Potential for northern range expansion of the understory flora of temperate Québec: edaphic, climatic and biotic factors
Bibliographic record
Abstract
The goal of my project was to determine the influence of abiotic and biotic factors on the distribution of forest plants to improve predictions of climate change effects on biodiversity. I made species distribution models of 207 species from eastern North America. These climate-species models indicated large northward displacements for most species. I then test if edaphic variables also contribute to distribution patterns. Model predictive accuracy and variable importance were compared for species' characteristics describing growth form, range boundaries within the study area, and prevalence. Both the climate-only and edaphic-only models performed well. The relative importance of variables varied with growth forms. This study highlighted the potential for non-climate aspects of the environment to pose a constraint to northern range expansion. In the third study, I proposed an approach to analyse current occupancy patterns at cold range edges to identify patterns consistent with climate or other environmental limitations. I identified species' realized growing degree day niche in order to sample zones central, marginal, or beyond-the-edge of this niche. I modelled habitat suitability, based on 11 non-climate variables, for each species, and compare the availability of, and occupancy on, suitable sites across zones, with the assumption that a limiting climate is likely to result in decreased occupancy or abundance on otherwise suitable sites toward the range limit. I also checked for evidence of shifts to warm micro-climate conditions at the range limit as a potential indication of climate limitations. I found that the availability of suitable sites declined across a latitudinal gradient for most species, while occupancy increased on suitable sites at range edge, and abundance did not vary significantly. A minority of species shifted to sites with warm micro-climate conditions; of these several also declined in abundance suggesting climate limitations. For most species studied, suitable site availability appears to determine the northern edges of distribution and, consequently, warming may not necessarily lead to range expansion. One explanation for greater occupancy at cold range edge is that there are differences in processes structuring communities along abiotic stress. I quantified, as an initial estimation of the role of biotic interactions in determining species distribution, the relative contribution of nestedness and turnover to beta diversity on and between niche (edaphically suitable) and matrix (unsuitable) habitats within the previously defined portions of species ranges. As well, I made a variation partition using distance-based RDAs for the full study area to assess the unique and shared contributions environmental variables. The regional analysis identified that at broad scale, the environmental and climatic variables contributed equally to patterns of nestedness or turnover, with most of the variation explained being shared between the variables. When zooming in on different portions of the range, the niche or matrix conditions did structure community patterns, with community composition diverging more even on similar niche conditions in the central range portion than at cold range edge. Community processes should be further investigated for their role in limiting species distribution, especially in the context of expected broad-scale community re-assembly with climate change. I conclude that climate is an important driver of plant distribution, but understanding the role of spatially-structured, co-occurring determinants such as the availability of edaphically suitable sites or competitive interactions, helps improve predictions of biodiversity response to a changing climate.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".