The acquisition of remote sensing data having an investigated quality level constitutes an important step to advance our understanding of the vegetation response to environmental factors. Spaceborne sensors introduce additional challenges that should be addressed to assure that derived findings are based on real phenomena, and not biased or misguided by instrument features or processing artifacts. As a consequence, updates to incorporate new advances and user requirements are regularly found on most cutting edge systems such as the MODIS system. In this dissertation, the objective was to design, characterize and assess any possible departure from current values, a MODIS VI algorithm for restoring the continuity 16-day 1-km product, based on the new 8-day 500-m MODIS SR product scheduled for MODIS C6. Additionally, the impact of increasing the time resolution from 16 to 8 days for the future basic MODIS C6 VI product was also assessed. The performance of the proposed algorithm was evaluated using high quality reference data and known biophysical relationships at several spatial and temporal scales. Firstly, it was evaluated using data from the ASRVN, FLUXNET-derived ecosystem GPP and an analysis of the seasonality parameters derived from current C5 and proxy C6 VI collections. The performance of the 8-day VI version was evaluated and contrasted with current 16-day using the reported correlation of the EVI with the GPP derived from CO2 flux measurements. Secondly, we performed an analysis at spatial level using entire images (or "tiles") to assess the BRDF effects on the VI product, as these can cause biases on the SR and VIs from scanning radiometers. Lastly, we evaluated the performance of the proposed algorithm for detecting inter-annual VI anomalies from long-term time series, as compared with current MODIS VI C5. For this, we analyzed the EVI anomalies from a densely vegetated evergreen region, for the period July-September (2000-2010). Results showed a high general similarity between results from both algorithms, but also systematic differences, suggesting that proposed algorithm towards C6 may represent an advance in the reduction of uncertainties for the MODIS VI product.

Bacteria have evolved sophisticated cellular transport mechanisms to maintain metal homeostasis to not only utilize metals as important cofactors but also to evade the toxicity of these ions. The delicate balance is maintained by several homeostatic mechanisms that range from active cytoplasmic export, modification, sequestration, and periplasmic detoxification of toxic metals to the extracellular milieu. One mechanism involves active periplasmic extrusion of toxic substrates via a transmembrane spanning tripartite protein complex. The mechanism of substrate binding and subsequent efflux has yet to be elucidated. However, genetic, comparative genomic, biochemical, and functional analyses of the components of the heavy-metal efflux family have allowed the development of proposed models for a substrate transport pathway. The goals of this research were to identify the roles these systems play and to further characterize these systems on a molecular level to ultimately understand the mechanism of substrate transport. Elucidating a transport pathway in metal transporters allows for the development of a revised working model, which ultimately can have implications for antimicrobial drug development.

The amoebae Naegleria fowleri, Acanthamoeba spp., and Balamuthia mandrillaris are free-living amoebae found in both water and soil. They are opportunistic pathogens in humans. Acanthamoeba is the most common cause of illness, usually infecting the eyes and sometimes causing a sight-threatening keratitis. Acanthamoeba spp. and B. mandrillaris can cause granulomatous amoebic encephalitis, in addition to infections of the lungs and skin. N. fowleri causes primary amoebic meningoencephalitis . There is little known regarding the ecology and occurrence of these organisms. A total of 36 high-use recreational surface waters in Arizona were surveyed over a period of two years to assess the occurrence of N. fowleri and seasonal and environmental factors. Overall, 9.3% of the warm weather samples collected were positive for N. fowleri, whereas 16.3% of the samples were positive during cold weather. Although the presence of N. fowleri could not be significantly correlated with physical and chemical parameters such as temperature, pH, turbidity, conductivity, and the presence of heterotrophic bacteria, total coliforms, and Escherichia coli, a weak correlation (0.52) with live amoebic activity was observed. Five lakes to the north and northeast of Phoenix tested positive for the N. fowleri on more than one occasion over multiple seasons. Finished drinking water samples (n= 785) from a municipal potable distribution system were evaluated for the presence of N. fowleri, B. mandrillaris and Acanthamoeba spp. from 18 different regions during three different sampling periods. Physical and chemical parameters were also evaluated but provided no significant correlations with the occurrence of amoebae or indicator organisms. A total of 138 samples (17.9%) were positive for viable amoebae in distribution water with more than an adequate chlorine residual (average of 0.86 mg/L). Microorganisms that are typically used to monitor microbial water quality such as coliforms and E. coli would likely not be found under these circumstances. Clusters with three or more samples testing positive for viable amoebae per region were observed during all three periods. Viable amoebae may not only provide a better assessment of the microbial quality of water, but such clustering could reveal areas with potential water quality issues within the distribution system.

