Труды сотрудников ИЛ им. В.Н. Сукачева СО РАН

/ K. R. Briffa [et al.] // Quat. Sci. Rev. - 2013. - Vol. 72. - P83-107, DOI 10.1016/j.quascirev.2013.04.008. - Cited References: 70. - KRB, TMM and TJO acknowledge support from NERC (NE/G018863/1). RMH, AVK, VSM and SGS acknowledge support from the partnership project of the Ural and Siberian Branches of the Russian Academy of Sciences (No 12-C-4-1038 and No 69). SGS, VSM and RMH acknowledge support from the Russian Foundation for Basic Research (No 11-04-00623-a, No 13-04-00961-a and No 13-04-02058). . - 25. - ISSN 0277-3791РУБ Geography, Physical + Geosciences, Multidisciplinary

Аннотация: The development of research into the history of tree growth and inferred summer temperature changes in Yamaha spanning the last 2000 years is reviewed. One focus is the evolving production of tree-ring width (TRW) and tree-ring maximum-latewood density (MXD) larch (Larix sibirica) chronologies, incorporating different applications of Regional Curve Standardisation (RCS). Another focus is the comparison of independent data representing past tree growth in adjacent Yamaha areas: Yamal and Polar Urals, and the examination of the evidence for common growth behaviour at different timescales. The sample data we use are far more numerous and cover a longer time-span at Yamal compared to the Polar Urals, but Yamal has only TRW, while there are both TRW and MXD for the Polar Urals. We use more data (sub-fossil and from living trees) than in previous dendroclimatic studies in this region. We develop a new TRW chronology for Yamal, more than 2000 years long and running up to 2005. For the Polar Urals we develop new TRW and MXD chronologies that show good agreement at short (<15 years) and medium (15-100 years) timescales demonstrating the validity of attempts to reconcile the evidence of longer-timescale information that they provide. We use a "conservative" application of the RCS approach (two-curve signal-free RCS), guarding against the possibility of "modern sample bias": a possible inflation of recent chronology values arising out of inadvertent selection of mostly relatively fast-growing trees in recent centuries. We also transform tree indices to have a normal distribution to remove the positive chronology skew often apparent in RCS TRW chronologies. This also reduces the apparent magnitude of 20th century tree-growth levels. There is generally good agreement between all chronologies as regards the major features of the decadal to centennial variability. Low tree-growth periods for which the inferred summer temperatures are approximately 2.5 degrees C below the 1961-90 reference are apparent in the 15-year smoothed reconstructions, centred around 1005, 1300, 1455, 1530, particularly the 1810s where the inferred cooling reaches -4 degrees C or even -6 degrees C for individual years, and the 1880s. These are superimposed on generally cool pre-20th century conditions: the long-term means of the pre-1900 reconstructed temperature anomalies range from -0.6 to -0.9 degrees C in our alternative reconstructions. There are numerous periods of one or two decades with relatively high growth (and inferred summer temperatures close to the 1961-1990 level) but at longer timescales only the 40-year period centred at 250 CE appears comparable with 20th century warmth. Although the central temperature estimate for this period is below that for the recent period, when we take into account the uncertainties we cannot be highly confident that recent warmth has exceeded the temperature of this earlier warm period. While there are clear warm decades either side of 1000 CE, neither TRW nor MXD data support the conclusion that temperatures were exceptionally high during medieval times. One previous version of the Polar Urals TRW chronology is shown here to be in error due to an injudicious application of RCS to non-homogeneous sample data, partly derived from root-collar samples that produce spuriously high chronology values in the 11th and 15th centuries. This biased chronology has been used in a number of recent studies aimed at reconstructing wider scale temperature histories. All of the chronologies we have produced here clearly show a generally high level of growth throughout their most recent 80 years. Allowing for chronology and reconstruction uncertainty, the mean of the last 100 years of the reconstruction is likely warmer than any century in the last 2000 years in this region. (C) 2013 The Authors. Published by Elsevier Ltd. All rights reserved.

Полный текст,
WOS,
Scopus

Держатели документа:
[Briffa, Keith R.
Melvin, Thomas M.
Osborn, Timothy J.] Univ E Anglia, Sch Environm Sci, Climat Res Unit, Norwich NR4 7TJ, Norfolk, England
[Hantemirov, Rashit M.
Mazepa, Valeriy S.
Shiyatov, Stepan G.] Russian Acad Sci, Ural Branch, Inst Plant & Anim Ecol, Ekaterinburg 620144, Russia
[Kirdyanov, Alexander V.] Russian Acad Sci, Siberian Branch, VN Sukachev Inst Forest, Krasnoyarsk 660036, Russia
[Esper, Jan] Johannes Gutenberg Univ Mainz, Dept Geog, D-55099 Mainz, Germany
Институт леса им. В.Н. Сукачева Сибирского отделения Российской академии наук : 660036, Красноярск, Академгородок 50/28

Доп.точки доступа:
Briffa, K.R.; Melvin, T.M.; Osborn, T.J.; Hantemirov, R.M.; Kirdyanov, A.V.; Mazepa, V.S.; Shiyatov, S.G.; Esper, J...

/ A. J. Dolman [et al.] // Biogeosciences. - 2012. - Vol. 9, Is. 12. - P5323-5340, DOI 10.5194/bg-9-5323-2012. - Cited References: 90. - The authors would like to acknowledge the inspiration of the Global Carbon Project's RECCAP team that laid the basis for the present work. A. J. D. and T. C. acknowledge partial support from the EU FP7 Coordination Action on Carbon Observing System (COCOS, grant agreement no. 212196 and the Operational Global Carbon Observing System (GEOCARBON, grant agreement no: 283080). A. S. and D. S. acknowledge support from European Union Grants FP7-212535 (Project CC-TAME), FP7-244122 (GHG-Europe), FP7-283080 (GEO-Carbon) and by the Global Environmental Forum, Japan (Project GEF-2).E.-D. S., N. T. and A. J. D. acknowledge support from the Russian "Megagrant" 11.G34.31.0014 from 30 November 2010 to E.-D. Schulze by the Russian Federation and the Siberian Federal University to support research projects by leading scientists at Russian Institutions of higher education. . - 18. - ISSN 1726-4170РУБ Ecology + Geosciences, Multidisciplinary

Аннотация: We determine the net land to atmosphere flux of carbon in Russia, including Ukraine, Belarus and Kazakhstan, using inventory-based, eddy covariance, and inversion methods. Our high boundary estimate is -342 TgC yr(-1) from the eddy covariance method, and this is close to the upper bounds of the inventory-based Land Ecosystem Assessment and inverse models estimates. A lower boundary estimate is provided at -1350 TgC yr(-1) from the inversion models. The average of the three methods is -613.5 TgC yr(-1). The methane emission is estimated separately at 41.4 Tg C yr(-1). These three methods agree well within their respective error bounds. There is thus good consistency between bottom-up and top-down methods. The forests of Russia primarily cause the net atmosphere to land flux (-692 TgC yr(-1) from the LEA. It remains however remarkable that the three methods provide such close estimates (-615, -662, -554 TgC yr(-1)) for net biome production (NBP), given the inherent uncertainties in all of the approaches. The lack of recent forest inventories, the few eddy covariance sites and associated uncertainty with upscaling and undersampling of concentrations for the inversions are among the prime causes of the uncertainty. The dynamic global vegetation models (DGVMs) suggest a much lower uptake at -91 TgC yr(-1), and we argue that this is caused by a high estimate of heterotrophic respiration compared to other methods.

