Relación entre la estructura forestal y la diversidad alfa en bosques de Colombia : aproximaciones en la Amazonia y el Caribe

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dc.contributor.advisorFagua González, José Camilo
dc.contributor.authorVallejo Mayo, Leidy Yuliana
dc.contributor.researchgroupGrupo de biodiversidad, biotecnología y conservación de ecosistemas
dc.coverage.countryColombia
dc.coverage.spatialAmazonía
dc.coverage.spatialCaribe
dc.coverage.tgnhttp://vocab.getty.edu/page/tgn/1000050
dc.date.accessioned2026-08-04T23:43:57Z
dc.date.available2026-08-04T23:43:57Z
dc.date.issued2026-06
dc.descriptionilustraciones, diagramas, fotografías, mapas, tablasspa
dc.description.abstractLa relación entre la diversidad arbórea y la estructura forestal es clave para comprender el funcionamiento de los bosques tropicales y fortalecer estrategias de monitoreo basadas en sensores remotos. Este estudio tuvo como objetivo evaluar la relación entre la α-diversidad arbórea y la estructura forestal vertical y horizontal en bosques tropicales de Colombia, así como identificar la escala espacial y el conjunto de predictores con mayor capacidad para explicar su variación. Para ello, se analizaron 23 parcelas permanentes de una hectárea distribuidas en dos regiones contrastantes (Amazonia y Caribe), integrando métricas de estructura forestal, predictores ambientales y variables de funcionamiento ecosistémico. La α-diversidad presentó valores más altos y mayor heterogeneidad en la Amazonia, mientras que el Caribe mostró valores más bajos y menor variabilidad interna. La estructura forestal vertical fue el principal predictor de la α-diversidad, superando a las métricas de estructura horizontal en capacidad explicativa. El análisis multiescala evidenció que un buffer de 50 m alrededor de las parcelas maximizó el desempeño predictivo, resaltando la importancia de ajustar la escala espacial de los predictores a procesos ecológicos locales. Los gradientes climáticos y las variables de funcionamiento ecosistémico aportaron información complementaria, con contribuciones variables según la métrica de diversidad evaluada. Los modelos Random Forest mostraron un desempeño superior y más estable que MARS. En conjunto, los resultados destacan el valor de la estructura vertical del dosel como proxy robusto de la α-diversidad arbórea y su potencial para el monitoreo espacial de la biodiversidad forestal. (Texto tomado de la fuente)spa
dc.description.abstractThe relationship between tree diversity and forest structure is key to understanding the functioning of tropical forests and strengthening remote sensing-based monitoring strategies. This study aimed to evaluate the relationship between tree α-diversity and vertical and horizontal forest structure in tropical forests of Colombia, as well as to identify the spatial scale and set of predictors with the greatest capacity to explain its variation. To this end, 23 one-hectare permanent plots distributed across two contrasting regions, the Amazon and the Caribbean, were analyzed by integrating forest structure metrics, environmental predictors, and ecosystem functioning variables. α-diversity showed higher values and greater heterogeneity in the Amazon, whereas the Caribbean showed lower values and less internal variability. Vertical forest structure was the main predictor of α-diversity, outperforming horizontal structure metrics in explanatory capacity. The multiscale analysis showed that a 50 m buffer around the plots maximized predictive performance, highlighting the importance of matching the spatial scale of predictors with local ecological processes. Climatic gradients and ecosystem functioning variables provided complementary information, with contributions that varied according to the diversity metric evaluated. Random Forest models showed higher and more stable performance than MARS. Overall, the results highlight the value of vertical canopy structure as a robust proxy for tree α-diversity and its potential for spatial monitoring of forest biodiversity.eng
dc.description.degreelevelMaestría
dc.description.degreenameMagister en Ciencias - Biología
dc.description.researchareaBiodiversidad, conservación y monitoreo de ecosistemas tropicales
dc.format.extent87 páginas
dc.format.mimetypeapplication/pdf
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/90508
dc.language.isospa
dc.publisherUniversidad Nacional de Colombia
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotá
dc.publisher.departmentDepartamento de Biología
dc.publisher.facultyFacultad de Ciencias
dc.publisher.placeBogotá, Colombia
dc.publisher.programBogotá - Ciencias - Maestría en Ciencias - Biología
dc.relation.indexedAgrosavia
dc.relation.indexedAgrovoc
dc.relation.referencesGrunwald, S. (2009). Multi-criteria characterization of recent digital soil mapping and modeling approaches.
dc.relation.referencesMalhi, Y. (2012). The productivity, metabolism and carbon cycle of tropical forest vegetation.
dc.relation.referencesMalhi, Y., Doughty, C., & Galbraith, D. (2011). The allocation of ecosystem net primary productivity in tropical forests.
dc.relation.referencesOlofsson, P., Van Laake, P.E., & Eklundh, L. (2007). Estimation of absorbed PAR across Scandinavia from satellite measurements.
dc.relation.referencesSenna, M.C.A., Costa, M.H., & Shimabukuro, Y.E. (2005). Fraction of photosynthetically active radiation absorbed by Amazon tropical forest: A comparison of field measurements, modeling, and remote sensing.
dc.relation.referencesKrishnadas, M., Sankaran, M., Page, N., Joshi, J., Machado, S., Nataraj, N., Chengappa, S.K., Kumar, V., Kumar, A., & Krishnamani, R. (2021). Seasonal drought regulates species distributions and assembly of tree communities across a tropical wet forest region.
dc.relation.referencesEsquivel‐Muelbert, A., Baker, T.R., Dexter, K.G., Lewis, S.L., Ter Steege, H., Lopez‐Gonzalez, G., Monteagudo Mendoza, A., Brienen, R., Feldpausch, T.R., Pitman, N., Alonso, A., Van Der Heijden, G., Peña‐Claros, M., Ahuite, M., Alexiaides, M., Álvarez Dávila, E., Murakami, A.A., Arroyo, L., Aulestia, M. ... Phillips, O.L. (2017). Seasonal drought limits tree species across the Neotropics.
