17 results on '"Kalamandeen, M"'
Search Results
2. Reconstructing 34 Years of Fire History in the Wet, Subtropical Vegetation of Hong Kong Using Landsat
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Chan, AHY, Guizar-Coutiño, A, Kalamandeen, M, Coomes, DA, Chan, AHY [0000-0001-6740-0680], Guizar-Coutiño, A [0000-0002-3509-9624], Kalamandeen, M [0000-0001-5385-7444], Apollo - University of Cambridge Repository, Chan, Aland HY [0000-0001-6740-0680], Guizar-Coutiño, Alejandro [0000-0002-3509-9624], and Kalamandeen, Michelle [0000-0001-5385-7444]
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remote sensing ,pre-processing ,fire ,subtropical ,rainforest ,landsat ,burn severity ,time-series ,seasonal ,General Earth and Planetary Sciences - Abstract
Peer reviewed: True, Funder: Bill & Melinda Gates Foundation, Burn-area products from remote sensing provide the backbone for research in fire ecology, management, and modelling. Landsat imagery could be used to create an accurate burn-area map time series at ecologically relevant spatial resolutions. However, the low temporal resolution of Landsat has limited its development in wet tropical and subtropical regions due to high cloud cover and rapid burn-area revegetation. Here, we describe a 34-year Landsat-based burn-area product for wet, subtropical Hong Kong. We overcame technical obstacles by adopting a new LTS fire burn-area detection pipeline that (1) Automatically uniformized Landsat scenes by weighted histogram matching; (2) Estimated pixel resemblance to burn areas based on a random forest model trained on the number of days between the fire event and the date of burn-area detection; (3) Iteratively merged features created by thresholding burn-area resemblance to generate burn-area polygons with detection dates; and (4) Estimated the burn severity of burn-area pixels using a time-series compatible approach. When validated with government fire records, we found that the LTS fire product carried a low area of omission (11%) compared with existing burn-area products, such as GABAM (49%), MCD64A1 (72%), and FireCCI51 (96%) while effectively controlling commission errors. Temporally, the LTS fire pipeline dated 76.9% of burn-area polygons within two months of the actual fire event. The product represents the first Landsat-based burn-area product in wet tropical and subtropical Asia that covers the entire time series. We believe that burn-area products generated from algorithms like LTS fire will effectively bridge the gap between remote sensing and field-based studies on wet tropical and subtropical fire ecology.
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- 2023
3. Limited biomass recovery from gold mining in Amazonian forests
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Kalamandeen, M, Gloor, E, Johnson, I, Agard, S, Katow, M, Vanbrooke, A, Ashley, D, Batterman, SA, Ziv, G, Holder‐Collins, K, Phillips, OL, Brondizio, ES, Vieira, I, and Galbraith, D
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parasitic diseases - Abstract
1. Gold mining has rapidly increased across the Amazon Basin in recent years, especially in the Guiana shield, where it is responsible for >90% of total deforestation. However, the ability of forests to recover from gold mining activities remains largely unquantified. 2. Forest inventory plots were installed on recently abandoned mines in two major mining regions in Guyana, and re‐censused 18 months later, to provide the first ground‐based quantification of gold mining impacts on Amazon forest biomass recovery. 3. We found that woody biomass recovery rates on abandoned mining pits and tailing ponds are among the lowest ever recorded for tropical forests, with close to no woody biomass recovery after 3–4 years. 4. On the overburden sites (i.e. areas not mined but where excavated soil is deposited), however, above‐ground biomass recovery rates (0.4–5.4 Mg ha−1 year−1) were within the range of those recorded in other secondary forests across the Neotropics following abandonment of pastures and agricultural lands. 5. Our results suggest that forest recovery is more strongly limited by severe mining‐induced depletion of soil nutrients, especially nitrogen, than by mercury contamination, due to slowing of growth in nutrient‐stripped soils. 6. We estimate that the slow recovery rates in mining pits and ponds currently reduce carbon sequestration across Amazonian secondary forests by ~21,000 t C/year, compared to the carbon that would have accumulated following more traditional land uses such as agriculture or pasture. 7. Synthesis and applications. To achieve large‐scale restoration targets, Guyana and other Amazonian countries will be challenged to remediate previously mined lands. The recovery process is highly dependent on nitrogen availability rather than mercury contamination, affecting woody biomass regrowth. The significant recovery in overburden zones indicates that one potential active remediation strategy to promote biomass recovery may be to backfill mining pits and ponds with excavated soil.
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- 2020
4. A bird’s eye view over ecosystem services in Natura 2000 sites across Europe
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Ziv, G, Hassall, C, Bartkowski, B, Cord, AF, Kaim, A, Kalamandeen, M, Landaverde-Gonzalez, P, Melo, JLB, Seppelt, R, Shannon, C, Vaclavik, T, Zoderer, BM, and Beckmann, M
- Abstract
Recent ‘New Conservation’ approaches called for more ecosystem services (ES) emphasis in conservation. We analysed data from 3757 Natura 2000 special protection areas (SPAs) and translated positive and negative impacts listed by conservation managers into indicators of the use of nine provisioning, regulating and cultural ES. Overall, the use of ES is considered by SPA managers to affect conservation goals more negatively than positively. ES associated with livestock keeping and fodder production are recorded as having the highest fraction of positive impacts on SPAs, ranging from 88% and 78% in the Boreal biogeographic region to 20% and 6% in the Mediterranean. The use of ES varied according to dominant habitat class, highlighting the dependence of specific ES on associated ecosystem functions. For instance, fibre production was the predominant ES throughout forest habitats while crop, fodder and livestock exhibit similar patterns of dominance across agricultural landscapes. In contrast, the use of wild food and recreation activities are seen as causing mainly negative effects across all habitats. Our analysis suggests that most uses of ES result in negative effects on conservation goals. These outcomes should be considered when implementing future conservation strategies.
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- 2018
5. Evaluation of Sub-National Population Projections: a Case Study for London and the Thames Valley
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Rees, P., primary, Clark, S., additional, Wohland, P., additional, and Kalamandeen, M., additional
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- 2018
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6. A Global Analysis of Deforestation in Moist Tropical Forest Protected Areas
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Spracklen, B. D., primary, Kalamandeen, M., additional, Galbraith, D., additional, Gloor, E., additional, and Spracklen, D. V., additional
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- 2015
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7. Author Correction: One sixth of Amazonian tree diversity is dependent on river floodplains.
