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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Effects of GPS Error on Animal Home Range Estimates

Hyzer, Garrett 01 January 2012 (has links)
This study examined how variables related to habitat cover types can affect the positional accuracy of Global Positioning System (GPS) data and, subsequently, how wildlife home range analysis can be influenced when utilizing this inaccurate data. This study focused on measuring GPS accuracy relative to five habitat variables: open canopy, sparse canopy, dense canopy, open water, and building proximity. The study took place in Hillsborough County, in residential areas that contain all of these habitat types. Five GPS devices, designed for wildlife tracking purposes, were used to collect the data needed for this study. GPS data was collected under the aforementioned scenarios in order to induce error into the data sets. Each data set was defined as a 1-hour data collecting period, with a fix rate of 60 seconds, which resulted in 60 points per sample. The samples were analyzed to determine the magnitude of effect the five variables have on the positional accuracy of the data. Thirty samples were collected for each of the following scenarios: (1) open grassland with uninhibited canopy closure, (2) sparse vegetation canopy closure, (3) dense vegetation canopy closure, (4) close proximity to buildings (<2 m), and (5) open water with uninhibited canopy closure. Then, GPS errors (in terms of mean and maximum distance from the mean center of each sample) were calculated for each sample using a geographic information system (GIS). Confidence intervals were calculated for each scenario in order to evaluate and compare the levels of error. Finally, this data was used to assess the effect of positional uncertainty on home range estimation through the use of a minimum convex polygon home range estimation technique. Open grassland and open water cover types were found to introduce the least amount of positional uncertainty into the data sets. The sparse coverage cover type introduces a higher degree of error into data sets, while the dense coverage and building proximity cover types introduce the greatest amount of positional uncertainty into the data sets. When used to create minimum convex polygon home range estimates, these data sets show that the home range estimates are significantly larger when the positional error is unaccounted for as opposed to when it is factored into the home range estimate.
2

Sex-Specific Patterns of Movement and Space Use in the Strawberry Poison Frog, Oophaga pumilio

Murasaki, Seiichi 28 June 2010 (has links)
The home range encompasses an animal’s movements as it goes about its normal activity, and several home range estimators have been developed. I evaluated the performance of the Minimum Convex Polygon, Bivariate Normal, and several kernel home range estimators in a geographical information system environment using simulations and a large database of O. pumilio mark-recapture locations. A fixed 90% kernel estimator using Least-Square Cross-Validation (to select the bandwidth) outperformed other methods of estimating home range size and was effective with relatively few capture points. Home range size, core area size, intrasexual overlap, and movement rates among coordinates were higher in female frogs than in male frogs. These measures likely reflect behavioral differences related to territoriality (males only) and parental care (both sexes). The simple Biological Index of Vagility (BIV) generated movement values that scaled well with home range size while revealing more information than home range estimates alone.
3

Aplicacao de determinante: area de poligono convexo e volume de piramide / Determinants of application: convex polygon area and volume of pyramid

Araujo, Elismar Jose de 17 June 2015 (has links)
Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2015-10-22T14:36:33Z No. of bitstreams: 2 Dissertação - Elismar Jose de Araujo - 2015.pdf: 3923576 bytes, checksum: 60a5b973a48070a14372679c6aa08221 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2015-10-22T14:39:53Z (GMT) No. of bitstreams: 2 Dissertação - Elismar Jose de Araujo - 2015.pdf: 3923576 bytes, checksum: 60a5b973a48070a14372679c6aa08221 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2015-10-22T14:39:53Z (GMT). No. of bitstreams: 2 Dissertação - Elismar Jose de Araujo - 2015.pdf: 3923576 bytes, checksum: 60a5b973a48070a14372679c6aa08221 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2015-06-17 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / This work will concentrate on making a rereading of the theories that surround the procedures for calculating the area of a convex polygon, as well as the volume of a pyramid whose base is a polygon convex, with its vertices properly represented in a coordinate system, in the plan or in space, respectively. Addresses some topics on arrays and determinant and some of its applications, in particular the study of polygon area and the volume of the pyramid. Based on applying a decisive factor for the calculation of the area of a triangle with its vertices represented in a coordinate system, presents a new theorem to calculate the area of any polygon convex, as well as, a new formula to calculate the volume of any pyramid with convex basis as a direct application of the volume of the tetrahedron with its vertices represented in an orthogonal system. For both, it was essential to the concept of coordinates in the plane and in space, vectors in the plane and in space, and some of its properties, being essential for the demonstrate the volume of the tetrahedron and the area of the triangle, using determinant. Keywords: Volume. Area. Convex polygon. Pyramid. Triangle. Tetrahedron / O presente trabalho versar a em fazer uma releitura das teorias que circundam os procedimentos de c alculo da area de um pol gono convexo, assim como, do volume de uma pir^amide cuja base e um pol gono convexo, com seus v ertices devidamente representados em um sistema de coordenadas, no plano ou no espa co, respectivamente. Aborda alguns t opicos sobre matrizes e determinante e algumas de suas aplica c~oes, em especial o estudo de area de pol gonos e o volume de pir^amide. Baseado na aplica c~ao de determinante para o c alculo da area de um tri^angulo com seus v ertices representados em um sistema de coordenadas, apresenta um novo teorema para o c alculo da area de qualquer pol gono convexo, assim como, uma nova f ormula para calcular o volume de qualquer pir^amide com base convexa como uma aplica c~ao direta do volume do tetraedro com seus v ertices representados em um sistema ortogonal. Para tanto, foi imprescind vel abordar o conceito de coordenadas no plano e no espa co, vetores no plano e no espa co e algumas de suas propriedades, sendo fundamentais para a demonstrar o volume do tetraedro e a area do tri^angulo, usando determinante.
4

