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CLIMATE-‐SMART AGRICULTURE: ADAPTATION, MITIGATION AND FOOD
SECURITY IN THE LAND SECTOR
Brownbag Friday Seminar UNEP, Nairobi, 27 February 2015
Henry Neufeldt World Agroforestry Centre (ICRAF)
What will we call the boundaries of Safe(r) operaTng spaces for the food systems?
Commission on Sustainable Agriculture and Climate Change 2012
Climate change impacts on yields
9.5-‐14.7 Gt CO2e (19-‐29%)
7.6-‐12.4 Gt CO2e (15-‐25%)
5.4-‐5.8 Gt CO2e (10-‐12%)
direct
indirect
global food system
Emissions from agricultural producNon, conversion of land and pre-‐ and postproducNon processes
EsNmated historical and projected GHG emissions
Smith et al in IPCC AR4 GWIII, 2007
• 38% as N2O from soils • 32% as CH4 from ruminant enteric fermentaNon • 12% mainly as N2O and CH4 through biomass burning • 11% mainly as CH4 in rice producNon • 7% as N2O and CH4 from manure management
Smith et al in IPCC AR5 GWIII, 2014
AFOLU emissions for the last four decades
Smith et al in IPCC AR5 GWIII, 2014
Global esNmates of costs and potenNals in the AFOLU sector
Short term Long term
Food security
MiNgaNon AdaptaNon
Small scales
Large scales
Climate-‐smart agriculture
Efficiency
Fairness
Food Systems
Three major stages of scaling up
Examples of no-‐Nll pracNces in different countries
GHG miNgaNon through no-‐Nll in selected countries
Country( Climate(zone(( Estimated(base(year(
Area((2007/8(
Mitigation(mean(and(range(
! ! ! (ha)! (Mt!CO2e)!
Australia! warm4dry! 1976! 17,000,000! !!95! 4209! 403!New!Zealand! cool4moist! 1993! 162,000! !!!!!!!0.7! !!!!!!!40.1! !!!!!!!1.4!
China! cool4dry! 2000! 2,000,000! !!!!!!!1.6! !!!!!!!44.9! !!!!!!!8.1!Kazakhstan! cool4dry! 2006! 1,200,000! !!!!!!!0.2! !!!!!!!40.6! !!!!!!!1.0!
USA! cool4moist! 1974! 26,500,000! 241! !!418! 510!Canada! cool4moist! 1985! 13,481,000! !!82! !!!!46! 174!
Brazil! warm4moist! 1992! 25,502,000! 146! !!489! 382!Argentina! warm4moist! 1993! 19,719,000! 109! !!467! 287!
Bolivia! warm4moist! 1996! 706,000! !!!!!!!3.1! !!!!!!!41.9! !!!!!!!8.1!Uruguay! warm4moist! 1999! 655,100! !!!!!!!2.0! !!!!!!!41.2! !!!!!!!5.3!
!
