Avian seed dispersal may be insufficient for plants to track future temperature change on tropical mountains
Bibliographic record
Abstract
Abstract Aim Climate change causes shifts in species ranges globally. Terrestrial plant species often lag behind temperature shifts, and it is unclear to what extent animal‐dispersed plants can track climate change. Here, we estimate the ability of bird‐dispersed plant species to track future temperature change on a tropical mountain. Location Tropical elevational gradient (500–3500 m.a.s.l.) in the Manú biosphere reserve, Peru. Time period From 1960–1990 to 2061–2080. Taxa Fleshy‐fruited plants and avian frugivores. Methods Using simulations based on the functional traits of avian frugivores and fruiting plants, we quantified the number of long‐distance dispersal (LDD) events that woody plant species would require to track projected temperature shifts on a tropical mountain by the year 2070 under different greenhouse gas emission scenarios [representative concentration pathway (RCP) 2.6, 4.5 and 8.5]. We applied this approach to 343 bird‐dispersed woody plant species. Results Our simulations revealed that bird‐dispersed plants differed in their climate‐tracking ability, with large‐fruited and canopy plants exhibiting a higher climate‐tracking ability. Our simulations also suggested that even under scenarios of strong and intermediate mitigation of greenhouse gas emissions (RCP 2.6 and 4.5), sufficient upslope dispersal would require several LDD events by 2070, which is unlikely for the majority of woody plant species. Furthermore, the ability of plant species to track future changes in temperature increased in simulations with a low degree of trait matching between plants and birds, suggesting that plants in generalized seed‐dispersal systems might be more resilient to climate change. Main conclusion Our study illustrates how the functional traits of plants and animals can inform predictive models of species dispersal and range shifts under climate change and suggests that the biodiversity of tropical mountain ecosystems is highly vulnerable to future warming. The increasing availability of functional trait data for plants and animals globally will allow parameterization of similar models for many other seed‐dispersal systems.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".