Occupancy versus colonization–extinction models for projecting population trends at different spatial scales
Nordén, Jenni; Harrison, Philip J.; Mair, Louise; Siitonen, Juha; Lundström, Anders; Kindvall, Oskar; Snäll, Tord
Peer reviewed, Journal article
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Date
2020Metadata
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- Scientific publications [1437]
Abstract
Understanding spatiotemporal population trends and their drivers is a key aim in
population ecology. We further need to be able to predict how the dynamics and
sizes of populations are affected in the long term by changing landscapes and climate.
However, predictions of future population trends are sensitive to a range of modeling
assumptions. Deadwood-dependent fungi are an excellent system for testing
the performance of different predictive models of sessile species as these species
have different rarity and spatial population dynamics, the populations are structured
at different spatial scales, and they utilize distinct substrates. We tested how the
projected large-scale occupancies of species with differing landscape-scale occupancies
are affected over the coming century by different modeling assumptions.
We compared projections based on occupancy models against colonization–extinction
models, conducting the modeling at alternative spatial scales and using fine- or
coarse-resolution deadwood data. We also tested effects of key explanatory variables
on species occurrence and colonization–extinction dynamics. The hierarchical
Bayesian models applied were fitted to an extensive repeated survey of deadwood
and fungi at 174 patches. We projected higher occurrence probabilities and more
positive trends using the occupancy models compared to the colonization–extinction
models, with greater difference for the species with lower occupancy, colonization
rate, and colonization:extinction ratio than for the species with higher estimates of
these statistics. The magnitude of future increase in occupancy depended strongly
on the spatial modeling scale and resource resolution. We encourage using colonization–
extinction models over occupancy models, modeling the process at the finest
resource-unit resolution that is utilizable by the species, and conducting projections
for the same spatial scale and resource resolution at which the model fitting is conducted.
Further, the models applied should include key variables driving the metapopulation
dynamics, such as the availability of suitable resource units, habitat quality,
and spatial connectivity.