Soundscape Mapping: Spatial Variability of Sound at Furman University

Looking at the entire soundscape and studying its spatial variability can often give us important information about the health of the ecosystem. However, most previous studies only measure sound intensity, and are therefore limited in their depiction of the soundscape. Another tool for mapping soundscapes is SPreAD-GIS. This tool models sound propagation in an area. However, previous studies have only used it to evaluate the effects of noise pollution, but not applied it towards depicting the soundscape as a whole. I mapped the soundscape of Furman University’s campus using sound intensity as well as many different soundscape indices in order to see how sound varied spatially and how landscape characteristics such as land cover and anthropogenic disturbances affected the soundscape. I used a combined approach of interpolating actual recording values and SPreAD-GIS modeling

Fracking in Pennsylvania: A Spatial Analysis of Impacts on Land Cover and Land Use, the Viewshed, and the Audioshed

Hydraulic fracturing is the process of extracting natural gas from layers of shale rock beneath the surface of the Earth. The largest source of natural gas in the US is the Marcellus Shale, largely located in Pennsylvania, and it is believed to hold about 141 trillion cubic feet of natural gas in its shale deposits. My study examined the impacts of well sites on land cover and land use, the viewshed, and the audioshed. To study the effect of wellpads on land use and land cover, we overlaid a layer of wellpads over land cover data as well as a layer of Pennsylvania natural resources. To study the visual and sound impacts of wellpads and compressor stations, we generated viewsheds and audiosheds and then calculated the percent of land, road, and trails impacted within different environment types. We found that the majority of producing wells are currently found in forested areas and within 1320 feet of a stream or wetland. However, we found that there is also seemingly a bias against placing wellpads near wetland areas. Additionally, rural land cover areas were found to have a disproportionate number of wellpads in relation to their area within the Marcellus shale region. Rural environments were also found to be impacted the highest in regards to the viewshed, having over 20% of the tile within the fracking viewshed for tiles with at least 2 wellpads. In regards to noise impacts, high road density areas and state forest areas were found to have similar percentages within the audioshed for tiles with at least one compressor station. So overall, in areas with at least 2 wellpads, rural areas have the most potential impacts due to fracking for both land cover and land use as well as the viewshed

Location matters: evaluating Greater Prairie-Chicken (Tympanuchus cupido) boom chorus propagation

Anthropogenic disturbances can affect species of conservation concern by influencing their behavior. Of special concern is the possibility that noise from anthropogenic structures in grassland habitats, such as wind turbines and roads, may affect the propagation of the low-frequency boom chorus of lekking male Greater Prairie-Chickens (Tympanuchus cupido). We used sound pressure levels from acoustic recordings taken at 10 leks in the Nebraska Sandhills, USA during 2013 and 2014 in a SPreAD-GIS sound propagation model to make spatial projections of the boom chorus under a variety of conditions including landscape composition, conspecific attendance, and weather. We then used sets of linear mixed models in a model selection process to determine how background noise, female and male lek attendance, time of day, relative humidity, air temperature, and wind speed affected the area of chorus propagation. The predicted area of propagation decreased with increasing background noise (β = -0.09, SE = 0.04) and increased with greater female lek attendance (β = 0.09, SE = 0.03), higher levels of relatively humidity (β = 0.07, SE = 0.03), and higher air temperatures (β = 0.05, SE = 0.03). Our analyses provide new insight on how acoustic, social, and meteorological factors influence an important reproductive behavior in an imperiled prairie grouse

MULTI AGENT-BASED ENVIRONMENTAL LANDSCAPE (MABEL) - AN ARTIFICIAL INTELLIGENCE SIMULATION MODEL: SOME EARLY ASSESSMENTS

The Multi Agent-Based Environmental Landscape model (MABEL) introduces a Distributed Artificial Intelligence (DAI) systemic methodology, to simulate land use and transformation changes over time and space. Computational agents represent abstract relations among geographic, environmental, human and socio-economic variables, with respect to land transformation pattern changes. A multi-agent environment is developed providing task-nonspecific problem-solving abilities, flexibility on achieving goals and representing existing relations observed in real-world scenarios, and goal-based efficiency. Intelligent MABEL agents acquire spatial expressions and perform specific tasks demonstrating autonomy, environmental interactions, communication and cooperation, reactivity and proactivity, reasoning and learning capabilities. Their decisions maximize both task-specific marginal utility for their actions and joint, weighted marginal utility for their time-stepping. Agent behavior is achieved by personalizing a dynamic utility-based knowledge base through sequential GIS filtering, probability-distributed weighting, joint probability Bayesian correlational weighting, and goal-based distributional properties, applied to socio-economic and behavioral criteria. First-order logics, heuristics and appropriation of time-step sequences employed, provide a simulation-able environment, capable of re-generating space-time evolution of the agents.Environmental Economics and Policy,

