Survey-gap analysis in expeditionary research: where do we go from here?
Survey-gap analysis in expeditionary research: where do we go from here?
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DOI：
10.1111/j.1095-8312.2005.00520.x
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发表时间：
2005-08-01
影响因子：
1.9
通讯作者：
Ferrier, S
中科院分区：
文献类型：
--
作者：
Funk, VA;Richardson, KS;Ferrier, S
深入偏远地区收集生物标本的研究考察为了解生物多样性提供了重要信息。然而，对鲜为人知的地区进行大规模的探险是昂贵和耗时的，时间很短，训练有素的人很难找到。此外，处理这些藏品和获得准确的身份证明需要时间和金钱。为了获得最大的投资回报，我们需要仔细确定采集探险的地点。在这项研究中，我们利用环境变量和现有的收集地点的信息，以帮助确定未来的探险地点。其他研究的结果被用来帮助选择环境变量，包括与温度、降雨量、岩性和地点之间的距离有关的变量。基于“艾德互补性”的调查差距分析工具被用来选择最有可能贡献最多新分类群的地点。该工具不评估如何以及收集以前访问过的现场调查网站可能是，但是，收集工作估计的基础上物种积累曲线。我们使用每个采集点的采集数量和/或物种数量来消除那些我们认为采集不佳的物种。植物，鸟类和昆虫从圭亚那进行了检查，使用调查差距分析工具，并确定了未来的收集探险的网站。圭亚那东南部地区几乎没有可收集的信息。由于政治原因，多年来一直无法进入，因此，最初选定的10个地点中有8个在该地区。为了评价该国其余地区，而且由于圭亚那政府目前没有计划开放该地区进行勘探，因此该国该地区未列入研究报告的其余部分。在选择前十个位点后，艾德互补值的范围急剧下降。对于植物，我们有最多的记录，选择的地区包括帕卡赖马山脉的几个地方，与东南部的边界，以及西北部的一个地点。对于鸟类，一个适度收集的群体，最强烈的需求是在西北部，其次是东部。昆虫的数据集最小，艾德互补值的范围最大;结果非常强调该国南部地区，但大多数地点似乎彼此等距，最有可能是因为数据不足。结果表明，使用调查差距分析工具，旨在解决一个位置的问题，使用连续的环境数据，可以帮助最大限度地利用我们的资源，收集新的生物多样性信息。(c)2005年，伦敦林奈学会。
Research expeditions into remote areas to collect biological specimens provide vital information for understanding biodiversity. However, major expeditions to little-known areas are expensive and time consuming, time is short, and well-trained people are difficult to find. In addition, processing the collections and obtaining accurate identifications takes time and money. In order to get the maximum return for the investment, we need to determine the location of the collecting expeditions carefully. In this study we used environmental variables and information on existing collecting localities to help determine the sites of future expeditions. Results from other studies were used to aid in the selection of the environmental variables, including variables relating to temperature, rainfall, lithology and distance between sites. A survey gap analysis tool based on 'ED complementarity' was employed to select the sites that would most likely contribute the most new taxa. The tool does not evaluate how well collected a previously visited site survey site might be; however, collecting effort was estimated based on species accumulation curves. We used the number of collections and/or number of species at each collecting site to eliminate those we deemed poorly collected. Plants, birds, and insects from Guyana were examined using the survey gap analysis tool, and sites for future collecting expeditions were determined. The south-east section of Guyana had virtually no collecting information available. It has been inaccessible for many years for political reasons and as a result, eight of the first ten sites selected were in that area. In order to evaluate the remainder of the country, and because there are no immediate plans by the Government of Guyana to open that area to exploration, that section of the country was not included in the remainder of the study. The range of the ED complementarity values dropped sharply after the first ten sites were selected. For plants, the group for which we had the most records, areas selected included several localities in the Pakaraima Mountains, the border with the south-east, and one site in the north-west. For birds, a moderately collected group, the strongest need was in the north-west followed by the east. Insects had the smallest data set and the largest range of ED complementarity values; the results gave strong emphasis to the southern parts of the country, but most of the locations appeared to be equidistant from one another, most likely because of insufficient data. Results demonstrate that the use of a survey gap analysis tool designed to solve a locational problem using continuous environmental data can help maximize our resources for gathering new information on biodiversity. (c) 2005 The Linnean Society of London.