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МИКРОБИОЛОГИЧЕСКАЯ ТРАНСФОРМАЦИЯ УГЛЕРОДА СН4 и СО2 В КРИОГЕННЫХ ПОЧВАХ ТУНДРОВЫХ И ЛЕСНЫХ ЭКОСИСТЕМ СИБИРИ

2017· article· ru· W2737793436 sur OpenAlexaboutno aff
И. Д. Гродницкая, С. Ю. Евграфова, Г. И. Антонов, С. Н. Сырцов, Denis E. Aleksandrov, М. Ю. Трусова, Н. В. Коробан

Notice bibliographique

RevueЖурнал "Лесоведение" · 2017
Typearticle
Langueru
DomaineEarth and Planetary Sciences
ThématiqueClimate change and permafrost
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésComputer science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

RUSSIAN JOURNAL OF FOREST SCIENCE. 2017, No. 5, pp. 111-127 MICROBIAL TRANSFORMATION OF CARBON CH4 AND CO2 IN PERMAFROST-AFFECTED SOILS IN TUNDRA AND FOREST ECOSYSTEMS IN SIBERIA I. D. Grodnitskaya 1 , S. Y. Evgrafova 1 , G. I. Antonov, S. N. Syrtsov 1,2 , D. E. Aleksandrov 1 , M. Y. Trusova 3 , N. V. Koroban 4 1 Forest Institute, Siberian Branch of the Russian Academy of Sciences Academgorodok, 50, bldg. 28, Krasnoyarsk, 660036, Russia E-mail: igrod@ksc.krasn.ru 2 Krasnoyarsk filial of the Information and Methodological Center for Expert Evaluation, Recording and Analysis of Circulation of Medical Products, Roszdravnadzor Kutuzova st., 1, bldg. 1, Krasnoyarsk, 660050, Russia 3 Institute of Biophysics, Siberian Branch of the Russian Academy of Sciences Academgorodok, 50, bldg. 50, Krasnoyarsk, 660036, Russia 4 Roche Diagnostika Rus Ltd. Letnikovskaya, 2, bldg. 2, Moscow, 115114, Russia Received 5 April 2016 We studied structure, dynamics and functional (biogeochemical) activity of microbial complexes of cryogenic soils in larch forests in Central Evenkia and polygonal tundra on Samoilovskii Island, Lena Delta. We found that daily flux of methane from soil surface is 3-5 times less in forest soil than in the center of polygon in tundra. Short-term heating to 18.5-22.5°C of permafrost-affected soil in larch forest caused sweetening of soil solution, shrinkage of eco-trophic groups of microorganisms and microbial biomass, as well as increase in greenhouse gases (CO 2 and CH 4 ) emission to the air. Notably the permafrost-affected soil on sandy deposits in tundra had highest microbial diversity of methanogenic archaea including Methanobacteriaceae , Methanomicrobiaceae , Methanosarcinaceae , Methanosaetaceae families. On the other hand only Methanosarcinacea were found in cryosols of larch forest. Both type I and type II methanotrophs were found in the forest soil, while only type II methanotrophs occurred in tundra soil. Keywords: сryogenic soils, larch forests, frost-crack polygons, tundra, dynamics and activity of microbial complexes, CH 4 and CO 2 emission, bacterial diversity. REFERENCES Amaral J.A., Archambault C., Richards S.R., Knowles R., Denitrification associated with Groups I and II methanotrophs in a gradient enrichment system, FEMS microbiology ecology , 1995, Vol. 18, No. 4, pp. 289-298. Anan'eva N.D., Mikrobiologicheskie aspekty samoochishcheniya i ustoichivosti pochv ( Microbial aspects of self-purification and resilience of soils ), Moscow: Nauka, 2003, 222 p. Anderson J.P.E., Domsch K.H., A physiological method for the quantitative measurement of microbial biomass in soils, Soil biology and biochemistry , 1978, Vol. 10, No. 3, pp. 215-221. Anderson T.