三种松毛虫混合种群幼虫抽样技术的研究

本文应用Taylor幂法则模型中的两个参数a和b,就3种松毛虫混合种群幼虫的抽样技术进行了以下几个方面的研究:①最适理论抽样数的确定;②种群密度的简易估计;③复序贯抽样技术;④简易序贯抽样技术;⑤简单随机抽样最适样方大小的确定;⑥资料代换方法。此外,文中还就种群聚集临界密度进行了探讨。为进行松毛虫种群动态的研究和实施综合管理决策,提供了优化的抽样设计,收到了良好的应用效果.     

3种松毛虫混合种群幼虫密度的简易估计及其序贯抽样决策模型

在3种松毛虫混合种群幼虫空间图式研究结果的基础上,按Iwao的方法,首先给出了种群密度的简易估计模型;利用Bechinski的方法,又建立起简易序贯抽样决策模型,简化了抽样过程,提高了决策分析的速度等。此外,还给出了再次改进的Iwao m-m模型的P-m关系,并就简易序贯抽样决策图的绘制进行了必要的讨论。     

La—m幂法则模型的抽样方法

基于笔者提出的研究生物种群空间格局的Ｌａ－ｍ幂法则模型（Ｌａ＝βｍ＾δ），本文推导出如下抽样设计方法：（１）种群密度的简易估计方法；（２）简单随机抽样最适理论抽样数的确定方法；（３）分层随机抽样最适理论抽样数的确定方法；（４）二阶抽样最适配额的确定方法；（５）按临界密度划分不同种群水平的序贯抽样方法；（６）最适样方大小的确定方法；（７）种群密度与负二项分布参数ｋ的关系以及Ｌａ－ｍ幂法则模型的非线性     

三种松毛虫混合种群幼虫抽样技术的研究

基于负二项分布公共K(K_c)值,文中就三种松毛虫混合种群幼虫的抽样技术进行了以下几个方面的探讨:①最适理论抽样数的确定;②复序贯抽样;③给出了以零频率估计幼虫密度和以概率保证的理论抽样数方法的结合,来实现有效的简易抽样;④推导出一个确定简单随机抽样最适样方大小的新的准则。     

松毒蛾序贯抽样技术的研究

在确定分布型的基础上,采用概率分布公式法,Taylor,Iwao、兰星平等回归分析方法和Green以及Willson的序贯分析方法,对松毒蛾幼虫和越冬蛹的序贯抽样作了分析研究。根据确定的序贯抽样方程,制作了序贯分析表和绘制了序贯分析图。对不同密度下的最适抽样数量和同一密度不同允许误差下的抽样数量进行了讨论。     

舞毒蛾卵块序贯抽样技术的研究

对舞毒蛾分布特征明显、种群数量稳定、历期时间长以及易于调查计数的卵块的序贯抽样技术进行了系统研究 ,提出了用于指导防治的一组序贯抽样方程和最适抽样数量的确定公式。     

杨干透翅蛾种群空间分布型及其应用的研究

利用平均拥挤度、扩散指数等5种聚集度指标以及Iwao回归模型、Taylor冥法则等方法分析了杨干透翅蛾幼虫种群的空间分布型。对结果分析得到杨干透翅蛾幼虫种群在林内呈现聚集分布,并且聚集度高;采用聚集均数法进行进一步分析表明聚集原因主要为生物学特性所致。同时,对杨干透翅蛾幼虫种群的理论抽样数和序贯抽样技术进行了初步研究。     

油松毛虫蛹种群的简易序贯抽样决策模型

本文将Steel-Torrie序贯决策模型与Gerrard-Chiang种群密度的简易估计模型相结合,推导出了油松毛虫蛹种群的“简易序贯决策”模型。拟定蛹种群的防治指标m。=3枚蛹/株,则相对应的有蛹株率P_1=exp[-(m。/1.9318)~(0:8717)]=77％,序贯决策限模型,即q个样株中有蛹株数的上界,下界,允许误差h=0.15时的最大抽样数q_(max)=[t_a~2P_t(1-P_t)]h~2≈32。 简易序贯抽样方法仅需检查样本单元中有无虫即可,而不必逐一统计虫口数,因而比较简便。     

昆虫空间分布型的估值序贯抽样与应用

本文依据参数估计原理,提出了昆虫空间分布型:正二项分布、泊松分布、负二项分布和奈曼分布的估值序贯抽样新模型,推导了不同分布的估值序贯抽样方程、最大数量抽样公式,讨论了序贯分析图的绘制方法。新模型具有计算简便、易于应用的优点,能将不同分布型的有关信息应用于抽样过程。在野外调查中,能够快速、准确地判断昆虫种群密度是否达到防治指标,为防治方案的制定提供了依据。本方法也为其它概率分布的估值序贯抽样提供了一个新的途径。     

竹梢凸唇斑蚜空间分布型及抽样技术研究

应用Taylor幂法则和Iwao回归法,对竹梢凸唇斑蚜空间分布型及抽样技术进行了研究,并进行了影响因素分析.结果表明:竹梢凸唇斑蚜在竹林间呈聚集分布,且符合负二项分布,聚集强度随种群密度的升高而增加;种群聚集主要是由昆虫本身的习性和某些环境因素引起.在空间分布型研究的基础上提出了理论抽样数和序贯抽样方案.     