The Cienega de Santa Clara is a 5600 ha, anthropogenic wetland in the delta of the Colorado River in Mexico. It is the inadvertent creation of the disposal of brackish agricultural waste water from the U.S. into the intertidal zone of the river delta in Mexico, but has become an internationally important wetland for resident and migratory water birds. The marsh is dominated by Typha domengensis with Phragmites australis as a sub-dominant species in shallower marsh areas. The most important factor controlling vegetation density was fire. The second significant (P<0.01) factor controlling NDVI was flow rate of agricultural drain water from the U.S. into the marsh. Reduced summer flows in 2001 due to canal repairs, and in 2010 during the YDP test run, produced the two lowest NDVI values of the time series from 2000 to 2011 (P<0.05). Salinity is a further determinant of vegetation dynamics as determined by greenhouse experiments, but was nearly constant over the period 2000 to 2011, so it was not a significant variable in regression analyses. Evapotranspiration (ET) and other water balance components were measured in Cienega de Santa Clara; we used a remote sensing algorithm to estimate ET from meteorological data and Enhanced Vegetation Index values from the Moderate Resolution Imaging Spectrometer (MODIS) sensors on the Terra satellite. We used Landsat NDVI imagery from 1978-2011 to determine the area and intensity of vegetation and to estimate evapotranspiration (ET) to construct a water balance. Remote sensing data was supplemented with hydrological data, site surveys and literature citations. The vegetated area increased from 1978 to 1995 and has been constant at about 4200 ha since then. The dominant vegetation type is Typha domingensis (southern cattail), and peak summer NDVI since 1995 has been stable at 0.379 (SD = 0.016), about half of NDVI(max). About 30% of the inflow water is consumed in ET, with the remainder exiting the Cienega as outflow water, mainly during winter months when T. domingensis is dormant.

A fundamental knowledge gap in understanding land-atmosphere interactions is accurate, high-resolution soil properties. Remote sensing and spatial modeling techniques can bridge the gap between site-specific soil properties and landscape variability, thereby improving predictions of soil attributes. Three studies were completed to advance soil prediction models in semiarid areas. The first study developed a soil pre-mapping technique using automated image segmentation that utilized soil-landscape relationships and surface reflectance to produce an effective map unit design in a 160,000 ha soil survey area. Overall classification accuracy of soil taxonomic units at the suborder was 58 % after including soil temperature regime. Physical soil properties were not significantly different for individual transects; however, properties were significantly different between soil pre-map units when soils from the entire study area were compared. Other studies used a raster approach to predict physical soil properties at a 5 m spatial resolution for a 6,265 ha area using digital soil mapping. The second study utilized remotely-sensed auxiliary data to develop a sampling design and compared three geostatistical techniques for predicting surface soil properties. Ordinary kriging had the smallest prediction error; however, regression kriging preserved landscape features present in the study area and demonstrated the potential of this technique for quantifying variability of soil components within soil map units. The third study applied quantitative data from soil prediction models in study 2 and additional models of subsurface properties to a pedotransfer function for predicting hydraulic soil parameters at the landscape scale. Saturated hydraulic conductivity and water retention parameters were used to predict water residence times for loss to gravity and evapotranspiration across the landscape. High water residence time for gravitational water corresponded to both low drainage density and high clay content, whereas high residence of plant available water was related to increased vegetation response. These studies illustrate the utility of digital soil mapping techniques for improving soil information at landscape scales, while reducing required resources. Resulting soil information is useful for quantifying landscape-scale processes that require constraint of spatial variability and prediction error of soil properties to better model hydrological and ecological responses to climate and land use change.

This dissertation examines the bacterial diversity of hyperarid and arid regions of the Atacama Desert, Chile, as a first step towards understanding the global biogeochemical significance of arid-land microbial communities. The specific objectives were to characterize bacterial diversity and infer the possible metabolic potential of these bacterial communities, and to evaluate the influence of moisture exposure on community structure. In addition, the strengths and limitations of available tools for probing microbial diversity and activity in terrestrial ecosystems were characterized for their application to extreme oligotrophic communities. Preliminary PCR-DGGE analysis of a west-east elevational transect from the Pacific Ocean near Antofagasta to the western slopes of the central Andes indicated that bacterial communities along this transect belonged to two distinct community types: 1) hyperarid (700 - 2000 m) and 2) arid (2500 - 4500 m) communities that included both vegetated and unvegetated regions. Subsequent diversity analysis of these two regions revealed novel but distinct communities in both regions. A greater diversity was observed in the unvegetated arid regions than in the unvegetated hyperarid areas. The unvegetated arid sites were characterized by a bacterial community harboring a combination of radiotolerant and halotolerant heterotrophs as wells as diverse phylotypes closely related to chemolithoautotrophs. These rare phylotypes may be uniquely adapted to arid ecosystems. Molecular tools evaluated for community diversity analysis included PCR-DGGE, Sanger-clone and 454-pyrosequencing analysis of 16S rRNA gene libraries, and the use of reverse transcriptase quantitative PCR (RT-qPCR) for quantifying the impact of environmental variables on the metabolic activity of a specific organism. These techniques were evaluated using the ecosystems of the Atacama Desert as well as model ecosystems designed to address specific questions. Molecular tools are invaluable to the study of microbial ecology because they facilitate the study of fastidious organisms that are difficult or impossible to culture, but the analysis presented in this dissertation demonstrates that each of these methods has limitations and biases which must be acknowledged to avoid inaccurate conclusions from skewed results. The most complete picture of the taxonomic and functional profile of a microbial community is obtained by employing a combination of molecular techniques.

