2. Our Team
• Southampton
(Poppy, Eigenbrod, Hudson, Mad
ise, Schreckenberg, plus
Dawson, Margetts)
• Conservation International (USA)
• Basque Centre for Climate
Change
• CIAT & CI International Colombia
plus Colombian research
centres, universities and NGOs
• Chancellor College, Malawi, plus
Worldfish and LEAD Africa
3. The overarching goal is to explicitly quantify the
linkages between the natural ecosystem services
that affect – and are affected by – food security
and nutritional health for the rural poor at the
forest-agricultural interface
Photo by Erwin Palacios CI Colombia
6. ASSETS Research Themes
Theme 1:
Drivers, pressures and linkages between
food security, nutritional health and ES
• Relationships
between
forest ES, food
& health
• Identifying key
drivers and
pressures
7. Choice of Case studies-
cutting across two continents
Africa & Amazonia:
different situations…… much in common
• Deforestation:
Africa much more advanced
Amazonia in rapd transition due to a range of drivers
• impacted by climate change and extreme weather events
• issues of extreme poverty, malnutrition and inequality
Our workshops selected paired case study regions in
Malawi and Colombia- as the best locations to address
our research questions, but also because of links to
partner organisations already active locally
8. Sub-Saharan Africa: Malawi
• One of the poorest countries on earth:
52% in poverty, 29% undernourished
• Mostly deforested: 27% remaining
• Prolonged droughts and occasional
extreme rain
• Paired case study regions: East Chilwa
and Chingale (Zomba West)
• 80% of people are subsistence
farmers or smallholders;
• Differences in rainfall, water
availability, forest cover…
• ….but with some protected forests
and wetlands (under pressure from
overexploitation & drought) Data from UNDP, FAO, CIA
Factbook,; imafe from nyastimes
9. Amazonia: Colombia
• Extremes of wealth and poverty in a fast
growing economy
• 45% forested- mostly in Amazonia and
Andes, but under great pressure
• Suffering climate & weather extremes:
La Nina, Climate Change
• Paired case study regions: Upper and
Lower Caqueta:
• 62% living in poverty
• At different stages of transition- driven
by incoming settlers, clearance for
cattle, soya, biofuels
• Several protected forest areas
• Indigenous groups may be most Data from UNDP, FAO, CIA
threatened by land use changes Factbook; image from
10. Participatory research
• Aims:
– To understand links between ES and food security
– To derive non-monetary values for different ES
• Well-being ranking of study communities
• Focus groups (differentiated by social group) to:
– Understand local concepts of food (in)security
– Identify ES that contribute to food security at different
temporal and spatial scales
• Seasonal calendars – seasonal coping strategies
• Community timelines – inter-annual food security
• Matrix scoring and ranking to prioritise the most important ES
for food security for different groups
• Participatory economic valuation of some ES
14. Measuring household poverty, food
security, and nutrition health
Aims:
• Identify poverty status of households using
objective and subjective measures
(expenditure, subjective wealth, assets)
• Measure food security and nutritional status of
under-five children in households across the
forest-agricultural gradient
• Deeper understanding of coping mechanisms
• Disseminate to, and feedback from the local
community
15. Food security surveys
• Aim : Assess availability, access, and utilisation of food
and how ES affects each
• Measures (men, women, children)
– Number of meals eaten on regular day/ yesterday
– Frequency of not having enough to eat in the past 6
months
– Frequency of sleeping hungry
– Detailed food consumption data including
types, sources, amounts (weighed), repeated to
capture seasonal variation
• Perception of hunger
– has enough to eat
– Hunger
• Nutritional health surveys
– Anthropometric measurements
16. ASSETS Research Themes
Theme 2:
Crises and tipping points: Past, present and
future interactions between food insecurity
and ES at the forest-agricultural interface
• Coping strategies
• Future scenarios
http://blogs.reuters.com/photographers-blog/2010/08/12/an-
aerial-view-of-sumatra-island/
17. The ARIES Model:
Artificial Intelligence for
Ecosystem Services
A bit of history
• Initially developed at the University
of Vermont (Gund Institute) and
Conservation International mainly
on NSF money by ESPA co-PI
Ferdinando Villa (now at Basque
Centre for Climate Change, Bilbao
Spain)
• Co-lead on ARIES is Miroslav Honzák
at Conservation International
Malawian
(Washington) boy, Zomba, November
2010
18. ARIES: summary
• A rapid spatial assessment tool for ecosystem
services and their values; not a single model but an
artificial intelligence assisted system that
customizes models to user goals.
• Demonstrates a mapping process for ecosystem
service provision, use, sink and flow while most ES
assessments only look at provision.
• Probabilistic, Bayesian models inform decision-
makers about the likelihood of possible scenarios;
users can explore effects of policy changes and
external events on estimates of uncertainty.
22. ASSETS Research Themes
Theme 3:
The science-policy interface: How can we
manage ES to reduce food insecurity and
increase nutritional health?
• Minimising risk of future
environmental change
• Influencing policy to better
manage ES conflicts, trade-offs
and synergies to sustain food
security and health?
http://news.bbc.co.uk/1/hi/world/south_asia/744
5570.stm
24. Stakeholder Engagement & Feedback
Target audience
• Community members
– Through village meetings, community radios
• National policymakers e.g. Govt, civil
society, NGOs
– National advisory board meetings, briefings, policy
briefs
• International policymakers
– Scientific advisory meetings & through partners
(CIAT, CI, WorldFish)
• Academic beneficiaries
25. Our consortium will undertake world class research on
ecosystem services (ES) for poverty alleviation at the
forest-agricultural interface and deliver evidence from a
range of sources and in various formats to inform policy
and behaviour.
Photo by Erwin Palacios CI
Colombia
We hope to make a difference to the lives of 2 million poor people
living in our case-study regions – up to 550 million people living in
similar environments around the world.
26. This presentation was produced by ASSETS (NE-J002267-
1), funded with support from the Ecosystem Services for
Poverty Alleviation Programme (ESPA). The ESPA
programme is funded by the Department for
International Development (DFID), the Economic and
Social Research Council (ESRC) and the Natural
Environment Research Council (NERC), as part of the UK’s
Living with Environmental Change Programme (LWEC).
The views expressed here are those of the authors and do
not necessarily represent those of the funders, the ESPA
Programme, the ESPA Directorate, or LWEC.
Editor's Notes
Source: Mathews Tsirizeni – LEAD Southern & Eastern Africa. Note – this slide has animation – the first picture shows flooding, the second the participatory GIS they have been doing to identify causes and solutions.
The provisionshed is constituted by all different ecosystem sources where the service is generated. The benefitshed identifies areas where potential recipients or users of benefit are. Precise pathways of flow from their point of origin to beneficiaries are identified. One of the key features of ARIES and what makes it different from other approaches is the flow analysis of ecosystem services.
For each specific beneficiary we can quantify, fluxes are precise and spatial, so it is known how much of the service reaches each beneficiary, and the trajectories required for the service to flow. Point by point we can tell how much each beneficiary receives from which specific area and this has important implications for example in payments for ecosystem services. As an example the analysis allows to identify areas that are critical for the delivery of a given service. Critical areas of ES flow should be given the highest importance in planning conservation of biodiversity and ES.