The integrated multi-method approach demonstrates that the relationship between ecosystem services and well-being in coastal Bangladesh is highly contingent and differentiated a result of its distinct social-ecological systems (see Chap. 22). Hence, the focus shifts to understanding how ecosystem services can reduce particular types of poverty for specific groups of people over different timescales.
Rural livelihoods are diverse over space and time, and populations rely on more than one provisioning ecosystem service for their income. Ecosystem services commonly occur in bundles (sets of services that repeatedly appear together) and as such certain groups of services are more accessible than others. The adoption of a social-ecological system approach allows diversification of ecosystem service use to be considered, including being dependent on a subsidiary service in a particular zone (e.g. fishing in an agricultural area) (Sect. 2.2.1). Thus, the probability of being poor varies in space with the available bundles of ecosystem services and proximity to certain geographical features such as the coast or major rivers, or access to roads and cities.
The ability of ecosystem services to create well-being is dynamic and path dependent. Current productivity is a result of policy decisions made regarding infrastructure (e.g. coastal embankments) and the prioritisation of ecosystem services (e.g. monoculture rice agriculture versus open access fisheries) which has implications for future benefits. For example, high levels of shrimp monoculture productivity are unsustainable where supporting services have already been eroded by high salinity, but are resilient against reversal due to sea-level rise and the near impossibility of large scale desalination of soil (Sect. 2.2.3).
This example also highlights trade-offs between different bundles of ecosystem services across time and space, affecting the provision of benefits to the poorest in rural settings. There has been a steady concentration of ecosystem services into agriculture and aquaculture that tend to benefit those with access to land, to the detriment of open access provisioning services (e.g. fishing) and supporting services such as water quality—that are crucial for the poor. Thus, while ecosystem services are alleviating poverty through the export of shrimp, for example, this approach is neither sustainable nor pro-poor (Sect. 2.2.4).
However, it is crucial to note that existing inequalities within villages that keep the poor trapped in poverty are unlikely to be redressed by ecosystem service-based interventions, especially in a monetised rural economy that is becoming progressively less dependent on local ecosystem services (see Chaps. 12 and 28). For example, currently, a third of the population studied in this research have no access to ecosystem services at all for income, and even fewer have access to land to cultivate (Sect. 2.2.5).
Finally, the opportunities and losses occurring in the region should be analysed in the context of the market economy. While traditional ecosystem-based and social mechanisms of survival and subsistence have been undermined by market-based approaches, many of the opportunities that could emerge—namely, more sophisticated off-farm activities—have not materialised. Thus, while ecosystem services are increasingly monetised, the subsistence activities they undermine have not been replaced. Migration to alternative labour markets and debt tend to fill any gaps in income.
The means by which ecosystem services generate well-being in Bangladesh is therefore in transition, moving from subsistence-based approaches that provide safety nets, but without the potential for poverty alleviation, to market-based approaches where economic benefits are greater but tend to accrue to fewer people living in these rural areas and those who already have resources. Concurrently, rural livelihoods have become less and less dependent on local ecosystem services, with off-farm work and migration to urban areas or alternative labour markets contributing a growing share to household incomes.
2.1 New Analysis of Ecosystems as Critical to Poverty and Development
The approach adopted in this research to understanding poverty-environment linkages is novel in four key ways. First, it takes an integrated, systems approach that considers interactions, feedbacks and trade-offs, which is missing in most analyses (Dempsey and Robertson 2012). Second, the research considers many different epistemic approaches including the consideration of poverty-environment linkages from multiple methodological and theoretical standpoints (Nicholls et al. 2016). Some of these are integrated within the modelling framework, while others provide richness and understanding to the findings. Third, the analysis is future oriented. It is not sufficient to understand present ecological determinants of well-being, without understanding the capacity for these systems or services to continue to generate well-being into the future under various political, social-economic and environmental scenarios. Finally, the outcome of the analysis is not an answer to a single question, but rather a process which provides key insights concerning associative and causal linkages that have the potential to untangle and answer a wide range of questions on poverty and the environment (Chap. 28).
