From Surface to Subsurface: Diversity, Composition, and Abundance of Sessile and Endolithic Bacterial, Archaeal, and Eukaryotic Communities in Sand, Clay and Rock Substrates in the Laurentians (Quebec, Canada)

Microbial communities play an important role in shallow terrestrial subsurface ecosystems. Most studies of this habitat have focused on planktonic communities that are found in the groundwater of aquifer systems and only target specific microbial groups. Therefore, a systematic understanding of the processes that govern the assembly of endolithic and sessile communities is still missing. This study aims to understand the effect of depth and biotic factors on these communities, to better unravel their origins and to compare their composition with the communities detected in groundwater. To do so, we collected samples from two profiles (~0–50 m) in aquifer sites in the Laurentians (Quebec, Canada), performed DNA extractions and Illumina sequencing. The results suggest that changes in geological material characteristics with depth represent a strong ecological and phylogenetical filter for most archaeal and bacterial communities. Additionally, the vertical movement of water from the surface plays a major role in shallow subsurface microbial assembly processes. Furthermore, biotic interactions between bacteria and eukaryotes were mostly positive which may indicate cooperative or mutualistic potential associations, such as cross-feeding and/or syntrophic relationships in the terrestrial subsurface. Our results also point toward the importance of sampling both the geological formation and groundwater when it comes to studying its overall microbiology.

Using machine learning to predict optimal electromagnetic induction instrument configurations for characterizing the shallow subsurface

Electromagnetic induction (EMI) is used widely for hydrological and other environmental studies. The apparent electrical conductivity (ECa), which can be mapped efficiently with EMI, correlates with a variety of important soil attributes. EMI instruments exist with several configurations of coil spacing, orientation, and height. There are general, rule-of-thumb guides to choose an optimal instrument configuration for a specific survey. The goal of this study was to provide a robust and efficient way to design this optimization task. In this investigation, we used machine learning (ML) as an efficient tool for interpolating among the results of many forward model runs. Specifically, we generated an ensemble of 100 000 EMI forward models representing the responses of many EMI configurations to a range of three-layer subsurface models. We split the results into training and testing subsets and trained a decision tree (DT) with gradient boosting (GB) to predict the subsurface properties (layer thicknesses and EC values). We further examined the value of prior knowledge that could limit the ranges of some of the soil model parameters. We made use of the intrinsic feature importance measures of machine learning algorithms to identify optimal EMI designs for specific subsurface parameters. The optimal designs identified using this approach agreed with those that are generally recognized as optimal by informed experts for standard survey goals, giving confidence in the ML-based approach. The approach also offered insight that would be difficult, if not impossible, to offer based on rule-of-thumb optimization. We contend that such ML-informed design approaches could be applied broadly to other survey design challenges.

Seismic velocity recovery in the subsurface: transient damage and groundwater drainage following the 2015 Gorkha earthquake, Nepal

Shallow earthquakes frequently disturb the hydrological and mechanical state of the subsurface, with consequences for hazard and water management. Transient post-seismic hydrological behaviour has been widely reported, suggesting that the recovery of material properties (relaxation) following ground shaking may impact groundwater fluctuations. However, the monitoring of seismic velocity variations associated with earthquake damage and hydrological variations are often done assuming that both effects are independent. In a field site prone to highly variable hydrological conditions, we disentangle the different forcing of the relative seismic velocity variations $\delta v$ retrieved from a small dense seismic array in Nepal in the aftermath of the 2015 Mw 7.8 Gorkha earthquake. We successfully model transient damage effects by introducing a universal relaxation function that contains a unique maximum relaxation timescale for the main shock and the aftershocks, independent of the ground shaking levels. Next, we remove the modeled velocity from the raw data and test whether the corresponding residuals agree with a background hydrological behaviour we inferred from a previously calibrated groundwater model. The fitting of the $\delta v$ data with this model is improved when we introduce transient hydrological properties in the phase immediately following the main shock. This transient behaviour, interpreted as an enhanced permeability in the shallow subsurface, lasts for $\sim$ 6 months and is shorter than the damage relaxation ($\sim$ 1 year). Thus, we demonstrate the capability of seismic interferometry to deconvolve transient hydrological properties after earthquakes from non-linear mechanical recovery.