Modified from UNEP Emissions Gap Report, 2013
System of rice intensificaNon as an example of improved nutrient and water management
Uphoff, 2012
Review of SRI management impacts on yield, water saving, costs of producNon and farmer income per ha in 13 countries Average: +50% yield -‐37.5% water use -‐16% costs +94% income
Uphoff 2012
Evergreen agriculture with
Faidherbia albida
GHG miNgaNon through agroforestry by regions
Region Annual rate 2000-‐2010 2011-‐2030 (Mt CO2/yr) (Mt CO2) (Mt CO2)
North America 24.6 270 491 Central America 10.1 111 201 South America 157.3 1,730 3,145 Europe 7.2 79 144 N Africa + W Asia 2.7 29 53 Sub-‐Saharan Africa 10.0 110 201 N + Central Asia -‐4.0 -‐44 -‐79 South Asia 23.5 258 469 South-‐East Asia 23.8 262 477 East Asia 36.2 398 723 Oceania 19.2 211 384 Globe 262.8 2,891 5,256
% Gt CO2/yr 0 0.26 20 0.37 25 0.39 30 0.41 50 0.47
SUSTAINABILITY CHALLENGES – LAND USE
Food vs. Fuel
Pastoral Land Use
Biodiversity
Watershed
Land Use – Socioeconomic & Environmental Sustainability
InnovaTon and food security
RelaNonship between innovaNveness (number of farming system changes) and household food security (number of food deficit months). Error bars indicate the 95% confidence interval of the mean
Kristjanson et al 2012
• Farmers most interested in reducing food insecurity • No long-‐ or medium-‐term planning possible under food insecure situaNon • Tree planNng (and other investments in livelihood improvements) only
aaer basic food security is guaranteed • Food insecurity rose by at least one month (above on average 3 months)
during drought and flooding • Coping strategies lead into ‘poverty trap’ • Agroforestry reduced food insecurity by about 1 month
All #s in %
Reduce QuanNty, Quality or # of meals
Comm-‐unity or family support
Help from Gov, NGO, Church
Borrow money
Casual Labor
Sell possess-‐ions or livestock
Consume Seeds
Children agend school less
Lower Nyando
85 30 42 32 28 72 72 38
Middle Nyando
38 23 18 37.5 25 40 61 12.5
Farmer climate coping strategies
Thorlakson and Neufeldt 2012
• Provide an enabling legal and poliNcal environment • Improve market accessibility • Involve farmers in the project-‐planning process • Improve access to knowledge and training • Introduce more secure tenure • Overcome the barriers of high opportunity costs to
land • Improve access to farm implements and capital
Thorlakson and Neufeldt, 2012
Barriers to adopNon of CSA in smallholder agriculture
GENDER ¢ What is the research that will provide evidence how women can benefit more? • Beger access to credits, income generaNng acNviNes and
fuel wood can help build producNve assets • ParNcipaNon in SLM projects is heavily influenced by
social norms and intra-‐household decision-‐making • Men and women value non-‐cash benefits of the projects,
including beger communicaNon and changing roles • Progress toward gender equity requires agenNon to
agency, structure and relaNons defining interacNons • New spaces for interacNon can open up opportuniNes • An iteraNve learning approach can improve project
success and gender equity outcomes • Focusing on CSA rather than carbon can enhance benefits
accruing to women in parNcular Bernier et al 2013
Increase in area under culNvaNon from 42% to 63%
Constraints: insecure tenure
Economic, Environmental and Social Impacts Unadjud Freehold Tenure
Effect Net returns to land ($ ha-‐1 y-‐1) $126 $288 2.28 Woody crops, woodlots etc (ha km-‐2) 5.4 25.6 4.7 Hedgerows (km km-‐2) 5.2 23.6 4.5 Social cost from embedding -‐$40 $30 $70 Social "tax" -‐32% +10% Norton-‐Griffiths 2012
... an increase of 1.3 million hectares at a rate of 1.4% per year
IMPACT OF TENURE ON TREE COVER AND AGROFORESTRY
Adjudicated Unadjudicated
Financial benefits of no-‐Nll wheat producNon in northern Kasakhstan
Derpsch et al 2010
Recommendation 1: Integrate food security and sustainable agriculture into global and national policies
Recommendation 2: Significantly raise the level of global investment in sustainable agriculture and food systems in the next decade
Recommendation 3: Sustainably intensify agricultural production while reducing greenhouse gas emissions and other negative environmental impacts of agriculture
Recommendation 4: Target populations and sectors that are most vulnerable to climate change and food insecurity
Recommendation 5: Reshape food access and consumption patterns to ensure basic nutritional needs are met and to foster healthy and sustainable eating habits worldwide
Recommendation 6: Reduce loss and waste in food systems, particularly from infrastructure, farming practices, processing, distribution and household habits
Recommendation 7: Create comprehensive, shared, integrated information systems that encompass human and ecological dimensions
Phot
o: N
. Pal
mer
(CIA
T)
Toward Tier 3 Sustainability—Toward risk miTgaTon and resilience in food systems
Commission on Sustainable Agriculture and Climate Change 2012
Discovery, tesNng and implementaNon of mechanisms across scales that allow for adapNve management and adapNve governance of social-‐ecological systems essenNal for long-‐term human provisioning Development of integrated metrics of safe space that are pracNcal and meaningful for decision-‐making by relevant communiNes in near real Nme SystemaNc gathering and integraNon of quality data and informaNon to generate knowledge in Nme frames and at scales relevant for decision-‐making through analyNcal tools, models and scenarios Establishment of legiNmate and empowered science policy dialogues that frame post–disciplinary science agendas on local, naNonal and internaNonal scales
Key areas of science innovaNon
Neufeldt, Jahn et al 2013
What is the Process?
