Limits and Possibilities for Sustainable Development in Northern Birch Forests: AO Gautestad, FE...
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Transcript of Limits and Possibilities for Sustainable Development in Northern Birch Forests: AO Gautestad, FE...
Limits and Possibilities for Sustainable Development in Northern Birch Forests:
AO Gautestad, FE Wielgolaski*, B Solberg**, I Mysterud*
* Department of Biology, University of Oslo, Norway
** Agricultural University of Norway, Department of Forestry, Ås, Norway
A general landscape-scale model relating mountain birch forest dynamics to various anthropogenic
influences, herbivory, and climate change
Outline
• Introduction: What can a model do for the HIBECO project?
• General model structure: Exploring spatiotemporal birch forest dynamics under influence from forestry in a homogeneous environment
• Adding realism I: Age-structured forest dynamics at scale 1 Ha
• Adding realism II: Dynamics in a heterogeneous landscape
• Adding realism III: Climate change scenarios• Adding realism IV: Influences from herbivores –
grazing ungulates and leaf-eating insects
0
500000
1000000
1500000
2000000
2500000
3000000
3500000
4000000
4500000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
Topoclimatic models for the height gradient in the HIBECO model
8.0
10.0
12.0
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20.0
0 100 200 300 400 500 600 700 800 900 1000
Height above bottom of valley, H
3-M
on
th M
ax. T
emp
erat
ure
, T
T = 15 +2 / (H/ 20 + 1) - 0.55 * H / 100
T = 13.7 -ABS(H-75)/80 + (1000+15.2*H)/2200
Purpose of the model
• An instrument linking various aspects of the HIBECO project closer together– HIBECO is an interdiciplinary project– Proper modeling requires explicit qualitative and quantitative
descriptions of essential variables and parameters and their dynamic interactions
• Exploring complex interactions in space and time: Scenarios– Basic scientific value– Practical value for management and politics: sustainable use of
birch forest resources and maintenance of the northern birch forest ecosystem
Sustainable use of mountain birch: How can modeling make a contribution?
• Birch is a keystone species in many parts of the Northern terrestrial ecosystems
• Mountain birch forest ranges are expanding due to a warmer climate and changes in cultural use of the landscape
• Mountain birch may become an increasingly important resource in the future (forestry etc.)
• Expansion of the forest ranges also means a parallel contraction of the treeless landscapes (problems related to reindeer herding and grazing field availability).
• Models may be used to explore long term interactions and consequences (“landscape behaviour”) under various hypothetical management regimes in virtual landscapes
Part 1: General Model Structure
Exploring spatiotemporal birch forest dynamics and disturbances in a
homogeneous environment
Pattern from intrinsic processes in a birch / forestry model system
100 m12.8 km
Rules for local cell disturbances (logging events)
• Rule 1:– At each time increment
randomly choose 5% of the cells
– Reset all chosen cells dominated by old-growth stands to young stands (i.e., local logging event at 1 Ha scale)
• Rule 2:– At each time increment
randomly choose one of the arena cells with old-growth stands
– Perform logging in this cell, and all connected cells with old-growth stands (i.e., logging with no spatial scale constraints up to arena size)
Time step: 10 12 14 16 18
Rule 1:
Rule 2:
Test: 150-year simulation
20 22 24 26 28
30 32 34 36 38
40 42 44 46 48
50 52 54 56 58
60 62 64 66 68
70 72 74 76 78
80 82 84 86 88
90 92 94 96 98
100 102 104 106 108
110 112 114 116 118
120 122 124 126 128
130 132 134 136 138
140 142 144 146 148
150
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1 11 21 31 41 51 61 71 81 91 101 111 121 131 141
Time
"Old
gro
wth
" c
ells
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7000
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"Dis
turb
ed
" c
ells
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1 11 21 31 41 51 61 71 81 91 101 111 121 131 141
Time
"Old
gro
wth
" ce
lls
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"Dis
turb
ed"
cells
Time series analysis of rule 2:
Large series (9200 time steps)
Fractal spatial pattern...
y = 4996x-0.8814
R2 = 0.9266
0
1000
2000
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0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000
Class
N
y = -0.881x + 3.6973
R2 = 0.9265
0
0.5
1
1.5
2
2.5
3
3.5
4
0 0.5 1 1.5 2 2.5 3 3.5 4
Log(class)
Lo
g(N
)
Disturbance size class histogram
y = -0.8435x + 2.6624
R2 = 0.7964
0
0.5
1
1.5
2
2.5
3
0 0.5 1 1.5 2 2.5 3 3.5 4
Log(class)
Lo
g(N
)
P(size class increment)/step)=0.9
n= ca 3700
Rule 2-pattern relatively insensitive to parameter adjustments
Here: relatively small local inter-cell variation in forest growth rate
Rule 2-pattern shows “mild chaos” on a return map of order 1
Comparing cover of old forest at time T (x-axis) with T+1 (y-axis)
y = -0.0003x2 + 2.1987x - 165.03R2 = 0.0566
0
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0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000
Step T
Step
T+1
Polynomial:
Statistical mechanics: Self-organized critical state...
