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Record W2885463866 · doi:10.1080/15230430.2018.1494941

Warming and shrub encroachment decrease decomposition in arid alpine and subalpine ecosystems

2018· article· en· W2885463866 on OpenAlexaff
Laurel M. Brigham, Ellen Esch, Christopher W. Kopp, Elsa E. Cleland

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of British Columbia
FundersNational Science Foundation
KeywordsShrubEnvironmental scienceEcosystemPerennial plantEcologyLitterClimate changeNutrient cycleGlobal warmingPlant communityAridAgronomyEcological successionBiology

Abstract

fetched live from OpenAlex

Climate change is shifting species distributions and altering plant community composition worldwide. For instance, with rising temperatures shrubs are encroaching into alpine ecosystems, resulting in important implications for ecosystem functioning. In particular, woody-plant encroachment could slow decomposition in systems traditionally dominated by herbaceous species. To evaluate how litter decomposition responded jointly to warming and shrub presence, we conducted a passive warming chamber experiment in subalpine and alpine plant communities in the White Mountains of California. Passive warming chambers were placed over plots with and without the range-expanding sagebrush Artemisia rothrockii at two elevations. Litter from A. rothrockii and the common perennial herb Trifolium andersonii decomposed for two years under the experimental treatments. Nitrate availability was measured with ion-exchange resins during the same time period. Warming decreased decomposition rates overall, associated with decreased soil moisture, but did not influence soil nitrate availability. Sagebrush presence decreased both decomposition rates and nitrate availability. Hence, future warming in this system will likely reduce decomposition rates, both directly and indirectly, via shrub encroachment. However, impacts on nutrient mineralization are less clear. These findings highlight how shifting species composition, through processes such as range expansions, can influence ecosystem responses to climate 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 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 score0.023
Threshold uncertainty score0.999

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.340
Teacher spread0.277 · 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.

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

Citations20
Published2018
Admission routes1
Has abstractyes

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