Exploring seascape genetics and kinship in the reef sponge <i><scp>S</scp>tylissa carteri</i> in the <scp>R</scp>ed <scp>S</scp>ea
Bibliographic record
Abstract
A main goal of population geneticists is to study patterns of gene flow to gain a better understanding of the population structure in a given organism. To date most efforts have been focused on studying gene flow at either broad scales to identify barriers to gene flow and isolation by distance or at fine spatial scales in order to gain inferences regarding reproduction and local dispersal. Few studies have measured connectivity at multiple spatial scales and have utilized novel tools to test the influence of both environment and geography on shaping gene flow in an organism. Here a seascape genetics approach was used to gain insight regarding geographic and ecological barriers to gene flow of a common reef sponge, Stylissa carteri in the Red Sea. Furthermore, a small-scale (<1 km) analysis was also conducted to infer reproductive potential in this organism. At the broad scale, we found that sponge connectivity is not structured by geography alone, but rather, genetic isolation in the southern Red Sea correlates strongly with environmental heterogeneity. At the scale of a 50-m transect, spatial autocorrelation analyses and estimates of full-siblings revealed that there is no deviation from random mating. However, at slightly larger scales (100-200 m) encompassing multiple transects at a given site, a greater proportion of full-siblings was found within sites versus among sites in a given location suggesting that mating and/or dispersal are constrained to some extent at this spatial scale. This study adds to the growing body of literature suggesting that environmental and ecological variables play a major role in the genetic structure of marine invertebrate populations.
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.
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 | 0.002 | 0.002 |
| 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 | 0.001 |
| 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".