Understanding species-habitat relationships for endangered species is critical for their conservation. However, many studies have limited value for conservation because they fail to account for habitat associations at multiple spatial scales, anthropogenic variables, and imperfect detection. We addressed these three limitations by developing models for an endangered wetland bird, Yuma Ridgway's rail (Rallus obsoletus yumanensis), that examined how the spatial scale of environmental variables, inclusion of anthropogenic disturbance variables, and accounting for imperfect detection in validation data influenced model performance. These models identified associations between environmental variables and occupancy. We used bird survey and spatial environmental data at 2473 locations throughout the species' U.S. range to create and validate occupancy models and produce predictive maps of occupancy. We compared habitat-based models at three spatial scales (100, 224, and 500 m radii buffers) with and without anthropogenic disturbance variables using validation data adjusted for imperfect detection and an unadjusted validation dataset that ignored imperfect detection. The inclusion of anthropogenic disturbance variables improved the performance of habitat models at all three spatial scales, and the 224-m-scale model performed best. All models exhibited greater predictive ability when imperfect detection was incorporated into validation data. Yuma Ridgway's rail occupancy was negatively associated with ephemeral and slow-moving riverine features and high-intensity anthropogenic development, and positively associated with emergent vegetation, agriculture, and low-intensity development. Our modeling approach accounts for common limitations in modeling species-habitat relationships and creating predictive maps of occupancy probability and, therefore, provides a useful framework for other species.

Orientador: Luís Felipe de Toledo Ramos Pereira / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Biologia / Made available in DSpace on 2018-08-27T11:16:08Z (GMT). No. of bitstreams: 1 Oliveira_IgorSoaresde_D.pdf: 4104401 bytes, checksum: 76046f01be0657270cbc44223cd762b9 (MD5) Previous issue date: 2015 / Resumo: As mudanças climáticas possuem potencial para alterar o funcionamento dos ecossistemas através da extinção de espécies e das conexões entre a biota e o ambiente, alterando os padrões aos quais estamos acostumados e exigindo adaptação. As alterações climáticas terão como uma de suas consequências a elevação oceânica, que pode redesenhar as costas de todos os continentes terrestres e afetar a biota associada. Nesse contexto, sobressaem-se os anfíbios como um grupo sensível que sofre diversas pressões e apresenta declínios populacionais, se destacando como vertebrados mais ameaçados da atualidade, com diversas espécies pouco conhecidas. Sendo assim, nesse trabalho analisamos múltiplos efeitos que dificultam a conservação dos anfíbios. Avaliamos os potenciais efeitos das mudanças climáticas e da elevação oceânica sobre os anfíbios com distribuição costeira. Também desenvolvemos um índice para classificar espécies com dados insuficientes com a finalidade de oferecer uma alternativa para a busca de informações para esses taxa e mudar sua classificação atual. Por fim, analisamos a disponibilidade histórica de clima adequado para uma linhagem endêmica do fungo quitrídio em busca de padrões que pudessem explicar sua distribuição e raridade atuais. Utilizamos ferramentas como modelos de distribuição de espécies e sistema de informação geográfica em busca de respostas às nossas questões. Nossos resultados corroboram as mudanças climáticas como um fenômeno com potencial devastador e alertam para potenciais perigos da elevação oceânica. Além disso, nosso índice para espécies deficientes em dados pode auxiliar a direcionar esforços em busca de novas informações. Por fim, nossas análises com relação ao fungo quitrídio corroboram a hipótese de endemismo para a linhagem Bd-Brazil e também evidenciam hábitat adequado passado para o Bd-GPL. Além disso, verificamos baixa sobreposição de nicho climático entre essas duas linhagens, indicando possibilidade de competição. Assim, esperamos que nossos resultados tenham contribuído para o conhecimento de múltiplas ameaças à conservação dos anfíbios e sirvam para direcionar futuros estudos / Abstract: Climate change has the potential to change ecosystem functioning through species extinction and disrupting connection between biota and environment, thus changing natural patterns and requiring adaptation. One certain consequence of climate change is the sea level rise, which is expected to redraw coastal shorelines worldwide and broadly affect coastal-associated biota. In this context, amphibians represent a sensitive group under several current pressures, exhibiting population decline, highlighted as the most current threaten vertebrates on Earth, and also, with several "data deficient" species. Thus, herein we analyzed multiple effects that hamper amphibian conservation. We evaluated potential climate change effects and sea level rise on amphibians with coastal distribution. Also, we developed an index to classify data deficient species in order to offer an alternative further research of such species to gather sufficient information to change their current status. Finally, we analyzed historical availability of suitable habitat for and endemic lineage of the chytrid fungus searching for patterns that explain its current distribution and rarity. We used tools as species distribution models and geographic information system to answer our questions. Our results corroborate climate change as a potentially devastating phenomena and we stress potential threatens derived from sea level rise. Moreover, the index we developed for data deficient species seems to work properly and may drive further effort in searching for further information for those species. Finally, our analyzes related to the chytrid fungus supported the hypothesis of endemism of Bd-Brazil, and also showed past environmental suitability for Bd-GPL. In addition, we verified low environmental niche overlap these two lineages, indicating possibility of competition. Thus, we expect our results may improve current knowledge about multiple threats to amphibian conservation, as well as, they may be used to guide further research / Doutorado / Ecologia / Doutor em Ecologia

