Implications of agricultural land use change to ecosystem services in the Ganges delta.

Ecosystems provide the basis for human civilization and natural capital for green economy and sustainable development. Ecosystem services may range from crops, fish, freshwater to those that are harder to see such as erosion regulation, carbon sequestration, and pest control. Land use changes have been identified as the main sources of coastal and marine pollution in Bangladesh. This paper explores the temporal variation of agricultural land use change and its implications with ecosystem services in the Ganges delta. With time agricultural lands have been decreased and wetlands have been increased at a very high rate mainly due to the growing popularity of saltwater shrimp farming. In a span of 28 years, the agricultural lands have been reduced by approximately 50%, while the wetlands have been increased by over 500%. A large portion (nearly 40%) of the study area is covered by the Sundarbans which remained almost constant which can be attributed to the strict regulatory intervention to preserve the Sundarbans. The settlement & others land use type has also been increased to nearly 5%. There is a gradual uptrend of shrimp and fish production in the study area. The findings suggest that there are significant linkages between agricultural land use change and ecosystem services in the Ganges delta in Bangladesh. The continuous decline of agricultural land (due to salinization) and an increase of wetland have been attributed to the conversion of agricultural land into shrimp farming in the study area. Such land use change requires significant capital, therefore, only investors and wealthier land owners can get the higher profit from the land conversion while the poor people is left with the environmental consequences that affect their long-term lives and livelihood. An environmental management plan is proposed for sustainable land use in the Ganges delta in Bangladesh.

High-resolution estimates of social distancing feasibility, mapped for urban areas in sub-Saharan Africa.

Social distancing has been widely-implemented as a public health measure during the COVID-19 pandemic. Despite widespread application of social distancing guidance, the feasibility of people adhering to such guidance varies in different settings, influenced by population density, the built environment and a range of socio-economic factors. Social distancing constraints however have only been identified and mapped for limited areas. Here, we present an ease of social distancing index, integrating metrics on urban form and population density derived from new multi-country building footprint datasets and gridded population estimates. The index dataset provides estimates of social distancing feasibility, mapped at high-resolution for urban areas across 50 countries in sub-Saharan Africa.

High-resolution population estimation using household survey data and building footprints.

The national census is an essential data source to support decision-making in many areas of public interest. However, this data may become outdated during the intercensal period, which can stretch up to several decades. In this study, we develop a Bayesian hierarchical model leveraging recent household surveys and building footprints to produce up-to-date population estimates. We estimate population totals and age and sex breakdowns with associated uncertainty measures within grid cells of approximately 100 m in five provinces of the Democratic Republic of the Congo, a country where the last census was completed in 1984. The model exhibits a very good fit, with an R2 value of 0.79 for out-of-sample predictions of population totals at the microcensus-cluster level and 1.00 for age and sex proportions at the province level. This work confirms the benefits of combining household surveys and building footprints for high-resolution population estimation in countries with outdated censuses.

Modelling household well-being and poverty trajectories: An application to coastal Bangladesh.

Resource-based livelihoods are uncertain and potentially unstable due to variability over time, including seasonal variation: this instability threatens marginalised populations who may fall into poverty. However, empirical understanding of trajectories of household well-being and poverty is limited. Here, we present a new household-level model of poverty dynamics based on agents and coping strategies-the Household Economy And Poverty trajectory (HEAP) model. HEAP is based on established economic and social insights into poverty dynamics, with a demonstration of the model calibrated with a qualitative and quantitative household survey in coastal Bangladesh. Economic activity in Bangladesh is highly dependent on natural resources; poverty is widespread; and there is high variability in ecosystem services at multiple temporal scales. The results show that long-term decreases in poverty are predicated more on the stability of, and returns from, livelihoods rather than their diversification. Access to natural resources and ecosystem service benefits are positively correlated with stable income and multidimensional well-being. Households that remain in poverty are those who experience high seasonality of income and are involved in small scale enterprises. Hence, seasonal variability in income places significant limits on natural resources providing routes out of poverty. Further, projected economic trends to 2030 lead to an increase in well-being and a reduction in poverty for most simulated household types.

Responses of Aquatic Plants to Eutrophication in Rivers: A Revised Conceptual Model.

