Download Russell Energy-Protein model presentation

Protein/Energy Model: Applied to
cumulative effects assessment
Energy – Protein model
disturbance
displacement
Model structure
FOOD INTAKE
RUMEN
ENERGY
(MEI)
disturbance
displacement
NITROGEN
(MNI)
ALLOCATION
Why Protein?
• By ignoring protein, we assume the growth of the
fetus, the production of milk and the replenishment of
muscle tissue is entirely dictated by available energy.
NOT TRUE
• An integral part of the weaning strategy in caribou –
critical to buffer environmental change
• While energy may be the key nutrient in winter, protein
is the key nutrient in summer
• “The resilience of Rangifer populations to respond to variable
patterns of food supply and metabolic demand may be related
to their ability to alter the timing and allocation of body
protein to reproduction.”
– Barboza 2008
DECISION TREE FOR CARIBOU WEANING STRATEGIES
Date
Above
Threshold
Below
Threshold
Weaning
Class
Reproductive
Impact
BIRTH
Calf Weight
gain
Calf Weight
gain
Cow Protein
gain
Cow Protein
gain
Early
September
Cow fat
weight
Cow fat
gain
Early
October
Calf fat
weight
Calf fat
weight
Late June
Mid July
Post-natal
weaner
Summer
weaner
Early
weaner
Calf dies
High probability of pregnancy
Calf dies
High probability of pregnancy
Lower overwinter calf survival
Later age of 1st reproduction
Higher overwinter cow survival
Increased probability of pregnancy
Extended
lactator
Lower probability of pregnancy
Higher overwinter calf survival
Normal
weaner
“Normal” probability of pregnancy
“Normal” overwinter calf survival
Linking energy-protein model with a population model
Scenarios (Daily Resolution)
Snow
Depth
Climate
Energy Protein Model
Climate database
Insects
Veg
Development
Birth rate
Activity
Physiological Predictions
Age first
reproduction
Impacts on
Calf survival
annually
POPULATION MODEL
Impacts on
Cow survival
Model applications
• Porcupine
– 1002 development
– Climate change
• George River
– Vehicle for data integration
• Bathurst
– Cumulative effects pilot project
• Central Arctic
– Prudhoe Bay oil development
• North Baffin
– Baffinland’s Mary River project
• Qamanirjuaq
– AREVA’s Kiggavik project
Residence time
(days)
Kiggavik assessment approach
5
4
3
2
1
0
• 100 cows/scenario
• Weaning status
• Fall body weights
Energy Protein Model
pregnancy
calf mortality
Population model
projected to 2050
Climate
database
(average)
Harvest
adjustment
needed to
offset
development
effects
Jay assessment components
EERX
ENERGY COST = EERX - EENRX
EENRX
Kiggavik assessment components
EIC
PIC
EIRX
PIRX
EERX
PERX
EEC
PEC
EINRX
PINRX
EENRX
PENRX
ENERGY BALANCE (EB) = EI-EE
ENERGY “COST” for RX caribou = EBC - EBRX
ENERGY “COST” for NRX caribou = EBC - EBNRX
PROTEIN BALANCE (PB) = PI-PE
PROTEIN “COST” for RX caribou = PBC - PBRX
PROTEIN “COST” for NRX caribou = PBC - PBNRX
Probability of Pregnancy
RESILIENCE the steeper the line;
the less the resilience
1
0.9
Probability of Pregnancy
0.8
0.7
PRODUCTIVITY
0.6
0.5
The lower the RBW associated with
50% p of pregnancy, the more
productive
0.4
0.3
0.2
0.1
0
0.4
0.5
0.6
0.7
RELATIVE Body Weight
0.8
0.9
1
Probability of pregnancy among arctic caribou herds in
relation to Relative Body Weight
1.2
Probability of Pregnancy
1
0.8
0.6
GEORGE
QAMANIRJUAQ
TAIMYR
0.4
0.2
0
0.4
0.5
0.6
0.7
Relative Body Weight
0.8
0.9
1
Probability of pregnancy among arctic caribou herds in
relation to Relative Body Weight
1.2
Probability of Pregnancy
1
0.8
GEORGE
0.6
QAMINURJUAQ
TAIMYR
BEV/BATHURST
0.4
PEARY
0.2
0
0.4
0.5
0.6
0.7
Relative Body Weight
0.8
0.9
1
Probability of pregnancy among arctic caribou herds in
relation to Relative Body Weight
1.2
Probability of Pregnancy
1
0.8
GEORGE
QAMINURJUAQ
0.6
TAIMYR
BEV/BATHURST
PEARY
0.4
CENTRAL ARCTIC
PORCUPINE
0.2
0
0.3
0.4
0.5
0.6
0.7
Relative Body Weight
0.8
0.9
1
Major advantages of E-P approach
linked to a population model
• Accounts for protein dynamics
• Flexible in designing scenarios – ask the “what-if”
questions
• Multi-scale: integrates from climate to population
– thus can develop scenarios that effect any scale
(climate, habitat, behaviour, demography)
• Incorporates age structure – important when
populations cycle
• Can model up to 1000 animals at once through a
scenario – i.e. can capture the population
variability and identify vulnerable cohorts