Two-stage sequential sampling for two rare species in western Inner Mongolia of China  被引量:1

Two-stage sequential sampling for two rare species in western Inner Mongolia of China

在线阅读下载全文

作  者:SHI JingJing ZHAO TianZhong LEI YuanCai 

机构地区:[1]School of Information Science and Technology, Beijing Forestry University [2]Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry

出  处:《Chinese Science Bulletin》2013年第4期507-516,共10页

基  金:supported by State Forestry Administration (201204510 and200904003);National Natural Science Foundation of China (31170588);Social commonweal Research Progvams of Ministry of Science and Technology (2005DIB5J142)

摘  要:To evaluate the efficiencies of different sampling methods for a rare and clustered population, we investigated the sampling effects for the two species Tamarix chinensis (Salt cedar) and Elaeagnus angustifolia (Russian olive) in western Inner Mongolia with two-stage sequential sampling, which is a new sampling method, traditional simple random sampling and two-stage sampling. Based on two-stage sequential sampling and two-stage sampling, each population was partitioned into four primary sampling units, and then two of them were randomly selected. Sampling designs were simulated based on the conditions of five secondary sampling unit areas, two criterion values, five initial secondary sampling units and two sequential secondary sampling units in 1000 repetitions. To evaluate the performance of the sampling designs for each method, the variance and relative error of the density estimates were used. The relative sampling efficiencies of the three sampling methods were compared using the same final sampling sizes. We analyzed the sampling efficiency generated by two-stage sequential sampling and found that it yielded smaller variances than those of simple random sampling and two-stage sampling in all sampling designs, and that two-stage sampling was more efficient than simple random sampling. Density estimates from the two-stage sequential sampling were very close to the true values. We also determined the optimum secondary sampling unit areas for the two species in the two-stage sequential sampling. It was best for Tamarix chinensis and Elaeagnus angustifolia when the secondary sampling unit areas were 200 and 100 m2 , respectively.To evaluate the efficiencies of different sampling methods for a rare and clustered population, we investigated the sampling ef- fects for the two species Tamarix chinensis (Salt cedar) and Elaeagnus angustifolia (Russian olive) in western Inner Mongolia with two-stage sequential sampling, which is a new sampling method, traditional simple random sampling and two-stage sampling. Based on two-stage sequential sampling and two-stage sampling, each population was partitioned into four primary sampling units, and then two of them were randomly selected. Sampling designs were simulated based on the conditions of five secondary sampling unit areas, two criterion values, five initial secondary sampling units and two sequential secondary sampling units in 1000 repetitions. To evaluate the performance of the sampling designs for each method, the variance and relative error of the den- sity estimates were used. The relative sampling efficiencies of the three sampling methods were compared using the same final sampling sizes. We analyzed the sampling efficiency generated by two-stage sequential sampling and found that it yielded smaller variances than those of simple random sampling and two-stage sampling in all sampling designs, and that two-stage sampling was more efficient than simple random sampling. Density estimates from the two-stage sequential sampling were very close to the true values. We also determined the optimum secondary sampling unit areas for the two species in the two-stage sequential sampling. It was best for Tamarix chinensis and Elaeagnus angustifolia when the secondary sampling unit areas were 200 and 100 m2, re- spectively.

关 键 词:顺序采样 内蒙古西部 物种 简单随机抽样 中国 采样方法 采样设计 密度估计 

分 类 号:Q948[生物学—植物学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象