Linking resource availability and heterogeneity to understorey species diversity through succession in boreal forest of Canada
Bibliographic record
Abstract
Abstract Understorey vegetation comprises the majority of species diversity and contributes greatly to ecosystem functioning in boreal forests. Although patterns of understorey abundance, species diversity and composition associated with forest stand development are well researched, mechanisms driving these patterns remain largely speculative. We sampled fire‐origin stands of varying stand ages and overstorey compositions on mesic sites of the boreal forest of Canada and used structural equation modelling (SEM) to link time since fire (stand age), light availability and heterogeneity, substrate heterogeneity and soil nitrogen to understorey vegetation cover and species diversity. The most parsimonious model for total understorey cover showed a positive direct effect of stand age ( r = .43) and an indirect effect via mean light level (0.18) and shrub cover (−0.11), with a positive total effect (0.50); the per cent broadleaf canopy had a direct negative effect (−0.22) and an indirect effect via shrub cover (−0.11). The model for total understorey species richness showed an indirect effect of stand age via mean light (0.24), light heterogeneity (0.10) and substrate heterogeneity (0.07), with a positive total effect (0.52); per cent broadleaf canopy had an indirect effect via light heterogeneity (0.09), and substrate heterogeneity (−0.10). Soil nitrogen did not significantly influence either understorey cover or species richness. The models for vascular plants followed similar trends to those for total understorey cover and species richness; however, there was an opposite indirect effect of light heterogeneity for both cover and species richness of non‐vascular plants. Shrub cover had positive direct and negative direct and indirect effects on both vascular and non‐vascular cover and species richness. Synthesis . Our findings indicate that understorey cover and species diversity are driven by time since disturbance, light availability as influenced by overstorey and shrub layers, but with important additional effects mediated by light and substrate heterogeneity. Non‐vascular understorey vegetation is more strongly determined by time since disturbance than vascular vegetation, and negatively affected by broadleaf tree abundance. The overall results highlight the importance of colonization, light availability and heterogeneity, substrate specialization and growth dynamics in determining successional patterns of boreal forest understorey vegetation.
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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 | 0.001 |
| 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".