The ecological interrelationships between the habitat composition, habitat quality and abundance of three wild ungulate species, viz. Chital (Axis axis), Sambar (Cervus unicolor) and Nilgai (Boselaphus tragocamelus) were investigated in three National Parks in India. The study sites differ in the structure and composition of the habitat and also occur along a rainfall gradient. The study incorporates a new approach of using forest compartments for gathering baseline ecological data. The significance of these compartments in serving as ecological bench-marks for monitoring habitat condition has been demonstrated. Toe-point transect, a modification of the point-intercept method has been extensively used to obtain rapid, reliable but coarse ecological data on ground and aerial cover and the results obtained are compared with those from the visual estimation method. Motorcycle and foot-based line transects have been used to obtain data on animal abundance. The significance of the results indicating that motorcycle transects are an efficient and reliable means of estimating the abundance of Chital and Nilgai, while foot transects provide more reliable estimates of Sambar abundance is discussed. Data on 22 habitat variables were gathered in the summer and winter seasons from all the study sites and were statistically analysed using Generalized Linear Interactive Modelling (GLIM) procedures. The habitat requirements of the three ungulate species have been determined, which enhance our understanding of the complex herbivore-habitat relationships. Analyses of habitat selection, central to the understanding of animal ecology, has been done to understand the mechanisms which permit species to co-exist. The results indicate that the three species are ecologically separated and that resource partitioning is achieved primarily by habitat partitioning. Sambar, a forest ungulate, largely occurs in the forest-woodland habitats; Chital, a species of the habitat 'edge', occurs in the woodland-grassland habitats while Nilgai prefers the miscellaneousopen and grassland habitats. The three ungulate species together contribute more than 78% to the total wild ungulate biomass. This is presumably because these species are by nature generalist and are able to exploit the unpredictable resources more efficiently than specialist species. The differential biomass/rainfall relationships of three species observed in the study have been explained on the basis of habitat requirements and feeding strategies adopted by these species. The ecological biogeography of the three ungulate species has been discussed and their ecological equivalents in Africa have been examined. The significance of above in enhancing our understanding of evolutionary biology is discussed. The study has shown that habitat composition is an all-important factor in large herbivore biology and that animal density may be used as an indicator of habitat quality.

Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. Understanding the nature of functional relationships (such as prey-predator) between species is important for building predictive models. However, modelling the interactions with external stressors over time and space is also essential for ecosystem-based approaches to fisheries management. With the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, fewer assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data and combined with existing knowledge. In this thesis, we explore Bayesian network modelling approaches, accounting for latent effects to reveal species dynamics within geographically different marine ecosystems. First, we introduce the concept of functional equivalence between different fish species and generalise trophic structure from different marine ecosystems in order to predict influence from natural and anthropogenic sources. The importance of a hidden variable in fish community change studies of this nature was acknowledged because it allows causes of change which are not purely found within the constrained model structure. Then, a functional network modelling approach was developed for the region of North Sea that takes into consideration unmeasured latent effects and spatial autocorrelation to model species interactions and associations with external factors such as climate and fisheries exploitation. The proposed model was able to produce novel insights on the ecosystem's dynamics and ecological interactions mainly because it accounts for the heterogeneous nature of the driving factors within spatially differentiated areas and their changes over time. Finally, a modified version of this dynamic Bayesian network model was used to predict the response of different ecosystem components to change in anthropogenic and environmental factors. Through the development of fisheries catch, temperature and productivity scenarios, we explore the future of different fish and zooplankton species and examine what trends of fisheries exploitation and environmental change are potentially beneficial in terms of ecological stability and resilience. Thus, we were able to provide a new data-driven modelling approach which might be beneficial to give strategic advice on potential response of the system to pressure.

