Document: ROB-3-51-11

Spatial patterns of population regulation and population viability in sage grouse (Centrocercus urophasianus spp.).

IRVINE, R.L.*, J.M.LAMONTAGNE, T.B.LOGAN, B.O.MA, C.M.ELKIN and E.E.CRONE

University of Calgary, Calgary, Alberta, Canada. ¹

Abstract:
Potential mechanisms driving population fluctuations can be explored by comparing predictions from mechanistic models with time series data. We investigated dynamical mechanisms in sage grouse populations, (Centrocercus urophasianus spp.), in Washington State (WA), Colorado (CO), and Alberta (AB), and assessed the viability of this declining species. Our objectives in were to: 1) examine the degree of spatial correlation among geographically separate populations, and 2) test the fit of mechanistic models to census counts over time. We used the methods of Dennis et al., 1991 to calculate population viability analyses (PVA's), and modified correlograms (Koenig, 1998) to assess patterns of spatial variance and covariance. We tested the fit of exponential, delayed-density-dependence, maternal effects and host-pathogen models using Akaike Information Criterion (AIC) and inferential trajectory fit using parameter estimates. AB populations exhibited consistently high spatial correlation over all distance categories, while CO showed no trend over increasing distances. WA populations were significantly negatively correlated at intermediate distances, while positively correlated at near and far distances. To explain sage grouse dynamics, no single model was preferred overall. Exponential and delayed-density-dependence models were proportionally favored more than models explicitly incorporating biological mechanisms. Inferential trajectory fits of models displayed the trends in the time series data, but not the fluctuations in sage grouse dynamics. Based on life history traits and environmental factors we hypothesized explanations for the spatial correlations. Alternately, the significant variation in correlation results could be caused by different dynamics operating in the separate populations.

Keywords: population viability analysis; sage grouse; inferential trajectory fit; model comparison; AIC; spatial correlation

This abstract is being presented at: 11:00 AM in session:
Oral Session #3: Avian Ecology.