WOS,
Scopus

Держатели документа:
[Dolman, A. J.
Chen, T.
van der Molen, M. K.
Marchesini, L. Belelli] Vrije Univ Amsterdam, Dept Earth Sci, NL-1081 HV Amsterdam, Netherlands
[Shvidenko, A.
Schepaschenko, D.] Int Inst Appl Syst Anal, A-2361 Laxenburg, Austria
[Ciais, P.] CEA CNRS UVSQ, IPSL LSCE, Ctr Etud Orme Merisiers, F-91191 Gif Sur Yvette, France
[Tchebakova, N.] SB RAS, VN Sukachev Inst Forest, Krasnoyarsk 660036, Russia
[Tchebakova, N.] SIF SB RAS, Krasnoyarsk, Russia
[Tchebakova, N.] Siberian Fed Univ, Krasnoyarsk, Russia
[van der Molen, M. K.] Wageningen Univ, Dept Meteorol & Air Qual, Wageningen, Netherlands
[Maximov, T. C.] RAS, Inst Biol Problems Cryolithozone, Siberian Branch, Yakutsk, Russia
[Maksyutov, S.] Natl Inst Environm Studies, Ctr Global Environm Res, Tsukuba, Ibaraki 3058506, Japan
[Schulze, E. -D.] Max Planck Inst Biogeochem, Jena, Germany

Доп.точки доступа:
Dolman, A.J.; Shvidenko, A...; Schepaschenko, D...; Ciais, P...; Tchebakova, N...; Chen, T...; van der Molen, M.K.; Marchesini, L.B.; Maximov, T.C.; Maksyutov, S...; Schulze, E.D.

[Text] / A. Z. Shvidenko [et al.] // Dokl. Earth Sci. - 2011. - Vol. 441, Is. 2. - P1678-1682, DOI 10.1134/S1028334X11120075. - Cited References: 15 . - 5. - ISSN 1028-334XРУБ Geosciences, Multidisciplinary

Аннотация: Verified estimates of wildfire area and related carbon emissions in territories of Russia are reported for the period of 1998-2010. It is shown that the average burnt area is estimated to be at 8.23 million hectares per year (uncertainty +/- 9.0%, confidence interval 0.9), and carbon emissions-121 Tg C yr(-1) (+/- 23%), with a significant interannual variability of these indicators. A quantitative characteristic of fire emissions by species is reported. Forests are a source of three quarters of all carbon emissions caused by wildfires. A significant acceleration of fire regimes is expected during the 21st century as a result of climate change in the country.

Полный текст,
Scopus,
WOS

Держатели документа:
[Shvidenko, A. Z.
Shchepashchenko, D. G.
McCallum, I.
Lakyda, I. P.] Int Inst Appl Syst Anal, A-2361 Laxenburg, Austria
[Shchepashchenko, D. G.] Moscow State Forest Univ, Moscow 141005, Moscow Oblast, Russia
[Shvidenko, A. Z.
Vaganov, E. A.
Sukhinin, A. I.] Russian Acad Sci, Sukachev Inst Forest, Siberian Div, Krasnoyarsk 660036, Russia
[Vaganov, E. A.] Siberian Fed Univ, Krasnoyarsk 660041, Russia
[Maksyutov, Sh Sh] Natl Inst Environm Studies, Tsukuba, Ibaraki, Japan

Доп.точки доступа:
Shvidenko, A.Z.; Shchepashchenko, D.G.; Vaganov, E.A.; Sukhinin, A.I.; Maksyutov, S.S.; McCallum, I...; Lakyda, I.P.

[Text] / E. A. Vaganova [et al.] // Contemp. Probl. Ecol. - 2008. - Vol. 1, Is. 2. - P168-182, DOI 10.1134/S1995425508020021. - Cited References: 67 . - 15. - ISSN 1995-4255РУБ Ecology

Аннотация: Results of measurements and calculations of carbon budget parameters of forests and swamps of Siberia are reported. The zonal variability of reserves (and an increment in reserves) of carbon in forest and swamp ecosystems is characterized, carbon dioxide fluxes are measured directly by means of microeddy pulsations, and an uncertainty brought into the calculation of carbon budget parameters by forest fires is estimated.

Полный текст,
WOS

Держатели документа:
[Vaganova, E. A.
Vedrova, E. F.
Verkhovets, S. V.
Efremov, S. P.
Efremova, T. T.
Onuchin, A. A.
Sukhinin, A. I.
Shibistova, O. B.] RAS, Siberian Branch, Sukachev Inst Forest, Krasnoyarsk 660036, Russia
[Kruglov, V. B.] Krasnoyarsk State Univ, Krasnoyarsk 660041, Russia

Доп.точки доступа:
Vaganov, E.A.; Vedrova, E.F.; Verkhovets, S.V.; Efremov, S.P.; Efremova, T.T.; Kruglov, V.B.; Onuchin, A.A.; Sukhinin, A.I.; Shibistova, O.B.

[Text] / L. B. Marchesini [et al.] // Biogeosciences. - 2007. - Vol. 4, Is. 4. - P581-595. - Cited References: 64 . - 15. - ISSN 1726-4170РУБ Ecology + Geosciences, Multidisciplinary

Аннотация: Steppe ecosystems represent an interesting case in which the assessment of carbon balance may be performed through a cross validation of the eddy covariance measurements against ecological inventory estimates of carbon exchanges (Ehman et al., 2002; Curtis et al., 2002). Indeed, the widespread presence of ideal conditions for the applicability of the eddy covariance technique, as vast and homogeneous grass vegetation cover over flat terrains (Baldocchi, 2003), make steppes a suitable ground to ensure a constrain to flux estimates with independent methodological approaches. We report about the analysis of the carbon cycle of a true steppe ecosystem in southern Siberia during the growing season of 2004 in the framework of the TCOS-Siberia project activities performed by continuous monitoring of CO2 fluxes at ecosystem scale by the eddy covariance method, fortnightly samplings of phytomass, and ingrowth cores extractions for NPP assessment, and weekly measurements of heterotrophic component of soil CO2 effluxes obtained by an experiment of root exclusion. The carbon balance of the monitored natural steppe was, according to micrometeorological measurements, a sink of carbon of 151.7 +/- 36.9 g Cm-2, cumulated during the growing season from May to September. This result was in agreement with the independent estimate through ecological inventory which yielded a sink of 150.1 g Cm-2 although this method was characterized by a large uncertainty (+/- 130%) considering the 95% confidence interval of the estimate. Uncertainties in belowground process estimates account for a large part of the error. Thus, in particular efforts to better quantify the dynamics of root biomass (growth and turnover) have to be undertaken in order to reduce the uncertainties in the assessment of NPP. This assessment should be preferably based on the application of multiple methods, each one characterized by its own merits and flaws.

WOS,
Scopus

Держатели документа:
Univ Tuscia, Dept Forest Resources & Environm, I-01100 Viterbo, Italy
Max Planck Inst Biogeochem, D-07745 Jena, Germany
RAS, SB, Sukachev Inst Forest, Krasnoyarsk 660036, Russia

Доп.точки доступа:
Marchesini, L.B.; Papale, D...; Reichstein, M...; Vuichard, N...; Tchebakova, N...; Valentini, R...

[Текст] / D. L. Grodnitsky // Zhurnal Obshchei Biol. - 1998. - Vol. 59, Is. 6. - С. 617-622. - Cited References: 117 . - 17. - ISSN 0044-4596РУБ Biology

Аннотация: The development of certain form depends on natural selection and morphogenesis. The former process is resulted in analogies - characters of convergent similarity, while the latter can lead to non-adaptive parallel similarity of relatives (homologous series of N.I. Vavilov). Morphogenetic factor is shaped by past selection but does not depend on it at each new evolution act: spectrum of forms that can be produced is totally determined by embryological mechanisms and precedes the beginning of an evolutionary change. Mutual independence of two factors allows to use Bohr's correspondence principle. According to this principle any explanation is not full: it has its own competence area with its own rules for conclusions; there is no rules for logic transition between groups of accidental events; interaction of factors is expressed only as a limitation of their pattern formation abilities. To diminish uncertainty one can use the principle of evolution stabilisation of function by N.V. Kokshaisky, i.e. statement that functions of organism level are kept stable in the process of evolution while some changes at the lower levels are possible. The higher level of changes, the more complete reconstruction takes place in organism. The direction of evolution is minimisation of total sum of changes. As a consequence, the higher hierarchical level of function, more adaptive characters are belonged to its structures. And opposite, the lower hierarchical level, the more freedom for morphogenetic changes, the form of structures becomes indifferent for selection. Therefore the characters of high hierarchical levels can be explained in terms of adaptation, while the features of low level - on the base of morphogenetic peculiarities.

