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Record W3193650010 · doi:10.1016/j.gecco.2021.e01775

Restoration in degraded subtropical broadleaved forests induces changes in soil bacterial communities

2021· article· en· W3193650010 on OpenAlex
Yuhua Ma, Chun Feng, Zhaocheng Wang, Cheng Huang, Xingzhao Huang, Wenjing Wang, Shaobo Yang, Songling Fu, Han Y. H. Chen

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

VenueGlobal Ecology and Conservation · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsLakehead University
Fundersnot available
KeywordsChronosequenceBiomass (ecology)Environmental scienceSoil carbonEcosystemEcologyForest restorationActinobacteriaSoil waterForest ecologyAgronomyAgroforestryBiology

Abstract

fetched live from OpenAlex

Soil resident bacterial communities are involved in myriad key processes that facilitate ecosystem functionality. However, our understanding of their diversity and compositional dynamics following ecological restoration, and the main factors that influence them, remains inadequate. We employed a chronosequence (0–1, 5–6, 11–12, 20–24, and 28–34 years since restoration) to examine the dynamic changes in soil bacterial diversity and composition, as well as the essential factors that affected them since the cessation of anthropogenic disturbances (e.g., recurring fuelwood collection and domestic animal grazing), and used old-growth forests as a reference in the subtropical forests of Eastern China. We found that soil bacterial diversity increased with time since restoration, and community compositions shifted toward being similar to those of old-growth forests over time. However, the recovery process was prolonged since the significant difference in soil bacterial diversity between degraded and restored forests did not occur until after 24 years since restoration. Multivariate analysis using multiple-response permutation procedures indicated the soil bacterial communities were compositionally distinct between degraded, restored, and old-growth forests. An analysis of indicator species revealed that forests at the early stage of recovery times supported Rokubacteria and Actinobacteria, while old-growth forests were distinguished by Chlamydiae. Soil carbon, microbial biomass carbon, soil water content, and microbial biomass nitrogen recovered over time and became increasingly akin to those of old-growth forest soils. Soil carbon, soil water content, and soil pH could explain 84.5% of the variations in bacterial community dynamics following restoration. Overall, this study revealed a prolonged recovery process of the community structures of soil bacteria (e.g., diversity, composition, and phylum abundance) following restoration, which was coupled with changes in soil properties in subtropical forests of China.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.895
Threshold uncertainty score1.000

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)0.0010.000

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 head0.024
GPT teacher head0.241
Teacher spread0.216 · 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