Inter‐specific and intra‐specific trait variation along short environmental gradients in an old‐growth temperate forest
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.
Bibliographic record
Abstract
Abstract Question When can we assume that inter‐specific trait variation is higher than intra‐specific trait variation in plant community ecology? Location Old‐growth deciduous forest in the G ault N ature R eserve, M ount S t. H ilaire ( Q uebec, C anada,45′32.957″ N , 73′08.884″ W ), with a shorter environmental gradient than normally exists in community studies. Methods We measured 15 functional traits on all tree saplings occurring in 39 (5–7‐m radius) sample plots. Using variance decomposition from mixed models and from sums of squares of community‐weighted traits, we determined the relative importance of temporal, spatial, inter‐specific, intra‐specific and intra‐individual variation in each trait. In total, we collected trait information on 3317 leaves from 786 twigs sampled on 422 saplings. Results For 12 of 15 traits, over 50% of the total variance existed between species and inter‐specific variation was always the most important source of variation. However for 14 traits, intra‐specific and environmental variation represented up to 28% of the total variation. Variation in community‐weighted trait means was mostly generated by changes in species composition, but intra‐specific trait variation was the dominate cause for leaf nitrogen, specific leaf area and tree branching. The intra‐individual and temporal sources of variation were not important. Conclusions Trait variation should be dominated by inter‐specific differences in most studies since they involve systems with more pronounced environmental gradients, higher species richness and more β‐diversity than used here. However, in studies with short gradients, or when using more plastic traits, it will be necessary to measure trait values for each site. It is important to quantify the β‐diversity of the environmental gradients in question in order to compare results across studies.
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 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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| 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 it