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Scaling up spruce budworm disturbance; implications
for long term forest protection strategies
Gui l laume Sa inte -Marie ( U Q AM – Q c , C a n a d a ) , Danie l D. Kneeshaw ( U Q AM ) ,
David A. MacLean ( U N B – N B , C a n a d a ) , Br ian R. Sturtevant ( U S F S – W I , U S A )
The spruce budworm (SBW)
• Defoliate primarily Abies balsamea >> Picea spp.
• 3 severe outbreaks in the last century 1910-1940-1970, and 2010
Context - the role of natural ennemies
• Hardwoods host a larger and more diverse community of parasitoids than softwoods
Context - the role of natural ennemies
• Hardwoods host a larger and more diverse community of parasitoids than softwoods
• Hardwood content would reduce susceptibility to SBW
Context - the role of natural ennemies
• Hardwoods host a larger and more diverse community of parasitoids than softwoods
• Hardwood content would reduce susceptibility to SBW
• Hypothesis already implemented operationnally, but little knowledge of the impact on timber supply
– Potential conflict with the spruce plantation approach?
Question addressed
Could the beneficial effect of hardwoods outpass that
of secondary/minor spruce hosts in terms of wood
losses reduction ?
Which preventive strategy is best ?
Question addressed
Could the beneficial effect of hardwoods outpass that
of secondary/minor spruce hosts in terms of wood
losses reduction ?
Which preventive strategy is best ?
Intro Models Hardwood protection
Forest management
Implications
Models description
Modeling approach – forest dynamics
• Forest dynamics simulator: LANDIS-II
(Schel ler et a l . 2007)
Intro Models Hardwood protection
Forest management
Implications
Modeling approach – forest dynamics
• Forest dynamics simulator: LANDIS-II
• Landscapes represented as grids of interacting cells
(Schel ler et a l . 2007)
Intro Models Hardwood protection
Forest management
Implications
Modeling approach – forest dynamics
• Forest dynamics simulator: LANDIS-II
• Landscapes represented as grids of interacting cells
• Cohorts of individual tree species interacting via life attributes (shade tolerance, longevity , dispersal,…)
(Schel ler et a l . 2007)
Intro Models Hardwood protection
Forest management
Implications
Modeling approach – forest dynamics
• Forest dynamics simulator: LANDIS-II
• Landscapes represented as grids of interacting cells
• Cohorts of individual tree species interacting via life attributes (shade tolerance, longevity , dispersal,…)
• SBW defoliation-related mortality based on : • susceptibi l ity (probabil ity of defoliation)
• vulnerabil ity (probabil ity of death fol lowing defol iation)
(Schel ler et a l . 2007)
Intro Models Hardwood protection
Forest management
Implications
Modeling approach – forest dynamics
• Forest dynamics simulator: LANDIS-II
• Landscapes represented as grids of interacting cells
• Cohorts of individual tree species interacting via life attributes (shade tolerance, longevity , dispersal,…)
• SBW defoliation-related mortality based on : • susceptibi l ity (probabil ity of defoliation)
• vulnerabil ity (probabil ity of death fol lowing defol iation)
(Schel ler et a l . 2007)
Intro Models Hardwood protection
Forest management
Implications
Forest dynamics simulation landbase –
Central Québec, Canada
- 3600 km² area
- 33000 active cells
- 10 ha resolution
- Spruce: 32%
- Balsam fir: 16%
- Hardwoods: 45%
Intro Models Hardwood protection
Forest management
Implications
The hardwood protection effect on
spruce-fir defoliation
Hardwood protection effect modeling
• Two hypothesis on the nature of parasitoids action:
Intro Models Hardwood protection
Forest management
Implications
Hardwood protection effect modeling
• Two hypothesis on the nature of parasitoids action:
1. Continuous – higher parasitoids levels through whole outbreak duration
0 %
12.5%
37.5%
62.5%
87.5%
% hardwood :
Defo
liation (
%)
0
25
50
75
100
Year
Continuous
Intro Models Hardwood protection
Forest management
Implications
Hardwood protection effect modeling
• Two hypothesis on the nature of parasitoids action:
1. Continuous – higher parasitoids levels through whole outbreak duration
2. Partial – higher parasitoids levels only during outbreak rise or decline phases
Rise
0
25
50
75
100
0
25
50
75
100
De
folia
tio
n (
%)
Decline
Year Year
0 %
12.5%
37.5%
62.5%
87.5%
% hardwood :
Defo
liation (
%)
0
25
50
75
100
Year
Continuous
Intro Models Hardwood protection
Forest management
Implications
Hardwood protection effect modeling:
Landscape-level
• Hardwood protection in LANDIS-II:
Intro Models Hardwood protection
Forest management
Implications
Hardwood protection effect modeling:
Landscape-level
• Hardwood protection in LANDIS-II: – Surrounding hardwoods reduce host susceptibility level
– Considers stand and landscape hardwood content (1 km radius; Campbell et al. 2008 )
Intro Models Hardwood protection
Forest management
Implications
Hardwood protection effect modeling:
Landscape-level results
• Landis-II maximum hardwood protection effect: – 68 % of normal (no hardwood effect) mortality level.
