Spatial distribution of biodiversity citizen science in a natural area depends on area accessibility and differs from other recreational area use.

Published online
25 Oct 2022
Content type
Journal article
Journal title
Ecological Solutions and Evidence

Mandeville, C. P. & Nilsen, E. B. & Finstad, A. G.
Contact email(s)

Publication language
Norway & Nordic Countries


Opportunistic citizen science produces large amounts of primary biodiversity data but is underutilized in the conservation and management of protected areas despite these areas' status as citizen science hotspots. Application of these data may be limited by the challenge of understanding sampling patterns associated with opportunistic data at a scale relevant to local area management. An improved understanding of citizen science activity patterns within protected areas could strengthen both data analysis and the local promotion and guidance of citizen science activity. We investigated local-scale patterns of citizen science activity, using a case study approach to examine citizen science activity in a recreationally popular natural area that serves as a regional citizen science hotspot. We modelled the relationship between local citizen science activity and 10 spatial covariates broadly related to ease of access and natural interest, factors which have been shown to drive citizen science activity at regional scales. We further compared the distribution of citizen science activity with that of professional data collection and recreational visitor activity in the study area. We found that citizen science data largely complement rather than replicate openly available professional data. Citizen science participation was primarily driven by ease of access, especially the presence of trails. However, citizen science use of the trail network differed from other types of recreational trail use, including a weaker preference for well-established trails and a stronger association with developed areas. This improved understanding of patterns in citizen science participation may be used to better account for spatial biases in citizen science data and to manage natural areas in a way that supports and guides future citizen science activity.

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