dc.relation.referencesEngelbrecht, B.M.J., Comita, L.S., Condit, R., Kursar, T.A., Tyree, M.T., Turner, B.L., & Hubbell, S.P. (2007). Drought sensitivity shapes species distribution patterns in tropical forests.
dc.relation.referencesKraft, N.J.B., Adler, P.B., Godoy, O., James, E.C., Fuller, S., & Levine, J.M. (2015). Community assembly, coexistence and the environmental filtering metaphor.
dc.relation.referencesMarks, C.O., Muller‐Landau, H.C., & Tilman, D. (2017). Tree diversity in relation to maximum tree height: evidence for the harshness hypothesis of species diversity gradients.
dc.relation.referencesMarks, C.O., Muller‐Landau, H.C., & Tilman, D. (2016). Tree diversity, tree height and environmental harshness in eastern and western North America.
dc.relation.referencesHijmans, R.J. (2020). terra: Spatial Data Analysis.
dc.relation.referencesAllen, C.D., Macalady, A.K., Chenchouni, H., Bachelet, D., McDowell, N., Vennetier, M., Kitzberger, T., Rigling, A., Breshears, D.D., Hogg, E.(., Gonzalez, P., Fensham, R., Zhang, Z., Castro, J., Demidova, N., Lim, J., Allard, G., Running, S.W., Semerci, A., & Cobb, N. (2010). A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests.
dc.relation.referencesRocchini, D., Boyd, D.S., Féret, J., Foody, G.M., He, K.S., Lausch, A., Nagendra, H., Wegmann, M., & Pettorelli, N. (2016). Satellite remote sensing to monitor species diversity: potential and pitfalls.
dc.relation.referencesYates, K.L., Bouchet, P.J., Caley, M.J., Mengersen, K., Randin, C.F., Parnell, S., Fielding, A.H., Bamford, A.J., Ban, S., Barbosa, A.M., Dormann, C.F., Elith, J., Embling, C.B., Ervin, G.N., Fisher, R., Gould, S., Graf, R.F., Gregr, E.J., Halpin, P.N. ... Sequeira, A.M. (2018). Outstanding Challenges in the Transferability of Ecological Models.
dc.relation.referencesOlden, J., Lawler, J., & Poff, N. (2008). Machine Learning Methods Without Tears: A Primer for Ecologists.
dc.relation.referencesMeyer, H., Reudenbach, C., Wöllauer, S., & Nauss, T. (2019). Importance of spatial predictor variable selection in machine learning applications – Moving from data reproduction to spatial prediction.
dc.relation.referencesJetz, W., Cavender-Bares, J., Pavlick, R., Schimel, D., Davis, F.W., Asner, G.P., Guralnick, R., Kattge, J., Latimer, A.M., Moorcroft, P., Schaepman, M.E., Schildhauer, M.P., Schneider, F.D., Schrodt, F., Stahl, U., & Ustin, S.L. (2016). Monitoring plant functional diversity from space.
dc.relation.referencesGrace, J.B., Anderson, T.M., Seabloom, E.W., Borer, E.T., Adler, P.B., Harpole, W.S., Hautier, Y., Hillebrand, H., Lind, E.M., Pärtel, M., Bakker, J.D., Buckley, Y.M., Crawley, M.J., Damschen, E.I., Davies, K.F., Fay, P.A., Firn, J., Gruner, D.S., Hector, A. ... Smith, M.D. (2016). Integrative modelling reveals mechanisms linking productivity and plant species richness.
dc.relation.referencesHardiman, B.S., Bohrer, G., Gough, C.M., Vogel, C.S., & Curtis, P.S. (2011). The role of canopy structural complexity in wood net primary production of a maturing northern deciduous forest.
dc.relation.referencesFahrig, L. (2003). Effects of Habitat Fragmentation on Biodiversity.
dc.relation.referencesFahrig, L. (2013). Rethinking patch size and isolation effects: the habitat amount hypothesis.
dc.relation.referencesEhbrecht, M., Schall, P., Juchheim, J., Ammer, C., & Seidel, D. (2016). Effective number of layers: A new measure for quantifying three-dimensional stand structure based on sampling with terrestrial LiDAR.
dc.relation.referencesPretzsch, H. (2014). Canopy space filling and tree crown morphology in mixed-species stands compared with monocultures.
dc.relation.referencesLevin, S.A. (1992). The Problem of Pattern and Scale in Ecology.
dc.relation.referencesMcGill, B.J. (2010). Matters of Scale.
dc.relation.referencesChase, J.M. & Leibold, M.A. (2003). Ecological Niches: Linking Classical and Contemporary Approaches. University of Chicago Press.
dc.relation.referencesPoorter, L., Rozendaal, D.M.A., Bongers, F., De Almeida-Cortez, J.S., Almeyda Zambrano, A.M., Álvarez, F.S., Andrade, J.L., Villa, L.F.A., Balvanera, P., Becknell, J.M., Bentos, T.V., Bhaskar, R., Boukili, V., Brancalion, P.H.S., Broadbent, E.N., César, R.G., Chave, J., Chazdon, R.L., Colletta, G.D. ... Westoby, M. (2019). Wet and dry tropical forests show opposite successional pathways in wood density but converge over time.
dc.relation.referencesLebrija-Trejos, E., Pérez-García, E.A., Meave, J.A., Bongers, F., & Poorter, L. (2010). Functional traits and environmental filtering drive community assembly in a species‐rich tropical system.
dc.relation.referencesChao, A., Chiu, C.H., & Jost, L. (2014). Unifying Species Diversity, Phylogenetic Diversity, Functional Diversity, and Related Similarity and Differentiation Measures Through Hill Numbers.
