Predicting Elk Nutritional Resources and
Habitat Use Across Large Landscapes:
the Westside Model
Topics:





Background of Westside elk modeling project
Development of elk nutrition model
Modeling methods for elk habitat use
Results of model selection and model validation
Example management applications and utility
Modeling Background
Why new elk models?

Earlier models still in use, but
many components unvalidated.

Data from many radiotelemetry studies now available
for use with new modeling
approaches.

More recent data collected on
elk nutritional resources for
modeling at landscape scales.
Project Objectives
1.
Build a nutrition model that predicts dietary
digestible energy for elk across all landscape conditions
during summer
2.
Build and evaluate a set of plausible, competing habitat
use models that predict the relative probability of elk
use at landscape extents
3.
Include nutrition model predictions as a covariate in
habitat use models
Project Objectives
4.
Include additional human disturbance and abiotic
covariates that potentially affect or account for the
probability of elk use of nutritional resources
5.
Use data from multiple study areas (diverse
environments & land ownerships) to construct, select,
and validate models
@Scott McCorquodale
The “Westside” elk models

Apply to summer range (June 1 – August 31)

Regional landscapes (>10,000 ha), multiple landowners,
integrated management

Female elk

Hunted populations

Management-focused, mechanistic models
Methods to model nutrition
Nooksack S.A.
Willapa Hills S.A.
Springfield S.A.
NUTRITION MODEL
Development of nutrition equations

Based on stand and overstory forest conditions

Separate equations for more mesic Pacific silver fir/mt.
hemlock vs. western hemlock potential natural vegetation
communities
Development of nutrition equations

Different equations for each of 3 study areas

Two final nutrition models



Forage biomass
Elk dietary digestible energy (DDE), predicted from biomass
Input variables: PNV zone, % canopy cover, hardwoods
Scaling up of field data to Westside landscapes

Mapped predicted
nutrition across Westside
region

Used readily available,
coarse-scale spatial data

Found excellent
agreement between
predicted DDE and elk
locations
Methods to Model Habitat Use
HABITAT USE
MODEL
Study areas & years:
7 Study Areas, 21 Years
Study area sizes:
˜ 13,400 to ˜ 98,000 ha
Average ˜ 57,000 ha
Covariate reduction
Nutrition
DDE (continuous)
DDE (categorical)
Accepted Biomass (AB)
Distance to:
High DDE
Mod DDE
Percent area in M to H
DDE
Quadratic, Cubic forms
Human
Disturbance
Density of & Distance
to:
Open Roads
Closed Road
High Traffic Roads
Low Traffic Roads
Public Use Roads
Administrative Use
Only
Motorized Use Trails
Quadratic, Cubic forms
Vegetation
Physical/
Other
Overstory CC
Slope (continuous)
Dominant CC
Slope (categorical)
Percent Area in:
Flat to Gentle Slope
Habitat Effectiveness of
Mod to Steep Slope
size/spacing of Cov & For
Very Steep Slope
Cover Quality
Aspect
Distance to:
Convexity
Forage
Curvature
Cover
Cover-Forage Edge
Soil Depth
Optimal Cover
Solar Radiation
Thermal Cover
Hiding Cover
Distance to Water
Cover-Forage Ratio
Land Ownership
Modeling methods
1.
Model the probability of elk use for each
model set and for combined models within
each study area
2.
Evaluate models using a model selection
approach
3.
Develop a regional model of elk use for
western OR and WA using a “meta-analysis”
approach
Model Selection Results
Best models

“Best of best”

Used top model from each model set

Evaluated 7 models within each of 5 study areas

Selected best model based on lowest summed rank
across all model training study areas
The best model included:

Dietary digestible
energy

Distance to open
roads

Distance to
cover/forage edge

Slope
Nutrition Model
•
% Canopy cover
Elk Habitat Use Model
•
DDE
• % Hardwoods
• Dist. to public roads
• Potential veg.
• % Slope
zone
• Dist. to edge
Dietary Digestible Energy (DDE)
Predicted Level of Elk Use
Model Validation Results
Summary

The best model was the top
performer in all 5 study areas

Marginal plots showed consistent
relationships between predicted use by
elk and each of the covariates in this
model

Validation with spatially independent
data sets showed a good fit for the
regional model across a wide spectrum
of conditions
Model Application
Elk Forage Analysis
Area (8,170 ha)
243 ha
Thinning Unit Analysis
Area (7,570 ha)
500 ha
Nutrition Summary
18
16
% Area in Good or Better Nutrition
14
Percent
12
10
Existing
Alt. 1
Alt. 2
8
6
4
2
0
Region
Elk Forage Areas
Thinning
% Change in Predicted Use from Baseline
55
49.8
40.4
40
% change
35.3
30.8
Opt1
Opt2
24.0
25
Opt3
15.2
12.4
12.4
9.5
10
-1.7
-5
Region
0.0
Elk Forage Area
0.0
Thin Units A
Analysis Area
Thin Units B
Management utility

Readily adaptable to land
management planning at
multiple scales across land
ownerships

Landscapes can be
characterized by nutritional
condition (e.g., poor, meeting
baseline needs)

Probability of elk use can be
estimated and mapped by
nutritional condition
Management utility

Human disturbance factors
can be managed to influence
elk use

Region 6 (FS) and OR-WA
(BLM) formally adopted as
“best available science”

User guidelines and technical
support available:
http://www.fs.fed.us/pnw/res
earch/elk/
Rachel Cook
Significance of work

Focus on mechanistic, management-focused models

Scaling up of nutrition to landscape levels

Modeled predictions of elk use directly link landscape
choices by elk to nutrition-based measures of population
health

Spatial inference

many years of data and elk locations from disparate data
sources
larger inference space than typical for elk
habitat models