Evaluation of museum collection data for use in biodiversity assessment
Evaluation of museum collection data for use in biodiversity assessment
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DOI：
10.1046/j.1523-1739.2001.015003648.x
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发表时间：
2001-06-01
影响因子：
6.3
通讯作者：
Chapman, RR
中科院分区：
文献类型：
--
作者：
Ponder, WF;Carter, GA;Chapman, RR
博物馆的自然历史藏品包含了对生物多样性保护决策至关重要的数据。总的来说，这些基于标本的数据描述了已知分类群在时间和空间上的分布。作为大多数已描述物种的最全面、最可靠的知识来源，这些记录可能用于回答广泛的保护和研究问题。然而，这些数据有缺点，特别是地理差距，主要是由于收集工作的临时性造成的。这个问题经常被提及，但很少以系统的方式加以解决。我们已经开发了一种方法来评估博物馆收藏数据，特别是窄范围分类群分布数据的可靠性。我们只收录了那些记录数量不合适、鉴定经过专家验证且位置准确性可接受的分类群。首先，我们将感兴趣的分类单元的可用数据与“背景数据”进行比较，“背景数据”由可能通过相同方法或由与感兴趣的分类单元相同的收集器捕获的那些生物体的记录组成。通过计算描述点的分离、密度和聚类的统计数据来评估背景采样工作的“充分性”，并通过生成采样密度等高线面，然后使用地理信息系统（GIS）技术对基于非生物（例如气候和地质）数据的物种分布进行建模预测。这些预测分布的鲁棒性可以通过迭代或自举来测试。这些方法共同提供了一种客观的手段来评估从博物馆收藏记录中获得的代表真实分布的分布的可能性。潜在地，它们可以用于评估物种地图、生物多样性评估或需要分布信息的类似应用中需要整理的任何点数据。
Natural-history collections in museums contain data critical to decisions in biodiversity conservation. Collectively, these specimen-based data describe the distributions of known taxa in time and space. As the most comprehensive, reliable source of knowledge for most described species, these records are potentially available to answer a wide range of conservation and research questions. Nevertheless, these data have shortcomings, notably geographic gaps, resulting mainly from the ad hoc nature of collecting effort. This problem has been frequently cited but rarely addressed in a systematic manner. We have developed a methodology to evaluate museum collection data, in particular the reliability of distributional data for narrow-range taxa. We included only those taxa for which there were nn appropriate number of records, expert verification of identifications and acceptable locality accuracy. First, we compared the available data for the taxon of interest to the "background data," comprised of records for those organisms likely to be captured by the same methods or by the same collectors as the taxon of interest. The "adequacy" of background sampling effort was assessed through calculation of statistics describing the separation, density, and clustering of points, and through generation of a sampling density contour surface Geographical information systems (GIS) technology was then used to model predicted distributions of species based on abiotic (e.g., climatic and geological) data. The robustness of these predicted distributions can be tested iteratively or by bootstrapping. Together these methods provide an objective means to assess the likelihood of the distributions obtained from museum collection records representing true distributions. Potentially, they could be used to evaluate any point data to be collated in species maps, biodiversity assessment, or similar applications requiring distributional information.