Sensory landscape impacts on odor-mediated predator-prey interactions at multiple spatial scales in salt marsh communities

This collection of research examines how changes in the sensory landscape, mediated by both odor and hydrodynamic properties, impact odor-mediated predator-prey interactions in salt marsh communities. I approached this research using an interdisciplinary framework that combined field and laboratory experimentation to address issues of scale and make connections between predator behavior and patterns of predation in the field. I explored a variety of interactions mediated by changes in the sensory landscape including; indirect effects of biotic structure on associated prey, predator responses to patches of prey with differing density and distribution, and dynamic interactions between predators and prey distributions. I found that biotic structure (oyster reefs [Crassostrea virginica]) has negative indirect effects on associated hard clam prey (Mercenaria mercenaria) through the addition of oyster reef odor cues that attract predators (blue crabs [Callinectes sapidus] and knobbed whelks [Busycon carica])and increase foraging success near the structural matrix. Variation in the structure of patch-scale prey odor plumes created by multiple prey results in predator-specific patterns of predation as a function of patch density and distribution which are mediated by differences in predator sensory ability. There is a potential negative feedback loop between blue crab predators and hard clam prey distributions; clam patches assume random within-patch distributions after exposure to blue crab predators, making the detection of patches by future blue crab predators more difficult. Sensory landscapes are also mediated by water flow, which transports prey odor plumes downstream to predators. Characterization of water flow in small-scale estuary systems indicates that values of turbulent flow parameters are highly context specific and depend on both tidal type (spring, neap, normal) and site. Wind and tidal range seem to be good predictors for wave components and turbulent components of fluctuating flow parameters, respectively, although the strength of their predictive ability is dependent on time scale. Modifications of the sensory landscape through changes in structurally-induced turbulence, mixing of individual plumes from multiple prey, and bulk velocity and turbulence characteristics need to be considered when formulating predictions as to the impact of predators on naturally occurring prey populations in the field.Ph.D.Committee Chair: Marc Weissburg; Committee Member: Donald Webster; Committee Member: Julia Kubanek; Committee Member: Lin Jiang; Committee Member: Mark Ha

Developing a Wildlife Tracking Extension for ArcGIS

Wildlife tracking is an essential task to gain better understanding of the migration pattern and use of space of the wildlife. Advances in computer technology and global positioning systems (GPS) have lowered costs, reduced processing time, and improved accuracy for tracking wild animals. In this thesis, a wildlife tracking extension is developed for ArcGIS 9.x, which allows biologists and ecologists to effectively track, visualize and analyze the movement patterns of wild animals. The extension has four major components: (1) data import; (2) tracking; (3) spatial and temporal analysis; and (4) data export. Compared with existing software tools for wildlife tracking, the major features of the extension include: (1) wildlife tracking capabilities using a dynamic data layer supported by a file geodatabase with 1 TB storage limit; (2) spatial clustering of wildlife locations; (3) lacunarity analysis of one-dimensional individual animal trajectories and two-dimensional animal locations for better understanding of animal movement patterns; and (4) herds evolvement modeling and graphic representation. The application of the extension is demonstrated using simulated data, test data collected by a GPS collar, and a real dataset collected by ARGOS satellite telemetry for albatrosses in the Pacific Ocean

Following fibroblast lineages in dermal development and scars

Fibroblast heterogeneity studies have shown that it vastly influences the outcome of wound repair (Griffin et al., 2020; Rinkevich et al., 2015). We aimed to characterize the origins of these heterogeneous populations in the publication I. Here we have shown that during dermal development there is an inherent inversion of fibroblast populations from abundant regenerative fibroblasts (ENFs) at early fetal stages of development, to abundant scar-producing fibroblasts (EPFs) during perinatal and adult life. Using novel imaging and analysis approaches, we have charted the dermal maturation dynamics of EPFs during the transition from scar-less (E12) to scarring stages (E16.5) of development. We then followed up on the role of scar-forming fibroblasts in postnatal and adult stages. In publication III, we identified the subcutaneous fascia as the main anatomical contributor of scars upon deep skin injury. Next, we followed the role of fascial scar producing cells, EPFs, and its contribution to scar formation in publication II. Here, we developed a relevant ex-vivo model called “scar-like tissue in a dish”- termed SCAD. We show that scars on SCADs emulate the bona fide in-vivo scar phenotype. Using this model, we visualize and chart live migration dynamics of EPFs at all stages of scar development. Further, using antibody screening and CRISPR-Cas9 based genetic approaches, we identified that N-Cadherin is the adhesion molecular that orchestrates EPF and fascial response to scarring. Finally, to check the clinical relevance, we validated our N-cadherin mechanistic findings in human skin biopsies from various anatomical locations. These findings provide a range of therapeutic avenues in modulating subcutaneous fascial response and prevention of pathological scars

Effect of gravity on inertial particle clustering and the Lagrangian attractors in Kinematic Simulation with different energy spectra

We study the clustering of inertial particles using a periodic kinematic simulation. A pre-defined Fourier based Eulerian flow field is established. The systematic Lagrangian tracking of particlesmakes it possible to identify the particles’ clustering patterns for different values of particle inertia and drift velocity. The different cases are characterised by different pairs of Stokes number (St) and Froude number (Fr)

