Stabilising sparse-data trends in the National Plant Monitoring Scheme: a scalable Bayesian model for plant abundance

Pescott, Oliver L.; Boyd, Robin J.

Stabilising sparse-data trends in the National Plant Monitoring Scheme: a scalable Bayesian model for plant abundance

Pescott, Oliver L. ORCID: https://orcid.org/0000-0002-0685-8046; Boyd, Robin J. ORCID: https://orcid.org/0000-0002-7973-9865. 2025 Stabilising sparse-data trends in the National Plant Monitoring Scheme: a scalable Bayesian model for plant abundance. Wallingford, UK Centre for Ecology & Hydrology, 15pp.

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Official URL: http://dx.doi.org/10.13140/RG.2.2.36345.38248

Abstract/Summary

The UK National Plant Monitoring Scheme produces around 600 annual species within-habitat trends that combine information on occupancy and positive cover. These trends underlie developing government indicators. We give a full specification of the Bayesian model and priors, and document changes introduced in the 2025 run (covering 2015-2024) relative to the 2024 run (2015-2023) to stabilise trends for sparsely recorded species. The principal change replaces first-order random-walk temporal priors with stationary autoregressive (AR(1)) priors; we also tighten several detection and cover priors. Future work will address non-response bias in NPMS survey returns.

Item Type:

Publication - Report (Technical Report)

Digital Object Identifier (DOI):

10.13140/RG.2.2.36345.38248

UKCEH and CEH Sections/Science Areas:

Biodiversity and Land Use (2025-)

Funders/Sponsors:

NERC, UKCEH, JNCC

Additional Information:

Open Access - full text available via Official URL link.

NORA Subject Terms:

Ecology and Environment
Botany
Data and Information