1. Trees and Forests for a Healthy World:
Vision for 2030
Tony Simons, Director General, ICRAF
VIII Brasilian Agroforestry Congress
November 21st 2011

2. Trees and Forests for a Healthy World
1. The Challenges
2. Guiding Paradigms
3. Looking ahead to 2030
4. Knowledge Transfer Opportunities
5. Some New Directions??

3. 1. The Challenges
Los Angeles Cairo City Tropical
city commuters populace deforestation
Differentiated problems? or interlinked global challenges?

4. Shifting Geopolitics, Demographics and Financing
Popn
billions
Asia
Africa
Latin America
1950 1970 1990 2010 2030 2050
Source: UN DESA, World Population Prospects 2008

5. Widening Inequality
Country Gini coefficient
Brazil 57%
Burkina Faso 39%
Cameroon 45%
China 41%
European Union 30%
Finland 26%
India 37%
Indonesia 37%
Kenya 42%
Malawi 39%
Namibia 71%
Peru 50%
Philippines 46%

6. Food Insecurity
‐ Global food prices doubled 2006 to 2008
‐ By 2050 we will need to produce 70% more food
‐ Growth in agriculture generates greatest
improvements for the poor
‐ Policies, good governance and investments as
important as technologies
‐ Better risk management and avoidance is
required
‐ Greater infrastructure needed in rural areas
‐ We need to produce as much food in the next
40 years as we have done in the last 8000 years

7. Food Security
we put far more
attention on the security
dimension than on the
food dimension

8. The world as we know it
www.worldmapper.org

9. Forest loss 1990-2000

10. Net forest growth 1990-2000

11. Adams J.M. & Faure H. (1997) (ed.s), QEN members. Review and Atlas of Palaeovegetation: Preliminary land
ecosystem maps of the world since the Last Glacial Maximum. Oak Ridge National Laboratory, TN,

12. Adams J.M. & Faure H. (1997) (ed.s), QEN members. Review and Atlas of Palaeovegetation: Preliminary land
ecosystem maps of the world since the Last Glacial Maximum. Oak Ridge National Laboratory, TN,

13. Choosing a forest definition
for the Clean Development Mechanism
FORESTS AND CLIMATE CHANGE WORKING PAPER 4 – 2006
http://www.fao.org/forestry/media/11280/1/0/
For the CDM, developing countries must choose the
parameter values from the ranges: “Forest” is a
minimum area of land of 0.05‐1.0 hectares with
tree crown cover (or equivalent stocking level) of
more than 10‐30 per cent with trees with the
potential to reach a minimum height of 2‐5 meters
at maturity in situ.

14. 50
The relationship between tree crown cover and ability
40 to add extra carbon looks something like this.
Opportunity
for 30
incremental
carbon
(t/ha) 20
10
10 20 30 40 50 60 70 80 90 100
% tree crown cover

15. Lower and upper limits for
CDM A/R
50
40
National governments can set their
Opportunity forest definition as tree cover
for 30 minimum threshold between
incremental 10% and 30%
carbon
(t/ha) 20
10
10 20 30 40 50 60 70 80 90 100
% crown cover

16. AR
at
10%
50
Avoided deforestation at 10%
40
Opportunity
for 30
incremental REDD
carbon
(t/ha) 20 Avoided deforestation at 30%
CDM A/R
10
Aff/Reforestation
at 30%
10 20 30 40 50 60 70 80 90 100
% crown cover

17. Any signs of deforestation?
….are included under forest, as are
areas normally forming part of the
forest area which are temporarily
unstocked as a result of human
intervention such as harvesting or
natural causes but which are expected
to revert to forest;
[FCCC/CP/2001/13/Add.1]

18. The foresters’ view of the world

19. The agroforestry view of the world

20. The integrated view of the world
Global tree cover inside and outside forest, according to the Global Land Cover 2000
dataset, the FAO spatial data on farms versus forest, and the analysis by Zomer et al.
(2009)