Range-use estimation and encounter probability for juvenile Steller sea lions (Eumetopias jubatus) in the Prince William Sound-Kenai Fjords region of Alaska

Meck, Stephen R. 21 March 2013 (has links)
Range, areas of concentrated activity, and dispersal characteristics for juvenile Steller sea lions Eumetopias jubatus in the endangered western population (west of 144° W in the Gulf of Alaska) are poorly understood. This study quantified space use by analyzing post-release telemetric tracking data from satellite transmitters externally attached to n = 65 juvenile (12-25 months; 72.5 to 197.6 kg) Steller sea lions (SSLs) captured in Prince William Sound (60°38'N -147°8'W) or Resurrection Bay (60°2'N -149°22'W), Alaska, from 2003-2011. The analysis divided the sample population into 3 separate groups to quantify differences in distribution and movement. These groups included sex, the season when collected, and the release type (free ranging animals which were released immediately at the site of capture, and transient juveniles which were kept in captivity for up to 12 weeks as part of a larger ongoing research program). Range-use was first estimated by using the minimum convex polygon (MCP) approach, and then followed with a probabilistic kernel density estimation (KDE) to evaluate both individual and group utilization distributions (UDs). The LCV method was chosen as the smoothing algorithm for the KDE analysis as it provided biologically meaningful results pertaining to areas of concentrated activity (generally, haulout locations). The average distance traveled by study juveniles was 2,131 ± 424 km. The animals mass at release (F[subscript 1, 63] = 1.17, p = 0.28) and age (F[subscript 1, 63] = 0.033, p = 0.86) were not significant predictors of travel distance. Initial MCP results indicated the total area encompassed by all study SSLs was 92,017 km², excluding land mass. This area was heavily influenced by the only individual that crossed over the 144°W Meridian, the dividing line between the two distinct population segments. Without this individual, the remainder of the population (n = 64) fell into an area of 58,898 km². The MCP area was highly variable, with a geometric average of 1,623.6 km². Only the groups differentiated by season displayed any significant difference in area size, with the Spring/Summer (SS) groups MCP area (Mdn = 869.7 km²) being significantly less than that of the Fall/Winter (FW) group (Mdn = 3,202.2 km²), U = 330, p = 0.012, r = -0.31. This result was not related to the length of time the tag transmitted (H(2) = 49.65, p = 0.527), nor to the number of location fixes (H(2) = 62.77, p = 0.449). The KDE UD was less variable, with 50% of the population within a range of 324-1,387 km2 (mean=690.6 km²). There were no significant differences in area use associated with sex or release type (seasonally adjusted U = 124, p = 0.205, r = -0.16 and U = 87, p = 0.285, r = -0.13, respectively). However, there were significant differences in seasonal area use: U = 328, p = 0.011, r = -0.31. There was no relationship between the UD area and the amount of time the tag remained deployed (H(2) = 45.30, p = 0.698). The kernel home range (defined as 95% of space use) represented about 52.1% of the MCP range use, with areas designated as "core" (areas where the sea lions spent fully 50% of their time) making up only about 6.27% of the entire MCP range and about 11.8% of the entire kernel home range. Area use was relatively limited – at the population level, there were a total of 6 core areas which comprised 479 km². Core areas spanned a distance of less than 200 km from the most western point at the Chiswell Islands (59°35'N -149°36'W) to the most eastern point at Glacier Island (60°54'N -147°6'W). The observed differences in area use between seasons suggest a disparity in how juvenile SSLs utilize space and distribute themselves over the course of the year. Due to their age, this variation is less likely due to reproductive considerations and may reflect localized depletion of prey near preferred haul-out sites and/or changes in predation risk. Currently, management of the endangered western and threatened eastern population segments of the Steller sea lion are largely based on population trends derived from aerial survey counts and terrestrial-based count data. The likelihood of individuals to be detected during aerial surveys, and resulting correction factors to calculate overall population size from counts of hauled-out animals remain unknown. A kernel density estimation (KDE) analysis was performed to delineate boundaries around surveyed haulout locations within Prince William Sound-Kenai Fjords (PWS-KF). To closely approximate the time in which population abundance counts are conducted, only sea lions tracked during the spring/summer (SS) months (May 10-August 10) were chosen (n = 35). A multiple state model was constructed treating the satellite location data, if it fell within a specified spatiotemporal context, as a re-encounter within a mark-recapture framework. Information to determine a dry state was obtained from the tags time-at-depth (TAD) histograms. To generate an overall terrestrial detection probability 1) The animal must have been within a KDE derived core-area that coincided with a surveyed haulout site 2) it must have been dry and 3) it must have provided at least one position during the summer months, from roughly 11:00 AM-5:00 PM AKDT. A total of 10 transition states were selected from the data. Nine states corresponded to specific surveyed land locations, with the 10th, an "at-sea" location (> 3 km from land) included as a proxy for foraging behavior. A MLogit constraint was used to aid interpretation of the multi-modal likelihood surface, and a systematic model selection process employed as outlined by Lebreton & Pradel (2002). At the individual level, the juveniles released in the spring/summer months (n = 35) had 85.3% of the surveyed haulouts within PWS-KF encompass KDE-derived core areas (defined as 50% of space use). There was no difference in the number of surveyed haulouts encompassed by core areas between sexes (F[subscript 1, 33] << 0.001, p = 0.98). For animals held captive for up to 12 weeks, 33.3% returned to the original capture site. The majority of encounter probabilities (p) fell between 0.42 and 0.78 for the selected haulouts within PWS, with the exceptions being Grotto Island and Aialik Cape, which were lower (between 0.00-0.17). The at-sea (foraging) encounter probability was 0.66 (± 1 S.E. range 0.55-0.77). Most dry state probabilities fell between 0.08-0.38, with Glacier Island higher at 0.52, ± 1 S.E. range 0.49-0.55. The combined detection probability for hauled-out animals (the product of at haul-out and dry state probabilities), fell mostly between 0.08-0.28, with a distinct group (which included Grotto Island, Aialik Cape, and Procession Rocks) having values that averaged 0.01, with a cumulative range of ≈ 0.00-0.02 (± 1 S.E.). Due to gaps present within the mark-recapture data, it was not possible to run a goodness-of-fit test to validate model fit. Therefore, actual errors probably slightly exceed the reported standard errors and provide an approximation of uncertainties. Overall, the combined detection probabilities represent an effort to combine satellite location and wet-dry state telemetry and a kernel density analysis to quantify the terrestrial detection probability of a marine mammal within a multistate modeling framework, with the ultimate goal of developing a correction factor to account for haulout behavior at each of the surveyed locations included in the study. / Graduation date: 2013
5

