Species' intrinsic traits inform their range limitations and vulnerability under environmental change
Bibliographic record
Abstract
Abstract Aim Understanding the factors that govern species' geographical ranges is of utmost importance for predicting potential range shifts triggered by environmental change. Species ranges are partially limited by their tolerances to extrinsic environmental conditions such as climate and habitat. However, they are also determined by the capacity of species to disperse, establish new populations and proliferate, which are in turn dependent on species intrinsic life‐history traits. So far, the contribution of intrinsic factors driving species distributions has been inconclusive, largely because intrinsic and extrinsic factors have not been examined simultaneously in a satisfactory way. We investigate how geographical ranges of plants are determined by both extrinsic environmental factors and species intrinsic life‐history traits. Location E urope. Methods We compiled a database on plant geographical ranges, environmental tolerances and life‐history traits that constitutes the largest dataset analysed to date (1276 species). We used generalized linear modelling to test if range size and range filling (the proportion of climatically suitable area a species occupies) are affected by dispersal distance, habitat breadth and 10 life‐history traits related to establishment and proliferation. Results The species characteristics that were most linked to range limitations of E uropean plant species were dispersal potential, seed bank persistence and habitat breadth (which together explained ≥ 30% of deviance in range filling and range size). Specific leaf area, which has been linked to establishment ability, made a smaller contribution to native range limitations. Main conclusions Our results can be used to improve estimates of extinction vulnerability under climate change. Species with high dispersal capacity, that can maintain viable seed banks for several years and that can live in an intermediate number of habitats have the fewest non‐climatic limitations on their ranges, and are most likely to shift their geographical ranges under climate change. We suggest that climate‐change risk assessments should not focus exclusively on dispersal capacity.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".