second Edition.Oxford University Press,New York,NY,1998.
[51]Fislier, R.A., Statistic method for scientific inference[M].London, UK:Oliver and Boyd,Edinburg. 1956.
[52]Franzen D.W.,Hofman V.L., Halvorson A.D.et al., Sampling for site-specific farming:TopograpHy and nutrient considerations.Better Crops, 1996,80(3):14~18.
[53]Goovaerts P.Geostatistics for Natural Resources Evaluation.Oxford University Press,NewYork,NY,1997.
[54]GoovaertsP.Ordinarycokriging revisited.Math.Geol,1998,30(1):21-42.
[55]GoovaertsR.Geostatistics in soil science:state-of-the-art and Perspectives.Geoderma 1999,89:1~45。
[56]Hevesi J A,Istok J D and Flint AL.Precipitation estimation in mountainous terrain using multivariate geostatistics.PartⅠ:Structural analysis.Appl.Meteor,1992,31:661~676.
[57]Hevesi J A,Istok J D and Flint AL.Precipitation estimation in mountainous terrain using multivariate geostatistics.PartⅡ:Isohyetal maps.Appl.Meteor,31:677~688.。
[58]Hammond MW.Comparison of PHospHorus and Potassium utilization with conventional and variable fertility management.Better Crops,1994,78(4):22~23.,
[59]Issaks E H and Srivastava R M.An introduction applied geostatistics.Wxford Universtiy Press.New York.USA. 1986.
[60]JoumelAG and Huijbregts C J.Mning geostatistics.London.Academic Press.UK,1978.
[61]Kamgar A, Hopmans JW, Wallender WW and Wendroth O.On Piotsize and sample number of neutron Probe measurements in small field trials.Soil Sci. 1993,156:213-224.
[62]Miller PM, Singer MJ and Nielsen DR. Spatial variability of wheat yield and soil properties on complex hills. Soil Sci AM.J. 1988,52:1133-1141.
[63]MullaDJ, 1989.soil spatial variability and methods of ananlysis.In Renard CM etal(ed.).soil, crop, and water management systems of rainfed agriculture in the SudanoSaheliajn zone:Proc.Int.Workshop.Niamey, Niger.7-lIJan..l987.ICRISAT, Patancheru, Andhra Pradesh, India.pp241-252.
[64]Matheron GPrinciples of geostatistics.Econ.Geol,1963,58:1246-1266.
[65]Nolin MC, Guertin SP and Wang C,1996.Within-field spatial variability of soil nutrients and corn yield in a Montreal lowlands clay soil.In Robert PC(ed.) Proc.Of the third international conference on Precision agriculture.Minneapolis, MN.23-26June1996, ASA, CSSA, and SSSA, Madison, WI.Pp257-270.
[66]Raul ponce, hernandez.Improving the representation of soil spatial variability in geograpHical information system.1994.
[67]SteinA.Soil variability and geostatistics.Proc.Kon.Ned.Akad.v.Wctchsch,2005,98(2):133-140.
[68]Santos D, MurpHy SLS, Taubner H, Smuchker AJM and Horn R.Uniform sepatation of concentric surface layers from soil aggregates. Soil Sci.Soc.Am.J.1997,61:720-724.
[69]Sokal RR and FJ Rohlf.Biometry 2 Edition,W H Freeman and Company New York.1981.
[70]Solie JB, Raun WR and Stone ML.Submeter spatial variability of selected soil and bermudagrass production variables.Soil Sci.Soc.AM.J.1999,63:1724-1733.
[71]Shi Z,K Wang,JS Bailey,C Jordan and AH Higgins,Temporal changes in the spatial distributions of some soil properties on a temperate grassland site.Soil use and management 2002:353-362.
[72]Trangmar B B, Yost R S, Uehara.G.APPlication of geostatistics to spatialStudies of soil Properties.Advances in agronomy,1985.38:44-94
[73]Vueura, E.et.al., Geostatistical sampling network for estimation of variogram [J], Soil Sci.Soc.Am.J.1983,48:708-716.
[74]Wilcke W, Kaupenjohann M.Difference in concentrations and fractions of aluminum and heavy metals between aggregate interior and exterior. Soil Sci, 1997,162:323-332
[75]Wagenet RJ.Measurements and interpretation spatially variable leaching Processes.Nielsen DR and Bouma J(Eds).Soil spatial variability.Proceedings of a Workshop of the ISSS and SSSA, LasVegas;NV.Pudoc Wageningen Perss, Wageningen, the Netherlands.PP 1985,209-235.
