Climate change and economic factors have led to a considerable increase in demand for renewable power generation in Texas, with yearly renewable generation increasing from 12% in 2015 to 34% in 2025. This study evaluates the feasibility of a 100 MW wind power plant located on the outskirts of El Paso, TX. The plant would require 30 to 40 wind turbines producing 3 MW each, powering up to 75,000 homes on average and providing clean, independent energy to the surrounding metropolitan area. The report focuses on the technical concerns of the proposed wind power plant and predicts its performance based on average hourly weather data in the region.

Per- and polyfluoroalkyl substances (PFAS) are man-made chemicals that have become increasingly detected in surface waters worldwide, yet accurate interpretation of environmental monitoring data is often complicated by widespread non-detect observations. This study evaluated PFAS occurrence along the upper Trinity River in north-central Texas and examined how treatment of censored data influences contamination assessment. Ten surface water samples were analyzed using EPA Method 1633, with 31.7% of the measurements below the reporting limit. Multiple imputation was applied to estimate site-level concentrations and quantify uncertainty associated with censored observations. Spatial analysis revealed a 12.8-fold difference in PFAS concentrations between background sites (53.7 ng/L) and hotspot sites (684.9 ng/L). Three sites exhibited fluorotelomer sulfonate signatures consistent with potential influence from aqueous film-forming foam (AFFF). Comparison with conventional RL/2 substitution methods revealed an underestimation of total PFAS concentrations by approximately 30–71 ng/L across sites, with the greatest bias occurring at background sites. All sampling sites exceeded current U.S. EPA drinking water standards for regulated PFAS compounds, suggesting potential implications for downstream drinking water systems. These findings demonstrate that statistical treatment of censored observations can substantially influence PFAS concentration estimates and the interpretation of contamination patterns.

This study established baseline information on bat resource use within the Leopard Ridge property of the Tanglewood Conservation Area in the Eastern Cape of South Africa to support long-term monitoring of a proposed mosaic habitat corridor. We focused on two key bat resources: water sources and a cave roost. Behavioral surveys were conducted at two river sites and one cave from May to July 2025 using infrared video recording paired with ultrasonic acoustic detectors to simultaneously document bat activity and echolocation calls. At water sources, cameras recorded bat presence, drinking events, and foraging behavior within the field of view, while concurrent acoustic recordings were used to identify species and confirm behaviors such as feeding and drinking through characteristic call structures. Drinking events were defined as bats contacting the water surface during flight, while foraging activity was identified by characteristic zig-zagging flight patterns and feeding buzzes in the acoustic recordings. At the cave roost, infrared video footage and automated image analysis were used to estimate nightly emergence counts, while concurrent acoustic recordings were used to estimate species composition among emerging bats. Together, these surveys provide baseline estimates of bat activity, drinking behavior, foraging use of water resources, and roost emergence within the study area. These data establish a reference point for evaluating how bat resource use changes as ecological restoration and corridor development progress within the Tanglewood Conservation Area.

Due to unprecedented urbanization in North Texas, coyotes have become more frequently observed in urban settings. The proposed project will examine the spatial distribution of coyote observations in North Texas, focusing on identifying spatial patterns. It also assesses whether these patterns are indicators of long-term adaptation in response to rapid urbanization in the region.  This study will use spatial analysis techniques to determine whether coyote observations are spatially clustered, identify potential hotspots, and assess whether the clustering is associated with a certain cover type. In addition, visual comparisons of multitemporal observations of data will be conducted to evaluate whether distribution patterns change over time. By integrating hotspot analysis and land cover data, the project aims to better understand how coyotes may be adapting to urban environments in North Texas.

This project proposes using ArcGIS-based spatial analysis to identify various vegetation zones at the Fort Worth Nature Center & Refuge and the surrounding areas, with the goal of supporting ecological management decisions. This will be accomplished through spatial overlay and other GIS analysis tools applied to relevant datasets, including topography (elevation), soil type, land cover, geology, and vegetation distribution derived from existing geospatial datasets. The distribution of plants based on these factors will help identify distinct zones, such as Fort Worth prairie, Cross Timbers savanna, and riparian forest. By compiling the results of the GIS analysis and producing maps to support both visual and statistical analysis, the project will provide insights for end users to identify existing and potentially new zones for ecological management.