Tropicalization of temperate ecosystems in North America: The northward range expansion of tropical organisms in response to warming winter temperatures
Bibliographic record
Abstract
Tropicalization is a term used to describe the transformation of temperate ecosystems by poleward-moving tropical organisms in response to warming temperatures. In North America, decreases in the frequency and intensity of extreme winter cold events are expected to allow the poleward range expansion of many cold-sensitive tropical organisms, sometimes at the expense of temperate organisms. Although ecologists have long noted the critical ecological role of winter cold temperature extremes in tropical-temperate transition zones, the ecological effects of extreme cold events have been understudied, and the influence of warming winter temperatures has too often been left out of climate change vulnerability assessments. Here, we examine the influence of extreme cold events on the northward range limits of a diverse group of tropical organisms, including terrestrial plants, coastal wetland plants, coastal fishes, sea turtles, terrestrial reptiles, amphibians, manatees, and insects. For these organisms, extreme cold events can lead to major physiological damage or landscape-scale mass mortality. Conversely, the absence of extreme cold events can foster population growth, range expansion, and ecological regime shifts. We discuss the effects of warming winters on species and ecosystems in tropical-temperate transition zones. In the 21st century, climate change-induced decreases in the frequency and intensity of extreme cold events are expected to facilitate the poleward range expansion of many tropical species. Our review highlights critical knowledge gaps for advancing understanding of the ecological implications of the tropicalization of temperate ecosystems in North America.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".