This dissertation examines the microbial and functional diversity in Kartchner Caverns, a limestone cave in Arizona, USA. Kartchner is highly oligotrophic due to the lack of photosynthesis and the limited inputs of organic material from the surface. This characteristic poses a challenge for microbial life in the cave. The first objective of this work was to evaluate the bacterial richness, diversity and taxonomic composition of speleothems surfaces within Kartchner Caverns in order to gain insight into the distribution patterns associated with these communities. Secondly, the metabolic strategies used by cave communities to survive harsh cave conditions were investigated based on phylogenetic associations and metagenomics. Both objectives were directed toward answering the questions "who are there?" and "what are they doing?". The 454-pyrotag analysis of the V6 region of the 16S rRNA gene revealed an unexpectedly high bacterial diversity with each speleothem supporting a unique bacterial community profile. A focused study on one room of the cave revealed three community types: Type 1 was dominated by the phylum Proteobacteria; Type 2 by Actinobacteria; and Type 3 by Acidobacteria. Phylogenetic associations of the sequences generated by the 454 sequencing and by a Sanger clone library suggested cave microbial communities are supported by chemoautotrophic activities such as nitrite and iron oxidation. Results from the phylogenetic associations guided the metagenomic analysis which supports the presence of chemoautotrophic activities in the cave. Genes for two complete CO2 fixation mechanisms, the Calvin-Benson-Bashan and the rTCA cycles were identified in the cave metagenome, as well as genes for ammonia and nitrite oxidation. These genes are associated with both Bacteria and Archaea suggesting members of both domains are acting as primary producers in the cave ecosystem. Comparative analysis of cave samples to other environments suggests an overabundance of DNA repair mechanisms which could be potentially used by cave communities to overcome the toxicity due to high concentrations of calcium on the speleothem surfaces. This work provides the first comprehensive analysis of the microbial diversity and potential strategies used by microbial communities to survive under the extreme conditions found in a semi-arid limestone cave environment.

Tilapia culture in Indonesia was started with the Mozambique Tilapia (Oreochromis mossambicus) in the 1930’s, and the Nile Tilapia (Oreochromis niloticus) the 1960’s. The genetic improvement program of the Nile Tilapia, has led Indonesia to be one of the main tilapia producers in the world. On the other hand, shrimp aquaculture in the country was not started until the 1960’s, it became more popular after the eye ablation technology for broodstock maturation was developed in the early 1980’s. The first experimental study was conducted to investigate the feasibility of low salinity shrimp farming in a polyculture system with tilapia. Polyculture increased the survival for shrimp (77% compared to 62%), but at the same time decreased the survival of tilapia (87% compared to 97%). Together, the data on survival, specific growth rates, and feed conversion ratios showed that the shrimp performed well at low salinity. The second experimental study investigated the feasibility of brackishwater shrimp farming in a polyculture system with tilapia. Polyculture increased the survival for shrimp (82% compared to 65%), and had higher survival for the tilapia (60% compared to 43%). The Red hybrid Tilapia strain used in the study experienced mortalities after one month, suggesting the need for a salt tolerant strain. The presence of tilapia stimulated the growth of microalgae (Chlorella dominance), promoted higher numbers of heterotrophic bacteria in the water, and had lower presumptive vibrios on TCBS agar. A challenge study was conducted by mixing pathogenic luminescent Vibrio harveyi UAZ-651 into shrimp and tilapia feed. The survival of shrimp in monoculture were significantly lower (20%) compared to in polyculture systems (75 - 95%). Mortality was not found in tilapia. Based on 16S rRNA gene sequence, shrimp monoculture water was dominated by marine Vibrio spp., while the polyculture system had Bacillus spp. and Vibrio spp. with high homology to V. cholerae. The presence of Bacillus spp. which produce a lactonase enzyme AiiA, seems to inhibit vibrio growth. While providing advantages, shrimp-tilapia polyculture might also contribute to streptococcosis transmission. Injecting shrimp with Streptococcus iniae and S. agalactiae resulted in mortalities. S. iniae caused higher mortality in the shrimp cultured in 20 ppt (40%) compared to 10 ppt (20%), and no mortality in 5 ppt. S. agalactiae caused higher mortality in 5 ppt (40%) compared to 10 ppt (20%) and 20 ppt (20%). Quorum sensing (QS) is a density dependent cell to cell communication process in bacteria. Based on challenge studies in shrimp, the luminescent Vibrio harveyi BB120 wild-type strain caused 75-90 % mortality through injection of 106 CFU/shrimp. The mortality patterns in the QS mutants suggest that QS defined, when specific virulence genes were expressed or repressed. As QS in V. harveyi consists of three different circuits, further experiments deployed six mutants lacking either a synthase or a receptor for each circuit. The highest survival in the CqsS (a receptor for CAI-1 circuit) mutant group indicates that the CAI-1 circuit is the most crucial for virulence, followed by the AI-2 and HAI-1 cascades. Chitin acquisition and oxygen scavenging may be two reasons for luminescence in V. harveyi evolution and why they infect shrimp.

