Functional niche differentiation in co-occurring congeneric plants / by Md Saiful Islam Khan.
Bibliographic record
Abstract
"Niche differentiation is argued as one of the mechanisms explaining species coexistence. Despite their sessile nature, similar resource needs and traits to acquire and utilize resources closely related plant species coexist. I hypothesized that i) spatial distribution of congeneric species would be similar because they are closely related with similar traits and resource needs and ii) each species will perform different biological functions (growth vs. reproduction) optimally at different points along a resource gradient and thereby differentiate their functional niche to ensure coexistence by complementary resource use. I collected data on two congeneric wild blueberry species, Vaccinium angustifolium and V. myrtilloides on occurrence from 13,500 20 x 20 cm quadrates, their growth and reproductive response to light and microhabitat parameters from 360 1 x 1 m quadrates along 90 30 m transects from 5 regions of NW Ontario [Northwestern Ontario]. I also grew these two species in a common garden experiment (CGE) under a shade gradient to test their response to light in competition-free environment. A chi-square test confirmed that V. angustifolium and V. myrtilloides are co-occurring species. Variance partitioning analysis revealed that light is the most important microsite variable. Frequency of occurrence showed their abundance gradually increase from low to high light with high niche overlaps. Regression model fitting of cover (indicating growth) and berry yield (indicating reproduction) along the light gradient provided species functional response curves.
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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".