Landscape ecology: Shifting mosaic
Disturbance rules vs. landscape element connectivity
Rule 1 (scale-specific) Rule 2, less synchronized Rule 2, relatively synchronized
•Stop series at a random point where overall cover of old-growth cells is approximately 6500 cells
•For the next time step, set disturbance intensity to 0.05 (every 20th cell expected to be perturbed), and let all local disturbances spread to all connected old-growth cells (Rule 2)
•Result: Fractal patterns show better overall connectivity between similar growth phase elements, both for young and old age classes.
Disturbance rules vs. landscape element connectivity
Rule 1 (scale-specific) Rule 2, less synchronized Rule 2, relatively synchronized
All three landscape patterns above offer the same overall logging output in the long run.
Parameter-sensitive connectivity pattern, in particular “Rule 1”-based management
Local management areas define upper scale range for age class pattern even for “scale-free” logging rules
Grain: 1 Ha
Extent: 128*128 = 16,384 Ha
Extent: 9 * 16,384 Ha = 147,456 Ha
Extent: 400 * 147,456 Ha = 58,982,400 Ha
768
km
12.8
km
Part 2
Adding realism I: Age-structured forest dynamics at scale 1 Ha
Time
Example from a “Rule 2” type of logging regime
Intense computation:
For each time increment, update more than 100 year classes for each of the arena’s 16384 1 Ha pixels (cells)…
Time series for arena: Old growth forest cover (upper line) and logging intensity (bars)
0
500
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2500
30001 4 7
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82
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91
Time (years)
Nu
mb
er
of
1 H
a c
ells
0
100
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1 4 7
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Time series for one particular cell:
Num
ber
of o
ld tr
ees
Intra-cell dynamics
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55
64
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82
91
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0
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S1
S4
S7
S10
S13
S16
S19
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10000
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30000
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70000
Number of trees
TimeAge class
Logging
Logging
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55
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73
82
91
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0
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4
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S1
S5
S9
S13
S17
S21
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2000000
4000000
6000000
8000000
10000000
12000000
Basal stem area
TimeAge class
Logging
Logging
Model behaviour needs careful validationExample: Time series for oldest age class (>=100 years) in a given 1 Ha cell
1 8
15 22
29 36
43 50
57
64
71
78
85
92
99
106
113
120
127
134
141
148
155
162
S1
0
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Nu
mb
er o
f tr
ees
Time
Time series for oldest age class >100 years
Logging
Logging
Part 3
Adding realism II: Dynamics in a heterogeneous landscape
Adding GIS layers for local abiotic conditions
Relative growth rate smaller close to tree line:
A function of altitudal summer temperature gradient
Frequency histogram template for potential or actual birch forest substrate at 1 Ha scale from index 0 (no potential for birch) to 5 (full cover)
0
10
20
30
40
50
60
1 2 3 4 5
Index
Pe
rce
nt
100
m
Part 4
Adding realism III: Climate change scenarios
Topoclimatic models for the height gradient in the HIBECO model
8.0
10.0
12.0
14.0
16.0
18.0
20.0
0 100 200 300 400 500 600 700 800 900 1000
Height above bottom of valley, H
3-M
on
th M
ax. T
emp
erat
ure
, T
T = 15 +2 / (H/ 20 + 1) - 0.55 * H / 100
T = 13.7 -ABS(H-75)/80 + (1000+15.2*H)/2200
Series 1: No disturbances Series 2: “Rule 1”-disturbances Series 3: “Rule 2”-disturbances
Climate change scenarios:
+ 2.4 C over the next 120 years
(scenarios – not prognoses!)
Part 5:
Adding realism IV: Influences from herbivores – grazing ungulates and leaf-
eating insects
Grazing ungulates (sheep, reindeer) and forest structure
“Rule 1”-generated pattern “Rule 2”-generated patterns
Sustainable pluralistic utilization of birch forest:
Logging rules (“policy”) can significantly influence the overall quality and availability of forest elements for other uses, like grazing habitat for sheep and reindeer, hiking/tourism, etc.
Leaf-eating moth outbreaks (Epirrita, Operopthera etc.)
Lower limit: 100 m above bottom of valley
(Winter inversion)
Upper limit: 13.5 ºC isotherm for 3-month max summer temperature
Outbreak constraints:
In this preliminary and hypothetical 120-year scenario insects have tree-killing preudoperiodic outbreaks every 8-12 years
http://www.hibeco.org