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5 results on '"Stropp, J."'

1. Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology.

Author

Pos E, de Souza Coelho L, de Andrade Lima Filho D, Salomão RP, Amaral IL, de Almeida Matos FD, Castilho CV, Phillips OL, Guevara JE, de Jesus Veiga Carim M, López DC, Magnusson WE, Wittmann F, Irume MV, Martins MP, Sabatier D, da Silva Guimarães JR, Molino JF, Bánki OS, Piedade MTF, Pitman NCA, Mendoza AM, Ramos JF, Hawes JE, Almeida EJ, Barbosa LF, Cavalheiro L, Dos Santos MCV, Luize BG, de Leão Novo EMM, Vargas PN, Silva TSF, Venticinque EM, Manzatto AG, Reis NFC, Terborgh J, Casula KR, Coronado ENH, Montero JC, Marimon BS, Marimon-Junior BH, Feldpausch TR, Duque A, Baraloto C, Arboleda NC, Engel J, Petronelli P, Zartman CE, Killeen TJ, Vasquez R, Mostacedo B, Assis RL, Schöngart J, Castellanos H, de Medeiros MB, Simon MF, Andrade A, Camargo JL, Demarchi LO, Laurance WF, Laurance SGW, de Sousa Farias E, Lopes MA, Magalhães JLL, Nascimento HEM, de Queiroz HL, Aymard GAC, Brienen R, Revilla JDC, Costa FRC, Quaresma A, Vieira ICG, Cintra BBL, Stevenson PR, Feitosa YO, Duivenvoorden JF, Mogollón HF, Ferreira LV, Comiskey JA, Draper F, de Toledo JJ, Damasco G, Dávila N, García-Villacorta R, Lopes A, Vicentini A, Noronha JC, Barbosa FR, de Sá Carpanedo R, Emilio T, Levis C, de Jesus Rodrigues D, Schietti J, Souza P, Alonso A, Dallmeier F, Gomes VHF, Lloyd J, Neill D, de Aguiar DPP, Araujo-Murakami A, Arroyo L, Carvalho FA, de Souza FC, do Amaral DD, Feeley KJ, Gribel R, Pansonato MP, Barlow J, Berenguer E, Ferreira J, Fine PVA, Guedes MC, Jimenez EM, Licona JC, Mora MCP, Peres CA, Zegarra BEV, Cerón C, Henkel TW, Maas P, Silveira M, Stropp J, Thomas-Caesar R, Baker TR, Daly D, Dexter KG, Householder JE, Huamantupa-Chuquimaco I, Pennington T, Paredes MR, Fuentes A, Pena JLM, Silman MR, Tello JS, Chave J, Valverde FC, Di Fiore A, Hilário RR, Phillips JF, Rivas-Torres G, van Andel TR, von Hildebrand P, Barbosa EM, de Matos Bonates LC, Doza HPD, Fonty É, Gómez RZ, Gonzales T, Gonzales GPG, Guillaumet JL, Hoffman B, Junqueira AB, Malhi Y, de Andrade Miranda IP, Pinto LFM, Prieto A, Rudas A, Ruschel AR, Silva N, Vela CIA, Vos VA, Zent EL, Zent S, Albuquerque BW, Cano A, Correa DF, Costa JBP, Flores BM, Holmgren M, Nascimento MT, Oliveira AA, Ramirez-Angulo H, Rocha M, Scudeller VV, Sierra R, Tirado M, Umaña MN, van der Heijden G, Torre EV, Vriesendorp C, Wang O, Young KR, Reategui MAA, Baider C, Balslev H, Cárdenas S, Casas LF, Farfan-Rios W, Ferreira C, Linares-Palomino R, Mendoza C, Mesones I, Torres-Lezama A, Giraldo LEU, Villarroel D, Zagt R, Alexiades MN, Garcia-Cabrera K, Hernandez L, Milliken W, Cuenca WP, Pansini S, Pauletto D, Arevalo FR, Sampaio AF, Sandoval EHV, Gamarra LV, Boenisch G, Kattge J, Kraft N, Levesley A, Melgaço K, Pickavance G, Poorter L, and Ter Steege H

Subjects
Entropy, Forests, Plants, Ecology, Tropical Climate, Ecosystem, Biodiversity
Abstract

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics., (© 2023. The Author(s).)