WOS,
Scopus

Держатели документа:
Russian Acad Sci, Siberian Branch, VN Sukachev Inst Forest Res, Krasnoyarsk 660036, Russia

Доп.точки доступа:
Grodnitsky, D.L.

[Text] / CSR Neigh [et al.] // Remote Sens. Environ. - 2013. - Vol. 137. - P274-287, DOI 10.1016/j.rse.2013.06.019. - Cited References: 75. - This study was made possible by NASA's Terrestrial Ecology program under grants NNH08ZDA001N-TE and NNH06ZDA001N-CARBON. We also acknowledge the NSERC Discovery Grant to Hank Margolis for contributing partial support for the airborne data collection in Canada. We would like to thank three anonymous reviewers who improved the quality and content of this manuscript. We would also like to thank Sergi Im, Mukhtar Naurzbaev, Pasha Oskorbin, and Marsha Dvinskaya of the Sukachev Institute of Forest and Bruce Cook from the NASA Goddard Space Flight Center for help in collecting field measurements in Siberia. . - 14. - ISSN 0034-4257РУБ Environmental Sciences + Remote Sensing + Imaging Science & Photographic Technology

Аннотация: The boreal forest accounts for one-third of global forests, but remains largely inaccessible to ground-based measurements and monitoring. It contains large quantities of carbon in its vegetation and soils, and research suggests that it will be subject to increasingly severe climate-driven disturbance. We employ a suite of ground-, airborne- and space-based measurement techniques to derive the first satellite LiDAR-based estimates of aboveground carbon for the entire circumboreal forest biome. Incorporating these inventory techniques with uncertainty analysis, we estimate total aboveground carbon of 38 +/- 3.1 Pg. This boreal forest carbon is mostly concentrated from 50 to 55 degrees N in eastern Canada and from 55 to 60 degrees N in eastern Eurasia. Both of these regions are expected to warm >3 degrees C by 2100, and monitoring the effects of warming on these stocks is important to understanding its future carbon balance. Our maps establish a baseline for future quantification of circumboreal carbon and the described technique should provide a robust method for future monitoring of the spatial and temporal changes of the aboveground carbon content. Published by Elsevier Inc.

Полный текст,
WOS,
Scopus

Держатели документа:
[Neigh, Christopher S. R.
Nelson, Ross F.
Ranson, K. Jon
Montesano, Paul M.
Sun, Guoqing] NASA, Biospher Sci Lab, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
[Margolis, Hank A.] Univ Laval, Ctr Etud Foret, Quebec City, PQ G1V 0A6, Canada
[Montesano, Paul M.] Sigma Space Corp, Lanham, MD 20705 USA
[Montesano, Paul M.
Sun, Guoqing] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
[Kharuk, Viacheslav] Russian Acad Sci, Sukachev Inst Forest, Krasnoyarsk 660036, Russia
[Naesset, Erik] Norwegian Univ Life Sci, Dept Ecol & Nat Resource Management, NO-1432 As, Norway
[Wulder, Michael A.] Nat Resources Canada, Pacific Forestry Ctr, Canadian Forest Serv, Victoria, BC V82Z 1M5, Canada
[Andersen, Hans-Erik] Univ Washington, US Forest Serv, Pacific NW Res Stn, Seattle, WA 98195 USA

Доп.точки доступа:
Neigh, CSR; Nelson, R.F.; Ranson, K.J.; Margolis, H.A.; Montesano, P.M.; Sun, G.Q.; Kharuk, V...; Naesset, E...; Wulder, M.A.; Andersen, H.E.; NASA [NNH08ZDA001N-TE, NNH06ZDA001N-CARBON]; NSERC Discovery Grant

[Text] / K. R. Briffa [et al.] // Holocene. - 2002. - Vol. 12, Is. 6. - P737-757, DOI 10.1191/0959683602hl587rp. - Cited References: 26 . - 21. - ISSN 0959-6836РУБ Geography, Physical + Geosciences, Multidisciplinary

Аннотация: A detailed description is presented of the statistical patterns of climate forcing of tree growth (annual maximum latewood density and ring-width time series), across a network of 387 specially selected conifer sites that circle the extra-tropical Northern Hemisphere, The influence of summer temperature dominates growth. A mean April-September response is optimum for describing the major forcing signal over the whole densitometric network, though a shorter June-July season is more relevant in central and eastern Siberia. The ring-width chronologies also have a shorter optimum (June-August) seasonal signal, but this is much weaker than the density signal. The association between tree-ring density and precipitation variability (as measured by partial correlations to account for the correlation between temperature and precipitation) is considerably weaker than with temperature. The ring-width response to precipitation is dominated by 'noise' and local site influences, though a negative response to winter precipitation in northern Siberia is consistent A with the suggestion of an influence of delayed snowmelt. Average correlations with winter temperatures are small for all regions and correlations with annual temperatures are positive only because of the strong link with summer temperatures. Reconstructions of summer temperature based on composite regional density chronologies for nine areas are presented. Five regions (northwestern North America, NWNA; eastern and central Canada, ECCA; northern Europe. NEUR; northern Siberia, NSIB; and eastern Siberia, ESIB) constitute an arbitrary 'northern' division of the network, while the four other regions (western North America, WNA; southern Europe, SEUR; central Asia, CAS and the Tibetan Plateau, TIBP) make up the 'southern' part, We also present two larger composite regional reconstructions comprising the data from the five higher-latitude (HILAT) and four lower-latitude (LOLAT) areas respectively: and a single series made up of data from all regions (ALL), which is highly correlated with Northern Hemisphere mean summer temperature. We calculate time-dependent uncertainty ranges for each of these reconstructions, though they are not intended to represent long timescales of temperature variability (>100 years) because the technique used to assemble the site chronologies precludes this. Finally, we examine in more detail the reduced sensitivity in the tree-growth data to decadal-timescale summer-temperature trends during the last 50 years, identified in earlier published work.

WOS,
Scopus

Держатели документа:
Univ E Anglia, Climat Res Unit, Norwich NR4 7TJ, Norfolk, England
Swiss Fed Inst Forest Snow & Landscape Res, CH-8903 Birmensdorf, Switzerland
Russian Acad Sci, Ural Div, Inst Plant & Anim Ecol, Ekaterinburg 620219, Russia
Russian Acad Sci, Siberian Div, Inst Forest, Krasnoyarsk 660036, Russia

Доп.точки доступа:
Briffa, K.R.; Osborn, T.J.; Schweingruber, F.H.; Jones, P.D.; Shiyatov, S.G.; Vaganov, E.A.

[Text] / K. R. Briffa [et al.] // J. Geophys. Res.-Atmos. - 2001. - Vol. 106, Is. D3. - P2929-2941, DOI 10.1029/2000JD900617. - Cited References: 25 . - 13. - ISSN 0747-7309РУБ Meteorology & Atmospheric Sciences

Аннотация: We describe new reconstructions of northern extratropical summer temperatures for nine subcontinental-scale regions and a composite series representing quasi "Northern Hemi sphere" temperature change over the last 600 years. These series are based on tree ring density data that have been processed using a novel statistical technique (age band decomposition) designed to preserve greater long-timescale variability than in previous analyses. We provide time-dependent and timescale-dependent uncertainty estimates for all of the reconstructions. The new regional estimates are generally cooler in almost all precalibration periods, compared to estimates obtained using earlier processing methods, particularly during the 17th century. One exception is the reconstruction for northern Siberia, where 15th century summers are now estimated to be warmer than those observed in the 20th century. In producing a new Northern Hemisphere series we demonstrate the sensitivity of the results to the methodology used once the number of regions with data, and the reliability of each regional series, begins to decrease. We compare our new hemisphere series to other published large-regional temperature histories, most of which lie within the lo confidence band of our estimates over most of the last 600 years. The 20th century is clearly shown by all of the palaeoseries composites to be the warmest during this period.