The Support Hub for Evidence-based Decision-making (SHED) is a demand-driven engagement structure for co-learning and subsequent co-negotiation of actions to achieve mutually agreed upon development outcomes.
shiftingdecision culture
for sustainable development.
ICRAF: United Nations Avenue, Gigiri, Nairobi, Kenya
[email protected] | +254 717 743 496www.agroforestry.com
It supports that decision-making must be able to embrace complexity across various developmental goals and investments, by facilitating integration across knowledge systems, sectors and institutions to support decision-making.
�� Decisions can be tested towards long-term V\[JVTLZ�HUK�PTWHJ[Z��PUJS\KPUN�X\HU[P�JH[PVU�VM�HSS�relevant variables and their uncertainties.
�� Emphasis placed on science and experience based, facilitated co-learning and integration across knowledge systems (research, practice and policy).
�� Embraces the complexity of decision-making across various developmental goals and investments, enabling decision makers to think VWLUS`�IL`VUK�H�ZWLJP�J�PU]LZ[TLU[�VY�NVHS��HZZLZZ�risks and explore diverse development trajectories.
�� The SHED provides decision makers with tools, methods and learning opportunities on science-based approaches to improving decision quality in sustainable development.
�� Decision makers, with knowledge resource persons, can identify with response options that provide the greatest potential for sustainable development returns on investment.
�� Negotiations are based on a much stronger foundational, science-based understanding of implications and necessary changes in behavior.
Unique attributes
Evidence-based decision-making is increasingly viewed as integral to advancing impacts by addressing
risk and improving returns on investment to achieve
sustainable development.
The Support Hub for Evidence-based Decision-making (SHED) is a demand-driven engagement structure for co-learning and subsequent co-negotiation of actions to achieve mutually agreed upon development outcomes.
shiftingdecision culture
for sustainable development.
ICRAF: United Nations Avenue, Gigiri, Nairobi, Kenya
[email protected] | +254 717 743 496www.agroforestry.com
It supports that decision-making must be able to embrace complexity across various developmental goals and investments, by facilitating integration across knowledge systems, sectors and institutions to support decision-making.
�� Decisions can be tested towards long-term V\[JVTLZ�HUK�PTWHJ[Z��PUJS\KPUN�X\HU[P�JH[PVU�VM�HSS�relevant variables and their uncertainties.
�� Emphasis placed on science and experience based, facilitated co-learning and integration across knowledge systems (research, practice and policy).
�� Embraces the complexity of decision-making across various developmental goals and investments, enabling decision makers to think VWLUS`�IL`VUK�H�ZWLJP�J�PU]LZ[TLU[�VY�NVHS��HZZLZZ�risks and explore diverse development trajectories.
�� The SHED provides decision makers with tools, methods and learning opportunities on science-based approaches to improving decision quality in sustainable development.
�� Decision makers, with knowledge resource persons, can identify with response options that provide the greatest potential for sustainable development returns on investment.
�� Negotiations are based on a much stronger foundational, science-based understanding of implications and necessary changes in behavior.
Unique attributes
Evidence-based decision-making is increasingly viewed as integral to advancing impacts by addressing
risk and improving returns on investment to achieve
sustainable development.