Compared to research on eutrophication in lakes, there has been significantly less work carried out on rivers despite the importance of the topic. However, over the last decade, there has been a surge of interest in the response of aquatic plants to eutrophication in rivers. This is an area of applied research and the work has been driven by the widespread nature of the impacts and the significant opportunities for system remediation. A conceptual model has been put forward to describe how aquatic plants respond to eutrophication. Since the model was created, there have been substantial increases in our understanding of a number of the underlying processes. For example, we now know the threshold nutrient concentrations at which nutrients no longer limit algal growth. We also now know that the physical habitat template of rivers is a primary selector of aquatic plant communities. As such, nutrient enrichment impacts on aquatic plant communities are strongly influenced, both directly and indirectly, by physical habitat. A new conceptual model is proposed that incorporates these findings. The application of the model to management, system remediation, target setting, and our understanding of multi-stressor systems is discussed. We also look to the future and the potential for new numerical models to guide management.

A framework for identifying and selecting long term adaptation policy directions for deltas.

Deltas are precarious environments experiencing significant biophysical, and socio-economic changes with the ebb and flow of seasons (including with floods and drought), with infrastructural developments (such as dikes and polders), with the movement of people, and as a result of climate and environmental variability and change. Decisions are being taken about the future of deltas and about the provision of adaptation investment to enable people and the environment to respond to the changing climate and related changes. The paper presents a framework to identify options for, and trade-offs between, long term adaptation strategies in deltas. Using a three step process, we: (1) identify current policy-led adaptations actions in deltas by conducting literature searches on current observable adaptations, potential transformational adaptations and government policy; (2) develop narratives of future adaptation policy directions that take into account investment cost of adaptation and the extent to which significant policy change/political effort is required; and (3) explore trade-offs that occur within each policy direction using a subjective weighting process developed during a collaborative expert workshop. We conclude that the process of developing policy directions for adaptation can assist policy makers in scoping the spectrum of options that exist, while enabling them to consider their own willingness to make significant policy changes within the delta and to initiate transformative change.

Applying the global RCP-SSP-SPA scenario framework at sub-national scale: A multi-scale and participatory scenario approach.

To better anticipate potential impacts of climate change, diverse information about the future is required, including climate, society and economy, and adaptation and mitigation. To address this need, a global RCP (Representative Concentration Pathways), SSP (Shared Socio-economic Pathways), and SPA (Shared climate Policy Assumptions) (RCP-SSP-SPA) scenario framework has been developed by the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC-AR5). Application of this full global framework at sub-national scales introduces two key challenges: added complexity in capturing the multiple dimensions of change, and issues of scale. Perhaps for this reason, there are few such applications of this new framework. Here, we present an integrated multi-scale hybrid scenario approach that combines both expert-based and participatory methods. The framework has been developed and applied within the DECCMA1 project with the purpose of exploring migration and adaptation in three deltas across West Africa and South Asia: (i) the Volta delta (Ghana), (ii) the Mahanadi delta (India), and (iii) the Ganges-Brahmaputra-Meghna (GBM) delta (Bangladesh/India). Using a climate scenario that encompasses a wide range of impacts (RCP8.5) combined with three SSP-based socio-economic scenarios (SSP2, SSP3, SSP5), we generate highly divergent and challenging scenario contexts across multiple scales against which robustness of the human and natural systems within the deltas are tested. In addition, we consider four distinct adaptation policy trajectories: Minimum intervention, Economic capacity expansion, System efficiency enhancement, and System restructuring, which describe alternative future bundles of adaptation actions/measures under different socio-economic trajectories. The paper highlights the importance of multi-scale (combined top-down and bottom-up) and participatory (joint expert-stakeholder) scenario methods for addressing uncertainty in adaptation decision-making. The framework facilitates improved integrated assessments of the potential impacts and plausible adaptation policy choices (including migration) under uncertain future changing conditions. The concept, methods, and processes presented are transferable to other sub-national socio-ecological settings with multi-scale challenges.

Soil salinity, household wealth and food insecurity in tropical deltas: evidence from south-west coast of Bangladesh.

As a creeping process, salinisation represents a significant long-term environmental risk in coastal and deltaic environments. Excess soil salinity may exacerbate existing risks of food insecurity in densely populated tropical deltas, which is likely to have a negative effect on human and ecological sustainability of these regions and beyond. This study focuses on the coastal regions of the Ganges-Brahmaputra delta in Bangladesh, and uses data from the 2010 Household Income and Expenditure Survey and the Soil Resource Development Institute to investigate the effect of soil salinity and wealth on household food security. The outcome variables are two widely used measures of food security: calorie availability and household expenditure on food items. The main explanatory variables tested include indicators of soil salinity and household-level socio-economic characteristics. The results of logistic regression show that in unadjusted models, soil salinisation has a significant negative effect on household food security. However, this impact becomes statistically insignificant when households' wealth is taken into account. The results further suggest that education and remittance flows, but not gender or working status of the household head, are significant predictors of food insecurity in the study area. The findings indicate the need to focus scholarly and policy attention on reducing wealth inequalities in tropical deltas in the context of the global sustainable deltas initiative and the proposed Sustainable Development Goals.

