P U R L A B M E A S U R I N G T H E I M P A C T O F S U S T A I - - PowerPoint PPT Presentation

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P U R L A B

M E A S U R I N G T H E I M P A C T O F S U S T A I N A B L E I N V E S T M E N T S I N S U P P L Y C H A I N

C O N T E N T

T H E P U R L A B M E T H O D O L O G Y P A R T N E R S H I P S A N D S T U D I E S O P P O R T U N I T I E S F O R P A R T N E R S H I P P I C T U R E S A P P E N D I X

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T H E P U R L A B ’ S P U R P O S E

TO IDENTIFY, MEASURE, AND VALUE ALL THE SERVICES (ENVIRONMENTAL, SOCIAL, CORPORATE) PROVIDED BY COMMUNITY AGROFORESTRY PROJECTS IN SUPPLY CHAINS Our core principles: scientific, holistic, transparent A collaboration between PUR PROJET, local partners, universities, research institutes, and companies investing in their supply chain

“[…] Not everything that counts can be counted, and not everything that can be counted counts.” W.Bruce Cameron PUR Lab is the research and expertise branch of PUR Projet. It is responsible for developing high level protocols and impact assessments methodologies. Together with several universities and experts, PUR Lab is able to respond to today’s challenges with scientifically sound solutions. Profoundly engaged with the world’s future, PUR Lab proposes multi-level and interdisciplinary approaches using modern techniques for a better tomorrow.

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C O N T E X T

IMPACTS OF COMMUNITY AGROFORESTRY PROJECTS ARE UNDERESTIMATED

• Trees provide free ecosystem services that are

traditionally not valued

• Additionally, PUR PROJET’s model provides social

and community benefits

• Finally, Insetting (sustainable investment within the

supply chain itself) represents new benefits for companies THERE IS A GROWING DEMAND FOR MORE DIVERSIFIED AND COMPREHENSIVE SIGNALS

• Companies need to demonstrate the benefits of

integrated agro-ecological and fair practices in their supply chain

• All services have to be considered jointly

Slash and burn, Peru

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S T A K E H O L D E R S

U N I V E R S I T I E S A N D R E S E A R C H I N S T I T U T E S

• Provide students and

researchers for field studies

• Bring scientific

background and support (validity of protocols, data interpretation)

• Bring support for

scientific publications

• Host thesis in

specialized research lab C O M P A N I E S I N V E S T I N G I N S U P P L Y C H A I N S U S T A I N A B I L I T Y

• Assist in implementing measurement

protocols within their supply chain

• Share their expertise on quality, supply

and market

• Participate in thesis and research work

P U R P R O J E T A N D L O C A L F A R M E R S G R O U P S

• Develop agroforestry

projects

• Implement measurement

protocols P U R P R O J E T

• Define global approach

and framework methodology

• Facilitate researchers’ field

work and logistics

• Compile and analyse all

research data and results

• Provide linkage between

academic and corporate stakeholders

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O R G A N I Z A T I O N

CORE TEAM

Marina Gavaldão Technical Director Arthur Rouanet Research Engineer

PUR LAB EXPERTS NETWORK

Bachelor Students Field technicians Eugenio Osvelí Silvestre Hernández, Guatemala Master Students PhD students Researchers Institutional experts

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Increase knowledge on community agroforestry and insetting

Our activities stimulate research on community reforestation benefits, beyond ecosystem services.

M I S S I O N

SERVICES QUANTIFICATION AND VALUATION KNOWLEDGE DEVELOPMENT Scientifically quantify and value the services provided Demonstrate the outstanding benefits of community agroforestry in agri-supply chains

We apply valuation methods and develop protocols from multiple research works, measuring the services generated by our projects. The valuation of ecosystems services permits to quantify the real return of a sustainable investment in agri-supply chains. We create simple communication tools to disseminate results. We develop protocols with students from local and northern countries universities. Experts and students share cutting-edge knowledge and expertise. Through our studies, we are able to create learning platforms to promote knowledge transfer.

