Social and Biophysical Dynamics of Reforesting
Systems: Tensions between Macro-scale Theories and
Local-scale Findings
Tom P. Evans1
1 Department
of Geography and Center for the Study of Institutions, Population and Environmental Change
2
Workshop in Political Theory and Policy Analysis
Indiana University
Bloomington, IN (USA)
Contact: evans@indiana.edu
May 23, 2007
Trajectories of Global Land Cover Change

Considerable amount of research focused on proximate causes
of deforestation, especially tropical deforestation

2
Lambin et al. 2001, Global Env. Change
Reforestation in Context of Global Environmental Change

Less attention has been focused on reforestation

Reforestation of increasing relevance



3
Global climate change and carbon related policy programs (carbon
trading)
Biodiversity loss
Impact of forest regrowth on hydrological dynamics

What is the potential for reforestation to offset losses of carbon
due to deforestation locally and globally?

What trajectories of land cover change are likely among
countries currently experiencing net deforestation?
Forest Transition Theory
abandoned/
4
Foley et al. 2005. Science
Pathways of Forest Transition

Transition to Forest Regrowth/Recovery
Rudel et al. 2005, Global Env. Change and others…

Economic Development Path



As economy develops, labor shifts from on-farm activities to off-farm
wage labor opportunities
Loss of on-farm labor results in abandonment of more remote, less
productive areas
Path reinforced when governments purchase unproductive areas



Greece, Ireland, Portugal, USA(?)
Forest Scarcity Path



5
Much of the US National Forest System followed this pathway
As timber products become more scarce, price for timber increasese,
(some) landowners plant trees instead of crops (e.g. India; Foster and
Rosenzweig, 2003)
Path reinforced when governments initiate reforestation programs and
subsidize tree planting efforts
India, China, Bangladesh, Vietnam
Pathways of FTT
6

Economic Development Path generally occurs at a higher ‘deforestation
trough point’ or level of net forest cover than the Forest Scarcity Path

US, European countries, generally 15-30%

Less developed countries, generally < 15%
Rudel et al. 2005
Reforestation Transitions
Forest Transition Theory




7
Tied to process of economic
development and transition
Therefore, generally applied to
national scale
Applicability at regional or local
scale is uncertain and one source
of criticism
What switches system from
deforestation to reforestation?

What determines rate of reforestation?

What determines (probable) point of
maximum reforestation?
% Forest Cover

Time
System States and FTT
Forest transitions and system
states

Five phases or system states can
be imagined in FTT






Is shift between states the product
of large shocks or modest dynamic
changes?



8
Natural system
Deforestation
Stable forest cover (trough)
Reforesting
Reforested  ???
Black death 14th century Europe
Great Depression (1920s) - US
World War II (1940s) - US
% Forest Cover

Time
Complexity and Land Change Science (LCS)

Geography/Human Dimensions of Global Change perspectives on
complexity (Manson 2001)

“Algorithmic complexity”

Difficulty in defining salient system components
 Simplest possible system definition that can replicate behavior of the system
(Chaitin 1992)

“Deterministic complexity”


“Aggregate complexity”

9
Interaction between system components can lead to shifts in system state or
equilibria
emergent behavior approach – interactions of agents/actors at one scale leads to
particular outcomes (e.g. landscape configuration) at another scale
Complexity and Land Change Science (LCS)

Deterministic complexity


Aggregate Complexity


10
Resilience Alliance – http://www.resalliance.org
Local level decision-makers (households), aggregate scale outcomes
(regional scale land cover composition and pattern)
Interactions between households
Deforestation in Eastern United States
11
Deforestation in Eastern United States

Indiana (68%) and Ohio (72%)
experienced the most dramatic
loss of forest cover in the
United States

Large areas suitable for
agricultural production where
native ecosystem type is forest
(pasture/grassland native state
in Iowa, Dakotas, most of
Illinois)
12
Reforestation in Eastern United States
13
Reforestation in Eastern United States