Mapping anthropogenic fill with GPR for unmarked grave detection: A case study from a possible location of Mokare’s grave, Albany, Western Australia

Geophysical techniques are a commonly used, non-invasive method for the location of unmarked graves. Contrary to popular perception, most studies rely not on directly imaging skeletal material but instead on locating the subsurface disturbance created by grave digging. This approach is effective only when sufficient contrast exists between detectable properties (such as structure, mineralogy or porosity) of the grave fill and the surrounding sediment. Resolving these features can be particularly problematic in disturbed areas where other anthropogenic fill is in place, as it is often complex in character and lacks a natural stratigraphy.In many cultural heritage projects, it is often more important to ensure that burials are not disturbed rather than to specifically locate them. Under these circumstances, ground penetrating radar (GPR) can be used to locate modern anthropogenic fill. This may show which areas of the site are younger than the targeted graves and therefore of no archaeological interest. This approach is trialled on a site thought to contain the grave of Mokare, a significant historical figure in the colonial settlement of the Albany area in Western Australia. The delineation of a package of modern fill in the shallow subsurface in the context of the probable history of earthworks on the site demonstrates that Mokare is not buried in the surveyed location. This approach, applied to suitable sites, could contribute to culturally sensitive non-invasive investigation of burial sites in other locations.

Assessing the impact of shallow subsurface pipe drainage on soil salinity and crop yield in arid zone

Purpose Soil salinization is one of the key problems of sustainable development of arid agricultural land. Exploring the use of shallow subsurface pipe drainage to improve soil salinization. Methods This study investigates the desalinization effect of shallow subsurface pipe drainage, in combination with drip irrigation under plastic mulch, in an arid region in China. Field data collection was conducted in 2010. Soil salinity at a range of soil depths, water EC and pH of subsurface pipe drainage and crop yield during crop growth stages in salinized farmlands were measured. Results and Conclusion The results show that soil salinity was reduced significantly on mildly (1–3 dS m−1) and moderately (3–6 dS m−1) salinized farmlands. The highest desalinization rate of mildly and moderately salinized soils was 51% and 91% respectively. The desalinization in upper soil layers, to a depth of 60 cm, was more significant than that in lower soil layers. Drainage water salinity was much higher than irrigation water salinity. Crop yield on mildly and moderately salinized land increased about 25% and 50%, respectively. This indicates that the combination of drip irrigation and shallow subsurface pipe drainage on farmlands is potential feasible to desalt farmlands and to improve crop yield. The study has led to a desalinization of 330 ha year−1 in Xinjiang.

A conceptual geological model for offshore wind sites in palaeo ice stream settings: The Utsira Nord site, North Sea

Conceptual geological models of the shallow subsurface which integrate geological and geotechnical information are important for more strategic data acquisition and engineering at offshore wind sites. Utsira Nord is an offshore wind site in the Norwegian North Sea. It covers an area of 23 km x 43 km within the Norwegian Channel palaeo ice stream, with an average water depth of 267 m making the site a candidate for floating offshore wind. The goal of this study is to present a preliminary conceptual geological model for the site, which combines an overview of previous knowledge about the complex ice streaming history of the Norwegian Channel with key observations from high resolution bathymetric data, 2D acoustic data, and shallow cores. Despite limited data, four geotechnical provinces can be defined: 1) exposed glacimarine to marine sediments, 2) buried to exposed subglacial traction till, 3) buried lodgment till and 4) shallowly buried to exposed crystalline bedrock. The model serves as a basis for planning site surveys at Utsira Nord and as a reference for offshore wind sites on other formerly glaciated coasts where palaeo ice stream systems are common, such as the northern coastlines of the United States and the United Kingdom.