African great apes indicate mammalian abundance across broad spatial scales
Bibliographic record
Abstract
Ongoing ecosystem change and biodiversity decline across the Afrotropics call for tools to monitor the state of African biodiversity or ecosystem elements (e.g., completeness and integrity) across extensive spatial and temporal scales. We assessed relationships in the co-occurrence patterns between great apes and other mammals, to evaluate if ape abundance serves as proxies of mammal diversity across broad spatial scales. We used camera trap footage recorded at 22 sites, each known to harbor a population of chimpanzees and/or gorillas, across 12 sub-Saharan African countries. From ~350,000 1-minute camera trap videos recorded between 2010 and 2016, we estimated mammalian community metrics [i.e., (species) richness, (Shannon) diversity, and body mass (hereafter simplified as “animal mass”)]—considering only medium and large-bodied species — and fitted Bayesian Regression Models to assess potential relationships between ape abundances and these metrics. We included site-level protection status, human footprint, and precipitation variance as control variables. We found that relationships between the abundance of great apes and the total abundance and body mass of non-ape mammals were largely positive. In contrast, relationships between ape abundance and mammal richness were less clear, except chimpanzee abundance as a predictor of mammalian richness inside protected areas and areas with high human impact. Relationships between ape abundance and mammal diversity were largely negative for both species, in that sites with higher ape abundances had mammalian communities with relatively uneven abundance distributions. Our findings suggest that gorillas and chimpanzees hold potential as indicators of specific elements of mammalian communities, especially population-level (abundance) and composition-related (body mass) characteristics. Monitoring ape populations may inform ecosystem management: declines in ape populations may serve as early warning signals and indicate a need for conservation interventions, as changes in ape abundance and community composition are likely to precede extirpation of other mammal species.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".