Algorithms for computing the optimal Geršgorin-type localizations / Алгоритми за рачунање оптималних локализација Гершгориновог типа / Algoritmi za računanje optimalnih lokalizacija Geršgorinovog tipa

Milićević Srđan 27 July 2020 (has links)
<p>There are numerous ways to localize eigenvalues. One of the best known results is that the spectrum of a given matrix ACn,n is a subset of a union of discs centered at diagonal elements whose radii equal to the sum of the absolute values of the off-diagonal elements of a corresponding row in the matrix. This result (Ger&scaron;gorin&#39;s theorem, 1931) is one of the most important and elegant ways of eigenvalues localization ([63]). Among all Ger&scaron;gorintype sets, the minimal Ger&scaron;gorin set gives the sharpest and the most precise localization of the spectrum ([39]). In this thesis, new algorithms for computing an efficient and accurate approximation of the minimal Ger&scaron;gorin set are presented.</p> / <p>Постоје бројни начини за локализацију карактеристичних корена. Један од најчувенијих резултата је да се спектар дате матрице АCn,n налази у скупу који представља унију кругова са центрима у дијагоналним елементима матрице и полупречницима који су једнаки суми модула вандијагоналних елемената одговарајуће врсте у матрици. Овај резултат (Гершгоринова теорема, 1931.), сматра се једним од најзначајнијих и најелегантнијих начина за локализацију карактеристичних корена ([61]). Међу свим локализацијама Гершгориновог типа, минимални Гершгоринов скуп даје најпрецизнију локализацију спектра ([39]). У овој дисертацији, приказани су нови алгоритми за одређивање тачне и поуздане апроксимације минималног Гершгориновог скупа.</p> / <p>Postoje brojni načini za lokalizaciju karakterističnih korena. Jedan od najčuvenijih rezultata je da se spektar date matrice ACn,n nalazi u skupu koji predstavlja uniju krugova sa centrima u dijagonalnim elementima matrice i poluprečnicima koji su jednaki sumi modula vandijagonalnih elemenata odgovarajuće vrste u matrici. Ovaj rezultat (Geršgorinova teorema, 1931.), smatra se jednim od najznačajnijih i najelegantnijih načina za lokalizaciju karakterističnih korena ([61]). Među svim lokalizacijama Geršgorinovog tipa, minimalni Geršgorinov skup daje najprecizniju lokalizaciju spektra ([39]). U ovoj disertaciji, prikazani su novi algoritmi za određivanje tačne i pouzdane aproksimacije minimalnog Geršgorinovog skupa.</p>

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