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Householder JE, Wittmann F, Schöngart J, Piedade MTF, Junk WJ, Latrubesse EM, Quaresma AC, Demarchi LO, de S Lobo G, Aguiar DPP, Assis RL, Lopes A, Parolin P, Leão do Amaral I, Coelho LS, de Almeida Matos FD, Lima Filho DA, Salomão RP, Castilho CV, Guevara-Andino JE, Carim MJV, Phillips OL, Cárdenas López D, Magnusson WE, Sabatier D, Revilla JDC, Molino JF, Irume MV, Martins MP, Guimarães JRDS, Ramos JF, Rodrigues DJ, Bánki OS, Peres CA, Pitman NCA, Hawes JE, Almeida EJ, Barbosa LF, Cavalheiro L, Dos Santos MCV, Luize BG, Novo EMML, Núñez Vargas P, Silva TSF, Venticinque EM, Manzatto AG, Reis NFC, Terborgh J, Casula KR, Costa FRC, Honorio Coronado EN, Monteagudo Mendoza A, Montero JC, Feldpausch TR, Aymard C GA, Baraloto C, Castaño Arboleda N, Engel J, Petronelli P, Zartman CE, Killeen TJ, Rincón LM, Marimon BS, Marimon-Junior BH, Schietti J, Sousa TR, Vasquez R, Mostacedo B, Dantas do Amaral D, Castellanos H, Medeiros MB, Simon MF, Andrade A, Camargo JL, Laurance WF, Laurance SGW, Farias ES, Lopes MA, Magalhães JLL, Mendonça Nascimento HE, Queiroz HL, Brienen R, Stevenson PR, Araujo-Murakami A, Baker TR, Cintra BBL, Feitosa YO, Mogollón HF, Noronha JC, Barbosa FR, de Sá Carpanedo R, Duivenvoorden JF, Silman MR, Ferreira LV, Levis C, Lozada JR, Comiskey JA, Draper FC, Toledo JJ, Damasco G, Dávila N, García-Villacorta R, Vicentini A, Cornejo Valverde F, Alonso A, Arroyo L, Dallmeier F, Gomes VHF, Jimenez EM, Neill D, Peñuela Mora MC, Carvalho FA, Coelho de Souza F, Feeley KJ, Gribel R, Pansonato MP, Ríos Paredes M, Barlow J, Berenguer E, Dexter KG, Ferreira J, Fine PVA, Guedes MC, Huamantupa-Chuquimaco I, Licona JC, Pennington T, Villa Zegarra BE, Vos VA, Cerón C, Fonty É, Henkel TW, Maas P, Pos E, Silveira M, Stropp J, Thomas R, Daly D, Milliken W, Pardo Molina G, Vieira ICG, Albuquerque BW, Campelo W, Emilio T, Fuentes A, Klitgaard B, Marcelo Pena JL, Souza PF, Tello JS, Vriesendorp C, Chave J, Di Fiore A, Hilário RR, Pereira LO, Phillips JF, Rivas-Torres G, van Andel TR, von Hildebrand P, Balee W, Barbosa EM, Bonates LCM, Doza HPD, Gómez RZ, Gonzales T, Gonzales GPG, Hoffman B, Junqueira AB, Malhi Y, Miranda IPA, Mozombite-Pinto LF, Prieto A, Rudas A, Ruschel AR, Silva N, Vela CIA, Zent S, Zent EL, Cano A, Carrero Márquez YA, Correa DF, Costa JBP, Flores BM, Galbraith D, Holmgren M, Kalamandeen M, Nascimento MT, Oliveira AA, Ramirez-Angulo H, Rocha M, Scudeller VV, Sierra R, Tirado M, Umaña MN, van der Heijden G, Vilanova Torre E, Ahuite Reategui MA, Baider C, Balslev H, Cárdenas S, Casas LF, Farfan-Rios W, Ferreira C, Linares-Palomino R, Mendoza C, Mesones I, Parada GA, Torres-Lezama A, Urrego Giraldo LE, Villarroel D, Zagt R, Alexiades MN, de Oliveira EA, Garcia-Cabrera K, Hernandez L, Palacios Cuenca W, Pansini S, Pauletto D, Ramirez Arevalo F, Sampaio AF, Valderrama Sandoval EH, Valenzuela Gamarra L, and Ter Steege H
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- 2024
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8. One sixth of Amazonian tree diversity is dependent on river floodplains.
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Householder JE, Wittmann F, Schöngart J, Piedade MTF, Junk WJ, Latrubesse EM, Quaresma AC, Demarchi LO, de S Lobo G, Aguiar DPP, Assis RL, Lopes A, Parolin P, Leão do Amaral I, Coelho LS, de Almeida Matos FD, Lima Filho DA, Salomão RP, Castilho CV, Guevara-Andino JE, Carim MJV, Phillips OL, Cárdenas López D, Magnusson WE, Sabatier D, Revilla JDC, Molino JF, Irume MV, Martins MP, Guimarães JRDS, Ramos JF, Rodrigues DJ, Bánki OS, Peres CA, Pitman NCA, Hawes JE, Almeida EJ, Barbosa LF, Cavalheiro L, Dos Santos MCV, Luize BG, Novo EMML, Núñez Vargas P, Silva TSF, Venticinque EM, Manzatto AG, Reis NFC, Terborgh J, Casula KR, Costa FRC, Honorio Coronado EN, Monteagudo Mendoza A, Montero JC, Feldpausch TR, Aymard C GA, Baraloto C, Castaño Arboleda N, Engel J, Petronelli P, Zartman CE, Killeen TJ, Rincón LM, Marimon BS, Marimon-Junior BH, Schietti J, Sousa TR, Vasquez R, Mostacedo B, Dantas do Amaral D, Castellanos H, Medeiros MB, Simon MF, Andrade A, Camargo JL, Laurance WF, Laurance SGW, Farias ES, Lopes MA, Magalhães JLL, Mendonça Nascimento HE, Queiroz HL, Brienen R, Stevenson PR, Araujo-Murakami A, Baker TR, Cintra BBL, Feitosa YO, Mogollón HF, Noronha JC, Barbosa FR, de Sá Carpanedo R, Duivenvoorden JF, Silman MR, Ferreira LV, Levis C, Lozada JR, Comiskey JA, Draper FC, Toledo JJ, Damasco G, Dávila N, García-Villacorta R, Vicentini A, Cornejo Valverde F, Alonso A, Arroyo L, Dallmeier F, Gomes VHF, Jimenez EM, Neill D, Peñuela Mora MC, Carvalho FA, Coelho de Souza F, Feeley KJ, Gribel R, Pansonato MP, Ríos Paredes M, Barlow J, Berenguer E, Dexter KG, Ferreira J, Fine PVA, Guedes MC, Huamantupa-Chuquimaco I, Licona JC, Pennington T, Villa Zegarra BE, Vos VA, Cerón C, Fonty É, Henkel TW, Maas P, Pos E, Silveira M, Stropp J, Thomas R, Daly D, Milliken W, Pardo Molina G, Vieira ICG, Albuquerque BW, Campelo W, Emilio T, Fuentes A, Klitgaard B, Marcelo Pena JL, Souza PF, Tello JS, Vriesendorp C, Chave J, Di Fiore A, Hilário RR, Pereira LO, Phillips JF, Rivas-Torres G, van Andel TR, von Hildebrand P, Balee W, Barbosa EM, Bonates LCM, Doza HPD, Gómez RZ, Gonzales T, Gonzales GPG, Hoffman B, Junqueira AB, Malhi Y, Miranda IPA, Mozombite-Pinto LF, Prieto A, Rudas A, Ruschel AR, Silva N, Vela CIA, Zent S, Zent EL, Cano A, Carrero Márquez YA, Correa DF, Costa JBP, Flores BM, Galbraith D, Holmgren M, Kalamandeen M, Nascimento MT, Oliveira AA, Ramirez-Angulo H, Rocha M, Scudeller VV, Sierra R, Tirado M, Umaña MN, van der Heijden G, Vilanova Torre E, Ahuite Reategui MA, Baider C, Balslev H, Cárdenas S, Casas LF, Farfan-Rios W, Ferreira C, Linares-Palomino R, Mendoza C, Mesones I, Parada GA, Torres-Lezama A, Urrego Giraldo LE, Villarroel D, Zagt R, Alexiades MN, de Oliveira EA, Garcia-Cabrera K, Hernandez L, Palacios Cuenca W, Pansini S, Pauletto D, Ramirez Arevalo F, Sampaio AF, Valderrama Sandoval EH, Valenzuela Gamarra L, and Ter Steege H