Most states have experienced
net reforestation, especially
Northeast US

Modest gains in Midwest US

Subset of states net
deforestation


14
Florida, NJ – urban growth
North Carolina, Tennessee?
15

Flat topography in north, rolling topography in
south

One major “urban” area


16
Indianapolis (850,000 residents)
Landscape dominated by corn/soybean rotation
in north and mosaic of forest and agriculture in
south
Local Scale Dynamics
Private land owners critical to trajectory of forest cover change in Indiana


87% of forest land in Indiana is on private land holdings
 Remaining forest lies within federal and state managed lands, the majority of
which are actively managed


Selective harvesting, some clearcutting
Communities are relatively weak
sources of institutions in this context

Some counties have planning/zoning
but not all, and those counties that do
have zoning do not necessarily have
plans that reinforce healthy forest
management
 Stay tuned…
17
Trajectories of Forest Change in Indiana
18
Monroe County, Indiana (Midwest US)

Roughly 30x40km, modest but steady population growth


100,000 in 1980  120,000 in 2000
Net Forest cover increase

~43% in 1939, ~60% in 1997
 This trough point and net amount of reforestation analogous to that seen in
Northeast USA
Monroe County
Population and Forest Cover in Indian Creek Township
1600
65.0
Population
1500
Forest Cover
60.0
1300
1200
55.0
1100
1000
50.0
900
800
45.0
700
600
1930
1940
1950
1960
1970
Year
19
1980
1990
40.0
2000
% forest
Number of people
1400
Net Reforestation in Monroe County

Aerial photography 19392003 provides the ability to
develop spatially explicit data
farther back in historical
record
100
Percent
80
60
Forest 1939
Forest
1939
Forest 2003
Forest
2003
40
20
0
0-5
5-10
10-20
20-30
Slope (Degrees)
20
30+
Macro Explanations of Reforestation?
Population and Forest Cover in Indian Creek Township


Plausible 1940-1960
1970-2000???
Commodity prices?
Majority of reforestation
occurred in early to mid-1900’s
60.0
1300
1200
55.0
1100
1000
50.0
900
800
45.0
700
600
1930
Great Depression
Land abandonment, particularly
marginal, non-sustainable
agricultural areas
1940
1950
1960
1970
1990
40.0
2000
Price Indices
500
4
Timber
Crops
400
3
300
2
200
1
100
0
1920
1930
1940
1950
1960
Year
21
1980
Year
Timber Price Index


Forest Cover
1400
% forest
Demographic change?

65.0
Population
1500
1970
1980
1990
0
2000
Corn Price Index


1600
Macro Explanations
Number of people

Biofuels and Ethanol Production

16 million hectares currently
enrolled in CRP, much of which
is due to expire

Price of corn


22
$1.86 in January 2006
> $3.70/bushel now (with
projections > $4/bushel)

Huge implications for global
food prices

Huge implications for current
trend of reforestation in US
Local Scale Dynamics

Household level surveys 1998 and 2003, land cover data derived from
Landsat satellite imagery 1984 and 1997

23
HH survey results integrated with landcover data through parcel boundary data

Both reforestation and deforestation occurring, but more reforestation
(8.4%) than deforestation (4.9%) for a net forest cover increase of 3.6%

Older landowners more likely to have reforestation

Parcels with more steep topography exhibited more reforestation

Overall, statistical results explain a relatively low proportion of the
variance for parcel level land cover change
Local Scale Dynamics

Large proportion of modeling literature focuses on relatively
simple explanations for land cover change trajectories


24
Topography
Accessibility, distance to markets

These simplistic explanations under-emphasize the role of
decision-making, and especially the diversity of decisionmaking strategies employed by land holders

Why would two landowners with similar land attributes
(parcel size, topographic distribution, accessibility) make
different land management decisions?
Spatial Clustering of Landcover Change
25

Concentration of parcels
with steep slopes in NE and
East part of county

Concentration of parcels
with shallow slopes in
SW part of county

NW and south-central
areas exhibit
heterogeneous mix of
‘steep’ parcels and
‘shallow’ parcels
Spatial Clustering of Landcover Change Trajectories

Most locations exhibit
heterogeneous mix of
landcover change trajectories

Selected locations of
clustered LCC

Deforestation
(large blue dots)

Reforestation
(large pink dots)
26
Agent-Based Modeling of Land Cover Change

Agent-based modeling focuses on
individual actors (households)
 How do interactions between
actors at local scale produce
particular landscape outcomes at higher
scales?

