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En écologie, dans le cadre par exemple d’études des services fournis par les écosystèmes, les modélisations descriptive, explicative et prédictive ont toutes trois leur place distincte. Certaines situations bien précises requièrent soit l’un soit l’autre de ces types de modélisation ; le bon choix s’impose afin de pouvoir faire du modèle un usage conforme aux objectifs de l’étude. Dans le cadre de ce travail, nous explorons dans un premier temps le pouvoir explicatif de l’arbre de régression multivariable (ARM). Cette méthode de modélisation est basée sur un algorithme récursif de bipartition et une méthode de rééchantillonage permettant l’élagage du modèle final, qui est un arbre, afin d’obtenir le modèle produisant les meilleures prédictions. Cette analyse asymétrique à deux tableaux permet l’obtention de groupes homogènes d’objets du tableau réponse, les divisions entre les groupes correspondant à des points de coupure des variables du tableau explicatif marquant les changements les plus abrupts de la réponse. Nous démontrons qu’afin de calculer le pouvoir explicatif de l’ARM, on doit définir un coefficient de détermination ajusté dans lequel les degrés de liberté du modèle sont estimés à l’aide d’un algorithme. Cette estimation du coefficient de détermination de la population est pratiquement non biaisée. Puisque l’ARM sous-tend des prémisses de discontinuité alors que l’analyse canonique de redondance (ACR) modélise des gradients linéaires continus, la comparaison de leur pouvoir explicatif respectif permet entre autres de distinguer quel type de patron la réponse suit en fonction des variables explicatives. La comparaison du pouvoir explicatif entre l’ACR et l’ARM a été motivée par l’utilisation extensive de l’ACR afin d’étudier la diversité bêta. Toujours dans une optique explicative, nous définissons une nouvelle procédure appelée l’arbre de régression multivariable en cascade (ARMC) qui permet de construire un modèle tout en imposant un ordre hiérarchique aux hypothèses à l’étude. Cette nouvelle procédure permet d’entreprendre l’étude de l’effet hiérarchisé de deux jeux de variables explicatives, principal et subordonné, puis de calculer leur pouvoir explicatif. L’interprétation du modèle final se fait comme dans une MANOVA hiérarchique. On peut trouver dans les résultats de cette analyse des informations supplémentaires quant aux liens qui existent entre la réponse et les variables explicatives, par exemple des interactions entres les deux jeux explicatifs qui n’étaient pas mises en évidence par l’analyse ARM usuelle. D’autre part, on étudie le pouvoir prédictif des modèles linéaires généralisés en modélisant la biomasse de différentes espèces d’arbre tropicaux en fonction de certaines de leurs mesures allométriques. Plus particulièrement, nous examinons la capacité des structures d’erreur gaussienne et gamma à fournir les prédictions les plus précises. Nous montrons que pour une espèce en particulier, le pouvoir prédictif d’un modèle faisant usage de la structure d’erreur gamma est supérieur. Cette étude s’insère dans un cadre pratique et se veut un exemple pour les gestionnaires voulant estimer précisément la capture du carbone par des plantations d’arbres tropicaux. Nos conclusions pourraient faire partie intégrante d’un programme de réduction des émissions de carbone par les changements d’utilisation des terres. / In ecology, in ecosystem services studies for example, descriptive, explanatory and predictive modelling all have relevance in different situations. Precise circumstances may require one or the other type of modelling; it is important to choose the method properly to insure that the final model fits the study’s goal. In this thesis, we first explore the explanatory power of the multivariate regression tree (MRT). This modelling technique is based on a recursive bipartitionning algorithm. The tree is fully grown by successive bipartitions and then it is pruned by resampling in order to reveal the tree providing the best predictions. This asymmetric analysis of two tables produces homogeneous groups in terms of the response that are constrained by splitting levels in the values of some of the most important explanatory variables. We show that to calculate the explanatory power of an MRT, an appropriate adjusted coefficient of determination must include an estimation of the degrees of freedom of the MRT model through an algorithm. This estimation of the population coefficient of determination is practically