On the territory of the Czech Switzerland National Park took place during the Holocene significant changes in vegetation cover to the form is most enrolled medium Holocene climatic optimum when broadleaf deciduous forests expanded into Central Europe. These transformations are caused by climatic changes. However, it started the process of soil acidification to this day that caused the other variations of the vegetation composition, even the extinction a variety of species especially in sandstone areas. In addition, in the last few centuries the human impact is graduating, which more or less of the original forests changes due to agricultural and economic reasons to breed-specific and the same-aged plantations which supports the already declining species diversity and relative abundance of the undergrowth species. This work focuses on a single species, evergreen undergrowth shrub Ledum palustre which is characterized by strong demands on its habitat and indicates the specific habitat type. It grows on the upper north-facing edges of rocks with plenty of light and humidity. At these locations stores organic material thanks the favourable hydrology. This makes possible to study the use of pollen and macroremains the paleoecology of the species. On the basis of recent occurrences and the relationships...

No description available.

The increase in truck traffic on highways has brought many problems and challenges to transportation planning and traffic operation, including traffic congestion, transportation system deficiency (insufficient truck parking, etc.), safety, infrastructure deterioration, environmental impacts (air quality and noise), economic development, and so forth. Along with the increase in truck traffic, the need for developing a statewide truck freight demand model has grown so that a state can estimate truck traffic at any point on its highways. The most significant hurdle to including freight transportation in the transportation modeling process is that most of the demand forecasting methodologies currently available were developed for passenger trips, not freight trips. This type of modeling methodology usually makes an assumption that freight trips follow the same behavioral mechanism as passenger trips. In order to overcome the weakness of using a typical four-step demand forecasting modeling process, the concept of commodity flow models (CFMs) can be used to develop a truck freight flow model. It is widely accepted that focusing on the freights enables CFMs to capture more accurately the fundamental economic mechanisms that drive freight movements. The type of commodity being carried is one of the most important characteristics of truck movements, and it is sometimes a challenge to obtain such information from the carriers. Thus, lately, the integration of the freight flow modeling and land use modeling has emerged as an alternate tool to estimate freight movements than the previously developed models. In this study, county-level multiple regression models relating land use to commodity flow were developed using a geographical information system and statistics. Then, a statistical/mathematical statewide commodity flow distribution model was developed by using a physical friction factor (physical distance), a statistical friction factor (Euclidean distance), and economic factors (differences of population and difference of employment among the counties). The commodity flow distributed among truck traffic analysis zones (TTAZs) by the statewide commodity flow distribution model were converted to truck trips and the resulting truck trips were assigned to Utah's truck routes using the all-or-nothing assignment procedure of TransCAD and a genetic algorithm. Truck freight data from the US Census Bureau's Commodity Flow Surveys, which have become available to the public for free via the Internet, enabled the development of a commodity flow based statewide truck freight demand model. It was found that the integration of the freight flow and land use data could be a practical method for modeling tuck traffic demand on state-wide truck routes although the current level of data availability on commodity flow and land use data still constrains the full capability of this type of modeling.

No description available.

<p>Recently, the Conway-Maxwell Poisson (COM-Poisson) cure rate model has been proposed which includes as special cases some of the well-known cure rate models discussed in the literature. Data obtained from cancer clinical trials are often right censored and the expectation maximization (EM) algorithm can be efficiently used for the determination of the maximum likelihood estimates (MLEs) of the model parameters based on right censored data.</p> <p>By assuming the lifetime distribution to be exponential, lognormal, Weibull, and gamma, the necessary steps of the EM algorithm are developed for the COM-Poisson cure rate model and some of its special cases. The inferential method is examined by means of an extensive simulation study. Model discrimination within the COM-Poisson family is carried out by likelihood ratio test as well as by information-based criteria. Finally, the proposed method is illustrated with a cutaneous melanoma data on cancer recurrence. As the lifetime distributions considered are not nested, it is not possible to carry out a formal statistical test to determine which among these provides an adequate fit to the data. For this reason, the wider class of generalized gamma distributions is considered which contains all of the above mentioned lifetime distributions as special cases. The steps of the EM algorithm are then developed for this general class of distributions and a simulation study is carried out to evaluate the performance of the proposed estimation method. Model discrimination within the generalized gamma family is carried out by likelihood ratio test and information-based criteria. Finally, for the considered cutaneous melanoma data, the two-way flexibility of the COM-Poisson family and the generalized gamma family is utilized to carry out a two-way model discrimination to select a parsimonious competing cause distribution along with a suitable choice of a lifetime distribution that provides the best fit to the data.</p> / Doctor of Philosophy (PhD)