27
How does heterogeneity
(diversity) of actors affect land
management outcomes?
Focus on Parcel/Household level analysis

Land-cover patterns at the
landscape scale as emergent
property of interactions at local
scale

Ownership parcels as building
blocks of the landscape that are
related to both composition and
configuration
28
Agent Based Modeling of Land Cover Change

Model of labor and resource allocation

Labor allocated to various land uses according to time series of price data


Homo-economicus or “Economic Man”…

Perfect decision maker


Forest, crops, pasture, off-farm labor
Perfect information, makes decisions that optimize utility
Model using landowners with diverse characteristics/preferences produces
best fit to observed land cover change at parcel level
(Evans and Kelley 2006, IJGIS)
29
Land Change Science - Integrated Research Design
Empirical Data
Analysis
Spatially
Explicit
Natural
Resource
Based
Experiments
Data Collection
30
Modeling
Theoretical
Developments
Policy
Recommendations
Experimental research

Common in some fields (psychology, economics) and
becoming accepted in other fields (political science,
anthropology)

D. Kahneman, 2002 Nobel Prize

Ostrom and Nagendra 2007. Insights on linking forests, trees,
and people from the air, on the ground and in the laboratory.
Proceedings of the National Academy of Sciences.

Spatial experimental research


31
Test theories of land-use decision-making to support empirical data
analysis from the field
Resource allocation experiment
Spatial Experiment – Resource allocation

Basic structure

15x15 cell landscape
 9 subjects/partitions, 25 cells each (5x5) – 45 subjects/experiment
 Subject decision: Place cells in either use B or G resource
 Prices of B and G change through experiment


Cash payout, subjects told their payout is proportional to their success in the
experiment

32
40 total decision-making rounds (prices exogenous)
Total revenue received through all rounds
Experiment Interface
33
Spatial Decision-Making Experiments

Comparison of landscapes from experiments and landscapes
from agent-based model demonstrate that experimental subjects
often do not choose optimal resource allocation
Landscape Composition of 5 s0e0 Experiment Sessions with
Landscape Composition
of Simulated Agents and
s0e0 Simulation
Experimental Subjects
120
Percent of Land in B
100
413
80
414
614
60
615
616
40
simulation
20
0
0
10
20
Round
34
30
40
Spatial Decision-Making Experiments
Landscapes emerging from
“Non-optimal” subject
decisions have different spatial
characteristics than “optimal”
landscapes produced from
simulations of “perfect”
decision-makers
Landscape Edge of 5 s0e0 Experiment Sessions with s0e0
Landscape
Edge of
Simulated Agents and
Simulation
Experimental Subjects
160
140
120
413
Total Edge

100
414
614
80
615
616
60
simulation
40
20

Greater landscape diversity
0
0
10
20
30
40
Round

More landscape edge
Landscape Edge of 5 s1e0 Experiment Sessions with s1e0
Landscape
Edge of
Simulated Agents and
Simulation
Experimental Subjects
Directly supports findings from
agent-based modeling


Diverse agent types
More complex landscape
patterns than predicted solely
by land suitability
160
140
120
225
Total Edge

100
226_1
226_2
80
302
304
60
simulation s1e0
40
20
0
0
10
20
Round
35
30
40
Matching Experiments to Simulations
Simulation run
No positive spatial externality
Heterogeneous suitability
Experiment run
No positive externality
Heterogeneous suitability
Simulation run
Positive spatial externality
Heterogeneous suitability
Experiment run
Positive externality
Heterogeneous suitability
36
Optimal
allocation
by round
BLUE
MIX
GREEN
Complexity in Transition from Deforestation to Reforestation

We do see support for “shock” explanation of system state change, transition from
deforestation to reforestation

Continuing process of reforestation is more subtle

Change in economic opportunities


Importance of heterogeneity, change in preferences, experiences and information
among actors


As economy develops, more off-farm wage labor opportunities
Evidence from household surveys supported by insights gained from agent-based models
and experimental research
Diversity of household level attributes key to the regional level pattern of land
cover change, transition from deforestation to reforestation