21. 2. Guiding Paradigms

22. Productivity
Intensification

23. Ecological functioning Productivity
Intensification

24. Ecological functioning Productivity
Income stability
Intensification

25. Ecological functioning Productivity
Income stability
optimal
Intensification

26. Some effects of trees are mediated through impact
on soil biota – trees increase abundance
Mean density of different soil biota and calculated response ratios
Agroforestry Agriculture RR References
Soil macrofauna (indiv m‐2) (indiv m‐2)
Earthworms 54.4 17.6 3.1 1,2,3,4,5,6
Beetles 20.9 9.6 2.2 1,2,5
Centipedes 2.7 0.5 5.6 1,2,5
Termites 90.7 81.0 1.1 1,2,5
Ants 23.2 8.6 2.7 1,2,5
Soil mesofauna (indiv m‐2) (indiv m‐2)
Collembola 3890.1 2000.7 1.9 7
Mites 5100.7 1860.1 2.7 7
Soil microfauna (indiv liter‐1) (indiv liter‐1)
Non‐parasitic nematodes 2922 1288 2.3 8
Parasitic nematodes 203.7 211.5 1 8
Barrios, Sileshi, Shepherd, Sinclair 2010

27. Water
Environmental services
Soil
Selection fertility Mechanization
Agroecosystem
diversity
Breeding Cropping system
Genetic IPM
potential Agricultural
inputs
GREEN International Assessment of
REVOLUTION Pests,
GOAL weeds Agricultural Science
Hunger Yield and
(IAASTD GOAL 1) diseases and Technology for
Development
Biotechnology Biotechnology
2005‐2008
IAASTD Marketing
GOAL 2 and trade Other
Population Health and Nutrition products
control
IAASTD IAASTD IAASTD
GOAL 5 GOAL 3 GOAL 6 Industry
Social Livelihoods Economic growth
sustainability
IAASTD Public /
Tradition and GOAL 4 Global
policies Private
Culture Environmental
Partnerships
sustainability

28. Sustainable Yields
Annual yield (t/ha)
FARM
2011 2012 2013 2014 2015 Total
Farm A 2.5 2.4 2.5 2.6 2.5 12.5
Farm B 3.5 3.2 2.5 1.9 1.4 12.5
Farm C 4.5 0.0 4.1 3.2 0.7 12.5
Farm D 2.5 2.9 3.1 3.6 4.1 16.2
Farm E 2.5 3.3 3.8 4.4 5.0 19.0

29. Limitations of Disciplinary Approaches
LANDSCAPE APPROACHES
Land units as non‐interacting aggregates
Economic or social synergies not accommodated
Social processes across land uses ignored or aggregated
Ghazoul, ISPC Meeting, 2011)

30. re‐ and afforestation
Fields,fallow, forest mosaic
Farm fo‐
Plantations
restry, Fields,
agrofo‐ Forests
rests & Parks
deforestation
Integrate Segregate

31. ‘deforestation’
natural forest
integrated,
Tree plan- multifunctional
tations landscape: crops, trees,
meadows and forest
patches
‘loss of forest
intensive
functions’
agriculture
Segregate Integrate
functions
Current legal, institutional Current reality
& educational paradigm

32. 3. Looking ahead to 2030

33. Science needs of development
1. Actionable Knowledge and Materials – solutions, options, germplasm
2. Robust Evidence for decision‐making for investments and policies
3. Proof of Application for impact at scale
4. Capacity Development and Mobilisation

34. Temporal Scale
Ecosystem processes
Lifespan timber tree
Lifespan atmosph CO2
Human lifespan
Time to project impact
Political Term
Project duration
Cropping season
0 1 10 100 1000
Log Scale Time (years)

35. Social scale Geographic scale Political scale
Farmer Individual
Family Farm Household
Village Village Village
Relatives Watershed Institutions
Ethnic Community District Local government
Social network Landscape
Nation Country Government
Region Region
Global International

36. The Science of Scaling Up
Science (noun) – to know, knowledge
Scaling up – to bring more benefits to more
people, more quickly and more lastingly
√ Multiplying and disseminating a new maize variety
?? Payment for environmental services
?? Agroecosystems improvement approach

37. Google Scholar
Extension ‐ 3,810,000 urls
Dissemination ‐ 992,000 urls
Technology transfer ‐ 522,000 urls
Scaling up ‐ 148,000 urls
Science of scaling up ‐ 15 urls

38. Impact Pathway Paradigm
Development
(application of knowledge)
Research
(building of knowledge)
Time (years)

39. New Impact Pathway Paradigm
Development
(proof of application &
application of knowledge)
Research
(building of knowledge)
Time (years)

