Ítem
Acceso Abierto

Wood strategies in a lowland rainforest of eastern Amazonia

dc.contributorSánchez, Adriana
dc.contributor.advisorPosada Hostettler, Juan Manuel Roberto
dc.contributor.gruplacGrupo de Ecología Funcional y Ecosistémica (EFE)
dc.creatorGonzález Melo, Germán Andrés
dc.creator.degreeDoctor en Ciencias Biomédicas y Biológicas
dc.creator.degreeLevelDoctorado
dc.creator.degreetypeFull time
dc.date.accessioned2023-03-10T19:33:17Z
dc.date.available2023-03-10T19:33:17Z
dc.date.created2023-01-25
dc.descriptionThis thesis consists of six chapters: the general introduction (this chapter), four research chapters (chapters 2-5), and a synthesis chapter (chapter 6). I first focused on WSG and wood anatomical traits (chapter 2), then looked at wood chemical traits (chapter 3), and then combined data on wood traits and species demography to assess the links between traits and demographic rates (chapter 4). Finally, I examined the implications of within-stem variations in WSG on biomass estimations at both the species and stand level (chapter 5). It is well established that wood specific gravity (WSG) can vary substantially from pith to bark (Williamson & Wiemann, 2010), which can reflect ontogenetic shifts in hydraulic, mechanical and storage demands during tree development (Hietz et al., 2013). However, the wood anatomical traits underlying these radial variations in WSG are not well understood, particularly for angiosperm tree species from humid tropical forests. In chapter 2, I used a set of wood functional traits, measured along the stem radial profile, to explain the anatomical drivers of radial shifts in WSG. Wood nutrients are expected to play a central role in tree functioning and life-history variations among woody species (Martin et al., 2014; Heinemann et al., 2016). Yet, very few studies have investigated how wood nutrients are related to other wood functional traits, or how they vary radially within stems, or across species and ecological guilds. In chapter 3, I related wood nutrients (i.e., phosphorous, calcium, potassium and magnesium) to WSG and xylem parenchyma fractions ininner and outer wood, and evaluated nutrient resorption rates at the species and ecological guilds level. One central assumption in trait-based ecology is that traits can predict species demography (Shipley et al., 2016). However, the predictive power of most traits on tree demographic rates is in general low. This pattern may be explained by two reasons: the use of “soft traits”, which might not fully capture some plant functions (Yang et al., 2018), and the lack of consideration of size-related changes in both traits and demographic rates (Iida & Swenson, 2019). In chapter 4, I combined demographic rates (i.e., diameter growth and mortality rates) of trees of different sizes and “hard traits” (i.e., chemical and anatomical traits) measured at different radial positions to explain the associations between wood traits and species demography during tree development. Besides its functional significance, wood specific gravity is also an important predictor of above-ground biomass (AGB) and, consequently, of biomass growth rates (BGR) estimations. Although radial shifts in WSG may have considerable effects on AGB and BGR estimations, at both the species and stand level, most regional and local studies do not consider these possible effects. In chapter 5, I quantified species percentage errors in AGB and BGR estimations that resulted from not taking into account radial trends in WSG, and extrapolated these species percentage errors to the stand level. Finally, in the last chapter (chapter 6), I synthesized the results of this thesis, and discussed how they complement existing knowledge on trait-based ecology. Furthermore, I outlined the limitations of this study and proposed future research directions.
