ВЛИЯНИЕ АЗОТА НА МИНЕРАЛИЗАЦИЮ И ГУМИФИКАЦИЮ ЛЕСНЫХ ОПАДОВ В МОДЕЛЬНОМ ЭКСПЕРИМЕНТЕ
Bibliographic record
Abstract
RUSSIAN JOURNAL OF FOREST SCIENCE. 2017, No. 2, pp. 128-139 THE CONTRIBUTION OF NITROGEN TO MINERALIZATION AND HUMIFICATION OF FOREST LITTER IN SIMULATION STUDY A. A. Larionova 1 , A. K. Kvitkina 1 , S. S. Bykhovets 1 , V. O. Lopes-de-Gerenyu 1 , Y. G. Kolyagin 2 , V. V. Kaganov 3 1 Institute of Physicochemical and Biological Problems of Soil Sciences, Russian Academy of Sciences Institutskaya st., 2, Pushchino, Moscow Oblast, 142290, Russia E-mail: larionova_al@rambler.ru 2 Faculty of Chemistry, Lomonosov Moscow State University Leninskie gory, 1, bldg.3, Moscow, 119991, Russia 3 Center for Forest Ecology and Productivity of the Russian Academy of Sciences Profsoyuznaya st., 84/32, bldg. 14, Moscow, 117997, Russia Received 16 June 2016 We carried out long-term incubations to study the contribution of endogenous and exogenous nitrogen to decomposition of various fractions of forest litter, sampled in linden, pine and aspen mixed forest in Prioksko-Terrasny Nature Reserve. Based on C:N ratio signatures (including endogenous nitrogen) the following sequence was found: mortmass of cyanobacteria Nostoсcommunae (C:N ratio 9), deciduous litter (C:N ratio 32), pine needles litter (C:N ratio 66), pine bark litter (C:N ratio 84), coarse woody debris of linden (C:N ratio 206), coarse woody debris of pine (C:N ratio 510). To find the effect of exogenous nitrogen we applied NH 4 NO 3 to the litters until the prescribed C:N ratio in the range of 5 to 204 has been reached. Mineralization was assessed by CO 2 emission intensity. Humification was measured by changes in the share of structural fragments in organic matter of litter from solid-state 13 C NMR. We found logarithmic relationship between the rate of carbon mineralization and initial C:N ratio in litter, having maximum at C:N ratio of 22. Mineral nitrogen treatment increased the intensity of mineralization of the litter fractions poor in nitrogen (C:N ratio exceeding 66) and inhibited CO 2 emission from decomposition of litter with high nitrogen content (C:N ratio from 9 to 32). During the litter decomposition the Alkyl/O-Alkyl ratio increased. It corresponds to the level of humification of plant matter in soils. Additional nitrogen treatment has stimulated humification, especially during pine needles decomposition. Thus we found the effect of endogenous and mineral nitrogen on both mineralization and humification of forest litter. Acknowledgements: This study was financially supported by the Russian foundation for basic research (14-04-01738, 14-04-01884). Keywords: forest litter, plant debris decomposition, C:N ratio, mineralization, humification, mineral nitrogen. 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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".