Полный текст,
WOS,
Scopus

Держатели документа:
Univ E Anglia, Climat Res Unit, Norwich NR4 7TJ, Norfolk, England
Swiss Fed Inst Forest Snow & Landscape Res, CH-8903 Birmensdorf, Switzerland
Russian Acad Sci, Inst Plant & Anim Ecol, Ural Branch, Ekaterinburg 620144, Russia
Inst Forest, Krasnoyarsk 660036, Russia

Доп.точки доступа:
Briffa, K.R.; Osborn, T.J.; Schweingruber, F.H.; Harris, I.C.; Jones, P.D.; Shiyatov, S.G.; Vaganov, E.A.

[Text] / M. V. Skomarkova [et al.] // Trees-Struct. Funct. - 2006. - Vol. 20, Is. 5. - P571-586, DOI 10.1007/s00468-006-0072-4. - Cited References: 55 . - 16. - ISSN 0931-1890РУБ Forestry

Аннотация: We investigated the variability of tree-ring width, wood density and C-13/C-12 in beech tree rings (Fagus sylvatica L.), and analyzed the influence of climatic variables and carbohydrate storage on these parameters. Wood cores were taken from dominant beech trees in three stands in Germany and Italy. We used densitometry to obtain density profiles of tree rings and laser-ablation-combustion-GC-IRMS to estimate carbon isotope composition (delta C-13) of wood. The sensitivity of ring width, wood density and delta C-13 to climatic variables differed; with tree-ring width responding to environmental conditions (temperature or precipitation) during the first half of a growing season and maximum density correlated with temperatures in the second part of a growing season (July-September). delta C-13 variations indicate re-allocation and storage processes and effects of drought during the main growing season. About 20% of inter-annual variation of tree-ring width was explained by the tree-ring width of the previous year. This was confirmed by delta C-13 of wood which showed a contribution of stored carbohydrates to growth in spring and a storage effect that competes with growth in autumn. Only mid-season delta C-13 of wood was related to concurrent assimilation and climate. The comparison of seasonal changes in tree-ring maximum wood density and isotope composition revealed that an increasing seasonal water deficit changes the relationship between density and C-13 composition from a negative relation in years with optimal moisture to a positive relationship in years with strong water deficit. The climate signal, however, is over-ridden by effects of stand density and crown structure (e.g., by forest management). There was an unexpected high variability in mid season delta C-13 values of wood between individual trees (-31 to -24 parts per thousand) which was attributed to competition between dominant trees as indicated by crown area, and microclimatological variations within the canopy. Maximum wood density showed less variation (930-990 g cm(-3) stop). The relationship between seasonal changes in tree-ring structure and C-13 composition can be used to study carbon storage and re-allocation, which is important for improving models of tree-ring growth and carbon isotope fractionation. About 20-30% of the tree-ring is affected by storage processes. The effects of storage on tree-ring width and the effects of forest structure put an additional uncertainty on using tree rings of broad leaved trees for climate reconstruction.

Полный текст,
WOS,
Scopus

Держатели документа:
Max Planck Inst Biogeochem, Jena, Germany
Russian Acad Sci, Inst Forest, SB, Krasnoyarsk 660036, Russia
Univ Calif Berkeley, ESPM Dept, Berkeley, CA 94720 USA

Доп.точки доступа:
Skomarkova, M.V.; Vaganov, E.A.; Mund, M...; Knohl, A...; Linke, P...; Boerner, A...; Schulze, E.D.

/ R. H.A. Baker [et al.] // EPPO Bulletin. - 2009. - Vol. 39, Is. 1. - P87-93, DOI 10.1111/j.1365-2338.2009.02246.x . - ISSN 0250-8052
Аннотация: PRATIQUE is an EC-funded 7th Framework research project designed to address the major challenges for pest risk analysis (PRA) in Europe. It has three principal objectives: (a) to assemble the datasets required to construct PRAs valid for the whole of the EU, (b) to conduct multi-disciplinary research that enhances the techniques used in PRA and (c) to provide a decision support scheme for PRA that is efficient and user-friendly. The research will be undertaken by scientists from 13 institutes in the EU and one each from Australia and New Zealand with subcontractors from institutes in China and Russia. They will produce a structured inventory of PRA datasets for the EU and undertake targeted research to improve existing procedures and develop new methods for (a) the assessment of economic, environmental and social impacts, (b) summarising risk while taking account of uncertainty, (c) mapping endangered areas (d) pathway risk analysis and systems approaches and (e) guiding actions during emergencies caused by outbreaks of harmful organisms. The results will be tested and provided as protocols, decision support systems and computer programs with examples of best practice linked to a computerised European and Mediterranean Plant Protection Organization (EPPO) PRA scheme. В© 2009 OEPP/EPPO.

Scopus

Держатели документа:
Central Science Laboratory, Sand Hutton, York YO30 7BH, United Kingdom
Department of Environmental Agronomy, University of Padova, 16a Via Universita, Legnaro PD, 35020, Italy
Landbouw-Economisch Instituut (LEI) B.V., 19 Burgemeester Patijnlaan, The Hague, 2585 BE, Netherlands
CABI Europe-Switzerland, 1 Rue des Grillons, Delemont, 2800, Switzerland
Centre for Environmental Policy, Imperial College London, Silwood Park, Ascot SL5 7PY, United Kingdom
European and Mediterranean Plant Protection Organization, 1 rue le Notre, Paris, 75016, France
Julius Kuhn-Institut (JKI), Bundesforschungsinstitut fur Kulturpflanzen, Messeweg 11/12, Braunschweig, 38104, Germany
University of Fribourg, 6 Chemin de Musee, Fribourgm 1700, Switzerland
Cooperative Research Centre for National Plant Biosecurity, CSIRO Entomology, 120 Meiers Road, Indooroopilly, 4068, Australia
Bio-Protection Research Centre, Lincoln University, PO Box 84, Lincoln, Canterbury, New Zealand
Plant Protection Institute, 35 Panayot Volov, Kostinbrod, 2230, Bulgaria
Wageningen University, 1 Hollandseweg, Wageningen, 6706 KN, Netherlands
Centre de Cooperation Internationale en Recherche Agronomique Pour le Developpement, UMR PVBMT, Pole de Protection des Plantes, 7 chemin de I'IRAT, Saint Pierre, Reunion, 97410, France
Institute of Botany, Academy of Sciences of the Czech Republic, Zamek 1, Prhonice, CZ 25243, Czech Republic
Faculty of Science, Department of Ecology, Charles University, Prague, Czech Republic
Institut National de la Recherche Agronomique, UR633, Zoologie Forestierem Ardon, Avenue de la Pomme de Pin, Ardon, Olivet, 45166, France
Sukachev Institute of Forest, Siberian Branch, Russian Academy of Science, Krasnoyarsk, Russian Federation
State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China

Доп.точки доступа:
Baker, R.H.A.; Battisti, A.; Bremmer, J.; Kenis, M.; Mumford, J.; Petter, F.; Schrader, G.; Bacher, S.; De Barro, P.; Hulme, P.E.; Karadjova, O.; Lansink, A.O.; Pruvost, O.; Pyek, P.; Roques, A.; Baranchikov, Y.; Sun, J.-H.

/ K. J. Ranson [et al.] // International Geoscience and Remote Sensing Symposium (IGARSS). - 2007. - 2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007 (23 June 2007 through 28 June 2007, Barcelona) Conference code: 71398. - Ст. 4423302. - P2306-2309, DOI 10.1109/IGARSS.2007.4423302 . -
Аннотация: Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. The biggest deficiency of the existing ground based forest inventories is the uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse, lacking, and often decades old. Remote sensing methods can overcome these problems. In this study, we used the moderate resolution imaging spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) and produced a map of timber volume for a 10В°?12В° area in Central Siberia. Using these methods, the mean timber volume for the forested area in the total study area was 203 m3/ ha. The new remote sensing methods used in this study provide a truly independent estimate of forest structure, which is not dependent on traditional ground forest inventory methods. В© 2007 IEEE.

