Las Quínoas oncoids: a new deposit of microbialites in the Salar de Antofalla (Catamarca, Argentina)

The Salar de Antofalla (salt flat) is located in the Puna region of Catamarca, in northern Argentina. In this paper we report and provide the first descriptive data of Las Quínoas, a modern system of oncoids located in the western margin of the salt flat. Oncoids were studied by insitu logging, polished and thin sections analysis. In addition, the 16s rRNA genes of microbial mats associated with these oncoids were amplified and sequenced to characterize the microbial biodiversity. Oncoids present discoidal to subrounded morphologies and sizes up to 15 cm in diameter. They are scattered along channels, which originate from the groundwater springs of a wetland and enter the salt flat. Its macrostructure is concentric and composed by three zones: 1. A nucleus zone built by clastic material in a carbonate matrix. 2. A well-laminated zone around the nucleus that shows two types of mesostructures: concentrically stacked spheroids (SS-C) and randomly stacked hemispheroids (SS-R), both showing an alternation of dense and dark micritic laminae with light micritic to microsparitic laminae. 3. A poorly-laminated zone, in the outermost sector of oncoids, with two types of mesostructures too: a laminated mesostructure composed also of an alternation of dense and dark micritic laminae with light micritic to microsparitic laminae, and a non-laminated mesostructure composed of agglomerated and cemented clastic material within a calcareous matrix (wackestones-packstones). Regarding the microbial diversity, the analyzed oncoids in this work are mainly inhabited by Proteobacteria (ca. 37.5%), Bacteroidetes (ca. 25.0%), and in less proportion Planctomycetes, Actinobacteria and Cyanobacteria.

Submarine groundwater discharge (SGD) in the springs of Sahlenburg tidal flat, Germany: a geochemical approach.

<p>Submarine groundwater discharge (SGD) is an important connection between fresh groundwater and the marine ecosystem. The scientific interest in SGD has grown considerably during the last decades due to the recognition of SGD in coastal environments as a significant source of nutrients and pollutants.  The Sahlenburg area (Northern Germany) is known by its highly permeable sediments and high rainfall precipitation that produces a large reservoir of groundwater.  Such characteristics are essential for industry, agriculture and drinking water supply with a large regional importance. In addition, this groundwater discharges in the form of highly productive springs directly into the adjacent tidal flats, with so far unknown effects on the local biogeochemistry.  The aim of this study was to characterize the spatial distribution of salinity, fluorescence dissolved organic matter (FDOM), dissolved organic matter (DOC) and total dissolved nitrogen (TDN) of the springs of Sahlenburg tidal flat area in Cuxhaven, Germany. We hypothesize that the SGD composition is changing on its way through the tidal flat due to biogeochemical factors. This may affect the composition of the water in the final part of the pathway with more influence of seawater. Porewater springs were sampled in February 2019 during low tide in three different types of locations in the tidal flat area: nearshore where the springs are located close to the vegetated shoreline (salt marsh), offshore approximately 70 meters from the vegetation and in the middle from both locations. In addition, porewater from a nearby sandy beach (around 500 meters away from the area of spring sampling), and surface samples from a nearby lake and seawater, were obtained. Salinity and FDOM were measured in situ, and DOC and TDN in the laboratory.  The preliminary data showed low average values for salinity in all springs (0.2-1.4), as well as in beach porewater, indicating strong influence of fresh groundwater in the whole area. When comparing the three spring location types, the lowest salinities were found offshore, and the highest nearshore. This difference could be due to the size of the springs, since nearshore springs usually were smaller when compared to offshore springs. Furthermore, depressions in the tidal flat relief close to nearshore springs favored seawater retention in pools during low tide. Additionally, we found higher average values for DOC and FDOM in the nearshore when compared with the other spring areas, but lower compared to the lake, beach porewater and seawater. The average values for TDN (272-452 µmol L<sup>-1</sup>) in the groundwater springs were higher when compared to all other sample types (beach porewater, seawater, and lake water) in this study. These values suggest an anthropogenic input (e.g., agriculture influence) in the surrounding watershed and might stimulate primary productivity in the tidal flat. We conclude that groundwater springs in Sahlenburg tidal flat differ locally in their biogeochemistry due to different residence times, heterogeneity of sediment layers, and size of the springs.</p><p> </p>