Modeling Sound in Ancient Maya Cities: Moving Towards a Synesthetic Experience using GIS & 3D Simulation

Digital technologies enable modeling of the potential role of sound in past environments. While digital approaches have limitations in objectively rendering reality, they provide an expanded platform that potentially increases our understanding of experience in the past and enhances the investigation of ancient landscapes. Digital technologies enable new experiences in ways that are multi-sensual and move us closer toward reconstructing holistic views of past landscapes. Archaeologists have successfully employed 2D and 3D tools to measure vision and movement within cityscapes. However, built environments are often designed to invoke synesthetic experiences that also include sound and other senses. Geographic Information Systems (GIS) and Virtual Reality (VR) allow archaeologists to measure and explore the acoustics of ancient spaces. I employ GIS and 3D modeling o measure sound propagation and reverberation using the main civic-ceremonial complex in ancient Copán as a case study. The goal is to create a synesthetic experience to enrich our and understanding of the role sight and sound played in ancient Maya cities. For the ancient Maya, sight and sound worked in concert to create ritually charged atmospheres and architecture served to shape these experiences. I use an immersive VR headset (Oculus Rift) to integrate vision with spatial sound and sight to facilitate an embodied experience in order to: (1) examine potential locations of ritual performance and (2) determine spatial placement and capacity of participants in these events. Advisor: Heather Richards-Rissett

Spatiotemporal analysis of forest fire risk models : a case study for a greek island

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesForest fires are a natural phenomenon which might have severe implications on natural and anthropogenic ecosystems. Consequently, the integrated protection of these ecosystems from forest fires is of high priority. The aim of the project lies in the development of two preventive models which will act in synergy in order to effectively protect the most critical natural resource of the island, namely, the abundant forests. Thus, fire risk modeling is combined with visibility analysis, so that we may primarily protect the most susceptible territory of the study area. The corner stone of the methodology is primarily relied on the multi-criteria decision analysis. This framework applied not only for the fire risk estimation and the corresponding evolution in a context of 20 years, but for visibility analysis as well, determining the most suitable locations for the establishment of a minimum number of watchtowers. The fire risk map for 2016 indicated that 34% of the entire study area is covered by territory of low fire risk; 27% of moderate risk; 34% of high and very high risk, while there is a 6% of the island which is characterized by extremely fire risk. Similar conclusions can be drawn for 1996, since no significant changes have been observed, especially on the land cover types and their spatial arrangement. Based on the visibility results, more than 40% of the entire island is visible from the selected location scheme consisting of just 8 watchtowers. The intense topography constituted the most critical barrier in increasing this percentage. Some good practices to counterbalance the relative small percentage of visibility could include; the extensive patrols in unmonitored regions through the intense road network of the island; the adoption of drones covering the aforementioned areas, especially when extreme meteorological conditions are expected

Ruumiliste otsustustugede arendamine võimaldamaks merede jätkusuutlikku majandamist

