{"id":97,"date":"2024-05-17T20:08:57","date_gmt":"2024-05-17T20:08:57","guid":{"rendered":"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/?page_id=97"},"modified":"2026-04-01T15:32:53","modified_gmt":"2026-04-01T15:32:53","slug":"research","status":"publish","type":"page","link":"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/research\/","title":{"rendered":"Research"},"content":{"rendered":"<style>.kb-row-layout-id97_dc585d-05 > .kt-row-column-wrap{align-content:start;}:where(.kb-row-layout-id97_dc585d-05 > .kt-row-column-wrap) > .wp-block-kadence-column{justify-content:start;}.kb-row-layout-id97_dc585d-05 > .kt-row-column-wrap{column-gap:var(--global-kb-gap-md, 2rem);row-gap:var(--global-kb-gap-md, 2rem);padding-top:var(--global-kb-spacing-xl, 4rem);padding-bottom:var(--global-kb-spacing-xl, 4rem);grid-template-columns:minmax(0, 1fr);}.kb-row-layout-id97_dc585d-05{background-image:url('https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/07\/ezgif-3-24420970cc-2.jpg');background-size:cover;background-position:center center;background-attachment:scroll;background-repeat:no-repeat;}.kb-row-layout-id97_dc585d-05 > .kt-row-layout-overlay{opacity:0.27;background-color:#000000;}@media all and (max-width: 1024px){.kb-row-layout-id97_dc585d-05 > .kt-row-column-wrap{grid-template-columns:minmax(0, 1fr);}}@media all and (max-width: 767px){.kb-row-layout-id97_dc585d-05 > .kt-row-column-wrap{grid-template-columns:minmax(0, 1fr);}}<\/style><div class=\"kb-row-layout-wrap kb-row-layout-id97_dc585d-05 alignnone kt-row-has-bg fullwidth-block wp-block-kadence-rowlayout\"><div class=\"kt-row-layout-overlay kt-row-overlay-normal\"><\/div><div class=\"kt-row-column-wrap kt-has-1-columns kt-row-layout-equal kt-tab-layout-inherit kt-mobile-layout-row kt-row-valign-top\">\n<style>.kadence-column97_fd79d4-dd > .kt-inside-inner-col,.kadence-column97_fd79d4-dd > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column97_fd79d4-dd > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column97_fd79d4-dd > .kt-inside-inner-col{flex-direction:column;}.kadence-column97_fd79d4-dd > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column97_fd79d4-dd > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column97_fd79d4-dd{position:relative;}@media all and (max-width: 1024px){.kadence-column97_fd79d4-dd > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}@media all and (max-width: 767px){.kadence-column97_fd79d4-dd > .kt-inside-inner-col{flex-direction:column;justify-content:center;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column97_fd79d4-dd\"><div class=\"kt-inside-inner-col\"><style>.wp-block-kadence-advancedheading.kt-adv-heading97_07082a-20, .wp-block-kadence-advancedheading.kt-adv-heading97_07082a-20[data-kb-block=\"kb-adv-heading97_07082a-20\"]{text-align:center;font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading97_07082a-20 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading97_07082a-20[data-kb-block=\"kb-adv-heading97_07082a-20\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading97_07082a-20 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading97_07082a-20[data-kb-block=\"kb-adv-heading97_07082a-20\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<h1 class=\"kt-adv-heading97_07082a-20 wp-block-kadence-advancedheading has-white-color has-text-color\" data-kb-block=\"kb-adv-heading97_07082a-20\">Research<\/h1>\n<\/div><\/div>\n\n<\/div><\/div>\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"468\" height=\"584\" src=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/image.png\" alt=\"\" class=\"wp-image-598\" srcset=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/image.png 468w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/image-240x300.png 240w\" sizes=\"auto, (max-width: 468px) 100vw, 468px\" \/><figcaption class=\"wp-element-caption\"><em>Seeds of selected woody plant species in the family Fabaceae (legumes) that inhabit Barro Colorado Island, Panama. The largest seeds pictured are approximately 6 cm long. Seed photos: Steve Paton. Digital arrangement: Ricardo Chong.<\/em><\/figcaption><\/figure>\n<\/div>\n\n\n<h2 class=\"wp-block-heading has-text-color has-link-color wp-elements-1\" style=\"color:#172a4b\">Tropical Plant Community Ecology<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Individual tropical forests commonly contain &gt;100 tree species and &gt;50 liana (woody vine) species in an area the size of a football field, and can contain &gt;1,000 woody plant species in a square kilometer. Ecologists have long sought to understand what mechanisms prevent one or a few species from outcompeting and excluding the others. Tradeoffs in performance among spatially varying habitats and temporally varying climate conditions clearly play a role, as do interactions with specialized natural enemies that tend to disproportionately plague and disadvantage any given species in areas where it is locally more common. How do tropical woody plant species differ in their functional traits, life history strategies, performance in different environmental conditions, and interactions with natural enemies?\u2002How do these differences affect species coexistence and contribute to whole-forest function?\u2002We conduct empirical and theoretical research to address these questions, with empirical research focused on central Panama and the ForestGEO network.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-text-color has-link-color wp-elements-2\" style=\"color:#172a4b\">Selected References<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Muller-Landau, Helene C<\/strong>. and S. Joseph Wright. 2024.&nbsp;<em>The First 100 Years of Research on Barro Colorado: Plant and Ecosystem Science (Volumes 1 and 2)<\/em>. Washington, D.C.: Smithsonian Institution Scholarly Press.