[76]Wallender WW.Smaple volume statistical relations for water content, infiltration and yield.Trans.AM.Soc.Agric.Eng.1987,30:1043-1050.
[77]Wbster R..Quantitative spatial analysis of soil in the field.Advanced in soil science.1985,3:1-70.
[78]Webster R and McBratney AB.Mapping soil fertility at Broom's Barn by simple kriging.J Sci.Food Agric.1987,38:97-115.
[79]Webster R.Quantitative Spatial analysis of soil in the field.Advance in Soil Science,1985,3:1-70.
[80]Yost R S, Uehara G,Fox R L.Geostatistical analysis of soil chemical properties of large land areas.l.Semivariograms[J].Soil Sci.Soc.Am.J.1984,46:1028-1037.
[81]Yost R S, Uehara.G.APPlication of geostatistics to spatial Studies of soil Properties.Advances in agronomy,1985.38:44-94.
[82]Zhang R, Warrick Aw and Meyers DE.Variance as a function of sample support size.Math.Geol.1990,22:107-121.
[2]陈浮,蹼励杰等.近20年太湖流域典型区土壤养分时空变化及驱动机理[J].土壤学报,2002.39(2)：23-44.
[3]陈志雄,VuaClniM,封丘地区土壤水分平衡研究工.田间土壤湿度的空间变异.土壤学报,1999.16(3)：35-42.
[4]丁瑞兴,黄骁.茶园—土壤系统铝和氟的生物地球化学循环及其对土壤酸化的影响.土壤学报,1991；28(3)：229-236.
[5]郭旭东,傅伯杰,马克明,陈利顶等.基于GIS和地统计学的土壤养分空间变异特征研究—以河北省遵化市为例[J].应用生态学报,2000,11(4)：557-563.
[6]海南省农业厅土肥站.海南土壤[M].海口：海南出版社,1993.
[7]韩江波服务“三农”产业重点选择研究及相关对策——以海南天然橡胶产业为例[J]农村金融研究2008(01)：74-77
[8]何鹏,吴敏,韦家少.海南省胶园土壤肥力质量指标的时空变异特性研究.中国农学通报,2008,24(10)：310-316.
[9]何向东,陆行正,吴小平.海南岛胶园土壤肥力区划及其利用的研究[J].热带农业科学,1991,(01)：40-48.
[10]何向东,吴小平.海南恳区胶园土壤肥力演变探研[J].热带农业科学,1997,(04)：16-22.
[11]何向东,吴小平等.海南垦区胶园肥力演变探研.热带农业科学,2002,22(1)：16-22
[12]侯景儒,尹镇南,等.实用地质统计学.北京：地质出版社,1998.
[13]黄绍文,金继运,杨俐苹等.乡镇级土壤养分空间变异与分区管理技术研究.精准农业与土壤养分管理.北京：大地出版社,2001.248-259.
[14]蒋菊生,王如松著.海南橡胶产业生态[M].北京：中国科学技术出版社，2004：1-34.
[15]雷志栋,杨诗秀,许志荣等,土壤特性空间变异性初步研究。水利学报, 1989,26(4)：309-315.
[16]雷志栋,杨诗秀,许志荣等.土壤特性空间变异特性初步研究.水利学报,1985,(9)：10-21.
[17]李菊梅,李生秀.几种营养元素在土壤中的分布类型[J].干早地区农业研究,1998,16(1)：69-75.
[18]李荣刚,农业污染的由来、危害与内涵.当代生态农业,1999(3-4)：63-64.
[19]林钊沐,黎仕聪,茶正早,等.中国热带土壤植胶后肥力变化与胶树平衡施肥[J].农田养分平衡与管理[C].南京：河海大学出版社,2000：407-414.
[20]刘杏梅,徐建明等.太湖流域土壤养分空间变异特征分析—以浙江省平湖市为例,浙江大学学报,2005.
[21]鲁如昆.土壤农业化学分析方法[M].中国农业科技出版社,2000.
[22]陆正行,吴小平,何向东等,海南岛胶园土壤的钾素状况,热带作物学报,1989,10(1)：17-23.
[23]麦全法.我国主要植胶区胶园生态系统养分变化趋势的研究[D].华南热带农业大学,2006.
[24]漆智平,余让水.海南主要土壤钾素状况与热带农业[J].热带农业科学,1997,(04)：48-54.
[25]全国土壤普查办公室.中国土壤普查数据.中国农业出版社,1997.
