climate - smart agriculture: adaptation, mitigation andfood security in the land sector

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


AFOLU emissions for the last four decades


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[PÄ�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�ZWLJPÄ�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.













Unique attributes
















Unique attributes




Support-‐Hub for Evidence-‐based Decision-‐making (SHED)













Unique attributes




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













Unique attributes
















Unique attributes




Climate Smart Agriculture Case













Unique attributes




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)

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m)

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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