unbiased. Since MRT is based upon discontinuity premises whereas canonical redundancy analysis (RDA) models continuous linear gradients, the comparison of their explanatory powers enables one to distinguish between those two patterns of species distributions along the explanatory variables. The extensive use of RDA for the study of beta diversity motivated the comparison between its explanatory power and that of MRT. In an explanatory perspective again, we define a new procedure called a cascade of multivariate regression trees (CMRT). This procedure provides the possibility of computing an MRT model where an order is imposed to nested explanatory hypotheses. CMRT provides a framework to study the exclusive effect of a main and a subordinate set of explanatory variables by calculating their explanatory powers. The interpretation of the final model is done as in nested MANOVA. New information may arise from this analysis about the relationship between the response and the explanatory variables, for example interaction effects between the two explanatory data sets that were not evidenced by the usual MRT model. On the other hand, we study the predictive power of generalized linear models (GLM) to predict individual tropical tree biomass as a function of allometric shape variables. Particularly, we examine the capacity of gaussian and gamma error structures to provide the most precise predictions. We show that for a particular species, gamma error structure is superior in terms of predictive power. This study is part of a practical framework; it is meant to be used as a tool for managers who need to precisely estimate the amount of carbon recaptured by tropical tree plantations. Our conclusions could be integrated within a program of carbon emission reduction by land use changes.

Orientador: Alexandre Magno Sebbenn / Resumo: Cariniana estrellensis e Cariniana legalis são uma das maiores árvores dos biomas florestais da Amazônia e Mata Atlântica, sendo atualmente vulneráveis à extinção devido ao intenso desmatamento desses biomas. Estratégias para conservação in situ e ex situ são urgentes e estudos de diversidade genética e fluxo de genes são chaves e para esses propósitos. Assim, investigamos a diversidade genética, a estrutura genética espacial (SGS) e o fluxo histórico de genes em populações fragmentadas de ambas as espécies, utilizando marcadores de microssatélites. Todas as árvores encontradas nas populações foram mapeadas, medidas para o diâmetro na altura do peito (DAP) e amostrado o cambio de casca. O índice de fixação (F), em alguns casos, foi significativamente maior em árvores com menor DAP, indicando que as árvores menores apresentam um maior parentesco do que as maiores. Foi detectada SGS significativa para populações de ambas as espécies (60-350 m), indicando um padrão de dispersão de genes de isolamento pela distância (IBD). Para ambas as espécies, foi observada alta imigração de semente (38,5-61,5%) e pólen (80,1-100%), mostrando que as populações não são isoladas geneticamente. Não foi detectada autofecundação, mas o cruzamento entre árvores relacionadas foi detectado nas espécies (8,9-12,5%), sugerindo uma seleção mais forte contra árvores de autofecundação do que se originou do cruzamento entre árvores relacionadas. A distância de dispersão de pólen e sementes em C. estrellensi... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Cariniana estrellensis and Cariniana legalis, two of the largest trees in the Amazon and Atlantic Forest biomes, are currently vulnerable to extinction due to the intense deforestation of these biomes. Strategies for in and ex situ conservation are urgent, and studies of genetic diversity and gene flow are key aspects needed to develop these strategeis. Thus, we investigate the genetic diversity, spatial genetic structure (SGS), and historical gene flow in fragmented populations of both species, using microsatellite markers. All trees found in the study populations were mapped, measured for diameter at breast height (DBH), and sampled for bark cambium. Our results show that in some cases, fixation index (F) was significantly higher in trees with lower DBH, indicating that smaller trees have higher levels of inbreeding than larger ones. Significant SGS was detected in populations of both species (60-350 m), indicating a gene dispersal pattern of isolation by distance (IBD). For both species, we found high seed (38.5-61.5%) and pollen (80.1-100%) immigration demonstrating that populations are not genetically isolated. No self-fertilization was detected, but we did find evidence of mating among related trees (8.9-12.5%), suggesting stronger selection against selfed individuals than those originated from mating among relatives. Pollen and seed dispersal distance for C. estrellensis reached longer distances (> 3 km) than for C. legalis (maximum of 385 m). However, pollen and seeds... (Complete abstract click electronic access below) / Doutor