The research also describes a range of plausible future trajectories derived in a participatory manner. Hence, while the individual components of the analysis are interesting, the integration of these components is ground-breaking—for example, the integration of social differentiation in rural settlements with biophysical outputs to model poverty through time based on changes in the natural environment.
2.2 Social Mechanisms Co-vary with the Bundles of Ecosystem Services
This research dynamically analyses the two most important ecosystem services in terms of livelihoods in the delta: agriculture (including aquaculture where appropriate Chap. 24) and fisheries (focusing on offshore capture fisheries Chap. 25) under future environmental change and management scenarios. The area and species distribution of the Sundarbans mangrove forest are also modelled with a preliminary assessment of ecosystem services including protection against storm surges (Chap. 26). These three key provisioning services were operationalised using seven social-ecological systems, defined as freshwater and brackish aquaculture, irrigated and non-irrigated agriculture, riverine and char environments, the coastal zone and the Sundarbans dependent zone (see Chap. 22, Adams et al. 2013, 2016).
The social-ecological system classification recognises that although in certain regions a specific type of service may dominate livelihoods, households usually have more than one type of income source and that these sources may change through the year depending on the character of the ecosystem (Raudsepp-Hearne et al. 2010). Households select different ecosystem services from within the bundle at different times of the year. Social-ecological systems are thus the result of human activities to mediate the negative impacts of environmental variability and to manage bundles of ecosystem services (Martín-López et al. 2012). Social systems dictate the rules of access to resources and influence the winners and losers of trade-offs between different benefits (Walker et al. 2004), ultimately affecting the relationship between ecosystem service dependence and poverty outcomes.
The relationship between ecosystem services and poverty changes because social mechanisms and other factors co-vary with bundles of ecosystem services. For example, the presence of opportunities for supplementing incomes with open access resources (e.g. fisheries, forest products), land ownership, opportunities for sharecropping and leasing land, agricultural labour, access to off-farm income opportunities, the level of exposure to extreme events, the impacts of cyclones and storm surges, the negative impacts on agriculture from aquaculture and the presence of landlords on whom the poor can rely for assistance through patron-client relationships all vary between social-ecological systems (see Adams and Adger 2016)
2.3 Spatial Variation in Ecosystem Services within Delta Environments
Assets, income, nutrition- and blood pressure
-related health indicators and subjective well-being vary with location. Waterlogging, high salinity and access are significantly associated with poverty in the study area with different spatial patterns apparent for these three variables (see Chap. 21 and Amoako Johnson et al. 2016). Soil salinity is significantly associated with poverty around the Sundarbans, waterlogging in the centre of the study area, while the lack of access dominates in the east of the study area. For example, the factors associated with asset poverty vary across the study area. Considering all social-ecological systems, the probability of being materially and subjectively poor decreases as household dependence on ecosystem services for income increases. However, the irrigated agricultural zone showed the opposite relationship, with increasing dependence on ecosystem services being associated with a higher probability of being materially poor.
Similar spatial and social-ecological system-based differences are found in the health indicators (Chap. 27) and in how individuals perceive their own well-being. Levels of malnourishment
are higher than the national average but vary across the study area. For example, food consumption varies across the study area and by social-ecological system. Irrigated agriculture areas show the lowest protein intake and one of the lowest calorie intakes. In comparison, households living in the char and rain-fed agricultural social-ecological systems also have low calorie intake levels, but the protein consumption (from fish) is much higher and child under-nutrition lower. This indicates that fish consumption appears crucial to health in some social-ecological system.
2.4 Temporal Variations in Well-Being from Ecosystems
Ecosystem services vary by season and across years with implications for chronic and seasonal
poverty. When examining past trends, three factors suggests that maintaining current productivity of agriculture and aquaculture will be challenging. First, historic analysis shows that recent increases in these provisioning services have been accompanied by concomitant decreases in underlying supporting services (see Chap. 5 and Hossain et al. 2016). Second, infrastructural interventions to facilitate increases in productivity of provisioning services (e.g. coastal embankments and polders) have caused a rigidity trap reducing flexibility in adaptation to future climate change (Adams et al. 2013). Third, seasonal changes (wet/dry seasons) in household livelihoods reflect changing work opportunities, leading to different long-term poverty trajectories (Lázár et al. 2016).