&nbsp;<a href=\"https:\/\/doi.org\/10.5479\/si.26048527\">https:\/\/doi.org\/10.5479\/si.26048527<\/a>&nbsp;<a href=\"https:\/\/striresearch.si.edu\/books\/bci100\/\">https:\/\/striresearch.si.edu\/books\/bci100\/<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Gora, Evan M.,&nbsp;<strong>Helene C. Muller-Landau<\/strong>, K. C. Cushman, Jeannine H. Richards, Phillip M. Bitzer, Jeffrey C. Burchfield, Pabloa Narvaez, and Stephen P. Yanoviak.&nbsp; 2025.&nbsp; How some tropical trees benefit from being struck by lightning: evidence for&nbsp;<em>Dipteryx oleifera<\/em>&nbsp;and other large-statured trees.&nbsp;&nbsp;<em>New Phytologist<\/em>&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/nph.70062\">https:\/\/doi.org\/10.1111\/nph.70062<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Jackson, Toby&nbsp;D., P. Bittencourt, J. Poffley, J. Anderson,&nbsp;<strong>Helene&nbsp;C. Muller-Landau<\/strong>, Pablo&nbsp;A. R. Ramos, L. Rowland, and D. Coomes. 2024. Wind Shapes the Growth Strategies of Trees in a Tropical&nbsp;Forest.&nbsp;<em>Ecology Letters<\/em>&nbsp;27: e14527.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/ele.14527\">https:\/\/doi.org\/10.1111\/ele.14527<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Broekman, M. J. E.,&nbsp;<strong>H. C. Muller-Landau<\/strong>, M. D. Visser, E. Jongejans, S. J. Wright, and H. de Kroon.&nbsp; 2019.&nbsp; Signs of stabilisation and stable coexistence.&nbsp;&nbsp;<em>Ecology Letters<\/em>&nbsp;22:1957-1975.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/ele.13349\">https:\/\/doi.org\/10.1111\/ele.13349<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Detto, M., and<strong>&nbsp;H. C. Muller-Landau<\/strong>.&nbsp; 2016.&nbsp; Stabilization of species coexistence in spatial models through the aggregation-segregation effect generated by local dispersal and nonspecific local interactions.&nbsp;&nbsp;<em>Theoretical Population Biology&nbsp;<\/em>112:97-108.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1016\/j.tpb.2016.08.008\">https:\/\/doi.org\/10.1016\/j.tpb.2016.08.008<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Detto, M. and&nbsp;<strong>H. C. Muller-Landau<\/strong>.&nbsp; 2016.&nbsp; Rates of formation and dissipation of clumping reveal lagged responses in tropical tree populations.&nbsp;&nbsp;<em>Ecology<\/em>&nbsp;97:1170-1181.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1890\/15-1505.1\">https:\/\/doi.org\/10.1890\/15-1505.1<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Marks, C. O.,&nbsp;<strong>H. C. Muller-Landau<\/strong>, and D. Tilman.&nbsp; 2016.&nbsp; Tree diversity, tree height and environmental harshness in eastern and western North America.&nbsp;&nbsp;<em>Ecology Letters<\/em>&nbsp;19:743-751.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/ele.12608\">https:\/\/doi.org\/10.1111\/ele.12608<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Muller-Landau, H. C.&nbsp;<\/strong>&nbsp;2010.&nbsp; The tolerance-fecundity tradeoff and the maintenance of diversity in seed size.&nbsp;&nbsp;<em>Proceedings of the National Academy of Sciences<\/em>&nbsp;107:4242-4247.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1073\/pnas.0911637107\">https:\/\/doi.org\/10.1073\/pnas.0911637107<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Larjavaara, M. and&nbsp;<strong>H. C. Muller-Landau<\/strong>.&nbsp; 2010.&nbsp; Rethinking the value of high wood density.&nbsp;&nbsp;<em>Functional Ecology<\/em>&nbsp;24:701-705.&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/j.1365-2435.2010.01698.x\">https:\/\/doi.org\/10.1111\/j.1365-2435.2010.01698.x<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Muller-Landau, Helene C.<\/strong>&nbsp; 2008.&nbsp; Colonization-related tradeoffs in tropical forests and their role in the maintenance of plant species diversity.&nbsp; Pages 182-195 in&nbsp;<em>Tropical Forest Community Ecology.<\/em>&nbsp;W. P. Carson and S. A. Schnitzer, editors. Blackwell Scientific.<\/p>\n<\/div><\/div>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"791\" src=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/bci_lidar-1-1024x791.jpg\" alt=\"\" class=\"wp-image-586\" style=\"aspect-ratio:16\/9;object-fit:cover;width:1200px\" srcset=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/bci_lidar-1-1024x791.jpg 1024w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/bci_lidar-1-300x232.jpg 300w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/bci_lidar-1-768x593.jpg 768w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/bci_lidar-1-1536x1187.jpg 1536w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/bci_lidar-1-2048x1583.jpg 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>Variation in topography (left) and canopy height (right) across Barro Colorado Island, Panama. Hillslope imagery of topography courtesy of Milton Solano. Canopy height map from Mascaro et al. 2011&nbsp;Biogeosciences<\/em><\/figcaption><\/figure>\n<\/div>\n\n\n<h2 class=\"wp-block-heading has-text-color has-link-color wp-elements-3\" style=\"color:#172a4b\">Tropical Forest Structure and Dynamics<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Mechanistic, physiologically based models can explain much of the variation in forest productivity with climate and soils, but little of the variation in mortality fluxes and biomass Tropical forests vary widely in their structure and dynamics \u2013 and thus in their carbon stocks and fluxes \u2013 even after controlling for forest age. A mechanistic understanding of this variation is critical to accurately predicting responses to global change.