1. Introduction to CCAP, conference objectives, outcomes for follow up, upcoming activities Regional Conference on Climate Change Adaptation in Coastal Areas: Perspectives from the Dasht, Indus, and Sunderbans Deltas 16-17 October 2012, Savar for a living planet

2. Project Description When:5-yrs (2011-2015) Where:Coastal Pakistan (Sindh, Balochistan) and regional deltas (Indus, Sunderbans, Dasht) Who:WWF-P, WWF-UK, LEAD, and associates: Friends of Indus Forum, Centre for Coastal Environmental Education, Andishe Ensanshahr Why:Adaptation planning, developing case for adaptation spending by GoP and donors based on primary data and field level findings What:Studies, capacity building, water sector focus, ground level interventions, UC level plans

3. Project Goals 1)By 2025, climate resilient ecosystems support coastal inhabitants’ livelihoods in Indus, Dasht, and Sunderbans. 2)By 2015, government and community adaptation capacity is increased, water governance strengthened,

4. Project Beneficiaries Keti Bunder:9,730 persons or 32% of UC’s 2012 pop. (4,423 males, 5,307 females) Kharo Chan:13,909 persons or 42% of the UC’s pop. (6,439 males, 7,470 females) Jiwani:sharing of best practices with coastal communities Regional dialogue: Bangladesh, Iran and India

5. Study 1 Study:Decision Support System (DSS) ToRs:- 40-50 years time-series data - 2 variables: 1) rainfall, 2) temperature - grid resolution: 25 km x 25 km - scale: sub-district (Talukah/Tehsil) - nationwide or coastal only? Applications:- identifying adapters and non-adapters - sub-district level food security planning

6. Study 2 Study:Farmers’ Adaptation to Salinity ToRs:- Cross section data on crop loss / yield reduction (perceived) - Sea level rise scenario analysis - Average sediment accumulation - Inundated land (horticultural & agricultural) - maps relating damages from multiple sources - 200+ soil and water samples Applications:- Policy: justification for ADP allocations - Planning food security interventions

7. Study 3 Study:Climate Data Modeling & Analysis ToRs:- District wise forecasts (temp / rainfall) - Sea level rise (historic) - agricultural impacts - scale: country wide (Indus Delta focus) - interpolation (141 stations) Applications:- Policy: LAPA design (intro to CC trends) - Policy: identification of threats and opportunities for planners using models that highlight counterintuitive notions, significant exceptions

8. Study 4 Study:Community Vulnerability Analysis (CVA) ToRs:- Surveys (Nov ‘11 & Jun ’12) - current and anticipated vulnerability - local perceptions & existing coping - 10 FGs & 10 inter-gen interviews / site - 10 respondents / FG (1 interview / resp) - 30 FGs & 30 interviews (3 sites) - sample size: 330 / season survey Applications:- Project interventions: design of activities, prioritization, etc. - Policy: tailor made needs-based justification, e.g., for climate neutralizing female education

9. Study 5 Study:Hazard Mapping ToRs:- local-scale legend-map listing of hazards - display of historic vs. present impacts - path correction based on preliminary CVA results Applications:- Project interventions: designing activities, prioritizing DRR and DRM deliverables, ensuring village specific needs are met - corroboration of other study findings (e.g., CVA)

10. Study 6 Study:Political and Institutional Analysis ToRs:- local adaptation plan stakeholders - modules on institutional process, gender, etc - recommendations, strategies, key questions raised and “what can your department do?” format Applications:- CC policy –LAPA linkage and strategy design

11. Study 7 Study:eFlows Analysis ToRs:- sediment morphology analysis - identification and ranking of assets - requirements of, implied present day status of, & scenario analysis of selected asset(s) Applications:- water governance lobbying

12. Study 8 Study:Best Adaptation Practices ToRs:- Mozambique, Sri Lanka, Thailand, Bangladesh, India - practices that can be replicated by practitioners - A methodology for VA - Review of WWF’s performance Applications:- basis for information sharing by regional networks, etc.