dc.relation.referencesHubbell, S.P. (2001). The Unified Neutral Theory of Biodiversity and Biogeography (MPB-32). Princeton University Press.
dc.relation.referencesDRYFLOR, , Banda-R, K., Delgado-Salinas, A., Dexter, K.G., Linares-Palomino, R., Oliveira-Filho, A., Prado, D., Pullan, M., Quintana, C., Riina, R., Rodríguez M., G.M., Weintritt, J., Acevedo-Rodríguez, P., Adarve, J., Álvarez, E., Aranguren B., A., Arteaga, J.C., Aymard, G., Castaño, A. ... Pennington, R.T. (2016). Plant diversity patterns in neotropical dry forests and their conservation implications.
dc.relation.referencesQuesada, M., Sanchez-Azofeifa, G.A., Alvarez-Añorve, M., Stoner, K.E., Avila-Cabadilla, L., Calvo-Alvarado, J., Castillo, A., Espírito-Santo, M.M., Fagundes, M., Fernandes, G.W., Gamon, J., Lopezaraiza-Mikel, M., Lawrence, D., Morellato, L.P.C., Powers, J.S., Neves, F.D.S., Rosas-Guerrero, V., Sayago, R., & Sanchez-Montoya, G. (2009). Succession and management of tropical dry forests in the Americas: Review and new perspectives.
dc.relation.referencesMurphy, P.G. & Lugo, A.E. (1986). ECOLOGY OF TROPICAL DRY FOREST.
dc.relation.referencesJohn, R., Dalling, J.W., Harms, K.E., Yavitt, J.B., Stallard, R.F., Mirabello, M., Hubbell, S.P., Valencia, R., Navarrete, H., Vallejo, M., & Foster, R.B. (2007). Soil nutrients influence spatial distributions of tropical tree species.
dc.relation.referencesCondit, R., Pitman, N., Leigh, E.G., Chave, J., Terborgh, J., Foster, R.B., Núñez, P., Aguilar, S., Valencia, R., Villa, G., Muller-Landau, H.C., Losos, E., & Hubbell, S.P. (2002). Beta-Diversity in Tropical Forest Trees.
dc.relation.referencesChave, J., Condit, R., Muller-Landau, H.C., Thomas, S.C., Ashton, P.S., Bunyavejchewin, S., Co, L.L., Dattaraja, H.S., Davies, S.J., Esufali, S., Ewango, C.E.N., Feeley, K.J., Foster, R.B., Gunatilleke, N., Gunatilleke, S., Hall, P., Hart, T.B., Hernández, C., Hubbell, S.P. ... Losos, E.C. (2008). Assessing Evidence for a Pervasive Alteration in Tropical Tree Communities.
dc.relation.referencesNorden, N., Umaña, M.N., Salgado‐Negret, B., González‐M, R., Rodríguez‐Buritica, S., Idárraga‐Piedrahita, �., Avella, A., Castaño‐Naranjo, A., Cuadros, H., García, D., García, H., Franke‐Ante, R., Garzón, F.C., González, M.A., Jurado, R., López‐Camacho, R., Nieto, J., Pizano, C., Rodríguez, G. ... Vergara, H. (2026). Tropical Dry Forests Challenge Macroecological Rules of Positive Relationships Between Species' Niche Breadth, Range Size and Abundance.
dc.relation.referencesFagua, J.C., Jantz, P., Burns, P., Jantz, S.M., Kilbride, J.B., & Goetz, S.J. (2026). Maps of forest vertical structure for Colombia, a megadiverse country.
dc.relation.referencesFagua, J.C. & Jantz, P. (2024). Mapping Tropical Dry Forest Gradients in an Andean Region with High Environmental Variability.
dc.relation.referencesFagua, J.C., Jantz, P., Rodriguez-Buritica, S., Duncanson, L., & Goetz, S.J. (2019). Integrating LiDAR, Multispectral and SAR Data to Estimate and Map Canopy Height in Tropical Forests.
dc.relation.referencesCleveland, W.S. (1979). Robust Locally Weighted Regression and Smoothing Scatterplots.
dc.relation.referencesJacoby, W.G. (2000). Loess: a nonparametric, graphical tool for depicting relationships between variables.
dc.relation.referencesCleveland, W.S. & Devlin, S.J. (1988). Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting.
dc.relation.referencesWright, S.P. (1992). Adjusted P-Values for Simultaneous Inference.
dc.relation.referencesBenjamini, Y. & Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency.
dc.relation.referencesSchober, P., Boer, C., & Schwarte, L.A. (2018). Correlation Coefficients: Appropriate Use and Interpretation.
dc.relation.referencesHauke, J. & Kossowski, T. (2011). Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data.
dc.relation.referencesPike, N. (2011). Using false discovery rates for multiple comparisons in ecology and evolution.
dc.relation.referencesBenjamini, Y. & Hochberg, Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing.
dc.relation.referencesWaite, T.A. & Campbell, L.G. (2006). Controlling the false discovery rate and increasing statistical power in ecological studies.
dc.relation.referencesHodson, T.O. (2022). Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not.
dc.relation.referencesChai, T. & Draxler, R.R. (2014). Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature.
dc.relation.referencesWillmott, C. & Matsuura, K. (2005). Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance.
dc.relation.referencesGoebes, P., Schmidt, K., Seitz, S., Both, S., Bruelheide, H., Erfmeier, A., Scholten, T., & Kühn, P. (2019). The strength of soil-plant interactions under forest is related to a Critical Soil Depth.
dc.relation.referencesDarmody, R., Daniels, W., Marlin, J., & Cremeens, D. (2009). TOPSOIL: WHAT IS IT AND WHO CARES?
