Disentangling the latitudinal and altitudinal shifts in community composition induced by climate change: the case of riparian birds
Bibliographic record
Abstract
Aim. This study investigates whether, and how the composition of riparian bird communities has been affected by climate warming and habitat change. Although these two forces act separately, their respective contributions are rarely examined. Moreover, while the response of a given community may be a function of latitude and altitude, most studies have focused on these gradients separately. Riparian ecosystems are an opportunity to investigate community change along latitudinal and elevational gradients. Location. France, three major rivers (the Doubs, the Allier, the Loire) Taxon. Birds. Methods. Drawing upon bird community monitoring data over a period of 31 years (1982–2013, n = 1286 point counts), we assessed community adjustment to temperature increase with the Community Temperature Index (CTI), and the homogenisation pattern following habitat conversion with the Community Specialisation Index (CSI). We evaluated the spatial climatic debt accumulated by communities, and the interaction between CTI and CSI trends. Furthermore, we tested differences in trends for lowland and highland elevations. Results. Over the study period the temperature increased by 1.17°C, and the CTI by 0.12°C, which corresponds to a spatial climatic debt of 4.9 km yr-1. Lowland, but not highland communities adjusted to warming, but there was a decline in species abundance. CSI trends revealed biotic homogenisation in both lowland and highland communities. This finding was uncorrelated with the CTI increase, and is thought to be due to pressure from land use change on community composition. Main conclusions. Riparian breeding bird communities have been affected by a temperature increase and, potentially, habitat change. Highland communities are most vulnerable to climate warming. Both climate warming and habitat change appear to have rapidly affected the composition of local communities, with expectable concerns on their diversity and specificity in the long term.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".