archives@tulane.edu / 1 / Peter Tellez

L'évolution adaptative contribue probablement à l'adaptation des populations à des changements environnementaux rapides, l'observation empirique de nombreux cas d'évolution rapide dans les populations naturelles suivant de forts changements environnementaux abondant en ce sens. Dans cette thèse, je me suis concentrée sur l'estimation du potentiel évolutif d'une population naturelle de hêtre commun (Fagus sylvatica), une espèce à long cycle de vie, subissant des stress hydriques chroniques. Je considère ici une définition du potentiel évolutif dans le sens strict de la capacité d'une population à évoluer ; c'est donc un paramètre directement lié au taux d'évolution futur de la population considérée. Cette thèse a pour but d'apporter des éléments manquants concernant l'étude de l'adaptation chez les arbres, le rôle de l'évolution adaptative dans la capacité des arbres à composer avec les changements environnementaux futurs étant encore largement méconnu.La population étudiée montre un potentiel évolutif important, imputable à divers traits (principalement la phénologie du débourrement végétatif, et le Delta13C) qui présentent une diversité génétique élevée, sont soumis à une forte pression de sélection, et contribuent significativement à la valeur adaptative. Cette thèse appuie donc l'hypothèse selon laquelle l'évolution adaptative jouera un rôle important dans l'adaptation des arbres aux changements environnementaux futurs. Le rôle de la dispersion demeure incertain du fait d'une dispersion du pollen et des graines restreinte, mais également d'indices d'évènements de dispersion à longue distances favorisés par la présence de mortalité densité dépendante. / Adaptive evolution may promote populations' adaptation to rapid environmental changes which is sustained by recurrent empirical demonstrations of rapid adaptive evolution in the wild consecutively to strong environmental changes. In this PhD, I focused on the estimation of the in-situ evolutionary potential of a wild European beech (Fagus sylvatica) population, a long-lived tree species, undergoing chronic water stresses. I here considered the evolutionary potential in the strict sense of “evolvability” i.e. the ability of population to evolve; this parameter is thus directly linked to the rate of future adaptive evolution. This PhD aimed to fill a gap in tree adaptation studies, the role of adaptive evolution in tree populations' ability to cope with future environmental changes remaining largely unresolved.The studied a population displayed a high evolutionary potential because of a strong in-natura genetic variability of some traits and the relevance of these traits in trees adaptation, this PhD support the hypothesis that adaptive evolution is likely to play a key role in trees adaptation to future environmental changes. The role of dispersal remains unclear with apparently very restricted seed and pollen dispersal but also clues of long dispersal events promoted by the occurrence of density-dependent mortality.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2018-04-09T12:04:41Z No. of bitstreams: 2 Dissertação - Oscar Daniel Plazas Jiménez - 2018.pdf: 5372786 bytes, checksum: ccb044675f67ad084ee0892aa9c09bae (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-04-09T12:42:46Z (GMT) No. of bitstreams: 2 Dissertação - Oscar Daniel Plazas Jiménez - 2018.pdf: 5372786 bytes, checksum: ccb044675f67ad084ee0892aa9c09bae (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-04-09T12:42:46Z (GMT). No. of bitstreams: 2 Dissertação - Oscar Daniel Plazas Jiménez - 2018.pdf: 5372786 bytes, checksum: ccb044675f67ad084ee0892aa9c09bae (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-03-06 / Theoretical and empirical evidence suggest that the mass ratio and the niche complementarity hypothesis are able to explain how species trait composition drives decomposition, an ecosystem process related with nutrient cycling and carbon sequestration. These two hypotheses are respectively related with the mean trait values of individuals present in a given community and its variance. Thus, it is impossible to test them adequately without experiments planned to approach these two aspects simultaneously. Although leaf functional traits influence decomposition process, an experimental design made to disentangle the unique, combined and strength of effects of the mechanisms proposed by MRH and NCH on decomposition should use leaf functional traits as predictors, but this has not yet been done. Here, we used two leaf nutritional traits (leaf nitrogen and magnesium-calcium content) and one structural trait (specific leaf area; SLA) from 20 species of seasonal dry forest to simulate leaf mixtures with different mean trait values (calculated as community-weighted mean; CWM) and variation of trait values (functional diversity; FD). For each trait, 40 leaf mixtures with different quasi-orthogonal combinations of CWM and FD were selected and left in the field to decompose for six months. We found that MRH mechanisms exert predominant role on decomposition where low and high CWM values were related with high biomass loss. Then, this add more evidence to support that the mean trait values of leaf mixtures are the main drivers of biomass loss. Contrary to previously evidences, trait complementarity does not increase efficiency and instead, an increasing in niche complementarity (high FD values) was followed by a decreasing in biomass loss efficiency. So, this question the importance of mechanism behind NCH on leaf decomposition. Additionally, we found that whereas nutritional traits were able to predict leaf decomposition, structural traits were not, in opposite to what is reported in the literature. Our results highlight that the mean resources quality of the leaf mixtures is the main driver of biomass loss and trait complementarity does not increase efficiency of biomass loss. Due to this, we proposed that in future studies mean resources quality of the leaf mixtures will be use as parameter to test and predict the possible impacts of human-induced changes on nutrient cycling and carbon sequestration. / Evidências empíricas e teóricas sugerem que os mecanismos propostos pelas hipóteses da razão da massa e da complementaridade de nicho (HRM e HCN respectivamente) são