Characterizing spatio-temporal variation in survival and recruitment with integrated population models
Authored by Robert J Cooper, Richard B Chandler, Jeff Hepinstall-Cymerman, Samuel Merker, Heather Abernathy-Conners
Date Published: 2018
DOI: 10.1642/auk-17-181.1
Sponsors:
United States National Science Foundation (NSF)
Platforms:
R
Model Documentation:
Other Narrative
Pseudocode
Model Code URLs:
Model code not found
Abstract
Efforts to understand population dynamics and identify high-quality
habitat require information about spatial variation in demographic
parameters. However, estimating demographic parameters typically
requires labor-intensive capture-recapture methods that are difficult to
implement over large spatial extents. Spatially explicit integrated
population models (IPMs) provide a solution by accommodating spatial
capture-recapture (SCR) data collected at a small number of sites with
survey data that may be collected over a much larger extent. We extended
the spatial IPM framework to include a spatio-temporal point process
model for recruitment, and we applied the model to 4 yr of SCR and
distance-sampling data on Canada Warblers (Cardellina canadensis) near
the southern extent of the species' breeding range in North Carolina,
USA, where climate change is predicted to cause population declines and
distributional shifts toward higher elevations. To characterize spatial
variation in demographic parameters over the climate gradient in our
study area, we modeled density, survival, and per capita recruitment as
functions of elevation. We used a male-only model because males
comprised >90\% of our point-count detections. Apparent survival was low
but increased with elevation, from 0.040 (95\% credible interval [Cl]:
0.0032-0.12) at 900 m to 0.29 (95\% CI: 0.16-0.42) at 1,500 m.
Recruitment was not strongly associated with elevation, yet density
varied greatly, from <0.03 males ha -1 below 1,000 m to >0.2 males ha -1
above 1,400 m. Point estimates of population growth rate were <1 at all
elevations, but 95\% Cls included 1. Additional research is needed to
assess the possibility of a long-term decline and to examine the effects
of abiotic variables and biotic interactions on the demographic
parameters influencing the species' distribution. The modeling framework
developed here provides a platform for addressing these issues and
advancing knowledge about spatial demography and population dynamics.
Tags
individual-based models
Demography
Climate-change
Species distributions
Habitat
selection
Spatial scales
Range shifts
Breeding bird survey
Cardellina canadensis
Distance sampling
Elevation
gradients
Spatio-temporal point
process
Capture-recapture models
Migratory bird
Estimating abundance
Projection models
Data augmentation
Dynamics models