Scopus

Держатели документа:
NASA GSFC, Code 614.4, Greenbelt, MD 20771, United States
Department of Geography, University of Maryland, College Park, MD 20742, United States
Sukachev Institute of Forest, Krasnoyarsk, Russian Federation
Science Systems and Applications Inc., Lanham, MD 20706, United States

Доп.точки доступа:
Ranson, K.J.; Nelson, R.; Kimes, D.; Sun, G.; Kharuk, V.; Montesano, P.

/ E. P.M. Grist [et al.] // Environ. Sci. Technol. - 2006. - Vol. 40, Is. 1. - P395-401, DOI 10.1021/es050871e . - ISSN 0013-936X
Аннотация: Species sensitivity distributions (SSDs) are increasingly used to analyze toxicity data but have been criticized for a lack of consistency in data inputs, lack of relevance to the real environment, and a lack of transparency in implementation. This paper shows how the Bayesian approach addresses concerns arising from frequentist SSD estimation. Bayesian methodologies are used to estimate SSDs and compare results obtained with time-dependent (LC50) and time-independent (predicted no observed effect concentration) endpoints for the insecticide chlorpyrifos. Uncertainty in the estimation of each SSD is obtained either in the form of a pointwise percentile confidence interval computed by bootstrap regression or an associated credible interval. We demonstrate that uncertainty in SSD estimation can be reduced by applying a Bayesian approach that incorporates expert knowledge and that use of Bayesian methodology permits estimation of an SSD that is more robust to variations in data. The results suggest that even with sparse data sets theoretical criticisms of the SSD approach can be overcome. В© 2006 American Chemical Society.

Scopus

Держатели документа:
CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tasmania 7001, Australia
Department of Probability and Statistics, University of Sheffield, Hicks Building, Sheffield S3 7RH, United Kingdom
Watts and Crane Associates, Faringdon, Oxfordshire SN7 7AG, United Kingdom
WRc, Henley Road, Marlow, Buckinghamshire SL7 2HD, United Kingdom
Environment Agency, Wallingford, Oxfordshire, OX10 8BD, United Kingdom

Доп.точки доступа:
Grist, E.P.M.; O'Hagan, A.; Crane, M.; Sorokin, N.; Sims, I.; Whitehouse, P.

/ L. Mukhortova [et al.] // Agric. For. Meterol. - 2015. - Vol. 200. - P97-108, DOI 10.1016/j.agrformet.2014.09.017 . - ISSN 0168-1923
Аннотация: The flux of CO2 from the soil to the atmosphere-soil respiration (RS), is one of the least known components of the terrestrial carbon cycle. RS depends on many factors and varies substantially in time and space. High uncertainty of RS flux valuation leads to a wide range of reported carbon budget estimates for Russian forests. We developed a modeling system for assessing soil carbon stock and heterotrophic soil respiration based on a possible maximum of relevant input indicators. The most comprehensive databases of RS in situ measurements focused on Northern Eurasia (780 records for the region) has been used. A statistical model for assessing RS of Russian forests and its separation in autotrophic and heterotrophic parts were elaborated based on in situ measurements, climate parameters, soil and land cover datasets. The spatial resolution of the model is 1km2. Russian forest soil accumulated 144.5PgC (or 17.6kgCm-2) in 1m depth, including 8.3PgC (or 1.0kgCm-2) in the labile topsoil organic layer. The total heterotrophic soil respiration (RH) flux for the Russian forest is estimated at 1.7PgCyr-1 (206gCm-2yr-1) that comprises 65% of Net Primary Production (NPP) and together with NPP is one of two major components of the net ecosystem carbon balance comprising on average 546TgCyr-1 (66gCm-2yr-1) for 2007-2009. Interannual variability or RH in 1996-2005 was estimated at 4.1% for forests of the whole country and typically from 5 to 11% for large individual regions with an average linear trend +0.2% per year. The uncertainty of annual average of RH was estimated at 8% (confidential interval 0.9).

Scopus,
Полный текст,
WOS

Держатели документа:
V.N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Academgorodok 50(28)Krasnoyarsk, Russian Federation
International Institute for Applied Systems AnalysisLaxenburg, Austria
Moscow State Forest UniversityMoscow Reg., Mytischi, Russian Federation

Доп.точки доступа:
Mukhortova, L.; Schepaschenko, D.; Shvidenko, A.; McCallum, I.; Kraxner, F.

/ P. M. Montesano [et al.] // Remote Sens. Environ. - 2014. - Vol. 154. - P398-407, DOI 10.1016/j.rse.2014.01.027 . - ISSN 0034-4257
Аннотация: In this study, we examined the uncertainty of aboveground live biomass (AGB) estimates based on light detection and ranging (LiDAR) and synthetic aperture radar (SAR) measurements distributed across a low-biomass vegetation structure gradient from forest to non-forest in boreal-like ecosystems. The conifer-dominant structure gradient was compiled from ground data amassed from multiple field expeditions in central Maine (USA), Aurskog (Norway), and across central Siberia (Russia). Single variable empirical models were built to model AGB from remote sensing metrics. Using these models, we calculated a root mean square error (RMSE) and a 95% confidence interval (CI) of the RMSE from the difference between the remote sensing AGB predictions and the ground reference AGB estimates within AGB intervals across a 0-100Mgha-1 boreal forest structure gradient. The results show that the error in AGB predictions (RMSE) and the error uncertainty (the CI) from LiDAR and SAR change across a forest gradient. The errors of airborne LiDAR and SAR metrics and spaceborne LiDAR platforms show a general trend of reduced relative errors as AGB magnitudes increase, particularly from 0 to 60Mgha-1. Empirical models relating spaceborne metrics to AGB and estimates of spaceborne LiDAR error uncertainty demonstrate the difficulty of characterizing differences in AGB at the site-level with current spaceborne sensors, particularly below 80Mgha-1 with less than 50-100% error.

Scopus,
Полный текст,
WOS

Держатели документа:
University of Maryland, Department of Geographical SciencesCollege Park, MD, United States
Sigma Space Corp.Lanham, MD, United States
Code 618,Biospheric Sciences Branch, NASA/Goddard Space Flight CenterGreenbelt, MD, United States
Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003As, Norway
Sukachev Institute of Forest, Siberian Branch, Russian Academy of SciencesAkademgorodok, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Montesano, P.M.; Nelson, R.F.; Dubayah, R.O.; Sun, G.; Cook, B.D.; Ranson, K.J.R.; N?sset, E.; Kharuk, V.

