Using biodiversity deconstruction to disentangle assembly and diversity dynamics of understorey plants along post‐fire succession in boreal forest
Bibliographic record
Abstract
ABSTRACT Aim The study aims to decipher the co‐occurrence of understorey plant assemblages and, accordingly, to identify a set of species groups (diversity deconstruction) to better understand the multiple causal processes underlying post‐fire succession and diversity patterns in boreal forest. Location North‐eastern Canadian boreal forest (49°07′–51°44′ N; 70°13′–65°15′ W). Methods Data on understorey plant communities and habitat factors were collected from 1097 plots. Species co‐occurrence was analysed using null model analysis. We derive species groups (i.e. biodiversity deconstruction) using the strength of pairwise species co‐occurrences after accounting for random expectation under a null model and cluster analyses. We examine the influence of a set of spatiotemporal environmental variables (overstorey composition, time‐since‐fire, spatial location and topography) on richness of species groups using Bayesian model averaging, and their relative influence through hierarchical partitioning of variance. Results Understorey plant assemblages were highly structured, with co‐occurrence‐based classification providing species groups that were coherently aggregated within, but variably segregated between, species groups. Group richness models indicate both common and distinct responses to factors affecting plant succession. For example, Group 2 (e.g.Rhododendron groenlandicumandCladina rangiferina) showed concurrent contrasting responses to overstorey composition and was strongly segregated from Groups 3 (e.g.Clintonia borealisandMaianthenum canadense) and 4 (e.g.Epilobium angustifoliumandAlnus rugosa). Groups 3 and 4 showed partial similarity, but they differed in their response to time‐since‐fire, drainage and latitude, which were more important for Group 1 (e.g.Ptilium crista‐castrensisandEmpetrum nigrum). A single successional model based on total richness masked crucial group‐level relationships with factors that we examined, such as latitude. Main conclusions By demonstrating the co‐occurrence structure and linking to causal factors, the results from this study characterize both common and distinct responses of understorey plants to biophysical attributes of sites, and potential interspecific interactions, behind non‐random assemblage structure during post‐fire succession. A biodiversity deconstruction approach could offer a concise and explicit framework to gain a better understanding of the complex assembly of ecological communities during succession.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".