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- Brazil, Forests, Biodiversity, Trees, Rivers, Floods
- Abstract
Amazonia's floodplain system is the largest and most biodiverse on Earth. Although forests are crucial to the ecological integrity of floodplains, our understanding of their species composition and how this may differ from surrounding forest types is still far too limited, particularly as changing inundation regimes begin to reshape floodplain tree communities and the critical ecosystem functions they underpin. Here we address this gap by taking a spatially explicit look at Amazonia-wide patterns of tree-species turnover and ecological specialization of the region's floodplain forests. We show that the majority of Amazonian tree species can inhabit floodplains, and about a sixth of Amazonian tree diversity is ecologically specialized on floodplains. The degree of specialization in floodplain communities is driven by regional flood patterns, with the most compositionally differentiated floodplain forests located centrally within the fluvial network and contingent on the most extraordinary flood magnitudes regionally. Our results provide a spatially explicit view of ecological specialization of floodplain forest communities and expose the need for whole-basin hydrological integrity to protect the Amazon's tree diversity and its function., (© 2024. The Author(s).)
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- 2024
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9. Consistent patterns of common species across tropical tree communities.
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Cooper DLM, Lewis SL, Sullivan MJP, Prado PI, Ter Steege H, Barbier N, Slik F, Sonké B, Ewango CEN, Adu-Bredu S, Affum-Baffoe K, de Aguiar DPP, Ahuite Reategui MA, Aiba SI, Albuquerque BW, de Almeida Matos FD, Alonso A, Amani CA, do Amaral DD, do Amaral IL, Andrade A, de Andrade Miranda IP, Angoboy IB, Araujo-Murakami A, Arboleda NC, Arroyo L, Ashton P, Aymard C GA, Baider C, Baker TR, Balinga MPB, Balslev H, Banin LF, Bánki OS, Baraloto C, Barbosa EM, Barbosa FR, Barlow J, Bastin JF, Beeckman H, Begne S, Bengone NN, Berenguer E, Berry N, Bitariho R, Boeckx P, Bogaert J, Bonyoma B, Boundja P, Bourland N, Boyemba Bosela F, Brambach F, Brienen R, Burslem DFRP, Camargo JL, Campelo W, Cano A, Cárdenas S, Cárdenas López D, de Sá Carpanedo R, Carrero Márquez YA, Carvalho FA, Casas LF, Castellanos H, Castilho CV, Cerón C, Chapman CA, Chave J, Chhang P, Chutipong W, Chuyong GB, Cintra BBL, Clark CJ, Coelho de Souza F, Comiskey JA, Coomes DA, Cornejo Valverde F, Correa DF, Costa FRC, Costa JBP, Couteron P, Culmsee H, Cuni-Sanchez A, Dallmeier F, Damasco G, Dauby G, Dávila N, Dávila Doza HP, De Alban JDT, de Assis RL, De Canniere C, De Haulleville T, de Jesus Veiga Carim M, Demarchi LO, Dexter KG, Di Fiore A, Din HHM, Disney MI, Djiofack BY, Djuikouo MK, Do TV, Doucet JL, Draper FC, Droissart V, Duivenvoorden JF, Engel J, Estienne V, Farfan-Rios W, Fauset S, Feeley KJ, Feitosa YO, Feldpausch TR, Ferreira C, Ferreira J, Ferreira LV, Fletcher CD, Flores BM, Fofanah A, Foli EG, Fonty É, Fredriksson GM, Fuentes A, Galbraith D, Gallardo Gonzales GP, Garcia-Cabrera K, García-Villacorta R, Gomes VHF, Gómez RZ, Gonzales T, Gribel R, Guedes MC, Guevara JE, Hakeem KR, Hall JS, Hamer KC, Hamilton AC, Harris DJ, Harrison RD, Hart TB, Hector A, Henkel TW, Herbohn J, Hockemba MBN, Hoffman B, Holmgren M, Honorio Coronado EN, Huamantupa-Chuquimaco I, Hubau W, Imai N, Irume MV, Jansen PA, Jeffery KJ, Jimenez EM, Jucker T, Junqueira AB, Kalamandeen M, Kamdem NG, Kartawinata K, Kasongo Yakusu E, Katembo JM, Kearsley E, Kenfack D, Kessler M, Khaing TT, Killeen TJ, Kitayama K, Klitgaard B, Labrière N, Laumonier Y, Laurance SGW, Laurance WF, Laurent F, Le TC, Le TT, Leal ME, Leão de Moraes Novo EM, Levesley A, Libalah MB, Licona JC, Lima Filho DA, Lindsell JA, Lopes A, Lopes MA, Lovett JC, Lowe R, Lozada JR, Lu X, Luambua NK, Luize BG, Maas P, Magalhães JLL, Magnusson WE, Mahayani NPD, Makana JR, Malhi Y, Maniguaje Rincón L, Mansor A, Manzatto AG, Marimon BS, Marimon-Junior BH, Marshall AR, Martins MP, Mbayu FM, de Medeiros MB, Mesones I, Metali F, Mihindou V, Millet J, Milliken W, Mogollón HF, Molino JF, Mohd Said MN, Monteagudo Mendoza A, Montero JC, Moore S, Mostacedo B, Mozombite Pinto LF, Mukul SA, Munishi PKT, Nagamasu H, Nascimento HEM, Nascimento MT, Neill D, Nilus R, Noronha JC, Nsenga L, Núñez Vargas P, Ojo L, Oliveira AA, de Oliveira EA, Ondo FE, Palacios Cuenca W, Pansini S, Pansonato MP, Paredes