[Text] / P. M. Montesano [et al.] // Remote Sens. Environ. - 2015. - Vol. 158. - P95-109, DOI 10.1016/j.rse.2014.10.029. - Cited References:90. - This work was supported by the NASA Terrestrial Ecology Program. Weacknowledge the expertise of Sergey Im, Pasha Oskorbin and MukhtarNaurzbaev that was critical to the success of various field expeditionsin remote areas of northern Siberia. We also acknowledge the importanceof the constructive criticism provided by the anonymous reviewers whohelped improve this manuscript. . - ISSN 0034-4257. - ISSN 1879-0704РУБ Environmental Sciences + Remote Sensing + Imaging Science & Photographic

Аннотация: The Forest Light (FLIGHT) radiative transfer model was used to examine the uncertainty of vegetation structure measurements from NASA's planned ICESat-2 photon counting light detection and ranging (LiDAR) instrument across a synthetic Larix forest gradient in the taiga-tundra ecotone. The simulations demonstrate how measurements from the planned spaceborne mission, which differ from those of previous LiDAR systems, may perform across a boreal forest to non-forest structure gradient in globally important ecological region of northern Siberia. We used a modified version of FLIGHT to simulate the acquisition parameters of ICESat-2. Modeled returns were analyzed from collections of sequential footprints along LiDAR tracks (link-scales) of lengths ranging from 20 m-90 m. These link-scales traversed synthetic forest stands that were initialized with parameters drawn from field surveys in Siberian Larix forests. LiDAR returns from vegetation were compiled for 100 simulated LiDAR collections for each 10 Mg . ha(-1) interval in the 0-100 Mg . ha-1 above-ground biomass density (AGB) forest gradient. Canopy height metrics were computed and AGB was inferred from empirical models. The root mean square error (RMSE) and RMSE uncertainty associated with the distribution of inferred AGB within each AGB interval across the gradient was examined.Simulation results of the bright daylight and low vegetation reflectivity conditions for collecting photon counting LiDAR with no topographic relief show that 1-2 photons are returned for 79%-88% of LiDAR shots. Signal photons account for similar to 67% of all LiDAR returns, while similar to 50% of shots result in 1 signal photon returned. The proportion of these signal photon returns do not differ significantly (p > 0.05) for AGB intervals >20 Mg . ha(-1). The 50 m link-scale approximates the finest horizontal resolution (length) at which photon counting LiDAR collection provides strong model fits and minimizes forest structure uncertainty in the synthetic Larix stands. At this link-scale AGB >20 Mg . ha(-1) has AGB error from 20-50% at the 95% confidence level. These results suggest that the theoretical sensitivity of ICESat-2 photon counting LiDAR measurements alone lack the ability to consistently discern differences in inferred AGB at 10 Mg . ha-1 intervals in sparse forests characteristic of the taiga-tundra ecotone. (C) 2014 Elsevier Inc. All rights reserved.

WOS,
Полный текст

Держатели документа:
Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA.
Sigma Space Corp, Lanham, MD 20706 USA.
NASA, Goddard Space Flight Ctr, Biospher Sci Branch, Greenbelt, MD 20771 USA.
Swansea Univ, Dept Geog, Swansea SA2 8PP, W Glam, Wales.
No Res Stn, Roslin EH26 9SY, Midlothian, Scotland.
Russian Acad Sci, Sukachev Inst Forest, Siberian Branch, Krasnoyarsk 660036, Russia.
ИЛ СО РАН

Доп.точки доступа:
Montesano, P. M.; Rosette, J.; Sun, G.; North, P.; Nelson, R.F.; Dubayah, R.O.; Ranson, K.J.; Kharuk, V.; NASA Terrestrial Ecology Program

[Text] / Y. L. Liu [et al.] // J. Geophys. Res.-Atmos. - 2015. - Vol. 120, Is. 7. - P2647-2660, DOI 10.1002/2014JD022531. - Cited References:61. - This research is supported by the NASA Land Use and Land Cover Change program (NASA-NNX09AI26G, NN-H-04-Z-YS-005-N, and NNX09AM55G); the Department of Energy (DE-FG02-08ER64599); the National Science Foundation (NSF-1028291, NSF-0919331, and AGS 0847472); and the NSF Carbon and Water in the Earth Program (NSF-0630319). D.G.M. acknowledges financial support from The Netherlands Organisation for Scientific Research (NWO) Veni grant 863.14.004. We acknowledge the Global Runoff Data Centre for the provision of the gauge station data. Runoff data in Peterson et al. [2002] were obtained from the R-ArcticNet database. A special acknowledgment is made to Brigitte Mueller and Martin Hirschi for the provision of the LandFlux-EVAL data set. Eddy covariance measurements were obtained from http://www.asianflux.com and http://gaia.agraria.unitus.it/, and meteorological station measurements were taken from ECA&D and CMA. We also acknowledge the different institutes developing and distributing the forcing climate data: University of East Anglia, ECMWF, NASA, NCEP/NCAR, and Princeton University. For model input files, source codes, and results, contact Q.Z. . - ISSN 2169-897X. - ISSN 2169-8996РУБ Meteorology & Atmospheric Sciences

Аннотация: The ecosystems in Northern Eurasia (NE) play an important role in the global water cycle and the climate system. While evapotranspiration (ET) is a critical variable to understand this role, ET over this region remains largely unstudied. Using an improved version of the Terrestrial Ecosystem Model with five widely used forcing data sets, we examine the impact that uncertainties in climate forcing data have on the magnitude, variability, and dominant climatic drivers of ET for the period 1979-2008. Estimates of regional average ET vary in the range of 241.4-335.7mmyr(-1) depending on the choice of forcing data. This range corresponds to as much as 32% of the mean ET. Meanwhile, the spatial patterns of long-term average ET across NE are generally consistent for all forcing data sets. Our ET estimates in NE are largely affected by uncertainties in precipitation (P), air temperature (T), incoming shortwave radiation (R), and vapor pressure deficit (VPD). During the growing season, the correlations between ET and each forcing variable indicate that T is the dominant factor in the north and P in the south. Unsurprisingly, the uncertainties in climate forcing data propagate as well to estimates of the volume of water available for runoff (here defined as P-ET). While the Climate Research Unit data set is overall the best choice of forcing data in NE according to our assessment, the quality of these forcing data sets remains a major challenge to accurately quantify the regional water balance in NE. Key Points

WOS

Держатели документа:
Purdue Univ, Dept Earth Atmospher & Planetary Sci, W Lafayette, IN 47907 USA.
Purdue Univ, Dept Agron, W Lafayette, IN 47907 USA.
Vrije Univ Amsterdam, Dept Earth Sci, Amsterdam, Netherlands.
Univ Ghent, Lab Hydrol & Water Management, B-9000 Ghent, Belgium.
China Agr Univ, Coll Resources & Environm Sci, Beijing 100094, Peoples R China.
Marine Biol Lab, Ctr Ecosyst, Woods Hole, MA 02543 USA.
Univ Calif Berkeley, Lawrence Berkeley Natl Lab, Div Earth Sci, Climate Sci Dept, Berkeley, CA 94720 USA.
Michigan State Univ, CGCEO Geog, E Lansing, MI 48824 USA.
Russian Acad Sci, VN Sukachev Inst Forest, Siberian Branch, Krasnoyarsk, Russia.
Russian Acad Sci, Inst Forest Sci, Lab Peatland Forestry & Ameliorat, Uspenskoye, Russia.

Доп.точки доступа:
Liu, Yaling; Zhuang, Qianlai; Miralles, Diego; Pan, Zhihua; Kicklighter, David; Zhu, Qing; He, Yujie; Chen, Jiquan; Tchebakova, Nadja; Sirin, Andrey; Niyogi, Dev; Melillo, Jerry; NASA [NASA-NNX09AI26G, NN-H-04-Z-YS-005-N, NNX09AM55G]; Department of Energy [DE-FG02-08ER64599]; National Science Foundation [NSF-1028291, NSF-0919331, AGS 0847472]; NSF [NSF-0630319]; Netherlands Organisation for Scientific Research (NWO) [863.14.004]

/ D. Schepaschenko [et al.] // Forests. - 2018. - Vol. 9, Is. 6, DOI 10.3390/f9060312 . - ISSN 1999-4907
Аннотация: Biomass structure is an important feature of terrestrial vegetation. The parameters of forest biomass structure are important for forest monitoring, biomass modelling and the optimal utilization and management of forests. In this paper, we used the most comprehensive database of sample plots available to build a set of multi-dimensional regression models that describe the proportion of different live biomass fractions (i.e., the stem, branches, foliage, roots) of forest stands as a function of average stand age, density (relative stocking) and site quality for forests of the major tree species of northern Eurasia. Bootstrapping was used to determine the accuracy of the estimates and also provides the associated uncertainties in these estimates. The species-specific mean percentage errors were then calculated between the sample plot data and the model estimates, resulting in overall relative errors in the regression model of -0.6%, -1.0% and 11.6% for biomass conversion and expansion factor (BCEF), biomass expansion factor (BEF), and root-to-shoot ratio respectively. The equations were then applied to data obtained from the Russian State Forest Register (SFR) and a map of forest cover to produce spatially distributed estimators of biomass conversion and expansion factors and root-to-shoot ratios for Russian forests. The equations and the resulting maps can be used to convert growing stock volume to the components of both above-ground and below-ground live biomass. The new live biomass conversion factors can be used in different applications, in particular to substitute those that are currently used by Russia in national reporting to the UNFCCC (United Nations Framework Convention on Climate Change) and the FAO FRA (Food and Agriculture Organization's Forest Resource Assessment), among others. © 2018 by the authors.

