Evolution of the Set of Signal Transduction Proteins in 10 Species of \u3cem\u3eShewanella\u3c/em\u3e

The recent completion of the sequencing of several species of the Shewanella genus provides a unique opportunity for comparative genomics studies. We chose the first 10 fully sequenced Shewanella genomes to investigate the evolution of signal transduction proteins (ST). ST is a universal and highly regulated system, and as a very well-studied system provides an excellent starting point for investigation. Furthermore, Shewanella have been shown to have a large number of two-component systems and diguanylate cyclases relative to their genome size. In this study we investigate the evolution of signal transduction across several Shewanella strains by utilizing a domainlevel approach for determining homology and orthology of the parent proteins. Proteins were broken down into their constituent domains and domain sized sequences and compared using a reciprocal best BLAST hit approach to determine homology between all of the species. Analysis of homologous domains and proteins revealed several levels of conservation and a core group of signal transduction proteins common to all members. Further analysis of domain homology provided putative annotations of previously unrecognized sequences and highlighted deficiencies in specific Pfam domain models. Analysis of paralogous domains and proteins showed agreement with 16s rRNA based estimates of evolution, although the position of S. oneidensis MR-1 was novel

LPMLE3 : a novel 1-D approach to study water flow in streambeds using heat as a tracer

We introduce LPMLE3, a new 1-D approach to quantify vertical water flow components at streambeds using temperature data collected in different depths. LPMLE3 solves the partial differential equation for coupled water flow and heat transport in the frequency domain. Unlike other 1-D approaches it does not assume a semi-infinite halfspace with the location of the lower boundary condition approaching infinity. Instead, it uses local upper and lower boundary conditions. As such, the streambed can be divided into finite subdomains bound at the top and bottom by a temperature-time series. Information from a third temperature sensor within each subdomain is then used for parameter estimation. LPMLE3 applies a low order local polynomial to separate periodic and transient parts (including the noise contributions) of a temperature-time series and calculates the frequency response of each subdomain to a known temperature input at the streambed top. A maximum-likelihood estimator is used to estimate the vertical component of water flow, thermal diffusivity, and their uncertainties for each streambed subdomain and provides information regarding model quality. We tested the method on synthetic temperature data generated with the numerical model STRIVE and demonstrate how the vertical flow component can be quantified for field data collected in a Belgian stream. We show that by using the results in additional analyses, nonvertical flow components could be identified and by making certain assumptions they could be quantified for each subdomain. LPMLE3 performed well on both simulated and field data and can be considered a valuable addition to the existing 1-D methods

Spatial Variability in Seepage from Unlined, Open Channels

Recent research into the interactions between streams or lakes and the aquifers beneath them highlights the usefulness of methods for determining movement of water between surface and groundwater sources. Several methods have successfully been employed to estimate these interactions in a variety of environments. As temperature sensor technology and computer capability has improved in the past decades, an increasing number of studies have used temperature and pressure information collected in surface water, streambed porous media, and groundwater in one-dimensional analytical or one-, two-, or even three-dimensional (1D, 2D, or 3D) numerical models that combine heat transport and fluid flux equations. This work compared the advantages and limitations of one- vs. two-dimensional numerical models and the applicability of the Stallman analytical solution for use in applications of heat as a tracer. Although the use of temperature data for estimating seepage and hydraulic conductivity has been shown to have several advantages over many other methods, it shares a common disadvantage of being a point measurement. Because spatial variability in seepage is often an important factor, a new model using the diffusion analogy to the shallow-water (Saint-Venant) equations was developed as a step toward estimating seepage losses from unlined channels.Comparison of numerical models showed that a 1D model can be useful when a simple, comparatively low-cost estimate of seepage from streambed temperature data is desired and streambed heterogeneity is not a concern. However, the assumption of strictly vertical water movement inherent in 1D models highlights the importance of temperature sensor placement to satisfy this condition. Alternatively, the Stallman analytical solution precisely reproduced velocities for moderate rates of infiltration (approximately ~1.5-4 m/d) despite sensor noise and uncertainty in either sensor spacing or thermal diffusivity. When seepage was close to zero or flow was from the groundwater into the streambed, uncertainty in input parameters and noise due to sensor accuracy had an effect on the accuracy of predicted seepage rates, likely due to a reduced change in amplitude with depth. The diffusion-wave model, coupled to the U.S. Geological survey groundwater model MODFLOW, produced longitudinal seepage velocities for several reaches of two irrigation canals that were comparable to the estimates reported in previous studies. This model may be a useful tool for predicting surface water/groundwater interactions along comparatively long stretches of man-made or natural channels at a finer scale than was previously convenient