Submitted by FRANCINE BEATRIZ DE SOUZA null (francinnysouza@yahoo.com.br) on 2018-03-25T19:33:25Z No. of bitstreams: 1 Francine__Tese_VersãoFinal_2018.pdf: 1284636 bytes, checksum: 8130187eea228723fe2e75938a47a468 (MD5) / Approved for entry into archive by Cristina Alexandra de Godoy null (cristina@adm.feis.unesp.br) on 2018-03-26T12:25:02Z (GMT) No. of bitstreams: 1 souza_fb_dr_ilha.pdf: 1284636 bytes, checksum: 8130187eea228723fe2e75938a47a468 (MD5) / Made available in DSpace on 2018-03-26T12:25:03Z (GMT). No. of bitstreams: 1 souza_fb_dr_ilha.pdf: 1284636 bytes, checksum: 8130187eea228723fe2e75938a47a468 (MD5) Previous issue date: 2018-02-09 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Cariniana estrellensis e Cariniana legalis são uma das maiores árvores dos biomas florestais da Amazônia e Mata Atlântica, sendo atualmente vulneráveis à extinção devido ao intenso desmatamento desses biomas. Estratégias para conservação in situ e ex situ são urgentes e estudos de diversidade genética e fluxo de genes são chaves e para esses propósitos. Assim, investigamos a diversidade genética, a estrutura genética espacial (SGS) e o fluxo histórico de genes em populações fragmentadas de ambas as espécies, utilizando marcadores de microssatélites. Todas as árvores encontradas nas populações foram mapeadas, medidas para o diâmetro na altura do peito (DAP) e amostrado o cambio de casca. O índice de fixação (F), em alguns casos, foi significativamente maior em árvores com menor DAP, indicando que as árvores menores apresentam um maior parentesco do que as maiores. Foi detectada SGS significativa para populações de ambas as espécies (60-350 m), indicando um padrão de dispersão de genes de isolamento pela distância (IBD). Para ambas as espécies, foi observada alta imigração de semente (38,5-61,5%) e pólen (80,1-100%), mostrando que as populações não são isoladas geneticamente. Não foi detectada autofecundação, mas o cruzamento entre árvores relacionadas foi detectado nas espécies (8,9-12,5%), sugerindo uma seleção mais forte contra árvores de autofecundação do que se originou do cruzamento entre árvores relacionadas. A distância de dispersão de pólen e sementes em C. estrellensis atingiu longa distância (> 3 km) do que em C. legalis (máximo de 385 m). No entanto, o pólen e as sementes em C. estrellensis e o pólen em C. legalis foram dispersos em um padrão de IBD. Os resultados sugerem que as populações estudadas são adequadas para conservação in situ e ex situ. / Cariniana estrellensis and Cariniana legalis, two of the largest trees in the Amazon and Atlantic Forest biomes, are currently vulnerable to extinction due to the intense deforestation of these biomes. Strategies for in and ex situ conservation are urgent, and studies of genetic diversity and gene flow are key aspects needed to develop these strategeis. Thus, we investigate the genetic diversity, spatial genetic structure (SGS), and historical gene flow in fragmented populations of both species, using microsatellite markers. All trees found in the study populations were mapped, measured for diameter at breast height (DBH), and sampled for bark cambium. Our results show that in some cases, fixation index (F) was significantly higher in trees with lower DBH, indicating that smaller trees have higher levels of inbreeding than larger ones. Significant SGS was detected in populations of both species (60-350 m), indicating a gene dispersal pattern of isolation by distance (IBD). For both species, we found high seed (38.5-61.5%) and pollen (80.1-100%) immigration demonstrating that populations are not genetically isolated. No self-fertilization was detected, but we did find evidence of mating among related trees (8.9-12.5%), suggesting stronger selection against selfed individuals than those originated from mating among relatives. Pollen and seed dispersal distance for C. estrellensis reached longer distances (> 3 km) than for C. legalis (maximum of 385 m). However, pollen and seeds of C. estrellensis and pollen of C. legalis were dispersed in an IBD pattern. The results suggest that the studied populations are suitable for in and ex situ conservation.