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Record W2069346657 · doi:10.1016/j.proenv.2012.01.193

Spatial and Temporal Variability of Nitrogen Deposition and Its Impacts on the Carbon Budget of China

2012· article· en· W2069346657 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProcedia Environmental Sciences · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversité du Québec à Montréal
Fundersnot available
KeywordsDeposition (geology)NitrogenEnvironmental scienceAtmospheric sciencesHydrology (agriculture)ChemistryGeologyStructural basin

Abstract

fetched live from OpenAlex

Nitrogen deposition in different regions has different volume and rate. And the impaction of nitrogen deposition is also inconformity on the different ecosystems. In order to study the atmospheric deposition of nitrogen stress on the carbon cycle, we analyzed the history, present and future trends in the evolution of nitrogen deposition, using remote sensing data and models. At the mean while, a series of spatial and temporal nitrogen deposition data was established and install into the Integrated Biosphere Simulator (IBIS), in order to found out the effects of different nitrogen deposition levels on the carbon budget in China. GOME and SCIAMICHY remote sensing data provide us a long time series of nitrogen dioxide column concentration data which can be fitted by the sine function. So it was used to construct nitrogen deposition data associated with ground observation data and recent research results of nitrogen deposition (dry and wet). Along with the nitrogen deposition data, two climate change seniors (A2 and B1) were used to drive the IBIS model. Comparing impact of different nitrogen deposition level, six simulation experiments have been set. The results show that ecosystem responses to nitrogen deposition will be different under future climate change scenarios. In the aggregate, more nitrogen input may not be able to bring more NPP and NEP in the future. At the meanwhile, the responses of different vegetation types to nitrogen deposition will show significant differences.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.183

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.186
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it