dc.relation.referencesJolliffe, I.T. & Cadima, J. (2016). Principal component analysis: a review and recent developments.
dc.relation.referencesSão Pedro, M., Smith, M.N., Zuquim, G., Tuomisto, H., Stark, S.C., Pereira, L.G.D.A., Bobrowiec, P.E.D., Bueno, A.S., Capaverde, U., Castilho, C., Esteban, E., Lima, A., Magnusson, W., Menger, J., Pinto, M.G., Rincón, L., Tavares, V.D.C., Waldez, F., & Schietti, J. (2025). Forest structure predicts plant and animal species diversity and composition changes in an Amazonian forest.
dc.relation.referencesPlant diversity and complexity patterns: local, regional and global dimensions: proceedings of an international symposium held at the Royal Danish Academy of Sciences and Letters in Copenhagen, Denmark, 25 - 28 May, 2003 ; [proceedings of the Symposium Plant Diversity and Complexity Patterns - Local, Regional and Global Dimensions ...] (2005). Reitzel.
dc.relation.referencesKuhn, M. (2007). caret: Classification and Regression Training.
dc.relation.referencesHastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning. Springer New York.
dc.relation.referencesStrobl, C., Boulesteix, A., Zeileis, A., & Hothorn, T. (2007). Bias in random forest variable importance measures: Illustrations, sources and a solution.
dc.relation.referencesKuhn, M. (2008).
dc.relation.referencesIrion, G., Müller, J., Nunes De Mello, J., & Junk, W.J. (1995). Quaternary geology of the Amazonian Lowland.
dc.relation.referencesMcGarigal, K. & Cushman, S.A. (2002). COMPARATIVE EVALUATION OF EXPERIMENTAL APPROACHES TO THE STUDY OF HABITAT FRAGMENTATION EFFECTS.
dc.relation.referencesCutler, D.R., Edwards, T.C., Beard, K.H., Cutler, A., Hess, K.T., Gibson, J., & Lawler, J.J. (2007). RANDOM FORESTS FOR CLASSIFICATION IN ECOLOGY.
dc.relation.referencesElith, J., Leathwick, J.R., & Hastie, T. (2008). A working guide to boosted regression trees.
dc.relation.referencesPoggio, L., De Sousa, L.M., Batjes, N.H., Heuvelink, G.B.M., Kempen, B., Ribeiro, E., & Rossiter, D. (2021). SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty.
dc.relation.referencesPaoli, G.D., Curran, L.M., & Zak, D.R. (2006). Soil nutrients and beta diversity in the Bornean Dipterocarpaceae: evidence for niche partitioning by tropical rain forest trees.
dc.relation.referencesFine, P.V.A. & Kembel, S.W. (2011). Phylogenetic community structure and phylogenetic turnover across space and edaphic gradients in western Amazonian tree communities.
dc.relation.referencesReich, P.B. & Oleksyn, J. (2004). Global patterns of plant leaf N and P in relation to temperature and latitude.
dc.relation.referencesWright, D.H. (1983). Species-Energy Theory: An Extension of Species-Area Theory.
dc.relation.referencesRunning, S.W., Nemani, R.R., Heinsch, F.A., Zhao, M., Reeves, M., & Hashimoto, H. (2004). A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production.
dc.relation.referencesMyneni, R., Knyazikhin, Y., & Park, T. (2015). MOD15A2H MODIS/Terra Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V006. NASA Land Processes Distributed Active Archive Center.
dc.relation.referencesZhao, M., Heinsch, F.A., Nemani, R.R., & Running, S.W. (2005). Improvements of the MODIS terrestrial gross and net primary production global data set.
dc.relation.referencesFick, S.E. & Hijmans, R.J. (2017). WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas.
dc.relation.referencesHengl, T., Mendes De Jesus, J., Heuvelink, G.B.M., Ruiperez Gonzalez, M., Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M.N., Geng, X., Bauer-Marschallinger, B., Guevara, M.A., Vargas, R., MacMillan, R.A., Batjes, N.H., Leenaars, J.G.B., Ribeiro, E., Wheeler, I., Mantel, S., & Kempen, B. (2017). SoilGrids250m: Global gridded soil information based on machine learning.
dc.relation.referencesWiens, J.A. (1989). Spatial Scaling in Ecology.
dc.relation.referencesRoberts, D.R., Bahn, V., Ciuti, S., Boyce, M.S., Elith, J., Guillera‐Arroita, G., Hauenstein, S., Lahoz‐Monfort, J.J., Schröder, B., Thuiller, W., Warton, D.I., Wintle, B.A., Hartig, F., & Dormann, C.F. (2017). Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure.
dc.relation.referencesKohavi, R. & John, G.H. (1997). Wrappers for feature subset selection.
dc.relation.referencesFriedman, J.H. (1991). Multivariate Adaptive Regression Splines.
dc.relation.referencesBreiman, L. (2001). Random Forests.
dc.relation.referencesZuur, A.F., Ieno, E.N., & Elphick, C.S. (2010).
dc.relation.referencesHolland, J.D., Bert, D.G., & Fahrig, L. (2004). Determining the Spatial Scale of Species' Response to Habitat.
dc.relation.referencesJackson, H.B. & Fahrig, L. (2015). Are ecologists conducting research at the optimal scale?
dc.relation.referencesStrobl, C., Boulesteix, A., Kneib, T., Augustin, T., & Zeileis, A. (2008). Conditional variable importance for random forests.
dc.relation.referencesJuárez–Fragoso, M.A., Perroni, Y., Dáttilo, W., Gómez–Díaz, J.A., & Guevara, R. (2024). The landscape scale of effect on the alpha and beta diversities of woody species in a semideciduous tropical forest.
dc.relation.referencesKursa, M.B. & Rudnicki, W.R. (2010).