Favor North-South university exchanges Raise awareness and education level of local populations on ecosystem and social services

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C O R E T E A M

MARINA GAVALDÃO, TECHNICAL DIRECTOR AND PROJECT MANAGER EUROPE Education:

• Forestry Engineering at the Superior School of agriculture “Luiz de Queiroz” (ESALQ),

University of São Paulo (USP), Brazil

• Master of Sciences in Development Studies: “Global ecology and sustainable

development”, University of Geneva, Switzerland Countries of experience:

• Latin America: Brazil
• Europe: France, Switzerland, United Kingdom, Germany and Portugal
• Asia: Cambodia, Afghanistan, Tajikistan, Northern India, Indonesia and Malaysia
• Africa: Mali, Benin, Burkina Faso, Senegal, Cameroon, DRC and Mozambique

10 years of work experience:

• Technical director of the climate change unit, GERES, France
• Independent consultant for GIZ, FAO, TNC (The Nature Conservancy) and EFECA

Publications on PES (payment for ecosystem services), climate change mitigation, carbon markets and socio-environmental and economic impacts. ARTHUR ROUANET, RESEARCH ENGINEER Education:

• Engineer's degree, Engineering Economics, Ecole des Ponts ParisTech, France
• Master of Science (MSc), EDDEE - Sustainable Development, Environmental and

Energy Economics, AgroParisTech, France Countries of experience:

• Latin America: Guatemala, Honduras, Peru, Argentine
• Africa: Togo

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T o o l s a n d p l a t f o r m s

P R O C E S S

TOOLS

• PUR

LAB bibliography: public scientific papers related to each indicator

• rganized

by service, geography, commodity, etc.

• PUR

LAB database: results

• f

the research conducted within the frame of PUR LAB

• Teaching and background material on community

agroforestry and insetting PLATFORMS

• Technical

advisory board (scientific partners, participating companies, PUR LAB)

• Recommendations on scientific validity, quality
• f methodology
• Revision
• f

research results: coherence, quality

• Recommendations on publications
• Public Website and blog: display the methodology,

the on-going research and the results

Farmer’s training, Pur Projet and Fundavi, Peru

C O N T E N T

T H E P U R L A B M E T H O D O L O G Y P A R T N E R S H I P S A N D S T U D I E S O P P O R T U N I T I E S F O R P A R T N E R S H I P P I C T U R E S A P P E N D I X

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O V E R A L L A P P R O A C H

Identification and classification of all services provided 7 categories : soil, water, biodiversity, climate, livelihood, population, corporate

1

Services quantification Selection of an indicator to measure the service level Based on a review of a thousand scientific studies

2

Services economic valuation Application of valuation methods to each service

3

Definition of field measurement protocols Specific to each service Easy to implement Universal Integrated to field operations

4

Iterative development and improvement Reflection upon indicators behaviour Study of new scientific papers Consideration of new possible protocols

6

Continuous measurement of services Application of tested protocols Data collection and interpretation

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Identification of 7 categories of services. For each category, identification of logic, exhaustive and non redundant sub- services: 49 in total*.

4 9 s e r v i c e s S E R V I C E S C L A S S I F I C A T I O N

C O M M U N I T Y A G R O F O R E S T R Y P R O J E C T S

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S O I L W A T E R P O P U L A T I O N B I O D I V E R S I T Y C L I M A T E L I V E L I H O O D C O R P O R A T E Soil enrichment Landslide and erosion avoided Better water quality Cycle regulation Stock increase Social cohesion Culture conservation Regulation Pollinisation Conservation Mitigation Adaptation Economic development Activity diversification Supply chain Brand equity Human resources