When we develop and use species distribution models to predict species' current or potential distributions, we are faced with the trade-offs between model generality, precision, and realism. It is important to know how to improve and validate model generality while maintaining good model precision and realism. However, it is difficult for ecologists to evaluate species distribution models using field-sampled data alone because the true species response function to environmental or ecological factors is unknown. Species distribution models should be able to approximate the true characteristics and distributions of species if ecologists want to use them as reliable tools. Simulated data provide the advantage of being able to know the true species-environment relationships and control the causal factors of interest to obtain insights into the effects of these factors on model performance. I used a case study on Bythotrephes longimanus distributions from several hundred Ontario lakes and a simulation study to explore the effects on model performance caused by several factors: the choice of predictor variables, the model evaluation methods, the quantity and quality of the data used for developing models, and the strengths and weaknesses of different species distribution models. Linear discriminant analysis, multiple logistic regression, random forests, and artificial neural networks were compared in both studies. Results based on field data sampled from lakes indicated that the predictive performance of the four models was more variable when developed on abiotic (physical and chemical) conditions alone, whereas the generality of these models improved when including biotic (relevant species) information. When using simulated data, although the overall performance of random forests and artificial neural networks was better than linear discriminant analysis and multiple logistic regression, linear discriminant analysis and multiple logistic regression had relatively good and stable model sensitivity at different sample size and detection limit levels, which may be useful for predicting species presences when data are limited. Random forests performed consistently well at different sample size levels, but was more sensitive to high detection limit. The performance of artificial neural networks was affected by both sample size and detection limit, and it was more sensitive to small sample size.

When we develop and use species distribution models to predict species' current or potential distributions, we are faced with the trade-offs between model generality, precision, and realism. It is important to know how to improve and validate model generality while maintaining good model precision and realism. However, it is difficult for ecologists to evaluate species distribution models using field-sampled data alone because the true species response function to environmental or ecological factors is unknown. Species distribution models should be able to approximate the true characteristics and distributions of species if ecologists want to use them as reliable tools. Simulated data provide the advantage of being able to know the true species-environment relationships and control the causal factors of interest to obtain insights into the effects of these factors on model performance. I used a case study on Bythotrephes longimanus distributions from several hundred Ontario lakes and a simulation study to explore the effects on model performance caused by several factors: the choice of predictor variables, the model evaluation methods, the quantity and quality of the data used for developing models, and the strengths and weaknesses of different species distribution models. Linear discriminant analysis, multiple logistic regression, random forests, and artificial neural networks were compared in both studies. Results based on field data sampled from lakes indicated that the predictive performance of the four models was more variable when developed on abiotic (physical and chemical) conditions alone, whereas the generality of these models improved when including biotic (relevant species) information. When using simulated data, although the overall performance of random forests and artificial neural networks was better than linear discriminant analysis and multiple logistic regression, linear discriminant analysis and multiple logistic regression had relatively good and stable model sensitivity at different sample size and detection limit levels, which may be useful for predicting species presences when data are limited. Random forests performed consistently well at different sample size levels, but was more sensitive to high detection limit. The performance of artificial neural networks was affected by both sample size and detection limit, and it was more sensitive to small sample size.