MR, Paudel E, Pauletto D, Pearson RG, Pena JLM, Pennington RT, Peres CA, Permana A, Petronelli P, Peñuela Mora MC, Phillips JF, Phillips OL, Pickavance G, Piedade MTF, Pitman NCA, Ploton P, Popelier A, Poulsen JR, Prieto A, Primack RB, Priyadi H, Qie L, Quaresma AC, de Queiroz HL, Ramirez-Angulo H, Ramos JF, Reis NFC, Reitsma J, Revilla JDC, Riutta T, Rivas-Torres G, Robiansyah I, Rocha M, Rodrigues DJ, Rodriguez-Ronderos ME, Rovero F, Rozak AH, Rudas A, Rutishauser E, Sabatier D, Sagang LB, Sampaio AF, Samsoedin I, Satdichanh M, Schietti J, Schöngart J, Scudeller VV, Seuaturien N, Sheil D, Sierra R, Silman MR, Silva TSF, da Silva Guimarães JR, Simo-Droissart M, Simon MF, Sist P, Sousa TR, de Sousa Farias E, de Souza Coelho L, Spracklen DV, Stas SM, Steinmetz R, Stevenson PR, Stropp J, Sukri RS, Sunderland TCH, Suzuki E, Swaine MD, Tang J, Taplin J, Taylor DM, Tello JS, Terborgh J, Texier N, Theilade I, Thomas DW, Thomas R, Thomas SC, Tirado M, Toirambe B, de Toledo JJ, Tomlinson KW, Torres-Lezama A, Tran HD, Tshibamba Mukendi J, Tumaneng RD, Umaña MN, Umunay PM, Urrego Giraldo LE, Valderrama Sandoval EH, Valenzuela Gamarra L, Van Andel TR, van de Bult M, van de Pol J, van der Heijden G, Vasquez R, Vela CIA, Venticinque EM, Verbeeck H, Veridiano RKA, Vicentini A, Vieira ICG, Vilanova Torre E, Villarroel D, Villa Zegarra BE, Vleminckx J, von Hildebrand P, Vos VA, Vriesendorp C, Webb EL, White LJT, Wich S, Wittmann F, Zagt R, Zang R, Zartman CE, Zemagho L, Zent EL, and Zent S
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- Biodiversity, Africa, Asia, Southeastern, Forests, Trees anatomy & histology, Trees classification, Trees growth & development, Tropical Climate
- Abstract
Trees structure the Earth's most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations
1-6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth's 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7 , we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world's most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees., (© 2024. The Author(s).)- Published
- 2024
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10. Mapping density, diversity and species-richness of the Amazon tree flora.
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Ter Steege H, Pitman NCA, do Amaral IL, de Souza Coelho L, de Almeida Matos FD, de Andrade Lima Filho D, Salomão RP, Wittmann F, Castilho CV, Guevara JE, Veiga Carim MJ, Phillips OL, Magnusson WE, Sabatier D, Revilla JDC, Molino JF, Irume MV, Martins MP, da Silva Guimarães JR, Ramos JF, Bánki OS, Piedade MTF, Cárdenas López D, Rodrigues DJ, Demarchi LO, Schöngart J, 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, Honorio Coronado EN, Monteagudo Mendoza A, Montero JC, Costa FRC, Feldpausch TR, Quaresma AC, Castaño Arboleda N, Zartman CE, Killeen TJ, Marimon BS, Marimon-Junior BH, Vasquez R, Mostacedo B, Assis RL, Baraloto C, do Amaral DD, Engel J, Petronelli P, Castellanos H, de Medeiros MB, Simon MF, Andrade A, Camargo JL, Laurance WF, Laurance SGW, Maniguaje Rincón L, Schietti J, Sousa TR, de Sousa Farias E, Lopes MA, Magalhães JLL, Nascimento HEM, de Queiroz HL, Aymard C GA, Brienen R, Stevenson PR, Araujo-Murakami A, Baker TR, Cintra BBL, Feitosa YO, Mogollón HF, Duivenvoorden JF, Peres CA, Silman MR, Ferreira LV, Lozada JR, Comiskey JA, Draper FC, de Toledo JJ, Damasco G, García-Villacorta R, Lopes A, Vicentini A, Cornejo Valverde F, Alonso A, Arroyo L, Dallmeier F, Gomes VHF, Jimenez EM, Neill D, Peñuela Mora MC, Noronha JC, de Aguiar DPP, Barbosa FR, Bredin YK, de Sá Carpanedo R, Carvalho FA, de Souza FC, Feeley KJ, Gribel R, Haugaasen T, Hawes JE, Pansonato MP, Ríos Paredes M, Barlow J, Berenguer E, da Silva IB, Ferreira MJ, Ferreira J, Fine PVA, Guedes MC, Levis C, Licona JC, Villa Zegarra BE, Vos VA, Cerón C, Durgante FM, Fonty É, Henkel TW, Householder JE, Huamantupa-Chuquimaco I, Pos E, Silveira M, Stropp J, Thomas R, Daly D, Dexter KG, Milliken W, Molina GP, Pennington T, Vieira ICG, Weiss Albuquerque B, Campelo W, Fuentes A, Klitgaard B, Pena JLM, Tello JS, Vriesendorp C, Chave J, Di Fiore A, Hilário RR, de Oliveira Pereira L, Phillips JF, Rivas-Torres G, van Andel TR, von Hildebrand P, Balee W, Barbosa EM, de Matos Bonates LC, Dávila Doza HP, Zárate Gómez R, Gonzales T, Gallardo Gonzales GP, Hoffman B, Junqueira AB, Malhi Y, de Andrade Miranda IP, Pinto LFM, Prieto A, Rudas A, Ruschel AR, Silva N, Vela CIA, Zent EL, Zent S, Cano A, Carrero Márquez YA, Correa DF, Costa JBP, Flores BM, Galbraith D, Holmgren M, Kalamandeen M, Lobo G, Torres Montenegro L, Nascimento MT, Oliveira AA, Pombo MM, Ramirez-Angulo H, Rocha M, Scudeller VV, Sierra R, Tirado M, Umaña MN, van der Heijden G, Vilanova Torre E, Reategui MAA, Baider C, Balslev H, Cárdenas S, Casas LF, Endara MJ, Farfan-Rios W, Ferreira C, Linares-Palomino R, Mendoza C, Mesones I, Parada GA, Torres-Lezama A, Urrego Giraldo LE, Villarroel D, Zagt R, Alexiades MN, de Oliveira EA, Garcia-Cabrera K, Hernandez L, Cuenca WP, Pansini S, Pauletto D, Ramirez Arevalo F, Sampaio AF, Valderrama Sandoval EH, Gamarra LV, Levesley A, Pickavance G, and Melgaço K
- Subjects
- Forests, Soil, Temperature, Trees, RNA, Long Noncoding
- Abstract
Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution., (© 2023. The Author(s).)