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• Soil organic carbon content enrichment
• Soil nitrogen content enrichment
• Soil microbial activity enhancement
• Soil salinity reduction
• Soil pollution remediation
• Soil fixation
• Landslide frequency diminution
• Indirect erosion damage reduction
• Nitrate pollution reduction
• Phosphate pollution reduction
• Pesticide pollution reduction
• Water turbidity reduction
• Flooding frequency reduction
• Water local holding capacity enhancement
• Water input enhancement by fog dripping
• Inter-species favorable allelopathic interactions

enhancement

• Pollination rate enhancement
• Integrated pest control
• Biodiversity preservation for conservation
• Carbon sequestration
• Nitrous oxide emission reduction
• Microclimatic regulation
• Wind breaking effect
• Protection against natural catastrophes

C L A S S I F I C A T I O N 1 / 2

1- SOIL 1.1 Soil quality 1.2 Soil quantity 2 - WATER 4 - CLIMATE 3 - BIODIVERSITY 2.1 Water quality 2.2 Water quantity 3.1 Support 3.2 Conservation 4.1 Mitigation 4.2 Adaptation

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• Timber production
• Fruit production
• Self-sufficiency goods production
• Endemic species identification for agroforestry
• Economic development capacity enhancement
• Complementary activity development
• Animal productivity enhancement
• Agriculture and forestry revenue stabilization
• Endemic spread reduction
• Atmospheric pollution reduction
• Noise pollution reduction
• Illicit crop area reduction
• Support social peace establishment
• Natural resource protection from looting
• Traditional culture and know-how conservation
• Agri-food commodity quality enhancement
• Supplier timing and volume reliability
• Transaction costs reduction
• Logistic costs reduction
• Anticipation of future supply shortage
• Environmental responsibility image
• Social responsibility image
• Employees performance
• Better job-seekers attraction
• Employees satisfaction and wellness enhancement

C L A S S I F I C A T I O N 2 / 2

7 - CORPORATE 7.1 Supply chain 7.2 Brand equity 7.3 Human resources 6 - POPULATION 5 –LIVELIHOOD 5.1 Tree products 5.2 Activity diversification 6.1 Health 6.2 Local society stability 6.3 Cultural livelihood

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S E R V I C E S Q U A N T I F I C A T I O N A N D V A L U A T I O N

Quantification of the services

• Methodology based on a review of a thousand

scientific publications

• Selection of an indicator to quantify the level of

service, following SMART criteria Example “Soil fixation” indicator is the reduction in loss of arable land due to erosion, in kg/ha/year. Economic valuation of the services

• Application
• f

valuation methods to each service (cost of alternative, cost of damages, etc.) Example “Soil fixation” service: the avoided loss of arable land can be assessed using its potential yield.

2 3

S M A R T c r i t e r i a

• Specific: accurately refer to a single service.
• Measurable:

specify thresholds that are measurable at a reasonable cost.

• Achievable:

should not require excessive technical, financial or resource inputs.

• Relevant:

focussed

• n

achieving management objectives.

• Tangible:

defined clearly and free from subjective elements.

E(c+) = 2,4241(V) - 1,1062 R² = 0,8128 E(c-) = 6,6569(V) - 3,5679 R² = 0,8173 0,00 20,00 40,00 60,00 80,00 100,00 120,00 5 10 15 20 25 30 35

Example of erosion measurement results

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Service

• Soil organic carbon content enrichment
• Soil nitrogen content enrichment
• Soil microbial activity enhancement
• Landslide frequency diminution
• Soil fixation
• Phosphate/Nitrate pollution reduction
• Water turbidity reduction
• Flooding frequency reduction
• Atmospheric water holding capacity
• Water local holding capacity enhancement
• Pollination rate enhancement
• Integrated pest control
• Biodiversity preservation for conservation value
• Carbon sequestration
• Nitrous oxide emission reduction
• Protection against natural catastrophes
• Microclimatic regulation
• Timber sales
• Self-sufficiency goods production (fuel-wood, spices, herbs, construction)
• Economic development capabilities enhancement
• Complementary activity development (bee heaving, tree nurseries)
• Agriculture and forestry revenue stabilization
• Epidemic spread reduction
• Illicit crop area reduction
• Support social peace establishment / insecurity reduction
• Natural resource protection from looting
• Traditional culture and know-how conservation
• Agri-food commodity quality enhancement
• Reduction of transaction costs
• Supplier volume and timing reliability
• Anticipation of future supply shortages
• Environmental responsibility image
• Social responsibility image
• Employees performance
• Better job-seekers attraction
• Employees satisfaction and welfare enhancement

