1. Tree cover in landscapes changes over time in complex non-linear ways, depending on how "forest" is defined. At certain scales, tree cover transitions follow a pattern of initial decline followed by recovery, as described in the basic forest transition hypothesis. 2. Increases in human population density are linked to decreases in natural forest cover, while increases in economic development and welfare are linked to increases in tree cover, as described in the population density and welfare hypothesis. 3. Spatial patterns of tree cover resemble the temporal dynamics described in hypothesis 2, reflecting the benefits derived from trees in different land cover types, as described in the spatial forest transition hypothesis. 4. Institutional changes from forest to agrarian regimes of

1. CRP6 Seminar Bogor – taking stock in CRP6.3 & 6.5 ; 13 March 2013
Tree cover transitions and investment in multi-
colored economy: hypotheses grounded in data
Tree cover transitions and land-
scape functions: does it matter?
Meine van Noordwijk
ICRAF

2. Geological history, pat- Global climate systems
terns & current activity based on oceans, land
& atmosphere
Flora and fauna and its biogeography
Land forms,vegetation,ecosystems,hydrology
Initial human Late-stage hu-
land use man land use
Land use is predictable from Land use dominates over
‘reading the landscape’ original terrain features

3. Planning, Incentives
Geology Institutions People
Tenure
Land forms
Climate
Landscape Space
multifunctionality
Vegetation
Flora&fauna
Hydrology Land Use Functions,
Systems services
Value chains Landscape -

4. Which trees are part of “forest”, which ones
part of the “agroforest”, or “agriculture”?

5. Tree cover transitions as uni-
fying concept for livelihoods,
landscape and governance
aspects
Old-growth
http://www.cifor.org/es/crp6/research-portfolio.html

7. SLO1 Rural income growth &
Millennium Development Goals
empowerment at bottom of
the gendered pyramid
Sustainable Development Goals
(Agro-)Ecosystem goods & services
Maintain & accelerate progress
Partnership
Food supply growth > in responsive
SLO2 growth in demand; food and adaptive
price affordable at bottom research
of gendered pyramid for/on/in
development
efforts,
Nutritional aspects of strengthening
SLO3 health improve at bottom capacity
of gendered pyramid
Landscape interactions:
Reverse negative trend
UNFCCC CBD UNCCD
Rio conventions
SLO4 Low emission Aichi targets: Zero net
development; areas, aware- land degra-
Reduce ness, species, dation
vulnerability governance,
through incentives
adaptation

8. Tree cover transitions: so what?
SLO1 Rural poverty
SLO2 Food production
SLO3 Health & Nutrition
Direct vs Profitability
Indirect Sustainability
SLO4 Natural Resource
Management
Trees as Trees as Trees as Trees as
• Assets • (emergency) food • Source of fruit, •Markers of land
• Affordable bio- • Staple (sago…) nutritional diver- tenure claims
energy source • Source of soil sity  health • Water recycling
• Income earners fertility for crops • Affordable bio- • Nutrient recy-
through products • Erosion control energy source cling
• Markers of land • Buffering climate • Medicinals • Carbon storage
tenure claims & soil temperature • Clean water • Climate buffer

9. Fruits as
healthy
part of
diets

10. Essentially there are only two possible
conditions for any specific field of science:
At least some of the evidence is
conflicting with the most compre-
hensive of current theories
Current theory is aligned with all
credible known facts

11. Identify and implement a rational
pathway to achieve change that is
deemed desirable by funders and
Theory of Change acceptable by gatekeepers
Question common Answers
Answer open Questions
Change of Theory
New
Our daily
Theory of
struggle
Change
called science

12. Three sessions reflect focal areas within
the landscape theme (CRP6.3):
• 10.15-11.15 I. Tree cover transition data and
research choices in sentinel landscapes
Facilitator: Peter Minang
• 11.15-12.15 II. Ecosystem service consequences
of tree cover transitions
Facilitator: Terry Sunderland
• 13.15-14.15 III. Learning landscapes: finding
solutions that reduce tradeoffs locally
Facilitator: Ujjwal Pradhan

