Earth observation and geospatial data can predict the relative distribution of village level poverty in the Sundarban Biosphere Reserve, India.

There is increasing interest in leveraging Earth Observation (EO) and geospatial data to predict and map aspects of socioeconomic conditions to support survey and census activities. This is particularly relevant for the frequent monitoring required to assess progress towards the UNs' Sustainable Development Goals (SDGs). The Sundarban Biosphere Reserve (SBR) is a region of international ecological importance, containing the Indian portion of the world's largest mangrove forest. The region is densely populated and home to over 4.4 million people, many living in chronic poverty with a strong dependence on nature-based rural livelihoods. Such livelihoods are vulnerable to frequent natural hazards including cyclone landfall and storm surges. In this study we examine associations between environmental variables derived from EO and geospatial data with a village level multidimensional poverty metric using random forest machine learning, to provide evidence in support of policy formulation in the field of poverty reduction. We find that environmental variables can predict up to 78% of the relative distribution of the poorest villages within the SBR. Exposure to cyclone hazard was the most important variable for prediction of poverty. The poorest villages were associated with relatively small areas of rural settlement (<∼30%), large areas of agricultural land (>∼50%) and moderate to high cyclone hazard. The poorest villages were also associated with less productive agricultural land than the wealthiest. Analysis suggests villages with access to more diverse livelihood options, and a smaller dependence on agriculture may be more resilient to cyclone hazard. This study contributes to the understanding of poverty-environment dynamics within Low-and middle-income countries and the associations found can inform policy linked to socio-environmental scenarios within the SBR and potentially support monitoring of work towards SDG1 (No Poverty) across the region.

Small Water Bodies in Great Britain and Ireland: Ecosystem function, human-generated degradation, and options for restorative action.

Small, 1st and 2nd-order, headwater streams and ponds play essential roles in providing natural flood control, trapping sediments and contaminants, retaining nutrients, and maintaining biological diversity, which extend into downstream reaches, lakes and estuaries. However, the large geographic extent and high connectivity of these small water bodies with the surrounding terrestrial ecosystem makes them particularly vulnerable to growing land-use pressures and environmental change. The greatest pressure on the physical processes in these waters has been their extension and modification for agricultural and forestry drainage, resulting in highly modified discharge and temperature regimes that have implications for flood and drought control further downstream. The extensive length of the small stream network exposes rivers to a wide range of inputs, including nutrients, pesticides, heavy metals, sediment and emerging contaminants. Small water bodies have also been affected by invasions of non-native species, which along with the physical and chemical pressures, have affected most groups of organisms with consequent implications for the wider biodiversity within the catchment. Reducing the impacts and restoring the natural ecosystem function of these water bodies requires a three-tiered approach based on: restoration of channel hydromorphological dynamics; restoration and management of the riparian zone; and management of activities in the wider catchment that have both point-source and diffuse impacts. Such activities are expensive and so emphasis must be placed on integrated programmes that provide multiple benefits. Practical options need to be promoted through legislative regulation, financial incentives, markets for resource services and voluntary codes and actions.

The relative contribution of sewage and diffuse phosphorus sources in the River Avon catchment, southern England: implications for nutrient management.

In order to effectively manage nutrient river load reductions and target remediation strategies, it is important to determine the relative contributions of diffuse and point sources across the river catchment. This study used a geographical information system (GIS) to apply phosphorus (P) export coefficients (obtained from the literature) to 58 water quality monitoring sites across a large, urbanised, mixed land use catchment, typical of southern lowland England (the River Avon, Warwickshire, UK). These coefficients were used to estimate the annual P load at each monitoring site, and also the relative contribution of point source (from sewage treatment works (STW)) and diffuse input (from both livestock and agricultural land use). The estimated annual P loads showed very close agreement (r2=0.98) with the measured total phosphorus (TP) loads. Sites with the highest proportion of P derived from STW had the highest TP concentrations and loads, and also had greater variations between seasons, with elevated P concentrations occurring during the summer months. The GIS model was re-run to determine the effect of an 80% reduction in P output from STW serving over 10,000 people, thereby assessing the effect of implementing the European Union's Urban Waste Water Treatment Directive (UWWTD). The exported TP load was reduced by 52%, but the sites with the highest TP concentrations were still those with the highest proportion of P derived from STW. The GIS model was re-run to estimate the impact of 80% P reductions at a further 11 STW of varying sizes. This reduced the total TP load by only 29 tonnes year-1, but greatly reduced the P concentrations in many highly nutrient contaminated tributaries. The number of sites with P concentrations greater than 1 mg l-1 was cut from 15 (before UWWTD implementation) to 2. These findings suggest that after UWWTD implementation, resources should focus on introducing tertiary sewage treatment at the remaining large STW, before targeting diffuse inputs. This conclusion is also likely to apply to other lowland river catchments in southern England, most of which have similar population densities to the River Avon.