Spatially varying population indices

Large scale monitoring is fundamental for reliably tracking the fate of animal populations under changing environments and land-use practices. A common application of large scale population monitoring data is to produce indices of temporal change in species abundances, which are used in environmental policy assessments of species and biodiversity statuses. For index estimation, spatio-temporal models can be used to take advantage of the spatial component of large scale data in order to better capture and understand spatial variation in population change. This paper presents a generalized approach to estimating indices of relative population change across different spatial and temporal scales from fits of spatio-temporal models to population monitoring data. Using flexible specifications of baselines for indices, the approach can be used for a range of different comparisons of abundance across space and time, aggregated at small as well as large spatial and short as well as long term temporal scales. This is illustrated in an application to Swedish monitoring data of the common cuckoo, for which we estimate a range of national, county-wise and fine scale indices. An R-package, spotr, that aids computation of indices from fitted models accompanies the paper. • A general definition of model based spatio-temporal indices of population abundance. • Covers flexible comparisons of abundance over space and time across multiple scales. • An illustration of different indices in a case study on bird data. • An R-package ‘spotr‘ for computing indices from fitted models.