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Record W4313573627 · doi:10.1111/oik.09559

Intraspecific trait variability mediates the effect of nitrogen addition and warming on aboveground productivity

2023· article· en· W4313573627 on OpenAlexaff
Li Zhang, Seraina L. Cappelli, Mengjiao Huang, Xiang Liu, Yao Xiao, Françoise Cardou, Yizhong Rong, Shurong Zhou

Bibliographic record

VenueOikos · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersHainan UniversityNational Natural Science Foundation of ChinaNanjing Forestry University
KeywordsIntraspecific competitionInterspecific competitionTraitBiologyProductivityEcosystemEcologyDominance (genetics)Global warmingClimate change

Abstract

fetched live from OpenAlex

Recent studies have shown that intraspecific trait variability is an important source of total trait variation. However, the contribution of intraspecific variability to ecosystem functions in the face of global change remains unknown. We quantified the relative contribution of intra‐ and inter‐specific functional changes on productivity in 48 plots subjected to eight years of nitrogen addition and warming in a Tibetan alpine meadow. The change of the mean (community weighted mean) and the variation (Rao's quadratic entropy) in trait values in response to nitrogen addition and warming were separated into the changes driven by interspecific and intraspecific trait variations using a variance partitioning method. We found that productivity showed a hump‐shaped response to nitrogen addition, with the highest productivity at intermediate levels of nitrogen addition. This hump‐shaped response was mediated by the changes in plant functional structure. A community having higher interspecific variation in plant height and individuals producing bigger leaf area can increase productivity via niche complementary and dominance effects, respectively. Warming reduced productivity directly and marginally decreased individuals' leaf area which suppressed productivity indirectly. Our research suggests a non‐negligible role of plant intraspecific trait variability in maintaining ecosystem functions, especially in the face of global change.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.235

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 head0.007
GPT teacher head0.222
Teacher spread0.215 · 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 designObservational
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

Citations13
Published2023
Admission routes1
Has abstractyes

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