E X A M P L E O F E C O N O M I C V A L U A T I O N

5 yrs 15 yrs 20 yrs 10 yrs 25 yrs Project implementation, Investment: 6000 $/ha

1500 $/ha/yr 2000 $/ha/yr 1000 $/ha/yr 100 $/ha/yr 200 $/ha/yr 150 $/ yr 800 $ / yr 100 $/ha/yr 130 $/ha/yr 200 $/ha/yr 1000 $/ha/yr 40 $/ yr 500 $/ha/yr 600 $ / yr 50 $/ha/yr 100 $/ha/yr 2000 $ / yr 1200 $ / yr 500 $ / yr 300 $/ha/yr 800 $/ha/yr 4000 $/ha/yr

800 $/ha/yr

150 $/ha/yr 100 $/ yr 100 $/ha/yr To be defined 1500 $/ha/yr 500 $/ha/yr To be defined To be defined To be defined 50 $/ha/yr 30 $/ha/yr 100 $/ha/yr

1 8 7 0 0 $ / y e a r / h a

Coffee farming / coffee buyer, Peru, Oro Verde

* Average values, based on literature and overall projects data. Needs to be refined with monitored data from specific project.

SOIL WATER BIODIVERSITY CLIMATE LIVELIHOOD POPULATION CORPORATE

3

Total potential economic value =

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F I E L D M E A S U R E M E N T P R O T O C O L S

Definition of measurement protocols According to service: generic protocol applicable in all projects, or specific protocol adapted to context

• Development of experimental methods
• Stratification of the area to perform measures
• n different profiles

Application of proof tested protocols

• Protocol implementation
• Protocol application over time: regular

collection of data on service measured

4 5

Shape and construction of the measurement device for erosion, Peru

C O N T E N T

T H E P U R L A B M E T H O D O L O G Y P A R T N E R S H I P S A N D S T U D I E S O P P O R T U N I T I E S F O R P A R T N E R S H I P P I C T U R E S A P P E N D I X

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P A R T N E R C O M P A N I E S

Tristan Lecomte with committed clients Field visit with clients in Ethiopia

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A C A D E M I C A N D I N S T I T U T I O N A L P A R T N E R S

U S A

Harvard UCLA Yale University

G U A T E M A L A

Universidad Rural, Universidad Rafael Landívar

H O N D U R A S

FHIA, UNA

C O L O M B I A

UniCauca, IWM, CENICAFE, Universidad Nacional UNAL

P E R U UNAS E T H I O P I A

University of Harare, dept. of zootechny, University of Wondo Genet,

• dept. of Forestry

ICRAF, World Agroforestry Centre

I N T E R N A T I O N A L

B E L G I U M ULB

F R A N C E

AgroParisTech, Supagro, ENSTIB, ONFI

G E R M A N Y

Adaptogether S W I T Z E R L A N D Bern BFH-HAFL

U K

UCL, Cambridge, Oxford

A S I A

University of Chiang Mai

• FORRU

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F I E L D S T U D I E S

G U A T E M A L A

2015

Soil Supagro & CENAF

2016

Biodiversity CENAF - ENCA

2015

Water Supagro

2016

Supply chain TBD

2015

Soil Yale University

2016

Biodiversity Unicauca & Cenicafé

2016

Water UniCauca & IWM & Supagro

2016

Livelihood Harvard

C O L O M B I A P E R U

2014

Soil UNAS & ENSAT

2014

Biodiversity UNAS

2014

Water San Martín & ENSAT

2014

Livelihood UCL & ENSTIB & UNAS & ULB

E T H I O P I A

Soil

• Univ. of Wondo

TBD

TBD

Biodiversity

• Univ. Of Wondo

TBD

Livelihood Harvard

2016

Soil UNA

2014-15

Biodiversity UNA

2014-15

H O N D U R A S

Livelihood Bern HAFL

2015

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A G R O F O R E S T R Y I M P A C T S O N S O I L F A U N A

