The Ancient Lakes of Indonesia: Towards Integrated Research on Speciation
Bibliographic record
Abstract
Ancient lakes have provided considerable insights into the drivers of speciation and adaptive radiation in aquatic organisms. Most studies of species-flocks, however, focus only on a single group of organisms, and few have attempted to integrate geological, limnological, ecological, and genetic drivers of speciation on multiple species-flocks at various trophic levels. As such, there is a need for a comprehensive model system for research on speciation in aquatic environments where multiple radiations are investigated at various levels of biological organization (e.g., individual, population, and ecosystem) and placed in light of geographical and geological setting. The ancient Malili Lakes of Sulawesi, Indonesia, are ideal candidates for such a model, and represent the only hydrologically connected ancient lakes in the world. These lakes are characterized by ultra-oligotrophy and unique physicochemical conditions that govern the composition and production of planktonic communities. At higher trophic levels, there are three recurring trends: (1) low taxonomic richness and simple community structures, (2) adaptive radiations with trophic specialization, and (3) remarkably high endemism with evolutionary innovations throughout the lakes and species-flocks. Furthermore, the restricted geographic distributions of species-flocks within the Malili Lakes indicate that each lake constitutes a unique environment, and dispersal among lakes is limited, despite close contemporary connectivity. These observations suggest that ecological and evolutionary processes are regulated from the bottom up, and speciation is primarily facilitated by interspecific and intraspecific competition for limited resources. The Malili Lakes represent an outstanding natural model for integrative research into speciation as they offer the opportunity to explore the roles of geography, dispersal, and selection in the radiation of aquatic organisms.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".