- Published
- 2023
- Full Text
- View/download PDF
11. More than 10,000 pre-Columbian earthworks are still hidden throughout Amazonia.
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Peripato V, Levis C, Moreira GA, Gamerman D, Ter Steege H, Pitman NCA, de Souza JG, Iriarte J, Robinson M, Junqueira AB, Trindade TB, de Almeida FO, Moraes CP, Lombardo U, Tamanaha EK, Maezumi SY, Ometto JPHB, Braga JRG, Campanharo WA, Cassol HLG, Leal PR, de Assis MLR, da Silva AM, Phillips OL, Costa FRC, Flores BM, Hoffman B, Henkel TW, Umaña MN, Magnusson WE, Valderrama Sandoval EH, Barlow J, Milliken W, Lopes MA, Simon MF, van Andel TR, Laurance SGW, Laurance WF, Torres-Lezama A, Assis RL, Molino JF, Mestre M, Hamblin M, Coelho LS, Lima Filho DA, Wittmann F, Salomão RP, Amaral IL, Guevara JE, de Almeida Matos FD, Castilho CV, Carim MJV, Cárdenas López D, Sabatier D, Irume MV, Martins MP, Guimarães JRDS, Bánki OS, Piedade MTF, Ramos JF, Luize BG, Novo EMML, Núñez Vargas P, Silva TSF, Venticinque EM, Manzatto AG, Reis NFC, Terborgh J, Casula KR, Demarchi LO, Honorio Coronado EN, Monteagudo Mendoza A, Montero JC, Schöngart J, Feldpausch TR, Quaresma AC, Aymard C GA, Baraloto C, Castaño Arboleda N, Engel J, Petronelli P, Zartman CE, Killeen TJ, Marimon BS, Marimon-Junior BH, Schietti J, Sousa TR, Vasquez R, Rincón LM, Berenguer E, Ferreira J, Mostacedo B, do Amaral DD, Castellanos H, de Medeiros MB, Andrade A, Camargo JL, Farias ES, Magalhães JLL, Mendonça Nascimento HE, de Queiroz HL, Brienen R, Cardenas Revilla JD, Stevenson PR, Araujo-Murakami A, Barçante Ladvocat Cintra B, Feitosa YO, Barbosa FR, Carpanedo RS, Duivenvoorden JF, de Noronha JDC, Rodrigues DJ, Mogollón HF, Ferreira LV, Householder JE, Lozada JR, Comiskey JA, Draper FC, de Toledo JJ, Damasco G, Dávila N, García-Villacorta R, Lopes A, Cornejo Valverde F, Alonso A, Dallmeier F, Gomes VHF, Jimenez EM, Neill D, Peñuela Mora MC, de Aguiar DPP, Arroyo L, Antunes Carvalho F, Coelho de Souza F, Feeley KJ, Gribel R, Pansonato MP, Ríos Paredes M, Brasil da Silva I, Ferreira MJ, Fine PVA, Fonty É, Guedes MC, Licona JC, Pennington T, Peres CA, Villa Zegarra BE, Parada GA, Pardo Molina G, Vos VA, Cerón C, Maas P, Silveira M, Stropp J, Thomas R, Baker TR, Daly D, Huamantupa-Chuquimaco I, Vieira ICG, Weiss Albuquerque B, Fuentes A, Klitgaard B, Marcelo-Peña JL, Silman MR, Tello JS, Vriesendorp C, Chave J, Di Fiore A, Hilário RR, Phillips JF, Rivas-Torres G, von Hildebrand P, Pereira LO, Barbosa EM, de Matos Bonates LC, Doza HPD, Zárate Gómez R, Gallardo Gonzales GP, Gonzales T, Malhi Y, de Andrade Miranda IP, Mozombite Pinto LF, Prieto A, Rudas A, Ruschel AR, Silva N, Vela CIA, Zent EL, Zent S, Cano A, Carrero Márquez YA, Correa DF, Costa JBP, Galbraith D, Holmgren M, Kalamandeen M, Lobo G, Nascimento MT, Oliveira AA, Ramirez-Angulo H, Rocha M, Scudeller VV, Sierra R, Tirado M, van der Heijden G, Vilanova Torre E, Ahuite Reategui MA, Baider C, Balslev H, Cárdenas S, Casas LF, Farfan-Rios W, Ferreira C, Linares-Palomino R, Mendoza C, Mesones I, Urrego Giraldo LE, Villarroel D, Zagt R, Alexiades MN, de Oliveira EA, Garcia-Cabrera K, Hernandez L, Palacios Cuenca W, Pansini S, Pauletto D, Ramirez Arevalo F, Sampaio AF, Valenzuela Gamarra L, and Aragão LEOC
- Subjects
- Humans, Brazil, Forests, Archaeology
- Abstract
Indigenous societies are known to have occupied the Amazon basin for more than 12,000 years, but the scale of their influence on Amazonian forests remains uncertain. We report the discovery, using LIDAR (light detection and ranging) information from across the basin, of 24 previously undetected pre-Columbian earthworks beneath the forest canopy. Modeled distribution and abundance of large-scale archaeological sites across Amazonia suggest that between 10,272 and 23,648 sites remain to be discovered and that most will be found in the southwest. We also identified 53 domesticated tree species significantly associated with earthwork occurrence probability, likely suggesting past management practices. Closed-canopy forests across Amazonia are likely to contain thousands of undiscovered archaeological sites around which pre-Columbian societies actively modified forests, a discovery that opens opportunities for better understanding the magnitude of ancient human influence on Amazonia and its current state.
- Published
- 2023
- Full Text
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12. Relationships between species richness and ecosystem services in Amazonian forests strongly influenced by biogeographical strata and forest types.
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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
- Full Text
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13. Amazon tree dominance across forest strata.
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Draper FC, Costa FRC, Arellano G, Phillips OL, Duque A, Macía MJ, Ter Steege H, Asner GP, Berenguer E, Schietti J, Socolar JB, de Souza FC, Dexter KG, Jørgensen PM, Tello JS, Magnusson WE, Baker TR, Castilho CV, Monteagudo-Mendoza A, Fine PVA, Ruokolainen K, Coronado ENH, Aymard G, Dávila N, Sáenz MS, Paredes MAR, Engel J, Fortunel C, Paine CET, Goret JY, Dourdain A, Petronelli P, Allie E, Andino JEG, Brienen RJW, Pérez LC, Manzatto ÂG, Zambrana NYP, Molino JF, Sabatier D, Chave J, Fauset S, Villacorta RG, Réjou-Méchain M, Berry PE, Melgaço K, Feldpausch TR, Sandoval EV, Martinez RV, Mesones I, Junqueira AB, Roucoux KH, de Toledo JJ, Andrade AC, Camargo JL, Del Aguila Pasquel J, Santana FD, Laurance WF, Laurance SG, Lovejoy TE, Comiskey JA, Galbraith DR, Kalamandeen M, Aguilar GEN, Arenas JV, Guerra CAA, Flores M, Llampazo GF, Montenegro LAT, Gomez RZ, Pansonato MP, Moscoso VC, Vleminckx J, Barrantes OJV, Duivenvoorden JF, de Sousa SA, Arroyo L, Perdiz RO, Cravo JS, Marimon BS, Junior BHM, Carvalho FA, Damasco G, Disney M, Vital MS, Diaz PRS, Vicentini A, Nascimento H, Higuchi N, Van Andel T, Malhi Y, Ribeiro SC, Terborgh JW, Thomas RS, Dallmeier F, Prieto A, Hilário RR, Salomão RP, Silva RDC, Casas LF, Vieira ICG, Araujo-Murakami A, Arevalo FR, Ramírez-Angulo H, Torre EV, Peñuela MC, Killeen TJ, Pardo G, Jimenez-Rojas E, Castro W, Cabrera DG, Pipoly J, de Sousa TR, Silvera M, Vos V, Neill D, Vargas PN, Vela DM, Aragão LEOC, Umetsu RK, Sierra R, Wang O, Young KR, Prestes NCCS, Massi KG, Huaymacari JR, Gutierrez GAP, Aldana AM, Alexiades MN, Baccaro F, Céron C, Muelbert AE, Rios JMG, Lima AS, Lloyd JL, Pitman NCA, Gamarra LV, Oroche CJC, Fuentes AF, Palacios W, Patiño S, Torres-Lezama A, and Baraloto C
- Subjects
- Biodiversity, Brazil, Humans, Forests, Trees
- Abstract
The forests of Amazonia are among the most biodiverse plant communities on Earth. Given the immediate threats posed by climate and land-use change, an improved understanding of how this extraordinary biodiversity is spatially organized is urgently required to develop effective conservation strategies. Most Amazonian tree species are extremely rare but a few are common across the region. Indeed, just 227 'hyperdominant' species account for >50% of all individuals >10 cm diameter at 1.3 m in height. Yet, the degree to which the phenomenon of hyperdominance is sensitive to tree size, the extent to which the composition of dominant species changes with size class and how evolutionary history constrains tree hyperdominance, all remain unknown. Here, we use a large floristic dataset to show that, while hyperdominance is a universal phenomenon across forest strata, different species dominate the forest understory, midstory and canopy. We further find that, although species belonging to a range of phylogenetically dispersed lineages have become hyperdominant in small size classes, hyperdominants in large size classes are restricted to a few lineages. Our results demonstrate that it is essential to consider all forest strata to understand regional patterns of dominance and composition in Amazonia. More generally, through the lens of 654 hyperdominant species, we outline a tractable pathway for understanding the functioning of half of Amazonian forests across vertical strata and geographical locations.