13. Study 9 Study:Socioeconomic Baseline ToRs:- income, expenditure, livelihoods - climate change adaptation measures - demographic data, migration - women’s employment, communications Applications:- measurement of progress, helping target interventions, design activities, assist feasibility for ground interventions, and promote evidence based policy making

14. Study 10 Study:Bangladesh Adaptation Literature Review focusing on the Agriculture Sector ToRs:- Case studies, in person interviews, existing models and forecasts, Applications:- basis for information sharing by regional networks, replication of best practices, etc.

15. Socioeconomic Baseline of Pakistan’s Coastal Areas for a living planet Regional Conference on Climate Change Adaptation in Coastal Areas: Perspectives from the Dasht, Indus, and Sunderbans Deltas 16-17 October 2012, Savar

16. 1. Income across CCAP sites 2. Livelihood indicators 3. Women’s earnings 4. Vulnerability of fishers 5. Adaptation strategies 6. Methodology Outline

17. National Poverty Line (2011, extrapolated) National Poverty Line in PKR (2011, extrapolated)

18. International Poverty Line (2011, extrapolated) International Poverty Line in USD (2011, extrapolated)

19. Cross-Site Income findings at a Glance Poverty Incidence :highest at Kharo (50%), then Keti (40%), then Jiwani (20%) (% below extrapolated 2011 poverty line of PKR 50 p.c. p.d) Monthly HH incomes :Kharo Chan (PKR 21,144), Jiwani (PKR 19,716) Keti Bunder (PKR 13,002) (mean household incomes bracketed alongside site names) Database :Comparison of 2011 to 2015, use by site staff to target villages for interventions based on 100+ variables that can be consulted

20. Other Livelihood Indicators Message : Significant obstacles stand in the way of a shift out of poverty Savings :Kharo (11-30%), Keti (30%) (% are savings ratios: i.e. net HH savings / net income) Loans :120,000 (Kharo), Keti (55,000) and 13,800 (Jiwani) (all figures in PKR and refer to sample averages) Resilience to shocks :Lowest at Keti, highest at Kharo (estimated mean HH ownership of all livestock varieties) Opportunity cost of time : worst impacted at Kharo (based on hours spent hauling water) Illiteracy :Keti (80%), Jiwani (40%)

21. Other Livelihood Indicators: Water Charges

22. Other Livelihood Indicators: Illiteracy

23. Other Livelihood Indicators: Health Facilities

24. Other Livelihood Indicators: Disease Prevalence

25. Women’s Earnings Message : Constraints to supplementing HH income are non-trivial Role as mothers :Lack health facilities (Kharo: diarrhea, malaria; Keti: also skin/eye disease, Jiwani: typhoid is common) Preventing deaths :Keti (70% mobiles, 10% radios) (sample shares reporting main source for information access) Average earnings :Jiwani (5,030), rilly only at Keti (700), embroidery only at Kharo (620) – note: demand isn’t constant (bracketed figures refer to PKR and averages per month) Diversified skills : best at Jiwani, worst at Kharo (from among rilly & hat making, embroidery, sewing, etc.)

26. Other Livelihood Indicators: Vocational Skills

27. Vulnerability of Fishers Message : NR dependency in the absence of sustainable practices and diversified livelihoods lowers CC adaptation resilience Exclusive fishers :Keti (68%), Jiw. (53%), Kharo (48%) (percentages of sampled respondents) Middlemen :Kharo (25-30%), Keti (100%+) (% disparity b/w market and fisher prices in seasonal fish) Price rises :Driven in part by illegal sale of Iranian oil at prices below OCAC rates – (seasonal & year round fish compared against 2008 baseline using 14.9% 3-year av. inflation)