40. Extension, Scaling Up
Research Dimension
Why ??????
What ?????
Where ????
When ???
HOW X
Best Bet, Good Practice, Guideline

41. Why not use Principles for Research in Scaling Up?
1. Problem based (utility, not pure curiousity)
2. Testing a hypothesis, construct, paradigm
3. Systematic/experimental approach
4. Observations (repeated)
5. Independent thinking, deductive reasoning
6. Documented and shared
7. Undergoes critical peer review (credible)
8. Validated, revalidated (robustness)
9. Unplanned serendipity
10.Progressive, building on base of knowledge, zero fraud

42. Scaling up defined
ExpandNet defines scaling up as "deliberate efforts to
increase the impact of health innovations tested in pilot
or experimental projects so as to benefit more people
and to foster policy and program development on a
lasting basis." This definition is more specific than when
ExpandNet is a global network of public health professionals and
scientists seeking to advance the practice and science of scaling up
the term is used in a general sense to mean broadening
successful health service innovations tested in experimental, pilot and
the impact of existing or new practices.
demonstration projects.
http://www.expandnet.net/PDFs/ExpandNet‐WHO%20Nine%20Step%20Guide%20published.pdf

44. Three main farm types in 2030
1. Medium and Large Size Farms
economies of scale, national food security
2. Individual smallholders
vulnerable, subsistence, poverty traps, marginalised
3. Collective smallholders
(relatives, neighbours, coops, interest groups)
more empowered, negotiation skills, aggregate produce, certification

45. 4. Knowledge Transfer Opportunities
Brasil Latin America
Africa Asia
Perhaps make abstracts of this Congress available in English

46. Changes over time in the source of germplasm for timber spp.
(Peru)
80
70
60
50
40 original
present
30
20
10
0
forest field relation n'bour unspec.
source

47. Changes over time in the source of germplasm for fruit spp.
(Peru)
70
60
50
40
original
30 present
20
10
0
forest field relation n'bour market outside unspec.
source

48. Amazonian Case studies
Guazuma crinita
Calycophyllum spruceanum

49. Guazuma crinita

50. Guazuma crinita

51. FAIRLY EFFICIENT OR EFFICIENTLY FAIR:
SUCCESS FACTORS AND CONSTRAINTS OF PAYMENT AND
REWARD SCHEMES FOR ENVIRONMENTAL SERVICES IN ASIA
Beria Leimona
Co authors: Meine van Noordwijk, Laxman Joshi,
Rachman Pasha, Betha Lusiana,,
Elok Mulyoutami, Nimatul Khasanah, Andree Ekadinata
ICRAF Science Week
12-17 September 2011
Nairobi

52. RUPES SITES IN ASIA
covering 12 sites in 8
countries
Bac Kan

53. Three approaches within PES
Paradigm
CES : COS : CIS :
(van Noordwijk & commoditization of ES, compensating or coinvestement in
Leimona, 2010) e.g. C markets opportunities skipped, stewardship, risk &
e.g. public fund benefit sharing
allocations
Condition
Requires A + B Requires B + C Requires C
(A helps as well)
A. Spatial & con‐ Yes (national AFOLU)
ceptual ES boun‐ No (subnational REDD)
daries clear? No (local: plot&tree)
B. All rightholders Yes (national constitu‐ Yes (national constitu‐
identified & in tion, UNFCCC rules) tion, UNFCCC rules)
agreement Yes? (subnat./sectors) Yes? (subnat./sectors)
No (local: plot&tree) No (local: plot&tree)
C. All stakeholders Yes? With nested MRV Yes? With nested MRV
engage in adaptive Yes? With nested MRV Yes? With nested MRV
learning Yes? Possible locally Yes? Possible locally
Conclusion National scale only Subnational scale Local plot&tree scale

54. Climate Smart Agriculture
‐ Increase sustainable productivity
‐ Strengthen farmers’ resilience (adaptation)
‐ Reduce agriculture GHG emissions
‐ Increase Carbon sequestration

55. The Political Dimension: African Union’s recent pre‐Durban COP17 publication

56. Climate Smart Agric and Ministerial Interests
Ministry Ministry Ministry Ministry Ministry Ministry
Agric Envt Water Lands Health Finance
Food Security
(Prodn & Income)
*** * ** ** **
Reduce GHG
emissions of agric
** ***
Mitigation
(increase Carbon
seq.) ** *** ** **
Farmer Resilience
(Adaptation)
*** ** ** **

57. MICCA Project
MICCA intends to facilitate sustained internalization
of agriculture mitigation practices in farming
systems in various agro‐ecological zones moving
towards a low carbon agriculture while increasing
resilience to climate change and agricultural
productivity
Within the Pilot Activities the goal is to increase
household food security, agricultural productivity,
ecosystem resilience while reducing greenhouse gas
emissions.