dc.description.abstractThis thesis consists of six chapters: the general introduction (this chapter), four research chapters (chapters 2-5), and a synthesis chapter (chapter 6). I first focused on WSG and wood anatomical traits (chapter 2), then looked at wood chemical traits (chapter 3), and then combined data on wood traits and species demography to assess the links between traits and demographic rates (chapter 4). Finally, I examined the implications of within-stem variations in WSG on biomass estimations at both the species and stand level (chapter 5). It is well established that wood specific gravity (WSG) can vary substantially from pith to bark (Williamson & Wiemann, 2010), which can reflect ontogenetic shifts in hydraulic, mechanical and storage demands during tree development (Hietz et al., 2013). However, the wood anatomical traits underlying these radial variations in WSG are not well understood, particularly for angiosperm tree species from humid tropical forests. In chapter 2, I used a set of wood functional traits, measured along the stem radial profile, to explain the anatomical drivers of radial shifts in WSG. Wood nutrients are expected to play a central role in tree functioning and life-history variations among woody species (Martin et al., 2014; Heinemann et al., 2016). Yet, very few studies have investigated how wood nutrients are related to other wood functional traits, or how they vary radially within stems, or across species and ecological guilds. In chapter 3, I related wood nutrients (i.e., phosphorous, calcium, potassium and magnesium) to WSG and xylem parenchyma fractions ininner and outer wood, and evaluated nutrient resorption rates at the species and ecological guilds level. One central assumption in trait-based ecology is that traits can predict species demography (Shipley et al., 2016). However, the predictive power of most traits on tree demographic rates is in general low. This pattern may be explained by two reasons: the use of “soft traits”, which might not fully capture some plant functions (Yang et al., 2018), and the lack of consideration of size-related changes in both traits and demographic rates (Iida & Swenson, 2019). In chapter 4, I combined demographic rates (i.e., diameter growth and mortality rates) of trees of different sizes and “hard traits” (i.e., chemical and anatomical traits) measured at different radial positions to explain the associations between wood traits and species demography during tree development. Besides its functional significance, wood specific gravity is also an important predictor of above-ground biomass (AGB) and, consequently, of biomass growth rates (BGR) estimations. Although radial shifts in WSG may have considerable effects on AGB and BGR estimations, at both the species and stand level, most regional and local studies do not consider these possible effects. In chapter 5, I quantified species percentage errors in AGB and BGR estimations that resulted from not taking into account radial trends in WSG, and extrapolated these species percentage errors to the stand level. Finally, in the last chapter (chapter 6), I synthesized the results of this thesis, and discussed how they complement existing knowledge on trait-based ecology. Furthermore, I outlined the limitations of this study and proposed future research directions.
dc.description.sponsorshipColciencias
dc.description.sponsorshipInstituto Smithsonian
dc.description.sponsorshipUniversidad del Rosario
dc.format.extent134 pp
dc.format.mimetypeapplication/pdf
dc.geoLocationAmazonía
dc.identifier.doihttps://doi.org/10.48713/10336_38204
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/38204
dc.language.isoeng
dc.publisherUniversidad del Rosario
dc.publisher.departmentEscuela de Medicina y Ciencias de la Salud
dc.publisher.programDoctorado en Ciencias Biomédicas y Biológicas
dc.rightsAttribution 4.0 International*
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)
dc.rights.licenciaPARGRAFO: En caso de presentarse cualquier reclamación o acción por parte de un tercero en cuanto a los derechos de autor sobre la obra en cuestión, EL AUTOR, asumirá toda la responsabilidad, y saldrá en defensa de los derechos aquí autorizados; para todos los efectos la universidad actúa como un tercero de buena fe.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.source.bibliographicCitationAche P, Fromm J, Hedrich R. 2010. Potassium-dependent wood formation in poplar: seasonal aspects and environmental limitations. Plant Biology 12: 259-267.
dc.source.bibliographicCitationAleixo I, Norris D, Hemerik L, Barbosa A, Prata E, Costa F, Poorter L. 2019. Amazonian rainforest trees mortality driven by climate and functional traits. Nature climate change 9: 384-388.
dc.source.bibliographicCitationAlvarez-Clare S, Kitajima K. 2007. Physical defense traits enhance seedling survival of Neotropical tree species. Functional Ecology 21: 1044-1054.
