Mapping Nutritional Resources
in the
Blue Mountains of NE Oregon
A crucial step in
linking habitat to
population responses
Our Focus : Late Summer/Early Autumn
WHY?
General DDE – Animal Performance Relationships
Percent of maximum
120
Poor
Marginal
Good
Excellent
<2.4 (53% DDM)
2.4-2.7
2.7-2.9
>2.9 (64% DDM)
100
80
60
40
20
0
Digestible energy of diets (kcal/gram of food)
Calf growth
Yearling growth
Yearling preg
Adult fat
Adult preg
Breeding times
Winter survival
General DDE – Animal Performance Relationships
Percent of maximum
120
Poor
Marginal
Good
Excellent
<2.4 (53% DDM)
2.4-2.7
2.7-2.9
>2.9 (64% DDM)
100
80
60
40
20
0
Digestible energy of diets (kcal/gram of food)
Calf growth
Yearling growth
Yearling preg
Adult fat
Adult preg
Breeding times
Winter survival
Blue Mountains Nutrition Mapping
Macroplots:
n = 285 total
n = 205 w/elk
Developing Nutritional Resource Maps:
The Methodology
•Biomass Sampling (by species)
•Over-story Measurements
(canopy cover, tree density,
basal area etc.)
•Nutritional quality (DE, DP,
tannins) of vegetation by forage
class (annual grass/forb,
deciduous shrub, perennial
grass/fob, evergreen shrub,
forest ferns)
Developing Nutritional Resource Maps:
The Methodology
Tame, lactating females are
used as a measuring device
to quantify the nutritional
quality of habitats relative to
requirements of the animal.
•Diet Quality (energy, protein)
•Intake rates (g/min, g/day)
•Nutrient intakes rates
(DE/min etc)
•Activity budgets
•Selection indices
Digestible Energy Content of Elk Diets,
or DDE:
Our Key Variable for Nutritional Resource Mapping
 DE plays a key, usually dominant role in virtually all life processes
and it greatly affects how much food ruminants can eat each day…the
“multiplier effect”.
 There is considerable precedence…National Research Council
presents livestock nutritional requirements guidelines several ways,
including DE content of food.
 Our objective is to build high resolution maps that show levels of
DDE across landscapes, on a pixel by pixel basis.
Integrating Plant Succession, Disturbance,
and Elk Nutrition
Habitat predictor variables
Stand/site
characteristics
Animal response variables
Stand age
Understory
vegetation
characteristics
Animal foraging
outcomes
Canopy cover
Composition
Bite mass
BA, QMD, TPH, HT
Biomass
Season
DP, DE
Climate
Palatability
Soils
Bite rate
Performance
outcomes
Fat, Repro, Surv
DDP, DDE
Foraging time
RANGELANDS
•Ponderosa pine
•Western juniper woodland
•Mountain mahogany
•Low sage
•Rigid sage
•Bluebunch wheatgrass
•Sandberg bluegrass
•Idaho fescue
•WY big sage
•Salt desert shrub
•Bitterbrush
•Threetip sage
•Mtn big sage
•Great Basin Pinyon-Juniper Woodland ...
Source
Type
Rangelands
Output
Algorithms
Date
Current Months Precip
Previous Months Precip
=
Rangelands
DDE
Potential
Vegetation
Type
Continuous
DDE
DRY FORESTS
•Rocky Mountain Aspen
Forest and Woodland
•Northern Rocky Mountain
Dry-Mesic Montane Mixed
Conifer Forest
•Inter-Mountain Basins
Aspen-Mixed Conifer Forest
and Woodland
•Northern Rocky Mountain
Montane-Foothill Deciduous
Shrubland
•Inter-Mountain Basins
Montane Riparian Systems
•Middle Rocky Mountain
Montane Douglas-fir Forest
and Woodland
Source
Potential
Vegetation
Type
Type
Output
Algorithms
Rangelands
Date
Current Months Precip
Previous Months Precip
=
Rangelands
DDE
Dry Forest
Date
Current Months Precip
Previous Months Precip
=
Dry Forest
DDE
Continuous
DDE
WET FORESTS
•Northern Rocky Mountain Mesic
Montane Mixed Conifer Forest
•Rocky Mountain Subalpine DryMesic Spruce-Fir Forest and
Woodland
•Rocky Mountain Subalpine
Mesic-Wet Spruce-Fir Forest and
Woodland
•Rocky Mountain Montane
Riparian Systems
•Rocky Mountain
Subalpine/Upper Montane
Riparian Systems
Source
Potential
Vegetation
Type
Type
Output
Algorithms
Rangelands
Date
Current Months Precip
Previous Months Precip
=
Rangelands
DDE
Dry Forest
Date
Current Months Precip
Previous Months Precip
=
Dry Forest
DDE
Wet Forest
Date
Current Months Precip
Previous Months Precip
Canopy Cover
=
Wet Forest
DDE
Continuous
DDE
WET MEADOWS
AGRICULTURE LANDS
•No data with tame elk
•Consultation with local ag
agents
•What crops are
grown?
•What crops would be
irrigated?
•Tables from NRC
•Estimate means
EVI > 3500 →
Irrigated = 2.65 kcal/g
EVI ≤ 3500 → Non-Irrigated = 2.40 kcal/g
Source
Potential
Vegetation
Type
Type
Output
Algorithms
Rangelands
Date
Current Months Precip
Previous Months Precip
=
Rangelands
DDE
Dry Forest
Date
Current Months Precip
Previous Months Precip
=
Dry Forest
DDE
Wet Forest
Date
Current Months Precip
Previous Months Precip
Canopy Cover
=
Wet Forest
DDE
Existing
Vegetation
Type
Agriculture
Wetland
Inventory
Wet Meadows
=
Potential &
Existing Veg.
Type
Excluded Types
=
Irrigated Ag
Enhanced Vegetation Index
(Greenness)
=
DDE*
Non-Irrigated Ag
DDE*
Wet Meadow
DDE*
No DDE
* Constant value
Continuous
DDE
60
50
40
30
20
10
0
60
50
40
30
20
10
0
70
60
50
40
30
20
10
0
July 1 available nutrition vs September 1
July 1 available nutrition vs September 1
80
70
60
50
40
30
20
10
0
1-Jul
1-Sep
Habitat Management Implications
I.
Ecological context
a. Seasonal & soil depth/moisture greatly limit options for improving summer
nutrition in dryer PNV types.
b. Will get greatest summer nutritional payoff by operating in relatively
wet/high elevation forest zones.
Habitat Management
Implications
II.
Habitat treatments
a. Dense conifer
overstories (>70%)
eliminate good
forage, and nutrient
intake rates are very
low.
b. Reductions in
overstory are
needed, although
uneven-aged
management may
be substantially
superior to
clearcutting.
Habitat Management Implications
I.
II.
Other habitats, other seasons
a. Early spring may also be crucial for recovering elk in 3rd
trimester. By early April, wet meadows and rangelands
provide superior forage. Minimizing human impacts near
these may be key.
Cattle and wild herbivore effects.