-H., Domsch K.H., Application of eco-physiological quotients q CO 2 and q D on microbial biomasses from soils of different cropping histories, Soil biology and biochemistry , 1990, Vol. 22, No. 2, pp. 251-255. Auman A.J., Speake C.C., Lidstrom M.E., nifH sequences and nitrogen fixation in type I and type II methanotrophs, Applied and environmental microbiology , 2001, Vol. 67, No. 9, pp. 4009-4016. Bergh J., Linder S.E., Effects of soil warming during spring on photosynthetic recovery in boreal Norway spruce stands, Global change biology , 1999, Vol. 5, No. 3, pp. 245-253. Bol'shiyanov D.Y., Makarov A.S., Shnaider V., Shtof G., Proiskhozhdenie i razvitie del'ty reki Leny (Genesis and formation of Lena delta), Saint-Petersburg: Izd-vo AANII, 2013, 266 p. Borjesson G., Sundh I., Svensson B., Microbial oxidation of CH 4 at different temperatures in landfill cover soils, FEMS microbiology ecology , 2004, Vol. 48, No. 3, pp. 305-312. Borjesson G., Sundh I., Tunlid A., Frostegard A., Svensson B.H., Microbial oxidation of CH 4 at high partial pressures in an organic landfill cover soil under different moisture regimes, FEMS microbiology ecology , 1998, Vol. 26, No. 3, pp. 207-217. Bugaenko T.N., Vidovoe raznoobrazie listvennichnykh assotsiatsii severnoi taigi Srednei Sibiri i ego poslepozharnaya  transformatsiya. Avtoref. diss. kand. biol. nauk (Post-fire changes in species diversity of larch associations in northern taiga of Central Siberia. Extended abstract of Candidate's biol. sci. thesis), Krasnoyarsk: IL SO RAN, 2002, 22 p. Chernov I.Y., Sinekologicheskii analiz gruppirovok drozhzhei Taimyrskoi tundry (Synecological analyzis of yeast aggregations in tundra of the Taymyr), Ekologiya , 1985, No. 1, pp. 54-60. Dedysh S.N., Methanotrophic bacteria of acid sphagnum peat bogs, Microbiology , 2002, Vol. 71, No. 6, pp. 638-650. Evgrafova S.Y., Grodnitskaya I.D., Krinitsyn Y.O., Syrtsov S.N., Masyagina O.V., Emissiya metana s poverkhnosti pochvy v tundrovykh i lesnykh ekosistemakh Sibiri (Methane emission from soil surface in the tundra and forest ecosystems in Siberia), Vestnik Krasnoyarskogo gosudarstvennogo agrarnogo universiteta , 2010, No. 12, pp. 80-86. Ganzert L., Jurgens G., Munster U., Wagner D., Methanogenic communities in permafrost-affected soils of the Laptev Sea coast, Siberian Arctic, characterized by 16S rRNA gene fingerprints, FEMS microbiology ecology , 2007, Vol. 59, No. 2, pp. 476-488. GOST 11306-83 . GOST 11623-89 . GOST 26570-95 . GOST 26715-85 . GOST 26717-85 . GOST 26718-85 . GOST 27894.1-88 . GOST 27894.3-88 . GOST 27894.4-88 . GOST 30502-97 . Graham D.W., Chaudhary J.A., Hanson R.S., Arnold R.G., Factors affecting competition between type I and type II methanotrophs in two-organism, continuous-flow reactors, Microbial ecology , 1993, Vol. 25, No. 1, pp. 1-17. Grodnitskaya I.D., Karpenko L.V., Knorre A.A., Syrtsov S.N., Microbial activity of peat soils of boggy larch forests and  bogs in the permafrost zone of Central Evenkia, Eurasian soil science , 2013, Vol. 46, No. 1, pp. 51-73. Hoj L., Olsen R.A., Torsvik V.L., Archaeal communities in High Arctic wetlands at Spitsbergen, Norway (78°N) as characterised by 16S rRNA gene fingerprinting, FEMS microbiology ecology , 2005, Vol. 53, No. 1, pp. 89-101. Khaziev F.K., Metody pochvennoi enzimologii (Methods of soil enzymology), Moscow: Nauka, 2005, 251 p. Metje M., Frenzel P., Methanogenesis and methanogenic pathways