Väitekirja elektrooniline versioon ei sisalda publikatsiooneMeremajanduse teostamiseks on vaja eri tüüpi ruumilist infot, millele tuginevad tööriistad on hädavajalikud kriisiolukorras reageerimiseks ja erinevate stsenaariumipõhiste analüüside läbiviimisel. Doktoritöös arendati veebipõhiseid operatiivseid otsustustugesid, mis võimaldavad koguda ja analüüsida andmeid ja teadmisi ning edastada tulemusi sidusrühmadele arusaadaval viisil, et hõlbustada kokkulepete sõlmimist. Sellist lähenemist illustreerib Next-Generation Smart Response Web (NG-SRW), mis võimaldab hinnata naftareostusega seotud keskkonnariske ja leida hädaolukordadele paremaid lahendusi. Naftalekke ruumilise leviku modelleerimine ja selle visualiseerimine võimaldab hinnata võimalike meetmete eeliseid, et kujundada sobiv reageerimisstrateegia. Lisaks valmis doktoritöö käigus PlanWise4Blue (PW4B) tööriist, millega hinnatakse erinevate survetegurite kumulatiivset mõju mereelustikule. PW4B tööriista saab kasutada inimtegevuste eraldi- ja koosmõjude prognoosimiseks nii tänapäevaste kui ka tuleviku kliimamuutuste tingimustes. Tööriista katsetati Läänemere piirkonnas Eesti mereala ruumilise planeerimise protsessis uurimaks erinevate meremajandamisstsenaariumite mõju erinevatele loodusväärtustele. Tulemused julgustavad kasutama modelleerimisel põhinevaid stsenaariumarvutusi otsustusprotsessides, et uurida inimtegevuse mõju ja/või kasu ökosüsteemi teenuste osutamisele ja vastupidi. Stsenaariumianalüüse kasutades saame teada ühiskonna eelistusi selle kohta, millist tulevikku nad eelistaksid ning paraneb otsustusprotsesside läbipaistvus.The maritime economy requires different types of spatial information, on which spatial decision support tools are essential to respond to crisis situations and to carry out different scenario-based analyses. This doctoral study developed web-based operational decision support tools to collect and analyse data and insights as well as to facilitate communication and discussion with stakeholders. Such an approach is illustrated by the Next-Generation Smart Response Web (NG-SRW), which enables the assessment of environmental risks associated with oil spills and the identification of better solutions to emergencies. By integrating the analysis and visualization of dynamic spill features, the benefits of potential response actions are compared to develop an appropriate response strategy. In addition, PlanWise4Blue (PW4B), a tool to assess the cumulative impact of different human pressures on marine life, was developed during the PhD. The PW4B tool can be used to predict the individual and combined effects of human activities under both current environmental conditions and future climate change. The tool has been tested in the Baltic Sea region in the Estonian marine spatial planning process to investigate the impacts of different marine management scenarios on different nature values. The results encourage the use of modelling-based scenario calculations in decision-making processes to explore effects and/or benefits of human activities to ecosystem services provision, and vice versa. Scenario analysis can be used to include society preferences of what future would they prefer and can improve transparency in decision-making processes.https://www.ester.ee/record=b550706

Ecological models at fish community and species level to support effective river restoration

RESUMEN Los peces nativos son indicadores de la salud de los ecosistemas acuáticos, y se han convertido en un elemento de calidad clave para evaluar el estado ecológico de los ríos. La comprensión de los factores que afectan a las especies nativas de peces es importante para la gestión y conservación de los ecosistemas acuáticos. El objetivo general de esta tesis es analizar las relaciones entre variables biológicas y de hábitat (incluyendo la conectividad) a través de una variedad de escalas espaciales en los ríos Mediterráneos, con el desarrollo de herramientas de modelación para apoyar la toma de decisiones en la restauración de ríos. Esta tesis se compone de cuatro artículos. El primero tiene como objetivos modelar la relación entre un conjunto de variables ambientales y la riqueza de especies nativas (NFSR), y evaluar la eficacia de potenciales acciones de restauración para mejorar la NFSR en la cuenca del río Júcar. Para ello se aplicó un enfoque de modelación de red neuronal artificial (ANN), utilizando en la fase de entrenamiento el algoritmo Levenberg-Marquardt. Se aplicó el método de las derivadas parciales para determinar la importancia relativa de las variables ambientales. Según los resultados, el modelo de ANN combina variables que describen la calidad de ribera, la calidad del agua y el hábitat físico, y ayudó a identificar los principales factores que condicionan el patrón de distribución de la NFSR en los ríos Mediterráneos. En la segunda parte del estudio, el modelo fue utilizado para evaluar la eficacia de dos acciones de restauración en el río Júcar: la eliminación de dos azudes abandonados, con el consiguiente incremento de la proporción de corrientes. Estas simulaciones indican que la riqueza aumenta con el incremento de la longitud libre de barreras artificiales y la proporción del mesohabitat de corriente, y demostró la utilidad de las ANN como una poderosa herramienta para apoyar la toma de decisiones en el manejo y restauración ecológica de los ríos Mediterráneos. El segundo artículo tiene como objetivo determinar la importancia relativa de los dos principales factores que controlan la reducción de la riqueza de peces (NFSR), es decir, las interacciones entre las especies acuáticas, variables del hábitat (incluyendo la conectividad fluvial) y biológicas (incluidas las especies invasoras) en los ríos Júcar, Cabriel y Turia. Con este fin, tres modelos de ANN fueron analizados: el primero fue construido solamente con variables biológicas, el segundo se construyó únicamente con variables de hábitat y el tercero con la combinación de estos dos grupos de variables. Los resultados muestran que las variables de hábitat son los ¿drivers¿ más importantes para la distribución de NFSR, y demuestran la importancia ecológica de los modelos desarrollados. Los resultados de este estudio destacan la necesidad de proponer medidas de mitigación relacionadas con la mejora del hábitat (incluyendo la variabilidad de caudales en el río) como medida para conservar y restaurar los ríos Mediterráneos. El tercer artículo busca comparar la fiabilidad y relevancia ecológica de dos modelos predictivos de NFSR, basados en redes neuronales artificiales (ANN) y random forests (RF). La relevancia de las variables seleccionadas por cada modelo se evaluó a partir del conocimiento ecológico y apoyado por otras investigaciones. Los dos modelos fueron desarrollados utilizando validación cruzada k-fold y su desempeño fue evaluado a través de tres índices: el coeficiente de determinación (R2 ), el error cuadrático medio (MSE) y el coeficiente de determinación ajustado (R2 adj). Según los resultados, RF obtuvo el mejor desempeño en entrenamiento. Pero, el procedimiento de validación cruzada reveló que ambas técnicas generaron resultados similares (R2 = 68% para RF y R2 = 66% para ANN). La comparación de diferentes métodos de machine learning es muy útil para el análisis crítico de los resultados obtenidos a través de los modelos. El cuarto artículo tiene como objetivo evaluar la capacidad de las ANN para identificar los factores que afectan a la densidad y la presencia/ausencia de Luciobarbus guiraonis en la demarcación hidrográfica del Júcar. Se utilizó una red neuronal artificial multicapa de tipo feedforward (ANN) para representar relaciones no lineales entre descriptores de L. guiraonis con variables biológicas y de hábitat. El poder predictivo de los modelos se evaluó con base en el índice Kappa (k), la proporción de casos correctamente clasificados (CCI) y el área bajo la curva (AUC) característica operativa del receptor (ROC). La presencia/ausencia de L. guiraonis fue bien predicha por el modelo ANN (CCI = 87%, AUC = 0.85 y k = 0.66). La predicción de la densidad fue moderada (CCI = 62%, AUC = 0.71 y k = 0.43). Las variables más importantes que describen la presencia/ausencia fueron: radiación solar, área de drenaje y la proporción de especies exóticas de peces con un peso relativo del 27.8%, 24.53% y 13.60% respectivamente. En el modelo de densidad, las variables más importantes fueron el coeficiente de variación de los caudales medios anuales con una importancia relativa del 50.5% y la proporción de especies exóticas de peces con el 24.4%. Los modelos proporcionan información importante acerca de la relación de L. guiraonis con variables bióticas y de hábitat, este nuevo conocimiento podría utilizarse para apoyar futuros estudios y para contribuir en la toma de decisiones para la conservación y manejo de especies en los en los ríos Júcar, Cabriel y Turia.Olaya Marín, EJ. (2013). Ecological models at fish community and species level to support effective river restoration [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/28853TESI