28. Vulnerability of Fishers: 2008-2011 baselines

29. Adapters and Non-Adapters CC Adaptation Strategies (% by village)

30. Adapters and Non-Adapters CC Adaptation Strategies (% by village)

31. Sampling and Data Methodology: -2-stage stratified cluster sampling technique at all 3 sites, size of samples varying from 132 to 576 (or 0.4% to 3% of UC pops) -Income determined through: -annual HH income questionnaire module (inflows also include property owned, land rented, remittances, etc.) -total monthly expenditure module (enumerators trained to obtain counterintuitive items listing) -above 2 corroborated through volumes and AUPs of livestock sales, agricultural sales and sharecropping arrangements, fishery sales, incomes from enterprise based on timber sale, NTFP sale, vegetation / handicrafts made from vegetation -corroboration of these items based on 2007 baseline -Plausibility of price and volume figures based on 3-yr and 4- yr average inflation extrapolation -Also via interviews of leaders in industry/business associas.

32. Negotiating Known Unknowns: “Better” Climate Adaptation Practices from the Indus Ocean Basin for a living planet Regional Conference on Climate Change Adaptation in Coastal Areas: Perspectives from the Dasht, Indus, and Sunderbans Deltas 16-17 October 2012, Savar

33. 1. Bangladesh 2. India 3. Sri Lanka 4. Mozambique 5. Thailand 6. Methodology Outline

34. Bangladesh Project:Sea barriers: afforestation & reforestation BAP 1:Strengthening of government capacity at various tiers, revision of coastal management policies, CC knowledge BAP 2:Prioritize most prized assets: livestock pen release timing, reinforced livestock killas, livelihoods diversification, aquaculture & food production combined with afforestation and reforestation BAP questions:how many families per ha? What crops? Aquaculture?

35. India Project:lobster fattening enterprises BAP 1:recognizing vulnerability across gender, class and caste lines (implications for adaptive infrastructure, participatory governance structures, and livelihood diversification) BAP 2:elevated latrines for women and children, village water committees (enhanced social capital implications has implications for improved negotiation of market prices) BAP questions:better prices from fattened crabs, etc? Loans for cages/pits to rear crabs? Collectives?

36. Sri Lanka Project:greenbelt plantations for tsunami victims BAP 1:community-led bioremediation of drinking water wells, tree/shrub plantation around wells, community groups to mobilize savings BAP 2:bioremediation plots double as kitchen gardens with women as main managers and beneficiaries. BAP questions:how to scale up and link social capital with higher tier governance structures? How to sustain bio-remediation?

37. Mozambique Project:when relocation is only feasible option to save lives BAP 1:migration should be voluntary, ability and willingness of institutions to support migrants, state encouragement to resettle, state incentives to strengthen infrastructure & livelihood diversification BAP 2:fruit and maize as insurance crops, offering additional produce when season permits. BAP questions:our equivalent of higher sandy lands? Our equivalent of self-organized, dual land-use systems? What incentives? Too Costly?

38. Thailand Project:social capital to develop NRM enterprise BAP 1:formation of a savings management group by villagers (implications for developing management and organizational skills), breeding and harvesting of mud crabs BAP 2:diversified income baskets: rubber plantations, fruit gardens, cultivating shrimp, day labor and fishing; support of local politicians to regain control of mangroves BAP questions:“crab banks” workable here? Workable to impose harvesting ban in breeding periods?

39. Project Methodology “Vulnerability”:Susceptibility to suffer damage, inability to recover from environmental extremes “Resilience”:socio-ecological system’s ability to absorb shocks without losses to productivity, environmental values and access to resources “Adaptation”:adjustment to stimuli and its effects to moderate harm or exploit opportunities Resilience Metrics:These are indicators for the BAP study, namely: “diversity” (e.g., livelihoods, access to eco-services), “ecosystem services” (e.g., access by poor), “equity” (e.g., participation and access / opportunity across genders), “social capital” and “infrastructure”

40. P-E Linkages (Pak & Indus Ecoregion) Fundamentals:Unresolved structural problems (esp. energy sector), 2 major floods, CPI persistently high (esp. large SBP- accommodated fiscal deficits), June ’12 YoY 4.2% growth, 60%+ pop > 25 yrs (pop to double to 0.4 bn by 2050) Just how poor:MoF est. 0.5 pc pts shaved off GDP growth from 2011 floods; 6.6m unemployed 2-3 mths, USD 2.6bn capital stock destroyed (1.2% GDP only); bumper winter-wheat crop, agricultural exports buoyed by cotton prices Indices:67% live in country; % Pop > USD 2/day fell 83%-60% (‘06-’12); poorest 20% worse off vs. ’02; 58% HH food insecure

41. Water and Food Security (Pak & Indus Ecoregion) Food :44% of children suffer chronic malnutrition, 15% acutely so (of 58% food insecure HHs, 30% mod/sev hunger, 7% severe acute); Pakistan has 120 districts, food deficit in 74 of those (62%, Balochistan severe); Water :availability is 1,100 cm/yr in 2011 vs. 5,500 cm/yr 60 yrs ago; 1,000 liters to 1 kg of wheat, 5 times that for 1 kg rice; Indus Basin water stress (> 1,700 cm/yr – about 1,329 cm/yr) Climate Change:Average temp to increase by 1% by 2030

42. The Determinants, Impact, and Cost Effectiveness of Climate Change Adaptation in the Indus Ecoregion LUMS WWF – P PIDE-hosted Inception workshop of the IDRC Project on Climate Change Adaptation, Water and Food Security in Pakistan 25-27 May 2012 for a living planet

43. 1. Description 2. Goals 3. Deliverables 4. Project Sites 5. Sampling and Data 6. Econometric Specification Outline

44. Project Description When:3-yrs (2012-2015) Where:Indus Ecoregion (Sindh), also Punjab Who:LUMS, WWF-P, SOAS / LSE Why:Options & ROE on Adaptation Spending What:2 studies (based on primary data), farmer tools (FFS, manuals), 6 policy studies

45. Project Goals 1)Equip planners & policy makers to take informed decisions (cost-effective and politically feasible CC adaptation interventions). 2)Mainstream micro-econometric and political economy study results into relevant government economic and social plans.

46. Project Deliverables Jul 2014:Micro-econometric study Nov 2014:Political economy study Jan 2015:Synthesis policy report 2013-14:Farmer field school curriculum, manual, exposure visits 2013-15:Student assisted faculty papers 2012:Technical advisory group 2012-13: 2 national consultations (sampling, methods) Feb 2015: High level conference on Climate Change and Food Security

47. Research questions What is the predicted change in yield and profit in wheat production as a result of climate change? (i.e., what is the difference between BAU values and amounts of 2012 and future ones – based on rainfall and temperature forecasts up to 2100 inputted in our Hedonic Production Function?). How does this change when assumptions about adaptation strategies are altered? How would adapters have fared had they not applied strategies, and how would non-adapters fare (i.e., what is the average treatment on the treated – adapters – and the untreated – non-adapters)? Which food security and LAPA policies and plans are in need of reform? Which adaptation strategies have farming households’ undertaken and are they paying off? What are their risk perceptions and food security/adaptation impacts of these?

48. Research steps Questionnaire design Focus group & key informant discussions, secondary data Reconnaissance surveys (1 per site, 3 sites; sampling strategy) Training of enumerators (1 manual to carry into field) Time series data (25x25 km or finer) and decadal forecasts of average increases/decreases in rainfall and temperature Pilot testing, questionnaire redesign, and main surveys (1 for each of the 3 sites, 500 questionnaires per site) Data rendered in.do &.dta files for analysis in STATA-12

49. Crop choice: why one crop (wheat)? Yield and quantities tied to food security concerns Especially responsive to temperature and rainfall changes Livestock as insurance/savings: small farmers obliged to grow wheat to feed livestock (household level food security) Production data on all other crops elicited; but, detailed questions on input cost, yield, etc. reserved for single crop (6 crops per plot grown over 12 months is not uncommon) Aside from the production function data required of a single crop, questions that proceed by eliminating harvest losses due to exogenous factors, or, crop-specific adaptation responses, too numerous to apply to multiple crops

50. LUMS-WWF Project Sites LUMS-WWF: Proposed sites in the Indus Ecoregion and Punjab Karachi

51. Site selection: why Sanghar, Nawabshah, Bhawalpur? Sites should have wheat cultivation representative of the Indus Ecoregion and/or concerned province (e.g., plot numbers, cropping, rotations, livestock grazing land, labor division across activities, farm wage rates, water sources) Access to respondents, mobilization of respondents within settlements, amenability and non-strategic behavior of respondents is better ensured in settlements where WWF-P is a recognized convener of community interventions. Model needs rainfall and temperatures to vary across sites Access to WWF-P administered Farmer Field Schools to implement manuals, master trainer trainings, farmer exchanges, and to access district/provincial steering committees serving 50-year vision of the Indus Ecoregion

52. Proposed methodology Sampling sufficient to cover adapters and non-adapters and variation in recorded precipitation and temperature Ricardian analysis of climate change impacts on agriculture, reading off yield/profit for different scenarios (Cobb-Douglas type Hedonic production function with probit/logit functional form) Control for selection bias in household adaptation strategy choice. Programme evaluation methods to give indication if those who adapted gain more or less than those who did not would have had they adapted (ATT-ATU). (This uses matching, PS matching for observables ; bounds analysis for testing of sensitivity; and, instrumental variables, regression discontinuity, endogenous switching regression for selection on unobservables.

53. Proposed questionnaire modules: 1.Members of households and education (work on farm activities and non-farm activities, farm wage rates) 1.Employment in the past 12 months (weeks/days on primary and secondary occupation, illness days). 2.Plot level data (no. of separated areas farmed, sizes, tenure type) 3.Labor composition: household/hired total numbers and days worked per activity by season (activities like land preparation, planting, weeding, irrigation, harvesting, post-harvest processing, livestock management) 4.Farming activity (by crop type: plant/harvest dates, % of plot, quantity harvested, own consumption, livestock consumption, loss to pests/disease, quantities sold, farm gate value, costs of seed, amount of seed, seed type, average yield)

54. Proposed questionnaire modules (continued..1): 6.Water source, irrigation system, fertilizer/pesticide use (costs) 7. Information on farm machinery, inputs, and farm buildings 8.Market proximity, transport used, etc. 9.Farm animals owned, born, sale price, lost/stolen/killed, purchase price, communal/own/open land grazing (number of months), livestock products sale and own consumption 10. Costs associated with crop/livestock transport, packaging/marketing, storage, post harvest losses 11.Acess to and extension services (advice, payment, organization, weather services, other sources of technical advice) 12.Source of household finance (normal average year income from farm and non-farm activity)

55. Proposed questionnaire modules (continued..2): 13.Access to credit (borrowed from whom, amounts, interest, repayment period) and subsidies (crop, input, direct, other) 14.Short term climate effects ( household adaptation strategies in response to temperature and rainfall fluctuations, wind, dust storms, etc. within and between seasons) what are the primary constraints in this regard? 15.Long term climate change (noticed long-term shifts in mean temperature and rainfall, made adjustments on your farm in response to temperature and rainfall ) 16.Module devoted to discovering the rationale for various adaptation measures for the purpose of establishing whether such practices were undertaken to ameliorate climate change related risks, or for unrelated reasons 17.Bidding game to identify risk perceptions

56. Questions for TAG members: -How can one characterize “adaptation” or types of adjustment in farming practices currently being undertaken because of rainfall and temperature changes? (e.g., changing crops, acres planted, planting and harvest dates) -What characteristics do “adapting households” typically possess (e.g., access to credit, access to information, motivation levels) -Which motivations can we typically mistake for adaptation? (i.e., actions resembling adaptation to climate variability or change but undertaken for altogether simpler and different reasons)