dc.source.bibliographicCitationAmusant N, Nigg M, Thibaut B, Beauchene J. 2014. Diversity of decay resistance strategies of durable tropical woods species: Bocoa prouacencis Aublet, Voucapoua americana Aublet, Inga alba (Sw.) Wild. International Biodeterioration and Biodegradation 94: 103-108.
dc.source.bibliographicCitationAnten NPR, Schieving F. 2010. The role of wood mass density and mechanical constraints in the economy of tree architecture. The American Naturalist 175: 250–260
dc.source.bibliographicCitationAubry-Kientz M, Rossi V, Wagner F, Hérault B. 2015. Identifying climatic drivers of tropical forests dynamics. Biogeosciences 12: 5583-5596.
dc.source.bibliographicCitationAubry-Kientz M, Hérault B, Ayotte-Trepanier C, Baraloto C, Rossi V. 2013. Toward trait-based mortality models for tropical forest. Plos One 8. e63678
dc.source.bibliographicCitationBaas P, Beeckman, K Čufar, De Micco V. 2016. Functional traits in wood anatomy. IAWA Journal 37:124-126.
dc.source.bibliographicCitationBaker T. Phillips O, Malhi Y. et al. 2004. Variation in Wood density determines spatial patterns in Amazonian forest biomass. Global Change Biology 10: 545-562.
dc.source.bibliographicCitationBastin JF, Fayolle A, Tarelkin Y, Van del Bulcke J, de Haulleville T, Mortier F. et al. 2015. Wood specific gravity variations and biomass of Central African tree species: The simple choice of the outer wood. Plos One. 10: e0142146
dc.source.bibliographicCitationBaraloto C, Forget PM, Goldberg D. 2005. Seed mass, seedling size and Neotropical tree seedling establishment. Journal of Ecology 93: 1156-1166.
dc.source.bibliographicCitationBaraloto C, Paine TCE, Patiño S, Bonal D, Héraul B, Chave J. 2010. Functional trait variation and sampling strategies in species-rich plant communities. Functional Ecology 24: 208-216.
dc.source.bibliographicCitationBaraloto C, Hardy OJ, Paine T, Dexter K, Cruaud C, Dunning L, Gonzalez MA. et al. 2012. Using functional traits and phylogenetic trees to examine the assembly of tropical tree communities. Journal of Ecology 100: 690–701.
dc.source.bibliographicCitationBaraloto C, Molto Q, Rebaud S. et al. 2012b. Rapid simultaneous estimation of aboveground biomass and tree species diversity across Neotropical forests: A comparison of field inventory methods. Biotropica 0: 1-11.
dc.source.bibliographicCitationBates D, M Maechler, Bolker B S, Walker S. 2015. Fitting linear mixed effects models using lme4. Journal of Statistical Software, 67: 1–48.
dc.source.bibliographicCitationBecker GS, Braun D, Gliniars R, H Dalitz. 2012. Relations between Wood variables and how they relate to tree size variables of tropical African tree species. Trees 26: 1101–1112.
dc.source.bibliographicCitationBeeckman H. 2016. Wood anatomy and trait-based ecology. IAWA Journal 37: 127-151.
dc.source.bibliographicCitationBeery, WH, Ifju G, McLain TE. 1983. Quantitative wood anatomy- relating anatomy to transverse tensile strength. Wood Fiber. Sci. 15, 395–407.
dc.source.bibliographicCitationBosc A, De Grandcourt A, Loustau D. 2003. Variability of stem and branch maintenance respiration in a Pinus pinaster tree. Tree Physiology 23: 227-236.
dc.source.bibliographicCitationBossu J. 2015. Potentiel de "Bagassa guianensis" et "Cordia alliodora" pour la plantation en zone tropicale. Description d'une stratégie de croissance optimale alliant vitesse de croissance et qualité du bois. PhD Thesis, University of Guyane, French Guiana.
