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Record W3174925423 · doi:10.1038/s41598-021-92423-5

Effects of thinning and understory removal on the soil water-holding capacity in Pinus massoniana plantations

2021· article· en· W3174925423 on OpenAlexaff
Ting Wang, Qing Xu, Deqiang Gao, Beibei Zhang, Haijun Zuo, Jing Jiang

Bibliographic record

VenueScientific Reports · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsUniversity of Calgary
FundersNational Key Research and Development Program of ChinaChinese Academy of ForestryMinistry of Science and Technology of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsThinningPinus massonianaUnderstoryEnvironmental scienceSoil waterAfforestationForest managementAgroforestryHydrology (agriculture)ForestryAgronomySoil scienceEcologyGeographyGeologyCanopyBiologyBotany

Abstract

fetched live from OpenAlex

Forest management practices play an important role in regulating the soil water-holding capacity of plantation. However, most studies focus on soil water dynamics present during large-scale forest loss and afforestation events, while little is known about how soil water under different forest management practices responds to rainfall events and which factors mainly regulate soil water-holding capacity. In this study, a stable hydrogen isotope was used to explore the contribution of three natural rainfall events (8.9, 13.3 and 67.7 mm) to soil water (CRSW) in a Pinus massoniana plantation under four forest management practices (no thinning (NTN), understory removal (USR), light-intensity thinning (LIT) and heavy-intensity thinning (HIT)) in the Three Gorges Reservoir Area of the Yangtze River Basin in China. Furthermore, a structural equation model was employed to determine the effects of vegetation biomass and soil properties on the CRSW. The results showed that plantation soil under different forest management practices exhibited different water-holding capacities. Following light (8.9 mm) and moderate (13.3 mm) rainfall events, the CRSW in the HIT stand was slightly higher than that in the other stands. Following heavy (66.7 mm) rainfall event, the CRSW of most layers in USR stand was not different from the other three stands, while the CRSW in the LIT and NTN stands was significantly higher than that in the HIT stand in the 0-100 cm soil layers, suggesting that soil in the LIT and NTN stands had a greater water-holding capacity than that in the HIT stand. In addition, soil properties were the main factors directly affecting the CRSW, explaining 60% and 37% of the variation in the CRSW on the first and seventh days after heavy rainfall, respectively. Overall, compared to the HIT stand, the LIT and NTN stands showed greater capacity in retaining rainwater. Therefore, under expected global changes with frequent occurrences of extreme precipitation events, methods involving light-intensity and no thinning should be employed to build up soil and water conservation functions, which will be critical for keeping water-holding capacity and moderating floods.

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 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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.035
GPT teacher head0.202
Teacher spread0.167 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations43
Published2021
Admission routes1
Has abstractyes

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