Lagged climate‐driven range shifts at species' leading, but not trailing, range edges revealed by multispecies seed addition experiment
Bibliographic record
Abstract
Climate change is causing many species' ranges to shift upslope to higher elevations as species track their climatic requirements. However, many species have not shifted in pace with recent warming (i.e. ‘range stasis'), possibly due to demographic lags or microclimatic buffering. The ‘lagged‐response hypothesis' posits that range stasis disguises an underlying climatic sensitivity if range shifts lag the velocity of climate change due to slow colonization (i.e. colonization credits) or mortality (i.e. extinction debt). Alternatively, the ‘microclimatic buffering hypothesis' proposes that small‐scale variation within the landscape, such as canopy cover, creates patches of suitable habitat within otherwise unsuitable macroclimates that create climate refugia and buffer range contractions. We simultaneously test both hypotheses by combining a large seed addition experiment of 25 plant species across macro‐ and micro‐scale climate gradients with adult occurrence records to compare patterns of seedling recruitment relative to adult ranges and microclimate in the North Cascades, USA. Despite high species‐to‐species variability in recruitment, community‐level patterns monitored for five years supported the lagged response hypothesis, with a mismatch between where seedlings recruit versus adults occur. On average, the seedling recruitment optimum shifted from the adult climatic range centre to historically cooler, wetter regions and many species recruited beyond their cold (e.g. leading) range edge. Meanwhile, successful recruitment occurred at warm and dry edges, despite recent climate change, suggesting that macroclimatic effects on recruitment do not drive trailing range dynamics. We did not detect evidence of microclimatic buffering due to canopy cover in recruitment patterns. Combined, our results suggest apparent range stasis in our system is a lagged response to climate change at the cool ends of species ranges, with range expansions likely to occur slowly or in a punctuated fashion.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".