Lake regionalization and diatom metacommunity structuring in tropical South America
Bibliographic record
Abstract
Lakes and their topological distribution across Earth's surface impose ecological and evolutionary constraints on aquatic metacommunities. In this study, we group similar lake ecosystems as metacommunity units influencing diatom community structure. We assembled a database of 195 lakes from the tropical Andes and adjacent lowlands (8°N-30°S and 58-79°W) with associated environmental predictors to examine diatom metacommunity patterns at two different levels: taxon and functional (deconstructed species matrix by ecological guilds). We also derived spatial variables that inherently assessed the relative role of dispersal. Using complementary multivariate statistical techniques (principal component analysis, cluster analysis, nonmetric multidimensional scaling, Procrustes, variance partitioning), we examined diatom-environment relationships among different lake habitats (sediment surface, periphyton, and plankton) and partitioned community variation to evaluate the influence of niche- and dispersal-based assembly processes in diatom metacommunity structure across lake clusters. The results showed a significant association between geographic clusters of lakes based on gradients of climate and landscape configuration and diatom assemblages. Six lake clusters distributed along a latitudinal gradient were identified as functional metacommunity units for diatom communities. Variance partitioning revealed that dispersal mechanisms were a major contributor to diatom metacommunity structure, but in a highly context-dependent fashion across lake clusters. In the Andean Altiplano and adjacent lowlands of Bolivia, diatom metacommunities are niche assembled but constrained by either dispersal limitation or mass effects, resulting from area, environmental heterogeneity, and ecological guild relationships. Topographic heterogeneity played an important role in structuring planktic diatom metacommunities. We emphasize the value of a guild-based metacommunity model linked to dispersal for elucidating mechanisms underlying latitudinal gradients in distribution. Our findings reveal the importance of shifts in ecological drivers across climatic and physiographically distinct lake clusters, providing a basis for comparison of broad-scale community gradients in lake-rich regions elsewhere. This may help guide future research to explore evolutionary constraints on the rich Neotropical benthic diatom species pool.
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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 | 0.000 |
| 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) | 0.000 | 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".