Modeling Stromatolite Formation with Diffusion-Limited Aggregation

Stromatolites, microbialites, and other microbially induced sedimentary structures exist in the rock record as far back as 3.6 billion years ago and continue to form in the present day. Better characterizing these structures and better understanding how they form is crucial in distinguishing these biosignatures from similar, abiotic structures, which can help us to understand the conditions of early Earth and early Mars. To that end, I have modified DLA 3D EXT, an open-source stromatolite modeling program, to more closely reflect the process of microbial trapping-and-binding by filamentous microbes in a calcite-precipitating hot spring system. This modified program includes a field of upright spikes that can trap incoming particles and sediment. I simulated stromatolites forming with different spike heights, spike spacings, and stickiness. To quantify these stromatolites’ morphologies, I obtained the fractal dimension and lacunarity of a section of each resulting structure. I found that stickiness affects morphology as measured by both fractal dimension and lacunarity. This may help us better distinguish true stromatolites from abiotic imposters

Forest disturbance and recovery: A general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure

Abrupt forest disturbances generating gaps \u3e0.001 km2 impact roughly 0.4–0.7 million km2a−1. Fire, windstorms, logging, and shifting cultivation are dominant disturbances; minor contributors are land conversion, flooding, landslides, and avalanches. All can have substantial impacts on canopy biomass and structure. Quantifying disturbance location, extent, severity, and the fate of disturbed biomass will improve carbon budget estimates and lead to better initialization, parameterization, and/or testing of forest carbon cycle models. Spaceborne remote sensing maps large-scale forest disturbance occurrence, location, and extent, particularly with moderate- and fine-scale resolution passive optical/near-infrared (NIR) instruments. High-resolution remote sensing (e.g., ∼1 m passive optical/NIR, or small footprint lidar) can map crown geometry and gaps, but has rarely been systematically applied to study small-scale disturbance and natural mortality gap dynamics over large regions. Reducing uncertainty in disturbance and recovery impacts on global forest carbon balance requires quantification of (1) predisturbance forest biomass; (2) disturbance impact on standing biomass and its fate; and (3) rate of biomass accumulation during recovery. Active remote sensing data (e.g., lidar, radar) are more directly indicative of canopy biomass and many structural properties than passive instrument data; a new generation of instruments designed to generate global coverage/sampling of canopy biomass and structure can improve our ability to quantify the carbon balance of Earth\u27s forests. Generating a high-quality quantitative assessment of disturbance impacts on canopy biomass and structure with spaceborne remote sensing requires comprehensive, well designed, and well coordinated field programs collecting high-quality ground-based data and linkages to dynamical models that can use this information

Evaluation of Early Microstructural Changes in the R6/1 Mouse Model of Huntington's Disease by Ultra-High Field Diffusion MR Imaging

Diffusion MRI (dMRI) has been able to detect early structural changes related to neurological symptoms present in Huntington's disease (HD). However, there is still a knowledge gap to interpret the biological significance at early neuropathological stages. The purpose of this study is two-fold: (i) establish if the combination of Ultra-High Field Diffusion MRI (UHFD-MRI) techniques can add a more comprehensive analysis of the early microstructural changes observed in HD, and (ii) evaluate if early changes in dMRI microstructural parameters can be linked to cellular biomarkers of neuroinflammation. Ultra-high field magnet (16.7T), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI) techniques were applied to fixed ex-vivo brains of a preclinical model of HD (R6/1 mice). Fractional anisotropy (FA) was decreased in deep and superficial grey matter (GM) as well as white matter (WM) brain regions with well-known early HD microstructure and connectivity pathology. NODDI parameters associated with the intracellular and extracellular compartment, such as intracellular ventricular fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fractions (IsoVF) were altered in R6/1 mice GM. Further, histological studies in these areas showed that glia cell markers associated with neuroinflammation (GFAP & Iba1) were consistent with the dMRI findings. dMRI can be used to extract non-invasive information of neuropathological events present in the early stages of HD. The combination of multiple imaging techniques represents a better approach to understand the neuropathological process allowing the early diagnosis and neuromonitoring of patients affected by HD.Fil: Segatto, Rodolfo Guillermo. University Of Illinois. Deparment Of Biological Science; Estados UnidosFil: Weissmann, Carina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Amin, Manish. University of Florida. Department of Microbiology and Cell Science; Estados UnidosFil: Angeles López, Quetzalli D.. Consejo Nacional de Ciencia y Tecnologia de Mexico. Centro de Investigacion Cientifica y de Educacion Superior de Ensenada Baja California.; MéxicoFil: García Lara, Lucia. Consejo Nacional de Ciencia y Tecnologia de Mexico. Centro de Investigacion Cientifica y de Educacion Superior de Ensenada Baja California.; MéxicoFil: Salinas Castellanos, Libia Catalina. Consejo Nacional de Ciencia y Tecnologia de Mexico. Centro de Investigacion Cientifica y de Educacion Superior de Ensenada Baja California.; MéxicoFil: Deyoung, Daniel. University of Florida. Department of Microbiology and Cell Science; Estados UnidosFil: Segovia, Jose Manuel. Consejo Nacional de Ciencia y Tecnologia de Mexico. Centro de Investigacion Cientifica y de Educacion Superior de Ensenada Baja California.; MéxicoFil: Mareci, Thomas H.. University of Florida. Department of Microbiology and Cell Science; Estados UnidosFil: Uchitel, Osvaldo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Magin, Richard L.. University Of Illinois. Deparment Of Biological Science; Estados Unido