The Support Hub for Evidence-based Decision-making (SHED) is a demand-driven engagement structure for co-learning and subsequent co-negotiation of actions to achieve mutually agreed upon development outcomes.
shiftingdecision culture
for sustainable development.
ICRAF: United Nations Avenue, Gigiri, Nairobi, Kenya
[email protected] | +254 717 743 496www.agroforestry.com
It supports that decision-making must be able to embrace complexity across various developmental goals and investments, by facilitating integration across knowledge systems, sectors and institutions to support decision-making.
�� Decisions can be tested towards long-term V\[JVTLZ�HUK�PTWHJ[Z��PUJS\KPUN�X\HU[P�JH[PVU�VM�HSS�relevant variables and their uncertainties.
�� Emphasis placed on science and experience based, facilitated co-learning and integration across knowledge systems (research, practice and policy).
�� Embraces the complexity of decision-making across various developmental goals and investments, enabling decision makers to think VWLUS`�IL`VUK�H�ZWLJP�J�PU]LZ[TLU[�VY�NVHS��HZZLZZ�risks and explore diverse development trajectories.
�� The SHED provides decision makers with tools, methods and learning opportunities on science-based approaches to improving decision quality in sustainable development.
�� Decision makers, with knowledge resource persons, can identify with response options that provide the greatest potential for sustainable development returns on investment.
�� Negotiations are based on a much stronger foundational, science-based understanding of implications and necessary changes in behavior.
Unique attributes
Evidence-based decision-making is increasingly viewed as integral to advancing impacts by addressing
risk and improving returns on investment to achieve
sustainable development.
Support-‐Hub for Evidence-‐based Decision-‐making (SHED)
The Support Hub for Evidence-based Decision-making (SHED) is a demand-driven engagement structure for co-learning and subsequent co-negotiation of actions to achieve mutually agreed upon development outcomes.
shiftingdecision culture
for sustainable development.
ICRAF: United Nations Avenue, Gigiri, Nairobi, Kenya
[email protected] | +254 717 743 496www.agroforestry.com
It supports that decision-making must be able to embrace complexity across various developmental goals and investments, by facilitating integration across knowledge systems, sectors and institutions to support decision-making.
�� Decisions can be tested towards long-term V\[JVTLZ�HUK�PTWHJ[Z��PUJS\KPUN�X\HU[P�JH[PVU�VM�HSS�relevant variables and their uncertainties.
�� Emphasis placed on science and experience based, facilitated co-learning and integration across knowledge systems (research, practice and policy).
�� Embraces the complexity of decision-making across various developmental goals and investments, enabling decision makers to think VWLUS`�IL`VUK�H�ZWLJP�J�PU]LZ[TLU[�VY�NVHS��HZZLZZ�risks and explore diverse development trajectories.
�� The SHED provides decision makers with tools, methods and learning opportunities on science-based approaches to improving decision quality in sustainable development.
�� Decision makers, with knowledge resource persons, can identify with response options that provide the greatest potential for sustainable development returns on investment.
�� Negotiations are based on a much stronger foundational, science-based understanding of implications and necessary changes in behavior.
Unique attributes
Evidence-based decision-making is increasingly viewed as integral to advancing impacts by addressing
risk and improving returns on investment to achieve
sustainable development.
Each phase unpacks to reveal elaborated
process steps
ArVculated goal to implementaVon
pathway
Entry point is appropriate to client
Non Linear Process
¢ Using SHED Principles: linked diverse knowledge systems to advance CSA in Kenya
¢ Researchers, development actors, farmer leaders, and the GOK Climate Change Unit convened to share scienNfic and experienNal evidence from 44 projects
¢ A synthesized and coherent technical presentaNon was delivered to the CC Secretariat and policy messages developed to be inpuged to Kenya Climate Change Policy Framework and a brief prepared for the COP-‐20.
¢ Technical Brief forthcoming in March 2015
Current Cases
The Support Hub for Evidence-based Decision-making (SHED) is a demand-driven engagement structure for co-learning and subsequent co-negotiation of actions to achieve mutually agreed upon development outcomes.
shiftingdecision culture
for sustainable development.
