The availability of online biodiversity data has increased in recent decades, aiding our understanding of diversity patterns and species richness–environment relationships across temporal and spatial scales. However, even the most exhaustive databases are prone to sampling biases, which create knowledge gaps in species distributions and increase uncertainty in model predictions. Regarding marine environments, intertidal zones are globally distributed and considered early warning systems for climate change impacts and species' range shifts. Owing to their relative accessibility, intertidal records should – supposedly – be less incomplete and biased compared to open-ocean and deep-sea areas. Yet, the extent and coverage of intertidal records available in global biodiversity databases remains unknown. In this study, we used a high-resolution worldwide tidal flat map to identify intertidal records of 11 563 benthic species from the OBIS (Ocean Biodiversity Information System) portal. Following a thorough data-cleaning process, we evaluated geographic patterns in observed species richness, site accessibility, sampling effort, and inventory completeness across latitudes. We demonstrate that observed species richness has mid-latitudinal peaks while the tropics accumulate species with missing records, similar to patterns described for the entire marine realm. These patterns correlate with disproportionate mid-latitude sampling efforts and poor tropical sampling coverage. Sixty-five percent of the mapped intertidal sites are located within 3 hours of a city, but sampling records remain almost absent along African Atlantic, South American Pacific, and Indo-Pacific coasts. Thus, even for the accessible and well-studied intertidal shorelines, database records are not free from geographical biases and their associated implications for biodiversity estimates. Our results highlight the need for a better data-sharing culture, and we hope to encourage initiatives promoting more and better-distributed research efforts on intertidal biodiversity, which could improve global scale detection and prediction of climate change impacts at regional and global scales.

中文翻译：

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浅水区覆盖度：生物多样性数据库记录中潮间带物种清单的不完整


近几十年来，在线生物多样性数据的可用性有所增加，有助于我们了解时间和空间尺度上的多样性模式和物种丰富度-环境关系。然而，即使是最详尽的数据库也容易出现抽样偏差，这会在物种分布中造成知识差距并增加模型预测的不确定性。在海洋环境方面，潮间带分布于全球，被认为是气候变化影响和物种范围变化的早期预警系统。由于潮间带记录相对可及，与公海和深海区域相比，潮间带记录应该不那么不完整和有偏见。然而，全球生物多样性数据库中可用的潮间带记录的范围和覆盖范围仍然未知。在这项研究中，我们使用高分辨率的全球潮汐平面图来识别来自 OBIS（海洋生物多样性信息系统）门户的 11 563 种底栖物种的潮间带记录。在彻底的数据清理过程之后，我们评估了不同纬度的观察到物种丰富度、地点可达性、采样工作和库存完整性的地理模式。我们证明，观察到的物种丰富度具有中纬度峰值，而热带地区积累了缺失记录的物种，类似于整个海洋领域描述的模式。这些模式与不成比例的中纬度采样工作和较差的热带采样覆盖率相关。65% 的潮间带地图位于城市 3 小时以内，但非洲大西洋、南美太平洋和印太沿岸几乎没有采样记录。 因此，即使对于可到达且经过充分研究的潮间带海岸线，数据库记录也并非没有地理偏见及其对生物多样性估计的相关影响。我们的结果突出了对更好的数据共享文化的需求，我们希望鼓励倡议促进更多和更好地分布的潮间带生物多样性研究工作，这可以改善全球尺度对区域和全球尺度气候变化影响的检测和预测。