Orientador: João Frederico da Costa Azevedo Meyer / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica / Made available in DSpace on 2018-08-24T22:34:38Z (GMT). No. of bitstreams: 1 Souza_JulianaMartaRodriguesde_D.pdf: 3368514 bytes, checksum: 4eec6362766752b87c0db7caebbeec84 (MD5) Previous issue date: 2014 / Resumo: O objetivo cumprido por esta tese é a criação e validação de uma técnica de recuperação de coeficientes de difusão para problemas ecológicos. O trabalho consta de oito capítulos e três deles são dedicados às ferramentas necessárias para a geração de dados sabidamente difusivos ou para o ajuste dos dados. Para a geração de dados trabalha-se com a obtenção da solução numérica de um problema difusivo tipicamente ecológico, combinando Elementos Finitos, Método de Galerkin e Crank-Nicolson. A seguir embasado-se no conceito de função densidade de probabilidade e em função de distribuição acumulada, lança-se mão do Método da Transformada Inversa. O Capítulo dedicado aos ajustes figura do trabalho para apresentar, ao leitor que ainda não havia tido contato, uma aplicação de um Algoritmo Genético. Tal algoritmo é usado para obter a solução de Quadrados Mínimos não-lineares em três parâmetros. A Regressão Linear tradicional, contando com apenas um parâmetro a ser ajustado também é utilizada. O principal conteúdo, o desenvolvimento do modelo e os resultados, excelentes, compõem mais dois Capítulos, o quinto e o sétimo, que, somados à Introdução, discussão sobre a bibliografia e Conclusão, fecham o trabalho. Discorre-se amplamente sobre o tipo de dado relativo a problemas ecológicos, e dificuldades inerentes, e sobre como o conhecimento sobre esse tipo de dados é fundamental no {\itshape design} do modelo. A cada passo dado, ferramenta desenvolvida ou introduzida, sua qualidade é atestada a fim de que, ao fim, a estrutura tenha sido construída sobre uma base sólida. O método recupera com sucesso coeficientes de difusão dentro de todo o espectro analisado, entre 0.0001 e 1 unidades de espaço ao quadrado por tempo; sendo possível tratar os dados de modo que a possibilidade de erro seja direcionada para uma hiper-estimativa, o que pode ser uma atitude previdente a depender do problema / Abstract: The goal attained by this thesis is the creation and validation of a diffusion coefficient, relative to ecological problems, recovery technique. Eight Chapters constitutes this work and three of them are dedicated to the tools needed for the diffusive related data generation or to the data fit. For the data generation, the numerical solution of a tipically ecological diffusive problem is obtained by combining Finite Elements, Galerkin's Method and Crank-Nicolson. Then, relying on the concepts of probability density function and cumulative distribution function, the Inverse Transform Method is applied. There is a Chapter dedicated to the fitting methods used here to introduce, to a reader who have not had the pleasure of meeting before, an application of a Genetic Algorithm. Such algorithm is used to obtain a non-linear Least Squares three parameter solution. The traditional Linear Regression is also used for fitting another version of the model. The main content, the development of the model and the excellent results compose two more Chapters, the fifth and the seventh that, when gathered to the Introduction, discussion about the bibliography and the Conclusion, closes the work. The kind of data related to ecological problems and the difficulties inherent to it are a main concern and deeply discussed. It is also focus of intense attention how the knowledge on this kind of data is fundamental for the method design. At each step, tool developed or introduced, its quality is attested with the purpose that, by the end of the work, the structure has been built on a solid basis. The method recovers succesfully diffusion coeficients with all the range analyzed, 0.0001 and 1 units of squared space over time; and it is also possible to determine the treatment for the data in such a way that error are directed to a hiper-estimative; that might be provident attitude depending on the problem / Doutorado / Matematica Aplicada / Doutora em Matemática Aplicada

<p>  </p> <p>The rise of technology as a data source for ecological research and biodiversity conservation has led to a host of new opportunities, and new challenges, for researchers, conservationists, policymakers, and land managers. As these technologies have become more common and more capable, researchers need improved methods and improved theoretical frameworks to integrate these technologies with each other; with social science and policy; and with land-use planning. This thesis proposes several of these conceptual and theoretical frameworks—one for integration of heterogeneous data and another for the integration of ecological data with economic decision-making and policy analysis. It then suggests new methodologies for data quality assurance. Lastly, it demonstrates the applicability of acoustic monitoring in a key land-use context: agriculture in a premium crop that is grown in global biodiversity hotspots. </p>