dc.relation.referencesArlot, S. & Celisse, A. (2009). A survey of cross-validation procedures for model selection. arXiv.
dc.relation.referencesDormann, C.F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., Marquéz, J.R.G., Gruber, B., Lafourcade, B., Leitão, P.J., Münkemüller, T., McClean, C., Osborne, P.E., Reineking, B., Schröder, B., Skidmore, A.K., Zurell, D., & Lautenbach, S. (2013). Collinearity: a review of methods to deal with it and a simulation study evaluating their performance.
dc.relation.referencesHarrell, (2015). Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis. Springer International Publishing.
dc.relation.referencesLegendre, P. & Legendre, L. (2012). Numerical ecology. Elsevier.
dc.relation.referencesHe, H.S., DeZonia, B.E., & Mladenoff, D.J. (2000). An aggregation index (AI) to quantify spatial patterns of landscapes.
dc.relation.referencesCongalton, R.G. & Green, K. (2019). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, Third Edition. CRC Press.
dc.relation.referencesHansen, M.C., Potapov, P.V., Moore, R., Hancher, M., Turubanova, S.A., Tyukavina, A., Thau, D., Stehman, S.V., Goetz, S.J., Loveland, T.R., Kommareddy, A., Egorov, A., Chini, L., Justice, C.O., & Townshend, J.R.G. (2013). High-Resolution Global Maps of 21st-Century Forest Cover Change.
dc.relation.referencesMitra, J.R., Ahmed, T.T., & Czajkowski, K. (2025). Landscape fragmentation and population distribution in refugee camps: evidence from the Rohingya refugee influx in Bangladesh.
dc.relation.referencesChao, A. & Jost, L. (2012). Coverage‐based rarefaction and extrapolation: standardizing samples by completeness rather than size.
dc.relation.referencesGood, I.J. (1953). THE POPULATION FREQUENCIES OF SPECIES AND THE ESTIMATION OF POPULATION PARAMETERS.
dc.relation.referencesSimpson, E.H. (1949). Measurement of Diversity.
dc.relation.referencesShannon, C.E. (1948). A Mathematical Theory of Communication.
dc.relation.referencesChao, A., Gotelli, N.J., Hsieh, T.C., Sander, E.L., Ma, K.H., Colwell, R.K., & Ellison, A.M. (2014). Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies.
dc.relation.referencesFisher, R.A., Corbet, A.S., & Williams, C.B. (1943). The Relation Between the Number of Species and the Number of Individuals in a Random Sample of an Animal Population.
dc.relation.referencesBeck, J. & Schwanghart, W. (2010).
dc.relation.referencesHill, M.O. (1973). Diversity and Evenness: A Unifying Notation and Its Consequences.
dc.relation.referencesHsieh, T.C., Ma, K.H., & Chao, A. (2016). iNEXT: an R package for rarefaction and extrapolation of species diversity ( H ill numbers).
dc.relation.referencesBaraloto, C., Molto, Q., Rabaud, S., Hérault, B., Valencia, R., Blanc, L., Fine, P.V.A., & Thompson, J. (2013). Rapid Simultaneous Estimation of Aboveground Biomass and Tree Diversity Across Neotropical Forests: A Comparison of Field Inventory Methods.
dc.relation.referencesEtter, A., McAlpine, C., Wilson, K., Phinn, S., & Possingham, H. (2006). Regional patterns of agricultural land use and deforestation in Colombia.
dc.relation.referencesGonzález-M, R., García, H., Isaacs, P., Cuadros, H., López-Camacho, R., Rodríguez, N., Pérez, K., Mijares, F., Castaño-Naranjo, A., Jurado, R., Idárraga-Piedrahíta, �., Rojas, A., Vergara, H., & Pizano, C. (2018). Disentangling the environmental heterogeneity, floristic distinctiveness and current threats of tropical dry forests in Colombia.
dc.relation.referencesPortillo-Quintero, C. & Sánchez-Azofeifa, G. (2010). Extent and conservation of tropical dry forests in the Americas.
dc.relation.referencesGroup, T.A.P. (2016). An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV.
dc.relation.referencesHaddad, N.M., Brudvig, L.A., Clobert, J., Davies, K.F., Gonzalez, A., Holt, R.D., Lovejoy, T.E., Sexton, J.O., Austin, M.P., Collins, C.D., Cook, W.M., Damschen, E.I., Ewers, R.M., Foster, B.L., Jenkins, C.N., King, A.J., Laurance, W.F., Levey, D.J., Margules, C.R. ... Townshend, J.R. (2015). Habitat fragmentation and its lasting impact on Earth’s ecosystems.
dc.relation.referencesLuo, W., Liang, J., Cazzolla Gatti, R., Zhao, X., & Zhang, C. (2019). Parameterization of biodiversity–productivity relationship and its scale dependency using georeferenced tree‐level data.
dc.relation.referencesWalter, J.A., Stovall, A.E.L., & Atkins, J.W. (2021). Vegetation structural complexity and biodiversity in the Great Smoky Mountains.
dc.relation.referencesMeyer, V., Saatchi, S., Ferraz, A., Xu, L., Duque, A., García, M., & Chave, J. (2019). Forest degradation and biomass loss along the Chocó region of Colombia.
dc.relation.referencesAsner, G.P., Clark, J.K., Mascaro, J., Galindo García, G.A., Chadwick, K.D., Navarrete Encinales, D.A., Paez-Acosta, G., Cabrera Montenegro, E., Kennedy-Bowdoin, T., Duque, �., Balaji, A., Von Hildebrand, P., Maatoug, L., Phillips Bernal, J.F., Yepes Quintero, A.P., Knapp, D.E., García Dávila, M.C., Jacobson, J., & Ordóñez, M.F. (2012). High-resolution mapping of forest carbon stocks in the Colombian Amazon.
