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Record W2069602962 · doi:10.2136/sssaj2008.0278l

Comments on “No‐Tillage and Soil‐Profile Carbon Sequestration: An On‐Farm Assessment”

2009· article· en· W2069602962 on OpenAlexaboutno aff
Robert M. Boddey, Cláudia Pozzi Jantalia, Bruno José Rodrígues Alves, Segundo Urquiaga

Bibliographic record

VenueSoil Science Society of America Journal · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsTillagePloughSoil carbonEnvironmental scienceSoil scienceCarbon sequestrationSoil waterSoil seriesTotal organic carbonSoil surveyAgronomySoil classificationChemistryEnvironmental chemistryEcologyCarbon dioxideBiology

Abstract

fetched live from OpenAlex

4 present data on soil organic carbon (SOC) concentrations from soils managed under no-tillage (NT) or plow-tillage (PT) from samples taken from studies of paired fields at 11 (MLRA) sites in three states of the USA. The results seem to show extremely large annual changes in soil organic C stocks between NT and PT to a depth of 60 cm, ranging from +3.75 to −6.65 Mg ha−1 yr−1 (Table 2). However, these values are far greater, and not compatible with, the data displayed in Fig. 2, nor the total stocks of soil N and the C/ N ratio displayed in Tables 3 and 4, respectively. However, the data displayed taken from seven studies in the literature (a total of 16 comparisons) are correctly reported as annual changes. Table 2 should thus be corrected as shown here (Table 1). A further error in the data presentation is in the vertical scale adopted for the Fig. 4, which suggests that most soil profiles contained over 200 Mg C ha−1 to a depth of 60 cm, and that several woodlots showed soil C stocks above 500 Mg C ha−1 to this depth. These errors do not change the main conclusion of the study that “the idea that no-tillage would also enhance soil organic carbon sequestration as an additional benefit of no-tillage technology needs a careful examination.” However the data as presented grossly exaggerate the magnitude of possible gains and losses in such systems. Although the authors cite two studies from southern Brazil, in neither was the soil sampled to a depth >40 cm. Two more recent studies from the same region on the same soil type (Typic Hapludox) were sampled to depths of 100 cm or more (8; 5). In the study of 8 where a N2–fixing legume (hairy vetch—Vicia villosa) was included as a winter crop with maize (Zea mays) in summer, the soil C stocks to 30 cm under NT management was between 5.4 and 9.1 Mg ha−1 greater than under PT. When the soil was sampled to the 100-cm depth the difference in C stocks increased to 16.9 Mg C ha−1 in both rotations. In the study of 5 in two rotations maize was planted in a mixture with either lablab (Lablab purpureum) or pigeon pea (Cajanus cajan). In these rotations, the C stocks to a 17.5-cm depth increased by between 7.9 and 8.4 Mg C ha−1 under NT after a 17-yr period. When sampling was made to 107.5 cm, the increase in soil C stocks under NT were even greater at 13.1 and 21.2 Mg C ha−1 Recent results from sites in the USA (6; 7; 4), as well earlier results from Canada (2; 9), suggest that increases in soil C to depths of 20 to 30 cm under NT do not necessarily indicate that any net C sequestration occurred, as higher concentrations of C can be encountered under PT at depths below this. However, the two studies on free-draining Oxisols in southern Brazil indicate that, (i) C accumulation is highly dependent on N supply (a positive N balance from legumes– 1), and, (ii) in these cases where C accumulation was detected within the “plow layer,” deeper sampling revealed that C sequestration under NT compared with PT was much greater than was to be expected from the shallower soil sampling. Data from all sites indicate that in all sampling to assess net changes in soil C due to changes in tillage practice it is essential to sample well below the plow layer (>60 cm). Most data from temperate regions suggest that superficial sampling will overestimate possible benefits of changes form PT to NT (3), but in the case of deep free-draining soils in the tropics it may be that shallow sampling could lead to gross underestimation of soil C sequestration after adoption of NT.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0200.012
Insufficient payload (model declined to judge)0.0100.006

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 head0.016
GPT teacher head0.275
Teacher spread0.258 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations8
Published2009
Admission routes1
Has abstractyes

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