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3. A global reference dataset for remote sensing of forest biomass. The Forest Observation System approach

Author

Shchepashchenko, D., Chave, J., Phillips, O.L., Lewis, S.L., Davies, S.J., Réjou-Méchain, M., Sist, P., Scipal, K., Perger, C., Herault, B., Labrière, N., Hofhansl, F., Affum-Baffoe, K., Aleinikov, A., Alonso, A., Amani, C., Araujo-Murakami, A., Armston, J., Arroyo, L., Ascarrunz, N., Azevedo, C., Baker, T., Bałazy, R., Banki, O., Bedeau, C., Berry, N., Bilous, A.M., Bilous, S.Y., Bissiengou, P., Blanc, L., Bobkova, K.S., Braslavskaya, T., Brienen, R., Burslem, D., Condit, R., Cuni-Sanchez, A., Danilina, D., del Castillo Torres, D., Derroire, G., Descroix, L., Doff Sotta, E., d'Oliveira, M.V.N., Dresel, C., Erwin, T., Evdokimenko, M.D., Falck, J., Feldpausch, T.R., Foli, E.G., Foster, R., Fritz, S., Garcia-Abril, A.D., Gornov, A., Gornova, M., Gothard-Bassébé, E., Gourlet-Fleury, S., Guedes, M., Hamer, K., Susanty, F.H., Higuchi, N., Honorio Coronado, E.N., Hubau, W., Hubbell, S., Ilstedt, U., Ivanov, V., Kanashiro, M., Karlsson, A., Karminov, V.N., Killeen, T., Konan, J.K., Konovalova, M., Kraxner, F., Krejza, J., Krisnawati, H., Krivobokov, L.V., Kuznetsov, M.A., Lakyda, I., Lakyda, P.I., Licona, J.C., Lucas, R.M., Lukina, N., Lussetti, D., Malhi, Y., Manzanera, J.A., Marimon, B., Marimon Junior, B.H., Martinez, R.V., Martynenko, O.V., Matsala, M.S., Matyashuk, R.K., Mazzei, L., Memiaghe, H., Mendoza, C., Monteagudo-Mendoza, A., Morozyuk, O.V., Mukhortova, L., Musa, S., Nazimova, D.I., Okuda, T., Oliveira, L.C., Ontikov, P.V., Osipov, A.F., Gutierrez, A.P., Pietsch, S., Playfair, M., Poulsen, J., Radchenko, V., Rodney, K., Rozak, A.H., Ruschel, A., Rutishauser, E., See, L., Shchepashchenko, M., Shevchenko, N., Shvidenko, A., Silva-Espejo, J.E., Silveira, M., Singh, J., Sonké, B., Souza, C., Stereńczak, K., Sullivan, M.J.P., Szatniewska, J., Taedoumg, H., ter Steege, H., Tikhonova, E., Toledo, M., Trefilova, O.V., Valbuena, R., Valenzuela Gamarra, L.V., Vedrova, E.F., Verhovets, S.V., Vidal, E., Vladimirova, N.A., Vleminckx, J., Vos, V.A., Vozmitel, F.K., Wanek, W., West, T.A.P., Woell, H., Woods, J.T., Wortel, V., Yamada, T., Zamah