dc.relation.referencesFagua, J.C., Jantz, P., Burns, P., Massey, R., Buitrago, J.Y., Saatchi, S., Hakkenberg, C., & Goetz, S.J. (2021). Mapping tree diversity in the tropical forest region of Chocó-Colombia.
dc.relation.referencesPotapov, P., Li, X., Hernandez-Serna, A., Tyukavina, A., Hansen, M.C., Kommareddy, A., Pickens, A., Turubanova, S., Tang, H., Silva, C.E., Armston, J., Dubayah, R., Blair, J.B., & Hofton, M. (2021). Mapping global forest canopy height through integration of GEDI and Landsat data.
dc.relation.referencesBergen, K.M., Goetz, S.J., Dubayah, R.O., Henebry, G.M., Hunsaker, C.T., Imhoff, M.L., Nelson, R.F., Parker, G.G., & Radeloff, V.C. (2009). Remote sensing of vegetation 3‐D structure for biodiversity and habitat: Review and implications for lidar and radar spaceborne missions.
dc.relation.referencesGoetz, S., Steinberg, D., Dubayah, R., & Blair, B. (2007). Laser remote sensing of canopy habitat heterogeneity as a predictor of bird species richness in an eastern temperate forest, USA.
dc.relation.referencesTurner, W., Spector, S., Gardiner, N., Fladeland, M., Sterling, E., & Steininger, M. (2003). Remote sensing for biodiversity science and conservation.
dc.relation.referencesMarselis, S.M., Tang, H., Armston, J.D., Calders, K., Labrière, N., & Dubayah, R. (2018). Distinguishing vegetation types with airborne waveform lidar data in a tropical forest-savanna mosaic: A case study in Lopé National Park, Gabon.
dc.relation.referencesDubayah, R., Blair, J.B., Goetz, S., Fatoyinbo, L., Hansen, M., Healey, S., Hofton, M., Hurtt, G., Kellner, J., Luthcke, S., Armston, J., Tang, H., Duncanson, L., Hancock, S., Jantz, P., Marselis, S., Patterson, P.L., Qi, W., & Silva, C. (2020). The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography.
dc.relation.referencesMarselis, S.M., Tang, H., Armston, J., Abernethy, K., Alonso, A., Barbier, N., Bissiengou, P., Jeffery, K., Kenfack, D., Labrière, N., Lee, S., Lewis, S.L., Memiaghe, H., Poulsen, J.R., White, L., & Dubayah, R. (2019). Exploring the relation between remotely sensed vertical canopy structure and tree species diversity in Gabon.
dc.relation.referencesGeorge-Chacon, S.P., Dupuy, J.M., Peduzzi, A., & Hernandez-Stefanoni, J.L. (2019). Combining high resolution satellite imagery and lidar data to model woody species diversity of tropical dry forests.
dc.relation.referencesBae, S., Levick, S.R., Heidrich, L., Magdon, P., Leutner, B.F., Wöllauer, S., Serebryanyk, A., Nauss, T., Krzystek, P., Gossner, M.M., Schall, P., Heibl, C., Bässler, C., Doerfler, I., Schulze, E., Krah, F., Culmsee, H., Jung, K., Heurich, M. ... Müller, J. (2019). Radar vision in the mapping of forest biodiversity from space.
dc.relation.referencesFricker, G.A., Wolf, J.A., Saatchi, S.S., & Gillespie, T.W. (2015). Predicting spatial variations of tree species richness in tropical forests from high‐resolution remote sensing.
dc.relation.referencesMaia, V.A., De Souza, C.R., De Aguiar-Campos, N., Fagundes, N.C.A., Santos, A.B.M., De Paula, G.G.P., Santos, P.F., Silva, W.B., De Oliveira Menino, G.C., & Dos Santos, R.M. (2020). Interactions between climate and soil shape tree community assembly and above-ground woody biomass of tropical dry forests.
dc.relation.referencesGuo, Q., Kelt, D.A., Sun, Z., Liu, H., Hu, L., Ren, H., & Wen, J. (2013). Global variation in elevational diversity patterns.
dc.relation.referencesToszogyova, A. & Storch, D. (2019). Global diversity patterns are modulated by temporal fluctuations in primary productivity.
dc.relation.referencesHawkins, B.A., Field, R., Cornell, H.V., Currie, D.J., Guégan, J., Kaufman, D.M., Kerr, J.T., Mittelbach, G.G., Oberdorff, T., O'Brien, E.M., Porter, E.E., & Turner, J.R.G. (2003). ENERGY, WATER, AND BROAD-SCALE GEOGRAPHIC PATTERNS OF SPECIES RICHNESS.
dc.relation.referencesWhittaker, R.H. (1960). Vegetation of the Siskiyou Mountains, Oregon and California.
dc.relation.referencesSilva, C.A., Saatchi, S., Garcia, M., Labriere, N., Klauberg, C., Ferraz, A., Meyer, V., Jeffery, K.J., Abernethy, K., White, L., Zhao, K., Lewis, S.L., & Hudak, A.T. (2018). Comparison of Small- and Large-Footprint Lidar Characterization of Tropical Forest Aboveground Structure and Biomass: A Case Study From Central Gabon.
dc.relation.referencesBalvanera, P., Brauman, K.A., Cord, A.F., Drakou, E.G., Geijzendorffer, I.R., Karp, D.S., Martín-López, B., Mwampamba, T.H., & Schröter, M. (2022). Essential ecosystem service variables for monitoring progress towards sustainability.
dc.relation.referencesFortier, R.P., Bernal-Escobar, M., Kullberg, A.T., Osorio Ospina, J.C., Herrera Medina, Y., Aragón, L., Palacios Hurtado, C., & Contreras, M.P. (2024). Diversity, composition, and structure of a 1-hectare tree plot in the cloud forest of the Sierra Nevada de Santa Marta, Colombia.