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\"><\/p>\n<cite>What are the patterns of variation in tropical forest structure and dynamics at local, regional, and global scales, in relation to environmental gradients, biogeography, and historical factors?&nbsp;<\/cite><\/blockquote>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\"><\/p>\n<cite>What mechanisms underly these patterns, and how can they be reproduced in vegetation models?<\/cite><\/blockquote>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\"><\/p>\n<cite>How does temporal environmental variation, including directional changes due to anthropogenic influences, affect tropical forests?<\/cite><\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We investigate these questions through empirical research in central Panama and with the&nbsp;<a href=\"https:\/\/forestgeo.si.edu\/\">ForestGEO<\/a>&nbsp;network of large-scale, tropical forest dynamics plots, together with modelling studies parameterized with and evaluated against empirical datasets. Research in the&nbsp;<a href=\"https:\/\/stri.si.edu\/facility\/barro-colorado\">Barro Colorado Nature Monument<\/a>&nbsp;and nearby Soberania National Park addresses the roles of topography and soils. While research in central Panama more broadly spans a regional rainfall gradient and extensive variation in soils.&nbsp;The broader ForestGEO network encompasses wide variation in climate, soils, disturbance regimes, and biogeographic realm.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-text-color has-link-color wp-elements-4\" style=\"color:#172a4b\">Selected References<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Gora, Evan M, Ian R. McGregor,&nbsp;<strong>Helene C. Muller-Landau<\/strong>, Jeffrey C. Burchfield, K. C. Cushman, Vanessa E. Rubio, Gisele Biem Mori, Martin J. P. Sullivan, Matthew W. Chmielewski, and Adriane Esquivel-Muelbert. 2025. Storms Are an Important Driver of Change in Tropical Forests.&nbsp;<em>Ecology Letters<\/em>&nbsp;28: e70157.&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/ele.70157\">https:\/\/doi.org\/10.1111\/ele.70157<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Muller-Landau, Helene C.<\/strong>, Camille Piponiot, Rolando P\u00e9rez, Salomon Aguilar, Suzanne Lao, David Mitre, and Richard Condit. 2024. Forest Biomass Carbon Stocks and Fluxes in a Broader Context: Insights and Opportunities Associated with the Central Panama Plot Network. Chapter 54 in&nbsp;<em>The First 100 Years of Research on Barro Colorado: Plant and Ecosystem Science<\/em>, ed. H. C. Muller-Landau and S. J. Wright, pp. 487-498. Washington, D.C.: Smithsonian Institution Scholarly Press.&nbsp;<a href=\"http:\/\/doi.org\/10.5479\/si.26880790\">http:\/\/doi.org\/10.5479\/si.26880790<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Piponiot, C.<\/strong>, K. J. Anderson-Teixeira, S. J. Davies, D. Allen, N. A. Bourg, D. F. R. P. Burslem, D. C\u00e1rdenas, C.-H. Chang-Yang, G. Chuyong, S. Cordell, H. S. Dattaraja, \u00c1. Duque, S. Ediriweera, C. Ewango, Z. Ezedin, J. Filip, C. P. Giardina, R. Howe, C.-F. Hsieh, S. P. Hubbell, F. M. Inman-Narahari, A. Itoh, D. Jan\u00edk, D. Kenfack, K. Kr\u00e1l, J. A. Lutz, J.-R. Makana, S. M. McMahon, W. McShea, X. Mi, M. Bt. Mohamad, V. Novotn\u00fd, M. J. O\u2019Brien, R. Ostertag, G. Parker, R. P\u00e9rez, H. Ren, G. Reynolds, M. D. Md Sabri, L. Sack, A. Shringi, S.-H. Su, R. Sukumar, I. F. Sun, H. S. Suresh, D. W. Thomas, J. Thompson, M. Uriarte, J. Vandermeer, Y. Wang, I. M. Ware, G. D. Weiblen, T. J. S. Whitfeld, A. Wolf, T. L. Yao, M. Yu, Z. Yuan, J. K. Zimmerman, D. Zuleta, and&nbsp;<strong>H. C. Muller-Landau<\/strong>. 2022. Distribution of biomass dynamics in relation to tree size in forests across the world.&nbsp;<em>New Phytologist<\/em>&nbsp;234: 1664-1677.&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/nph.17995\">https:\/\/doi.org\/10.1111\/nph.17995<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Muller-Landau, H. C., K. C. Cushman, E. E. Arroyo<\/strong>, I. Martinez Cano, K. J. Anderson-Teixeira, and<strong>&nbsp;B. Backiel<\/strong>. 2021. Patterns and mechanisms of spatial variation in tropical forest productivity, woody residence time, and biomass.&nbsp;<em>New Phytologist<\/em>&nbsp;229: 3065-3087.&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/nph.17084\">https:\/\/doi.org\/10.1111\/nph.17084<\/a>.&nbsp;<em>Invited Tansley review.<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Rutishauser, E.<\/strong>, S. J. Wright, R. Condit, S. P. Hubbell, S. J. Davies, and&nbsp;<strong>H. C. Muller-Landau.<\/strong>&nbsp; 2020.&nbsp; Testing for changes in biomass dynamics in large-scale forest datasets.&nbsp;&nbsp;<em>Global Change Biology&nbsp;<\/em>26:1485-1498.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/gcb.14833\">https:\/\/doi.org\/10.1111\/gcb.14833<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Detto, M.,<\/strong>&nbsp;<strong>H. C. Muller-Landau,&nbsp;<\/strong>J. Mascaro, and G. P. Asner.&nbsp; 2013.&nbsp; Hydrological networks and associated topographic variation as templates for the spatial organization of tropical forest vegetation.&nbsp;&nbsp;<em>PLOS ONE<\/em>&nbsp;8(10):e76296.&nbsp;<a href=\"https:\/\/doi.org\/10.1371\/journal.pone.0076296\">https:\/\/doi.org\/10.1371\/journal.pone.0076296<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Mascaro, J.,<\/strong>&nbsp;G. P. Asner,&nbsp;<strong>H. C. Muller-Landau,&nbsp;<\/strong>M. van Breugel, J. Hall, and K. Dahlin. 2011. Controls over aboveground forest carbon density on Barro Colorado Island, Panama.&nbsp;&nbsp;<em>Biogeosciences<\/em>&nbsp;8:1615-1629.