Gretchen R. Miller

Mapping Potential Groundwater-Dependent Ecosystems for Sustainable Management

Ecosystems which rely on either the surface expression or subsurface presence of groundwater are known as groundwater-dependent ecosystems (GDEs). A comprehensive inventory of GDE locations at an appropriate management scale is a necessary first-step for sustainable management of supporting aquifers; however, this information is unavailable for most areas of concern. To address this gap, this study created a two-step algorithm which analyzed existing geospatial and remote sensing data to identify potential GDEs at both state/province and aquifer/basin scales. At the state/province scale, a geospatial information system (GIS) database was constructed for Texas, including climate, topography, hydrology, and ecology data. From these data, a GDE index was calculated, which combined vegetative and hydrological indicators. The results indicated that central Texas, particularly the Edwards Aquifer region, had highest potential to host GDEs. Next, an aquifer/basin scale remote sensing-based algorithm was created to provide more detailed maps of GDEs in the Edwards Aquifer region. This algorithm used Landsat ETM+ and MODIS images to track the changes of NDVI for each vegetation pixel. The NDVI dynamics were used to identify the vegetation with high potential to use groundwater--such plants remain high NDVI during extended dry periods and also exhibit low seasonal and inter-annual NDVI changes between dry and wet seasons/years. The results indicated that 8% of natural vegetation was very likely using groundwater. Of the potential GDEs identified, 75% were located on shallow soil averaging 45 cm in depth. The dominant GDE species were live oak, ashe juniper, and mesquite.

Modeling Vadose Zone Processes during Land Application of Food-Processing Waste Water in California's Central Valley

Land application of food-processing waste water occurs throughout Californias Central Valley and may be degrading local ground water quality, primarily by increasing salinity and nitrogen levels. Natural attenuation is considered a treatment strategy for the waste, which often contains elevated levels of easily degradable organic carbon. Several key biogeochemical processes in the vadose zone alter the characteristics of the waste water before it reaches the ground water table, including microbial degradation, crop nutrient uptake, mineral precipitation, and ion exchange. This study used a process-based, multi-component reactive flow and transport model (MIN3P) to numerically simulate waste water migration in the vadose zone and to estimate its attenuation capacity. To address the high variability in site conditions and waste-stream characteristics, four food-processing industries were coupled with three site scenarios to simulate a range of land application outcomes. The simulations estimated that typically between 30 and 150% of the salt loading to the land surface reaches the ground water, resulting in dissolved solids concentrations up to sixteen times larger than the 500 mg L(-1) water quality objective. Site conditions, namely the ratio of hydraulic conductivity to the application rate, strongly influenced the amount of nitrate reaching the ground water, which ranged from zero to nine times the total loading applied. Rock-water interaction and nitrification explain salt and nitrate concentrations that exceed the levels present in the waste water. While source control remains the only method to prevent ground water degradation from saline wastes, proper site selection and waste application methods can reduce the risk of ground water degradation from nitrogen compounds.

A statistical method for estimating wood thermal diffusivity and probe geometry using in situ heat response curves from sap flow measurements.

The heat pulse method is widely used to measure water flux through plants; it works by using the speed at which a heat pulse is propagated through the system to infer the velocity of water through a porous medium. No systematic, non-destructive calibration procedure exists to determine the site-specific parameters necessary for calculating sap velocity, e.g., wood thermal diffusivity and probe spacing. Such parameter calibration is crucial to obtain the correct transpiration flux density from the sap flow measurements at the plant scale and subsequently to upscale tree-level water fluxes to canopy and landscape scales. The purpose of this study is to present a statistical framework for sampling and simultaneously estimating the trees thermal diffusivity and probe spacing from in situ heat response curves collected by the implanted probes of a heat ratio measurement device. Conditioned on the time traces of wood temperature following a heat pulse, the parameters are inferred using a Bayesian inversion technique, based on the Markov chain Monte Carlo sampling method. The primary advantage of the proposed methodology is that it does not require knowledge of probe spacing or any further intrusive sampling of sapwood. The Bayesian framework also enables direct quantification of uncertainty in estimated sap flow velocity. Experiments using synthetic data show that repeated tests using the same apparatus are essential for obtaining reliable and accurate solutions. When applied to field conditions, these tests can be obtained in different seasons and can be automated using the existing data logging system. Empirical factors are introduced to account for the influence of non-ideal probe geometry on the estimation of heat pulse velocity, and are estimated in this study as well. The proposed methodology may be tested for its applicability to realistic field conditions, with an ultimate goal of calibrating heat ratio sap flow systems in practical applications.

Leaf surface traits and water storage retention affect photosynthetic responses to leaf surface wetness among wet tropical forest and semiarid savanna plants

While it is reasonable to predict that photosynthetic rates are inhibited while leaves are wet, leaf gas exchange measurements during wet conditions are challenging to obtain due to equipment limitations and the complexity of canopy-atmosphere interactions in forested environments. Thus, the objective of this study was to evaluate responses of seven tropical and three semiarid savanna plant species to simulated leaf wetness and test the hypotheses that (i) leaf wetness reduces photosynthetic rates (Anet), (ii) leaf traits explain different responses among species and (iii) leaves from wet environments are better adapted for wet leaf conditions than those from drier environments. The two sites were a tropical rainforest in northern Costa Rica with ~4200 mm annual rainfall and a savanna in central Texas with ~1100 mm. Gas exchange measurements were collected under dry and wet conditions on five sun-exposed leaf replicates from each species. Additional measurements included leaf wetness duration and stomatal density. We found that Anet responses varied greatly among species, but all plants maintained a baseline of activity under wet leaf conditions, suggesting that abaxial leaf Anet was a significant percentage of total leaf Anet for amphistomatous species. Among tropical species, Anet responses immediately after wetting ranged from -31% (Senna alata (L.) Roxb.) to +21% (Zamia skinneri Warsz. Ex. A. Dietr.), while all savanna species declined (up to -48%). After 10 min of drying, most species recovered Anet towards the observed status prior to wetting or surpassed it, with the exception of Quercus stellata Wangenh., a savanna species, which remained 13% below Anet dry. The combination of leaf wetness duration and leaf traits, such as stomatal density, trichomes or wax, most likely influenced Anet responses positively or negatively. There was also overlap between leaf traits and Anet responses of savanna and tropical plants. It is possible that these species converge on a relatively conservative response to wetness, each for divergent purposes (cooling, avoiding stomatal occlusion, or by several unique means of rapid drying). A better understanding of leaf wetness inhibiting photosynthesis is vital for accurate modeling of growth in forested environments; however, species adapted for wet environments may possess compensatory traits that mitigate these effects.

Upscaling transpiration in diverse forests: Insights from a tropical premontane site

Department of Ecosystem Science and Management, Texas A&M University, 2138 TAMU, College Station, TX 77843, USA 2 INVISTA S.à r.l., 5060 FM 1006, Orange, TX 77630, USA Department of Civil Engineering, Texas A&M University, 3136 TAMU, College Station, TX 77843‐3136, USA Correspondence Georgianne W. Moore, Department of Ecosystem Science and Management, Texas A&M University, 2138 TAMU, College Station, TX 77843, USA. Email: gwmoore@tamu.edu Funding information Soltis and Hammer families; U.S. Department of Energy, Office of Science, Biological and Environmental Research, Grant/Award Number: DE‐SC0010654; National Science Foundation, Grant/Award Number: EAR‐1004874