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Record W4408887820 · doi:10.1111/jvs.70032

Successful Alien Plant Species Exhibit Functional Dissimilarity From Natives Under Varied Climatic Conditions but Not Under Increased Nutrient Availability

2025· article· en· W4408887820 on OpenAlexaff
Marija Milanović, Jonathan D. Bakker, Lori Biederman, Elizabeth T. Borer, Jane A. Catford, Elsa E. Cleland, Nicole Hagenah, Sylvia Haider, W. Stanley Harpole, Kimberly J. Komatsu, Andrew S. MacDougall, Christine Römermann, Eric W. Seabloom, Sonja Knapp, Ingolf Kühn

Bibliographic record

VenueJournal of Vegetation Science · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Guelph
FundersDeutsche ForschungsgemeinschaftDeutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-LeipzigNational Science Foundation
KeywordsNutrientEcologyAlienBiologyPlant communitySpecies richness

Abstract

fetched live from OpenAlex

ABSTRACT Aims The community composition of native and alien plant species is influenced by the environment (e.g., nutrient addition and changes in temperature or precipitation). A key objective of our study is to understand how differences in the traits of alien and native species vary across diverse environmental conditions. For example, the study examines how changes in nutrient availability affect community composition and functional traits, such as specific leaf area and plant height. Additionally, it seeks to assess the vulnerability of high‐nutrient environments, such as grasslands, to alien species colonization and the potential for alien species to surpass natives in abundance. Finally, the study explores how climatic factors, including temperature and precipitation, modulate the relationship between traits and environmental conditions, shaping species success. Location In our study, we used data from a globally distributed experiment manipulating nutrient supplies in grasslands worldwide (NutNet). Methods We investigate how temporal shifts in the abundance of native and alien species are influenced by species‐specific functional traits, including specific leaf area (SLA) and leaf nutrient concentrations, as well as by environmental conditions such as climate and nutrient treatments, across 17 study sites. Mixed‐effects models were used to assess these relationships. Results Alien and native species increasing in their abundance did not differ in their leaf traits. We found significantly lower specific leaf area (SLA) with an increase in mean annual temperature and lower leaf Potassium with mean annual precipitation. For trait–environment relationships, when compared to native species, successful aliens exhibited an increase in leaf Phosphorus and a decrease in leaf Potassium with an increase in mean annual precipitation. Finally, aliens' SLA decreased in plots with higher mean annual temperatures. Conclusions Therefore, studying the relationship between environment and functional traits may portray grasslands' dynamics better than focusing exclusively on traits of successful species, per se.

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)0.001
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 score0.177
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
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 head0.024
GPT teacher head0.279
Teacher spread0.254 · 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

Citations4
Published2025
Admission routes1
Has abstractyes

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