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首页> 外文会议>Statistics, mathematics and computers : Caring for the forest: research in a changing world >DESIGNING SURVEYS OF FOREST DIVERSITY USING STATISTICAL SAMPLING PRINCIPLES
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DESIGNING SURVEYS OF FOREST DIVERSITY USING STATISTICAL SAMPLING PRINCIPLES

机译：使用统计抽样原理设计森林多样性调查

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Monitoring to detect changes in forest biodiversity requires that the data 1) actually reflect spatial and temporal patterns in biodiversity that are of interest, 2) are reliable and repeatable, and 3) use resources (time, money) optimally. Biodiversity sampling has emphasized field protocols, assuming that standardization will result in data that accurately reflect true diversity patterns. However, many sources of bias and variability exist that may confound temporal and spatial comparisons of biodiversity measures, even if the field sampling is identical at all locations (e.g., forest biodiversity plots). In particular, measures such as presence/absence, species richness, relative abundance, and diversity indices are sensitive to 1) unequal sampling probabilities among species; 2) low probability of sampling rare species; 3) biased sampling; and 4) spatially or temporally heterogeneous sampling. Standardized field methods and the use of techniques such as species-area relationships are not robust to the above. These problems can be ameliorated through proper definition of a target population, judicious choice of a sampling frame and method for selecting sampling units, and collection of ancillary data to estimate and adjust for sampling heterogeneity. Complicating matters, forest biodiversity surveys frequently are implemented at one level of spatial resolution but used for comparisons at other levels. Finally, resources are limited, and it is unlikely that all objectives of a forest biodiversity survey can be met. Sampling and decision theories can be used to evaluate how a survey is likely to meet conservation objectives, and in adaptively refining surveys and re-allocating survey efforts.
机译：监测森林生物多样性变化的监测要求数据1）实际反映感兴趣的生物多样性的空间和时间格局，2）可靠且可重复，3）最佳利用资源（时间，金钱）。假设标准化将导致数据准确反映真实的多样性模式，则生物多样性采样强调了现场协议。但是，即使在所有地点（例如，森林生物多样性地块）的田间采样都是相同的，也存在许多偏差和变异性的来源，可能使生物多样性措施的时间和空间比较混乱。尤其是，诸如存在/不存在，物种丰富度，相对丰度和多样性指数之类的措施对1）物种之间不平等的采样概率很敏感； 2）采样稀有物种的可能性低； 3）有偏抽样；和4）空间或时间上的异质采样。标准化的现场方法和诸如物种-地区关系之类的技术的使用对上述内容都不可靠。可以通过适当定义目标人群，明智地选择抽样框架和选择抽样单位的方法以及收集辅助数据以估计和调整抽样异质性来改善这些问题。使事情变得复杂的是，森林生物多样性调查通常是在空间分辨率的一个层面上进行的，而在其他层面上则用于比较。最后，资源有限，不可能实现森林生物多样性调查的所有目标。抽样和决策理论可用于评估调查可能达到保护目标的方式，以及适应性地完善调查和重新分配调查工作的方式。

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