Is shrimp farming a successful adaptation to salinity intrusion? A geospatial associative analysis of poverty in the populous Ganges-Brahmaputra-Meghna Delta of Bangladesh.

The Ganges-Brahmaputra-Meghna delta of Bangladesh is one of the most populous deltas in the world, supporting as many as 140 million people. The delta is threatened by diverse environmental stressors including salinity intrusion, with adverse consequences for livelihood and health. Shrimp farming is recognised as one of the few economic adaptations to the impacts of the rapidly salinizing delta. Although salinity intrusion and shrimp farming are geographically co-located in the delta, there has been no systematic study to examine their geospatial associations with poverty. In this study, we use multiple data sources including Census, Landsat Satellite Imagery and soil salinity survey data to examine the extent of geospatial clustering of poverty within the delta and their associative relationships with salinity intensity and shrimp farming. The analysis was conducted at the union level, which is the lowest local government administrative unit in Bangladesh. The findings show a strong clustering of poverty in the delta, and whilst different intensities of salinization are significantly associated with increasing poverty, neither saline nor freshwater shrimp farming has a significant association with poverty. These findings suggest that whilst shrimp farming may produce economic growth, in its present form it has not been an effective adaptation for the poor and marginalised areas of the delta. The study demonstrates that there are a series of drivers of poverty in the delta, including salinization, water logging, wetland/mudflats, employment, education and access to roads, amongst others that are discernible spatially, indicating that poverty alleviation programmes in the delta require strengthening with area-specific targeted interventions.

Spatial and temporal dynamics of multidimensional well-being, livelihoods and ecosystem services in coastal Bangladesh.

Populations in resource dependent economies gain well-being from the natural environment, in highly spatially and temporally variable patterns. To collect information on this, we designed and implemented a 1586-household quantitative survey in the southwest coastal zone of Bangladesh. Data were collected on material, subjective and health dimensions of well-being in the context of natural resource use, particularly agriculture, aquaculture, mangroves and fisheries. The questionnaire included questions on factors that mediate poverty outcomes: mobility and remittances; loans and micro-credit; environmental perceptions; shocks; and women's empowerment. The data are stratified by social-ecological system to take into account spatial dynamics and the survey was repeated with the same respondents three times within a year to incorporate seasonal dynamics. The dataset includes blood pressure measurements and height and weight of men, women and children. In addition, the household listing includes basic data on livelihoods and income for approximately 10,000 households. The dataset facilitates interdisciplinary research on spatial and temporal dynamics of well-being in the context of natural resource dependence in low income countries.

Projected changes in area of the Sundarban mangrove forest in Bangladesh due to SLR by 2100.

The Sundarbans mangrove ecosystem, located in India and Bangladesh, is recognized as a global priority for biodiversity conservation and is an important provider of ecosystem services such as numerous goods and protection against storm surges. With global mean sea-level rise projected as up to 0.98 m or greater by 2100 relative to the baseline period (1985-2005), the Sundarbans - mean elevation presently approximately 2 m above mean sea-level - is under threat from inundation and subsequent wetland loss; however the magnitude of loss remains unclear. We used remote and field measurements, geographic information systems and simulation modelling to investigate the potential effects of three sea-level rise scenarios on the Sundarbans within coastal Bangladesh. We illustrate how the Sea Level Affecting Marshes Model (SLAMM) is able to reproduce the observed area losses for the period 2000-2010. Using this calibrated model and assuming that mean sea-level is a better proxy than the SLAMM assumed mean lower low water for Mangrove area delineation, the estimated mangrove area net losses (relative to year 2000) are 81-178 km2, 111-376 km2 and 583-1393 km2 for relative sea-level rise scenarios to 2100 of 0.46 m, 0.75 m and 1.48 m, respectively and net subsidence of ±2.5 mm/year. These area losses are very small (<10 % of present day area) and significantly smaller than previous research has suggested. Our simulations also suggest that erosion rather than inundation may remain the dominant loss driver to 2100 under certain scenarios of sea-level rise and net subsidence. Only under the highest scenarios does inundation due to sea-level rise become the dominant loss process.

Simulating yield response of rice to salinity stress with the AquaCrop model.

