Appendix E. Predicted probabilities of use by migrant and resident elk as a function of herbaceous forage biomass at two levels within the home-range scale.

Predicted probabilities of use by migrant and resident elk as a function of herbaceous forage biomass at two levels within the home-range scale

Appendix A. Modeling peak of growing season availability of forage-biomass components for elk.

Modeling peak of growing season availability of forage-biomass components for elk

Appendix F. Linear mixed-effects time-series models for forage (herbaceous and shrub) biomass exposure for migrant and resident elk GPS locations, 2002–2004.

Linear mixed-effects time-series models for forage (herbaceous and shrub) biomass exposure for migrant and resident elk GPS locations, 2002–2004

Diagram of the modeled predator-prey dynamics.

<p>Schematic diagram showing the modeled predator-prey interactions of Banff elk (E), Bow Valley elk (N) and Bow Valley wolves (P) for Models 1, 2, 3, 4 and 5. Arrows with solid lines represent interactions present in all years in all models. The Banff elk grow logistically with growth rate, g, and carrying capacity, K. The Bow Valley elk grow exponentially with rate, r, and encounter or interact with wolves at rate, d or d₂. Bow Valley wolves convert some proportion of elk encountered into new wolves with conversion efficiency, c, and have mortality rate, x. The dashed arrow (— —) represents the Banff elk relocation parameter (s) that occurred during the years 1998–2001 in all models. The dashed and double dotted arrow (– ·· –) represents the density-dependent dispersal parameter (m) for Models 2 and 4, the dashed and single dotted arrow (– · –) represents the anti-predator movement parameter (f) for Models 3 and 4, and the dotted arrow (▪▪) represents the short-term, source-sink wolf predation parameter (d₁) for Model 5.</p

Appendix B. Modeling forage maturation using NDVI and ground maturation models.

Modeling forage maturation using NDVI and ground maturation models

Appendix C. Estimating growing-season parameters for phenology modeling.

Estimating growing-season parameters for phenology modeling

Appendix D. Individual MODIS-interval quality–quantity regression equations.

Individual MODIS-interval quality–quantity regression equations

Model selection results for Models 1, 2, 3, 4 and 5 fit to the time-series data of Banff elk, Bow Valley elk and Bow Valley wolves for winters of 1985/1986–2010/2011.

a<p>RSS is the sum of the squared residuals from the model prediction with the median chain value of 100,000 MCMC samples.</p>b<p>AICc is Akaike's information criterion corrected for a small sample computed based upon the RSS.</p>c<p>ΔAICc is the difference between the model with the lowest AICc and a particular model.</p>d<p><i>w_i</i> is the relative model likelihood.</p

Parameter estimates and 95% credibility intervals (CIs) for the Banff elk, Bow Valley elk and Bow Valley wolves from winters of 1985/1986–2010/2011 for Models 1, 2, 3, 4 and 5.

<p>Parameter estimates and 95% credibility intervals (CIs) for the Banff elk, Bow Valley elk and Bow Valley wolves from winters of 1985/1986–2010/2011 for Models 1, 2, 3, 4 and 5.</p

Model 1 fit for all populations.

<p>Model 1 fit for the Banff elk population (a), Bow Valley elk population (b) and Bow Valley wolf population (c) from winter of 1985/1986–2010/2011. Population data shown with dots (•) and model fit shown with a solid line (—).</p