Scopus,
Смотреть статью,
WOS

Держатели документа:
International Institute for Applied Systems Analysis, Laxenburg, Austria
Forestry Faculty, Bauman Moscow State Technical University, Mytischi, Russian Federation
School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
Institute of Forest Siberian Branch Russian Academy of Sciences, Akademgorodok, Krasnoyarsk, Russian Federation
Education and Research Institute of Forestry and Park Gardening, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine
Institute of Numerical Mathematics of Russian Academy of Sciences, Ul. Gubkina 8, Moscow, Russian Federation
The Earth Science Museum, M.V. Lomonosov Moscow State University, 1 Leninskiye Gory, GSP-1, Moscow, Russian Federation

Доп.точки доступа:
Schepaschenko, D.; Moltchanova, E.; Shvidenko, A.; Blyshchyk, V.; Dmitriev, E.; Martynenko, O.; See, L.; Kraxner, F.

/ D. Schepaschenko [et al.] // Sci Data. - 2019. - Vol. 6, Is. 1. - P198, DOI 10.1038/s41597-019-0196-1 . - ISSN 2052-4463
Аннотация: 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.

Scopus,
Смотреть статью,
WOS

Держатели документа:
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Laxenburg, A-2361, Austria
Forestry faculty, Bauman Moscow State Technical University, Mytischi141005, Russian Federation
Laboratoire Evolution et Diversite Biologique CNRS/Universite Paul Sabatier, Toulouse, France
School of Geography, University of Leeds, Leeds, LS2 9JT, United Kingdom
University College London, 30 Guilford Street, London, WC1N 1EH, United Kingdom
Forest Global Earth Observatory, Smithsonian Tropical Research Institute, P.O. Box 37012WA 20013, United States
AMAP, IRD, CNRS, CIRAD, INRA, University Montpellier, Montpellier, France
CIRAD, Forets et Societes, Campus International de Baillarguet, Montpellier, F-34398, France
Forets et Societes, Univ Montpellier, CIRAD, Montpellier, F-34398, France
European Space Agency, ESTEC, Noordwijk, Netherlands
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Laxenburg, A-2361, Austria
Spatial Focus GmbHVienna, Austria
Department Foresterie et Environnement (DFR FOREN), Institut National Polytechnique Felix Houphouet-Boigny, BP 2661Yamoussoukro, Cote d'Ivoire
Mensuration Unit, Forestry Commission of Ghana, Kumasi, Ghana
Center of Forest Ecology and Productivity of the Russian Academy of SciencesMoscow 117997, Russian Federation
Smithsonian Conservation Biology Institute, 1100 Jefferson Dr SW, DCWA, United States
Centre for International Forestry Research, CIFOR, Jalan CIFOR ,Situ Gede, Bogor, 16115, Indonesia
Universidad Autonoma Gabriel Rene MorenoSanta Cruz, Bolivia
Department of Geographical Sciences, University of Maryland, MD, 2181 Lefrak Hall ,College Park20742, United States
Joint Remote Sensing Research Program, School of Earth and Environmental Sciences, University of Queensland, Chamberlain Building (35), Campbell Road ,St Lucia Campus, Brisbane, 4072, Australia
Museo de Historia Natural Noel Kempff Mercado, Universidad Autonoma Gabriel Rene Moreno Av. Irala 565 - casillaSanta Cruz 2489, Bolivia
Instituto Boliviano de Investigacion Forestal, Av. 6 de agosto # 28, Km 14 doble via La GuardiaCasillaSanta Cruz 6204, Bolivia
Embrapa, Rodovia AM 10, km 29AM, Manaus, 69010-970, Brazil
Forest Research Institute, Department of Geomatics, Braci Lesnej 3 ,Sekocin Stary, Raszyn, 05-090, Poland
ONF, ONF-Reserve de Montabo Cayenne Cedex, Cayenne, BP 7002; 97307, French Guiana
Landscapes and Livelihoods Group, 20 Chambers St, Edinburgh, EH1 1JZ, United Kingdom
National University of Life and Environmental Sciences of Ukraine, General Rodimtsev 19Kyiv 3041, Ukraine
Herbier National du Gabon (IPHAMETRA), B.P 1165, Libreville, Gabon
Institute of Biology, Komi Scientific Center, Ural Branch of Russian Academy of Sciences, Syktyvkar, 167982, Russian Federation
School of Biological Sciences, University of Aberdeen, Cruickshank Building, St Machar Drive, Aberdeen, AB24 3UU, United Kingdom
Morton Arboretum, 4100 Illinois Rte. 53, Lisle, 60532, United States
Department of Environment and Geography, University of York, Heslington, York, YO10 5NG, United Kingdom
V.N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, 660036, Russian Federation
Instituto de Investigaciones de la Amazonia Peruana, Av. Abelardo Quinones km 2.5Apartado Postal 784, Iquitos, Peru
CIRAD, UMR EcoFoG, Campus Agronomique - BP 701, Kourou, 97387, French Guiana
Embrapa, Rodovia Juscelino Kubitscheck, no 2.600, 68903-419, Km 5Caixa Postal 10, Macapa, Brazil
Embrapa, BR 364, Caixa postal 321, Rio Branco, 69.900-970, Brazil
SI Entomology, Smithsonian Institution, DC, PO Box 37012 ,MRC 187WA, United States
Department Forest Ecology and Management, Swedish University of Agricultural Sciences, SLU, Umea, SE 901 83, Sweden
Geography, College of Life and Environmental Sciences, University of Exeter, Laver Building, North Park Road, Exeter, EX4 4QE, United Kingdom
Forestry Research Institute of Ghana, KNUST, UP Box 63, Kumasi, Ghana
Field Musium, 1400S Lake Shore Dr, Chicago, 60605, United States
Universidad Politecnica de Madrid ,Calle Ramiro de MaeztuMadrid 28040, Spain
Institut Centrafricain de Recherche Agronomique, ICRA, BP 122Bangui, Central African Republic
School of Biology, University of Leeds, Leeds, LS2 9JT, United Kingdom
Forestry and Environment Research Development and Innovation Agency, Jalan Gunung Batu No 5, Bogor, 16610, Indonesia
Instituto Nacional de Pesquisas da Amazonia - Coordenacao de Pesquisas em Silvicultura Tropical, Manaus, 69060-001, Brazil
Gent-Woodlab, Laboratory of Wood Technology, Department of Environment, Ghent University, Ghent, 9000, Belgium
Department of Ecology and Evolutionary Biology, University of California, 621 Charles E. Young Dr. South, Los Angeles, CA, 90095-1606, USA
Embrapa Amazonia Oriental, Travessa Doutor Eneas Pinheiro, Belem, 66095-903, Brazil
World Wildlife Fund, Calle Diego de Mendoza 299, Santa Cruz de la Sierra, Bolivia
boulevard Francois Mitterrand01BP 3770Abidjan, Cote d'Ivoire
Global Change Research Institute CAS, Belidla 986/4a, Brno, 603 00, Czech Republic
Department of Geography and Earth Sciences, Aberystwyth University, AberystwythSY23 3DB, United Kingdom
School of Geography and the Environment, University of Oxford, Oxford, OX1 3QY, United Kingdom
Laboratorio de Ecologia Vegetal, Universidade do Estado de Mato Grosso, UNEMAT, Campus de Nova Xavantina, Nova Xavantina, Mato Grosso 78.690-000, Brazil
Jardin Botanico de Missouri; Universidad Nacional de San Antonio Abad del Cusco, Oxapampa, Peru
Russian Institute of Continuous Education in Forestry, Pushkino, 141200, Russian Federation
Institute for Evolutionary Ecology of the National Academy of Sciences of UkraineKyiv 03143, Ukraine
University of Oregon, 1585 E 13th AveOR, Eugene, 97403, United States
Forest Management in Bolivia, Bolivia
FRIM Forest Reserach Institute of Malaysia, 52109 Kepong, Selangor, Kuala Lumpur, Malaysia
Hiroshima University, 1-7-1 Kagamiyama ,Higashi-HiroshimaHiroshima 739-8521, Japan
Forestry faculty, Bauman Moscow State Technical University, Mytischi141005, Russian Federation
Center for Agricultural research in SurinameParamaribo 1914, Suriname
Nicholas School of the Environment, Duke University, P.O. Box 90328, Durham, 27708, United States
IIC, Iwokrama International Centre for Rain Forest Conservation and Development, 77 High Street, Georgetown, Guyana
Cibodas Botanic Gardens - Indonesian Institute of Sciences (LIPI)43253, Indonesia
Smithsonian Tropical Research Institute, Balboa, Ancon, Panama 3092, Panama
Museu Universitario, Universidade Federal do Acre, BR 364, Km 04 - Distrito Industrial, Rio Branco, 69915-559, Brazil
Guyana Forestry Commission, 1 Water Street, Guyana
Plant Systematic and Ecology Laboratory, University of Yaounde I, P.O. Box 047, Yaounde, Cameroon
Bioversity international, P.O. Box 2008, Yaounde
Naturalis Biodiversity Center, Leiden, Netherlands
School of Natural Sciences, Bangor University, Thoday Building. Deiniol Rd, Bangor, LL57 2UW, United Kingdom
Siberian Federal University, 79, Krasnoyarsk, 660041, Russian Federation
Reshetnev Siberian state university of science and technology, pr. Mira 82, Krasnoyarsk, 660049, Russian Federation
Department of Forest Sciences, Luiz de Queiroz College of Agriculture, University of Sao Paolo, PO Box 9 ,Av. Padua Dias ,11, Piracicaba, Sao Paulo 13418-900, Brazil
State Nature Reserve Denezhkin Kamen, Sverdlovsk reg, Lenina, Russian Federation
International Center for Tropical Botany, Department of Biological Sciences, Florida International University, FL, 11200 S.W. 8th Street, Miami, 33199, United States
Universidad Autonoma del Beni, Riberalta, Bolivia
Department of Microbiology and Ecosystem Science, Division of Terrestrial Ecosystem research, University of Vienna, Althanstrasse 14Vienna A-1090, Austria
New Zealand Forest Research Institute (Scion) Te Papa Tipu Innovation Park ,49 Sala Street, Rotorua, 3046, New Zealand
Unaffiliated (retired), Bad Aussee, 8990, Austria
W.R.T College of Agriculture and Forestry, University of Liberia, Capitol Hill, Monrovia, 9020, Liberia
FRIM Forest Research Institute of Malaysia, 52109 Kepong, Selangor, Kuala Lumpur, Malaysia