CONTEXT

• Localization : Honduras, Olancho,

Aprosacao project

• Climate : Sub tropical humid
• Soil: Inceptisol (USDA

Classification)

• Crop: Cocoa

OUR PARTNER

• Universidad Nacional de

Agricultura, Honduras (UNA)

5 10 15 20 25 30

• L. Terrestris

Scolopendra Phyllophaga Total

Macro- biodiversity*

Full sun Agroforestry Reforested area Secondary forest

4 TIMES MORE MACRO ORGANISMS

IN AGROFORESTRY SYSTEMS THAN IN FULL SUN SYSTEMS

4 x

INFLUENCE OF LAND USE ON SOIL MACRO BIODIVERSITY

*Average number of individuals per 0,19m3 sample over various measurements

• Organic matter

decomposition

• Soil structuring
• Predation on

potential pest species

• Organic matter

decomposition

• Predation on potential

pest species

23 49% 39% 65% 35% 0% 20% 40% 60% 80% 100%

Percentage of healthy fruits

INFLUENCE OF TREE DENSITY ON HARVEST QUALITY AND YIELDS

100 200 300 400 500 600 High density Medium density Low density Full sun

Yields** (kg/ha)

A G R O F O R E S T R Y I M P A C T S O N Y I E L D S

CONTEXT

• Localization: Peru, San Martin, Alto

Huayabamba project

• Climate: Subtropical humid
• Soil: Inceptisol (USDA Classification)
• Crop: Cacao

OUR PARTNERS

• Université libre de Bruxelles, Belgium
• Universidad Agraria de la Selva, Peru

INCREASE OF 86% OF QUALITY* AND 62% OF COCOA YIELDS

IN CULTURE UNDER TREE SHADE VS FULL SUN

+84 % +62 %

38,6%

*Quality: rate of healthy fruit ** Harvests from July-August 2015 440 trees/ha 270 trees/ha 50 trees/ha 0 tree/ha

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A G R O F O R E S T R Y I M P A C T S O N E R O S I O N

78% SOIL LOSS REDUCTION

BY REFORESTING A BARE SOIL PLOT CONTEXT

• Localization: Peru, San Martin,

Alto Huayabamba project

• Climate: Subtropical humid
• Soil: Inceptisol (USDA

Classification)

• Slope: 47 %
• Crop: Cocoa

* Tons of eroded soil

OUR PARTNERS

• UNAS, Universidad Agraria de la

Selva, Peru

• ENSAT, École Nationale Supérieure

Agronomique de Toulouse, France

• Montpellier SupAgro, École

Nationale Supérieure Agronomique de Montpellier, France IMPACTS OF SOIL EROSION Land degradation

• Fertility loss (nutrients, organic

matter, biodiversity)

• Water storage capacity loss
• Soil organic carbon loss
• Exposed tree roots

Downstream water pollution

• Risk of eutrophication
• Turbidity
• 78 %
• 98 %

Bare soil: 53 tons lost/ha/year* Reforested area: 12 tons loss/ha/year* Secondary forest: 0,2 tons loss/ha/year*

C O N T E N T

T H E P U R L A B M E T H O D O L O G Y P A R T N E R S H I P S A N D S T U D I E S O P P O R T U N I T I E S F O R P A R T N E R S H I P P I C T U R E S A P P E N D I X

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U N I V E R S I T I E S A N D R E S E A R C H I N S T I T U T E S : S H A R E R E S O U R C E S A N D E X P E R T I S E

Contact: purlab@purprojet.com FIND STUDENTS ON CONVERGING RESEARCH TOPICS

• Identify convergences and synergies between

PUR Lab topics and university work

• Identify students willing to do their research

work on PUR Lab topics

• Supervise the students research work

SCIENTIFIC ADVISOR ROLE

• Review

PUR Lab’s methodologies, scientific protocols, results, and give recommendations on possible improvements