dc.relation.referencesTuomisto, H., Ruokolainen, K., Kalliola, R., Linna, A., Danjoy, W., & Rodriguez, Z. (1995). Dissecting Amazonian Biodiversity.
dc.relation.referencesFigueiredo, F.O.G., Zuquim, G., Tuomisto, H., Moulatlet, G.M., Balslev, H., & Costa, F.R.C. (2018). Beyond climate control on species range: The importance of soil data to predict distribution of Amazonian plant species.
dc.relation.referencesHiggins, M.A., Ruokolainen, K., Tuomisto, H., Llerena, N., Cardenas, G., Phillips, O.L., Vásquez, R., & Räsänen, M. (2011). Geological control of floristic composition in Amazonian forests.
dc.relation.referencesTuomisto, H., Van Doninck, J., Ruokolainen, K., Moulatlet, G.M., Figueiredo, F.O.G., Sirén, A., Cárdenas, G., Lehtonen, S., & Zuquim, G. (2019). Discovering floristic and geoecological gradients across Amazonia.
dc.relation.referencesGentry, A.H. (1988). Changes in Plant Community Diversity and Floristic Composition on Environmental and Geographical Gradients.
dc.relation.referencesDuivenvoorden, J.F. (1994). Vascular plant species counts in the rain forests of the middle Caquetá area, Colombian Amazonia.
dc.relation.referencesGentry, A.H. (1988). Tree species richness of upper Amazonian forests.
dc.relation.referencesSabatini, F.M., Jiménez-Alfaro, B., Jandt, U., Chytrý, M., Field, R., Kessler, M., Lenoir, J., Schrodt, F., Wiser, S.K., Arfin Khan, M.A.S., Attorre, F., Cayuela, L., De Sanctis, M., Dengler, J., Haider, S., Hatim, M.Z., Indreica, A., Jansen, F., Pauchard, A. ... Bruelheide, H. (2022). Global patterns of vascular plant alpha diversity.
dc.relation.referencesBohn, F.J. & Huth, A. (2017). The importance of forest structure to biodiversity–productivity relationships.
dc.relation.referencesLiang, J., Crowther, T.W., Picard, N., Wiser, S., Zhou, M., Alberti, G., Schulze, E., McGuire, A.D., Bozzato, F., Pretzsch, H., de-Miguel, S., Paquette, A., Hérault, B., Scherer-Lorenzen, M., Barrett, C.B., Glick, H.B., Hengeveld, G.M., Nabuurs, G., Pfautsch, S. ... Reich, P.B. (2016). Positive biodiversity-productivity relationship predominant in global forests.
dc.relation.referencesTer Steege, H., Pitman, N.C.A., Do Amaral, I.L., De Souza Coelho, L., De Almeida Matos, F.D., De Andrade Lima Filho, D., Salomão, R.P., Wittmann, F., Castilho, C.V., Guevara, J.E., Veiga Carim, M.D.J., Phillips, O.L., Magnusson, W.E., Sabatier, D., Revilla, J.D.C., Molino, J., Irume, M.V., Martins, M.P., Da Silva Guimarães, J.R. ... Melgaço, K. (2023). Mapping density, diversity and species-richness of the Amazon tree flora.
dc.relation.referencesRaven, P.H., Gereau, R.E., Phillipson, P.B., Chatelain, C., Jenkins, C.N., & Ulloa Ulloa, C. (2020). The distribution of biodiversity richness in the tropics.
dc.relation.referencesBass, M.S., Finer, M., Jenkins, C.N., Kreft, H., Cisneros-Heredia, D.F., McCracken, S.F., Pitman, N.C.A., English, P.H., Swing, K., Villa, G., Di Fiore, A., Voigt, C.C., & Kunz, T.H. (2010). Global Conservation Significance of Ecuador's Yasuní National Park.
dc.relation.referencesFAO, (2024). The State of the World’s Forests 2024 – Forest-sector innovations towards a more sustainable future. FAO.
dc.relation.referencesEcosystems and human well-being: synthesis (2005). Island Press.
dc.relation.referencesUlloa Ulloa, C., Acevedo-Rodríguez, P., Beck, S., Belgrano, M.J., Bernal, R., Berry, P.E., Brako, L., Celis, M., Davidse, G., Forzza, R.C., Gradstein, S.R., Hokche, O., León, B., León-Yánez, S., Magill, R.E., Neill, D.A., Nee, M., Raven, P.H., Stimmel, H. ... Jørgensen, P.M. (2017). An integrated assessment of the vascular plant species of the Americas.
dc.relation.referencesStein, A., Gerstner, K., & Kreft, H. (2014). Environmental heterogeneity as a universal driver of species richness across taxa, biomes and spatial scales.
dc.relation.referencesAntonelli, A. & Sanmartín, I. (2011). Why are there so many plant species in the Neotropics?
dc.relation.referencesPettorelli, N., Wegmann, M., Skidmore, A., Mücher, S., Dawson, T.P., Fernandez, M., Lucas, R., Schaepman, M.E., Wang, T., O'Connor, B., Jongman, R.H., Kempeneers, P., Sonnenschein, R., Leidner, A.K., Böhm, M., He, K.S., Nagendra, H., Dubois, G., Fatoyinbo, T. ... Geller, G.N. (2016). Framing the concept of satellite remote sensing essential biodiversity variables: challenges and future directions.
dc.relation.referencesVihervaara, P., Auvinen, A., Mononen, L., Törmä, M., Ahlroth, P., Anttila, S., Böttcher, K., Forsius, M., Heino, J., Heliölä, J., Koskelainen, M., Kuussaari, M., Meissner, K., Ojala, O., Tuominen, S., Viitasalo, M., & Virkkala, R. (2017). How Essential Biodiversity Variables and remote sensing can help national biodiversity monitoring.
