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Taxonomist survey biases and the unveiling of biodiversity patterns

机译:分类学家调查偏见和生物多样性模式的揭幕

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Basic and applied studies based on biodiversity data need accurate information on the distribution of species. However, several studies clearly show that this information is frequently biased, mainly as a consequence of aggregated survey patterns in which taxonomists repeatedly select localities with specific characteristics. In this study, we have constructed three different but simple virtual species richness scenarios to simulate the capacity of random, aggregated or regular survey designs to reveal the true biodiversity pattern. We are specifically interested in the effect of taxonomist insistence on surveying those localities that guarantee success in the collection of as many species as possible (species richness bias), and on the coordinated or uncoordinated character of the efforts carried out by the whole community of taxonomists. In all simulated species richness scenarios, a survey directed towards those localities that were previously recognized as having a higher species richness value is not recommended if the aim is to recover the true geographical pattern of species richness in a given territory. This aggregated process of allocating survey localities is probably caused by the primary aim of taxonomists, which is to acquire specimens of rare species and/or as many species as possible. However, an increase in taxonomist curiosity towards non-surveyed localities near those previously identified as the richest allows one to obtain better results, provided that the species richness pattern is not too patchy and the effort for discovering the true map is not too difficult. Our results suggest that planned survey designs are necessary when most of the data comes from studies not specifically designed to reveal the distribution of biodiversity. The capacity of this data to represent the real geographical pattern of biodiversity may depend on the capacity of the taxonomist community to be self-motivated.
机译:基于生物多样性数据的基本和应用研究需要准确的物种分布信息。然而,几项研究清楚地表明,这种信息经常偏见,主要是由于分类师反复选择具有特定特征的地方的聚合调查模式的结果。在这项研究中,我们建造了三种不同但简单的虚拟物种丰富情景,以模拟随机,汇总或常规调查设计的能力,以揭示真正的生物多样性模式。我们专门对分类学家坚持对调查这些地方的影响,这些地方的效果是在收集尽可能多的物种中(物种丰富大偏见),以及分类学家整个社区进行的协调或不协调的性格。在所有模拟物种中的丰富情景中,如果目的是在特定领土中恢复物种丰富性的真实地理模式,则不建议将先前被认为具有更高物种丰富价值的地方的调查。这种分配调查区域的汇总过程可能是由分类学家的主要目标引起的,这是获得罕见物种和/或尽可能多种物种的标本。然而,分类师在以前被确定为最富有的人附近的非调查地区的好奇心的提升性允许人们获得更好的结果,条件是该物种丰富的模式不是太斑驳,发现真实地图的努力不是太难。我们的研究结果表明,当大多数数据来自没有专门旨在揭示生物多样性分配的研究时,需要计划的调查设计。这种数据代表生物多样性的真实地理模式的能力可能取决于分类学家界的能力是自我激励的。

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