&nbsp;<a href=\"https:\/\/doi.org\/10.5194\/bg-8-1615-2011\">https:\/\/doi.org\/10.5194\/bg-8-1615-2011<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Muller-Landau, H. C.,&nbsp;<\/strong>R. S. Condit, K. E. Harms, C. O. Marks, S. C. Thomas, S. Bunyavejchewin, G. Chuyong, L. Co, S. Davies, R. Foster, S. Gunatilleke, N. Gunatilleke, T. Hart, S. P. Hubbell, A. Itoh, A. R. Kassim, D. Kenfack, J. V. LaFrankie, D. Lagunzad, H. S. Lee, E. Losos, J.-R. Makana, T. Ohkubo, C. Samper, R. Sukumar, I.-F. Sun, N. Supardi M. N., S. Tan, D. Thomas, J. Thompson, R. Valencia, M. I. Vallejo, G. Villa Mu\u00f1oz, T. Yamakura, J. K. Zimmerman, H. S. Dattaraja, S. Esufali, P. Hall, F. He, C. Hernandez, S. Kiratiprayoon, H. S. Suresh, C. Wills, and P. Ashton. 2006. Comparing tropical forest tree size distributions with the predictions of metabolic ecology and equilibrium models.&nbsp;<em>Ecology Letters<\/em>&nbsp;9:589-602.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/j.1461-0248.2006.00915.x\">https:\/\/doi.org\/10.1111\/j.1461-0248.2006.00915.x<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Muller-Landau, H. C.,&nbsp;<\/strong>R. S. Condit, J. Chave, S. C. Thomas, S. A. Bohlman, S. Bunyavejchewin, S. Davies, R. Foster, S. Gunatilleke, N. Gunatilleke, K. E. Harms, T. Hart, S. P. Hubbell, A. Itoh, A. R. Kassim, J. V. LaFrankie, H. S. Lee, E. Losos, J.-R. Makana, T. Ohkubo, R. Sukumar, I.-F. Sun, N. Supardi M. N., S. Tan, J. Thompson, R. Valencia, G. Villa Mu\u00f1oz, C. Wills, T. Yamakura, G. Chuyong, H. S. Dattaraja, S. Esufali, P. Hall, C. Hernandez, D. Kenfack, S. Kiratiprayoon, H. S. Suresh, D. Thomas, M. I. Vallejo, and P. Ashton. 2006. Testing metabolic ecology theory for allometric scaling of tree size, growth, and mortality in tropical forests.&nbsp;<em>Ecology Letters<\/em>&nbsp;9:575-588.&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/j.1461-0248.2006.00904.x\">https:\/\/doi.org\/10.1111\/j.1461-0248.2006.00904.x<\/a><\/p>\n<\/div><\/div>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"682\" src=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/07\/1e39830d-d1f9-47e4-8c5c-50de6fd18d8b-1024x682.jpg\" alt=\"\" class=\"wp-image-880\" style=\"aspect-ratio:16\/9;object-fit:cover;width:1200px\" srcset=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/07\/1e39830d-d1f9-47e4-8c5c-50de6fd18d8b-1024x682.jpg 1024w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/07\/1e39830d-d1f9-47e4-8c5c-50de6fd18d8b-300x200.jpg 300w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/07\/1e39830d-d1f9-47e4-8c5c-50de6fd18d8b-768x512.jpg 768w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/07\/1e39830d-d1f9-47e4-8c5c-50de6fd18d8b-1536x1024.jpg 1536w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/07\/1e39830d-d1f9-47e4-8c5c-50de6fd18d8b.jpg 2000w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>Lianas (woody vines) on and near a host tree on Barro Colorado Island, Panama.<\/em><\/figcaption><\/figure>\n<\/div>\n\n\n<h2 class=\"wp-block-heading has-text-color has-link-color wp-elements-5\" style=\"color:#172a4b\">Lianas and Vines<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Lianas (woody climbing plants) and vines (nonwoody climbing plants) vary widely in abundance among forests. Their abundance is critically important to forest structure and dynamics, because trees infested with lianas and vines grow more slowly and have higher mortality rates.&nbsp; Liana abundance and diversity is particularly high in many tropical forests.&nbsp; What are the patterns, mechanisms, and consequences of variation in liana abundance among forests? &nbsp;&nbsp;We are addressing these questions through a combination of theoretical and empirical research.&nbsp; Our theoretical work spans from very simple models of liana-tree interactions to demographic vegetation models.&nbsp; Our empirical analyses draw on long-term datasets on tropical tree demography and liana load, as well as large databases of plant functional traits.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-text-color has-link-color wp-elements-6\" style=\"color:#172a4b\">Selected References<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Muller-Landau, H. C.,<\/strong>&nbsp;and S. W. Pacala. 2020. What determines the abundance of lianas and vines? In&nbsp;<em>Unsolved Problems in Ecology<\/em>, ed. A. Dobson, D. Tilman and R. Holt, pp. 239-264. Princeton, NJ: Princeton University Press.&nbsp;<em>Recognized with the Smithsonian Secretary\u2019s Research Prize.<\/em>&nbsp;<a href=\"https:\/\/doi.org\/10.2307\/j.ctvs9fh2n.23\">https:\/\/doi.org\/10.2307\/j.ctvs9fh2n.23<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a><strong>Muller-Landau, H. C.<\/strong>&nbsp;<\/a>and M. D. Visser.&nbsp; 2019.&nbsp; How do lianas and vines influence competitive differences and niche differences among tree species? Concepts and a case study in a tropical forest.&nbsp;&nbsp;<em>J. Ecology<\/em>&nbsp;107:1469-1481.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/1365-2745.13119\">https:\/\/doi.org\/10.1111\/1365-2745.13119<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Visser, M. D., H. C. Muller-Landau<\/strong>, S. A. Schnitzer, H. de Kroon, E. Jongejans, and S. J. Wright. 2018. A host-parasite model explains variation in liana infestation among co-occurring tree species.&nbsp;<em>Journal of Ecology&nbsp;<\/em>106:2435-2445.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/1365-2745.12997\">https:\/\/doi.org\/10.1111\/1365-2745.12997<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Visser, M. D.<\/strong>, S. A. Schnitzer,&nbsp;<strong>H. C. Muller-Landau<\/strong>, E. Jongejans, H. de Kroon, L. S. Comita, S. P. Hubbell, and S. J. Wright.&nbsp; 2018.&nbsp; Tree species vary widely in their tolerance for liana infestation: a case study of differential host response to generalist parasites.