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13 results on '"Zambrano, Angelica M Almeyda"'

1. Bringing the forest back : Restoration priorities in Colombia

Author

Williams, Brooke A., López-Cubillos, Sofía, Ochoa-Quintero, Jose Manuel, Crouzeilles, Renato, Villa-Piñeros, Marcelo, Cubides, Paola Johanna Isaacs, Schmoeller, Marina, Marin, Wilmer, Tedesco, Anazelia, Bastos, Diego, Suárez-Castro, Andrés Felipe, Jiménez, Luis Hernando Romero, Broadbent, Eben N., Zambrano, Angelica M. Almeyda, Vincent, Jeffrey R., Yi, Yuanyuan, Chazdon, Robin L., Watson, James E. M., Urbano, Elkin Alexi Noguera, Rodriguez, Cristian Alexander Cruz, and Beyer, Hawthorne L.

Published
2024

2. Dominance and rarity in tree communities across the globe: Patterns, predictors and threats

Author

Hordijk, Iris, Bialic‐Murphy, Lalasia, Lauber, Thomas, Routh, Devin, Poorter, Lourens, Rivers, Malin C, Steege, Hans ter, Liang, Jingjing, Reich, Peter B, de‐Miguel, Sergio, Nabuurs, Gert‐Jan, Gamarra, Javier GP, Chen, Han YH, Zhou, Mo, Wiser, Susan K, Pretzsch, Hans, Paquette, Alain, Picard, Nicolas, Hérault, Bruno, Bastin, Jean‐Francois, Alberti, Giorgio, Abegg, Meinrad, Yao, Yves C Adou, Zambrano, Angelica M Almeyda, Alvarado, Braulio V, Alvarez‐Davila, Esteban, Alvarez‐Loayza, Patricia, Alves, Luciana F, Ammer, Christian, Antón‐Fernández, Clara, Araujo‐Murakami, Alejandro, Arroyo, Luzmila, Avitabile, Valerio, Corredor, Gerardo A Aymard, Baker, Timothy, Banki, Olaf, Barroso, Jorcely, Bastian, Meredith L, Birigazzi, Luca, Birnbaum, Philippe, Bitariho, Robert, Boeckx, Pascal, Bongers, Frans, Bouriaud, Olivier, Brancalion, Pedro HS, Brandl, Susanne, Brienen, Roel, Broadbent, Eben N, Bruelheide, Helge, Bussotti, Filippo, Gatti, Roberto Cazzolla, Cesar, Ricardo G, Cesljar, Goran, Chazdon, Robin, Chisholm, Chelsea, Cienciala, Emil, Clark, Connie J, Clar, David B, Colletta, Gabriel, Coomes, David, Valverde, Fernando Cornejo, Corral‐Rivas, Jose J, Crim, Philip, Cumming, Jonathan, Dayanandan, Selvadurai, de Gasper, André L, Decuyper, Mathieu, Derroire, Géraldine, DeVries, Ben, Djordjevic, Ilija, Iêda, Amaral, Dourdain, Aurélie, Dolezal, Jiri, Obiang, Nestor Laurier Engone, Enquist, Brian, Eyre, Teresa, Fandohan, Adandé Belarmain, Fayle, Tom M, Ferreira, Leandro V, Feldpausch, Ted R, Finér, Leena, Fischer, Markus, Fletcher, Christine, Frizzera, Lorenzo, Gianelle, Damiano, Glick, Henry B, Harris, David, Hector, Andrew, Hemp, Andreas, Hengeveld, Geerten, Herbohn, John, Hillers, Annika, Coronado, Eurídice N Honorio, Hui, Cang, Cho, Hyunkook, Ibanez, Thomas, Jung, Ilbin, Imai, Nobuo, Jagodzinski, Andrzej M, and Jaroszewicz, Bogdan

Subjects
Environmental Sciences, Ecological Applications, Ecology, Biological Sciences, Machine Learning and Artificial Intelligence, Life on Land, Life Below Water
Abstract