Published
2023
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2. Relationships between species richness and ecosystem services in Amazonian forests strongly influenced by biogeographical strata and forest types.

Author

Steur G, Ter Steege H, Verburg RW, Sabatier D, Molino JF, Bánki OS, Castellanos H, Stropp J, Fonty É, Ruysschaert S, Galbraith D, Kalamandeen M, van Andel TR, Brienen R, Phillips OL, Feeley KJ, Terborgh J, and Verweij PA

Subjects
Biodiversity, Carbon, Trees, Ecosystem, Forests
Abstract

Despite increasing attention for relationships between species richness and ecosystem services, for tropical forests such relationships are still under discussion. Contradicting relationships have been reported concerning carbon stock, while little is known about relationships concerning timber stock and the abundance of non-timber forest product producing plant species (NTFP abundance). Using 151 1-ha plots, we related tree and arborescent palm species richness to carbon stock, timber stock and NTFP abundance across the Guiana Shield, and using 283 1-ha plots, to carbon stock across all of Amazonia. We analysed how environmental heterogeneity influenced these relationships, assessing differences across and within multiple forest types, biogeographic regions and subregions. Species richness showed significant relationships with all three ecosystem services, but relationships differed between forest types and among biogeographical strata. We found that species richness was positively associated to carbon stock in all biogeographical strata. This association became obscured by variation across biogeographical regions at the scale of Amazonia, resembling a Simpson's paradox. By contrast, species richness was weakly or not significantly related to timber stock and NTFP abundance, suggesting that species richness is not a good predictor for these ecosystem services. Our findings illustrate the importance of environmental stratification in analysing biodiversity-ecosystem services relationships., (© 2022. The Author(s).)

Published
2022
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3. Evolutionary diversity is associated with wood productivity in Amazonian forests.

Author

Coelho de Souza F, Dexter KG, Phillips OL, Pennington RT, Neves D, Sullivan MJP, Alvarez-Davila E, Alves Á, Amaral I, Andrade A, Aragao LEOC, Araujo-Murakami A, Arets EJMM, Arroyo L, Aymard C GA, Bánki O, Baraloto C, Barroso JG, Boot RGA, Brienen RJW, Brown F, Camargo JLC, Castro W, Chave J, Cogollo A, Comiskey JA, Cornejo-Valverde F, da Costa AL, de Camargo PB, Di Fiore A, Feldpausch TR, Galbraith DR, Gloor E, Goodman RC, Gilpin M, Herrera R, Higuchi N, Honorio Coronado EN, Jimenez-Rojas E, Killeen TJ, Laurance S, Laurance WF, Lopez-Gonzalez G, Lovejoy TE, Malhi Y, Marimon BS, Marimon-Junior BH, Mendoza C, Monteagudo-Mendoza A, Neill DA, Vargas PN, Peñuela Mora MC, Pickavance GC, Pipoly JJ 3rd, Pitman NCA, Poorter L, Prieto A, Ramirez F, Roopsind A, Rudas A, Salomão RP, Silva N, Silveira M, Singh J, Stropp J, Ter Steege H, Terborgh J, Thomas-Caesar R, Umetsu RK, Vasquez RV, Célia-Vieira I, Vieira SA, Vos VA, Zagt RJ, and Baker TR

