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Informing biodiversity monitoring with integrated distribution models 2026

Abstract

Model-based data integration offers the opportunity to analyse structured and unstructured monitoring data in a unified analytical framework.

We investigate whether adding different amounts of structured presence/ absence data to a large presence-only dataset produces improved estimates of model parameters. We use data collected through standardised transect walks and opportunistic records of bumblebee species occurrence to answer this question. Model estimates might be improved either through increased precision or by reduction of the biases inherent in opportunistic data.

Overall, we have shown that the integrated models provide an advantage over modelling the unstructured presence-only data alone. The magnitude of the benefit provided by the integrated model depends on the amount of information shared between the dataset and whether the signals provided by the two data sources are complementary or contrasting.

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Resource type Publication

Topic category Environment

Reference date 2026·05·01

Citation
Mancini, F., Pocock, M.J.O., Comont, R., Carvell, C. & Isaac, N.J.B. 2026. Informing biodiversity monitoring with integrated distribution models. JNCC Report 826. JNCC, Peterborough, ISSN 0963-8091.

Lineage
This work was supported by the Terrestrial Surveillance Development and Analysis (TSDA) Partnership, comprised of the UK Centre for Ecology & Hydrology, British Trust for Ornithology, and the Joint Nature Conservation Committee.

Responsible organisation
Communications, JNCC publisher

Limitations on public access No limitations

Use constraints Available under the Open Government Licence 3.0

Metadata date 2026·05·27

Metadata point of contact
Communications, JNCC

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