&nbsp;<em>Journal of Ecology&nbsp;<\/em>106:781-792.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/1365-2745.12815\">https:\/\/doi.org\/10.1111\/1365-2745.12815<\/a><\/p>\n<\/div><\/div>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"682\" src=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/mg_4625-1024x682.jpg\" alt=\"\" class=\"wp-image-610\" style=\"aspect-ratio:16\/9;object-fit:cover;width:1200px\" srcset=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/mg_4625-1024x682.jpg 1024w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/mg_4625-300x200.jpg 300w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/mg_4625-768x512.jpg 768w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/mg_4625-1536x1024.jpg 1536w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/mg_4625.jpg 2000w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading has-text-color has-link-color wp-elements-7\" style=\"color:#172a4b\">Landscape-scale Research Enabled with Drones<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Drones (unoccupied aerial vehicles) now make it possible to easily and frequently take aerial photos and collect other types of data over large areas. &nbsp;Since 2014, we have been using drones to monitor tropical forests in Panama. This method enables us to monitor forests at high temporal resolution and over large areas, and provides detailed information on the crowns of canopy trees, which account for the majority of photosynthesis and biomass. We are currently monitoring tropical forest dynamics and phenology (leafing, flowering, and fruiting) of individual trees on the 50 ha forest dynamics plot on Barro Colorado Island at high temporal resolution by collecting 3-cm-resolution imagery every week. (Weekly collection began in early 2023; monthly data collection in 2014.)\u2002We are evaluating landscape-level forest dynamics across all 1543 ha of Barro Colorado Island through annual flights collecting 20-cm resolution imagery, which became monthly in late 2023 with NSF-NERC funding to the&nbsp;<a href=\"https:\/\/www.caryinstitute.org\/science\/research-projects\/gigante-revealing-what-kills-worlds-largest-trees\">Gigante&nbsp;<\/a>project.&nbsp; Additional flights target other research sites in central Panama.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">KC Cushman and Helene Muller-Landau lead a tropical forest&nbsp;<a href=\"https:\/\/atfs-dwg.github.io\/\">Drones Working Group<\/a>&nbsp;in association with the&nbsp;<a href=\"https:\/\/www.alliancetropicalforestscience.net\/\">Alliance for Tropical Forest Science<\/a>&nbsp;to share experience and knowledge on how to collect and analyze drone-acquired imagery and data for investigation of&nbsp;tropical&nbsp;forest structure, dynamics, composition, and\/or function.&nbsp; Longer term, we hope to facilitate multi-site collaborative studies that investigate similarities and differences across sites, and establish standardized methods for drone data collection.&nbsp; We envision building a community of practice for&nbsp;tropical&nbsp;forest researchers currently working with or hoping to work with drone data in the future.&nbsp;Anyone can join the group email list by filling out the form at&nbsp;<a href=\"https:\/\/forms.office.com\/g\/3yPDrJfDth\">https:\/\/forms.office.com\/g\/3yPDrJfDth<\/a>&nbsp;See our&nbsp;<a href=\"https:\/\/atfs-dwg.github.io\/\">web site<\/a>&nbsp;for more information.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-text-color has-link-color wp-elements-8\" style=\"color:#172a4b\">Selected References<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Park, John Y., Jeremy W. Lichstein,&nbsp;<strong>Helene C. Muller-Landau<\/strong>, S. Joseph Wright, and Stephanie A. Bohlman. 2025. Interspecific variation in leaf phenology and its relationship with plant traits in a seasonal tropical forest.&nbsp;<em>Functional Ecology<\/em>&nbsp;40: 433-450.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/1365-2435.70240\">https:\/\/doi.org\/10.1111\/1365-2435.70240<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Araujo, Raquel Fernandes, Evan M. Gora, Carlos H. S. Celes<\/strong>, Stephen P. Yanoviak, and&nbsp;<strong>Helene C. Muller-Landau.&nbsp;<\/strong>2025. Quantifying patterns of lightning-caused canopy disturbances via integration of drone imagery and field surveys.&nbsp;<em>Biotropica<\/em>&nbsp;57: e70083.&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/btp.70083\">https:\/\/doi.org\/10.1111\/btp.70083<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Lee, C. K. F., G. Song,&nbsp;<strong>H. C. Muller-Landau<\/strong>, S. Wu, S. J. Wright, K. C. Cushman, R. F. Araujo, S. Bohlman, Y. Zhao, Z. Lin, Z. Sun, P. C. Y. Cheng, M. K.-P. Ng, and J. Wu. 2023. Cost-effective and accurate monitoring of flowering across multiple tropical tree species over two years with a time series of high-resolution drone imagery and deep learning.&nbsp;<em>ISPRS Journal of Photogrammetry and Remote Sensing<\/em>, 201: 92-103.&nbsp;<a href=\"https:\/\/doi.org\/10.1016\/j.isprsjprs.2023.05.022\">https:\/\/doi.org\/10.1016\/j.isprsjprs.2023.05.022<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Cushman, K. C.<\/strong>, M. Detto,&nbsp;<strong>M. Garc\u00eda<\/strong>, and&nbsp;<strong>H. C. Muller-Landau<\/strong>. 2022. Soils and topography control natural disturbance rates and thereby forest structure in a lowland tropical landscape.&nbsp;<em>Ecology Letters<\/em>&nbsp;25: 1126-1138.&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/ele.13978\">https:\/\/doi.org\/10.1111\/ele.13978<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Araujo, R. F., S. Grubinger, C. H. S. Celes<\/strong>, R. I. Negr\u00f3n-Ju\u00e1rez,&nbsp;<strong>M. Garcia, J. P. Dandois<\/strong>, and&nbsp;<strong>H. C. Muller-Landau<\/strong>. 