• Share

expertise and knowledge with

• ther

project’s partners

• Invite

project’s local stakeholders (local universities students, projects’ technical team) to classes/trainings on related topics Field visit with UNA’s head of natural resources departement, Honduras

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C O M P A N I E S : A C O L L A B O R A T I V E W O R K T O O P T I M I S E S U S T A I N A B L E I N V E S T M E N T

Contact: purlab@purprojet.com PUR LAB OUTPUTS SUSTAINABLE INVESTMENT IN SUPPLY CHAIN Feasibility assessment and project design Implementation of the plantations, in collaboration with cooperatives Overall monitoring of the project and reporting Ex ante Valuation of the services provided by the project Implementation

• f field

measurement protocols Ex post Quantification of the services provided and refined valuation of the project Communication tools presenting the results Extra value creation Optimisation of investment

C O N T E N T

T H E P U R L A B M E T H O D O L O G Y P A R T N E R S H I P S A N D S T U D I E S O P P O R T U N I T I E S F O R P A R T N E R S H I P P I C T U R E S A P P E N D I X

Pluviometer training, part of Nespresso impact study on soil erosion, Vista Hermosa, Unión Cantinil, Guatemala

Analysing soil physical and chemical properties with our partner Anacafé, Huehuetenango, Guatemala

Agroforestry erosion plot, Unión Cantinil, Huehuetenango, Guatemala

Deforested land, Cuyamel, Olancho, Honduras

Slash and burn, Alto Huayabamba, Peru

C O N T E N T

T H E P U R L A B M E T H O D O L O G Y P A R T N E R S H I P S A N D S T U D I E S O P P O R T U N I T I E S F O R P A R T N E R S H I P P I C T U R E S A P P E N D I X

A g r o f o r e s t r y i m p a c t s o n s o i l e r o s i o n

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C O N T E X T

IMPACTS OF SOIL EROSION Land degradation

• Fertility loss (nutrients, organic matter,

biodiversity)

• Water storage capacity loss
• Soil organic carbon loss
• Exposed tree roots

Downstream water pollution

• Risk of eutrophication
• Turbidity

OUR PARTNERS

• UNAS, Universidad Agraria de la Selva,

Peru

• ENSAT, École Nationale Supérieure

Agronomique de Toulouse, France

• Montpellier SupAgro, Ecole Nationale

Supérieure Agronomique de Montpellier, France Slash and burn on future cocoa field, San Martin, Peru

KEY NUMBERS

• In tropical region, it takes thousands years to form a few centimetres
• f soil. It is much more in cold regions. (Keeping the land alive,

FAO,1990)

• ”Erosion carries away 25 to 40 billion tons of topsoil every year”

according to FAO. (Status of the world’s soil resources, FAO, 2015)

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P R O T O C O L

OBJECTIVE

• To assess the impact of land use on soil loss and

runoff TREATMENTS AND REPETITIONS

• 5 years study
• 4 types of land use: monoculture, agroforestry,

reforested area, secondary forest

• 2 plots per land-use

METHOD

• Experimental crop method (Fournier, 1954): collecting

eroded soil and runoff from a 10m² artificial watershed Crop selection Study of crop characteristics Plots construction Soil loss measurement Data analysis Chemical and physical soil analysis to assess erosion risk Continuous measurement of soil loss and runoff after each precipitation Installation of 10m² - erosion plots

1 2 4 5 3

Assessment of the relationship between soil loss, runoff and precipitation Land use is a variable,

• ther parameters are

constant 5,0 m 2,0 m 10 m² - artificial watershed Collection system Constant slope

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P r o t o c o l i m p l e m e n t a t i o n