Point transect sampling of deadwood: a comparison with well-established sampling techniques for the estimation of volume and carbon storage in managed forests

In managed forests, the occurrence of deadwood (DW) can be regarded as a stochastically rare event with strong clumping and high local variability (Meyer in Forstwissenschaftliches Centralblatt 118:167–180, 1999). Traditional sampling techniques, such as Fixed Area Sampling, Angle Count Sampling and Line Intersect Sampling, do not regard this fact and may be inefficient for surveys of DW, because of limited search areas. A sampling technique that should remedy this shortcoming is Point Transect Sampling (Buckland et?al. in Introduction to distance sampling: estimating abundance of biological populations. Oxford University Press, Oxford, 2001; Advanced distance sampling: estimating abundance of biological populations. Oxford University Press, Oxford, 2004), where as a matter of principle, all objects that are sighted from a fixed location are counted. We compare Point Transect Sampling with the other well-established sampling approaches for the estimation of volume, necromass and carbon storage in terms of precision and sampling effort. It is shown that Point Transect Sampling is the superior method for sampling standing DW regarding efficiency, whereas for sampling downed DW, it is clearly outperformed by Line Intersect Sampling.     

Spatial distribution and sampling of Thaumetopoea pityocampa (Den. & Schiff.) (Lep. Thaumetopoeidea) populations on Pinus pinaster Ait. in Montesinho, N. Portugal

The pine processionary moth, Thaumetopoea pityocampa (Den. & Schiff.) is one of the most destructive pine pests in the Mediterranean countries. The first objective of this study was to analyse the spatial distribution of this insect on the tree on Pinus pinaster Ait., in northeast Portugal. The second objective was to develop two sampling plans: a sampling plan with fixed levels of precision for estimating T. pityocampa populations and a sequential sampling plan to classify the pest. Population estimates were made by registering the number of insect egg batches on 90 trees distributed over 3 stands during a 3-year study (1997–2000). Taylor's power law and Iwao regression were used to analyse the spatial distribution of the pest. Taylor's power law fitted the data better (r² = 0.775) than Iwao's regression model (r² = 0.704). The aggregation indices (b and β) were both significantly greater than one, indicating the aggregation of T. pityocampa egg batches. Optimal sample sizes for fixed precision levels of 0.10, 0.15 and 0.25 were estimated with Taylor's regression coefficients. Required sample sizes increased dramatically with increased levels of precision. The two sampling plans presented should be a tool for research on population dynamics and pest management decision.     

A review of the sampling theory of comprehensive forest resources monitoring

Sampling is a key technique in comprehensive forest resources monitoring. The history of the sampling survey was briefly reviewed and sampling theories were classified and compared in detail. On the basis of that, the application of different sampling methods in comprehensive forest resources monitoring was illustrated in accordance with the sampling classification of Michael Köhl et al. Improvement of the sampling system in China was discussed to meet the new requirements of forest monitoring.     

森林资源抽样调查技术方法研究进展

抽样调查是森林资源综合监测调查的关键技术和方法.本文介绍了抽样理论的发展和国内外森林抽样调查发展过程,论述了森林调查中主要抽样方法的特点和研究现状,其中包括等概和不等概抽样、基于遥感的抽样、针对稀疏总体分布的抽样调查技术方法,并对这些抽样技术在国内外森林资源调查中的应用进行了综述,概括了抽样调查技术方法的发展趋势,最后总结了抽样技术方法还存在的一些问题.     

再次改进的Iwao m -m模型在昆虫种群抽样技术研究中的应用

于秀林等(1986)再次改进了Iwao m-m模型,更为准确地描述了m-m关系。本文将该模型应用于昆虫种群抽样技术的研究中,推导出一组抽样设计模型。     

Estimating stand transpiration in a Eucalyptus populnea woodland with the heat pulse method: measurement errors and sampling strategies

Sap flow measurement techniques, such as the heat pulse (compensation) method, are practical means for estimating the water use of individual trees and are often the only reasonable alternative for measuring forest and woodland transpiration in complex heterogeneous terrain. The need to scale estimates of water use from a sample of individual stems to a stand (population) of known area may be satisfied by applying scalars of flux based on tree size or domain. We estimated the aggregate errors in applying the heat pulse technique to the estimation of stand transpiration in a poplar box (Eucalyptus populnea F.J. Muell.) woodland in southeastern Queensland, Australia, by a combination of precision analyses, experimental validation and Monte Carlo simulations of sampling errors. Errors in sap flux density measurements were approximately 13%. The potential error in the flux estimates for individual stems with stratified sampling of sap flux density with depth and bole quadrant based on four sensors was an additional 25%. Conducting wood area, diameter at 1.3 m, leaf area and domain based on Ecological Field Theory all proved excellent scalars of flux at the stand level. With a sample size of six trees stratified by diameter, coefficients of variation in scaling to the stand level were approximately 5% for any of these scalars. The greatest potential source of error in estimating stand transpiration by the heat pulse method was in the measurement of the fluxes of individual stems; scaling these measurements to a homogeneous stand of trees involved less uncertainty.     

