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Distinct roles of plant and microbial communities in ecosystem multifunctionality during grassland degradation and restoration

2025· article· en· W4411116475 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

VenueGeoderma · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaCanadian Anesthesiologists' Society
KeywordsGrasslandEcosystemGrassland ecosystemGrassland degradationEnvironmental scienceRestoration ecologyAgroforestryDegradation (telecommunications)Plant communityEnvironmental resource managementEcosystem servicesEcologyEcological successionBiologyEngineering

Abstract

fetched live from OpenAlex

Understanding the mechanisms of grassland degradation and restoration is critically important for maintaining the health of grasslands, which occupy one-third of the planet’s land surface. Extensive research has focused on the impacts of plant communities on ecosystem multifunctionality (EMF) during grassland degradation and restoration, but soil microbial communities have been left out. This project investigated the roles of plant and soil microbial communities in regulating EMF across five grassland ecosystems spanning a 3,500 km transect. We quantified EMF based on eight ecosystem functions and assessed its dynamics during seven phases: natural grassland, moderate degradation, heavy degradation, severe degradation, short-term fencing, medium-term fencing, and long-term fencing. Our results showed that during grassland degradation, bacterial diversity declined more slowly than fungal and plant diversity, and EMF decline was primarily driven by reductions in plant diversity and the abundance of perennial forbs. During grassland restoration, the bacterial community recovered much faster than the plant and fungal communities, emerging as the primary driver of EMF recovery. Structural equation modeling identified plant and microbial communities as the most important predictors of EMF, even after accounting for climate and soil properties. Soil bacterial diversity and the relative abundance of dominant bacterial taxa (e.g., Actinobacteria , Proteobacteria , and Verrucomicrobia ) were key determinants of EMF recovery. Functional redundancy and resilience of these dominant bacterial taxa enabled consistent EMF recovery across diverse climate conditions. This study provides valuable insights into the distinct roles that soil microbial and plant communities play in driving EMF dynamics during grassland degradation and restoration. Our findings highlight the dominant role of soil bacteria in grassland restoration, suggesting that future management practices should prioritize promoting soil bacterial communities to enhance grassland recovery.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.949

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)0.0000.000

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 head0.012
GPT teacher head0.202
Teacher spread0.190 · 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