ICRAF: United Nations Avenue, Gigiri, Nairobi, Kenya
[email protected] | +254 717 743 496www.agroforestry.com
It supports that decision-making must be able to embrace complexity across various developmental goals and investments, by facilitating integration across knowledge systems, sectors and institutions to support decision-making.
�� Decisions can be tested towards long-term V\[JVTLZ�HUK�PTWHJ[Z��PUJS\KPUN�X\HU[P�JH[PVU�VM�HSS�relevant variables and their uncertainties.
�� Emphasis placed on science and experience based, facilitated co-learning and integration across knowledge systems (research, practice and policy).
�� Embraces the complexity of decision-making across various developmental goals and investments, enabling decision makers to think VWLUS`�IL`VUK�H�ZWLJP�J�PU]LZ[TLU[�VY�NVHS��HZZLZZ�risks and explore diverse development trajectories.
�� The SHED provides decision makers with tools, methods and learning opportunities on science-based approaches to improving decision quality in sustainable development.
�� Decision makers, with knowledge resource persons, can identify with response options that provide the greatest potential for sustainable development returns on investment.
�� Negotiations are based on a much stronger foundational, science-based understanding of implications and necessary changes in behavior.
Unique attributes
Evidence-based decision-making is increasingly viewed as integral to advancing impacts by addressing
risk and improving returns on investment to achieve
sustainable development.
The Support Hub for Evidence-based Decision-making (SHED) is a demand-driven engagement structure for co-learning and subsequent co-negotiation of actions to achieve mutually agreed upon development outcomes.
shiftingdecision culture
for sustainable development.
ICRAF: United Nations Avenue, Gigiri, Nairobi, Kenya
[email protected] | +254 717 743 496www.agroforestry.com
It supports that decision-making must be able to embrace complexity across various developmental goals and investments, by facilitating integration across knowledge systems, sectors and institutions to support decision-making.
�� Decisions can be tested towards long-term V\[JVTLZ�HUK�PTWHJ[Z��PUJS\KPUN�X\HU[P�JH[PVU�VM�HSS�relevant variables and their uncertainties.
�� Emphasis placed on science and experience based, facilitated co-learning and integration across knowledge systems (research, practice and policy).
�� Embraces the complexity of decision-making across various developmental goals and investments, enabling decision makers to think VWLUS`�IL`VUK�H�ZWLJP�J�PU]LZ[TLU[�VY�NVHS��HZZLZZ�risks and explore diverse development trajectories.
�� The SHED provides decision makers with tools, methods and learning opportunities on science-based approaches to improving decision quality in sustainable development.
�� Decision makers, with knowledge resource persons, can identify with response options that provide the greatest potential for sustainable development returns on investment.
�� Negotiations are based on a much stronger foundational, science-based understanding of implications and necessary changes in behavior.
Unique attributes
Evidence-based decision-making is increasingly viewed as integral to advancing impacts by addressing
risk and improving returns on investment to achieve
sustainable development.
Climate Smart Agriculture Case
The Support Hub for Evidence-based Decision-making (SHED) is a demand-driven engagement structure for co-learning and subsequent co-negotiation of actions to achieve mutually agreed upon development outcomes.
shiftingdecision culture
for sustainable development.
ICRAF: United Nations Avenue, Gigiri, Nairobi, Kenya
[email protected] | +254 717 743 496www.agroforestry.com
It supports that decision-making must be able to embrace complexity across various developmental goals and investments, by facilitating integration across knowledge systems, sectors and institutions to support decision-making.
�� Decisions can be tested towards long-term V\[JVTLZ�HUK�PTWHJ[Z��PUJS\KPUN�X\HU[P�JH[PVU�VM�HSS�relevant variables and their uncertainties.
�� Emphasis placed on science and experience based, facilitated co-learning and integration across knowledge systems (research, practice and policy).