2021. Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5&nbsp;years of monthly drone data for a 50-ha plot.&nbsp;<em>Biogeosciences<\/em>&nbsp;18: 6517-6531.&nbsp;<a href=\"https:\/\/doi.org\/10.5194\/bg-18-6517-2021\">https:\/\/doi.org\/10.5194\/bg-18-6517-2021<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Park, John Y.,&nbsp;<strong>H. C. Muller-Landau<\/strong>, J. W. Lichstein, S. W. Rifai,&nbsp;<strong>J. P. Dandois<\/strong>, and S. A. Bohlman.&nbsp; 2019.&nbsp; Quantifying leaf phenology of individual trees and species in a tropical forest using unmanned aerial vehicle (UAV) images.&nbsp;&nbsp;<em>Remote Sensing&nbsp;<\/em>11:1534.&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.3390\/rs11131534\">https:\/\/doi.org\/10.3390\/rs11131534<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading has-text-color has-link-color wp-elements-9\" style=\"color:#172a4b\">Selected Datasets and Code<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>V\u00e1squez, V., M. Garc\u00eda,<\/strong> M. Hern\u00e1ndez, and <strong>H. C. Muller-Landau<\/strong>. 2023. Barro Colorado Island 50-ha plot aerial photogrammetry orthomosaics and digital surface models for 2018-2023: Globally and locally aligned time series. Smithsonian Tropical Research Institute. Smithsonian Figshare. <a href=\"https:\/\/doi.org\/10.25573\/data.24784053\">https:\/\/doi.org\/10.25573\/data.24784053<\/a> &nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Garcia, M., V. V\u00e1squez, and H. C. Muller-Landau<\/strong>. 2023. Barro Colorado whole-island aerial photogrammetry products for 2018-2023. Smithsonian Tropical Research Institute. Smithsonian Figshare. <a href=\"https:\/\/doi.org\/10.25573\/data.24757284\">https:\/\/doi.org\/10.25573\/data.24757284<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>V\u00e1squez, V., K. C. Cushman, P. Ramos, C.<\/em> Williamson, P. Villareal, L. F. Gomez Correa, and <strong>H. C. Muller-Landau<\/strong>. 2023. Barro Colorado Island 50-ha plot crown maps: manually segmented and instance segmented. Smithsonian Tropical Research Institute. Smithsonian Figshare. <a href=\"https:\/\/doi.org\/10.25573\/data.24784053\">https:\/\/doi.org\/10.25573\/data.24784053<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Cushman, K. C., H. C. Muller-Landau<\/strong>, M. Detto, and M. Garcia. 2022. Datasets for \u201cSoils and topography control natural disturbance rates and thereby forest structure in a lowland tropical landscape&#8221;. Smithsonian Tropical Research Institute. Smithsonian Figshare. <a href=\"https:\/\/doi.org\/10.25573\/data.17102600.v1\">https:\/\/doi.org\/10.25573\/data.17102600.v1<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Garcia, M., J. P. Dandois, R. F. Araujo, S. Grubinger, and <strong>H. C. Muller-Landau<\/strong>. 2021. Color orthomosaics of the 50-ha plot on Barro Colorado Island, Panama, for 2014-2019. Smithsonian Tropical Research Institute. Smithsonian Figshare. <a href=\"https:\/\/doi.org\/10.25573\/data.16869259.v2\">https:\/\/doi.org\/10.25573\/data.16869259.v2<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Garcia, M., J. P. Dandois, R. F. Araujo, S. Grubinger, and <strong>H. C. Muller-Landau.<\/strong> 2021. Surface elevation models and associated canopy height change models for the 50-ha plot on Barro Colorado Island, Panama, for 2014-2019. . Smithsonian Tropical Research Institute. Smithsonian Figshare. <a href=\"https:\/\/doi.org\/10.25573\/data.14417933\">https:\/\/doi.org\/10.25573\/data.14417933<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These datasets are part of a collection of Panama forest UAV data on Smithsonian Figshare, which can be viewed at&nbsp;<a href=\"https:\/\/smithsonian.figshare.com\/projects\/Panama_Forest_Landscapes_UAV\/115572\">https:\/\/smithsonian.figshare.com\/projects\/Panama_Forest_Landscapes_UAV\/115572<\/a><\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"556\" src=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/bci50haorthomosaic-1024x556.jpeg\" alt=\"\" class=\"wp-image-1795\" srcset=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/bci50haorthomosaic-1024x556.jpeg 1024w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/bci50haorthomosaic-300x163.jpeg 300w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/bci50haorthomosaic-768x417.jpeg 768w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/bci50haorthomosaic.jpeg 1440w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>An orthomosaic image of the 50-ha forest dynamics plot on Barro Colorado Island, Panama. The red rectangle indicates the plot boundaries.<\/em><\/figcaption><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"768\" src=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/img_1240-1024x768.jpeg\" alt=\"\" class=\"wp-image-1798\" srcset=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/img_1240-1024x768.jpeg 1024w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/img_1240-300x225.jpeg 300w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/img_1240-768x576.jpeg 768w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/img_1240.jpeg 1440w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>Image of the forest canopy on Barro Colorado Island captured by a drone. The yellow flowering tree is Handroanthus guayacan (formerly known as Tabebuia guayacan); the purple flowering tree is Jacaranda copaia.