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Data_Sheet_1_Citizen science and roadkill trends in the Korean herpetofauna: The importance of spatially biased and unstandardized data.CSV (83.93 kB)

Data_Sheet_1_Citizen science and roadkill trends in the Korean herpetofauna: The importance of spatially biased and unstandardized data.CSV

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posted on 2022-08-12, 05:04 authored by Yucheol Shin, Kyungmin Kim, Jordy Groffen, Donggul Woo, Euigeun Song, Amaël Borzée

Roadkills are a major threat to the wildlife in human-modified landscapes. Due to their ecology, relatively small size, and slow movement, amphibians and reptiles are particularly prone to roadkill. While standardized roadkill surveys provide valuable data for regional roadkill trends, such surveys are often resource-intensive and have limited geographic coverage. Herein, we analyzed a roadkill dataset of the Korean herpetofauna derived from the citizen science database iNaturalist and compared the overall roadkill trends detected in the iNaturalist data with standardized survey-based literature data. Our results show that the overall citizen science data provide a good picture of roadkill trends for the Korean herpetofauna in terms of recorded species. We detected both similarities and notable differences between the iNaturalist and literature data. The most notable differences between the two datasets were found in the number of recorded species, distribution across habitat types, and distribution across elevational ranges. Even with spatially biased sampling, the iNaturalist data had a considerably broader geographic coverage compared to standardized surveys. In addition, we related the presence of roadkills of amphibians and reptiles to the presence of agricultural lands, forests, and grassland. While the unstandardized nature of the citizen science data can be criticized, we argue that this feature also acts as an advantage for this type of data, as citizen science can better detect roadkills of rare species or seasonal events, such as mass migration of amphibians, and inform population trends and threats. Thus, our results highlight the importance of spatially biased and unstandardized citizen science data for roadkill detection. This study builds on previous studies demonstrating citizen science as a viable method of roadkill surveys.

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