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黄花甸子流域土壤全氮、速效磷、速效钾的空间变异

李龙,姚云峰**,秦富仓   

  1. (内蒙古农业大学生态环境学院, 呼和浩特 010018)
  • 出版日期:2015-02-07 发布日期:2015-02-07

Spatial variability of soil total nitrogen, available phosphorus and available potassium in Huanghuadianzi watershed.

LI Long, YAO Yun-feng**, QIN Fu-cang   

  1. (College of Ecology and Environmental Science, Inner Mongolia Agricultural University, Hohhot 010018, China)
  • Online:2015-02-07 Published:2015-02-07

摘要:

选择赤峰市敖汉旗黄花甸子流域为研究对象,以实地取样数据为基础,结合空间自相关、半变异函数及克里格插值方法,分析流域内全氮、速效磷和速效钾的空间变异特征。结果表明:全氮、速效磷和速效钾总体上均呈岛状分布,全氮和速效磷呈现较为分散的斑点状的肥岛状分布;速效钾呈现明显的岛状分布。3种养分的空间自相关性均随着滞后距离的增加而降低,并存在明显的正、负相关区域,并分别与其空间聚集和空间孤立区域相对应。速效磷的C0/(C+C0)为17.21%,具有强烈空间相关性。全氮、速效钾的C0/(C+C0)分别为27.03%和44.99%,属于中等程度的空间相关性。空间自相关距离与变程均表现为全氮<速效磷<速效钾。不同土地利用方式下各养分含量总体表现为农地>林地>草地。人为活动是影响研究区养分空间变异的主要原因。
 

关键词: 低空遥感, 高光谱成像仪, 多光谱成像仪, 热红外成像仪, 无人机生态学, 激光雷达

Abstract: The spatial autocorrelation, semi-variograms and Kriging interpolation were used to study the spatial variations of total nitrogen, available phosphorus and available potassium in Huanghuadianzi watershed in Aohan Chifeng, Inner Mongolia based on the field sampling. The results showed that total nitrogen, available phosphorus and available potassium were in island distribution on the whole. Total nitrogen and available phosphorus showed a scattered “fertile islands” distribution, while available potassium showed an obvious island distribution. The spatial autocorrelation of nutrients increased with the decrease of lag distance. There were positively and negatively correlated regions, corresponding to the spatial clustering and spatial isolation, respectively. The C0/(C+C0) value of available phosphorus was 17.21%, belonging to a strong spatial correlation. Such values for total nitrogen and available potassium were 27.03% and 44.99%, respectively, belonging to a moderate spatial correlation. Both spatial autocorrelation distance and range were in order of total nitrogen < available phosphorus < available potassium. The nutrient contents under different landuse types were in order of cropland > forestland > grassland. Human activity was the main factor influencing the spatial variability of nutrients in the study area.

Key words: unmanned aerial vehicles ecology, low-altitude remote sensing, multispectral imager, LiDAR, hyperspectral imager, thermal infrared imager