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Record W3205235105 · doi:10.1186/s13717-021-00334-0

Effects of sulfuric, nitric, and mixed acid rain on the decomposition of fine root litter in Southern China

2021· article· en· W3205235105 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEcological Processes · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
FundersPostdoctoral Science Foundation of Jiangsu ProvinceJiangsu Agricultural Science and Technology Innovation FundPriority Academic Program Development of Jiangsu Higher Education InstitutionsGovernment of Jiangsu ProvinceChina Postdoctoral Science FoundationLakehead University
KeywordsAcid rainNitric acidChemistryNitrogenSulfuric acidDecompositionLitterPhosphorusNitrateNutrientSoil pHSoil acidificationSoil waterEnvironmental chemistryAgronomyEnvironmental scienceSoil scienceInorganic chemistryBiology

Abstract

fetched live from OpenAlex

Abstract Background China has been increasingly subject to significant acid rain, which has negative impacts on forest ecosystems. Recently, the concentrations of NO 3 − in acid rain have increased in conjunction with the rapid rise of nitrogen deposition, which makes it difficult to precisely quantify the impacts of acid rain on forest ecosystems. Methods For this study, mesocosm experiments employed a random block design, comprised of ten treatments involving 120 discrete plots (0.6 m × 2.0 m). The decomposition of fine roots and dynamics of nutrient loss were evaluated under the stress of three acid rain analogues (e.g., sulfuric (SO 4 2− /NO 3 − 5:1), nitric (1:5), and mixed (1:1)). Furthermore, the influences of soil properties (e.g., soil pH, soil total carbon, nitrogen, C/N ratio, available phosphorus, available potassium, and enzyme activity) on the decomposition of fine roots were analyzed. Results The soil pH and decomposition rate of fine root litter decreased when exposed to simulated acid rain with lower pH levels and higher NO 3 − concentrations. The activities of soil enzymes were significantly reduced when subjected to acid rain with higher acidity. The activities of soil urease were more sensitive to the effects of the SO 4 2− /NO 3 − (S/N) ratio of acid rain than other soil enzyme activities over four decomposition time periods. Furthermore, the acid rain pH significantly influenced the total carbon (TC) of fine roots during decomposition. However, the S/N ratio of acid rain had significant impacts on the total nitrogen (TN). In addition, the pH and S/N ratio of the acid rain had greater impacts on the metal elements (K, Ca, and Al) of fine roots than did TC, TN, and total phosphorus. Structural equation modeling results revealed that the acid rain pH had a stronger indirect impact (0.757) on the decomposition rate of fine roots (via altered soil pH and enzyme activities) than direct effects. However, the indirect effects of the acid rain S/N ratio (0.265) on the fine root decomposition rate through changes in soil urease activities and the content of litter elements were lower than the pH of acid rain. Conclusions Our results suggested that the acid rain S/N ratio exacerbates the inhibitory effects of acid rain pH on the decomposition of fine root litter.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.136

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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