Subjects
Forests, Phylogeny, Tropical Climate, Ecosystem, Wood
Abstract

Higher levels of taxonomic and evolutionary diversity are expected to maximize ecosystem function, yet their relative importance in driving variation in ecosystem function at large scales in diverse forests is unknown. Using 90 inventory plots across intact, lowland, terra firme, Amazonian forests and a new phylogeny including 526 angiosperm genera, we investigated the association between taxonomic and evolutionary metrics of diversity and two key measures of ecosystem function: aboveground wood productivity and biomass storage. While taxonomic and phylogenetic diversity were not important predictors of variation in biomass, both emerged as independent predictors of wood productivity. Amazon forests that contain greater evolutionary diversity and a higher proportion of rare species have higher productivity. While climatic and edaphic variables are together the strongest predictors of productivity, our results show that the evolutionary diversity of tree species in diverse forest stands also influences productivity. As our models accounted for wood density and tree size, they also suggest that additional, unstudied, evolutionarily correlated traits have significant effects on ecosystem function in tropical forests. Overall, our pan-Amazonian analysis shows that greater phylogenetic diversity translates into higher levels of ecosystem function: tropical forest communities with more distantly related taxa have greater wood productivity.

Published
2019
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4. Drought sensitivity of the Amazon rainforest.

Author

Phillips OL, Aragão LE, Lewis SL, Fisher JB, Lloyd J, López-González G, Malhi Y, Monteagudo A, Peacock J, Quesada CA, van der Heijden G, Almeida S, Amaral I, Arroyo L, Aymard G, Baker TR, Bánki O, Blanc L, Bonal D, Brando P, Chave J, de Oliveira AC, Cardozo ND, Czimczik CI, Feldpausch TR, Freitas MA, Gloor E, Higuchi N, Jiménez E, Lloyd G, Meir P, Mendoza C, Morel A, Neill DA, Nepstad D, Patiño S, Peñuela MC, Prieto A, Ramírez F, Schwarz M, Silva J, Silveira M, Thomas AS, Steege HT, Stropp J, Vásquez R, Zelazowski P, Alvarez Dávila E, Andelman S, Andrade A, Chao KJ, Erwin T, Di Fiore A, Honorio C E, Keeling H, Killeen TJ, Laurance WF, Peña Cruz A, Pitman NC, Núñez Vargas P, Ramírez-Angulo H, Rudas A, Salamão R, Silva N, Terborgh J, and Torres-Lezama A

Subjects
Atmosphere, Brazil, Carbon, Carbon Dioxide, Climate, South America, Tropical Climate, Biomass, Droughts, Ecosystem, Trees growth & development
Abstract

Amazon forests are a key but poorly understood component of the global carbon cycle. If, as anticipated, they dry this century, they might accelerate climate change through carbon losses and changed surface energy balances. We used records from multiple long-term monitoring plots across Amazonia to assess forest responses to the intense 2005 drought, a possible analog of future events. Affected forest lost biomass, reversing a large long-term carbon sink, with the greatest impacts observed where the dry season was unusually intense. Relative to pre-2005 conditions, forest subjected to a 100-millimeter increase in water deficit lost 5.3 megagrams of aboveground biomass of carbon per hectare. The drought had a total biomass carbon impact of 1.2 to 1.6 petagrams (1.2 x 10(15) to 1.6 x 10(15) grams). Amazon forests therefore appear vulnerable to increasing moisture stress, with the potential for large carbon losses to exert feedback on climate change.

Published
2009
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5. Tree mode of death and mortality risk factors across Amazon forests