Intro Models Hardwood protection
Forest management
Implications
Hardwood protection effect modeling:
Landscape-level results
• Landis-II maximum hardwood protection effect: – 68 % of normal (no hardwood effect) mortality level.
– Equivalent to average Rise & Decline hardwood effect scenarios (65-70%) at stand scale.
Rise
0
25
50
75
100
0
25
50
75
100
De
folia
tio
n (
%)
Decline
Year Year
Intro Models Hardwood protection
Forest management
Implications
Hardwood protection effect modeling:
Landscape-level results
• Landis-II maximum hardwood protection effect: – 68 % of normal (no hardwood effect) mortality level.
– Equivalent to average Rise & Decline hardwood effect scenarios (65-70%) at stand scale.
ForPro system (SBWDSS):
% hardwood vs. defoliation
(based on Su et al.(1999))
Rise
0
25
50
75
100
0
25
50
75
100
De
folia
tio
n (
%)
Decline
Year Year
Intro Models Hardwood protection
Forest management
Implications
Sainte-Marie et al.(in prep.))
Preventive forest management scenarios
LANDIS-II simulation scenarios
200-year simulations
• SBW outbreaks (30-year return interval , max. severity)
– With and without hardwood protection
• Forest management (70-year rotation) – Extensive management (clearcutting only)
– Intensive management (black spruce plantations)
Intro Models Hardwood protection
Forest management
Implications
Available biomass per management scenario Bi
omas
s (‘00
0 To
ns/h
a)
Softwoods
Hardwoods
Total
Simulation year
Intro Models Hardwood protection
Forest management
Implications
0 50 100 150 2000
1000
2000
3000
4000
5000
Spruce budworm (normal)
Available biomass per management scenario Bi
omas
s (‘00
0 To
ns/h
a)
Softwoods
Hardwoods
Total
Simulation year
0 50 100 150 2000
1000
2000
3000
4000
5000
spruce budworm (reduced)
Intro Models Hardwood protection
Forest management
Implications
0 50 100 150 2000
1000
2000
3000
4000
5000
Spruce budworm (normal)
0 50 100 150 2000
1000
2000
3000
4000
Extensive (70-yr rotation)
Available biomass per management scenario Bi
omas
s (‘00
0 To
ns/h
a)
Softwoods
Hardwoods
Total
Simulation year
0 50 100 150 2000
1000
2000
3000
4000
5000
spruce budworm (reduced)
Intro Models Hardwood protection
Forest management
Implications
0 50 100 150 2000
1000
2000
3000
4000
5000
Spruce budworm (normal)
0 50 100 150 2000
1000
2000
3000
4000
Extensive (70-yr rotation)
Available biomass per management scenario Bi
omas
s (‘00
0 To
ns/h
a)
Softwoods
Hardwoods
Total
Simulation year
0 50 100 150 2000
1000
2000
3000
4000
5000
spruce budworm (reduced)
Less silvicultural efforts than current
management
Intro Models Hardwood protection
Forest management
Implications
0 50 100 150 2000
1000
2000
3000
4000
5000
Spruce budworm (normal)
0 50 100 150 2000
1000
2000
3000
4000
Extensive (70-yr rotation)
0 50 100 150 2000
1000
2000
3000
4000
intensive (current)
Available biomass per management scenario Bi
omas
s (‘00
0 To
ns/h
a)
Softwoods
Hardwoods
Total
Simulation year
0 50 100 150 2000
1000
2000
3000
4000
5000
spruce budworm (reduced)
Plantation rate:
4% / 10 yrs
Intro Models Hardwood protection
Forest management
Implications
0 50 100 150 2000
1000
2000
3000
4000
5000
Spruce budworm (normal)
0 50 100 150 2000
1000
2000
3000
4000
Extensive (70-yr rotation)
0 50 100 150 2000
1000
2000
3000
4000
intensive (current)
0 50 100 150 2000
1000
2000
3000
4000
intensive (improved)
Available biomass per management scenario Bi
omas
s (‘00
0 To
ns/h
a)
Softwoods
Hardwoods
Total