Assessing river discharge dynamics through relative surface water extent changes in river basins

Surface water in rivers is vital for human society. However, our current understanding of the dynamics and drivers of river flows relies predominantly on stream gauging data, which are limited in spatial coverage and involve significant costs. Remote sensing techniques have emerged as complementary tools for monitoring river discharge, but these satellite-based methods often require complex data processing. This paper introduces a simple, yet effective and robust methodology to understand river discharge, using Australian rivers as a case study. Our findings reveal that changes in relative surface water extent within river basins can effectively capture river discharge dynamics. Moreover, we observe a linear relationship between relative surface water extent and river discharge in hilly basins and a quadratic relationship in flat basins. The new approach helps monitor river flows in ungauged river basins, and it has the potential to bridge the gap between local and regional understandings of water dynamics.</p

Flux dynamics at the groundwater-surface water interface in a tropical catchment

© 2017 Elsevier GmbH. This manuscript version is made available under the CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (July 2017) in accordance with the publisher’s archiving policySeasonal shifts between wet and dry seasons cause marked changes in river flow regimes and therefore exchanges with the streambed surface. This seasonal variation is particularly apparent in tropical climates, which are characterized by strong differences between wet and dry seasons. However, fluxes between surface water and groundwater and the impacts of these interactions on streambed dynamics are rarely investigated in tropical climates, where few surface water-groundwater field investigations have been performed. In this study, an intermittent river in south coastal Vietnam was investigated to better understand links between seasonal hydrologic shifts, human use of water resources, and streambed dynamics. Three transects along the main tributary were instrumented with water level and streambed temperature sensors to examine both spatial and temporal variability in stream-aquifer dynamics. Calibrated models estimated increasing streambed fluxes along the length of the river, with highly variable fluxes up to 1.6 m2 h−1 upstream and 0.2 m2 h−1 downstream during the rainy season (i.e. the rate of the total amount of water exchanged per meter of river length) decreasing to low fluxes of 1.0 m2 h−1 upstream and 0.15 m2 h−1 downstream in the dry season before flow ceased. During the wet and into the dry season the river was gaining (i.e. flux from the aquifer into the river) at all times and all locations with the notable exception of fluxes into the streambed only at the upstream and downstream sites during peak flow of the largest captured rain event (550 mm in 164 h). Based on 30 years of precipitation data, this suggests that water is pushed from the stream into the streambed approximately three times per year. Groundwater withdrawal by households near the cross-sections was found to have a comparatively small effect on streambed fluxes, reducing the flux by up to 3% during dry conditions, although this pumping did cause a reversal in the gradient to the stream for a short period (less than 12 h) on one occasion during the dry season

Error in hydraulic head and gradient time-series measurements: a quantitative appraisal

&amp;lt;p&amp;gt;&amp;lt;strong&amp;gt;Abstract.&amp;lt;/strong&amp;gt; Hydraulic head and gradient measurements underpin practically all investigations in hydro(geo)logy. There is sufficient information in the literature to suggest that head measurement errors may be so large that flow directions can not be inferred reliably, and that their magnitude can have as great an effect on the uncertainty of flow rates as the hydraulic conductivity. Yet, educational text books contain limited content regarding measurement techniques and studies rarely report on measurement errors. The objective of our study is to review currently-accepted standard operating procedures in hydrological research and to determine the smallest head gradients that can be resolved. To this aim, we first systematically investigate the systematic and random measurements errors involved in collecting time series information on hydraulic head at a given location: (1) geospatial position, (2) point of head, (3) depth to water, and (4) water level time series. Then, by propagating the random errors, we find that with current standard practice, horizontal head gradients&amp;amp;#8201;&amp;lt;&amp;amp;#8201;10&amp;lt;sup&amp;gt;&amp;amp;#8722;4&amp;lt;/sup&amp;gt; are resolvable at distances&amp;amp;#8201;&amp;amp;#10886;&amp;amp;#8201;170&amp;amp;#8201;m. Further, it takes extraordinary effort to measure hydraulic head gradients&amp;amp;#8201;&amp;lt;&amp;amp;#8201;10&amp;lt;sup&amp;gt;&amp;amp;#8722;3&amp;lt;/sup&amp;gt; over distances&amp;amp;#8201;&amp;lt;&amp;amp;#8201;10&amp;amp;#8201;m. In reality, accuracy will be worse than our theoretical estimates because of the many possible systematic errors. Regional flow on a scale of kilometres or more can be inferred with current best-practice methods, but processes such as vertical flow within an aquifer cannot be determined until more accurate and precise measurement methods are developed. Finally, we offer a concise set of recommendations for water level, hydraulic head and gradient time series measurements. We anticipate that our work contributes to progressing the quality of head time series data in the hydro(geo)logical sciences, and provides a starting point for the development of universal measurement protocols for water level data collection.&amp;lt;/p&amp;gt; </jats:p