<\/em><\/figcaption><\/figure>\n<\/div><\/div>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"678\" src=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/luehea_with_flower_hires-1024x678.jpg\" alt=\"\" class=\"wp-image-1792\" srcset=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/luehea_with_flower_hires-1024x678.jpg 1024w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/luehea_with_flower_hires-300x199.jpg 300w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/luehea_with_flower_hires-768x508.jpg 768w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2026\/01\/luehea_with_flower_hires.jpg 1228w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">An example close-up drone photo taken 6 m above the canopy on Barro Colorado Island, Panama. This level of detail often enables the visible canopy plants to be identified to species.<br><\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Building the Basis for Automated Species ID<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">In 2024, we were awarded a Smithsonian path-finding grant to develop the basis for automated identification of woody plants in diverse tropical forests.\u2002Technological advances in hyperspectral imaging, laser scanning, and artificial intelligence now offer the potential for automated species identification of individual plants using remote sensing, smartphones, and\/or other tools.&nbsp; This would enable large-scale, species-specific data collection in tropical forest and empower a wider range of researchers, students, and citizen scientists to contribute.&nbsp; However, to realize this potential we need to collect high-quality training data and analyze these data to develop appropriate machine learning algorithms and determine which types or combinations of data are most useful for species identification.&nbsp;&nbsp;We are currently collecting and publishing high-quality data on hyperspectral reflectance of flowers, fruits, leaves, and bark of tree and liana species in central Panama.&nbsp; We aim to quantify within-species consistency and among-species differentiation in hyperspectral reflectance of different plant parts.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In February 2025, we partnered with NASA in the AVUELO field campaign, which involved the collection of extensive airborne hyperspectral data combined with the collection of canopy leaf samples. Collection of auxiliary data and data processing and analysis are ongoing. More information on the dedicated&nbsp;<a href=\"https:\/\/hmullerlandau.com\/avuelo\/\">AVUELO web page<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We are also collaborating with Etienne Lalibert\u00e9 (U. Montreal) to collect close-up drone photos of the tropical forest canopy, associate high-quality plant species taxonomic labels to these photos, and develop AI approaches to identifying such photos to species. This also contributes directly to our longer-term effort to map canopy trees and lianas across all of Barro Colorado Island, Panama.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Selected Publications<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Osorio-Ospina, Juan Camilo, Daria Lipsky, Lily Pitcher, Melvin Hern\u00e1ndez,&nbsp;<\/strong>and<strong>&nbsp;Helene C. Muller-Landau<\/strong>. 2026. Hyperspectral Reflectance Data for Flowers, Fruits, Bark, and Leaves of Plants on Barro Colorado Island, Panama. Smithsonian Research Data Repository.&nbsp;<a href=\"https:\/\/doi.org\/10.60635\/C3ZG9V\">https:\/\/doi.org\/10.60635\/C3ZG9V<\/a>&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Lalibert\u00e9, Etienne, Antoine Caron-Guay, Vincent Le Falher, Guillaume Tougas,&nbsp;<strong>Helene C Muller-Landau<\/strong>, Gonzalo Rivas-Torres, Thomas R Walla, Hugo Baudchon,&nbsp;<strong>M\u00e9lvin Hernandez<\/strong>, Adrian Buena\u00f1o, Anna Weber, Jeffrey Q Chambers, Jomber Chota Inuma,&nbsp;<strong>Fernando Ara\u00faz, Jorge Valdes<\/strong>, Andr\u00e9s Hern\u00e1ndez, David Brassfield, Paulo Araujo Filho,&nbsp;<strong>Vicente Vasquez<\/strong>, Adriana Simonetti, Daniel Magnabosco Marra, Caroline de Moura Vasconcelos, Jarol Fernando Vaca, Geovanny Rivadeneyra, Jos\u00e9 Illanes, Luis A Salagaje-Muela, Jefferson Gualinga.&nbsp; 2025.&nbsp; Seeing the forest and the trees: a workflow for automatic acquisition of ultra-high resolution drone photos of tropical forest canopies to support botanical and ecological studies.&nbsp;<em>bioRxiv<\/em>&nbsp;<a href=\"https:\/\/doi.org\/10.1101\/2025.09.02.673753\">https:\/\/doi.org\/10.1101\/2025.09.02.673753<\/a>&nbsp;&nbsp;<\/p>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"682\" src=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/01-0610-2-1024x682.jpg\" alt=\"\" class=\"wp-image-493\" style=\"aspect-ratio:16\/9;object-fit:cover;width:1200px\" srcset=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/01-0610-2-1024x682.jpg 1024w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/01-0610-2-300x200.jpg 300w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/01-0610-2-768x512.jpg 768w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/01-0610-2-1536x1024.jpg 1536w, https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/05\/01-0610-2.jpg 2000w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading has-text-color has-link-color wp-elements-10\" style=\"color:#172a4b\">Improving the Representation of Tropical Forests in Earth System Models<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Earth system models (ESMs) simulate the earth\u2019s climate system and its interaction with vegetation, and are used to predict the influences of policy scenarios on future atmospheric composition and climates. Among other things, these models simulate the feedbacks between tropical forests and the climate system. However, these models are currently unable to correctly capture observed spatial and temporal variation in tropical forest carbon budgets, and diverge wildly in their predictions of future responses. We are collaborating with the development teams for the FATES and LM3-PPA model to improve the representation of tropical forests in these models by building more accurate representations of key processes and improving parameter estimates, and to evaluate these models against multiple types of empirical data.