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Effects of growing conditions and source habitat on plant traits and functional group definition

2001· article· en· W2120318287 on OpenAlex
Andrew R. Dyer, Deborah E. Goldberg, Roy Turkington, C. Sayre

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

VenueFunctional Ecology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of British Columbia
FundersNational Science Foundation
KeywordsBiologyHabitatTraitBiomass (ecology)EcologyForbResource Acquisition Is InitializationPlant communityResource (disambiguation)GrasslandResource allocationSpecies richness

Abstract

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Summary Plant functional groups are used to describe patterns of community organization. However, they are defined either by suites of correlated traits or by species groupings, and the responses of these two definitions to changing environmental conditions are unknown. We assessed 14 growth and morphological traits under low‐ and high‐resource conditions of 42 annual plant species from two source communities in Israel that differed in resource availability. As current theory predicts, plants growing in the high‐resource treatment were larger, had twofold greater relative growth rate (RGR) and thinner leaves, and allocated less biomass to roots than plants grown in the low‐resource treatment. Differences in these traits were less consistent between the two source communities. Instead, taxonomic groups (grasses, legumes and a group of other forbs), regardless of source, differed in most characteristics. Three general groups of species (functional groups) were identified in both resource treatments using cluster analysis on all 14 traits. In both resource treatments monocots were almost completely separated into one distinct cluster, regardless of source habitat, while the two other, mainly dicot, clusters were partially separated by habitat. However, the species composition and trait characterization of the dicot clusters differed strongly between treatments. Under low‐resource conditions the two dicot clusters were separated by size traits and seed mass, but under high‐resource conditions, they were separated by above‐ground size, morphology and RGR. Principal components analysis demonstrated inconsistency in relationships among traits and species groupings between treatments. The first two principal components emphasized different aspects of growth depending on the treatment; the third axis was defined by growth rates. As with the cluster analysis, plots of species scores revealed relatively little separation of species by habitat. The response of each species varies for different traits and with growing conditions. Variation may differ among species within a functional group, producing different definitions of functional groups under different experimental conditions. Because most functional group analyses are performed on data collected without manipulation of growing conditions, conclusions concerning the response of species or communities to changes in environmental conditions may be problematic.

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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 score0.113
Threshold uncertainty score0.440

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 head0.010
GPT teacher head0.190
Teacher spread0.181 · 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