Author

Lily Rodriguez Bayona, Zorayda Restrepo Correa, Marisol Toledo, Ben Hur Marimon Junior, José Luís Camargo, Ima Célia Guimarães Vieira, Georgia Pickavance, Pieter A. Zuidema, Christopher Baraloto, Javier Silva Espejo, Maria Cristina Peñuela-Mora, Nadir Pallqui Camacho, Wendeson Castro, Simon L. Lewis, Susan G. Laurance, Marcos Silveira, Karina Liana Lisboa Melgaço Ladvocat, René G. A. Boot, Simone Aparecida Vieira, Isau Huamantupa-Chuquimaco, Lourens Poorter, Eurídice N. Honorio Coronado, Jeanneth Villalobos Cayo, Armando Torres-Lezama, David A. Neill, Eric Arets, Thomas E. Lovejoy, Gerardo Flores Llampazo, Benoit Burban, Carlos A. Quesada, Kuo-Jung Chao, Casimiro Mendoza, Hans ter Steege, Gabriela Lopez-Gonzalez, Paulo S. Morandi, Adriana Prieto, Juliana Stropp, Eliana Jimenez-Rojas, James Singh, Jon Lloyd, Timothy R. Baker, Jérôme Chave, Ana Andrade, Patrick Meir, Roderick Zagt, Fernando Cornejo Valverde, Joey Talbot, Marielos Peña-Claros, Luzmila Arroyo, Nigel C. A. Pitman, Frans Bongers, Michel Baisie, Plínio Barbosa de Camargo, Alejandro Araujo-Murakami, Varun Swamy, Julio Serrano, Raquel Thomas, Aurora Levesley, Emanuel Gloor, Julie Peacock, David W. Galbraith, Nallaret Davila Cardozo, Adriane Esquivel-Muelbert, Jeanne Houwing-Duistermaat, Timothy J. Killeen, Yadvinder Malhi, Rodolfo Vásquez Martínez, Abel Monteagudo-Mendoza, Edmar Almeida de Oliveira, Natalino Silva, Rafael de Paiva Salomão, Hirma Ramírez-Angulo, Jorcely Barroso, Adriano José Nogueira Lima, Simone Matias Reis, Emilio Vilanova Torre, William F. Laurance, Guido Pardo, James A. Comiskey, Agustín Rudas, Sophie Fauset, Martin J. P. Sullivan, Everton Cristo de Almeida, Luiz E. O. C. Aragão, Rafael Herrera, Percy Núñez Vargas, John Terborgh, Victor Chama Moscoso, Ted R. Feldpausch, Aurélie Dourdain, Damien Bonal, Beatriz Schwantes Marimon, Gerardo A. Aymard C, Esteban Alvarez Dávila, Peter J. Van Der Meer, Luis Valenzuela Gamarra, Terry L. Erwin, Lilian Blanc, Anthony Di Fiore, Antonio Carlos Lola da Costa, Haiyan Liu, Vincent A. Vos, Foster Brown, Roel J. W. Brienen, Patricia Alvarez Loayza, Oliver L. Phillips, Clément Stahl, Niro Higuchi, John Pipoly, Jhon del Aguila Pasquel, Thomas A. M. Pugh, Maxime Rejou-Machain, Geertje M. F. van der Heijden, Peter van der Hout, University of Leeds, Plymouth University, SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Evolution et Diversité Biologique (EDB), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ecologie des forêts de Guyane (UMR ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), European Project: 291585,EC:FP7:ERC,ERC-2011-ADG_20110209,T-FORCES(2012), University of Plymouth, Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Esquivel-Muelbert A., Phillips O.L., Brienen R.J.W., Fauset S., Sullivan M.J.P., Baker T.R., Chao K.-J., Feldpausch T.R., Gloor E., Higuchi N., Houwing-Duistermaat J., Lloyd J., Liu H., Malhi Y., Marimon B., Marimon Junior B.H., Monteagudo-Mendoza A., Poorter L., Silveira M., Torre E.V., Davila E.A., del Aguila Pasquel J., Almeida E., Loayza P.A., Andrade A., Aragao L.E.O.C., Araujo-Murakami A., Arets E., Arroyo L., Aymard C G.A., Baisie M., Baraloto C., Camargo P.B., Barroso J., Blanc L., Bonal D., Bongers F., Boot R., Brown F., Burban B., Camargo J.L., Castro W., Moscoso V.C., Chave J., Comiskey J., Valverde F.C., da Costa A.L., Cardozo N.D., Di Fiore A., Dourdain A., Erwin T., Llampazo G.F., Vieira I.C.G., Herrera R., Honorio Coronado E., Huamantupa-Chuquimaco I., Jimenez-Rojas E., Killeen T., Laurance S., Laurance W., Levesley A., Lewis S.L., Ladvocat K.L.L.M., Lopez-Gonzalez G., Lovejoy T., Meir P., Mendoza C., Morandi P., Neill D., Nogueira Lima A.J., Vargas P.N., de Oliveira E.A., Camacho N.P., Pardo G., Peacock J., Pena-Claros M., Penuela-Mora M.C., Pickavance G., Pipoly J., Pitman N., Prieto A., Pugh T.A.M., Quesada C., Ramirez-Angulo H., de Almeida Reis S.M., Rejou-Machain M., Correa Z.R., Bayona L.R., Rudas A., Salomao R., Serrano J., Espejo J.S., Silva N., Singh J., Stahl C., Stropp J., Swamy V., Talbot J., ter Steege H., Terborgh J., Thomas R., Toledo M., Torres-Lezama A., Gamarra L.V., van der Heijden G., van der Meer P., van der Hout P., Martinez R.V., Vieira S.A., Cayo J.V., Vos V., Zagt R., Zuidema P., Galbraith D., University of St Andrews. School of Geography & Sustainable Development, and Systems Ecology