14. The logarithm of human population density is a
good predictor of the fraction of land area reported
as forest (across different forest types)
We can identify
countries that have
more than 10%
extra, or more
than 10% forest
deficit relative to
what is expected
for their
population density

15. For 29 Developing Countries reporting increases in fo-rest
area (“beyond forest transition point”), the pattern matches
that of 83 other Developing Countries
However, FT patterns are less likely in countries that have
more than 10% forest deficit

16. A key assumption in the CGIAR is the Borlaug hypothesis that
ag yield increase will save forests…
There’s a little bit of evidence suporting it, but not a lot…

17. Forest transition points are less likely
where the firewood footprint still
exceeds 0.15 ha p.p.

18. 1. Tree cover in landscapes changes in quality, quantity and pattern in non-linear fashion;
depending on the operational forest definition used, tree cover transitions at certain scales
show a ‘forest transition’ graph of decline followed by recovery (basic forest transition
hypothesis)
2. Tree cover transitions in time can be understood as the resultant of time-variant processes,
with increases in human population density (or rather the logarithm of it) linked to decrease
of natural forest cover, and increases in HDI (or other economic indicators) linked to
increases in tree cover (population density and welfare hypothesis)
3. The spatial pattern in quality and quantity of tree cover from urban areas with (surrounding)
trees to areas with few trees and open-field agriculture towards remaining natural forest
show more than coincidental resemblance with the temporal dynamics of hypotheses 2, as
both patterns reflects benefits derived from tree cover relative to other land cover types
(spatial forest transition hypothesis).
4. Institutional change from a ‘forest’ to an ‘agrarian’ regime of tenure and control is essential
for the transition from decline towards increase of tree cover to occur (agroforestation or
tenurial reform hypothesis)
5. What happens in one part of the tree cover transition is linked at driver and/or actor level to
other parts of the landscape as A) profitability of tree planting depends on access to tree
and forest products elsewhere, B) migrational flows modify human population density in
sink and source areas, etc.), C) landscape-wide rules instigated to address specific issues in
parts of the curve (e.g. ‘illegal logging’ control) affect actors elsewhere (landscape linkage
hypothesis; the ‘sparing’ hypothesis that agricultural intensification saves forests is a special
form of it)

19. Forest and tree cover transitions: a unifying concept
1 Choice across CRP6
of Y-axis
6
Core
2 3 4 5
Temporal Spatial Institutional X-linkage of
pattern, X- pattern, challenge at actions in
axis X-axis turning point landscape

20. Stakeholder:
1. Undisturbed natural forest Rainforest foundation
2. Undisturbed + sust. logged natural forest Conservation agency
3. Closed canopy undisturbed + logged forest
4A. as 3 + agroforest Forest ecologist
4B. as 3 + timber plantations Ministry of Forestry
4C. as 3 + agroforest + timber plant’s + estate crops UNFCCC definition
4D as 4C + shrub Modis data

21. 6. Drivers of tree cover transition are space/time dependent and knowledge on past
drivers in a certain landscape cannot be directly extrapolated towards the future; yet
there may be predictability in the succession of drivers (driver change hypothesis)
7. Land use types that are part of the tree cover transition
differ in effectiveness of ‘provisioning’ and ‘environment-
al’ goods and services, labour absorption and profitability
(tradeoff hypothesis, ASB Matrix)
8. Tree cover of all types and in all stages is positively
associated with buffer functions in an ecological, social
and economic sense, with the spatial pattern and degree
of integration linked to human resilience and adaptive
capacity in the face of climate and market variability
(integration, buffer and resiliency hypothesis)
9. Appreciation of tree cover and its associated ecosystem services varies with gender,
wealth, cultural backgrounds, ecological knowledge and exposure to extreme events,
leading to diversity of opinion and preferences for status quo and possible changes in
tree cover (‘diversity of stakes’ hypothesis; includes gender specificity)

