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Mapping N deposition impacts on soil microbial biomass across global terrestrial ecosystems

2023· article· en· W4324353163 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGeoderma · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiomass (ecology)EcosystemTerrestrial ecosystemDeposition (geology)Environmental scienceSoil waterBiodiversityEnvironmental chemistryAgronomyEcologySoil scienceBiologyChemistry

Abstract

fetched live from OpenAlex

Soil microorganisms are key for biodiversity and ecosystem processes. Recent meta-analyses based on nitrogen (N) addition experiments reported an overall negative impact of elevated N on soil microbial biomass on a global scale. However, individual studies have reported divergent effects of N addition, ranging from strongly negative to even positive. Moreover, N deposition varies temporally and spatially worldwide. It remains uncertain how the effects of N deposition on soil microbial biomass vary across global terrestrial ecosystems over time. Through the synthesis of 374 N addition experiments across six continents, we revealed that low quantities of N increased the soil microbial biomass, but high N amounts strongly reduced it. Moreover, the N addition effects were strongly contingent on the ecosystem type, being highly negative in grasslands (−19.3 ± 6.2%, mean and 95% confidence intervals), negative in forests (−8.6 ± 4.2%), and positive in croplands (15.1 ± 12.3%). Further, the soil microbial biomass was most negatively affected by N addition in acidic soils. By combining our meta-analysis results from N addition experiments and global N deposition data, we revealed that the global soil microbial biomass increased by 10.0% in response to cumulative N deposition from 2000–2020. However, regions encompassing the Eastern U.S., Southern Brazil, Europe, and Eastern Asia, with high N deposition rates and large forested areas of acidic soils, were hotspots for microbial biomass loss. Our findings challenge the long-held notion that N deposition has universal negative impacts on soil microbial biomass. Instead, we show that the N deposition impacts on soil microbial biomass are dependent on the amounts of elevated N, ecosystem type, and soil pH, for which N-deposition-induced soil acidification acts as an internal mechanism.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.249
Teacher spread0.227 · 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