Not all who wander are lost: Trail bias in community science.

ABSTRACT: The exponential growth and interest in community science programs is producing staggering amounts of biodiversity data across broad temporal and spatial scales. Large community science datasets such as iNaturalist and eBird are allowing ecologists and conservation biologists to answer novel questions that were not possible before. However, the opportunistic nature of many of these enormous datasets leads to biases. Spatial bias is a common problem, where observations are biased towards points of access like roads and trails. iNaturalist-a popular biodiversity community science platform-exhibits strong spatial biases, but it is unclear how these biases affect the quality of biodiversity data collected. Thus, we tested whether fine-scale spatial bias due to sampling from trails affects taxon

SUBMITTER: Geurts EM 

PROVIDER: S-EPMC10289309 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature