Predicting range shifts of African apes under global change scenarios
Bibliographic record
Abstract
ABSTRACT Aim Modelling African great ape distribution has until now focused on current or past conditions, whilst future scenarios remain scarcely explored. Using an ensemble forecasting approach, we predicted changes in taxon-specific distribution under future scenarios of climate, land-use and human population changes. Location Sub-Saharan Africa Methods We compiled occurrence data on African ape populations from the IUCN A.P.E.S. database and extracted relevant human-, climate- and habitat-related predictors representing current and future (2050) conditions to predict taxon-specific distribution under a best- and a worst-case scenario, using ensemble forecasting. Given the large effect on model predictions, we further tested algorithm sensitivity by considering default and non-default modelling options. The latter included interactions between predictors and polynomial terms in correlative algorithms. Results The future distributions of gorilla and bonobo populations are likely to be directly determined by climate-related variables. In contrast, future chimpanzee distribution is influenced mostly by anthropogenic variables. Both our modelling approaches produced similar model accuracy, although a slight difference in the magnitude of range change was found for Gorilla beringei beringei, G. gorilla diehli , and Pan troglodytes schweinfurthii . On average, a decline of 50% of the geographic range ( non-default ; or 55% default ) is expected under the best scenario if no dispersal occurs (57% non-default or 58% default in worst scenario). However, new areas of suitable habitat are predicted to become available for most taxa if dispersal occurs (81% or 103% best, 93% or 91% worst, non-default and default , respectively), except for G. b. beringei . Main Conclusions Despite the uncertainty in predicting the precise proportion of suitable habitat by 2050, both modelling approaches predict large range losses for all African apes. Thus, conservation planners urgently need to integrate land-use planning and simultaneously support conservation and climate change mitigation measures at all decision-making levels both in range countries and abroad.
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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 | 0.001 | 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".