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Record W3155860714 · doi:10.1139/as-2020-0007

Community-level functional traits of alpine vascular plants, bryophytes, and lichens after long-term experimental warming

2021· article· en· W3155860714 on OpenAlexvenueno aff
Kristel van Zuijlen, Kari Klanderud, Oda Sofie Dahle, Åshild Hasvik, Maria Skar Knutsen, Siri Lie Olsen, Snorre Sundsbø, Johan Asplund

Bibliographic record

VenueArctic Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsnot available
FundersNorges Forskningsråd
KeywordsBryophyteLichenVascular plantBiologyEcologyThallusBotanyEnvironmental scienceAgronomySpecies richness

Abstract

fetched live from OpenAlex

We measured community-level traits of vascular plants, lichens, and bryophytes in an alpine Dryas octopetala L. heath in Finse, Norway, after nearly two decades of experimental warming by open-top chambers. We hypothesized that under warming (1) vascular plant traits would shift from resource conservative towards more resource acquisitive, and (2) lichen and bryophyte traits would shift to those associated with drier conditions, due to increased evapotranspiration. Both hypotheses were not supported, as vascular plant nitrogen concentration decreased, whereas carbon to nitrogen ratio increased with warming, indicative of a less resource acquisitive strategy, and lichen specific thallus area and water holding capacity were unresponsive. Bryophyte specific shoot length increased, and carbon concentration and water holding capacity tended to decrease under warming, concurrent with increased vegetation height and litter cover indicating stronger competition from vascular plants. Intraspecific variation was most important for vascular plant and lichen traits, whereas species turnover was the main driver of bryophyte trait variation. This indicates that bryophytes may be affected more strongly by future warming than vascular plants and lichens in our study system. We highlight the importance of studying traits of different primary producer groups simultaneously, as they may respond differently to the same environmental changes.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.789
Threshold uncertainty score0.572

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 head0.043
GPT teacher head0.241
Teacher spread0.198 · 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

Citations15
Published2021
Admission routes1
Has abstractyes

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