Cyclura ricordii is an endemic iguana from Hispaniola and is listed as Critically Endangered on the IUCN. The main threats are predation by introduced mammals, habitat destruction and hunting. The present study focused on two nesting areas in Pedernales in the Dominican Republic. The hypothesis tested is that natal philopatry influences dispersal and nest site selection. Monitoring and sampling took place during 2012-2013. Polymorphic markers were used to evaluate whether natal philopatry limits dispersal at multiple spatial scales. Ripley’s K, revealed that nests were significantly clustered. Hierarchical AMOVA revealed that nest site aggregations did not explain a significant portion of genetic variation. However, Mantel’s tests revealed significant positive correlations between genetic and geographic distance. These results indicate that natal philopatry limits dispersal at a course spatial scale, but does not influence nest site selection at a fine spatial scale.

When analyzing ecological data, one considers traditional multivariate techniques to be unsuitable. The use of dissimilarity coefficients and distance matrices is a way, how to solve this problem. In this work we present some of these coefficients and distance-based tests: Mantel test, several versions of ANOSIM and MRPP tests and distance-based test for homogeneity of multivariate dispersions. We focus on relationships among these tests and illustrate the use with an example. We also discuss the difficulties of interpretation of the results of these tests.

Submitted by (ana.araujo@ufrpe.br) on 2016-05-20T12:26:11Z No. of bitstreams: 1 Ana Clara Paixao Campos.pdf: 1515481 bytes, checksum: 29c30eb35f6e7da1f6e63d0971def668 (MD5) / Made available in DSpace on 2016-05-20T12:26:11Z (GMT). No. of bitstreams: 1 Ana Clara Paixao Campos.pdf: 1515481 bytes, checksum: 29c30eb35f6e7da1f6e63d0971def668 (MD5) Previous issue date: 2013-02-02 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Knowing the spatial pattern of patients with genetic disease with physical disabilities in the treatment of Pernambuco AACD is of great importance because it makes it possible to guide the basic care assistance to these individuals and provide solid basis for planning public health policies. However, there are few references in the literature using the tools of spatial analysis in the context of disability. This dissertation was structured in the form of two papers. In the first article the global Moran's I index was used to characterize the spatial pattern of the rate of patients with genetic disease with physical disabilities in the AACD treatment of Pernambuco and the results were compared with those obtained with the randomization test. In both approaches we found the existence of spatial pattern for the rate of patients with genetic disease with physical disabilities in the treatment of Pernambuco AACD when we took into account the rates of four municipalities closest to each location. In the second article we evaluated the performance of the global Moran's I index and the Mantel test with Spearman correlation, both using randomization to assess the statistical significance, regarding the ability to detect spatial pattern for the rate of patients with diseases genetic with physical disabilities in the AACD treatment of Pernambuco. The results showed that the global Moran's I index proved to be a more satisfactory method for detecting the spatial pattern, since it uses the information in its calculations of the neighborhood, and provide greater control of the rejection rates of the null hypothesis under study. / Conhecer o padrão espacial dos portadores de doença genética com deficiência física em tratamento na AACD de Pernambuco é de grande importância, pois torna possível orientar a assistência aos cuidados básicos desses indivíduos e fornecer base sólida para o planejamento de políticas públicas de saúde. Entretanto, existem poucas referências na literatura utilizando o instrumental da análise espacial no contexto da deficiência física. A presente dissertação foi estruturada na forma de dois artigos científicos. No primeiro artigo o Índice I global de Moran foi utilizado para caracterizar o padrão espacial da taxa de pacientes portadores de doença genética com deficiência física em tratamento na AACD de Pernambuco e os resultados encontrados foram comparados com os obtidos através do teste de aleatorização. Em ambas as metodologias constatou-se a existência de padrão espacial agregado para a taxa de pacientes portadores de doença genética com deficiência física em tratamento na AACD de Pernambuco quando se levou em consideração as taxas dos 4 municípios mais próximos de cada localidade. No segundo artigo foi avaliado o desempenho do índice I global de Moran e do teste de Mantel com correlação de Spearman, ambos utilizando aleatorização para avaliar a significância da estatística, no que tange a capacidade de detectar padrão espacial para a taxa de pacientes portadores de doenças genéticas com deficiência física em tratamento na AACD de Pernambuco. Os resultados indicaram que o índice I global de Moran mostrou-se uma metodologia mais satisfatória para detectar do padrão espacial, uma vez que utiliza em seus cálculos as informações da vizinhança, além de proporcionar maior controle das taxas de rejeição da hipótese nula em estudo.

