Stacked species distribution models and macroecological models provide congruent projections of avian species richness under climate change
Bibliographic record
Abstract
Abstract Aim Using survey data for North American birds, we assess how well historical patterns of species richness are explained by stacked species distribution models and macroecological models. We then describe the degree to which projections of future species richness differ, employing both modelling approaches across multiple emissions scenarios. Location USA and Canada. Methods We use Audubon Christmas Bird Count and North American Breeding Bird Survey data to estimate current and future species richness of birds using two distinct approaches. In the first, we model richness by stacking predictions from individual species distribution models. In the second, we model richness directly, ignoring the contributions of specific taxa to richness estimates. Results The two modelling approaches show similar accuracies when validated with historical observations, particularly winter observations, and result in similar patterns of richness when projected onto current and future climate spaces. Patterns of projected change in species richness differed markedly between winter and summer seasons regardless of modelling approach. Our models suggest that bird species richness in winter will increase or remain stable across much of North America. In contrast, species richness in summer is projected to decrease over much of North America, except part of northern Canada, suggesting that climate may constrain many breeding bird species and communities in the future. Main conclusions Stacked species distribution models and macroecological models produce similar estimates of current and future species richness for each of two seasons despite being built on different concepts of community assembly. Our results suggest that, although the mechanisms that shape geographical variation in biodiversity remain uncertain, these limitations do not impede our ability to predict patterns of species richness at broad scales. Congruence of species richness projections across modelling approaches is encouraging for conservation planning efforts that focus on retaining biodiversity into the future.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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 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".