Tracking movements of decapod crustaceans: a review of a half-century of telemetry-based studies
Bibliographic record
Abstract
Decapod crustaceans are ecologically and economically important invertebrates but are vulnerable to anthropogenic pressures and climate change. Understanding their spatial ecology is essential for their management and conservation, with telemetry emerging as a useful tool to quantify space-use and movements. Here, we synthesized the use of telemetry to study decapods among articles published from 1971 to 2019 (n = 102 studies), by taxonomic group of the study species, study location, objectives, number of animals tagged and their tag recovery rate, types (and trends) of telemetry used, and IUCN conservation status. These studies revealed insight into the behaviours and roles of decapods across habitats and geographic regions. The most common study species were crayfish and lobsters (41%, Astacidea), and these studies also had the highest number of individuals tagged per study (mean = 149 individuals). Most studies (86%) were conducted in the northern hemisphere. Acoustic tags were the most commonly used equipment (66% of studies) and were first employed in 1971, followed by radio-telemetry (mid-1990s), passive integrated transponders (mid-2000s), and data storage tags (late 2000s). Almost half (48%) of studies focused on species that had a conservation status of Least Concern, perhaps reflecting an applied science focus on animals of commercial interest rather than conservation importance. The positive allometric relationship between body length and movement rate (exponent = 0.86) demonstrates the type of broader ecological insight that combining these studies can provide. Tracking decapod movements will likely become increasingly important for managing fisheries, protecting sensitive species, and understanding invasion biology.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".