Aim: Ecological and anthropogenic factors shift the abundances of dominant and rare tree species within local forest communities, thus affecting species composition and ecosystem functioning. To inform forest and conservation management it is important to understand the drivers of dominance and rarity in local tree communities. We answer the following research questions: (1) What are the patterns of dominance and rarity in tree communities? (2) Which ecological and anthropogenic factors predict these patterns? And (3) what is the extinction risk of locally dominant and rare tree species?. Location: Global. Time period: 1990–2017. Major taxa studied: Trees. Methods: We used 1.2 million forest plots and quantified local tree dominance as the relative plot basal area of the single most dominant species and local rarity as the percentage of species that contribute together to the least 10% of plot basal area. We mapped global community dominance and rarity using machine learning models and evaluated the ecological and anthropogenic predictors with linear models. Extinction risk, for example threatened status, of geographically widespread dominant and rare species was evaluated. Results: Community dominance and rarity show contrasting latitudinal trends, with boreal forests having high levels of dominance and tropical forests having high levels of rarity. Increasing annual precipitation reduces community dominance, probably because precipitation is related to an increase in tree density and richness. Additionally, stand age is positively related to community dominance, due to stem diameter increase of the most dominant species. Surprisingly, we find that locally dominant and rare species, which are geographically widespread in our data, have an equally high rate of elevated extinction due to declining populations through large-scale land degradation. Main conclusions: By linking patterns and predictors of community dominance and rarity to extinction risk, our results suggest that also widespread species should be considered in large-scale management and conservation practices.

Published
2024

3. Liana optical traits increase tropical forest albedo and reduce ecosystem productivity

Author

Meunier, Félicien, Visser, Marco D, Shiklomanov, Alexey, Dietze, Michael C, Q., J Antonio Guzmán, Sanchez‐Azofeifa, G Arturo, De Deurwaerder, Hannes PT, Moorthy, Sruthi M Krishna, Schnitzer, Stefan A, Marvin, David C, Longo, Marcos, Liu, Chang, Broadbent, Eben N, Zambrano, Angelica M Almeyda, Muller‐Landau, Helene C, Detto, Matteo, and Verbeeck, Hans

Subjects
Biological Sciences, Ecology, Bayes Theorem, Carbon Cycle, Ecosystem, Forests, Tropical Climate, ecosystem demography model, forest albedo, forest energy balance, PROSPECT-5, radiative transfer models, structural parasitism, tropical lianas, Environmental Sciences, Biological sciences, Earth sciences, Environmental sciences
Abstract

Lianas are a key growth form in tropical forests. Their lack of self-supporting tissues and their vertical position on top of the canopy make them strong competitors of resources. A few pioneer studies have shown that liana optical traits differ on average from those of colocated trees. Those trait discrepancies were hypothesized to be responsible for the competitive advantage of lianas over trees. Yet, in the absence of reliable modelling tools, it is impossible to unravel their impact on the forest energy balance, light competition, and on the liana success in Neotropical forests. To bridge this gap, we performed a meta-analysis of the literature to gather all published liana leaf optical spectra, as well as all canopy spectra measured over different levels of liana infestation. We then used a Bayesian data assimilation framework applied to two radiative transfer models (RTMs) covering the leaf and canopy scales to derive tropical tree and liana trait distributions, which finally informed a full dynamic vegetation model. According to the RTMs inversion, lianas grew thinner, more horizontal leaves with lower pigment concentrations. Those traits made the lianas very efficient at light interception and significantly modified the forest energy balance and its carbon cycle. While forest albedo increased by 14% in the shortwave, light availability was reduced in the understorey (-30% of the PAR radiation) and soil temperature decreased by 0.5°C. Those liana-specific traits were also responsible for a significant reduction of tree (-19%) and ecosystem (-7%) gross primary productivity (GPP) while lianas benefited from them (their GPP increased by +27%). This study provides a novel mechanistic explanation to the increase in liana abundance, new evidence of the impact of lianas on forest functioning, and paves the way for the evaluation of the large-scale impacts of lianas on forest biogeochemical cycles.