Shari, N.H., Zo-Bi, I.C., Shchepashchenko, D., Chave, J., Phillips, O.L., Lewis, S.L., Davies, S.J., Réjou-Méchain, M., Sist, P., Scipal, K., Perger, C., Herault, B., Labrière, N., Hofhansl, F., Affum-Baffoe, K., Aleinikov, A., Alonso, A., Amani, C., Araujo-Murakami, A., Armston, J., Arroyo, L., Ascarrunz, N., Azevedo, C., Baker, T., Bałazy, R., Banki, O., Bedeau, C., Berry, N., Bilous, A.M., Bilous, S.Y., Bissiengou, P., Blanc, L., Bobkova, K.S., Braslavskaya, T., Brienen, R., Burslem, D., Condit, R., Cuni-Sanchez, A., Danilina, D., del Castillo Torres, D., Derroire, G., Descroix, L., Doff Sotta, E., d'Oliveira, M.V.N., Dresel, C., Erwin, T., Evdokimenko, M.D., Falck, J., Feldpausch, T.R., Foli, E.G., Foster, R., Fritz, S., Garcia-Abril, A.D., Gornov, A., Gornova, M., Gothard-Bassébé, E., Gourlet-Fleury, S., Guedes, M., Hamer, K., Susanty, F.H., Higuchi, N., Honorio Coronado, E.N., Hubau, W., Hubbell, S., Ilstedt, U., Ivanov, V., Kanashiro, M., Karlsson, A., Karminov, V.N., Killeen, T., Konan, J.K., Konovalova, M., Kraxner, F., Krejza, J., Krisnawati, H., Krivobokov, L.V., Kuznetsov, M.A., Lakyda, I., Lakyda, P.I., Licona, J.C., Lucas, R.M., Lukina, N., Lussetti, D., Malhi, Y., Manzanera, J.A., Marimon, B., Marimon Junior, B.H., Martinez, R.V., Martynenko, O.V., Matsala, M.S., Matyashuk, R.K., Mazzei, L., Memiaghe, H., Mendoza, C., Monteagudo-Mendoza, A., Morozyuk, O.V., Mukhortova, L., Musa, S., Nazimova, D.I., Okuda, T., Oliveira, L.C., Ontikov, P.V., Osipov, A.F., Gutierrez, A.P., Pietsch, S., Playfair, M., Poulsen, J., Radchenko, V., Rodney, K., Rozak, A.H., Ruschel, A., Rutishauser, E., See, L., Shchepashchenko, M., Shevchenko, N., Shvidenko, A., Silva-Espejo, J.E., Silveira, M., Singh, J., Sonké, B., Souza, C., Stereńczak, K., Sullivan, M.J.P., Szatniewska, J., Taedoumg, H., ter Steege, H., Tikhonova, E., Toledo, M., Trefilova, O.V., Valbuena, R., Valenzuela Gamarra, L.V., Vedrova, E.F., Verhovets, S.V., Vidal, E., Vladimirova, N.A., Vleminckx, J., Vos, V.A., Vozmitel, F.K., Wanek, W., West, T.A.P., Woell, H., Woods, J.T., Wortel, V., Yamada, T., Zamah Shari, N.H., and Zo-Bi, I.C.

Abstract

Forest biomass is an essential indicator for monitoring the Earth’s ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities. Live, most up-to-date dataset is available at https://forest-observation-system.net

Published
2019

4. The Forest Observation System, building a global reference dataset for remote sensing of forest biomass

Author

Schepaschenko, D., Chave, J., Phillips, O.L., Lewis, S.L., Davies, S.J., Réjou-Méchain, M., Sist, P., Scipal, K., Perger, C., Herault, B., Labrière, N., Hofhansl, F., Affum-Baffoe, K., Aleinikov, A., Alonso, A., Amani, C., Araujo-Murakami, A., Armston, J., Arroyo, L., Ascarrunz, N., Azevedo, C., Baker, T., Bałazy, R., Bedeau, C., Berry, N., Bilous, A.M., Bilous, S., Bissiengou, P., Blanc, L., Bobkova, .S., Braslavskaya, T., Brienen, R., Burslem, D., Condit, R., Cuni-Sanchez, A., Danilina, D., del Castillo Torres, D., Derroire, G., Descroix, L., Sotta, E.D., d’Oliveira, M.V.N., Dresel, C., Erwin, T., Evdokimenko, M.D., Falck, J., Feldpausch, T.R., Foli, E.G., Foster, R., Fritz, S., Garcia-Abril, A.D., Gornov, A., Gornova, M., Gothard-Bassébé, E., Gourlet-Fleury, S., Guedes, M., Hamer, K.C., Susanty, F.H., Higuchi, N., Coronado, E.N.H., Hubau, W., Hubbell, S., Ilstedt, U., Ivanov, V.V., Kanashiro, M., Karlsson, A., Karminov, V.N., Killeen, T., Koffi, J.-C., Konovalova, M., Kraxner, F., Krejza, J., Krisnawati, H., Krivobokov, L.V., Kuznetsov, M.A., Lakyda, I., Lakyda, P.I., Licona, J.C., Lucas, R.M., Lukina, N., Lussetti, D., Malhi, Y., Manzanera, J.A., Marimon, B., Marimon, B.H., Martinez, R.V., Martynenko, O.V., Matsala, M., Matyashuk, R.K., Mazzei, L., Memiaghe, H., Mendoza, C., Mendoza, A.M., Moroziuk, Olga V., Mukhortova, L., Musa, S., Nazimova, D.I., Okuda, T., Oliveira, L.C., Ontikov, P.V., Osipov, A., Pietsch, S., Playfair, M., Poulsen, J., Radchenko, V.G., Rodney, K., Rozak, A.H., Ruschel, A., Rutishauser, E., See, L., Shchepashchenko, M., Shevchenko, N., Shvidenko, A., Silveira, M., Singh, J., Sonké, B., Souza, C., Stereńczak, K., Stonozhenko, L., Sullivan, M., Szatniewska, J., Taedoumg, H., ter Steege, H., Tikhonova, E., Toledo, M., Trefilova, O.V., Valbuena, R., Gamarra, L.V., Vasiliev, S., Vedrova, E.F., Verhovets, S.V., Vidal, E., Vladimirova, N.A., Vleminckx, J., Vos, V.A., Vozmitel, F.K., Wanek, W., West, T., Woell, H., Woods, J.T., Wortel, V., Yamada, T., Nur Hajar, Z., Zo-Bi, I., Schepaschenko, D., Chave, J., Phillips, O.L., Lewis, S.L., Davies, S.J., Réjou-Méchain, M., Sist, P., Scipal, K., Perger, C., Herault, B., Labrière, N., Hofhansl, F., Affum-Baffoe, K., Aleinikov, A., Alonso, A., Amani, C., Araujo-Murakami, A., Armston, J., Arroyo, L., Ascarrunz, N., Azevedo, C., Baker, T., Bałazy, R., Bedeau, C., Berry, N., Bilous, A.M., Bilous, S., Bissiengou, P., Blanc, L., Bobkova, .S., Braslavskaya, T., Brienen, R., Burslem, D., Condit, R., Cuni-Sanchez, A., Danilina, D., del Castillo Torres, D., Derroire, G., Descroix, L., Sotta, E.D., d’Oliveira, M.V.N., Dresel, C., Erwin, T., Evdokimenko, M.D., Falck, J., Feldpausch, T.R., Foli, E.G., Foster, R., Fritz, S., Garcia-Abril, A.D., Gornov, A., Gornova, M., Gothard-Bassébé, E., Gourlet-Fleury, S., Guedes, M., Hamer, K.C., Susanty, F.H., Higuchi, N., Coronado, E.N.H., Hubau, W., Hubbell, S., Ilstedt, U., Ivanov, V.V., Kanashiro, M., Karlsson, A., Karminov, V.N., Killeen, T., Koffi, J.-C., Konovalova, M., Kraxner, F., Krejza, J., Krisnawati, H., Krivobokov, L.V., Kuznetsov, M.A., Lakyda, I., Lakyda, P.I., Licona, J.C., Lucas, R.M., Lukina, N., Lussetti, D., Malhi, Y., Manzanera, J.A., Marimon, B., Marimon, B.H., Martinez, R.V., Martynenko, O.V., Matsala, M., Matyashuk, R.K., Mazzei, L., Memiaghe, H., Mendoza, C., Mendoza, A.M., Moroziuk, Olga V., Mukhortova, L., Musa, S., Nazimova, D.I., Okuda, T., Oliveira, L.C., Ontikov, P.V., Osipov, A., Pietsch, S., Playfair, M., Poulsen, J., Radchenko, V.G., Rodney, K., Rozak, A.H., Ruschel, A., Rutishauser, E., See, L., Shchepashchenko, M., Shevchenko, N., Shvidenko, A., Silveira, M., Singh, J., Sonké, B., Souza, C., Stereńczak, K., Stonozhenko, L., Sullivan, M., Szatniewska, J., Taedoumg, H., ter Steege, H., Tikhonova, E., Toledo, M., Trefilova, O.V., Valbuena, R., Gamarra, L.V., Vasiliev, S., Vedrova, E.F., Verhovets, S.V., Vidal, E., Vladimirova, N.A., Vleminckx, J., Vos, V.A., Vozmitel, F.K., Wanek, W., West, T., Woell, H., Woods, J.T., Wortel, V., Yamada, T., Nur Hajar, Z., and Zo-Bi, I.

Abstract

Forest biomass is an essential indicator for monitoring the Earth’s ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world’s forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.

Published
2019

5. Introducing global peat-specific temperature and pH calibrations based on brGDGT bacterial lipids

Author

Naafs, B. D. A., Inglis, G. N., Zheng, Y., Amesbury, M. J., Biester, H., Bindler, Richard, Blewett, J., Burrows, M. A., del Castillo Torres, D., Chambers, F. M., Cohen, A. D., Evershed, R. P., Feakins, S. J., Galka, M., Gallego-Sala, A., Gandois, L., Gray, D. M., Hatcher, P. G., Honorio Coronado, E. N., Hughes, P. D. M., Huguet, A., Kononen, M., Laggoun-Defarge, F., Lahteenoja, O., Lamentowicz, M., Marchant, R., McClymont, E., Pontevedra-Pombal, X., Ponton, C., Pourmand, A., Rizzuti, A. M., Rochefort, L., Schellekens, J., De Vleeschouwer, F., Pancost, R. D., Naafs, B. D. A., Inglis, G. N., Zheng, Y., Amesbury, M. J., Biester, H., Bindler, Richard, Blewett, J., Burrows, M. A., del Castillo Torres, D., Chambers, F. M., Cohen, A. D., Evershed, R. P., Feakins, S. J., Galka, M., Gallego-Sala, A., Gandois, L., Gray, D. M., Hatcher, P. G., Honorio Coronado, E. N., Hughes, P. D. M., Huguet, A., Kononen, M., Laggoun-Defarge, F., Lahteenoja, O., Lamentowicz, M., Marchant, R., McClymont, E., Pontevedra-Pombal, X., Ponton, C., Pourmand, A., Rizzuti, A. M., Rochefort, L., Schellekens, J., De Vleeschouwer, F., and Pancost, R. D.

Abstract

Glycerol dialkyl glycerol tetraethers (GDGTs) are membrane-spanning lipids from Bacteria and Archaea that are ubiquitous in a range of natural archives and especially abundant in peat. Previous work demonstrated that the distribution of bacterial branched GDGTs (brGDGTs) in mineral soils is correlated to environmental factors such as mean annual air temperature (MAAT) and soil pH. However, the influence of these parameters on brGDGT distributions in peat is largely unknown. Here we investigate the distribution of brGDGTs in 470 samples from 96 peatlands around the world with a broad mean annual air temperature (-8 to 27 degrees C) and pH (3-8) range and present the first peat-specific brGDGT-based temperature and pH calibrations. Our results demonstrate that the degree of cyclisation of brGDGTs in peat is positively correlated with pH, pH = 2.49 x CBTpeat + 8.07 (n = 51, R-2 = 0.58, RMSE = 0.8) and the degree of methylation of brGDGTs is positively correlated with MAAT, MAAT(peat) (degrees C) = 52.18 x MBT'(5me) - 23.05 (n = 96, R-2 = 0.76, RMSE = 4.7 degrees C). These peat-specific calibrations are distinct from the available mineral soil calibrations. In light of the error in the temperature calibration (similar to 4.7 degrees C), we urge caution in any application to reconstruct late Holocene climate variability, where the climatic signals are relatively small, and the duration of excursions could be brief. Instead, these proxies are well-suited to reconstruct large amplitude, longer-term shifts in climate such as deglacial transitions. Indeed, when applied to a peat deposit spanning the late glacial period (similar to 15.2 kyr), we demonstrate that MAAT(peat) yields absolute temperatures and relative temperature changes that are consistent with those from other proxies. In addition, the application of MAAT(peat) to fossil peat (i.e. lignites) has the potential to reconstruct terrestrial climate during the Cenozoic. We conclude that there is clear potential to us

Published
2017
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6. Introducing global peat-specific temperature and pH calibrations based on brGDGT bacterial lipids

Author

Naafs, B.D.A., primary, Inglis, G.N., additional, Zheng, Y., additional, Amesbury, M.J., additional, Biester, H., additional, Bindler, R., additional, Blewett, J., additional, Burrows, M.A., additional, del Castillo Torres, D., additional, Chambers, F.M., additional, Cohen, A.D., additional, Evershed, R.P., additional, Feakins, S.J., additional, Gałka, M., additional, Gallego-Sala, A., additional, Gandois, L., additional, Gray, D.M., additional, Hatcher, P.G., additional, Honorio Coronado, E.N., additional, Hughes, P.D.M., additional, Huguet, A., additional, Könönen, M., additional, Laggoun-Défarge, F., additional, Lähteenoja, O., additional, Lamentowicz, M., additional, Marchant, R., additional, McClymont, E., additional, Pontevedra-Pombal, X., additional, Ponton, C., additional, Pourmand, A., additional, Rizzuti, A.M., additional, Rochefort, L., additional, Schellekens, J., additional, De Vleeschouwer, F., additional, and Pancost, R.D., additional

Published
2017
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7. Effects of different times and intensities of fructification pruning in camu-camu plants.

Author

Abanto Rodríguez, C., Alves Chagas, E., Cardoso Chagas, P., Del Castillo Torres, D., Sakazaki, R. T., and Mathews Delgado, J. P.

Abstract

Copyright of Fruits is the property of International Society for Horticultural Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2017
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8. Spatio-temporal trends of mercury levels in alluvial gold mining spoils areas monitored between rainy and dry seasons in the Peruvian Amazon.

Author

Becerra-Lira E, Rodriguez-Achata L, Muñoz Ushñahua A, Corvera Gomringer R, Thomas E, Garate-Quispe J, Hilares Vargas L, Nascimento Herbay PR, Gamarra Miranda LA, Umpiérrez E, Guerrero Barrantes JA, Pillaca M, Cusi Auca E, Peña Valdeiglesias J, Russo R, Del Castillo Torres D, and Velasquez Ramírez MG

Subjects
Seasons, Peru, Gold, Clay, Mining, Soil, Environmental Monitoring, Mercury analysis
Abstract

Artisanal and small-scale gold mining (ASGM) in the Amazon has degraded tropical forests and escalated mercury (Hg) pollution, affecting biodiversity, ecological processes and rural livelihoods. In the Peruvian Amazon, ASGM annually releases some 181 tons of Hg into the environment. Despite some recent advances in understanding the spatial distribution of Hg within gold mine spoils and the surrounding landscape, temporal dynamics in Hg movement are not well understood. We aimed to reveal spatio-temporal trends of soil Hg in areas degraded by ASGM.,. We analyzed soil and sediment samples during the dry and rainy seasons across 14 ha of potentially contaminated sites and natural forests, in the vicinities of the Native community of San Jacinto in Madre de Dios, Peru. Soil Hg levels of areas impacted by ASGM (0.02 ± 0.02 mg kg -1 ) were generally below soil environmental quality standards (6.60 mg kg -1 ). However, they showed high variability, mainly explained by the type of natural cover vegetation, soil organic matter (SOM), clay and sand particles. Temporal trends in Hg levels in soils between seasons differed between landscape units distinguished in the mine spoils. During the rainy season, Hg levels decreased up to 45.5% in uncovered soils, while in artificial pond sediments Hg increased by up to 961%. During the dry season, uncovered degraded soils were more prone to lose Hg than sites covered by vegetation, mainly due to higher soil temperatures and concomitantly increasing volatilization. Soils from natural forests and degraded soil covered by regenerating vegetation showed a high capacity to retain Hg mainly due to the higher plant biomass, higher SOM, and increasing concentrations of clay particles. Disturbingly, our findings suggest high Hg mobility from gold mine spoil to close by sedimentary materials, mainly in artificial ponds through alluvial deposition and pluvial lixiviation. Thus, further research is needed on monitoring, and remediation of sediments in artificial to design sustainable land use strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Published
2024
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9. SNP Markers as a Successful Molecular Tool for Assessing Species Identity and Geographic Origin of Trees in the Economically Important South American Legume Genus Dipteryx.

Author

Honorio Coronado EN, Blanc-Jolivet C, Mader M, García-Dávila CR, Aldana Gomero D, Del Castillo Torres D, Flores Llampazo G, Hidalgo Pizango G, Sebbenn AM, Meyer-Sand BRV, Paredes-Villanueva K, Tysklind N, Troispoux V, Massot M, Carvalho C, de Lima HC, Cardoso D, and Degen B

Subjects
Bayes Theorem, Cluster Analysis, Dipteryx classification, Genetic Markers, Genotype, Geography, INDEL Mutation, South America, Trees genetics, Dipteryx genetics, Polymorphism, Single Nucleotide
Abstract

Dipteryx timber has been heavily exploited in South America since 2000s due to the increasing international demand for hardwood. Developing tools for the genetic identification of Dipteryx species and their geographical origin can help to promote legal trading of timber. A collection of 800 individual trees, belonging to 6 different Dipteryx species, was genotyped based on 171 molecular markers. After the exclusion of markers out of Hardy-Weinberg equilibrium or with no polymorphism or low amplification, 83 nuclear, 29 chloroplast, 13 mitochondrial single nucleotide polymorphisms (SNPs), and 2 chloroplast and 5 mitochondrial INDELS remained. Six genetic groups were identified using Bayesian Structure analyses of the nuclear SNPs, which corresponded to the different Dipteryx species collected in the field. Seventeen highly informative markers were identified as suitable for species identification and obtained self-assignment success rates to species level of 78-96%. An additional set of 15 molecular markers was selected to determine the different genetic clusters found in Dipteryx odorata and Dipteryx ferrea, obtaining self-assignment success rates of 91-100%. The success to assign samples to the correct country of origin using all or only the informative markers improved when using the nearest neighbor approach (69-92%) compared to the Bayesian approach (33-80%). While nuclear and chloroplast SNPs were more suitable for differentiating the different Dipteryx species, mitochondrial SNPs were ideal for determining the genetic clusters of D. odorata and D. ferrea. These 32 selected SNPs will be invaluable genetic tools for the accurate identification of species and country of origin of Dipteryx timber., (© The American Genetic Association 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Published
2020
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10. Molecular evidence for three genetic species of Dipteryx in the Peruvian Amazon.

Author

Garcia-Davila C, Aldana Gomero D, Renno JF, Diaz Soria R, Hidalgo Pizango G, Flores Llampazo G, Castro-Ruiz D, Mejia de Loayza E, Angulo Chavez C, Mader M, Tysklind N, Paredes-Villanueva K, Del Castillo Torres D, Degen B, and Honorio Coronado EN

Subjects
Alleles, DNA, Plant genetics, Genetic Variation, Genotype, Haplotypes genetics, Microsatellite Repeats genetics, Peru, Phylogeny, Rivers, Sequence Analysis, DNA, Species Specificity, Dipteryx genetics, Plastids genetics
Abstract

There is a high international demand for timber from the genus Dipteryx, or "shihuahuaco" as it is known in Peru. Developing tools that allow the identification and discrimination of Dipteryx species is therefore important for supporting management of natural populations and to underpin legal trade of its timber. The objective of this study was the molecular characterization of Dipteryx species in the Peruvian Amazonia. Two plastid regions (cpDNA: trnH-psbA and matK) were sequenced and 11 microsatellite markers (nDNA) were genotyped for 32 individuals identified as Dipteryx charapilla, D. micrantha morphotype 1 and D. micrantha morphotype 2. Using the concatenated sequences of the plastid genes, we identified ten haplotypes that were not shared between the species or between the D. micrantha morphotypes. Haplotypic diversity was greater in D. micrantha morphotype 2 and D. charapilla than in D. micrantha morphotype 1, which presented only one haplotype with a wide distribution in Peru. The microsatellites allowed the discrimination of the same three clades and identified diagnostic alleles for each clade. These results allowed us to demonstrate that the two morphotypes of D. micrantha are different at both the plastid and nuclear markers, which supports the existence of three genetically distinct species in Peru. This study provides information for the genetic discrimination of Dipteryx species and emphasises the importance of conserving the genetic variability of this genus in the Peruvian Amazonia.

Published
2020
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11. The Forest Observation System, building a global reference dataset for remote sensing of forest biomass.

Author

Schepaschenko D, Chave J, Phillips OL, Lewis SL, Davies SJ, Réjou-Méchain M, Sist P, Scipal K, Perger C, Herault B, Labrière N, Hofhansl F, Affum-Baffoe K, Aleinikov A, Alonso A, Amani C, Araujo-Murakami A, Armston J, Arroyo L, Ascarrunz N, Azevedo C, Baker T, Bałazy R, Bedeau C, Berry N, Bilous AM, Bilous SY, Bissiengou P, Blanc L, Bobkova KS, Braslavskaya T, Brienen R, Burslem DFRP, Condit R, Cuni-Sanchez A, Danilina D, Del Castillo Torres D, Derroire G, Descroix L, Sotta ED, d'Oliveira MVN, Dresel C, Erwin T, Evdokimenko MD, Falck J, Feldpausch TR, Foli EG, Foster R, Fritz S, Garcia-Abril AD, Gornov A, Gornova M, Gothard-Bassébé E, Gourlet-Fleury S, Guedes M, Hamer KC, Susanty FH, Higuchi N, Coronado ENH, Hubau W, Hubbell S, Ilstedt U, Ivanov VV, Kanashiro M, Karlsson A, Karminov VN, Killeen T, Koffi JK, Konovalova M, Kraxner F, Krejza J, Krisnawati H, Krivobokov LV, Kuznetsov MA, Lakyda I, Lakyda PI, Licona JC, Lucas RM, Lukina N, Lussetti D, Malhi Y, Manzanera JA, Marimon B, Junior BHM, Martinez RV, Martynenko OV, Matsala M, Matyashuk RK, Mazzei L, Memiaghe H, Mendoza C, Mendoza AM, Moroziuk OV, Mukhortova L, Musa S, Nazimova DI, Okuda T, Oliveira LC, Ontikov PV, Osipov AF, Pietsch S, Playfair M, Poulsen J, Radchenko VG, Rodney K, Rozak AH, Ruschel A, Rutishauser E, See L, Shchepashchenko M, Shevchenko N, Shvidenko A, Silveira M, Singh J, Sonké B, Souza C, Stereńczak K, Stonozhenko L, Sullivan MJP, Szatniewska J, Taedoumg H, Ter Steege H, Tikhonova E, Toledo M, Trefilova OV, Valbuena R, Gamarra LV, Vasiliev S, Vedrova EF, Verhovets SV, Vidal E, Vladimirova NA, Vleminckx J, Vos VA, Vozmitel FK, Wanek W, West TAP, Woell H, Woods JT, Wortel V, Yamada T, Nur Hajar ZS, and Zo-Bi IC

Subjects
Conservation of Natural Resources, Environmental Monitoring methods, Biomass, Forests, Remote Sensing Technology
Abstract

Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.

Published
2019
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