What Controls Connectivity? An Empirical, Multi-Species Approach
Bibliographic record
Abstract
The exchange of individuals among habitat patches (connectivity) has broad relevance for the conservation and management of marine metapopulations. Elemental fingerprinting-based research conducted over the past 12 years along the open coastline and bays of San Diego County in southern California evaluated connectivity patterns for seven species: one native and two invasive mussels, an oyster, a brachyuran crab, and two fishes. The studies spanned different years and seasons but overlapped considerably in space, allowing comparisons of dispersal patterns across species, and assessment of the relative importance of location, circulation, and intra-annual and inter-annual variability. We asked whether the species exhibited commonalities in directional transport, transport distances, sources and sinks, self-recruitment, and bay-ocean exchange. Linked connectivity-demographic analyses conducted for two species of mytilid mussels and two fishes allowed evaluation of the contributions of realized connectivity to metapopulation dynamics relative to other life-history attributes. Common trends across species include average along-shore dispersal distances of 15-35 km and seasonal changes in direction of dispersal that mirrored patterns of along-shore circulation. We observed greater isolation of back-bay populations, significant exchange from front bay to ocean, and high self-recruitment in locations on the northern, open coast, and in the southern bays. Connectivity was rarely the most influential driver of growth and persistence of metapopulations, but influenced the importance of other vital rates. Several locations served consistently as sources of larvae or as nurseries for multiple species, but there were few sites in common that were sinks. For the mussels, reproductive timing guided directional transport. These results imply that local management (e.g., habitat protection, opening of the mouths of lagoons, location of aquaculture farms) may be effective along this coastline. Regional, multi-species assessments of exchange of larvae should move us closer to ecosystem-based management.
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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 | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".