[26]石锦芹,丁瑞兴,刘友兆。尿素和茶树落叶对土壤的酸化作用.茶叶科学,1999,19(1)：7-12.
[27]孙羲.植物营养原理.中国农业出版社.1995,13-416
[28]王巧环 刘志崴 王甲因,海南农垦胶园土壤养分现状及平衡施肥,热带农科.1999,5：8-14..,
[29]王学锋,章衡.土壤有机质的空间变异性研究[J].土壤,1995,27(2)：85-89.
[30]王政权.地统计学及其在生态学中的应用.北京,科学出版社.1999.
[31]徐吉炎,土壤调查数据地域统计的最佳估值研究：彰武县表层土全氮量的半方差图和块状Kriging估值.土壤学报,1983,20(4)：419-430.
[32]严昶升,土壤肥力研究方法[M].北京：农业出版社,1988
[33]杨玉玲,文启凯,田长彦,等.土壤空间变异研究现状及展望.干旱区研 究.2001,18(2)：50-55.
[34]袁可能.植物营养元素的土壤化学.北京：科学出版设,1983.
[35]张文渊,水环境中的氮污染特征与影响因素.黑龙江环境通报,2000,24(5)1：27-28
[36]张焱华,何鹏等.橡胶园土壤酶活性与土壤肥力的关系.中国农学通报,2007,23(11)：375-379
[37]周慧珍,龚子同.土壤空间变异性研究[J].土壤学报.1996,33(3)：232-241.
[38]朱兆良,我国土壤供氮和化肥氮去向研究的进展.土壤,1985,17(4)1：2-9
[39]Azimi-Zonooz A,Krajewski W F,Bowles D S and Seo D J.Spatial rainfall estimation by linear and non-linear cokriging of radar-rainfall and raingage data.Stochastic ydrol. Hydraul.1989,3:51-67.
[40]Bedient P B and Huber W C.Hydrology and Floodplain Analysis:Second Edition. Addison-Wesley,New York.NY, 1992.
[41]Bogres R and MallarinoAP.Field-seale variability of pHospHorus and Potassium uptake by no -till com and soybean.Soil Sci.Soc.Am.J. 1997,61:846-853.。
[42]Borga M and Vizzaccaro A.On the interpolation of hydrologic variables:formal equivalence of multiquadratic surface fitting and kriging.Hydrol,1997,195(1-4):160~171.
[43]Boyer DG, Wrihgt RJ, Feldhake CM and Bligh DP.Soil spatial variability in steeply sloping acid soil environment.5011Sei. 1991,161:278-287.
[44]Burrough P A.Soil variability:a late 20th, century view.[J].Soil and fertilizers. 1993 56(5):529~562.
[45]Cahn MD,Hummel JW and Brouer BH. Spatial analysis of soil fertility for sitespecific crop management.soil Sci.Am.J. 1994,58:1240-1248.
[46]Chien YL, DY Lee, HY Guo, KH Houng.Geostatistical analysis of soil properties of mid-west Taiwan soils.Soil Science. 1997,162:291-297.
[47]Clark I.Practical geostatistics.Applied Science Publishers LTD.London,1981.
[48]Dane JH, Reed RB and Hopmans JW.Estimating Soil Parameters and sample site by bootstrapping.Soil Sci.Soc.Am.J.1986,5:283-287.
[49]David M J.Geostatistical ore reserve estimation.Amsterdam Elsevier,1997.
[50]Deutsch C V and Journel A G.GSLIB:Geostatistical Software Library and User's Guide:Second Edition.Oxford University Press,New York,NY,1998.
[51]Fislier, R.A., Statistic method for scientific inference[M].London, UK:Oliver and Boyd,Edinburg. 1956.
[52]Franzen D.W.,Hofman V.L., Halvorson A.D.et al., Sampling for site-specific farming:TopograpHy and nutrient considerations.Better Crops, 1996,80(3):14~18.
[53]Goovaerts P.Geostatistics for Natural Resources Evaluation.Oxford University Press,NewYork,NY,1997.
[54]GoovaertsP.Ordinarycokriging revisited.Math.Geol,1998,30(1):21-42.
[55]GoovaertsR.Geostatistics in soil science:state-of-the-art and Perspectives.Geoderma 1999,89:1~45。
[56]Hevesi J A,Istok J D and Flint AL.Precipitation estimation in mountainous terrain using multivariate geostatistics.PartⅠ:Structural analysis.Appl.Meteor,1992,31:661~676.
