Site selection algorithms for optimal ecological monitoring design
Comprehensive monitoring of biodiversity to direct conservation action is foundational to addressing the ongoing biodiversity crisis. As integrative monitoring programs increasingly come online in response to multilateral biodiversity agreements, establishing best practices for optimal design is critical. Appropriately selecting monitoring locations is fundamental for producing robust biodiversity data. Despite extensive development of algorithms to systematically select sites, practical discussions of which algorithm is optimal for different monitoring settings is largely absent from the literature. Here, we benchmark the performance of four common selection algorithms, outline the characteristics of the suite of algorithms suitable for ecological monitoring design, and offer recommendations for their best use under different constraints on network design. While all algorithms outperformed simple random samples, performance differences were negligible between algorithms. We recommend instead that practitioners choose algorithms based on feature availability, which varies greatly between algorithms.
Authors
- Kari Norman (ORCID: https://orcid.org/0000-0002-2029-2325)
- Timothée Poisot (ORCID: https://orcid.org/0000-0002-0735-5184)
Institutions
- Rocky Mountain Research Station (US)
- Rocky Mountain Research (United States) (US)
- Université de Montréal (CA)
Publication Details
- Journal
- Ecological Indicators
- Published
- 2025-08-29
- DOI
- https://doi.org/10.1016/j.ecolind.2025.114104
- Primary Topic
- Soil Geostatistics and Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00