dc.relation.referencesPereira, H.M., Ferrier, S., Walters, M., Geller, G.N., Jongman, R.H.G., Scholes, R.J., Bruford, M.W., Brummitt, N., Butchart, S.H.M., Cardoso, A.C., Coops, N.C., Dulloo, E., Faith, D.P., Freyhof, J., Gregory, R.D., Heip, C., Höft, R., Hurtt, G., Jetz, W. ... Wegmann, M. (2013). Essential Biodiversity Variables.
dc.relation.referencesFagua, J. & Jantz, P. (2025). Maps of forest vertical structure for Colombia, a megadiverse country. Zenodo.
dc.relation.referencesBernal, R., Gradstein, R., & Celis, M. (Eds.). (2019). Catálogo de plantas y líquenes de Colombia. Instituto de Ciencias Naturales, Universidad Nacional de Colombia.
dc.relation.referencesBGCI (2021). State of the World’s Trees. BGCI, Richmond, UK.
dc.relation.referencesColPlantA (2025). Useful Plants of Colombia. Facilitated by the Royal Botanic Gardens, Kew. Available at: https://colplanta.org/ (Consulted, 24 November 2025)
dc.relation.referencesErwin, T. L. (1982). Tropical forests: Their richness in Coleoptera and other arthropod species. The Coleopterists Bulletin, 36(1), 74–75.
dc.relation.referencesEtter A., Andrade A., Saavedra K., Cortés, J., Amaya P. & Aróvalo, P. (2020). Colombia un país en riesgo ecológico: una aplicación de la Lista Roja de Ecosistemas a sus ecosistemas terrestres continentales. 60pp. Centro Editorial Javeriano, Bogotá.
dc.relation.referencesGentry, A.H. (1991). La región amazónica. Págs.53-64 en: VilIegas, G. & E. Hurtado. (eds.). Selva húmeda de Colombia. 2ed. Villegas Editores, Bogotá.
dc.relation.referencesInstituto de Hidrología, Meteorología y Estudios Ambientales - Ideam (2017). Monitoreo y seguimiento al fenómeno de la deforestación en Colombia. http://www.ideam.gov.co/web/ecosistemas/deforestacion-colombia
dc.relation.referencesInstituto de Hidrología, Meteorología y Estudios Ambientales - Ideam (2024). Informe del estado del ambiente y los recursos naturales renovables - 2023. https://www.ideam.gov.co/sala-de-prensa/informes/Estado-del-ambiente-y-los-recursos-naturales
dc.relation.referencesInfante Betancour, J.A. (2016). Plantas con flores de la Amazonia colombiana: riqueza, endemismo y representatividad en la gran región amazónica (Doctoral dissertation). Universidad Nacional de Colombia. Bogotá, D.C.
dc.relation.referencesLondoño Vega, A. C. & Alvarez Dávila, E. (1997). Composición florística de dos bosques (Tierra firme y varzea) en la región de Araracuara, Amazonia Colombiana. Caldasia, 19(3), 431–463. https://revistas.unal.edu.co/index.php/cal/article/view/17444
dc.relation.referencesMcGarigal K., Cushman, S.A. & Ene, E. (2023). FRAGSTATS v4: Spatial Pattern Analysis Program for Categorical Maps. Computer software program produced by the authors; available at the following web site: https://www.fragstats.org
dc.relation.referencesMapBiomas Colombia. (2025). Proyecto MapBiomas Colombia – Colección de mapas anuales de cobertura y uso del suelo. Fundación Gaia Amazonas, RAISG y Red MapBiomas. Recuperado el 24 noviembre 2025, de https://colombia.mapbiomas.org/
dc.relation.referencesPires, J.M., & Prance, G.T. (1985). The vegetation types of the brazilian amazon. Págs.109-145 en: Prance,G.T.& T.E. Lovejoy. (eds.). Amazonia. Pergamon Press, Oxford.
dc.relation.referencesPizano, C., & García, H. (Eds.). (2014). El bosque seco tropical en Colombia. Instituto de Investigación de Recursos Biológicos Alexander von Humboldt (IAvH). Bogotá, D.C., Colombia.
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.agrovocBiodiversidadspa
dc.subject.agrovocbiodiversityeng
dc.subject.agrovocTeledetecciónspa
dc.subject.agrovocremote sensingeng
dc.subject.agrovocClimatologíaspa
dc.subject.agrovocclimatologyeng
dc.subject.ddc500 - Ciencias naturales y matemáticasspa
dc.subject.proposalEstructura ecosistémicaspa
dc.subject.proposalFragmentación del paisajespa
dc.subject.proposalMARSspa
dc.subject.proposalPerfil horizontalspa
dc.subject.proposalPerfil verticalspa
dc.subject.proposalRandom Forestspa
dc.subject.proposalRiquezaspa
dc.subject.proposalEcosystem structureeng
dc.subject.proposalHorizontal profileeng
dc.subject.proposalLandscape fragmentationeng
dc.subject.proposalMARSeng
dc.subject.proposalRandom Foresteng
dc.subject.proposalRichnesseng
dc.subject.proposalVertical profileeng
dc.titleRelación entre la estructura forestal y la diversidad alfa en bosques de Colombia : aproximaciones en la Amazonia y el Caribespa
dc.title.translatedRelationship between forest structure and alpha diversity in Colombian forests : approaches from the Amazon and the Caribbeaneng
dc.typeTrabajo de grado - Maestría
dc.type.coarhttp://purl.org/coar/resource_type/c_bdcc
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.contentText
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.redcolhttp://purl.org/redcol/resource_type/TM
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dcterms.audience.professionaldevelopmentInvestigadores
dcterms.audience.professionaldevelopmentEstudiantes
dcterms.audience.professionaldevelopmentEspecializada
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2

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