Date post: | 22-Nov-2014 |
Category: |
Education |
Upload: | steps-centre |
View: | 578 times |
Download: | 0 times |
Closing the Loop: Climate Science, Development Practice & Policy Interactions in Dryland Agro-
Ecological Systems
Andy Dougill, Evan Fraser, Claire Quinn, Lindsay Stringer & Chasca Twyman
www.cccep.ac.uk
Aims
CCCEP ‘Closing the Loop’ Work Package Aims of –
• Integration of quantitative vulnerability analysis with participatory research to assess vulnerability pathways
• Better linking of scientific & local-level knowledge perspectives into adaptation policy / decision-making
• Comparison of local & scientific understandings of climate change & risk management as guide on need for local level monitoring to ‘close the loop’ in forward planning
Case Study Analyses
1. Ecology & Society Special feature ‘Resilience and Vulnerability of Arid and Semi-Arid Social Ecological Systems’ with 8 case study papers (Niger, Botswana x2, South Africa, Mali, Ghana, Spain, Nicaragua) – Dougill et al., 2010 on-line
Reflection on value of participatory dynamic systems modelling approaches with range of qualitative – quantitative case study perspectives
2. Farming systems research assessing drought-coping strategies & cropping choice adaptations in rural Malawi, Botswana & Ghana
Vulnerability Framework
Agro-ecosytem resilience
FragileRobust
Socio-economic affluence
Limited assets
Abundant assets
Institution capacity to respond to crisis
Low
High 1 2
3 4
5 6
7 8
Movement in this direction indicates increasing vulnerability to environmental changes
Movement in this direction indicates increasing resilience to to environmental changes
Fraser 2007, Climatic Change, 83(4)
CENTURY
DECADE
SEASON
COUNTRY + REGIONAL FIELD
Exposure – Impact - Adaptation
ACCESS TO INPUTS/FOOD
Agent-Based ModDecision Model
PRA
FOOD SUPPLY
Crop-Climate Models
FOOD DISTRIBUTION
Economic modelsStatistical models
Tem
pora
l scale
Spatial scale
Closing loops - Tools
Participatory methods to ID
adaptation strategies
Large-area crop models + climate /
climate change simulations
Statistical methods to ID
socio-economic
characteristics
Tem
pora
l scale
CENTURY
DECADE
SEASON
COUNTRY + REGIONAL FIELD
Spatial scale
Identifying sensitivity to drought
Minor drought Major drought Drought Index
C
rop
Failu
re In
dex
Min
or c
rop
loss
M
ajor
cro
p lo
ss
Sensitive
Resilient
Increasing vulnerability
See Simelton et al., 2009. Env Sci & Policy, 12, 438 -452.
Quantitative modelling
Conventional social sciences
1. Establish problem and boundaries of agro-ecosystem
2. Interview experts or stakeholders to establish a narrative that explains the system
3. Analyse narrative using a flow chart or “mind map”
4. Reflect & make policy / practice recommendations
5. Explore each relationship within the system through expert focus groups to quantify whether relationships are linear or non-linear, their slope etc.
6. Run different simulations of the model to explore scenarios
Example Case Study: Kalahari Rangelands
Pastoral Botswana
Bush Encroached System
Reed & Dougill, 2010. JAE, 74(1), 149-155
More private land
Establishing bore holes
Increased grazing densities
Government policy to privatize land
Market growth
Bush encroachment
Forage
Imported feed
Number of cows
Rainfall
Income Ability to move cows to neighbour-
-
From 8 researcher & policy-maker interviews post environmental & participatory projects – linked to development of rangeland management guides
Model quantification post 3 expert focus groups with follow-up’s to discuss & show – linked to village level livestock no’s
The effect of “Agricultural Best Management” scenario to help reduce impact of climate change
Rel
ativ
e V
alu
e
Private herd
Communal herd
Best Management
Baseline
Best ManagementBaseline
A significant rise
Limited change0
0.5
1
1.5
2
2.5
1 4 7 1013 1619 2225 2831 34 3740 4346 4952 5558 6164 6770 73 7679 8285 8891 94
Time in “Model Iterations” ~ years
Pro-poor land reform scenario
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94
Rel
ativ
e V
alu
e
Private herd
Communal herd
Land reform
Land reform
Land reform
Baseline
A significant drop
A significant rise
Time in “Model Iterations” ~ years
Implications of this model• Enacting pro-poor land reform is more effective at helping
communal farmers maintain incomes in light of climate change than promoting agricultural best management
• Privatisation retains maximum national-level herd size though inequitable distribution
• Outputs of model used to stimulate discussion & to guide local-level field research
• Best management guides produced & their value to be quantified
Benefits of Process at Multiple Scales Across Diverse Case Studies
• Participatory processes at local level led to decision-making tools & actions, but also fed into District & National scale modelled generalisations
• Explanatory narratives can give explanation & provide situated accounts of relationships between livelihoods, ecosystem services and policies
• Storylines (& no’s) aim to stimulate, provoke & communicate vision of possible futures. The process leads to learning & interpretation of greater value than predictions produced
• Natural angst in quantification leads to dangers in communications on key policy interventions identified
Conclusions
• Whilst a tension exists between scientific & participatory knowledges, communication and dialogue between these approaches has benefits and explicit resolution not essential• Process of narratives into models helps policy-makers to better understand system dynamics and complexity, though uncertainties in developing to predictive models (=> use as ‘throw-away’ models)• Consistent simplified framing of vulnerability proved appropriate across range of approaches & case studies => can bring insights across multiple scales
www.cccep.ac.uk