�� Embraces the complexity of decision-making across various developmental goals and investments, enabling decision makers to think VWLUS`�IL`VUK�H�ZWLJP�J�PU]LZ[TLU[�VY�NVHS��HZZLZZ�risks and explore diverse development trajectories.
�� The SHED provides decision makers with tools, methods and learning opportunities on science-based approaches to improving decision quality in sustainable development.
�� Decision makers, with knowledge resource persons, can identify with response options that provide the greatest potential for sustainable development returns on investment.
�� Negotiations are based on a much stronger foundational, science-based understanding of implications and necessary changes in behavior.
Unique attributes
Evidence-based decision-making is increasingly viewed as integral to advancing impacts by addressing
risk and improving returns on investment to achieve
sustainable development.
LAND HEALTH SURVEILLANCE
Consistent field protocol
Soil spectroscopy Coupling with remote sensing Prevalence, Risk factors, Digital mapping
Sentinel sites Randomized sampling schemes
Marshall et al. (2012) • Declines in evapotranspiraNon are expected to conNnue over much of the Sahelo-‐Sudan mid-‐21st century [A]
• Recent and rapid expansion of agricultural land use • Decline in indirect moisture
recycling [B] • Direct and local moisture
decoupling [C] • Forests, reforestaNon, and afforestaNon
through agroforestry could lead to less rainfall variability…
A
C Koster et al. (2006)
Spracklen and Taylor (2012)
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
0
200
400
600
800
1000
1796
1801
1806
1811
1816
1821
1826
1831
1836
1841
1846
1851
1856
1861
1866
1871
1876
1881
1886
1891
1896
1901
1906
1911
1916
1921
1926
1931
1936
1941
1946
1951
1956
1961
1966
1971
1976
1981
1986
1991
1996
2001
2006
Inde
x
Rainfall (m
m)
Years
Rainfall(mm) Master chrono
• Up-‐front public sector finance needed to turn projects viable • Projects build insNtuNonal capacity • Projects deliver food security and adaptaNon with miNgaNon co-‐benefits • Insurance schemes provide safety nets against falling into the poverty trap • Combining many and diverse investments in land can increase returns and drive
large-‐scale investment in sustainable NRM • Robust M+E frameworks are needed to quanNfy how different CSA pracNces reduce
climate risk
Foster et al 2013
• Set up at least one biocarbon project in Burkina Faso and Sierra Leone
• Develop the carbon projects from the incepNon phase to commercial level as viable and tangible development outcomes
• Include AFOLU, REDD and a combinaNon of REDD/AFOLU projects
• Include wood fuels in the carbon projects
• Include CA, water management, biodiversity benefits, etc. where it makes sense
• Build the capacity at naNonal and regional scales that allow scaling up
BIODEV concrete measures
Diagram of Bio-‐C project potenTal structure
Climate-‐smart agriculture1 pracNces can contribute to food security of resource-‐poor rural populaNons while providing important adaptaNon and miNgaNon co-‐benefits if they are adapted to local condiNons
and naNonal policies, and global food systems are in tune with sustainable development goals.
1Agriculture is understood to consist of crops, livestock, forests, fisheries and aquaculture
Key messages
In order to maximize the synergies between the three pillars (producNon, adaptaNon, miNgaNon)
agricultural policies should consider mulNple targets from the outset, and research is needed that idenNfies the relaNve contribuNons of different
pracNces to each of the pillars.
Key messages
Overcoming barriers to adopNon of climate-‐smart agriculture for long-‐term transformaNon toward sustainable management of resources requires: naNonal agriculture development plans with
appropriate insNtuNons at naNonal to local levels; provision of infrastructure; access to informaNon and training; access to capital and insurance; stakeholder parNcipaNon; and, last but not least, improvement of
tenure arrangements.
Key messages
Investment in improved natural resource management through climate finance can provide
essenNal livelihood (through improved and diversified income, strengthened insNtuNonal
capacity, reduced climate risk) and global miNgaNon benefits if high investment risks and low returns on
investment can be overcome.
Key messages
Thanks for a future