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Investigating the Ecophysiological Adaptations of Agroforests to Drought and Heatwaves Under the Modulating Influence of the Critical Zone Architecture
Jesus Manuel Ochoa-Rivero 1, 2, Katya Esquivel-Herrera1, Marguerite Mauritz 3, Anthony Darrouzet-Nardi 3, Frida D. Garcia-Ledezma 4, Luisa Camacho-Medina 1, Angel Ventura 1, Victoria Martinez 3, Lixin Jin 1, Luis Castruita-Esparza 5, Mukund Rao 6, Hugo A. Gutiérrez-Jurado 1 1 The University of Texas at El Paso, Department of Earth, Environmental and Resource Sciences 2 Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias 3 The University of Texas at El Paso, Biological Sciences 4 Stanford University, Doerr School of Sustainability, Stanford 5 Universidad Autonoma de Chihuahua, Facultad de Ciencias Agrícolas y Forestales 6 Columbia University, Tree Ring Laboratory, Lamont-Doherty Earth Observatory (LDEO) Global environmental change, soil structure and properties, and human management all interact to define the hydrologic and ecologic dynamics of agroecosystems in drylands. For example, Pecan trees (Carya illinoinensis) of the U.S. Southwest show legacy effects of soil textural differences on tree size and their physiological traits at the leaf level. We hypothesize that at interannual timescales, these conditions promote leaf plasticity from one year to another impacting the ecosystem water use and its efficiency. To address this hypothesis, this study explores two questions: 1) Have trees changed their ecophysiological traits at the leaf in response to stress from extreme climatic events in previous years? In other words, do trees have memory and adapt their leaves to become more or less water-use-efficient depending on their previous season conditions? And 2) If expressed are those changes in leaf morphology modulated by the architecture of the critical zone on which the trees are growing? We randomly selected pecan trees in two contrasting soil textures in a pecan orchard in West, Texas. Half of the trees are growing on fi ne textured (clayey) soils, and the other half are growing on coarse textured (sandy loam) soils. During the 2023 and 2024 growing seasons, we measured ecophysiological characteristics, responses, and functions of tree leaves using two leaflets in three positions of the branch: basal, middle, and apical, between 5:00 am and 6:00 pm. The resulting physiological parameters were analyzed and correlated with water sources, soil texture, and climate conditions. Preliminary results show pecan trees exhibit differential water sourcing and water-use efficiency adaptations based on soil texture and extreme climatic events. Leaf plasticity seems to be influenced by previous growing season conditions (air temperature and dryness). These findings are shedding light on how soil properties together with climatic extremes impact pecan trees' resource use dynamics and can inform agricultural practices promoting sustainable cultivation in diverse soil environments. Keywords: photosynthesis, water assimilation, abiotic stress |
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Evaluating a Machine Learning Workflow for Aftershock Catalog Construction: The 2017 Tehuantepec Mw8.2 Sequence
Marc Garcia The University of Texas at El Paso The September 8th, 2017, Mw 8.2 Tehuantepec earthquake was one of the strongest intraplate earthquakes in Mexico’s recorded history, generating over 30,000 aftershocks and highlighting the need for improved aftershock monitoring in the Tehuantepec region. In this project, we adapt and apply an open-source, machine learning–assisted workflow to construct a high-resolution aftershock catalog. The workflow integrates PhaseNet, a convolutional neural network trained to detect and pick P- and S-wave arrivals from continuous seismic waveforms, with GaMMA, an unsupervised Bayesian Gaussian Mixture Model for phase association and initial event characterization. These machine learning tools are combined with established location programs: HypoInverse for absolute event location using a region-specific 1D velocity model, and HypoDD for double-difference relative relocation. We processed six months of continuous waveform data from 28 stations, including a temporary RAPID deployment, enhancing azimuthal coverage and detectability across the offshore rupture zone. The resulting catalog exhibits high pick quality, improved location resolution, and internally consistent magnitude calculations, particularly for low-magnitude aftershocks. This study highlights how integrating and tuning modern ML tools with traditional relocation methods can produce scalable, high-quality catalogs in complex subduction settings. |
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The linkage of above and below ground structural diversity within a shrub invaded Chihuahuan Desert landscape
