Herrera Daniel J, Schalk Christopher M, Jensen Alex J, Goldstein Benjamin R, Rooney Brigit R, Kays Roland, McShea William J, Cove Michael V
North Carolina Museum of Natural Sciences Raleigh North Carolina USA.
USDA Forest Service, Southern Research Station Nacogdoches Texas USA.
Ecol Evol. 2025 Jul 20;15(7):e71805. doi: 10.1002/ece3.71805. eCollection 2025 Jul.
Crowd-sourced biodiversity data, such as those housed in the iNaturalist platform, are increasingly used to monitor species distributions. Such data represent unstructured biodiversity surveys that are generally comprised of incidental observations and do not report variation in sampling effort. These discrepancies may yield data that is incongruent with data from structured surveys. To assess whether mammalian iNaturalist data are reflective of data from traditional structured surveys, we calculated and compared measures of mammalian species richness and species pool similarity using data from unstructured surveys (i.e., iNaturalist) and data from structured camera trap surveys and bat acoustic surveys. We found that data from structured and unstructured surveys generally document similar mammalian species richness, but the two survey types document different species pools. Human population density and proxies for species pool breadth were most strongly associated with discrepancies in datasets, with data being most similar in areas of high human population density and lower species richness. Our analyses revealed that dataset similarity varied across geography and community metric for most taxa, but that structured and unstructured surveys produced consistently unreconcilable datasets for bats. These findings suggest that unstructured datasets like iNaturalist may offer reliable data for some taxa and geographies, but that these data are not universally applicable to all research scenarios.
众包生物多样性数据，例如iNaturalist平台所收录的数据，正越来越多地用于监测物种分布。这类数据代表了非结构化的生物多样性调查，通常由偶然观察组成，且未报告抽样力度的差异。这些差异可能产生与结构化调查数据不一致的数据。为了评估iNaturalist哺乳动物数据是否反映了传统结构化调查的数据，我们使用非结构化调查（即iNaturalist）数据以及结构化相机陷阱调查和蝙蝠声学调查数据，计算并比较了哺乳动物物种丰富度和物种库相似性的指标。我们发现，结构化和非结构化调查的数据通常记录了相似的哺乳动物物种丰富度，但这两种调查类型记录的物种库不同。人口密度和物种库广度的代理指标与数据集中的差异关联最为紧密，在人口密度高且物种丰富度较低的地区，数据最为相似。我们的分析表明，对于大多数分类群而言，数据集相似性因地理区域和群落指标而异，但结构化和非结构化调查针对蝙蝠产生的数据始终无法协调一致。这些发现表明，像iNaturalist这样的非结构化数据集可能为某些分类群和地理区域提供可靠数据，但这些数据并非普遍适用于所有研究场景。