in a peat from subarctic permafrost, Environmental microbiology , 2007, Vol. 9, No. 4, pp. 954-964. Mishustin E.N., Mikrobnye assotsiatsii pochvennykh tipov (Microbial associations in different soil types), Problemy i metody biologicheskoi diagnostiki i indikatsii pochv (Biological caharacterization and indication of soils: challenges and methods) , Moscow, 22-24 December 1976, Moscow: Nauka, 1976, pp. 19-42. Netrusov A.I., Praktikum po mikrobiologii (Practicum in microbiology), Moscow: Akademiya, 2005, 603 p. Parinkina O.M., Mikroflora tundrovykh pochv. Ekologo-geograficheskie osobennosti i produktivnost' (Microflora of soils in tundra. Environmental and geographical specifics and productivity), Leningrad: Nauka, 1989. Rivkina E., Gilichinsky D., Wagener S., Tiedje J., Mcgrath J., Biochemical activity of anaerobic microorganisms from buried permafrost sediments, Geomicrobiology journal , 1998, Vol. 15, No. 3, pp. 187-193. Rivkina E.M., Kraev G.N., Krivushin K.V., Laurinavichus K.S., Fyodorov-Davydov D.G., Kholodov A.L., Shcherbakova V.A., Gilichinsky D.A., Metan v vechnomerzlykh otlozheniyakh severo-vostochnogo sektora Arktiki (Methane in permafrost of Northeastern Arctic), Kriosfera Zemli , 2006, Vol. 10, No. 3, pp. 23-41. Rivkina E.M., Laurinavichus K.S., Gilichinsky D.A., Shcherbakova V.A., Methane generation in permafrost sediments, Doklady Biological Sciences , 2002, Vol. 383, No. 1, pp. 179-181. Schinner F., Ohlinger R., Kandeler E., Margesin R., Methods in soil biology , Berlin - Heidelberg: Springer, 1996, 426 p. Shishov L.L., Tonkonogov V.D., Lebedeva I.I., Gerasimova M.I., Klassifikatsiya i diagnostika pochv Rossii (Classification and recognition of soils in Russia), Smolensk: Oikumena, 2004, 342 p. Sorokin N.D., Mikroflora taezhnykh pochv Srednei Sibiri (Microflora of taiga soils in Central Siberia), Novosibirsk: Nauka, 1981, 144 p. Sorokin N.D., Evgrafova S.Y., Pashenova N.V., Grodnitskaya I.D., Polyakova G.G., Afanasova E.N., Mikrobiologicheskaya indikatsiya i monitoring narushennykh lesnykh ekosistem Sibiri (Microbiological indication and monitoring of disturbed forest ecosystems of Siberia), Sibirskii ekologicheskii zhurnal , 2005, Vol. 12, No. 4, pp. 687-692. Wagner D., Kobabe S., Pfeiffer E.-M., Hubberten H.-W., Microbial controls on methane fluxes from a polygonal tundra of the Lena Delta, Siberia, Permafrost and periglacial processes , 2003, Vol. 14, No. 2, pp. 173-185. Wright J.F., Chuvilin E.M., Dallimore S.R., Yakushev V.S., Nixon E.M., Methane hydrate formation and dissociation in fine sands at temperatures near 0°C, 7 th International conference on permafrost , Yellowknife, Canada, 23-27 June 1998: Universite Laval, Centre d'etudes nordiques, 1998, pp. 1147-1153. Zvyagintsev D.G., Metody pochvennoi mikrobiologii i biokhimii (Methods of soil biology and biochemistry), Moscow: Izd-vo MGU, 1991, 304 p.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,027
Score d'incertitude au seuil0,090

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0020,002
Communication savante0,0030,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0270,007

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,089
Tête enseignante GPT0,284
Écart entre enseignants0,195 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2017
Routes d'admission1
Résumé présentoui

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