H U E H U E T E N A N G O - G U A T E M A L A

3 TYPES OF LAND USE: bare soil, coffee in monoculture, coffee in agroforestry 6 REPETITIONS: 2 plots per land use

Rain Gauge installation Erosion plot on bare soil

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R E S U L T S – A L T O H U A Y A B A M B A , P E R U

CONTEXT

• Climate: subtropical humid
• Soil: Inceptisol (USDA Classification)
• Slope: 47 %

FIRSTS RESULTS

• 78% soil loss reduction between bare soil

and reforested area

• The eroded soil by unit of runoff is higher on

bare soil than reforested area

• The relation between eroded soil and runoff is

quadratic: a major precipitation event leads to more eroded soil than several minor ones, for the same total runoff NEXT STEPS

• Enhancing statistical significance and extracting

new data from Peru (2 years results) and from Guatemala (1 year results)

y = 269,99x2 R² = 0,87 y = 331,51x2 + 832,4x R² = 0,8802 2 000 4 000 6 000 8 000 10 000 12 000 14 000 16 000 18 000 1 2 3 4 5 6 7 Eroded soil (kg/ha) Runoff (mm) P1 - Reforested area P2 - Bare soil

Correlation between eroded soil and runoff

* Tons of eroded soil

• 78 %
• 98 %

Bare soil: 53 tons lost/ha/year* Reforested area: 12 tons loss/ha/year* Secondary forest: 0,2 tons loss/ha/year*

A g r o f o r e s t r y i m p a c t s o n s o i l f a u n a

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C O N T E X T

SOIL MACRO-BIODIVERSITY

• Major soil quality indicator
• Provider of ecosystem services: soil formation, decomposition and nutrient cycling, carbon and nitrogen fixation and

sequestration, infiltration, purification and storage of water OUR PARTNERS

• Universidad Nacional de Agricultura, Honduras (UNA)

STUDIED SPECIES Name Function Scolopendra sp Predation on potential pest species, regulation of soil food web and integrated pest management Phyllophaga sp Predation on potential pest species and organic matter decomposition Lumbricus terrestris Soil structuring and aeration, organic matter decomposition Source: Metral et al., 2006

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P R O T O C O L

OBJECTIVE

• To assess the impact of land use on macro-organisms biodiversity and quantity

TREATMENTS AND REPETITIONS

• 4 types of land use: full sun, agroforestry, reforested area, secondary forest
• 6 plots per land use, 5 samplings per plots

METHOD: TROPICAL SOIL BIOLOGY and FERTILITY

• An ISO normalized method (ISO 23611-5:2011)

25 cm 30 cm 25 cm Land use is a variable, other parameters are constant Crop selection Macro-organisms counting Data analysis Sampling Excavation of a 19 cm3 soil cube in each sampling spot Characterization of the macro-organisms present in the soil sample, by species Number of individuals Diversity of species

1 4 5 3 2

5 sampling spots in a 100 m² area Sampling zone delimitation 10 m 10 m

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I n f l u e n c e o f l a n d u s e o n s o i l m a c r o b i o d i v e r s i t y

R E S U L T S - A P R O S A C A O , H O N D U R A S

5 10 15 20 25 30

• L. Terrestris

Scolopendra Phyllophaga Total Macro-biodiversity* INFLUENCE OF LAND USE ON SOIL MACROBIODIVERSITY Full sun Agroforestry Reforested area Secondary forest CONTEXT

• Type of soil: Inceptisol, Alfisol

(USDA classification)

• Climate: subtropical humid

FIRST RESULTS

• Agroforestry

and reforested systems contains about 4 times more macro-organisms than full sun systems NEXT STEPS

• Doing

more repetitions to increase statistical significance *Average number of individuals per 0,19m3 sample over various measurements X 4

A g r o f o r e s t r y i m p a c t s o n y i e l d s

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C O N T E X T

YIELDS QUALITY AND QUANTITY

• Cocoa yields depend upon cacao plant’s general status, soil quality, climate, agricultural practices, shade.
• Harvest’s quality can be evaluated from the damaged fruits rate.

