Data from: Long-term demographic surveys reveal a consistent relationship between average occupancy and abundance within local populations of a butterfly metapopulation

Species distribution models are the tool of choice for large-scale
population monitoring, environmental association studies, and predictions
of range shifts under future environmental conditions. Available data and
familiarity of the tools rather than the underlying population dynamics
often dictate the choice of specific method — especially for the case of
presence–absence data. Yet, for predictive purposes, the relationship
between occupancy and abundance embodied in the models should reflect the
actual population dynamics of the modelled species. To understand the
relationship of occupancy and abundance in a heterogeneous landscape at
the scale of local populations, we built a spatio-temporal regression
model of populations of the Glanville fritillary butterfly (Melitaea
cinxia) in a Baltic Sea archipelago. Our data comprised nineteen years of
habitat surveys and snapshot data of land use in the region. We used
variance partitioning to quantify relative contributions of land use,
habitat quality, and metapopulation covariates. The model revealed a
consistent and positive, but noisy relationship between average occupancy
and mean abundance in local populations. Patterns of abundance were highly
variable across years, with large uncorrelated random variation and strong
local population stochasticity. In contrast, the spatio-temporal random
effect, habitat quality, population connectivity, and patch size explained
variation in occupancy, vindicating metapopulation theory as the basis for
modelling occupancy patterns in fragmented landscapes. Previous abundance
was an important predictor in the occupancy model, which points to a
spillover of abundance into occupancy dynamics. While occupancy models can
successfully model large-scale population structure and average occupancy,
extinction probability estimates for local populations derived from
occupancy-only models are overconfident, as extinction risk is dependent
on actual, not average, abundance.