MétaCan
Menu
Back to cohort
Record W2148007941 · doi:10.1111/aec.12213

Floristic composition in relation to environmental gradients across <scp>K</scp>wa<scp>Z</scp>ulu‐<scp>N</scp>atal, <scp>S</scp>outh <scp>A</scp>frica

2014· article· en· W2148007941 on OpenAlex

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

VenueAustral Ecology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsCascades (Canada)
Fundersnot available
KeywordsFloristicsEdaphicGrasslandEcologyGeographyVegetation (pathology)Species richnessBiologySoil water

Abstract

fetched live from OpenAlex

Abstract Conservation planning in the face of global change is still in its infancy. A suggested approach is to incorporate environmental gradients into conservation planning as they reflect the ecological and evolutionary processes generating and maintaining diversity. Our study provides a framework to identify the dominant environmental gradients determining floristic composition and pattern. Nonmetric multidimensional scaling was used on 2155 sampling plots in savanna and grassland habitat located across the province of K wa Z ulu‐ N atal, S outh A frica (94 697 km 2 ), a floristically rich region having steep environmental gradients, to determine the dominant gradients. Hierarchical cluster analysis was used to group similar plots which were then used in a C lassification and R egression T ree analysis to determine the environmental delimiters of the identified vegetation clusters. Temperature‐related variables were the strongest delimiters of floristic composition across the province, in particular mean annual temperature. Frost duration was the primary variable in the C lassification and R egression T ree analysis with important implications for savanna/grassland dynamics. Soil properties (base, pH status) and moisture variables accounted for most of the variation for the second and third axes of floristic variation. Given that climatic and edaphic variables were well correlated with floristic composition, it is anticipated that a changing climate will have a marked influence on floristic composition. We predict warmer temperatures may facilitate the spread of frost sensitive savanna species into previously cooler, grassland areas. Species associated with specific soil types will not easily be able to move up the altitudinal gradient to cooler climes because geology is aligned in an approximately north‐south direction compared with increasing altitude from east‐west. Future conservation planning should take cognisance of these gradients which are surrogates for ecological and evolutionary processes promoting persistence.

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.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0000.007

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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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