The use of new multiparametric observatory platforms for the remote monitoring and exploration of deep-sea ecosystems at day-night and seasonal temporal scales
Bibliographic record
Abstract
Traditional sampling technologies such as trawling but also novel ones as ROV surveying are oriented toward a high spatial coverage without repeating data collection at fixed seabed windows. The temporal repetition is often neglected so any reported difference in sampling among sites or studies may potentially be confounded with time-induced variations as a product of rhythmic population displacements within the continental margin seabed and water column 3D scenarios. Behaviour is an important life trait conditioning our perception of deep-sea biodiversity, being its rhythmic expression upon different diel (i.e. 24-h based day-night and tidal cycles) poorly known. In this context, technological step forward must be taken in order to observe community changes in deep-sea areas as a product of population behavioural patterns. Here, I studied how activity rhythms of benthic species within deep-sea communities modulate their composition, species abundances, richness, biodiversity and other life-history trait information in representative deep-sea environments through the use of multiparametric video-fixed cabled and non-cabled stations plus moving platforms. At the same time, I provided new methodological sampling hints on data collection protocols and analyses specifically tuned to the different characteristic of each observatory platform. I shed new light on the regulation that environmental cycles exert on animals' rhythmic behavior, revealing that the main environmental rulers affecting deep-sea benthic communities are still day-night indirect or more direct tidal-oriented cycles which act on endobenthic, benthopelagic, and nektobenthic migrations. Las tecnologías de muestreo tradicionales, como la pesca de arrastre, pero también las nuevas, como los trabajos con ROV, están orientadas hacia una elevada cobertura espacial sin necesariamente repetir la recopilación de datos en ventanas fijas de los fondos marinos. Esa repetición temporal es a menudo obviada por lo que cualquier diferencia en el muestreo entre sitios o estudios puede quedar enmascarada por las variaciones a escala temporal como resultado de los desplazamientos rítmicos de la población dentro del margen continental marino y el volumen tridimensional de columna de agua. El comportamiento en los animales es un rasgo importante que condiciona nuestra percepción de la diversidad biológica de los fondos marinos, siendo su expresión rítmica diaria (es decir, ciclos día-noche y mareales) mal conocida. En este contexto, hay una necesidad de avance tecnológico y metodológico que permita la observación de las variaciones en las comunidades del mar profundo en las zonas de aguas profundas como producto de los patrones de comportamiento poblacional. Aquí estudié cómo los ritmos comportamentales de las especies bentónicas y bentopelágicas modulan composición, abundancia de especies, riqueza, diversidad biológica y otra información del ciclo biológico de dichas especies y comunidades dentro de ecosistemas representativos del mar profundo mediante el uso de sistemas de cableado submarino multiparamétrico, plataformas submarinas no cableadas y plataformas submarinas móviles. Al mismo tiempo, aporté nuevas recomendaciones metodológicas sobre protocolos de recolección y análisis de datos específicamente ajustadas a las diferentes particularidades y necesidades de las susodichas tecnologías de observación submarina. Los resultados de este trabajo han ayudado a comprender mejor la regulación que los ciclos ambientales ejercen sobre el comportamiento rítmico de los animales, revelando que los principales factores ambientales que gobiernan las comunidades bentónicas de aguas profundas siguen siendo el ciclo día-noche de forma indirecta y el mareal de forma más directa que actúan modulando los desplazamientos endobentónicos, bentopelágicos y migraciones nektobentónicas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".