Abstract

Ecological monitoring provides indispensable data for biodiversity conservation and sustainable resource management. However, the complexity and variability inherent in ecological monitoring data necessitate robust verification processes to ensure data integrity. This study employed Benford's Law, a statistical principle traditionally used in fields such as finance and health sciences, to evaluate the authenticity of ecological monitoring data related to the abundance of migratory bird species across various locations in South Korea. Benford's Law anticipates a specific logarithmic distribution of leading digits in naturally occurring numerical datasets. Our investigation involved two stages of analysis: a first-order analysis considering the leading digit and a second-order analysis examining the first two digits of bird population counts. While the first-order analysis displayed moderate conformity to Benford's Law that suggested overall data integrity, the second-order analysis revealed more pronounced deviations, indicating potential inconsistencies or inaccuracies in certain subsets of the data. Although our data did not perfectly align with Benford's Law, these deviations underscore the complex nature of ecological research, which is influenced by a multitude of environmental, methodological, and human factors.