Groundwater chemistry is highly variable and dependent on environmental conditions, and it is not entirely understood how all these factors contribute to groundwater chemistry. This study aims to examine some of the factors that contribute to groundwater heterogeneity in the Amazon Rainforest. This was done by collecting groundwater samples from piezometers in three different regions of the Amazon Basin in Brazil, and then analyzing them in the lab for cations and anions, as well as dissolved inorganic and organic carbon. Environmental conditions were measured in the field using portable probes. The results were analyzed and compared with previously established figures for tropical forests. Statistical analyses were performed using SPSS and R in order to establish correlations and linear relationships between the studied variables.Understanding how groundwater supplies are affected is important for being able to predict and manage environmental change that can degrade groundwater sources. This knowledge could also help in developing strategies for groundwater remediation efforts in areas where supplies are contaminated.

Throughout Amazonia, earthworks are found in areas of diverse linguistic and ethnic backgrounds. The distribution of these earthworks within various linguistic and ethnic areas suggests a multiethnic or multilinguistic network, in which interaction between these diverse groups occurred, creating diverse communities. Movement and communication within Amazonia along river networks allowed for this interaction. Interaction between groups in Amazonia may have also influenced the different methods of landscape modification. This thesis presents a GIS-based spatial analysis of raised fields, a type of agricultural earthwork found throughout the Llanos de Mojos (Mojos), located in the Beni Department of Bolivia. The distribution of fields, forest islands, and rivers was analyzed to distinguish the relationship between these features in the study area. The spatial analysis distinguished patterns between raised fields found along two sets of rivers, the Iruyañez and Omi Rivers, and the Yacuma and Rapulo Rivers. Spatial patterns found within these distributions were also compared to the distribution of linguistic groups in the area. Among these patterns, it is seen that one kind of agricultural earthwork is found in areas associated with different linguistic groups. The spatial patterns found among the raised fields and forest islands in relation to the linguistic groups in the area demonstrate the fluidity between groups in the region. Insight to movement and communication in Mojos can be understood through the interaction between linguistic groups and the distribution of archaeological features in the region.

The Quinato wetland, a remnant of a Pleistocene river course through northeastern Bolivia, has undoubtedly been the site of human landscape modification and domestication by pre-Columbian peoples. A 2021 study suggests that these modification practices, which have been tied to seasonal adaptation, were quite different between areas of the wetland. In response to these findings, the present study uses unsupervised classifications from the 50-year span of existent Landsat satellite imagery data, dating from 1972 to 2022, to create a chronological profile of the wetland. This record allows for the assessment of how yearly, seasonal changes to wetland growth and shrinkage contribute to longer-term trends. No significant increase or decrease in wetland size overall is suggested by the data, although a distinct, common seasonal pattern is detectable. This data, narrowed to the two sites investigated in the previously mentioned study, shows a similar seasonal patterning as that of the larger wetland at these two sites, but also detects a greater stability in wetland area for the region that was first modified by pre-Columbian peoples.

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The Amazon River drainage basin is known as the most biodiverse region in the world. Regarding freshwater fish, this region contains around 15% of the world's fish richness. The fish family Serrasalmidae have a variety of feeding preferences including Pacus (herbivores) and Piranhas (carnivores). Fruit eating fish species are evolutionarily the oldest species in the family and have a mutualistic interaction with flooded forests. Considering the diversity of feeding habits of the Serrasalmidae family, it represents an excellent model to study ecological questions related to factors that influence the spatial distribution of species and factors that contribute to the maintenance of biodiversity. I first analyzed how differences in dietary preferences influence the spatial distribution and habitat associations of species at the landscape scale using diet data and three proxies of habitat association derived from satellite products. Using Phylogenetic Generalized Least Squares models I evaluated the relationship between habitat association and feeding guilds. Differences in resource distribution (assessed through feeding guilds) can influence habitat associations. Considering the hydrological variability (i.e., floodplain extent) and landscape heterogeneity that characterize floodplains, the patterns of habitat association vary with the spatial scale considered. Second, I identified factors that aid in sustaining aquatic biodiversity in floodplain forests of the Amazon River basin, focusing on frugivorous fish. I used descriptors of the floodplain ecosystem- and landscape-level variables to assess their contribution to the maintenance of fish species richness. Using Generalized Linear Models (GLM) with negative binomial distribution I found that greater plant richness could offer a greater variety of food resources for frugivorous fishes and that a more extensive floodplain area provides larger forested habitat for fishes that depend on forest-derived food resources, as such subbasins with these characteristics support a greater frugivorous fish species richness. This work provides valuable information on species habitat associations by fish as well as food resource dynamics, floodplain dependence, and advances our understanding of the intricate relationship between forests and fish at a basin scale. This information is critical for assessing the impact of anthropogenic activities on freshwater ecosystems and can be used to inform conservation strategies in the tropics.

Least Cost Path Analysis (LCPA) is a GIS-based approach for calculating the most efficient route between a start and end point, often in terms of shortest time or least amount of energy. The approach is often applied in archaeology to estimate locations of sites, and routes between them. We applied LCPA to estimate how sites in the Andes in the eastern portion of the Inka empire may have connected to sites in the western Amazon Basin. Our approach further used the known Inka Road network to test performance of two types of LCP models (linear vs. areal calculation) and four types of cost functions. LCPs can be calculated with an areal approach, where each cell of the DEM is given one overall slope value, or linearly, where the direction of travel across a cell affects the slope value. Four different algorithms were tested: Tobler's Hiking Function (1993), Tobler's Hiking Function with a vertical exaggeration of 2.3 based on human perceptions of slope (Pingel 2010), Pingel's empirical estimation approach (2010), and Pandolf et al.'s energy expenditure equation (1977) using both an areal and linear approach for all the algorithms. An initial study was conducted in the Cusco region and results were compared to the Inka Road network using the linear accuracy assessment method of Goodchild and Hunter (1997) and Güimil-Fariña and Parcero-Oubiña (2015). The findings suggest that the empirical estimation and caloric cost methods were the most accurate and performed similarly, both were more accurate than travel-time based costs, and linear methods were better than areal based methods when using higher resolution DEM inputs. / Master of Science / Least Cost Path Analysis (LCPA) is a method used for determining the most efficient route between a start and end point, often in terms of shortest time or least amount of energy. The approach is often applied in archaeology to estimate locations of sites, and routes between them. We applied LCPA to estimate how sites in the Andes in the eastern portion of the Inka empire may have connected to sites in the western Amazon Basin. Our approach further used the known Inka Road network to test performance of two types of Least Cost Path (LCP) models (linear vs. areal calculation) and four types of cost functions. LCPs can be calculated with an areal approach, where each cell in an elevation dataset is given one overall slope value, or linearly, where the direction of travel across a cell affects the slope value. Four different ways of calculating cost were tested: Tobler's Hiking Function (1993) using time as a cost, Tobler's Hiking Function with a vertical exaggeration of 2.3 where the cost is based on human perceptions of slope (Pingel 2010), Pingel's empirical estimation approach (2010) based on the preexisting Inka Road system, and Pandolf et al.'s energy expenditure equation (1977). All four ways of calculating costs were used both an areal and linear approach. An initial study was conducted in the Cusco region and results were compared to the Inka Road network by seeing what percent of each LCP was within 500 m of the Inka Road. The findings suggest that the empirical estimation and energy based methods were the most accurate and performed similarly, both were more accurate than travel-time based costs, and linear methods were better than areal based methods when using higher resolution elevation data inputs.