Eli Nyawunu, Elizabeth LaRue The University of Texas at El Paso There are different dimensions of diversity, both above and belowground, that each play a crucial role in ecosystem processes. Structural diversity – the volume and arrangement of vegetation within the ecosystem – has been shown to have a close relationship with ecosystem function, because the physical arrangement of vegetation influences the location of resources and habitat. However, the spatial patterns and linkage of above and belowground structural diversity is not all well characterized. Dryland landscapes that are invaded by shrubs have a characteristic pattern of patchy plant spacing, that may result in predicable relationships between above and belowground structural diversity. We used remote sensing approaches to quantify spatial patterns in above and belowground structural diversity across a shrub invaded landscape in the northern Chihuahuan Desert. Aboveground structural diversity of shrub vegetation was measured with unoccupied aerial vehicle (UAV) lidar at a honey mesquite dominated site at the Jornada Experimental Range (Las Cruces, NM). The structural diversity of coarse lateral roots was measured within the UAV footprint with Ground Penetrating Radar. Preliminary results show spatial heterogeneity in metrics that describe the biomass and structural arrangement of roots within the soil profile and aboveground shrub cover and height. We also observed a positive relationship between shrub cover with the heterogeneity in root biomass but a negative relationship with the heterogeneity of root depth. Remote sensing of above and belowground structural diversity could provide a basis for future monitoring tools of dryland structure and function in response to global change threats such as shrub encroachment. Keywords: Belowground, Chihuahuan Desert, Radio assisted detection and ranging, Remote sensing, Root biomass, Vegetation structure |
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Artificial Light At Night (ALAN)
Randall Walker, Kelly Ramirez The University of Texas at El Paso Artificial light at night (ALAN) illuminates the night sky allowing humans to extend the day length for work, socializing and cultural activities. While ALAN is beneficial to our developing society, it takes a significant toll on biological organisms that use the moon and stars for cues. Negatively affecting the circadian rhythm of biological organisms, anthropogenic activity increase in areas that originally lacked light, and the amount of short or long pulses of light intensity. Previously research has shown that insects, birds, some mammals and even plants are significantly influenced by ALAN. Yet, there is a lack of understanding how ALAN varies among different classes of microorganisms, if or how Alan effects microorganisms better as a whole or individual species, how ALAN influences a plants fitness with seasonal or human changes, behavioral, physiological, or metabolic responses, and how spatial variations of light exposure affects microbial activity. Soil biodiversity, including bacteria, archaea, fungi, and other eukaryotes largely colonize the top 5-10cm of soils and are a significant contributor to ecosystem processes like nutrient cycling, supporting primary productivity, and water filtration. In dryland systems, this layer of soil biodiversity is congregated in soil crusts (or biocrusts or cryptobiotic soils). Since soils contain microbes with different types of metabolisms, previous work has shown that some microbes cue to light, this research will explore if ALAN can impact microbial community diversity at local, regional, or global scales. To address this question I will use 3 different microbial data sets: (1) central park, NYC; (2) tall-grass prairie in the midwestern USA, and (3) a global sample set ranging from Alaska to Antarctica. |
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Multi-Physics Based Modelling Approach to Understand Plunging Flows in Scaled-Down Geometrically Similar Laboratory Experiment and Field–Scale Bedrock Rivers Using Eddy-Resolving Models
Jayanga T. Samarasinghe, Laura V. Alvarez The University of Texas at El Paso Fluid flow-induces incisions in bedrock rivers have a significant role in landscape evolution. Yet, the influence of flows in bedrock rivers for incision mechanisms remains unclear. Field experiments conducted in the Fraser River suggest that these incisions are caused by plunging flows. Plunging flows are complex fluid flows often observed in bedrock rivers with constriction-pool-widening (CPW) channel morphology. These flows associated velocity inversions result in shear stresses at bed, responsible for sediment transport, and subsequent incisions. However, field experiments are complex and uncertain while laboratory experiments showed distortions in flow dynamics. Numerical modeling serves as a tool to address this issue. However, neither field-laboratory experiments nor numerical models can fully capture natural processes due to limitations and simplifications. Therefore, the combination of both would help to have a better understanding of the flow processes. Recently, Computational Fluid Dynamics (CFD) models have emerged as a method for accurately simulating turbulent flows. The present study is conducted to understand complex fluid dynamics in plunging flows, using CFD models. The computational domains for field-scale and laboratory experiment model were constructed from a structured hexagonal grid mesh. LES technique was employed to resolve anisotropic turbulence above a spatial filter, and pimpleFoam was used as the incompressible solver algorithm for velocity-pressure coupling. The boundary conditions imposed for the models at riverbed and sidewalls in the computational domain are set as non-slip and integrated with the rough-wall function, water surface is set as slip, and the inlet with velocities corresponds to high and low flows. CFD simulations show that CPW morphology and discharge govern the formation of plunging flows and velocity inversions. This velocity inversion causes high bed shear stresses, leading to erosion and incisions. Moreover, the developed CFD model can be used as a benchmark for understanding complex fluid dynamics and flow processes, in bedrock rivers. |
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