In-migration


Agricultural extension




37
New agricultural practices introduced
Innovators adopt new agricultural methods, diversify land uses
Education
Environmental valuation
Risk, learning
Limitations of Forest Transition Theory

Reforestation has generally occurred in areas most marginal for agricultural
production

Steep slopes, areas of low accessibility, poor soils
 Physiographic diversity of reforested state is lower than pre-settlement forest
cover



Large amount of reforestation, especially in developing countries, is
plantation forest (e.g. eucalyptus)



Alleged benefits in terms of carbon, more questionable ecological benefits
Hydrological benefits
Loose definition of forest


38
Lowland forests, valley bottoms
Implications for ecological diversity
Rubber plantations in Laos, palm oil categorized as forest in Southeast Asia
Again, questionable ecological benefit
Rubber Adoption in PDR Loas

Rural landscape dominated by smallholders practicing shifting cultivation

Diverse land suitability, areas suitable for lowland rice vs. areas for upland
crops

Introduction of rubber from China (social networks)

7 year lag between planting trees and collecting rubber
 Major household decision to allocate land, must consider level of risk aversion
and prediction of future rubber market prices
39
Rubber Adoption in PDR Loas

Agent based model



40
Households allocate labor to different land holdings based on HH labor
availability
HH decide to maintain existing land uses or transition to new land uses
Spatial interaction and social network measure, lead to faster or slower
adoption within community

Are early adopters better off than late adopters?

Demo
Acknowledgements

Midwest US/Brazilian Amazon project



Laos PDR project



41
U.S. National Science Foundation (US research)
Elinor Ostrom, Shanon Donnelly, Hugh Kelley, Wenjie Sun, Jimmy
Walker, Sean Sweeney, Jerry Busemeyer, Vicky Meretsky
Jeff Fox, John Vogler, Khamla Panvilay – East-West Center
NASA, NSF funding
Center for the Study of Institutions, Population and
Environmental Change (CIPEC); Workshop in Political
Theory and Policy Analysis; Indiana University
Literature
Elmqvist and e. al. (2007). "Patterns of Loss and Regeneration of Tropical Dry Forest in Madagascar: The Social Institutional Context." PLoS
ONE 2(5).
Evans, T. P. and H. Kelley (2004). "Multi-scale analysis of a household level agent-based model of landcover change." Journal of Environmental
Management 72(1/2): 57-72.
Evans, T. P. and H. Kelley (in press). "Assessing the transition from deforestation to forest regrowth with an agent-based model of land cover
change for South-Central Indiana (USA)." Geoforum.
Evans, T. P., W. Sun, et al. (2006). "Spatially explicit experiments for the exploration of land-use decision-making dynamics." International
Journal of Geographical Information Science 20(9): 1013-1037.
Foley, J. A., R. DeFries, et al. (2005). "Global Consequences of Land Use." Science 309(5734): 570-574.
Geist, H. J. and E. F. Lambin "Proximate Causes and Underlying Driving Forces of Tropical Deforestation." BioScience 52(2): 143-150.
Lambin, E. F., B. L. Turner, et al. (2001). "The causes of land-use and land-cover change: moving beyond the myths." Global Environmental
Change, Part A: Human and Policy Dimensions 11(4): 261-269.
Ostrom, E. and H. Nagendra (2006). "Insights on linking forests, trees, and people from the air, on the ground, and in the laboratory." Proceedings
of the National Academy of Sciences: 0607962103.
Perz, S. G. (2007). "Grand Theory and Context-Specificity in the Study of Forest Dynamics: Forest Transition Theory and Other Directions." The
Professional Geographer 59(1): 105-114.
Perz, S. G. and D. L. Skole (2003). "Secondary Forest Expansion in the Brazilian Amazon and the Refinement of Forest Transition Theory."
Society & Natural Resources 16(4): 277-294.
Rudel, T. K., O. T. Coomes, et al. (2005). "Forest transitions: towards a global understanding of land use change." Global Environmental Change
15(1): 23-31.
42
Thank you.…
Questions?
43