Simulation year
0 50 100 150 2000
1000
2000
3000
4000
5000
spruce budworm (reduced)
Intro Models Hardwood protection
Forest management
Implications
7% / 10 yrs
0 50 100 150 2000
1000
2000
3000
4000
5000
Spruce budworm (normal)
0 50 100 150 2000
1000
2000
3000
4000
Extensive (70-yr rotation)
Available biomass per management scenario Bi
omas
s (‘00
0 To
ns/h
a)
Softwoods
Hardwoods
Total
Simulation year
0 50 100 150 2000
1000
2000
3000
4000
5000
spruce budworm (reduced)
0 50 100 150 2000
1000
2000
3000
4000
Extensive (normal SBW)
Intro Models Hardwood protection
Forest management
Implications
0 50 100 150 2000
1000
2000
3000
4000
5000
Spruce budworm (normal)
0 50 100 150 2000
1000
2000
3000
4000
Extensive (70-yr rotation)
Available biomass per management scenario Bi
omas
s (‘00
0 To
ns/h
a)
Softwoods
Hardwoods
Total
Simulation year
0 50 100 150 2000
1000
2000
3000
4000
5000
spruce budworm (reduced)
0 50 100 150 2000
1000
2000
3000
4000
Extensive (normal SBW)
Intro Models Hardwood protection
Forest management
Implications
0 50 100 150 2000
1000
2000
3000
4000
5000
Spruce budworm (normal)
Total SW:
20,800,000
21,900,000
Tons / ha
0 50 100 150 2000
1000
2000
3000
4000
Extensive (70-yr rotation)
Available biomass per management scenario Bi
omas
s (‘00
0 To
ns/h
a)
Softwoods
Hardwoods
Total
Simulation year
0 50 100 150 2000
1000
2000
3000
4000
5000
spruce budworm (reduced)
Total SW:
77,600,000
60,300,000
Tons / ha
0 50 100 150 2000
1000
2000
3000
4000
Extensive (normal SBW)
Intro Models Hardwood protection
Forest management
Implications
0 50 100 150 2000
1000
2000
3000
4000
5000
Spruce budworm (normal)
Results – total cumulative available softwood
Scenario
Cumulative
available softwood
(Tons/ha)
Spruce budworm only 77,600,000
Extensive management 21,900,000
Intensive management
(4%/10 years) 30,000,000
Intensive management
(7%/10 years) 34,800,000
Take home – is preventive management
effective in terms of softwood production?
• YES, more softwood production in the intensive management scenarios vs. simplest management
Intro Models Hardwood protection
Forest management
Implications
Take home – is preventive management
effective in terms of softwood production?
• YES, more softwood production in the intensive management scenarios vs. simplest management
• Defoliation-reducing effect of hardwoods insufficient – Management produces enough hardwood encroachment
without insisting on hardwoods preservation
Intro Models Hardwood protection
Forest management
Implications
Take home – is preventive management
effective in terms of softwood production?
• YES, more softwood production in the intensive management scenarios vs. simplest management
• Defoliation-reducing effect of hardwoods insufficient – Management produces enough hardwood encroachment
without insisting on hardwoods preservation
• Intensive management remains the best option…
Intro Models Hardwood protection
Forest management
Implications
THANKS!
• Eric Beaulieu ( for model calibration work)
• Brian Sturtevant, Brian Miranda ( for technical support & more!)
• Québec Nature & Technology Fund ( funding)
• Québec Chief Forester’s Office ( funding)
The effect of 20 years of preventive
silviculture on forest composition
- 1985-2004 in Eastern Québec
- Intensive silviculture:
- Plantations
- Precom. Thinning
Extensive management
Intensive management
Are
a (‘
00
0 h
a)
1985 stand types
Intro Models Hardwood protection
Forest management
Implications
