Revistes Catalanes amb Accés Obert (RACO)

Ritmes al mar profund: efecte sobre l’avaluació de les comunitats i noves tecnologies d’estudi

Jacopo Aguzzi


In their behavioural, physiological and molecular functioning, animals follow temporal patterns collectively known as biological rhythms. Massive three-dimensional displacements of species occur at periodicities ranging from 12.4 h (tidal rhythms) and 24 h (day-night rhythms) to months (e.g. seasonal reproductive rhythms). This temporal adjustment of behavioural activity to geophysical cycles in light intensity, photoperiod length and hydrodynamism produces a strong and complex temporal variability in marine ecosystems, which complicates ecological studies focusing on populations and biodiversity assessments. Important constraints in sampling repeatability at statistically relevant frequencies limit the progress of marine ecology, especially in the increasingly anthropic-threatened but still largely unexplored deep sea (65% of the planet’s surface is below 1000 m depth). Within the framework of a novel seafloor video-cabled observatory technology that is progressively being installed in large oceanographic networks, it is now possible to explore and monitor ecosystems at sampling frequencies and over temporal durations never attained before. Fluctuations in video-counted individuals can be considered a proxy of populational behavioural rhythms in response to cycles of environmental parameters measured simultaneously through oceanographic, chemical and geologic sensors. Time-series analysis protocols can be implemented according to the following steps: i) periodogram analysis for the detection of significant periodicity; ii) waveform analysis for the measurement of rhythm phases (e.g. diurnal/nocturnal or monthly/seasonal peaks); and iii) integrated waveform analysis. In waveform analysis (step ii), data sets will be sectioned into segments of length equal to the periodicity of the geophysical cycle of reference (as assessed in step i). The values of all sub-sets will be averaged at corresponding timings to obtain a consensus curve (the waveform). The identification of a peak will be carried out to relate the significant increase in population activity to a particular moment in the fluctuation of the geophysical cycle. The integrated analysis of waveforms for all species (in step iii) and geophysical cycles will be carried out to evidence the temporal linkage among peaks, as an indication of a reliable cause-effect relationship.

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