Spatial Heterogeneity and Kinetic Regulation of Arsenic Dynamics in Mangrove Sediments: The Sundarbans, Bangladesh

The biogeochemistry of arsenic (As) in sediments is regulated by multiple factors such as particle size, dissolved organic matter (DOM), iron mobilization, and sediment binding characteristics, among others. Understanding the heterogeneity of factors affecting As deposition and the kinetics of mobilization, both horizontally and vertically, across sediment depositional environments was investigated in Sundarban mangrove ecosystems, Bengal Delta, Bangladesh. Sediment cores were collected from 3 different Sundarbans locations and As concentration down the profiles were found to be more associated with elevated Fe and Mn than with organic matter (OM). At one site chosen for field monitoring, sediment cores, pore and surface water, and in situ diffusive gradients in thin films (DGT) measurements (which were used to model As sediment pore-water concentrations and resupply from the solid phase) were sampled from four different subhabitats. Coarse-textured riverbank sediment porewaters were high in As, but with a limited resupply of As from the solid phase compared to fine-textured and high organic matter content forest floor sediments, where porewater As was low, but with much higher As resupply. Depositional environment (overbank verses forest floor) and biological activity (input of OM from forest biomass) considerably affected As dynamics over very short spatial distances in the mosaic of microhabitats that constitute a mangrove ecosystem.

Combining multi-scale geophysical techniques for robust hydro-structural characterisation in catchments underlain by hard rock in post-glacial regions

Accurate conceptual models of groundwater systems are essential for correct interpretation of monitoring data in catchment studies. In surface-water dominated hard rock regions, modern ground and surface water monitoring programmes often have very high resolution chemical, meteorological and hydrological observations but lack an equivalent emphasis on the subsurface environment, the properties of which exert a strong control on flow pathways and interactions with surface waters. The reasons for this disparity are the complexity of the system and the difficulty in accurately characterising the subsurface, except locally at outcrops or in boreholes. This is particularly the case in maritime north-western Europe, where a legacy of glacial activity, combined with large areas underlain by heterogeneous igneous and metamorphic bedrock, make the structure and weathering of bedrock difficult to map or model. Traditional approaches which seek to extrapolate information from borehole to field-scale are of limited application in these environments due to the high degree of spatial heterogeneity. Here we apply an integrative and multi-scale approach, optimising and combining standard geophysical techniques to generate a three-dimensional geological conceptual model of the subsurface in a catchment in NE Ireland. Available airborne LiDAR, electromagnetic and magnetic data sets were analysed for the region. At field-scale surface geophysical methods, including electrical resistivity tomography, seismic refraction, ground penetrating radar and magnetic surveys, were used and combined with field mapping of outcrops and borehole testing. The study demonstrates how combined interpretation of multiple methods at a range of scales produces robust three-dimensional conceptual models and a stronger basis for interpreting groundwater and surface water monitoring data.

Exploiting Human Resource Requirements to Infer Human Movement Patterns for Use in Modelling Disease Transmission Systems: An Example from Eastern Province, Zambia

In this research, an agent-based model (ABM) was developed to generate human movement routes between homes and water resources in a rural setting, given commonly available geospatial datasets on population distribution, land cover and landscape resources. ABMs are an object-oriented computational approach to modelling a system, focusing on the interactions of autonomous agents, and aiming to assess the impact of these agents and their interactions on the system as a whole. An A* pathfinding algorithm was implemented to produce walking routes, given data on the terrain in the area. A* is an extension of Dijkstra's algorithm with an enhanced time performance through the use of heuristics. In this example, it was possible to impute daily activity movement patterns to the water resource for all villages in a 75 km long study transect across the Luangwa Valley, Zambia, and the simulated human movements were statistically similar to empirical observations on travel times to the water resource (Chi-squared, 95% confidence interval). This indicates that it is possible to produce realistic data regarding human movements without costly measurement as is commonly achieved, for example, through GPS, or retrospective or real-time diaries. The approach is transferable between different geographical locations, and the product can be useful in providing an insight into human movement patterns, and therefore has use in many human exposure-related applications, specifically epidemiological research in rural areas, where spatial heterogeneity in the disease landscape, and space-time proximity of individuals, can play a crucial role in disease spread.

Using choice experiments to explore the spatial distribution of willingness to pay for rural landscape improvements

We report findings from a choice experiment survey designed to estimate the economic benefits of policy measures to improve the rural landscape in the Republic of Ireland. Using a panel mixed logit specification to account for unobserved taste heterogeneity we derived individual-specific willingness-to-pay (WTP) estimates for each respondent in the sample. We subsequently investigated the spatial dependence of these estimates. Results suggest the existence of positive spatial autocorrelation for all rural landscape attributes. As a means of benefit transfer, kriging methods were employed to interpolate WTP estimates across the whole of the Republic of Ireland. The kriged WTP surfaces confirm the existence of spatial dependence and illustrate the implied spatial variation and regional disparities in WTP for all the rural landscape improvements investigated.

Community structure, diversity and spatial organization of enchytraeids in Mediterranean urban holm oak stands

There is a strong northern bias in Europe as regards enchytraeid community ecology, particularly in urban settings. We approached the enchytraeid assemblages of urban holm oak stands in Naples and Siena adopting a high intensity sampling that, for the first time in the Mediterranean climate zone, would ensure that the data collected be representative of the target populations. Structural parameters (diversity and evenness, biomass, size classes, aggregation) were compared across different spatial (regional, urban district, within habitat) and temporal scales (season and year). Species richness was found to change significantly only at regional scale; background data suggest that this may depend on the higher environmental heterogeneity occurring at Naples. Differences in size class structure were significant only on a seasonal scale and within either city separately. With one exception (Fridericia bulbosa s.s.), the patterns of spatial aggregation of the common species were fairly robust and the total range of patchiness was consistent with previous studies, despite the different sampling methodologies. The size of the sampling unit, the number of replicates per plot and the number of plots proposed in this study appear suitable to obviate the difficulties of evaluating Mediterranean enchytraeid communities.

Spatial Variations of the Methanogenic Communities in the Sediments of Tropical Mangroves

Methane production by methanogens in mangrove sediments is known to contribute significantly to global warming, but studies on the shift of methanogenic community in response to anthropogenic contaminations were still limited. In this study, the effect of anthropogenic activities in the mangrove sediments along the north and south coastlines of Singapore were investigated by pyrosequencing of the mcrA gene. Our results showed that hydrogenotrophic, acetoclastic and methylotrophic methanogens coexist in the sediments. The predominance of the methylotrophic Methanosarcinales reflects the potential for high methane production as well as the possible availability of low acetate and high methylated C-1 compounds as substrates. A decline in the number of acetoclastic/methylotrophic methanogens in favor of hydrogenotrophic methanogens was observed along a vertical profile in Sungei Changi, which was contaminated by heavy metals. The diversity of methanogens in the various contaminated stations was significantly different from that in a pristine St. John’s Island. The spatial variation in the methanogenic communities among the different stations was more distinct than those along the vertical profiles at each station. We suggest that the overall heterogeneity of the methanogenic communities residing in the tropical mangrove sediments might be due to the accumulated effects of temperature and concentrations of nitrate, cobalt, and nickel.