[57]Hevesi J A,Istok J D and Flint AL.Precipitation estimation in mountainous terrain using multivariate geostatistics.PartⅡ:Isohyetal maps.Appl.Meteor,31:677~688.。
[58]Hammond MW.Comparison of PHospHorus and Potassium utilization with conventional and variable fertility management.Better Crops,1994,78(4):22~23.,
[59]Issaks E H and Srivastava R M.An introduction applied geostatistics.Wxford Universtiy Press.New York.USA. 1986.
[60]JoumelAG and Huijbregts C J.Mning geostatistics.London.Academic Press.UK,1978.
[61]Kamgar A, Hopmans JW, Wallender WW and Wendroth O.On Piotsize and sample number of neutron Probe measurements in small field trials.Soil Sci. 1993,156:213-224.
[62]Miller PM, Singer MJ and Nielsen DR. Spatial variability of wheat yield and soil properties on complex hills. Soil Sci AM.J. 1988,52:1133-1141.
[63]MullaDJ, 1989.soil spatial variability and methods of ananlysis.In Renard CM etal(ed.).soil, crop, and water management systems of rainfed agriculture in the SudanoSaheliajn zone:Proc.Int.Workshop.Niamey, Niger.7-lIJan..l987.ICRISAT, Patancheru, Andhra Pradesh, India.pp241-252.
[64]Matheron GPrinciples of geostatistics.Econ.Geol,1963,58:1246-1266.
[65]Nolin MC, Guertin SP and Wang C,1996.Within-field spatial variability of soil nutrients and corn yield in a Montreal lowlands clay soil.In Robert PC(ed.) Proc.Of the third international conference on Precision agriculture.Minneapolis, MN.23-26June1996, ASA, CSSA, and SSSA, Madison, WI.Pp257-270.
[66]Raul ponce, hernandez.Improving the representation of soil spatial variability in geograpHical information system.1994.
[67]SteinA.Soil variability and geostatistics.Proc.Kon.Ned.Akad.v.Wctchsch,2005,98(2):133-140.
[68]Santos D, MurpHy SLS, Taubner H, Smuchker AJM and Horn R.Uniform sepatation of concentric surface layers from soil aggregates. Soil Sci.Soc.Am.J.1997,61:720-724.
[69]Sokal RR and FJ Rohlf.Biometry 2 Edition,W H Freeman and Company New York.1981.
[70]Solie JB, Raun WR and Stone ML.Submeter spatial variability of selected soil and bermudagrass production variables.Soil Sci.Soc.AM.J.1999,63:1724-1733.
[71]Shi Z,K Wang,JS Bailey,C Jordan and AH Higgins,Temporal changes in the spatial distributions of some soil properties on a temperate grassland site.Soil use and management 2002:353-362.
[72]Trangmar B B, Yost R S, Uehara.G.APPlication of geostatistics to spatialStudies of soil Properties.Advances in agronomy,1985.38:44-94
[73]Vueura, E.et.al., Geostatistical sampling network for estimation of variogram [J], Soil Sci.Soc.Am.J.1983,48:708-716.
[74]Wilcke W, Kaupenjohann M.Difference in concentrations and fractions of aluminum and heavy metals between aggregate interior and exterior. Soil Sci, 1997,162:323-332
[75]Wagenet RJ.Measurements and interpretation spatially variable leaching Processes.Nielsen DR and Bouma J(Eds).Soil spatial variability.Proceedings of a Workshop of the ISSS and SSSA, LasVegas;NV.Pudoc Wageningen Perss, Wageningen, the Netherlands.PP 1985,209-235.
[76]Wallender WW.Smaple volume statistical relations for water content, infiltration and yield.Trans.AM.Soc.Agric.Eng.1987,30:1043-1050.
[77]Wbster R..Quantitative spatial analysis of soil in the field.Advanced in soil science.1985,3:1-70.
[78]Webster R and McBratney AB.Mapping soil fertility at Broom's Barn by simple kriging.J Sci.Food Agric.1987,38:97-115.
[79]Webster R.Quantitative Spatial analysis of soil in the field.Advance in Soil Science,1985,3:1-70.
[80]Yost R S, Uehara G,Fox R L.Geostatistical analysis of soil chemical properties of large land areas.l.Semivariograms[J].Soil Sci.Soc.Am.J.1984,46:1028-1037.
[81]Yost R S, Uehara.G.APPlication of geostatistics to spatial Studies of soil Properties.Advances in agronomy,1985.38:44-94.
[82]Zhang R, Warrick Aw and Meyers DE.Variance as a function of sample support size.Math.Geol.1990,22:107-121.