A 40-year evaluation of drivers of African rainforest change
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background Tropical forests are repositories of much of the world’s biodiversity and are critical for mitigation of climate change. Yet, the drivers of forest dynamics are poorly understood. This is in large part due to the lack of long-term data on forest change and changes in drivers. Methodology We quantify changes in tree abundance, diversity, and stand structure along transects first enumerated in 1978 and resampled 2019 in Kibale National Park, Uganda. We tested five predictions. First, based on the purported role of seed dispersal and herbivory and our quantification of changes in the abundance of frugivores and herbivores, we tested two predictions of how faunal change could have influenced forest composition. Second, based on an evaluation of life history strategies, we tested two predictions concerning how the forest could have changed following disturbance that happened prior to written history. Finally, based on a 50-year climate record, we evaluate the possible influence of climate change on forest dynamics. Results More trees were present on the assessed transects in 2019 (508) than in 1978 (436), species richness remained similar, but diversity declined as the number of dominant species increased. Rainfall increased by only 3 mm over the 50 years but this had not significant effect on forest changes measured here. Annual average monthly maximum temperature increased significantly by 1.05 °C over 50 years. The abundance of frugivorous and folivorous primates and elephants increased over the 50 years of monitoring. Neither the prediction that an increase in abundance of seed dispersing frugivores increases the abundance of their preferred fruiting tree species, nor that as an increase in folivore abundance causes a decline in their preferred species were supported. As predicted, light-demanding species decreased in abundance while shade-tolerant species increased as expected from Kibale being disturbed prior to historical records. Finally, while temperature increased over the 50 years, we found no means to predict a priori how individual species would respond. Conclusions Our study revealed subtle changes in the tree community over 40 years, sizable increases in primate numbers, a substantial increase in the elephant population and an increase in local temperature. Yet, a clear picture of what set of interactions impact the change in the tree community remains elusive. Our data on tree life-history strategies and frugivore/herbivore foraging preferences suggest that trees species are under opposing pressures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.034 | 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 it