Les distributions d'espèces observées dans un environnement hétérogène résultent de plusieurs processus déterministes et stochastiques agissant comme des filtres pour contraindre la coexistence des espèces. L’action successive de ces processus a pour conséquence directe de structurer spatialement la composition des communautés et la variation de ces compositions (i.e., diversité bêta). Un des objectifs majeurs de l'écologie des communautés et métacommunautés consiste à identifier et quantifier les effets respectifs de ces différents processus sur la diversité bêta des communautés afin de mieux comprendre et prédire la distribution de la biodiversité. L'expérimentation étant difficilement possible, les processus responsables de la variation spatiale de la composition des communautés sont généralement inférés à partir des structures spatiales des distributions d’espèces observées dans la nature. La thèse s’inscrit dans ce contexte et vise à améliorer les outils de statistique multivariée permettant d’identifier et quantifier l'effet des processus écologiques structurant les communautés et métacommunautés. En particulier, il est proposé d’intégrer les échelles écologiques et les modèles nuls contraints pour étudier l’effet de l’environnement. La décomposition des relations trait-environnement dans les échelles spatiales et phylogénétiques permet une étude plus approfondie du filtrage environnemental en associant son échelle spatiale d’action au signal phylogénétique des traits sélectionnés pour capturer l’histoire évolutive associée au filtrage environnemental. L’interprétation en terme de processus évolutifs est néanmoins limitée et mériterait l’intégration de modèles nuls phylogénétiquement contraints pour une analyse plus fine. Dans la continuité, des modèles nuls spatialement contrains ont été développés et intégrés à deux analyses multivariées très largement utilisées en écologie des communautés (i.e., partitionnement de variation et test de Mantel) pour estimer et tester l’effet de l’environnement sur les assemblages d’espèces. Ces deux analyses présentaient une surestimation de leur statistique mesurée ainsi qu’un taux anormal de faux positifs lorsque les distributions d’espèces (via processus de dispersion limitée) et l’environnement étaient indépendamment spatialement structurés. L’intégration de modèles nuls spatialement contraints a permis d’ajuster à la fois les estimations et les tests de ces deux analyses illustrant ainsi le besoin d’utiliser des modèles nuls écologiquement contraints pour une identification et quantification correctes des processus écologiques / Species distributions observed in an heterogeneous environment result from multiple deterministic and stochastic processes acting as filters to constrain species co-existence. As a direct consequence, the successive actions of these processes spatially structure communities composition and the variation of these compositions (i.e., beta-diversity). One of the major objective in community and metacommunity ecology is to identify and quantify the respective effects of these different processes on communities beta-diversity to better understand and predict the distribution of biodiversity. Experiments being hardly possible, processes responsible for the spatial variation of communities composition are generally inferred from spatial patterns of species distributions observed in nature. In this context, the thesis aims at improving multivariate statistical tools conducted to identify and quantify the effects of ecological processes shaping communities and metacommunities. In particular, this thesis proposes to integrate ecological scales and constrained null models to study the effect of environment.Decomposing trait-environment relationships through spatial and phylogenetic scales allows to further study environmental filtering. The association of spatial scales involved in environmental filtering with the phylogenetic signals of traits allowed to capture the evolutive history related to environmental filtering. The interpretation in terms of evolutive processes is however limited and phylogenetically-constrained null models should be considered to improve the analysis. Following on from this work, spatially-constrained null models were developed and integrated into two multivariate analyses widely used in community ecology (i.e., variation partitioning and Mantel tests) to estimate and test the effect of environmental filtering on species assemblages. Both approaches presented overestimation of their computed statistic as well as high rates of false positive when species distributions (via limited dispersal) and environmental conditions were independently spatially structured. Integrating spatially-constrained null models allowed to adjust both their tests and the values of their statistic, as such demonstrating the need of using ecologically-constrained null models to correctly identify and quantify ecological processes.For future works, the thesis suggests that adopting a scaling approach to study ecological processes in addition to mechanistic null models could offer the possibility to distinguish processes from one another