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首页> 外文期刊>Conservation Biology >Limitations of biodiversity databases: Case study on seed-plant diversity in Tenerife, Canary Islands
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Limitations of biodiversity databases: Case study on seed-plant diversity in Tenerife, Canary Islands

机译：生物多样性数据库的局限性：加那利群岛特内里费岛种子植物多样性案例研究

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Databases on the distribution of species can be used to describe the geographic patterns of biodiversity. Nevertheless, they have limitations. We studied three of these limitations: (1) inadequacy of raw data to describe richness patterns due to sampling bias, (2) lack of survey effort assessment (and lack of exhaustiveness in compiling data about survey effort), and (3) lack of coverage of the geographic and environmental variations that affect the distribution of organisms. We used a biodiversity database (BIOTA-Canarias) to analyze richness data from a well-known group (seed plants) in an intensively surveyed area (Tenerife Island). Observed richness and survey effort were highly correlated. Species accumulation curves could not be used to determine survey effort because data digitalization was not exhaustive, so we identified well-sampled sites based on observed richness to sampling effort ratios. We also developed a predictive model based on the data from well-sampled sites and analyzed the origin of the geographic errors in the obtained extrapolation by means of a geographically constrained cross-validation. The spatial patterns of seed-plant species richness obtained from BIOTA-Canarias data were incomplete and biased. Therefore, some improvements are needed to use this database (and many others) in biodiversity studies. We propose a protocol that includes controls on data quality, improvements on data digitalization and survey design to improve data quality, and some alternative data analysis strategies that will provide a reliable picture of biodiversity patterns.
机译：物种分布数据库可用于描述生物多样性的地理模式。但是，它们有局限性。我们研究了其中三个局限性：（1）由于抽样偏差而导致的原始数据不足以描述丰富度模式;（2）缺乏调查工作量评估（并且在收集有关调查工作量的数据时没有详尽无遗），以及（3）缺乏覆盖影响生物体分布的地理和环境变化。我们使用了生物多样性数据库（BIOTA-Canarias）来分析密集调查区域（特内里费岛）中一个知名群体（种子植物）的丰富度数据。观察到的丰富度和调查工作高度相关。物种积累曲线不能用于确定调查工作量，因为数据数字化并不详尽，因此我们根据观察到的丰富度与工作量比率来确定采样良好的地点。我们还基于来自采样良好的站点的数据开发了一种预测模型，并通过地理约束的交叉验证对获得的推断中的地理误差的起源进行了分析。从BIOTA-Canarias数据获得的种子植物物种丰富度的空间格局不完整且有偏差。因此，需要进行一些改进才能在生物多样性研究中使用该数据库（以及许多其他数据库）。我们提出了一个协议，其中包括对数据质量的控制，对数据数字化和调查设计的改进以提高数据质量，以及一些替代性的数据分析策略，这些策略将提供可靠的生物多样性模式。

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