?rea de concentra??o: Manejo florestal e silvicultura. / Submitted by Jos? Henrique Henrique (jose.neves@ufvjm.edu.br) on 2017-06-09T22:52:32Z No. of bitstreams: 2 talles_hudson_souza_lacerda.pdf: 1852089 bytes, checksum: 5f25d81aee4d02d93913bfc83196ecb3 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Rodrigo Martins Cruz (rodrigo.cruz@ufvjm.edu.br) on 2017-06-14T19:22:36Z (GMT) No. of bitstreams: 2 talles_hudson_souza_lacerda.pdf: 1852089 bytes, checksum: 5f25d81aee4d02d93913bfc83196ecb3 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-06-14T19:22:36Z (GMT). No. of bitstreams: 2 talles_hudson_souza_lacerda.pdf: 1852089 bytes, checksum: 5f25d81aee4d02d93913bfc83196ecb3 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / O objetivo desse trabalho foi avaliar, do ponto de vista estat?stico e biol?gico, simula??es realizadas por dois modelos de distribui??o diam?trica, ajustados pelos m?todos de aproxima??o linear e m?xima verossimilhan?a, em planta??es de eucalipto submetidos a desbaste. Os dados foram provenientes de um povoamento h?brido de Eucalyptus grandis x Eucalyptus urophylla, sob regime de desbaste, localizado no nordeste da Bahia, vinculados ? empresa BAHIA SPECIALTY CELLULOSE. Os dados utilizados neste estudo foram obtidos nas idades 27, 40, 50, 61, 76, 87, 101, 112, 122, 137, 147, 158 e 165 meses. Esse povoamento foi submetido a tratamentos de remo??o seletiva de 20%, 35% e 50%, nas idades 58 e 142 meses. Utilizou-se dois modelos de distribui??o diam?trica, empregando bases de dados observadas aos 27 meses (antes do primeiro desbaste), aos 61 meses (ap?s o primeiro desbaste) e aos 147 meses (ap?s o segundo desbaste). Por meio dos modelos gerou-se tr?s sistemas, os quais se diferiram no m?todo de ajuste da fun??o Weibull. No sistema 1 os par?metros da fun??o Weibull foram ajustados pelo m?todo de aproxima??o linear. No sistema 2 e no sistema 3, os par?metros foram ajustados pelo m?todo da m?xima verossimilhan?a. As proje??es realizadas pelos sistemas foram confrontadas com as distribui??es diam?tricas observadas, por meio do teste de ader?ncia Kolmogorov-Smirnov a 1% de signific?ncia, e pelo teste F de Graybill, com n?vel de signific?ncia de 5%. Os tr?s sistemas proporcionaram distribui??es diam?tricas projetadas estatisticamente semelhantes ?s observadas, antes e ap?s o desbastes. O sistema 2 apresentou um maior percentual de proje??es n?o significativas para os dois testes estat?sticos empregados. As simula??es realizadas pelos modelos apresentaram realismo estat?stico e tend?ncia do crescimento da distribui??o de di?metros para diferentes porcentagens de desbaste. Houve maior efici?ncia dos modelos ao se utilizar distribui??es diam?tricas observadas em idades imediatamente antes do desbaste. As proje??es das distribui??es diam?tricas, empregando-se como base inicial as distribui??es observadas antes do primeiro desbaste e imediatamente ap?s os desbastes (simula??es 1, 2 e 3), foram mais precisas do que as proje??es obtidas quando foram utilizadas somente as distribui??es diam?tricas observadas antes do primeiro desbaste como base inicial para as proje??es e, em seguida, simulados os desbastes nas idades previstas e, por ?ltimo, realizadas as proje??es empregando-se a distribui??o estimada remanescente do desbaste como base inicial para projetar as distribui??es para idades subsequentes (simula??es 4, 5 e 6). / Disserta??o (Mestrado) ? Programa de P?s-Gradua??o em Ci?ncia Florestal, Universidade Federal dos Vales do Jequitinhonha e Mucuri, 2017. / The objective of the study was evaluated from the statistical and biological point of view, simulations performed by two models of diametric distribution, adjusted by linear approximation and maximum likelihood methods, in eucalyptus plantations submitted to thinning. The data were found in a hybrid settlement of Eucalyptus grandis x Eucalyptus urophylla, under thinning regime, located in the northeast region of Bahia, linked to the company BAHIA ESPECIALIDADE CELULOSE. The data used in this study 27, 40, 50, 61, 76, 87, 101, 112, 122, 137, 147, 158 and 165 months. This population was submitted to treatments of selective removal of 20%, 35% and 50%, in the ages 58 and 142 months. Two diametric distribution models were used, using data bases observed at 27 months (before the first thinning), at 61 months (after the first thinning) and at 147 months (after the second thinning). By means of the models three systems were generated, the channels did not differ any method of adjustment of the Weibull function. No system 1 of the Weibull function parameters were adjusted by the linear approximation method. In system 2 and in system 3 the parameters were adjusted by the maximum likelihood method. As the projections performed by the systems were compared with the observed diametric distributions, using the Kolmogorov-Smirnov test at 1% significance, by the Graybill F test, with a significance level of 5%. The three systems provided by the statistically projected diametric distributions for observations, before and after the deviations. System 2 presents a higher percentage of nonsignificant projections for the two statistical tests used. As simulations of model execution demonstrated statistical realism and tendency of growth of the distribution of diameters for different percentages of thinning. There was greater efficiency of the models of use of diametric distributions observed in ages before thinning. As the projections of the diametric distributions, using as an initial basis as distributions observed before the first thinning and after the slabs (simulations 1, 2 and 3), were more accurate than the projections obtained when only diametric distributions observed before the first Thinning as the initial basis for the projections and then simulated the lagging at the predicted ages and finally performed as projections using an estimated remnant distribution of the thinning as the initial basis for designing as distributions for subsequent ages (simulations 4, 5 and 6).