- Published
- 2021
- Full Text
- View/download PDF
14. Biased-corrected richness estimates for the Amazonian tree flora.
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Ter Steege H, Prado PI, Lima RAF, 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, Cárdenas López D, Magnusson WE, Wittmann F, Martins MP, Sabatier D, Irume MV, da Silva Guimarães JR, Molino JF, Bánki OS, Piedade MTF, Pitman NCA, Ramos JF, Monteagudo Mendoza A, Venticinque EM, Luize BG, Núñez Vargas P, Silva TSF, de Leão Novo EMM, Reis NFC, Terborgh J, Manzatto AG, Casula KR, Honorio Coronado EN, Montero JC, Duque A, Costa FRC, Castaño Arboleda N, Schöngart J, Zartman CE, Killeen TJ, Marimon BS, Marimon-Junior BH, Vasquez R, Mostacedo B, Demarchi LO, Feldpausch TR, Engel J, Petronelli P, Baraloto C, Assis RL, Castellanos H, Simon MF, de Medeiros MB, Quaresma A, Laurance SGW, Rincón LM, Andrade A, Sousa TR, Camargo JL, Schietti J, Laurance WF, de Queiroz HL, Nascimento HEM, Lopes MA, de Sousa Farias E, Magalhães JLL, Brienen R, Aymard C GA, Revilla JDC, Vieira ICG, Cintra BBL, Stevenson PR, Feitosa YO, Duivenvoorden JF, Mogollón HF, Araujo-Murakami A, Ferreira LV, Lozada JR, Comiskey JA, de Toledo JJ, Damasco G, Dávila N, Lopes A, García-Villacorta R, Draper F, Vicentini A, Cornejo Valverde F, Lloyd J, Gomes VHF, Neill D, Alonso A, Dallmeier F, de Souza FC, Gribel R, Arroyo L, Carvalho FA, de Aguiar DPP, do Amaral DD, Pansonato MP, Feeley KJ, Berenguer E, Fine PVA, Guedes MC, Barlow J, Ferreira J, Villa B, Peñuela Mora MC, Jimenez EM, Licona JC, Cerón C, Thomas R, Maas P, Silveira M, Henkel TW, Stropp J, Paredes MR, Dexter KG, Daly D, Baker TR, Huamantupa-Chuquimaco I, Milliken W, Pennington T, Tello JS, Pena JLM, Peres CA, Klitgaard B, Fuentes A, Silman MR, Di Fiore A, von Hildebrand P, Chave J, van Andel TR, Hilário RR, Phillips JF, Rivas-Torres G, Noronha JC, Prieto A, Gonzales T, de Sá Carpanedo R, Gonzales GPG, Gómez RZ, de Jesus Rodrigues D, Zent EL, Ruschel AR, Vos VA, Fonty É, Junqueira AB, Doza HPD, Hoffman B, Zent S, Barbosa EM, Malhi Y, de Matos Bonates LC, de Andrade Miranda IP, Silva N, Barbosa FR, Vela CIA, Pinto LFM, Rudas A, Albuquerque BW, Umaña MN, Carrero Márquez YA, van der Heijden G, Young KR, Tirado M, Correa DF, Sierra R, Costa JBP, Rocha M, Vilanova Torre E, Wang O, Oliveira AA, Kalamandeen M, Vriesendorp C, Ramirez-Angulo H, Holmgren M, Nascimento MT, Galbraith D, Flores BM, Scudeller VV, Cano A, Ahuite Reategui MA, Mesones I, Baider C, Mendoza C, Zagt R, Urrego Giraldo LE, Ferreira C, Villarroel D, Linares-Palomino R, Farfan-Rios W, Farfan-Rios W, Casas LF, Cárdenas S, Balslev H, Torres-Lezama A, Alexiades MN, Garcia-Cabrera K, Valenzuela Gamarra L, Valderrama Sandoval EH, Ramirez Arevalo F, Hernandez L, Sampaio AF, Pansini S, Palacios Cuenca W, de Oliveira EA, Pauletto D, Levesley A, Melgaço K, and Pickavance G
- Subjects
- Brazil, Biodiversity, Classification methods, Forests, Rivers, Trees classification
- Abstract
Amazonian forests are extraordinarily diverse, but the estimated species richness is very much debated. Here, we apply an ensemble of parametric estimators and a novel technique that includes conspecific spatial aggregation to an extended database of forest plots with up-to-date taxonomy. We show that the species abundance distribution of Amazonia is best approximated by a logseries with aggregated individuals, where aggregation increases with rarity. By averaging several methods to estimate total richness, we confirm that over 15,000 tree species are expected to occur in Amazonia. We also show that using ten times the number of plots would result in an increase to just ~50% of those 15,000 estimated species. To get a more complete sample of all tree species, rigorous field campaigns may be needed but the number of trees in Amazonia will remain an estimate for years to come.
- Published
- 2020
- Full Text
- View/download PDF
15. Long-term thermal sensitivity of Earth's tropical forests.
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Sullivan MJP, Lewis SL, Affum-Baffoe K, Castilho C, Costa F, Sanchez AC, Ewango CEN, Hubau W, Marimon B, Monteagudo-Mendoza A, Qie L, Sonké B, Martinez RV, Baker TR, Brienen RJW, Feldpausch TR, Galbraith D, Gloor M, Malhi Y, Aiba SI, Alexiades MN, Almeida EC, de Oliveira EA, Dávila EÁ, Loayza PA, Andrade A, Vieira SA, Aragão LEOC, Araujo-Murakami A, Arets EJMM, Arroyo L, Ashton P, Aymard C G, Baccaro FB, Banin LF, Baraloto C, Camargo PB, Barlow J, Barroso J, Bastin JF, Batterman SA, Beeckman H, Begne SK, Bennett AC, Berenguer E, Berry N, Blanc L, Boeckx P, Bogaert J, Bonal D, Bongers F, Bradford M, Brearley FQ, Brncic T, Brown F, Burban B, Camargo JL, Castro W, Céron C, Ribeiro SC, Moscoso VC, Chave J, Chezeaux E, Clark CJ, de Souza FC, Collins M, Comiskey JA, Valverde FC, Medina MC, da Costa L, Dančák M, Dargie GC, Davies S, Cardozo ND, de Haulleville T, de Medeiros MB, Del Aguila Pasquel J, Derroire G, Di Fiore A, Doucet JL, Dourdain A, Droissart V, Duque LF, Ekoungoulou R, Elias F, Erwin T, Esquivel-Muelbert A, Fauset S, Ferreira J, Llampazo GF, Foli E, Ford A, Gilpin M, Hall JS, Hamer KC, Hamilton AC, Harris DJ, Hart TB, Hédl R, Herault B, Herrera R, Higuchi N, Hladik A, Coronado EH, Huamantupa-Chuquimaco I, Huasco WH, Jeffery KJ, Jimenez-Rojas E, Kalamandeen M, Djuikouo MNK, Kearsley E, Umetsu RK, Kho LK, Killeen T, Kitayama K, Klitgaard B, Koch A, Labrière N, Laurance W, Laurance S, Leal ME, Levesley A, Lima AJN, Lisingo J, Lopes AP, Lopez-Gonzalez G, Lovejoy T, Lovett JC, Lowe R, Magnusson WE, Malumbres-Olarte J, Manzatto ÂG, Marimon BH Jr, Marshall AR, Marthews T, de Almeida Reis SM, Maycock C, Melgaço K, Mendoza C, Metali F, Mihindou V, Milliken W, Mitchard ETA, Morandi PS, Mossman HL, Nagy L, Nascimento H, Neill D, Nilus R, Vargas PN, Palacios W, Camacho NP, Peacock J, Pendry C, Peñuela Mora MC, Pickavance GC, Pipoly J, Pitman N, Playfair M, Poorter L, Poulsen JR, Poulsen AD, Preziosi R, Prieto A, Primack RB, Ramírez-Angulo H, Reitsma J, Réjou-Méchain M, Correa ZR, de Sousa TR, Bayona LR, Roopsind A, Rudas A, Rutishauser E, Abu Salim K, Salomão RP, Schietti J, Sheil D, Silva RC, Espejo JS, Valeria CS, Silveira M, Simo-Droissart M, Simon MF, Singh J, Soto Shareva YC, Stahl C, Stropp J, Sukri R, Sunderland T, Svátek M, Swaine MD, Swamy V, Taedoumg H, Talbot J, Taplin J, Taylor D, Ter Steege H, Terborgh J, Thomas R, Thomas SC, Torres-Lezama A, Umunay P, Gamarra LV, van der Heijden G, van der Hout P, van der Meer P, van Nieuwstadt M, Verbeeck H, Vernimmen R, Vicentini A, Vieira ICG, Torre EV, Vleminckx J, Vos V, Wang O, White LJT, Willcock S, Woods JT, Wortel V, Young K, Zagt R, Zemagho L, Zuidema PA, Zwerts JA, and Phillips OL
- Subjects
- Acclimatization, Biomass, Carbon metabolism, Earth, Planet, Wood, Carbon Cycle, Climate Change, Forests, Hot Temperature, Trees metabolism, Tropical Climate
- Abstract
The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (-9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth's climate., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)