Published
2022

4. Co-limitation towards lower latitudes shapes global forest diversity gradients

Author

Liang, Jingjing, Gamarra, Javier G. P., Picard, Nicolas, Zhou, Mo, Pijanowski, Bryan, Jacobs, Douglass F., Reich, Peter B., Crowther, Thomas W., Nabuurs, Gert-Jan, de-Miguel, Sergio, Fang, Jingyun, Woodall, Christopher W., Svenning, Jens-Christian, Jucker, Tommaso, Bastin, Jean-Francois, Wiser, Susan K., Slik, Ferry, Hérault, Bruno, Alberti, Giorgio, Keppel, Gunnar, Hengeveld, Geerten M., Ibisch, Pierre L., Silva, Carlos A., ter Steege, Hans, Peri, Pablo L., Coomes, David A., Searle, Eric B., von Gadow, Klaus, Jaroszewicz, Bogdan, Abbasi, Akane O., Abegg, Meinrad, Yao, Yves C. Adou, Aguirre-Gutiérrez, Jesús, Zambrano, Angelica M. Almeyda, Altman, Jan, Alvarez-Dávila, Esteban, Álvarez-González, Juan Gabriel, Alves, Luciana F., Amani, Bienvenu H. K., Amani, Christian A., Ammer, Christian, Ilondea, Bhely Angoboy, Antón-Fernández, Clara, Avitabile, Valerio, Aymard, Gerardo A., Azihou, Akomian F., Baard, Johan A., Baker, Timothy R., Balazy, Radomir, Bastian, Meredith L., Batumike, Rodrigue, Bauters, Marijn, Beeckman, Hans, Benu, Nithanel Mikael Hendrik, Bitariho, Robert, Boeckx, Pascal, Bogaert, Jan, Bongers, Frans, Bouriaud, Olivier, Brancalion, Pedro H. S., Brandl, Susanne, Brearley, Francis Q., Briseno-Reyes, Jaime, Broadbent, Eben N., Bruelheide, Helge, Bulte, Erwin, Catlin, Ann Christine, Cazzolla Gatti, Roberto, César, Ricardo G., Chen, Han Y. H., Chisholm, Chelsea, Cienciala, Emil, Colletta, Gabriel D., Corral-Rivas, José Javier, Cuchietti, Anibal, Cuni-Sanchez, Aida, Dar, Javid A., Dayanandan, Selvadurai, de Haulleville, Thales, Decuyper, Mathieu, Delabye, Sylvain, Derroire, Géraldine, DeVries, Ben, Diisi, John, Do, Tran Van, Dolezal, Jiri, Dourdain, Aurélie, Durrheim, Graham P., Obiang, Nestor Laurier Engone, Ewango, Corneille E. N., Eyre, Teresa J., Fayle, Tom M., Feunang, Lethicia Flavine N., Finér, Leena, Fischer, Markus, Fridman, Jonas, Frizzera, Lorenzo, de Gasper, André L., Gianelle, Damiano, Glick, Henry B., Gonzalez-Elizondo, Maria Socorro, Gorenstein, Lev, Habonayo, Richard, Hardy, Olivier J., Harris, David J., Hector, Andrew, Hemp, Andreas, Herold, Martin, Hillers, Annika, Hubau, Wannes, Ibanez, Thomas, Imai, Nobuo, Imani, Gerard, Jagodzinski, Andrzej M., Janecek, Stepan, Johannsen, Vivian Kvist, Joly, Carlos A., Jumbam, Blaise, Kabelong, Banoho L. P. R., Kahsay, Goytom Abraha, Karminov, Viktor, Kartawinata, Kuswata, Kassi, Justin N., Kearsley, Elizabeth, Kennard, Deborah K., Kepfer-Rojas, Sebastian, Khan, Mohammed Latif, Kigomo, John N., Kim, Hyun Seok, Klauberg, Carine, Klomberg, Yannick, Korjus, Henn, Kothandaraman, Subashree, Kraxner, Florian, Kumar, Amit, Kuswandi, Relawan, Lang, Mait, Lawes, Michael J., Leite, Rodrigo V., Lentner, Geoffrey, Lewis, Simon L., Libalah, Moses B., Lisingo, Janvier, López-Serrano, Pablito Marcelo, Lu, Huicui, Lukina, Natalia V., Lykke, Anne Mette, Maicher, Vincent, Maitner, Brian S., Marcon, Eric, Marshall, Andrew R., Martin, Emanuel H., Martynenko, Olga, Mbayu, Faustin M., Mbuvi, Musingo T. E., Meave, Jorge A., Merow, Cory, Miscicki, Stanislaw, Moreno, Vanessa S., Morera, Albert, Mukul, Sharif A., Müller, Jörg C., Murdjoko, Agustinus, Nava-Miranda, Maria Guadalupe, Ndive, Litonga Elias, Neldner, Victor J., Nevenic, Radovan V., Nforbelie, Louis N., Ngoh, Michael L., N’Guessan, Anny E., Ngugi, Michael R., Ngute, Alain S. K., Njila, Emile Narcisse N., Nyako, Melanie C., Ochuodho, Thomas O., Oleksyn, Jacek, Paquette, Alain, Parfenova, Elena I., Park, Minjee, Parren, Marc, Parthasarathy, Narayanaswamy, Pfautsch, Sebastian, Phillips, Oliver L., Piedade, Maria T. F., Piotto, Daniel, Pollastrini, Martina, Poorter, Lourens, Poulsen, John R., Poulsen, Axel Dalberg, Pretzsch, Hans, Rodeghiero, Mirco, Rolim, Samir G., Rovero, Francesco, Rutishauser, Ervan, Sagheb-Talebi, Khosro, Saikia, Purabi, Sainge, Moses Nsanyi, Salas-Eljatib, Christian, Salis, Antonello, Schall, Peter, Schepaschenko, Dmitry, Scherer-Lorenzen, Michael, Schmid, Bernhard, Schöngart, Jochen, Šebeň, Vladimír, Sellan, Giacomo, Selvi, Federico, Serra-Diaz, Josep M., Sheil, Douglas, Shvidenko, Anatoly Z., Sist, Plinio, Souza, Alexandre F., Stereńczak, Krzysztof J., Sullivan, Martin J. P., Sundarapandian, Somaiah, Svoboda, Miroslav, Swaine, Mike D., Targhetta, Natalia, Tchebakova, Nadja, Trethowan, Liam A., Tropek, Robert, Mukendi, John Tshibamba, Umunay, Peter Mbanda, Usoltsev, Vladimir A., Vaglio Laurin, Gaia, Valentini, Riccardo, Valladares, Fernando, van der Plas, Fons, Vega-Nieva, Daniel José, Verbeeck, Hans, Viana, Helder, Vibrans, Alexander C., Vieira, Simone A., Vleminckx, Jason, Waite, Catherine E., Wang, Hua-Feng, Wasingya, Eric Katembo, Wekesa, Chemuku, Westerlund, Bertil, Wittmann, Florian, Wortel, Verginia, Zawiła-Niedźwiecki, Tomasz, Zhang, Chunyu, Zhao, Xiuhai, Zhu, Jun, Zhu, Xiao, Zhu, Zhi-Xin, Zo-Bi, Irie C., and Hui, Cang