22. A view from the modern
LU planners kitchen:
From the “silo- approach”
to (intensive) agriculture,
production forestry and
conservation areas set-
aside, we can cook a
landscape that is more
palatable than any of the
ingredients, by adding
local preferences, using a
variety of tools

23. Regulate and/or reward
 people * influence * concern
Who will monitor
Who’ll have to pay? compliance? Litigation
Political prominence
What will it cost? Implement &
monitor
What can be done to stop,
mitigate, undo or adapt? Evaluate, re-
assess
How much and where?
Who’s to blame?
Is it a Cause-effect
problem? mechanisms
Scoping Stakeholder Negotiation Implemen- Re-eva-
analysis response tation luation
Stage of the issue cycle
Tomich et al. 2004

24. 10. Feedback mechanisms from beneficiaries of
(certain types of) tree cover to the drivers/agents
can take multiple forms (rules, incentives, suasion,
investment in value chains and technology) and
needs to be evaluated in the interaction between
instruments rather than as specifically targeted
approaches (‘no silver bullet’ hypothesis)
11. Dynamics of tree cover changes can be influenced by multistakeholder negotiation support
processes, that recognize multiple knowledge, perceptions, stakes, power and influence
(Negotiation support hypothesis; includes gender specificity)
12. Public discourse on aspects of tree cover
transition and the relevance of interventions follows
a policy issue cycle, with different opportunities for
knowledge-based analysis to support and influence
the emergence of transparent, effective, efficient
and fair solutions, linking platforms of political will
to actionable knowledge (impact pathway
hypothesis)

25. New tech- F. Support for technological innovation
G nology
A1. Land use policies, spatial development planning, roads
A2. LU rights (e.g. community forest mngmnt)
Livelihoods, provisioning &
profitability G
G
Land Conse- G Response/
Actors/
G Drivers use/cover quences & feedback
agents
changes functions options
Biodiversity, Watershed G
G
functions, GHG emissions,
Institutions, C. Suasion and institutional support
Landscape beauty
identity,
pride B2. PES and conditional ES incentives
B1. Incentive structure through policy change (tax, subsidy etc)
G = Potential gender specificity of analysis & targeting of interventions
Modified from: Van Noordwijk, M., B. Lusiana, G. Villamor, H. Purnomo, and S. Dewi. 2011. Feedback loops added to four conceptual models linking land change
with driving forces and actors. Ecology and Society 16(1): r1. [online] URL: http://www.ecologyandsociety.org/vol16/iss1/resp1/

26. http://www.espconference.org/ESP_Conference

27. New green economy, integrated rural-
urban development coalitions… GDP, national econo-
Economic development planning mic growth or decline
Mar- Food, fibre, income  Harvestable products Commodity-
Sustainable development metrics
ket access, product- ser-
tax,subs. Provisioning services vice value
Human Management chains, x-
popula- & behavioural Land use practices border trade
tion & Δ choices of in a landscape Waterflows
Land use land users AgTech context (quality,quantity,
zoning, Regulating, supporting regularity)
use and & cultural services Macro-&me-
property so climate
rights Human & environmental health&well-being Biodiversity
Environmental & wellfare targeted planning Natural ca-
Happiness pital ac-
monitoring counting

28. Three sessions reflect focal areas within
the landscape theme (CRP6.3):
• 10.15-11.15 I. Tree cover transition data and
research choices in sentinel landscapes
Facilitator: Peter Minang
• 11.15-12.15 II. Ecosystem service consequences
of tree cover transitions
Facilitator: Terry Sunderland
• 13.15-14.15 III. Learning landscapes: finding
solutions that reduce tradeoffs locally
Facilitator: Ujjwal Pradhan