Abstract
Interspecific interactions and movement are key factors that drive the
coexistence of metapopulations in heterogenous landscapes. Yet, it is
challenging to understand these factors because separating movement from
local population processes relied on capture-based data that are
difficult to collect. Recent development of spatially explicit dynamic
N-mixture models (SEDNMs) made it possible to draw inference on local
population growth and movement using count data of unmarked populations.
Here, we further developed SEDNMs to account for interspecific
interactions and both false positive and false negative observation
errors. Simulations showed that the models provide unbiased parameter
estimates regardless of the ecological system (competition,
predator-prey), observation process (binomial, Poisson), and sampling
situation. Case studies further demonstrated the capabilities of these
models in revealing important ecological processes including
competition, predator-prey interactions, movement patterns, and
differential habitat preferences. The flexible structures of these
models make them highly adaptive and relevant in population and
community ecology.