Published
2022
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7. Habitat preference in the critically endangered yellow-tailed woolly monkey (Lagothrix flavicauda) at La Esperanza, Peru

Author

Almeyda Zambrano, Sandra L., Broadbent, Eben N., Shanee, Sam, Shanee, Noga, Deluycker, Anneke, Steinberg, Michael, Ford, Scott A., Hernandez Jaramillo, Alma, Fernandez-Hilario, Robin, Lagos Castillo, Carolina, Zambrano, Angelica M. Almeyda, Almeyda Zambrano, Sandra L., Broadbent, Eben N., Shanee, Sam, Shanee, Noga, Deluycker, Anneke, Steinberg, Michael, Ford, Scott A., Hernandez Jaramillo, Alma, Fernandez-Hilario, Robin, Lagos Castillo, Carolina, and Zambrano, Angelica M. Almeyda

Published
2019

8. Monitoring The Brazilian Savanna with lidar and RGB Sensors Onboard Remotely Piloted Aircraft Systems

Author

Ferreira, Manuel Eduardo, primary, Oliveira-da-Costa, Marcelo, additional, Alves, Leomar R., additional, Albuquerque, Rafael W., additional, Broadbent, Eben, additional, de Almeida, Danilo R. A., additional, Avino, Felipe Spina, additional, Cezare, Cassio H. G., additional, Zambrano, Angelica M. Almeyda, additional, and Wilkinson, Ben, additional

Published
2019
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9. Unveiling spatial and temporal heterogeneity of a tropical forest canopy using high-resolution NIRv, FCVI, and NIRvrad from UAS observations.

Author

Merrick, Trina, Pau, Stephanie, Detto, Matteo, Broadbent, Eben North, Bohlman, Stephanie, Still, Christopher J., and Zambrano, Angelica M. Almeyda

Subjects
TROPICAL forests, FOREST canopies, AIRBORNE lasers, NORMALIZED difference vegetation index, CROWNS (Botany), DRONE aircraft
Abstract

Presented here for the first time are emerging vegetation indicators: near-infrared reflectance (NIRv) of vegetation, the fluorescence correction vegetation index (FCVI), and radiance (NIRvrad) of vegetation, for a tropical forest canopy calculated using UAS-based hyperspectral data. Fine-scale tropical forest heterogeneity represented by NIRv, FCVI, and NIRvrad, is investigated using unmanned aerial vehicle data and eddy covariance-based gross primary productivity estimates. By exploiting near-infrared signals, emerging vegetation indicators captured the greatest spatiotemporal variability, followed by the enhanced vegetation index (EVI), then the normalized difference vegetation index (NDVI), which saturates. Wavelet analyses showed the dominant spatial variability of all indicators is driven by tree clusters and larger-than-tree-crown size gaps (not individual tree crowns or leaf clumps), but emerging indices and EVI captured structural information at smaller spatial scales (~50 m) than NDVI (~90 m) and lidar (~70 m). As predicted in previous studies, we confirm that NIRv and FCVI are virtually identical for a dense green canopy despite the differences in how these indices were derived. Furthermore, we show that NIRvrad, which does not require separate irradiance measurements, correlated most strongly with gross primary productivity and photosynthetically active radiation. These emerging indicators, which are related to canopy structure and the radiation regime of vegetation canopies are promising tools to improve understanding of tropical forest canopy structure and function. [ABSTRACT FROM AUTHOR]

Published
2021
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10. Recent deforestation drove the spike in Amazonian fires.