Spatial prediction of spring locations in data poor region of Central Himalayas

This research explores the methods for understanding groundwater springs distribution and occurrence using Geographic Information System (GIS) and Machine Learning technique in data poor areas of the Central Himalayas. The objectives of this study are to analyse the distribution of natural springs, evaluate three random forest models for its predictability and establish a model for the prediction of occurrence of springs. This study evaluates the primary causal factors for occurrence of springs. The data used in this study consists of 20 parameters based on topography, geology, lithology, hydrology and land use as causal factors, whereas 621 spring location and discharge (n = 621) measured during 2014–2016 and 815 non-spring locations (generated by GIS tool) use as supporting evidence to train (80%) and test (20%) the prediction model. Results show that the Bootstrap method is comparatively reliable (92% accuracy) over Boosted tree (64% accuracy) and Decision tree (74% accuracy) methods to classify and predict the occurrence of springs in the watershed. Bootstrap Forest shows the high Prediction rate for True Positive (82% actual spring predicted as a spring) and True Negative (89% actual non-spring predicted as non-spring), and the model seems consistent in both responses. This model was then applied to an independent dataset to predict spring location estimates with 75% accuracy. Therefore, spatial statistical methods prove efficient at predicting spring occurrence in data poor regions.

Specialized meltwater biodiversity persists despite widespread deglaciation

Glaciers are important drivers of environmental heterogeneity and biological diversity across mountain landscapes. Worldwide, glaciers are receding rapidly due to climate change, with important consequences for biodiversity in mountain ecosystems. However, the effects of glacier loss on biodiversity have never been quantified across a mountainous region, primarily due to a lack of adequate data at large spatial and temporal scales. Here, we combine high-resolution biological and glacier change (ca. 1850–2015) datasets for Glacier National Park, USA, to test the prediction that glacier retreat reduces biodiversity in mountain ecosystems through the loss of uniquely adapted meltwater stream species. We identified a specialized cold-water invertebrate community restricted to the highest elevation streams primarily below glaciers, but also snowfields and groundwater springs. We show that this community and endemic species have unexpectedly persisted in cold, high-elevation sites, even in catchments that have not been glaciated in ∼170 y. Future projections suggest substantial declines in suitable habitat, but not necessarily loss of this community with the complete disappearance of glaciers. Our findings demonstrate that high-elevation streams fed by snow and other cold-water sources continue to serve as critical climate refugia for mountain biodiversity even after glaciers disappear.

Induced Polarization as a Proxy for CO2-Rich Groundwater Detection—Evidences from the Ardennes, South-East of Belgium

CO 2 -rich mineral groundwaters are of great economic and touristic interest but their origin and circulation paths in the underground are often poorly understood. A deeper understanding of the system plumbery and the development of non—to minimally—invasive near-surface geophysical methods for the prospection of potential productive areas is therefore of great interest to manage future supply. The objective of this contribution is to assess the ability of the time-domain induced polarization (TDIP) method, combined with the electrical resistivity tomography (ERT) method, to make the distinction between CO 2 -rich groundwater from non-gaseous groundwater. Three combined ERT/TDIP tomographies were performed above known uplift zones in the south-east of Belgium where thousands of CO 2 -rich groundwater springs exist. On all profiles, important contrasts in both electrical resistivity and chargeability distributions were observed in the vicinity of the upflow zone, also reflected in the normalized chargeability sections computed from the measured data. Low resistivity vertical anomalies extending in depth were interpreted as a saturated fracture network enabling the upflow of deep groundwater to the surface. High chargeability anomalies appearing directly close to the CO 2 -rich groundwater springs were inferred to metallic oxides and hydroxides precipitation in the upper part of the aquifer, linked to pressure decrease and changing redox conditions in the up-flowing groundwater approaching the land surface. The combined interpretation of electrical resistivity and induced polarization datasets provides a very promising method for a robust prospection of CO 2 -rich groundwater.