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-text-color has-link-color wp-elements-11\" style=\"color:#172a4b\">Selected References<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Hanbury-Brown, A. R., T. L. Powell, <strong>H. C. Muller-Landau<\/strong>, S. J. Wright, and L. M. Kueppers. 2022.&nbsp; Simulating environmentally-sensitive tree recruitment in vegetation demographic models. <em>New Phytologist <\/em>253:78-93.&nbsp; <a href=\"https:\/\/doi.org\/10.1111\/nph.18059\">https:\/\/doi.org\/10.1111\/nph.18059<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Needham, J. F., G. Arellano, S. J. Davies, R. A. Fisher, V. Hammer, R. G. Knox, D. Mitre, <strong>H. C. Muller-Landau,<\/strong> D. Zuleta, and C. D. Koven. 2022. Tree crown damage and its effects on forest carbon cycling in a tropical forest. <em>Global Change Biology<\/em>, 28: 5560-5574. <a href=\"https:\/\/doi.org\/https:\/doi.org\/10.1111\/gcb.16318\">https:\/\/doi.org\/https:\/\/doi.org\/10.1111\/gcb.16318<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Koven, C. D., R. G. Knox, R. A. Fisher, J. Q. Chambers, B. O. Christoffersen, S. J. Davies, M. Detto, M. C. Dietze, B. Faybishenko, J. Holm, M. Huang, M. Kovenock, L. M. Kueppers, G. Lemieux, E. Massoud, N. G. McDowell, <strong>H. C. Muller-Landau<\/strong>, J. F. Needham, R. J. Norby, T. Powell, A. Rogers, S. P. Serbin, J. K. Shuman, A. L. S. Swann, C. Varadharajan, A. P. Walker, S. J. Wright, and C. Xu. 2020. Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama. <em>Biogeosciences<\/em>, 17: 3017-3044. https:\/\/doi.org\/10.5194\/bg-17-3017-2020 <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Mart\u00ednez Cano I, E. Shevliakova, S. Malyshev, S. J. Wright, M. Detto, S. W. Pacala, and <strong>H. C. Muller-Landau<\/strong>. 2020. Allometric constraints and competition enable the simulation of size structure and carbon fluxes in a dynamic vegetation model of tropical forests (LM3PPA-TV). <em>Global Change Biology<\/em>. DOI: <a href=\"https:\/\/onlinelibrary.wiley.com\/doi\/abs\/10.1111\/gcb.15188\">10.1111\/gcb.15188<\/a><\/p>\n<\/div><\/div>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading has-text-color has-link-color wp-elements-12\" style=\"color:#172a4b\">Separate web pages on other major research projects on which we are collaborating<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/geo-trees.org\/\">AVUELO<\/a>: Calibration and evaluation of hyperspectral remote sensing data for tropical forests with NASA AVIRIS<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/geo-trees.org\/\">GEOTREES<\/a>: High-accuracy ground data for satellite-derived biomass mapping<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.caryinstitute.org\/science\/research-projects\/gigante-revealing-what-kills-worlds-largest-trees\">GIGANTE<\/a> multi-site study of tropical tree mortality<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.leverhulme.ac.uk\/research-project-grants\/escaping-enemy-spatial-ecology-rainforest-tree%E2%80%93insect-interactions\">Spatial ecology of tree-insect interactions<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.caryinstitute.org\/science\/research-projects\/ecology-lightning\">Effects of lightning<\/a> on tree mortality and forest structure <\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.alliancetropicalforestscience.net\/\">Alliance for Tropical Forest Science<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/atfs-dwg.github.io\/\">ATFS Drones Working Group<\/a><\/p>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div style=\"width: 100vw;position: relative;left: 50%;right: 50%;margin-left: -50vw;margin-right: -50vw;overflow: hidden\">\n  <img decoding=\"async\" src=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/wp-content\/uploads\/sites\/205\/2024\/07\/ezgif-3-24420970cc-2.jpg\" style=\"width: 100%;height: 200px;object-fit: cover\">\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Research Tropical Plant Community Ecology Individual tropical forests commonly contain &gt;100 tree species and &gt;50 liana (woody vine) species in an area the size of a football field, and can contain &gt;1,000 woody plant species in a square kilometer. Ecologists have long sought to understand what mechanisms prevent one or a few species from outcompeting [&hellip;]<\/p>\n","protected":false},"author":61,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"_kad_blocks_custom_css":"","_kad_blocks_head_custom_js":"","_kad_blocks_body_custom_js":"","_kad_blocks_footer_custom_js":"","_exactmetrics_skip_tracking":false,"footnotes":"","_members_access_role":[],"_members_access_error":""},"class_list":["post-97","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Research - Quantitative Forest Ecology Lab | Smithsonian Tropical Research Institute<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/striresearch.si.edu\/quantitative-forest-ecology\/research\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Research - Quantitative Forest Ecology Lab | Smithsonian Tropical Research Institute\" \/>\n<meta property=\"og:description\" content=\"Research Tropical Plant Community Ecology Individual tropical forests commonly contain &gt;100 tree species and &gt;50 liana (woody vine) species in an area the size of a football field, and can contain &gt;1,000 woody plant species in a square kilometer. 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