Author

Cardil, Adrián, de-Miguel, Sergio, Silva, Carlos A, Reich, Peter B, Calkin, David, Brancalion, Pedro H S, Vibrans, Alexander C, Gamarra, Javier G P, Zhou, M, Pijanowski, Bryan C, Hui, Cang, Crowther, Thomas W, Hérault, Bruno, Piotto, Daniel, Salas-Eljatib, Christian, Broadbent, Eben North, Zambrano, Angelica M Almeyda, Picard, Nicolas, Aragăo, Luiz E O C, and Bastin, Jean-Francois

Published
2020
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12. Aboveground Biomass Estimation in Amazonian Tropical Forests: a Comparison of Aircraft- and GatorEye UAV-borne LiDAR Data in the Chico Mendes Extractive Reserve in Acre, Brazil.

Author

d'Oliveira, Marcus V. N., Broadbent, Eben N., Oliveira, Luis C., Almeida, Danilo R. A., Papa, Daniel A., Ferreira, Manuel E., Zambrano, Angelica M. Almeyda, Silva, Carlos A., Avino, Felipe S., Prata, Gabriel A., Mello, Ricardo A., Figueiredo, Evandro O., Jorge, Lúcio A. de Castro, Junior, Leomar, Albuquerque, Rafael W., Brancalion, Pedro H. S., Wilkinson, Ben, and Oliveira-da-Costa, Marcelo

Subjects
BIOMASS estimation, LIDAR, TROPICAL forests, FOREST surveys, FOREST biomass, FOREST density, DIGITAL elevation models, DRONE aircraft
Abstract

Tropical forests are often located in difficult-to-access areas, which make high-quality forest structure information difficult and expensive to obtain by traditional field-based approaches. LiDAR (acronym for Light Detection And Ranging) data have been used throughout the world to produce time-efficient and wall-to-wall structural parameter estimates for monitoring in native and commercial forests. In this study, we compare products and aboveground biomass (AGB) estimations from LiDAR data acquired using an aircraft-borne system in 2015 and data collected by the unmanned aerial vehicle (UAV)-based GatorEye Unmanned Flying Laboratory in 2017 for ten forest inventory plots located in the Chico Mendes Extractive Reserve in Acre state, southwestern Brazilian Amazon. The LiDAR products were similar and comparable among the two platforms and sensors. Principal differences between derived products resulted from the GatorEye system flying lower and slower and having increased returns per second than the aircraft, resulting in a much higher point density overall (11.3 ± 1.8 vs. 381.2 ± 58 pts/m2). Differences in ground point density, however, were much smaller among the systems, due to the larger pulse area and increased number of returns per pulse of the aircraft system, with the GatorEye showing an approximately 50% higher ground point density (0.27 ± 0.09 vs. 0.42 ± 0.09). The LiDAR models produced by both sensors presented similar results for digital elevation models and estimated AGB. Our results validate the ability for UAV-borne LiDAR sensors to accurately quantify AGB in dense high-leaf-area tropical forests in the Amazon. We also highlight new possibilities using the dense point clouds of UAV-borne systems for analyses of detailed crown structure and leaf area density distribution of the forest interior. [ABSTRACT FROM AUTHOR]

Published
2020
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13. Global restoration opportunities in tropical rainforest landscapes.

Author

Brancalion, Pedro H. S., Niamir, Aidin, Broadbent, Eben, Crouzeilles, Renato, Barros, Felipe S. M., Zambrano, Angelica M. Almeyda, Baccini, Alessandro, Aronson, James, Goetz, Scott, Reid, J. Leighton, Strassburg, Bernardo B. N., Wilson, Sarah, and Chazdon, Robin L.

Subjects
*RAIN forests, *FOREST restoration, *FOREST conservation, *BIODIVERSITY conservation, *CLIMATE change mitigation, *BIOLOGICAL adaptation, *WATER security
Abstract

The article informs on a study conducted for analysing global restoration opportunities in tropical rainforest landscapes. It mentions that concentrating restoration investments in landscapes with high benefits and feasibility would maximize the potential to mitigate anthropogenic impacts and improve human well-being. It also informs on identifying restoration opportunities in areas that combine high potential for socioenvironmental benefits with high restoration feasibility.

Published
2019
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