Since the 1950s, production of rice
and fisheries has increased consistently with gross domestic product (GDP) and per capita income (Hossain et al. 2016). However, this has been accompanied by a decrease in the quality of supporting services such as water quality and availability, natural hazard and erosion protection and maintenance of biodiversity, as well as availability of forest products. Thus, although provisioning ecosystem services of rice and agriculture have supported national level growth, it has been at the expense of the systems that support them (including potentially irrigation-induced salinisation of soil) and therefore may not be sustainable into the future (see Chap. 24).
During the 1990s, many provisioning and supporting ecosystem services declined (Hossain et al. 2016) linked to the modification
of the natural functioning of rivers and their interaction with the floodplain. This includes tidal sediment deposition outside of the polders and drainage congestion within the polders (Islam 2006), while the interiors of polders have lost substantial elevation (e.g. Hoque and Alam 1997). It was these polders
that initially enabled an increase in productivity by protecting the floodplain from inundation and, in turn, allowed the development of multi-cropping and aquaculture.
The longer-term future implications of such past and irreversible changes to the natural environment are problematic. For example, while productivity increases were enabled by this infrastructure, continued increases will be challenged under a future changing climate (Adams et al. 2014). Some of these problems may be ameliorated through upgrading the embankments but a more fundamentally sustainable long-term management technique such as controlled sedimentation within polders to build elevation, termed ‘tidal river management’ in Bangladesh (Amir et al. 2013; Auerbach et al. 2015), may be beneficial on a large scale. Looking into the future it is unclear whether an increase in GDP
will eventually lead to the environmental investment necessary (i.e. following the environmental Kuznets curve, Hossain et al. 2016) to halt the further degradation of supporting services for agriculture.
Agricultural models of the delta (Chaps. 24 and 28) show that dry season
productivity is currently constrained by salinity. Crop productivity may be maintainable to 2050 due to the positive impacts of projected increases in rainfall, temperature (within the range of rice) and CO2 fertilisation. The constraining factors are fertility and heat stress if the monsoon season rains remain sufficient to remove salinity that has accumulated during the dry season. This, however, will be impacted in the longer term by sea-level rise, subsidence, dry season decreases in upstream flow and human water management (Chaps. 13, 16 and 17). Again tidal river management may be applied. A second crop could provide an additional income although income from wet season rice cultivation is constrained by low market prices.
Fisheries are second only to agriculture as a source of income in Bangladesh and form the main source of protein (Chap. 27). Offshore capture fisheries models (Chap. 25) project small decreases in overall fisheries productivity with climate change. It remains to be seen whether such decreases can be offset with sustainable management practices. However, the two most important fish species (Bombay duck and especially Hilsa) are susceptible to a potential collapse due to unsustainable fishing practices. This would intensify livelihood stress for subsistence fishers and emphasise the importance of sustainable exploitation of these resources.
A final way that temporal dimensions can provide answers as to why and when ecosystem services may be able to alleviate poverty emerges from analysis of long-term poverty trajectories, driven by day-to-day coping strategies and seasonal livelihood diversification. These trajectories have been characterised for a range of livelihood diversification strategies in a quantitative model (Lázár et al. 2016) based on survey data collected as part of this research (see Chap. 23 and Adams et al. 2016), household income and expenditure data and census data. Modelling livelihood trajectories for different archetypal households, with different seasonal livelihood strategies and multiple coping strategies during periods of low income, shows the transient nature of poverty and the ways in which farm and off-farm employment combine to create more or less stable well-being pathways. The analysis (see Chap. 28) shows that, while land ownership is crucial to avoid poverty, the poverty outcomes of small landowners are highly variable. Differences in micro-level choices therefore accumulate to create different outcomes for households with similar livelihood and poverty characteristics. The analysis also shows that most households have incomes that do not come from ecosystem services. Many households have two or three income sources, and almost all households show seasonal changes in their income type. Strategies vary, with different variations in income between seasons and different diversification strategies to maintain income. Modelling poverty trajectories in this way allows these seasonal drivers of long-term poverty dynamics to be integrated with other biophysical models to understand drivers of poverty at different scales and how poverty may change in the future under different interventions. Simulation results reveal the poverty alleviation role of off-farm income types and the importance of the quality of that off-farm employment, since households relying on small-scale, cottage industries are most likely to be poor and stay poor. These results support other studies that indicate land ownership is a necessary stepping stone out of poverty as it provides households with the capital to access high end off-farm income opportunities.