The interaction of flow regimes and nutrient fluxes on the water quality and ecosystem health of a clear, freshwater wetland

Across the globe, the hydrology and ecology of wetland systems have been altered by anthropogenic activities, sometimes leading to regime shift or even ecosystem collapse. Often, it is not only the impact of one stressor, but the combination of multiple stressors interacting that ultimately leads to adverse ecological impact in wetland systems. However, because of the difficulty in measuring the combined, dynamic effects of multiple stressors, relatively few studies estimate the relative importance of multiple stressors on wetland ecosystems. We combined controlled laboratory and field experiments with a modeling exercise to examine the relative importance of flow and nutrient loads on the resilience of a clear, groundwater-fed wetland dominated by macrophytes. We examined the potential for a combination of lower inflow and higher nutrient loads to increase phytoplankton growth and reduce light availability, culminating in a reduction in macrophyte growth due to the shading of the phytoplankton. This combination of events could result in a collapse of this endemic ecosystem, including local extinction of several endangered species. We found that the resilience of the macrophyte-dominated wetlands is maintained by preserving high flow even under increasing phosphorus concentrations. Nutrient availability increases as flow decreases, favoring pelagic algal development and inducing a shift in the ecosystem conditions. This shows that focusing only on input nutrient levels, as is often done in open waters of concern, is not sufficient to preserve the native ecosystem and highlights the need to consider multiple factors when assessing anthropogenic impacts on wetlands.Margaret Shanafield, Anna Rigosi, Yang Liu and Justin Brooke

Active heat pulse sensing of 3-D-flow fields in streambeds

© Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License.Profiles of temperature time series are commonly used to determine hyporheic flow patterns and hydraulic dynamics in the streambed sediments. Although hyporheic flows are 3-D, past research has focused on determining the magnitude of the vertical flow component and how this varies spatially. This study used a portable 56-sensor, 3-D temperature array with three heat pulse sources to measure the flow direction and magnitude up to 200 mm below the water–sediment interface. Short, 1 min heat pulses were injected at one of the three heat sources and the temperature response was monitored over a period of 30 min. Breakthrough curves from each of the sensors were analysed using a heat transport equation. Parameter estimation and uncertainty analysis was undertaken using the differential evolution adaptive metropolis (DREAM) algorithm, an adaption of the Markov chain Monte Carlo method, to estimate the flux and its orientation. Measurements were conducted in the field and in a sand tank under an extensive range of controlled hydraulic conditions to validate the method. The use of short-duration heat pulses provided a rapid, accurate assessment technique for determining dynamic and multi-directional flow patterns in the hyporheic zone and is a basis for improved understanding of biogeochemical processes at the water–streambed interface

An underground drip water monitoring network to characterize rainfall recharge of groundwater at different geologies, environments, and climates across Australia

Understanding when and why groundwater recharge occurs is of fundamental importance for the sustainable use of this essential freshwater resource for humans and ecosystems. However, accurately capturing this component of the water balance is widely acknowledged to be a major challenge. Direct physical measurements identifying when groundwater recharge is occurring are possible by utilizing a sensor network of hydrological loggers deployed in underground spaces located in the vadose zone. Through measurements of water percolating into these spaces from above, we can record the potential groundwater recharge process in action. By using automated sensors, it is possible to precisely determine when recharge occurs (which event, month, or season and for which climate condition). Combined with daily rainfall data, it is possible to quantify the “rainfall recharge threshold”, the amount of rainfall needed to generate groundwater recharge, and its temporal and spatial variability. Australia's National Groundwater Recharge Observing System (NGROS) provides the first dedicated sensor network for observing groundwater recharge at an event scale across a wide range of geologies, environments, and climate types representing a wide range of Australian hydroclimates. Utilizing tunnels, mines, caves, and other subsurface spaces located in the vadose zone, the sensors effectively record “deep drainage”, water that can move beyond the shallow subsurface and root zone to generate groundwater recharge. The NGROS has the temporal resolution to capture individual recharge events, with multiple sensors deployed at each site to constrain the heterogeneity of recharge between different flow paths, and to quantify (including uncertainty bounds) rainfall recharge thresholds. Established in 2022, the network is described here together with examples of data being generated.</p