Impacts to Quail Space Use and Demographics from Oil and Gas Development

Southern Texas contains some of the last relatively unfragmented habitat for northern bobwhite (Colinus virginianus; hereafter, bobwhite) and scaled quail (Callipepla squamata) in the United States. Development of the Eagle Ford Shale hydrocarbon formation in this region could negatively impact quail and their habitat. Our objective was to examine the indirect effects of oil and gas activity (traffic and noise) on bobwhite and scaled quail on 2 private ranches in southern Texas. In 2015 and 2016, we radio-marked bobwhite and scaled quail in 2 areas where oil and gas activity was occurring (disturbed treatment) and 2 areas where little oil and gas activity occurred (undisturbed treatment). We measured vehicle passages and modeled noise propagation from oil and gas infrastructure at 2 biologically relevant frequencies (250 Hz and 1,000 Hz) in our study area to quantify oil and gas disturbance and examine its effects on quail space use (site selection and home range size) and demographics (survival, nest success, and density). Bobwhite and scaled quail selected areas 0–200 m and \u3e425 m, respectively, from the primary, high-traffic roads in the disturbed treatment. In the undisturbed treatment, bobwhite and scaled quail selected areas 0–425 m and 0–300 m from primary roads, respectively. Bobwhite and scaled quail selected areas with sound levels 0–1.6 and 0–2.2 dB above ambient levels at the 250-Hz frequency level, respectively. At 1,000 Hz, bobwhite and scaled quail selected areas with sound levels 0–2 and 0–3.2 dB above ambient levels, respectively. We found no evidence that disturbance variables affected bobwhite and scaled quail home range size, survival, or density. We found bobwhite nest success decreased as sound levels (dB) at 250 Hz increased; we found no relationship between nest success and disturbance for scaled quail, possibly as they avoided major oil and gas disturbances. In calculations of the total footprint of quail habitat loss, indirect loss due to oil and gas activity needs to be considered in addition to direct loss due to conversion of rangeland to oil and gas infrastructure