capazes de explicar como a composição de atributos funcionais das espécies determina a decomposição, um importante processo ecossistêmico relacionado com a ciclagem de nutrientes e o sequestro de carbono. Essas duas hipóteses estão relacionadas, respectivamente, com o valor médio dos atributos das espécies presentes em uma dada assembleia ou com a sua variação. Portanto, é impossível testar adequadamente essas duas hipóteses sem experimentos planejados para abordar simultaneamente esses dois aspectos, algo que é raramente feito. Os atributos funcionais foliares apresentam forte efeito nas taxas de decomposição em ecossistemas terrestres. Assim, um desenho experimental feito para separar a magnitude relativa dos efeitos únicos e combinados da HRM e HCN sobre a decomposição de folhas deve usar atributos foliares como preditores, mas até agora isso não foi feito. Neste trabalho, simulamos misturas de folhas com diferentes valores médios ponderados pela abundância (i.e., community weighted mean, CWM) de atributos e dispersão (i.e., functional diversity; FD) destes valores para dois atributos foliares nutricionais (conteúdo de nitrogênio e conteúdo de magnésio e cálcio) e um atributo estrutural (área foliar específica; SLA) quantificados para 20 espécies de floresta estacional semidecídua. Para cada atributo, selecionamos 40 misturas de folhas com diferentes combinações quase-ortogonais de CWM e FD que posteriormente foram deixadas durante seis meses no campo para decompor. No geral, encontramos que os mecanismos propostos pela HRM têm um papel predominante na decomposição, porque altos e baixos valores de CWM estiveram relacionados com uma alta perda de biomassa. Isso adiciona mais evidência à que os valores médios dos atributos das misturas de folhas são os principais determinantes da perda de biomassa. Porém, diferente do esperado, o aumento da complementaridade dos atributos das misturas de folhas (isto é, altos 8 valores de FD) levou à uma diminuição da eficiência da perda de biomassa e não à um aumento, como era esperado. Isso coloca em questão a importância dos mecanismos propostos pela HCN na decomposição de folhas. Adicionalmente, encontramos que os atributos nutricionais foliares foram capazes de predizer a perda de biomassa enquanto que, ao contrário do reportado na literatura, o atributo estrutural SLA não teve qualquer relação com a decomposição. Nossos resultados destacam que em misturas de folhas os valores médios do conteúdo de nutrientes estão associados com as taxas de decomposição e a complementaridade dos atributos não incrementou a eficiência na perda de biomassa. Portanto, nós propomos que em estudos futuros os valores médios do conteúdo de nutrientes das misturas de folhas sejam usados como parâmetros para testar e predizer os possíveis efeitos das mudanças na biodiversidade induzidos pelo homem sobre a ciclagem de nutrientes e o sequestro de carbono

<p dir="ltr">Reflectance spectroscopy has been increasingly used in forestry due to its ability to rapidly, efficiently, and non-destructively detect tree stress, enabling timely and cost-effective forest management decisions. This dissertation synthesizes three studies and five experiments to understand and improve our ability to use spectral data to estimate a variety of foliar physiochemical traits and identify spectral responses in multi-stress environments, thus, advancing our understanding and application of hyperspectral data in forest management.</p><p dir="ltr">The first study seeks to refine the hyperspectral approach to monitoring tree stress by selecting optimal wavelength ranges to enhance the estimation of foliar traits, such as CO₂ assimilation rate, specific leaf area, leaf water content, and concentrations of foliar nitrogen, sugars, and gallic acid. The study revealed that model performance varied significantly across the different wavelength ranges tested and consistently, including longer wavelength regions improved trait estimation for all traits modeled. This research also established a framework for discovering novel or previously unknown absorption features associated with functional traits, thereby laying the groundwork for expanded spectral applications. This advancement enables the estimation of diverse foliar traits and facilitates detailed stress detection in trees.</p><p dir="ltr">The second study focuses on assessing the effectiveness of hyperspectral data in estimating foliar functional trait responses to various biotic and abiotic stressors and to differentiate those stressors in black walnut (<i>Juglans nigra </i>L.) and red oak (<i>Quercus rubra</i> L.) seedlings. We demonstrated that spectral data can reliably estimate a wide range of foliar traits, highlighting its potential as a surrogate for reference data in understanding plant responses to stress. This research revealed that spectral leaf predictions can effectively provide stress-specific insights into tree physiochemical responses to biotic and abiotic stressors.</p><p dir="ltr">The third study explores the application of hyperspectral reflectance to identify drought-induced foliar responses in black walnut seedlings during their initial field establishment. Chemometric models developed from greenhouse experiments were applied to spectral data collected in the field to assess their transferability and accuracy in predicting various leaf traits under drought stress. Using only spectral data, we demonstrated that seedlings show distinct spectral responses to past and ongoing drought stress, with varying degrees depending on seed provenances. This research aims to provide practical insights for utilizing spectral analysis in real-world conditions and understanding the challenges of using spectral tools in the field.</p><p dir="ltr">Collectively, this dissertation demonstrates the robust potential of hyperspectral reflectance technology in advancing the monitoring of tree health. By optimizing spectral range selection, reliably estimating tree foliar traits under stress conditions, differentiating various stressors in controlled environments, and effectively detecting current and past drought stress in field conditions, this research offers valuable insights for improving forest health monitoring and management strategies in response to environmental challenges.</p>