The FAO AquaCrop model has been widely applied throughout the world to simulate crop responses to deficit water applications. However, its application to saline conditions is not yet reported, though saline soils are common in coastal areas. In this study, we parameterized and tested AquaCrop to simulate rice yield under different salinity regimes. The data and information required in the model were collected through a field experiment at the Bangladesh Agricultural Research Institute, Gazipur. The experiment was conducted with the BRRI Dhan28, a popular boro rice variety in Bangladesh, with five levels of saline water irrigation, three replicates for each level. In addition, field monitoring was carried out at Satkhira in the southwest coastal region of Bangladesh to collect data and information based on farmers' practices and to further validate the model. The results indicated that the AquaCrop model with most of its default parameters could replicate the variation of rice yield with the variation of salinity reasonably well. The root mean square error and mean absolute error of the model yield were only 0.12 t per ha and 0.03 t per ha, respectively. The crop response versus soil salinity stress curve was found to be convex in shape with a lower threshold of 2 dS m(-1), an upper threshold of 10 dS m(-1) and a shape factor of 2.4. As the crop production system in the coastal belt of Bangladesh has become vulnerable to climate induced sea-level rise and the consequent increase in water and soil salinity, the AquaCrop would be a useful tool in assessing the potential impact of these future changes as well as other climatic parameters on rice yield in the coastal region.

Agricultural livelihoods in coastal Bangladesh under climate and environmental change--a model framework.

Coastal Bangladesh experiences significant poverty and hazards today and is highly vulnerable to climate and environmental change over the coming decades. Coastal stakeholders are demanding information to assist in the decision making processes, including simulation models to explore how different interventions, under different plausible future socio-economic and environmental scenarios, could alleviate environmental risks and promote development. Many existing simulation models neglect the complex interdependencies between the socio-economic and environmental system of coastal Bangladesh. Here an integrated approach has been proposed to develop a simulation model to support agriculture and poverty-based analysis and decision-making in coastal Bangladesh. In particular, we show how a simulation model of farmer's livelihoods at the household level can be achieved. An extended version of the FAO's CROPWAT agriculture model has been integrated with a downscaled regional demography model to simulate net agriculture profit. This is used together with a household income-expenses balance and a loans logical tree to simulate the evolution of food security indicators and poverty levels. Modelling identifies salinity and temperature stress as limiting factors to crop productivity and fertilisation due to atmospheric carbon dioxide concentrations as a reinforcing factor. The crop simulation results compare well with expected outcomes but also reveal some unexpected behaviours. For example, under current model assumptions, temperature is more important than salinity for crop production. The agriculture-based livelihood and poverty simulations highlight the critical significance of debt through informal and formal loans set at such levels as to persistently undermine the well-being of agriculture-dependent households. Simulations also indicate that progressive approaches to agriculture (i.e. diversification) might not provide the clear economic benefit from the perspective of pricing due to greater susceptibility to climate vagaries. The livelihood and poverty results highlight the importance of the holistic consideration of the human-nature system and the careful selection of poverty indicators. Although the simulation model at this stage contains the minimum elements required to simulate the complexity of farmer livelihood interactions in coastal Bangladesh, the crop and socio-economic findings compare well with expected behaviours. The presented integrated model is the first step to develop a holistic, transferable analytic method and tool for coastal Bangladesh.

An assessment of the fine sediment dynamics in an upland river system: INCA-Sed modifications and implications for fisheries.

There is a need for better links between hydrology and ecology, specifically between landscapes and riverscapes to understand how processes and factors controlling the transport and storage of environmental pollution have affected or will affect the freshwater biota. Here we show how the INCA modelling framework, specifically INCA-Sed (the Integrated Catchments model for Sediments) can be used to link sediment delivery from the landscape to sediment changes in-stream. INCA-Sed is a dynamic, process-based, daily time step model. The first complete description of the equations used in the INCA-Sed software (version 1.9.11) is presented. This is followed by an application of INCA-Sed made to the River Lugg (1077 km(2)) in Wales. Excess suspended sediment can negatively affect salmonid health. The Lugg has a large and potentially threatened population of both Atlantic salmon (Salmo salar) and Brown Trout (Salmo trutta). With the exception of the extreme sediment transport processes, the model satisfactorily simulated both the hydrology and the sediment dynamics in the catchment. Model results indicate that diffuse soil loss is the most important sediment generation process in the catchment. In the River Lugg, the mean annual Guideline Standard for suspended sediment concentration, proposed by UKTAG, of 25 mg l(-1) is only slightly exceeded during the simulation period (1995-2000), indicating only minimal effect on the Atlantic salmon population. However, the daily time step simulation of INCA-Sed also allows the investigation of the critical spawning period. It shows that the sediment may have a significant negative effect on the fish population in years with high sediment runoff. It is proposed that the fine settled particles probably do not affect the salmonid egg incubation process, though suspended particles may damage the gills of fish and make the area unfavourable for spawning if the conditions do not improve.