Temperature is the major driver of distribution patterns for C<sub>4</sub> and C<sub>3</sub> BEP grasses along tropical elevation gradients in Hawai‘i, and comparison with worldwide patterns
Bibliographic record
Abstract
The distribution patterns of C 4 and C 3 grasses in relation to climate have attracted much attention, but few studies have examined grass distributions along tropical elevation gradients. Previous studies identified either temperature, precipitation, or both variables as the major climatic factor(s) driving these distributions. Here we investigated relative dominance of C 4 grasses in relation to climate along five elevation gradients in Hawai‘i. The transition temperature between C 4 and C 3 BEP (Bambusoideae, Ehrhartoideae, and Pooideae) grasses (where their relative dominance is equal) was determined; in our study, the subfamily Bambusoideae was not included. A worldwide synthesis of previous studies testing climatic factors and transition temperatures associated with C 4 and C 3 grass distributions was also carried out. Mean July maximum temperature was significantly correlated with C 4 dominance along all elevation transects in Hawai‘i, while precipitation was only correlated along three transects when precipitation was correlated with temperature. A spatially explicit multiple regression model indicated that C 4 relative cover was best explained by temperature. Temperature appears to be the major climatic factor shaping distribution patterns of C 4 and C 3 BEP grasses in Hawai‘i. According to the worldwide analysis, temperature primarily influenced grass distribution patterns more often in temperate studies (70%) than in tropical studies (45%). Degree of correlation or covariance between temperature and precipitation was rarely reported in previous studies, although this can strongly affect conclusions. C 4 -C 3 BEP transition temperatures (mean July maximum) ranged from 18 to 21 °C in Hawai‘i; these transition temperatures are lower than those reported in temperate localities (26–31 °C), but similar to transition temperatures for other localities at tropical latitudes (21–22 °C). A warming climate is likely to shift C 4 grass dominance upward in elevation, threatening higher elevation native communities by perpetuating a grass–fire cycle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".