dc.source.bibliographicCitationBossu J, Lehneback R, Corn S, Regazzi A, Beauchêne J, Clair B. 2018. Interlocked grain and density patterns in Bagassa guianensis: changes with ontogeny and mechanical consequences for trees. Trees 32: 1643-1655
dc.source.bibliographicCitationBrodersen C, Mc Elrone J. 2013. Maintenance of xylem network transport capacity: A review of embolism repair in vascular plants. Frontiers in Plant Science 4: 1–11.
dc.source.bibliographicCitationBurnham KP, Anderson DR. 2002. Model selection and multimodel inference: A practical informationtheoretic approach. Springer, New York, USA.
dc.source.bibliographicCitationCarlquist S. 2001. Comparative wood anatomy: systematic, ecological and evolutionary aspects of dicotyledon wood. Springer: Berlin.
dc.source.bibliographicCitationCarlquist S. 2015. Living cells in wood. 1. Absence, scarcity and histology of axial parenchyma as keys to function. Botanical Journal of the Linnean Society 177: 291-321.
dc.source.bibliographicCitationCarneiro de Oliveira J, Mendes dos Santos MG, Santos SP, Vitória AP, Rossato DR, Pedreira de Miranda L & Funch LS. 2021. Leaf trait variability maintains similar leaf Exchange rhythms in Hirtella glandulosa Spreng. (Chrysobalanaceae) populations growing on contrasting soil types in the Brazilian Atlantic Forest. Brazilian Journal of Botany 44: 753-765.
dc.source.bibliographicCitationChapin FS, Schulze ED, HA Mooney. 1990. The ecology and economics of storage inn plants. Annual review of ecology and systematics 21: 423-447.
dc.source.bibliographicCitationChapin FS III, Matson P, Vitousek PM. 2011. Nutrient cyclcing. In Chapin et al (eds). Principles of terrestial eocsystem ecology. Second edition. Springer.
dc.source.bibliographicCitationChave J, Muller-Landau H, Baker T. et al. 2006. Regional and phylogenetic variation in wood density across 2456 Neotropical tree species. Ecological Applications 16: 2356-2367
dc.source.bibliographicCitationChave J, Coomes D, Jansen S, Lewis SL, Swenson NG, Zane A. 2009. Towards a worldwide wood economics spectrum. Ecology Letters 12: 351-366.
dc.source.bibliographicCitationChave, J. et al. 2014. Improved allometric models to estimate the aboveground biomass of tropical trees. Global Change Biology 20 (10): 3177-3190.
dc.source.bibliographicCitationChazdon R, Broadbent E, Rozendal DMA. et al. 2016. Carbon sequestration potential of second- growth regeneration in the Latin American tropics. Science advances 2 (5). DOI: 10.1126/sciadv.1501639.
dc.source.bibliographicCitationClark DA, Brown S, Kicklighter D. et al. 2001. Net primary production in tropical forests: an evaluation and synthesis of existing field data. Ecological Applications 11: 371–384.
dc.source.instnameinstname:Universidad del Rosario
dc.source.reponamereponame:Repositorio Institucional EdocUR
dc.subjectWood traits
dc.subjectDemography
dc.subjectFunctional ecology
dc.subjectTropical forests
dc.subjectEcology
dc.subject.keywordWood traits
dc.subject.keywordDemography
dc.subject.keywordFunctional ecology
dc.subject.keywordTropical forests
dc.subject.keywordEcology
dc.titleWood strategies in a lowland rainforest of eastern Amazonia
dc.title.TranslatedTitleEstrategias ecológicas de madera en un bosque humedo de tierras bajas en la Amazonia oriental
dc.typemasterThesis
dc.type.documentTesis
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersion
dc.type.spaTesis
local.department.reportEscuela de Medicina y Ciencias de la Salud
Archivos
Bloque original
Mostrando1 - 1 de 1
Cargando...
Miniatura
Nombre:
Wood-strategies-in-a-lowland-rainforest-of-eastern-Amazonia-Tesis_AGM.pdf
Tamaño:
5.38 MB
Formato:
Adobe Portable Document Format
Descripción: