ESPA Deltas Stakeholder Workshop Health, Livelihood, Wellbeing Nexus in the Context of Ecosystem Service Provision Findings from ESPA delta Social Survey Dr. Peter Kim Streatfield Emeritus Scientist Center for Population, Urbanization and Climate Change (CPUCC) Icddr, b 16th September 2015, Dhaka, Bangladesh Need to drop my name, and put your names – whoever is going to present. Can keep the whole team list of names below if you want.

Presentation Outline Study areas and Sampling Framework ESPA Deltas study: Scope and Framework Study areas and Sampling Framework Survey Overview Questionnaire Structure Household Survey Results and Findings Conclusion

ESPA Delta Study: Aims and Scopes To understand the present relationship between ecosystem services and human well-being To project how these ecosystem services might evolve over the next few decades (up to 100 years) To analyze how policy can influence these outcomes and promote ecosystem services and human well-being icddr,b is working under WP3 and lead the socio-economic survey component of the study. icddr,b and partners from UK universities leading socio-economic survey to explore spatial and temporal distribution as well as variations of ecosystem services for better conceptualizing Ecosystem Services and Poverty Nexus to guide national and international policy actions towards global priority of Poverty Alleviation.

WP5 integration framework (ΔDIEM) Relative SLR timeseries WP5 integration framework (ΔDIEM) Library of Channel Cross-sectional Area (polder height, channel volume) Climatic Parameters (temperature, precipiation) River flows GWAVA / INCA Polder maintenance ? discharge flow depth Mangrove model? GW quality emulator MODFLOW output River salinity emulator FVCOM output Flooding / Inundation emulator Delft-2D (tidal amplitude) output Groundwater salinity River salinity available land Morphology Soil salinity Library of Governance restrictions (protected areas, other regulation) Land Cover maps/emulator/model (agriculture, aquaculture, mangrove, water, floodplain, settlement) Library of crop preferences Access to market ? cropping pattern area Demand: Global food prices (rice & shrimp) area area Marine Fisheries catches (environment, governance) GAM: Generalised Additive Model Inland Fisheries GAM stat. model Shrimp statistical model Agriculture model improved CROPWAT Total inland catches (river, pond, shrimp) Marine catches Inland catches (fish) Bagda/Golda yield Crop yield Livelihood of the socio-ecological groups

ESPA Delta Study: Working Groups icddr,b

Survey Structure: Study Area Map You could add names of Khulna and Barisal Divisions. Unless you bring them in a later slide.

Survey Structure: Socio-Ecological Systems (SESs) Socio-Ecological Zones Major Characteristics/ Dominancy Irrigated Agriculture (Boro) Dry season rice cultivation, land use livelihoods Rain Fed Agriculture (Aman) Wet season rice dominated, land use for agriculture Charland (Riverine) Riverine livelihoods, no land use for agriculture Marine and Coastal Periphery Coastal fisheries, fish landing spots, boat building, no land use for agriculture Freshwater Shrimp (Golda) Aquaculture (freshwater shrimp), land use livelihoods, Vicinity to city area Saltwater Prawn (Bagda) Aquaculture (saltwater shrimp), land use livelihoods Sundarban Dependent Forest Products, offshore fishing, no land use for agriculture

Survey Structure: Sampling Framework

Survey Structure: Survey Timeframe WG 3: ESPA DELTA SOCIAL SURVEY First Round Mid Feb-Mid June [June, 14] Second Round Mid June-Mid Oct [Nov, 14] Third Round Mid Oct-Mid Feb [Feb, 15] February 2014- February 2015 2012 ESPA Delta Project time frame 2016

Household Questionnaire Survey: Successful Interviews

Household Questionnaire Survey: Response and Non-response rate Somebody may ask you what Reason #2 means. Can you give an example?

Themes of HH Questionnaire Survey and Survey Results General Characteristics of HH Multi-dimensional poverty Environmental Quality Migration Health Ecosystem services Gender Loans and Revenue Water salinity Livelihood Wellbeing Attachment to place Shocks Income diversity Hard to read this. Would have been better to use 2 columns side by side with headings in horizontal format so easy to read.

Household Survey Demographics General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity This is example of poor layout of pie charts. The chart is huge but the text / legend is so small no one will be able to read the numbers. Please increase font size of the legend and figures so they can be easily read. You could shrink the size of the Pies as there is no need to fill the screen with them leaving too little space for text.

Household Survey Demographics General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Same comment here - text and legend too small to read

Seasonal change in Main Drinking Water Source General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Will anyone know where the different areas are located. For example, where is Badga area which is a bit like Sundarban dependant area. You have a map.

Seasonal change in salinity level in tube well (depth > 500 ft) General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Seems like there is very little variation in salinity by season. That is surprising.

Salinity Distribution Map of Deep Tubewell Round 1 General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity

Salinity Distribution Map of Deep Tubewell Round 2 General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity

Salinity Distribution Map of Deep Tubewell Round 3 General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity

High Blood Pressure by Sex over Seasons General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity As there was little variation across seasons in salinity levels, then I guess it is not surprising that there is also little variability in (pre-)hypertension by season. A bit higher in round 2.

High Blood Pressure by Age group over Seasons General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Very clear pattern of rising hypertension by age. Does not seem to change much by season, whereas levels of pre-hypertension seems to be much higher in Round 2, then drop a little in Round 3.

Prevalence of Hypertension among Men by Socio-Ecological Zones General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Very clear pattern of rising hypertension by age. Does not seem to change much by season, whereas levels of pre-hypertension seems to be much higher in Round 2, then drop a little in Round 3.

Prevalence of Hypertension among Women by Socio-Ecological Zones General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Very clear pattern of rising hypertension by age. Does not seem to change much by season, whereas levels of pre-hypertension seems to be much higher in Round 2, then drop a little in Round 3.

Adult (15-59 Years) Nutritional Status (BMI) over Seasons General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity No seasonality in % normal, though slight declining trend in “Thin”.

Children Nutritional Status (Z-Score) over Seasons General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Interesting – Rounds 2 and 3 show big decline in all indicators.

Malnutrition of under-five children by socio-ecological zones General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Not clear what the X-axis means here. Can you give an axis title.

High blood pressure increases with the increase of salinity level in drinking water General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Very important slide. A bit hard to read as so many columns of same colours. Show (linear) rising hypertension with rising salinity, but not same pattern with pre-hypertension where levels are highest for the “Slightly Saline (1000-2000)”.

“Two Third of the Households use Ecosystem Services” General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Income from ES % 0 % 34.5 1-49 % 37.1 50-100 % 28.3

Dependency on Ecosystem Services General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Not clear what the X-axis means here. Can you give an axis title.

Measuring Poverty Cost of basic needs General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Cost of basic needs - A poor household is one that is unable to afford the food required to meet basic nutritional requirements Subjective wellbeing - A poor household is one where the household head rates his or her satisfaction with life as 4 out of 10 or less now, and as 4 out of 10 thinking forward to five years time. Two measures currently being analysed but more indicators available in the questionnaire data.

Measuring Dependence on Ecosystem Services General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Dependency based on contribution to household income from: - Agriculture - Aquaculture - Fisheries - Livestock and poultry - Homestead/farm forestry. Total income also includes off-farm labor, service employment, formal and informal business, remittances, loans and interest.

Calculation Methods General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Binomial logistic regression model with dichotomous variable – Poor/Not Poor as the outcome variable Socio-economic variables controlled for: household size, dependency ratio, sex of the household head and levels of education Interested in levels of ecosystem service use, socio- ecological system and the role of traditional coping strategies such as loans, remittances and sharecropping.

“Dependence on Ecosystem Decreases the Likelihood of Material and Subjective Poverty” General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity “The Relationship Between Poverty and Ecosystem Service Dependence is Influenced by the Socio-Ecological System in which the Household is Located”

Access and coping strategies General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Land ownership is significantly associated with subjective and material wellbeing Remittances are significantly associated with subjective wellbeing. High-interest, informal loans are significantly associated with material poverty Point 3 means “significantly POSITIVELY associated” – right? If yes then say it please.

Conclusion General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Two- third of the rural population rely on ecosystem services for livelihood generation Ecosystem services relate to poverty in a binary way – those with access are less likely to be poor and vice versa The socio-ecological system in which a household is located influences the ability to use ecosystem services to stay out of poverty Coping strategies such as remittances, loans and sharecropping have less influence on the relationship between ecosystem services and poverty

Conclusion General characteristics of HH Water Salinity Health Ecosystem Services Multi-dimensional poverty Environmental quality Gender Loans and Revenue Migration Livelihood Well Being Attachment to place Shocks Income Diversity Among the seven SESs, four SESs show higher salinity in deep tubewell water as per Bangladesh drinking water standard High blood pressure increases with the increase of salinity level in drinking water Children nutritional status shows noticeable variation over the survey period The Socio-ecological survey provided key findings in terms of coastal Bangladesh- believed to be very critical for future policy outcome for sustainable development

ESPA Delta: Consortium Partners