Genomic connectivity and adaptation signals of the freshwater sponge <i>Ephydatia muelleri</i> across its distribution
Bibliographic record
Abstract
1. Abstract Freshwater sponges fulfill critical ecological functions, including maintaining water quality, regulating nutrient dynamics, offering habitats for diverse taxa, and serving as a vital food source for various species. However, their patterns of dispersal and genetic connectivity remain inadequately understood, posing significant challenges to effective conservation assessments. We examined genetic connectivity and genetic adaptation to local environmental conditions in Ephydatia muelleri across its geographic range using ddRADseq-derived SNPs from 106 individuals collected from 11 localities spanning North America, Europe, and Asia. Analysis of 3,182 neutral SNPs revealed low connectivity and strong genetic structure among regions within two main genetic clusters of North America and Eurasia, while 115 SNPs identified to be under selection showed considerable evidence for differentiated, polygenic adaptation to light and temperature conditions across sampled locations, as well as selection on gene regulatory processes. These findings align with the “monopolization hypothesis”, suggesting that historical climatic and geological conditions of the Last Glacial Maximum, including habitat expansion, contraction, and natural barriers, have contributed more to the current genetic structure of E. muelleri populations than contemporary gene flow, which is restricted by monopolistic habitat colonization by this species. Our results provide novel support for ecological theory on dispersal in aquatic invertebrates, as well as insights into the plasticity of E. muelleri in the face of varying environmental conditions that are fundamentally important for freshwater ecosystem conservation.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".