A1 Journal article (refereed)
Identifying sites with high biodiversity value using filtered species records from a biodiversity information facility (2024)

Duflot, R., & Vähätalo, A. V. (2024). Identifying sites with high biodiversity value using filtered species records from a biodiversity information facility. Diversity and Distributions, Early View. https://doi.org/10.1111/ddi.13864

JYU authors or editors

Duflot, Rémi
Vähätalo, Anssi

Publication details

All authors or editors: Duflot, Rémi; Vähätalo, Anssi V.

Journal or series: Diversity and Distributions

ISSN: 1366-9516

eISSN: 1472-4642

Publication year: 2024

Publication date: 22/05/2024

Volume: Early View

Publisher: Wiley-Blackwell

Publication country: United Kingdom

Publication language: English

DOI: https://doi.org/10.1111/ddi.13864

Publication open access: Openly available

Publication channel open access: Open Access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/95269

Abstract

Aim
Efficient mitigation of the biodiversity crisis requires targeted conservation actions in locations with high species richness, the presence of endangered species and unique species communities. However, prioritising sites remains challenging because of sparse knowledge on biodiversity, limiting the possibility of communicating efficiently with local decision makers. We examine easy-to-replicate, yet robust, methods to identify areas with high conservation values on large spatial scales using data filtering and complementary biodiversity indicators based on species records from a biodiversity information facility.

Location
Finland, Europe.

Methods
We illustrate the protocol by focusing on Lepidoptera in Finnish municipal districts. We mobilised over 3 million species records on 878 native Lepidoptera (2001–2020) from the Finnish Biodiversity Information Facility. We estimated the richness of overall and endangered species using species accumulation curves, as well as the uniqueness of species communities, using measures of local contribution to beta diversity (LCBD). After testing for multiple thresholds and their effect on indicator accuracy, 97 districts with >5000 records were included in the analyses.

Results
Estimated overall species richness was highest on the southern coast and significantly decreased in the North, following a known pattern with Lepidoptera in Finland. Species richness was not the highest in the districts with the greatest number of records and the ranking differed from the raw data, demonstrating the importance of correcting for sampling intensity. The estimated number of endangered species correlated with overall species richness, except in northernmost districts, where the proportion of endangered species was exceptionally high. High LCBD replacement (i.e. unique species communities) was concentrated in the Southwest (hemi-boreal) and North (northern boreal) of the country.

Main Conclusions
We provided an example and interpretations of how scalable biodiversity indicators based on accumulation curves and LCBD analyses, and careful data filtering (thresholds) can be used to identify sites with conservation priorities from multi-sourced species records.

Keywords: biodiversity; Lepidoptera; prioritisation; citizen science; conservation; endangered species

Free keywords: biodiversity; butterfly; citizen science; conservation planning; Lepidoptera; prioritisation; threatened species

Fields of science: