The Forest Observation System, building a global reference dataset for remote sensing of forest biomass
Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu dataset, časopisecké články, práce podpořená grantem
Grantová podpora
4000114425/15/NL/FF/gp
European Space Agency (ESA) - International
19-77-30015
Russian Science Foundation (RSF) - International
PubMed
31601817
PubMed Central
PMC6787017
DOI
10.1038/s41597-019-0196-1
PII: 10.1038/s41597-019-0196-1
Knihovny.cz E-zdroje
- MeSH
- biomasa * MeSH
- lesy * MeSH
- monitorování životního prostředí metody MeSH
- technologie dálkového snímání * MeSH
- zachování přírodních zdrojů MeSH
- Publikační typ
- časopisecké články MeSH
- dataset MeSH
- práce podpořená grantem MeSH
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.
AMAP IRD CNRS CIRAD INRA University Montpellier Montpellier France
Bioversity international P O Box 2008 Messa Yaoundé Cameroun
Center for Agricultural research in Suriname CELOS 1914 Paramaribo Suriname
Centre for International Forestry Research CIFOR Jalan CIFOR Situ Gede Bogor 16115 Indonesia
CIRAD Forêts et Sociétés Campus International de Baillarguet Montpellier F 34398 France
CIRAD UMR EcoFoG Campus Agronomique BP 701 Kourou 97387 France French Guiana
Department of Environment and Geography University of York Heslington York YO10 5NG UK
Department of Geography and Earth Sciences Aberystwyth University Aberystwyth SY23 3DB UK
Embrapa Amazonia Oriental Travessa Doutor Enéas Pinheiro Belém PA 66095 903 Brazil
Embrapa BR 364 Caixa postal 321 Rio Branco CEP 69 900 970 Brazil
Embrapa Rodovia AM 10 km 29 Manaus AM 69010 970 Brazil
Embrapa Rodovia Juscelino Kubitscheck Km 5 no 2 600 Macapa Caixa Postal 10 CEP 68903 419 Brazil
European Space Agency ESTEC Noordwijk The Netherlands
Forest Management in Bolivia Sacta Bolivia
Forest Research Institute Department of Geomatics Braci Leśnej 3 Sękocin Stary Raszyn 05 090 Poland
Forestry faculty Bauman Moscow State Technical University Mytischi 141005 Russia
Forestry Research Institute of Ghana UP Box 63 KNUST Kumasi Ghana
Forêts et Sociétés Univ Montpellier CIRAD Montpellier F 34398 France
FRIM Forest Research Institute of Malaysia 52109 Kepong Selangor Kuala Lumpur Malaysia
FRIM Forest Reserach Institute of Malaysia 52109 Kepong Selangor Kuala Lumpur Malaysia
Global Change Research Institute CAS Bělidla 986 4a Brno 603 00 Czech Republic
Guyana Forestry Commission 1 Water Street Kingston Georgetown Guyana
Herbier National du Gabon B P 1165 Libreville Gabon
Hiroshima University 1 7 1 Kagamiyama Higashi Hiroshima Hiroshima 739 8521 Japan
Institut Centrafricain de Recherche Agronomique ICRA BP 122 Bangui Central African Republic
Jardín Botánico de Missouri; Universidad Nacional de San Antonio Abad del Cusco Oxapampa Peru
Laboratoire Evolution et Diversité Biologique CNRS Université Paul Sabatier Toulouse France
Mensuration Unit Forestry Commission of Ghana 4 3rd Avenue Ridge Kumasi POB M434 Ghana
Morton Arboretum 4100 Illinois Rte 53 Lisle 60532 IL USA
Naturalis Biodiversity Center Leiden The Netherlands
Nicholas School of the Environment Duke University P O Box 90328 Durham NC 27708 USA
ONF ONF Réserve de Montabo Cayenne Cedex Cayenne BP 7002; 97307 French Guiana
Plant Systematic and Ecology Laboratory University of Yaoundé 1 P O Box 047 Yaounde Cameroon
Reshetnev Siberian state university of science and technology pr Mira 82 Krasnoyarsk 660049 Russia
Russian Institute of Continuous Education in Forestry Institutskaya 17 Pushkino 141200 Russia
School of Biology University of Leeds Leeds LS2 9JT UK
School of Geography and the Environment University of Oxford Oxford OX1 3QY UK
School of Geography University of Leeds Leeds LS2 9JT UK
SI Entomology Smithsonian Institution PO Box 37012 MRC 187 Washington DC DC 20013 7012 USA
Siberian Federal University Svobodnyy Ave 79 Krasnoyarsk 660041 Russia
Smithsonian Tropical Research Institute Balboa Ancon Panama 3092 Panama
Sodefor boulevard François Mitterrand Cocody Abidjan 01BP 3770 Côte d'Ivoire
Spatial Focus GmbH Vienna Austria
State Nature Reserve Denezhkin Kamen Lenina 6 Sverdlovsk reg Severouralsk 624480 Russia
The Field Musium 1400S Lake Shore Dr Chicago IL 60605 USA
The Landscapes and Livelihoods Group 20 Chambers St Edinburgh EH1 1JZ UK
Unaffiliated Sommersbergseestrasse 291 Bad Aussee 8990 Austria
Universidad Autónoma del Beni Riberalta Bolivia
Universidad Autonoma Gabriel Rene Moreno Santa Cruz Bolivia
Universidad Politecnica de Madrid Calle Ramiro de Maeztu 7 Madrid 28040 Spain
University College London 30 Guilford Street London WC1N 1EH UK
University of Oregon 1585 E 13th Ave Eugene OR 97403 USA
W R T College of Agriculture and Forestry University of Liberia Capitol Hill Monrovia 9020 Liberia
World Wildlife Fund Calle Diego de Mendoza 299 Santa Cruz de la Sierra Bolivia
doi: 10.1038/ncomms7857 PubMed
Zobrazit více v PubMed
Bojinski S, et al. The Concept of Essential Climate Variables in Support of Climate Research, Applications, and Policy. Bull. Am. Meteorol. Soc. 2014;95:1431–1443. doi: 10.1175/BAMS-D-13-00047.1. DOI
Pereira HM, et al. Essential Biodiversity Variables. Science. 2013;339:277–278. doi: 10.1126/science.1229931. PubMed DOI
Schepaschenko, D.
Chave Jérôme, Davies Stuart J., Phillips Oliver L., Lewis Simon L., Sist Plinio, Schepaschenko Dmitry, Armston John, Baker Tim R., Coomes David, Disney Mathias, Duncanson Laura, Hérault Bruno, Labrière Nicolas, Meyer Victoria, Réjou-Méchain Maxime, Scipal Klaus, Saatchi Sassan. Ground Data are Essential for Biomass Remote Sensing Missions. Surveys in Geophysics. 2019;40(4):863–880. doi: 10.1007/s10712-019-09528-w. DOI
Réjou-Méchain Maxime, Tanguy Ariane, Piponiot Camille, Chave Jérôme, Hérault Bruno. biomass : an r package for estimating above-ground biomass and its uncertainty in tropical forests. Methods in Ecology and Evolution. 2017;8(9):1163–1167. doi: 10.1111/2041-210X.12753. DOI
Anderson‐Teixeira KJ, et al. CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change. Glob. Change Biol. 2015;21:528–549. doi: 10.1111/gcb.12712. PubMed DOI
Malhi Y, et al. An international network to monitor the structure, composition and dynamics of Amazonian forests (RAINFOR) J. Veg. Sci. 2002;13:439–450. doi: 10.1111/j.1654-1103.2002.tb02068.x. DOI
Lewis SL, et al. Increasing carbon storage in intact African tropical forests. Nature. 2009;457:1003–1006. doi: 10.1038/nature07771. PubMed DOI
Qie L, et al. Long-term carbon sink in Borneo’s forests halted by drought and vulnerable to edge effects. Nat. Commun. 2017;8:1966. doi: 10.1038/s41467-017-01997-0. PubMed DOI PMC
Lopez‐Gonzalez G, Lewis SL, Burkitt M, Phillips OL. ForestPlots.net: a web application and research tool to manage and analyse tropical forest plot data. J. Veg. Sci. 2011;22:610–613. doi: 10.1111/j.1654-1103.2011.01312.x. DOI
Schepaschenko D, et al. A dataset of forest biomass structure for Eurasia. Sci. Data. 2017;4:201770. doi: 10.1038/sdata.2017.70. PubMed DOI PMC
Pietsch, S. A. Modelling ecosystem pools and fluxes.
Sist P, et al. The Tropical managed Forests Observatory: a research network addressing the future of tropical logged forests. Appl. Veg. Sci. 2015;18:171–174. doi: 10.1111/avsc.12125. DOI
TERN Auscover.
Condit RS, et al. Tropical forest dynamics across a rainfall gradient and the impact of an El Niño dry season. J. Trop. Ecol. 2004;20:51–72. doi: 10.1017/S0266467403001081. DOI
Liang J, et al. Positive biodiversity-productivity relationship predominant in global forests. Science. 2016;354:196. doi: 10.1126/science.aaf8957. PubMed DOI
Labrière N, et al. In situ reference datasets from the TropiSAR and AfriSAR campaigns in support of upcoming spaceborne biomass missions. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2018;11:3617–3627. doi: 10.1109/JSTARS.2018.2851606. DOI
Taylor P, et al. Landscape-scale controls on aboveground forest carbon stocks on the Osa peninsula, Costa Rica. PLOS ONE. 2015;10:e0126748. doi: 10.1371/journal.pone.0126748. PubMed DOI PMC
Hofhansl F, et al. Sensitivity of tropical forest aboveground productivity to climate anomalies in SW Costa Rica. Glob. Biogeochem. Cycles. 2014;28:1437–1454. doi: 10.1002/2014GB004934. DOI
Piponiot C, et al. Carbon recovery dynamics following disturbance by selective logging in Amazonian forests. eLife. 2016;5:e21394. doi: 10.7554/eLife.21394. PubMed DOI PMC
Lewis Simon L, et al. Above-ground biomass and structure of 260 African tropical forests. Philos. Trans. R. Soc. B Biol. Sci. 2013;368:20120295. doi: 10.1098/rstb.2012.0295. PubMed DOI PMC
Sullivan MJP, et al. Field methods for sampling tree height for tropical forest biomass estimation. Methods Ecol. Evol. 2018;9:1179–1189. doi: 10.1111/2041-210X.12962. PubMed DOI PMC
ter Steege H, et al. Hyperdominance in the Amazonian tree flora. Science. 2013;342:1243092. doi: 10.1126/science.1243092. PubMed DOI
Baker TR, et al. Fast demographic traits promote high diversification rates of Amazonian trees. Ecol. Lett. 2014;17:527–536. doi: 10.1111/ele.12252. PubMed DOI PMC
Johnson MO, et al. Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models. Glob. Change Biol. 2016;22:3996–4013. doi: 10.1111/gcb.13315. PubMed DOI PMC
Aguirre‐Gutiérrez J, et al. Drier tropical forests are susceptible to functional changes in response to a long-term drought. Ecol. Lett. 2019;22:855–865. doi: 10.1111/ele.13243. PubMed DOI
Phillips OL, et al. Drought Sensitivity of the Amazon Rainforest. Science. 2009;323:1344–1347. doi: 10.1126/science.1164033. PubMed DOI
Esquivel‐Muelbert A, et al. Seasonal drought limits tree species across the Neotropics. Ecography. 2017;40:618–629. doi: 10.1111/ecog.01904. DOI
Feldpausch TR, et al. Amazon forest response to repeated droughts. Glob. Biogeochem. Cycles. 2016;30:964–982. doi: 10.1002/2015GB005133. DOI
Chave J, et al. Improved allometric models to estimate the aboveground biomass of tropical trees. Glob. Change Biol. 2014;20:3177–3190. doi: 10.1111/gcb.12629. PubMed DOI
Feldpausch TR, et al. Tree height integrated into pantropical forest biomass estimates. Biogeosciences. 2012;9:3381–3403. doi: 10.5194/bg-9-3381-2012. DOI
Bastin J-F, et al. Pan-tropical prediction of forest structure from the largest trees. Glob. Ecol. Biogeogr. 2018;27:1366–1383. doi: 10.1111/geb.12803. DOI
Feldpausch TR, et al. Height-diameter allometry of tropical forest trees. Biogeosciences. 2011;8:1081–1106. doi: 10.5194/bg-8-1081-2011. DOI
Phillips OL. Changes in the Carbon Balance of Tropical Forests: Evidence from Long-Term Plots. Science. 1998;282:439–442. doi: 10.1126/science.282.5388.439. PubMed DOI
Slik JWF, et al. Large trees drive forest aboveground biomass variation in moist lowland forests across the tropics. Glob. Ecol. Biogeogr. 2013;22:1261–1271. doi: 10.1111/geb.12092. DOI
Hubau W, et al. The persistence of carbon in the African forest understory. Nat. Plants. 2019;5:133. doi: 10.1038/s41477-018-0316-5. PubMed DOI