Subjects
0106 biological sciences, Chemistry(all), Software_GENERAL, Bos- en Landschapsecologie, General Physics and Astronomy, Forests, 01 natural sciences, Amazonegebied, Carbon sink, Trees, Growth–survival trade-off, Risk Factors, Tropical climate, Forest and Landscape Ecology, Biomass, lcsh:Science, Biomass (ecology), GE, Multidisciplinary, Ecology, Amazon rainforest, Bomen, Mortality rate, food and beverages, risk factors, mortality, trees, PE&RC, Tropical ecology, Tree (data structure), population characteristics, Vegetatie, Bos- en Landschapsecologie, InformationSystems_MISCELLANEOUS, Brazil, geographic locations, GE Environmental Sciences, Environmental Monitoring, Carbon Sequestration, Science, Physics and Astronomy(all), Models, Biological, 010603 evolutionary biology, General Biochemistry, Genetics and Molecular Biology, Article, Tree mortality, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Amazonia, Tropische bossen, parasitic diseases, Forest ecology, Life Science, Bosecologie en Bosbeheer, Ecosystem, Author Correction, Vegetatie, Proportional Hazards Models, Tropical Climate, Vegetation, Biochemistry, Genetics and Molecular Biology(all), DAS, social sciences, General Chemistry, Carbon Dioxide, 15. Life on land, Forest Ecology and Forest Management, Sterfte, lcsh:Q, Vegetation, Forest and Landscape Ecology, 010606 plant biology & botany
Abstract

The carbon sink capacity of tropical forests is substantially affected by tree mortality. However, the main drivers of tropical tree death remain largely unknown. Here we present a pan-Amazonian assessment of how and why trees die, analysing over 120,000 trees representing > 3800 species from 189 long-term RAINFOR forest plots. While tree mortality rates vary greatly Amazon-wide, on average trees are as likely to die standing as they are broken or uprooted—modes of death with different ecological consequences. Species-level growth rate is the single most important predictor of tree death in Amazonia, with faster-growing species being at higher risk. Within species, however, the slowest-growing trees are at greatest risk while the effect of tree size varies across the basin. In the driest Amazonian region species-level bioclimatic distributional patterns also predict the risk of death, suggesting that these forests are experiencing climatic conditions beyond their adaptative limits. These results provide not only a holistic pan-Amazonian picture of tree death but large-scale evidence for the overarching importance of the growth–survival trade-off in driving tropical tree mortality., Tree mortality has been shown to be the dominant control on carbon storage in Amazon forests, but little is known of how and why Amazon forest trees die. Here the authors analyse a large Amazon-wide dataset, finding that fast-growing species face greater mortality risk, but that slower-growing individuals within a species are more likely to die, regardless of size.

Published
2020
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