枣步曲幼虫空间分布型及抽样技术的研究

通过ＩｗａｏＸ－Ｘ回归测定，枣步曲幼虫的空间分布为奈曼－Ａ型分布或波松－二项分布，分布的基本成分为致密的个体群，个体群间及个体群内的分布均为随机分布，个体群的面积小于或等于１株树，对于估值抽样提出了两种方案，即整体抽样和层抽样，前者以随机抽样和棋盘式抽样为优，并给出了理论抽样公式，后者以最下层抽样代替整株抽样估计种群密度，可以提高抽样效率，降低抽样费用，且估计精度能达到科研与生产的要求，最后给出Ｉ     

森林资源调查中不同样地设置方法的比较

角规控制检尺样地是一种高效的抽样方法。以延寿县国家重点生态公益林监测为例,对用角规控制检尺样地与圆形样地2种样地设置方法进行比较,结果表明：角规控制检尺样地在森林资源调查总体控制中是准确可靠的,但也存在一定的局限性。     

Adaptive cluster sampling for estimation of deforestation rates

National estimates of deforestation rates may be based on a survey. Precise estimation requires an efficient design. When deforestation rates are low (<1%) large sample sizes are required with traditional sampling designs to meet a precision target. This study explores the efficiency of adaptive cluster sampling (ACS) for this estimation problem. The efficiency is assessed by simulated ACS sampling from 18,200 × 200 km populations with 78–10,742 deforestation polygons (DFP) of different shape and size and average 10-year deforestation rates between 0.2% and 1.0%. Each population is composed of four million square 1 ha population units (PU) in a regular grid. Relative root mean square errors (RMSE) of ACS were, depending on sample size, 30–50% lower than comparable errors with simple random sampling (SRS) designs. ACS achieves this advantage by adaptively adding PUs to an initial SRS sample of size n. Realized ACS sample sizes were, on average, twice the nominal size (n). Three measures of ACS efficiency indicated that the costs of adaptively increasing the sample size are critical for the effectiveness of ACS. Population effects were manifest in all estimators. Estimates of the abundance, size, and shape of DFPs will allow a prediction of these effects. Populations dominated by a few large DFPs were clearly unsuited for ACS. The performance of ACS relative to that of SRS was similar across plot sizes of 1, 10, and 40 ha. The general conclusion of this study is that the lower RMSE of ACS remains attractive when the average cost of adaptively adding a PU to the initial sample is low relative to the average cost of sampling a PU at random.     

毛红椿天然群体遗传多样性及取样策略探讨

[目的]研究毛红椿天然群体遗传多样性取样策略,为其种质资源收集、保存和遗传多样性保护等提供参考依据。[方法]利用8对微卫星分子标记进行毛红椿天然群体遗传多样性和空间自相关分析,综合制定其天然群体合理取样策略。[结果]毛红椿天然群体等位基因数平均为7.5个,期望杂合度(H_e)和多态性信息指数(PIC)均值分别为0.643 7和0.636 0,基因分化系数(G_(ST))均值为0.290 7。在遗传多样性取样策略方面,提出了根据毛红椿群体基因分化系数来确定取样群体遗传变异所占总变异比例的运算公式为1-(G_(ST))~(n-1),其中,n为取样群体的数量。当取样群体达到4个时,基本上能包括该树种97.5%的遗传变异;同时确定了目标群体的选择方法,应选择与其它群体间基因分化系数均值较大的4个群体,即贵州册亨(CH)、浙江遂昌(SC)、浙江仙居(XJ)和云南师宗(SZ)。通过构建云南宾川(BC)、云南师宗(SZ)和江西宜丰(YF)群体内取样单株数量与基因多样性和等位基因之间的捕获曲线,确定了群体内取样单株数量应达到15个以上;毛红椿天然群体内300～520 m范围内的单株间存在相似关系,超出此范围个体间差别较大,说明在进行群体内单株取样时,单株间距应大于520 m。[结论]取样群体数量、群体间遗传分化系数、群体内单株数量以及单株间距离等影响了毛红椿取样群体的遗传多样性。毛红椿天然群体遗传多样性取样策略为取样群体4个、每个群体最少取样15个单株,单株间距大于520 m。