58. Participatory
Assessment of
Current and
Potential Climate
Smart Practices
Using and Improving Awareness Raising,
Predictive Tools for Capacity
Potential Impact Increasing Productivity Development and
Demonstrations
Reducing Environmental
Footprint
Baseline
Measurement and Introduction or
Monitoring of Land testing of Climate
Health Smart Practices
Greenhouse Gases

59. Engaging multiple stakeholders to facilitate
enhanced climatic risk management

60. Trees on farms: Tackling the triple challenge
of mitigation, adaptation and food security
Trees on farms address
climate change mitigation
and adaptation, and food
security by storing carbon,
buffering against climate‐
related impacts and providing
additional income through
tree‐based products

61. Tools for monitoring, reporting and verification
The Carbon Benefits Project aims to provide
a cost‐effective end‐to‐end estimation and
support system for showing carbon benefits
in GEF and potentially other natural
resource management projects
The system will be applicable to a wide
range of soils, climates and land uses

62. New book
to be launched at COP17

63. Timber Value Chain (per standing tree) Assumptions:
For Vitex grown in Meru
Seed germination 60%
Nursery survival 85%
$0.01 Field survival 70%
seed sowing, watering, tending 15 year rotation
Three lengths 2.8m a 40cm dbh
$0.30 Sawnwood recovery 40%
Nursery seedling Carbonprice $14 per tonne
Planting, weeding, protecting Wood density 0.65 tree, 0.55 pole
$0.01
(year 1)
Product value Sapling in field
thinning, pruning, protecting
thinning, pruning, protecting (year 2) Carbon value
(total)
$42.85
$7.14
Standing pole in field Standing tree in field $9.45
$1.15
(year 9) (year 16)
Felling, limbing, cutting, stacking
Felling, limbing, stacking $50.00
$8.57 Felled tree at farm gate $6.30
Pole at farm gate $0.86
Transport, sizing, stacking
$64.28
Log at timber yard $6.30
Transport, sizing, stacking
Sawing, grading, stacking If 15% is
Gross – with no:
permanent
Community
$128.57 then it
risk $17.14
DNA Pole in merchant yard $0.86 Sawn wood at timber yard equals US$0.37
$2.52
verification
Carbon Value Chain Farmer Project Manager Broker Buyer
$8.08 $12.01 $14.00
(If use half life cycle of 30 years and Roy and Phelps decay curve then 15% of carbon still stored at 100 years)

64. INNOVATION: Rural Resource Centers
ICRAF‐WCA has been experimenting the
concept of rural resource centres and
relay organisations for the
dissemination of agroforestry
innovations and more particularly
participatory tree domestication, for
the last 5 years in Cameroon, DRC
and Nigeria.
Degrande A et al,. 2010. Agroforestry innovations supporting
livelihoods in conservation landscapes: experiences from the
World Agroforestry Centre in the Congo Basin. Paper presented
at the National Forum on Forests, 29‐30 March 2010, Yaoundé,
Cameroon.

65. KEY SERVICES PROVIDED BY RRCs
Skills development in areas such as nursery practices
(Tree Domestication, group dynamics and marketing)
Information and demonstration of new technologies
and innovations
Access to market information
Links with market actors particularly from the private
sector
A forum for exchange of information among farmers
and between farmers and other stakeholders
Seed, seedlings and other inputs

66. Spread
350
317
300
250
Numbers
200
Nigeria
150 DRC
Cameroon
100
50
43
0
2009 2010 2009 2010
RC Smallholder
nurseries
Asaah E.K., et al, (2011). Trees, Agroforestry and
Multifunctional Agriculture in Cameroon.
International Journal of Agricultural Sustainability
9 (1): 110‐119.

