MétaCan
Menu
Back to cohort
Record W2142099870 · doi:10.2980/i1195-6860-12-3-391.1

Species richness of alien plants in South Africa: Environmental correlates and the relationship with indigenous plant species richness

2005· article· en· W2142099870 on OpenAlexvenueno aff
David M. Richardson, Mathieu Rouget, Samantha J. Ralston, Richard M. Cowling, Berndt J. van Rensburg, Wilfried Thuiller

Bibliographic record

VenueEcoscience · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
FundersDST-NRF Centre of Excellence for Invasion BiologyUniversity of Cape TownDepartment of Science and Technology, Ministry of Science and Technology, IndiaNational Research Foundation
KeywordsSpecies richnessAlienEcologyIntroduced speciesHerbariumInvasive speciesBody size and species richnessGeographyBiodiversityBiologyVegetation (pathology)PopulationDemography

Abstract

fetched live from OpenAlex

:This study explores the correlates of alien plant species richness in South Africa at the scale of quarter-degree squares (QDS; ª 25 ¥ 27 km; 675 km2). We considered all alien plant species for which we had records and a subset of these – those that invade natural and semi-natural vegetation. The main source of data for species richness of indigenous and alien plant species was a national database based on herbarium specimens. For invasive alien species, data were from a national atlassing project. First, we explored the importance of energy availability and habitat heterogeneity as correlates of indigenous, alien, and invasive alien plant species richness. Linear regression models showed that species richness in the three groups of plants was explained by the same variables: a principal component of climatic factors and topographic roughness were the top-ranking variables for all groups. Next, we examined the role of indigenous species richness together with a range of environmental and human-activity variables in explaining species richness of alien and invasive alien plants. Results reveal an interplay of natural features and variables that quantify the dimension of human activities. If indigenous species richness is ignored, human-activity variables are more strongly correlated with alien species richness than with invasive alien species richness. Numbers of alien and invasive species in QDSs are significantly correlated with indigenous plant species richness in the 1,597 QDSs selected for analysis, a pattern consistent with findings from other parts of the world. Analysis of residuals between observed and predicted values showed that patterns differed between biomes. The results are useful for planning long-term intervention policy at the national scale; they suggest that areas with rich native biodiversity will face a sustained onslaught from invasive alien species and that ongoing management actions will be required to reduce and mitigate impacts from biological invasions in these areas.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.012
GPT teacher head0.185
Teacher spread0.173 · 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 source (direct Gemma or distilled Codex), 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

Citations98
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueEcoscienceSame topicEcology and Vegetation Dynamics StudiesFrench-language works237,207