Advancements in computation and development of physically based hydrologic models to simulate complex vadose zone scenarios helped the research community to evaluate different scenarios easily compared to long-term field experiments. However, some field data collection is necessary to obtain input data such as soil properties, water usage and land management practices to validate the model performance specific to the site. Data obtained from field experiments conducted in 2011 at Hespler farms, Winkler, MB was used in this research for model calibration and validation. The hydrologic model, HYDRUS (2D/3D) was evaluated using parameters such as visual and statistical analysis. Model evaluation during the calibration and validation stage gave RMSE values of 0.019 and 0.015 cm3 cm-3; PBIAS values of -1.01 and -0.14, respectively, suggesting that the model was efficient in simulating soil water content similar to the field observed data. The validated models were then used to simulate outcomes for different scenarios such as 30-year rainfall data (1986 – 2015), different soil physical properties, and drainage system design parameters. Models simulating free drainage predicted lower soil water content compared to controlled drainage leading to 6 – 60 more trafficable days for 8 m spacing and 0.9 drain base depth. Free drainage predicted 8 – 110 additional trafficable days compared to controlled drainage for 15 m spacing and 1.1 drain depth. Heavier than normal rainfall events caused high water contents leading to a few years with a very low to no trafficable days under controlled drainage conditions. The comparisons are presented based on models using free drain conditions. Models with 8-m drain spacing predicted a 1 to 10-day increase in the number of trafficable days compared to the 15-m drain spacing. Drains placed at a base depth of 1.1 m below the soil surface predicted 4 - 40 more trafficable days compared to those installed at a base depth of 0.9 m. / October 2017

Despite being the driest inhabited continent, Australia has one of the highest per capita water consumptions in the world. In addition, instead of having fit-for-purpose water supplies (using different qualities of water for different applications), highly treated drinking water is used for nearly all of Australia's urban water supply needs, including landscape irrigation. The water requirement of urban landscapes, particularly urban parklands, is of growing concern. The estimation of evapotranspiration (ET) and subsequently plant water requirements in urban vegetation needs to consider the heterogeneity of plants, soils, water, and climate characteristics. This research contributes to a broader effort to establish sustainable irrigation practices within the Adelaide Parklands in Adelaide, South Australia. In this paper, two practical ET estimation approaches are compared to a detailed Soil Water Balance (SWB) analysis over a one year period. One approach is the Water Use Classification of Landscape Plants (WUCOLS) method, which is based on expert opinion on the water needs of different classes of landscape plants. The other is a remote sensing approach based on the Enhanced Vegetation Index (EVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra satellite. Both methods require knowledge of reference ET calculated from meteorological data. The SWB determined that plants consumed 1084 mmyr(-1) of water in ET with an additional 16% lost to drainage past the root zone, an amount sufficient to keep salts from accumulating in the root zone. ET by MODIS EVI was 1088 mmyr(-1), very close to the SWB estimate, while WUCOLS estimated the total water requirement at only 802 mmyr(-1), 26% lower than the SWB estimate and 37% lower than the amount actually added including the drainage fraction. Individual monthly ET by MODIS was not accurate, but these errors were cancelled out to give good agreement on an annual time step. We conclude that the MODIS EVI method can provide accurate estimates of urban water requirements in mixed landscapes large enough to be sampled by MODIS imagery with 250-m resolution such as parklands and golf courses.