Mitchard ETA, et al. Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites. Glob. Ecol. Biogeogr. 2014;23:935–946. doi: 10.1111/geb.12168. PubMed DOI PMC
Santoro M, et al. Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR. Remote Sens. Environ. 2015;168:316–334. doi: 10.1016/j.rse.2015.07.005. DOI
Valbuena R, et al. Enhancing of accuracy assessment for forest above-ground biomass estimates obtained from remote sensing via hypothesis testing and overfitting evaluation. Ecol. Model. 2017;366:15–26. doi: 10.1016/j.ecolmodel.2017.10.009. DOI
Thomas CD, et al. Extinction risk fromclimate change. Nature. 2004;427:145–148. doi: 10.1038/nature02121. PubMed DOI
Esquivel‐Muelbert A, et al. Compositional response of Amazon forests to climate change. Glob. Change Biol. 2019;25:39–56. doi: 10.1111/gcb.14413. PubMed DOI PMC
Brienen RJW, et al. Long-term decline of the Amazon carbon sink. Nature. 2015;519:344–348. doi: 10.1038/nature14283. PubMed DOI
Pan Y, et al. A large and persistent carbon sink in the world’s forests. Science. 2011;333:988–993. doi: 10.1126/science.1201609. PubMed DOI
Phillips OL, Hall P, Gentry AH, Sawyer SA, Vásquez R. Dynamics and species richness of tropical rain forests. Proc. Natl. Acad. Sci. 1994;91:2805–2809. doi: 10.1073/pnas.91.7.2805. PubMed DOI PMC
de Souza FC, et al. Evolutionary heritage influences Amazon tree ecology. Proc R Soc B. 2016;283:20161587. doi: 10.1098/rspb.2016.1587. PubMed DOI PMC
Coronado ENH, et al. Phylogenetic diversity of Amazonian tree communities. Divers. Distrib. 2015;21:1295–1307. doi: 10.1111/ddi.12357. DOI
ter Steege H, et al. Estimating the global conservation status of more than 15,000 Amazonian tree species. Sci. Adv. 2015;1:e1500936. doi: 10.1126/sciadv.1500936. PubMed DOI PMC
Sullivan MJP, et al. Diversity and carbon storage across the tropical forest biome. Sci. Rep. 2017;7:39102. doi: 10.1038/srep39102. PubMed DOI PMC
Fauset S, et al. Hyperdominance in Amazonian forest carbon cycling. Nat. Commun. 2015;6:6857. doi: 10.1038/ncomms7857. PubMed DOI PMC
Levis C, et al. Persistent effects of pre-Columbian plant domestication on Amazonian forest composition. Science. 2017;355:925–931. doi: 10.1126/science.aal0157. PubMed DOI
Willcock S, et al. Land cover change and carbon emissions over 100 years in an African biodiversity hotspot. Glob. Change Biol. 2016;22:2787–2800. doi: 10.1111/gcb.13218. PubMed DOI
Réjou-Méchain M, et al. Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks. Biogeosciences. 2014;11:6827–6840. doi: 10.5194/bg-11-6827-2014. DOI
Knapp N, Fischer R, Huth A. Linking lidar and forest modeling to assess biomass estimation across scales and disturbance states. Remote Sens. Environ. 2018;205:199–209. doi: 10.1016/j.rse.2017.11.018. DOI
Chave J, et al. Towards a worldwide wood economics spectrum. Ecol. Lett. 2009;12:351–366. doi: 10.1111/j.1461-0248.2009.01285.x. PubMed DOI
Zanne AE, 2009. Global Wood Density Database. Dryad Digital Repository. DOI
Zagreev, V. V.
Schepaschenko D, et al. Improved estimates of biomass expansion factors for Russian forests. Forests. 2018;9:312. doi: 10.3390/f9060312. DOI
Schepaschenko D, 2019. A global reference dataset for remote sensing of forest biomass. The Forest Observation System approach. IIASA. PubMed DOI PMC
Baker TR, et al. Variation in wood density determines spatial patterns in Amazonian forest biomass. Glob. Change Biol. 2004;10:545–562. doi: 10.1111/j.1365-2486.2004.00751.x. DOI
Marthews, T. R.
Phillips OL, et al. Species matter: wood density influences tropical forest biomass at multiple scales. Surv. Geophys. 2019 doi: 10.1007/s10712-019-09540-0. PubMed DOI PMC
Baker TR, et al. Maximising synergy among tropical plant systematists, ecologists, and evolutionary biologists. Trends Ecol. Evol. 2017;32:258–267. doi: 10.1016/j.tree.2017.01.007. PubMed DOI