Name Description Solution Monilisasis – Moniliophthora roreri Caused by a fungus Intern and extern necrosis of the fruit Suppressing the damaged fruits to stop propagation Aborted Natural mechanism exacerbated in stressful conditions Identifying the cause: lack or excess of water, light or nutrients Rot - Phytophtora Fruit infection and death Damages on the trunk and branches Applying fungicide Adapting cultural practices Insects The insects feed on cocoa Vector of viruses Applying insecticide Implementing biological control Adapting cultural practices OUR PARTNERS

• Université libre de Bruxelles, Belgium
• Universidad Agraria de la Selva, Peru
• Localization: Peru, San Martin, Alto

Huayabamba project

• Climate: Subtropical humid
• Soil: Inceptisol (USDA Classification)
• Crop: Cacao

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P R O T O C O L

OBJECTIVE

• To assess the optimal shade tree density to warranty cocoa yield and quality

TREATMENTS AND REPETITIONS

• 4 different shade tree densities
• Three 1000 m² crops per treatment with same cocoa density: 1800 trees/ha

High density 440 timber trees/ha Medium density 270 timber trees/ha Low density 50 timber trees/ha Full sun 0 timber trees/ha NOTA BENE A very similar protocol is applicable to coffee. Crop selection Crop characterization Harvest quality Harvest quantity Producer enquiry Data analysis Measurement of cocoa and timber tree height Classification of the fruits on quality Measurement of cocoa yields all year long Survey on producer’s opinion

• n harvest

Assessment of harvest quality and quantity Timber tree density is a variable, other parameters are constant

1 2 3 5 6 4

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H a r v e s t q u a l i t y

R E S U L T S – A L T O H U A Y A B A M B A , P E R U

0% 10% 20% 30% 40% 50% 60% 70% Healthy Aborted Moniliasis Rotted Pest Number of fruits in percentage of the total Influence of tree density on fruit abortion and diseases development Full sun Low density Medium density High density July 2015 In this case, low tree density is the optimum (50 timber trees / ha) with an increase of 84% of the quality*, a diminution by 41% of abortion rate, and less pests and diseases.

*Rate of healthy fruit

+84 %

• 41 %

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H a r v e s t q u a l i t y

R E S U L T S – A L T O H U A Y A B A M B A , P E R U

0% 1% 2% 3% 4% 5% 6% 7% 8% Total damaged Moniliasis Rotted Pest Number of fruit in percentage of the total Influence of tree density on fruit damages Full sun Low density Medium density High density FIRST RESULTS

• Full sun condition

increases by 86% the rate

• f damaged fruit in

comparison with low tree

• density. It could be

explained by the lack of biological control in full sun system

• High density systems

generate more humidity which explains fungi diseases development July 2015

• 86 %

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H a r v e s t q u a n t i t y

R E S U L T S – A L T O H U A Y A B A M B A , P E R U

50 100 150 200 250 300 350 400 450 Harvest 1 (Feb 15) Harvest 2 (Mar 15) Harvest 3 (Jul 15) Harvest 4 (Aug 15) Cocoa yields (kg/ha) Influence of tree density on cocoa yields Full sun Low density Medium density High density In this case, a low density of trees induces an increase of 71% of the yields in harvest 3 (biggest harvest for the period under review) in comparison with full sun. +71 %

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G l o b a l c o n c l u s i o n s

R E S U L T S – A L T O H U A Y A B A M B A , P E R U

FIRST RESULTS

• There exists an optimum timber tree density for

harvest quality and yields. In our particular context, it could be around 50 trees/ha.

• Full

sun and high tree density are both damageable for harvest quality and yields.

• Low tree density increases fruits health and

yields compared to full sun system.

• Full sun conditions increase by 86% the rate of

damaged fruit in comparison with low tree density. NEXT STEPS

• Doing more repetitions with different farmers to

increase statistical significance

• Studying a lower range of tree density
• Collecting data all year long to assess the impact
• f tree density over a long-term period

CONTACT

purlab@purprojet.com