This research has therefore confirmed the need to consider ecosystem services for poverty alleviation in the wider context of agrarian reform. Many of the barriers to creating pro-poor ecosystem services-based livelihoods emerge from processes put into place during the ‘Green Revolution’—for example, polders (Adams et al. 2014), and, more recently, the Blue Revolution of the aquaculture industry (Amoako Johnson et al. 2016). The judgement is whether any environmental degradation is justified for food security, national wealth objectives and the fair distribution of benefits
2.5 Ecosystem Service Trade-offs between Social-Ecological Systems and Labour Mobility
Whether or not ecosystem services are a force for good in the diverse and dynamic delta environment of coastal Bangladesh relates to the nature of the trade-offs between different social-ecological systems. Trade-offs are an important part of the ecosystem service framework; for each service prioritised, another service will be diminished (Rodriguez et al. 2006). The same is true in the delta. Analysing past trends in the delta shows trade-offs between provisioning ecosystem services (that have been increasing) and the systems that support them (that have shown a consistent decline) (Hossain et al. 2016).
In the study area, trade-offs tended to work in a way that further concentrates rights to ecosystem services to those that already have them. For example, agriculture and aquaculture practices contribute to the degradation of the open access resources on which the landless depend, leaving them even further marginalised. This can be conceptualised by looking at the nature of the property rights system. Social-ecological systems where private property rights dominate, such as aquaculture, are most destructive to other systems. Ecosystem services from open access systems more readily co-exist. People react to changes in ecosystem services and there is a livelihood mobility dimension to any trade-offs between social-ecological systems. People move to alternative systems, or change jobs, to counteract the seasonality and irregularity of income from ecosystem services in one social-ecological system and when systems are degraded over the long term or labour is no longer required (e.g. as agricultural land is converted to agriculture employment declines significantly). Thus, migration of people between systems and livelihoods counters to the availability of ecosystem services.
Figure 2.1 illustrates some of the ways in which ecosystem services and benefits are transferred between different social-ecological systems across space and time, and the concurrent migration flows following livelihood opportunities. Ecosystem benefits, and thus people, move from one social-ecological system to another because of land use change and the transformation of one system to another, and seasonally. For example, where embankments protect the flood plain from inundation, those dependent on capture fisheries for livelihoods (e.g. traditional fishermen, boatmen for transportation) rely more heavily on the other social-ecological systems, move into off-farm opportunities or leave the area in search of economic opportunities. Therefore, labour is constantly moving between these different systems based on the season or the availability of resources.
Ecosystem services and benefits, or the capacity of a system to be productive, are also ‘moving’ between each system, the productivity of each social-ecological system being affected by the productivity of the others. The movement of ecosystem services between the systems is exemplified in the supply of wild shrimp larvae for pond aquaculture, sourced in the Sundarbans forest. While subsistence fishing exists without any detriment to the Sundarbans, this fry collection is a destructive process, not only to the Sunderbans where fish productivity is reduced because of bycatch but also in offshore fisheries, since the Sundarban forest supports nurseries for offshore fisheries by providing a supply of shrimp fry (Islam and Islam 2011). Thus the increase in productivity of shrimp farms has been at the expense of the Sundarbans biodiversity and productivity and the offshore fish catch