Small scale population trend assessment from large scale monitoring data

2026-06-16

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Jonas Knape *

Debora Arlt

DOI：10.1016/j.biocon.2026.111962

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Monitoring is an important prerequisite for biodiversity conservation, typically conducted at national scales while conservation actions often are implemented at more local scales. We ask to what extent large scale monitoring data are useful for estimating change at smaller local scales where status assessments are needed, but accurate data lacking. We compare three main modelling strategies, a global strategy where trends are assumed to be the same across the large-scale area, a local strategy estimating trends using data only from the small area, and a spatial modelling strategy where trends are allowed to vary more flexibly across space. Using national bird monitoring data for 58 species, we show that the spatial strategy is better at predicting population change than both local and global strategies for most species. The improvement is of a similar magnitude as the improvement of the global and local strategies over a static model assuming no temporal trend. Compared to the local strategy, estimates of change using the spatial strategy are slightly lower in magnitude and with a median reduction in standard errors of around 25%. The local strategy does not predict better than the global strategy for half of the species, but has clearly better performance for a handful of species. Spatial modelling strategies lead to clear but variable improvements in local species status assessments from large-scale monitoring data, increasing the number of species and areas for which accurate local assessments can be made, and aiding the evidence base for local conservation efforts.

Small scale population trend assessment from large scale monitoring data

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