- Published
- 2020
- Full Text
- View/download PDF
16. Rarity of monodominance in hyperdiverse Amazonian forests.
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Ter Steege H, Henkel TW, Helal N, Marimon BS, Marimon-Junior BH, Huth A, Groeneveld J, Sabatier D, Coelho LS, Filho DAL, Salomão RP, Amaral IL, Matos FDA, Castilho CV, Phillips OL, Guevara JE, Carim MJV, Cárdenas López D, Magnusson WE, Wittmann F, Irume MV, Martins MP, Guimarães JRDS, Molino JF, Bánki OS, Piedade MTF, Pitman NCA, Mendoza AM, Ramos JF, Luize BG, Moraes de Leão Novo EM, Núñez Vargas P, Silva TSF, Venticinque EM, Manzatto AG, Reis NFC, Terborgh J, Casula KR, Honorio Coronado EN, Montero JC, Feldpausch TR, Duque A, Costa FRC, Arboleda NC, Schöngart J, Killeen TJ, Vasquez R, Mostacedo B, Demarchi LO, Assis RL, Baraloto C, Engel J, Petronelli P, Castellanos H, de Medeiros MB, Quaresma A, Simon MF, Andrade A, Camargo JL, Laurance SGW, Laurance WF, Rincón LM, Schietti J, Sousa TR, de Sousa Farias E, Lopes MA, Magalhães JLL, Mendonça Nascimento HE, Lima de Queiroz H, Aymard C GA, Brienen R, Revilla JDC, Vieira ICG, Cintra BBL, Stevenson PR, Feitosa YO, Duivenvoorden JF, Mogollón HF, Araujo-Murakami A, Ferreira LV, Lozada JR, Comiskey JA, de Toledo JJ, Damasco G, Dávila N, Draper F, García-Villacorta R, Lopes A, Vicentini A, Alonso A, Dallmeier F, Gomes VHF, Lloyd J, Neill D, de Aguiar DPP, 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, Peñuela Mora MC, Villa B, Cerón C, Maas P, Silveira M, Stropp J, Thomas R, Baker TR, Daly D, Dexter KG, Huamantupa-Chuquimaco I, Milliken W, Pennington T, Ríos Paredes M, Fuentes A, Klitgaard B, Pena JLM, Peres CA, Silman MR, Tello JS, Chave J, Cornejo Valverde F, Di Fiore A, Hilário RR, Phillips JF, Rivas-Torres G, van Andel TR, von Hildebrand P, Noronha JC, Barbosa EM, Barbosa FR, de Matos Bonates LC, Carpanedo RS, Dávila Doza HP, Fonty É, GómeZárate Z R, Gonzales T, Gallardo Gonzales GP, Hoffman B, Junqueira AB, Malhi Y, Miranda IPA, Pinto LFM, Prieto A, Rodrigues DJ, Rudas A, Ruschel AR, Silva N, Vela CIA, Vos VA, Zent EL, Zent S, Weiss Albuquerque B, Cano A, Carrero Márquez YA, Correa DF, Costa JBP, Flores BM, Galbraith D, Holmgren M, Kalamandeen M, Nascimento MT, Oliveira AA, Ramirez-Angulo H, Rocha M, Scudeller VV, Sierra R, Tirado M, Umaña Medina MN, van der Heijden G, Vilanova Torre E, Vriesendorp C, Wang O, Young KR, Ahuite Reategui MA, 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, de Oliveira EA, Garcia-Cabrera K, Hernandez L, Palacios Cuenca W, Pansini S, Pauletto D, Ramirez Arevalo F, Sampaio AF, Sandoval EHV, Valenzuela Gamarra L, Levesley A, Pickavance G, and Melgaço K
- Abstract
Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such "monodominant" forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees ≥ 10 cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors.
- Published
- 2019
- Full Text
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17. Pervasive Rise of Small-scale Deforestation in Amazonia.
- Author
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Kalamandeen M, Gloor E, Mitchard E, Quincey D, Ziv G, Spracklen D, Spracklen B, Adami M, Aragão LEOC, and Galbraith D
- Subjects
- Bolivia, Brazil, Geography, Peru, Conservation of Natural Resources, Rainforest
- Abstract
Understanding forest loss patterns in Amazonia, the Earth's largest rainforest region, is critical for effective forest conservation and management. Following the most detailed analysis to date, spanning the entire Amazon and extending over a 14-year period (2001-2014), we reveal significant shifts in deforestation dynamics of Amazonian forests. Firstly, hotspots of Amazonian forest loss are moving away from the southern Brazilian Amazon to Peru and Bolivia. Secondly, while the number of new large forest clearings (>50 ha) has declined significantly over time (46%), the number of new small clearings (<1 ha) increased by 34% between 2001-2007 and 2008-2014. Thirdly, we find that small-scale low-density forest loss expanded markedly in geographical extent during 2008-2014. This shift presents an important and alarming new challenge for forest conservation, despite reductions in overall deforestation rates.
- Published
- 2018
- Full Text
- View/download PDF
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