67. Rehabilitation of old cocoa farms
• Improved variety grafted to old
cocoa tree
– Success rate 59‐73 %
– Variation on growth
– Variation among clones
4 weeks after grafting

68. Project Vision for Change (V4C)
First flowers after 5 months
First pod at 9 months

69. COCOA IMPACTS
• This approach for
rehabilitation of old cocoa will
help farmers to reduce poverty
in rural areas.
• The production is expected to
move from 400kg/ha to 1.5
ton/ha
•This approach used for
300,000 farmers will then be
extended to other cocoa
production countries
• Help to increase production
while avoid new clearing for
new plantations

70. International conference to take stock of current policies,
thinking and practice, successes and failures of ongoing and
past reforms in extension and advisory services and build a
coalition moving forward to specifically address meeting the
future needs of small‐holder farmers, marginalized
communities, women and youth in a sustainable and cost
effective manner.
CTA, FARA, GFRAS, IFAD, FAO, AGRA, KARI, ICRAF and others
http://extensionconference2011.cta.int/

71. Small-scale Large-scale
saw mill saw mill
Small-holder
production Independent Out‐grower
growers schemes
Large-holder
production Industrial
plantations

73. Farmers imagine the crown size and how
many trees may fit along a boundary

74. And typically plant boundary/contour trees at final spacing

75. Of course because of variation in trees and the
micro‐site, later we see differences in growth

76. The challenge is to get farmers to plant at
greater than final spacing

77. We can then learn about
farmers’ thresholds by
= getting them to select
the best of two trees

78. Demonstrations on farmer’s fields are good because
the concepts may be too abstract otherwise

82. 5. Some new/stronger directions in agroforestry
1. Land tenure, rights and resources
2. Production economics
3. Tree commodities (cocoa, coffee, rubber, oilpalm, others)
4. Productivity gap and how trees can help
5. Adaptation decision support
6. Location‐based intelligence (new Geoinformatics work)
7. Co‐investment PES model development
8. Capacity Development (incl. local level)
9. Agroforestry indicators
10. M&E and Impact Assessment
11. Science of Scaling Up
12. Genomics of trees

83. Forest definition Forest definition
based on X% canopy based on insti‐tutions
cover & intent
Non-forest without trees
Trees Forest Forest
outside with without
forest trees trees
Clearfelling/ re‐
plant is accep‐ted
Including e.g. as forest; no time‐
agroforests, oil limit on ‘replant’
palm plantation

84. RED = Reducing emissions from (gross) REDD+ = idem, + restocking within and towards
deforestation: only changes from ‘forest’ to ‘forest’ ; in some versions RED+ will also include
‘non‐forest’ land cover types are included, and peatlands, regardless of their forest status ;
details very much depend on the operational details still depend on the operational
definition of ‘forest’ definition of ‘forest’
REDD++ = REALU = idem, + all transitions in land
REDD = idem, + (forest) degradation, or the
cover that affect C storage, whether peatland or
shifts to lower C‐stock densities within the
mineral soil, trees‐outside‐forest, agroforest,
forest; details very much depend on the
plantations or natural forest. It does not depend on
operational definition of ‘forest’
the operational definition of ‘forest’

85. Annex‐I Non‐ A REDD PEAT SLM Agricult. Alleviating
Emissions all Annex‐I / and intensi‐ rural
sectors CDM R SFM fication poverty
Export of wood Biofuel, agrocommodities
Non‐accountable
footprint

86. Reducing Emissions from All Land Uses: The
case for a whole landscape approach
A whole‐landscape approach
to reducing emissions and
managing carbon stocks can
help address the drivers of
deforestation, reduce
problems like leakage, and
enhance participation of
developing countries in a
REDD deal.

87. CGIAR Research Program on
Forests, Trees and Agroforestry

88. New disciplines
“CONSILIENCE: the methods and assumptions of any field of study
should be consistent with the known and accepted facts in other
disciplines” E.J. Wilson.
Social Transdisciplinary Biological
Sciences Sciences Sciences
Anthropology Landscape ecology Botany
Economy Ecological economy Ecology
Policy Genetics
Political ecology
Sociology Zoology
Land change …
…
Human ecology…

89. Best Practices Support on:
Where to plant – trees suitable for your area
What to plant – trees suitable for your purposes
Which to plant – sources of tree seeds
How to plant – good tree nursery practices
How to engage communities and scale up

90. Remember, people who support agroforestry
1. Live longer
2. Have more friends
3. Enjoy a better love life
Don’t believe it, then try it and see