Доп.точки доступа:
Schepaschenko, D.; Chave, J.; Phillips, O. L.; Lewis, S. L.; Davies, S. J.; Rejou-Mechain, M.; Sist, P.; Scipal, K.; Perger, C.; Herault, B.; Labriere, 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.; Balazy, R.; Bedeau, C.; Berry, N.; Bilous, A. M.; Bilous, S. Y.; Bissiengou, P.; Blanc, L.; Bobkova, K. S.; Braslavskaya, T.; Brienen, R.; Burslem, D. F.R.P.; 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-Bassebe, 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.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.; Junior, B. H.M.; Martinez, R. V.; Martynenko, O. V.; Matsala, M.; Matyashuk, R. K.; Mazzei, L.; Memiaghe, H.; Mendoza, C.; Mendoza, A. M.; Moroziuk, O. V.; Mukhortova, L.; Musa, S.; Nazimova, D. I.; Okuda, T.; Oliveira, L. C.; Ontikov, P. V.; Osipov, A. F.; 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.; Sonke, B.; Souza, C.; Sterenczak, K.; Stonozhenko, L.; Sullivan, M. J.P.; 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. A.P.; Woell, H.; Woods, J. T.; Wortel, V.; Yamada, T.; Nur Hajar, Z. S.; Zo-Bi, I. C.

/ S. F. Gouveia, J. G. Rubalcaba, V. Soukhovolsky [et al.] // Ecol. Model. - 2020. - Vol. 424. - Ст. 109032, DOI 10.1016/j.ecolmodel.2020.109032. - Cited References:58. - We thank the kind audience of the Symposium `Applications of theoretical physics in ecology' during the 22nd Biennial Conference of The International Society for Ecological Modelling (ISEM), at Salzburg, Austria, for their feedback to the talks that resulted in this work. This work was supported by an Institute Serrapilheira grant provided to SFG (G-1709-18372) and INCT Ecology, Evolution, and Conservation of Biodiversity -EECBio (CNPq/FAPEG, grant 380733/2017-0). SFG also thanks CNPq (grants 451863/2019-4, 303180/2016-1, and 402469/2016-0) and CAPES/FAPITEC (grants 88881.157451/2017-01 and 88881.157961/2017-01). The work of VS and OT is supported by the Russian Foundation of Basic Research (grant 18-04-00119), and the work of RR by the Spanish Ministry of Economy, Industry, and Competitiveness (grant CGL2016-76747-R) and ERDF Funds. . - ISSN 0304-3800. - ISSN 1872-7026РУБ Ecology

Аннотация: Physics and ecology focus on different domains of nature and have developed under distinct scientific paradigms. Still, both share critical features, such as dealing with systems of irreducible complexity and inherent uncertainty at a fundamental level. Physics has embraced such complexity earlier and has devised robust analytical approaches to describe general principles of its systems, a path that ecosystem ecology has tracked, but organism-based ecology has only started to. Here, we outline approaches from physics - from classical to quantum mechanics - to address ecological questions that deal with emergent patterns of biodiversity, such as species' distribution, niche, and trait variation, which are of particular interest to community ecology, biogeography, and macroecology. These approaches can be further extended, which would provide these fields with a rationale common to other scientific fields within and outside ecology.

WOS

Держатели документа:
Univ Fed Sergipe, Dept Ecol, Sao Cristovao, Sergipe, Brazil.
Univ Montana, Div Biol Sci, Missoula, MT 59812 USA.
VN Sukachev Inst Forest SB RAS, Krasnoyarsk, Russia.
Siberian Fed Univ, Krasnoyarsk, Russia.
Univ Evora CIBIO InBIO UE, Res Ctr Biodivers & Genet Resources, Evora, Portugal.
Univ Malaga, Fac Sci, Dept Anim Biol, Biogeog Divers & Conservat Res Team, Malaga, Spain.

Доп.точки доступа:
Gouveia, Sidney F.; Rubalcaba, Juan G.; Soukhovolsky, Vladislav; Tarasova, Olga; Barbosa, A. Marcia; Real, Raimundo; Institute Serrapilheira [G-1709-18372]; INCT Ecology, Evolution, and Conservation of Biodiversity -EECBio (CNPq/FAPEG) [380733/2017-0]; CNPqNational Council for Scientific and Technological Development (CNPq) [451863/2019-4, 303180/2016-1, 402469/2016-0]; CAPES/FAPITEC [88881.157451/2017-01, 88881.157961/2017-01]; Russian Foundation of Basic ResearchRussian Foundation for Basic Research (RFBR) [18-04-00119]; Spanish Ministry of Economy, Industry, and Competitiveness [CGL2016-76747-R]; ERDF Funds