Short- and long-term movement patterns in the freshwater whipray (Himantura dalyensis) determined by the signal processing of passive acoustic telemetry data

2012 ◽  
Vol 63 (4) ◽  
pp. 341 ◽  
Author(s):  
Hamish A. Campbell ◽  
Matthew Hewitt ◽  
Matthew E. Watts ◽  
Stirling Peverell ◽  
Craig E. Franklin

Patterns of movement in aquatic animals reflect ecologically important behaviours. Cyclical changes in the abiotic environment influence these movements, but when multiple processes occur simultaneously, identifying which is responsible for the observed movement can be complex. Here we used acoustic telemetry and signal processing to define the abiotic processes responsible for movement patterns in freshwater whiprays (Himantura dalyensis). Acoustic transmitters were implanted into the whiprays and their movements detected over 12 months by an array of passive acoustic receivers, deployed throughout 64 km of the Wenlock River, Qld, Australia. The time of an individual’s arrival and departure from each receiver detection field was used to estimate whipray location continuously throughout the study. This created a linear-movement-waveform for each whipray and signal processing revealed periodic components within the waveform. Correlation of movement periodograms with those from abiotic processes categorically illustrated that the diel cycle dominated the pattern of whipray movement during the wet season, whereas tidal and lunar cycles dominated during the dry season. The study methodology represents a valuable tool for objectively defining the relationship between abiotic processes and the movement patterns of free-ranging aquatic animals and is particularly expedient when periods of no detection exist within the animal location data.

2020 ◽  
Author(s):  
Michael J. Williamson ◽  
Emma J Tebbs ◽  
Terrence P Dawson ◽  
David J Curnick ◽  
Francesco Ferretti ◽  
...  

Abstract Background There are now a wide array of field and laboratory techniques available for gaining insight into the movement and behaviour of sharks. Although acoustic telemetry may lack the fine-scale resolution of some satellite technologies, the low cost and longer battery life make it a powerful tool for investigating elasmobranch behaviour. Here, we develop a novel approach to analysing acoustic telemetry data, using detection gaps to infer movement patterns to and from monitored reef habitats, to investigate spatial and temporal segregation between two sympatric shark species in a large remote MPA. Methods A total of 102 grey reef sharks (Carcharhinus amblyrhynchos) and 76 silvertip sharks (Carcharhinus albimarginatus) were fitted with long-term acoustic transmitters and tracked inside a large acoustic array of reef-based receivers in the British Indian Ocean Territory MPA, between 2014 and 2018. From the resulting dataset (768,081 detections), movements between receivers and recursive loops to the same receiver were identified. Using the durations of inter-receiver movements (i.e. detection gaps), individual behaviours were classified into ‘restricted’ or potential wider ‘out of range’ movements. Drivers of these movements were identified using network analysis, GLMMs and multi-model inference starting from an a priori set of explanatory variables. Results In general, silvertip sharks were more likely to undertake ‘out of range’ movements than grey reef sharks. ‘Out of range’ movements were more common at night compared to during the day, and during the wet season compared to the dry season. In addition, the difference in ‘out of range’ movements between the two species increased at night. These results suggest spatial and temporal segregation of movements between the two species. Conclusions We present a novel analysis of detection gaps from acoustic telemetry data to infer differential movement patterns and describe how species organise in space and time. Furthermore, this approach shows that acoustic telemetry gap analysis can be used for comparative studies, or combined, with other research techniques to better understand the functional role of sharks in reef ecosystems, moving towards more informed strategies for the conservation and management of the marine environment.


2022 ◽  
Vol 8 ◽  
Author(s):  
Chantel Elston ◽  
Paul D. Cowley ◽  
Rainer G. von Brandis ◽  
James Lea

Abiotic factors often have a large influence on the habitat use of animals in shallow marine environments. Specifically, tides may alter the physical and biological characteristics of an ecosystem while changes in temperature can cause ectothermic species to behaviorally thermoregulate. Understanding the contextual and relative influences of these abiotic factors is important in prioritizing management plans, particularly for vulnerable faunal groups like stingrays. Passive acoustic telemetry was used to track the movements of 60 stingrays at a remote and environmentally heterogeneous atoll in Seychelles. This was to determine if habitat use varied over daily, diel and tidal cycles and to investigate the environmental drivers behind these potential temporal patterns. Individuals were detected in the atoll year-round, but the extent of their movement and use of multiple habitats increased in the warmer NW-monsoon season. Habitat use varied over the diel cycle, but was inconsistent between individuals. Temperature was also found to influence stingray movements, with individuals preferring the deeper and more thermally stable lagoon habitat when extreme (hot or cold) temperature events were observed on the flats. Habitat use also varied over the tidal cycle with stingrays spending a higher proportion of time in the lagoon during the lowest tides, when movement on the flats were constrained due to shallow waters. The interplay of tides and temperature, and how these varied across diel and daily scales, dynamically influenced stingray habitat use consistently between three species in an offshore atoll.


2007 ◽  
Vol 3 ◽  
pp. 117693510700300 ◽  
Author(s):  
Hyunjin Shin ◽  
Miray Mutlu ◽  
John M. Koomen ◽  
Mia K. Markey

Noise in mass spectrometry can interfere with identification of the biochemical substances in the sample. For example, the electric motors and circuits inside the mass spectrometer or in nearby equipment generate random noise that may distort the true shape of mass spectra. This paper presents a stochastic signal processing approach to analyzing noise from electrical noise sources (i.e., noise from instrumentation) in MALDI TOF mass spectrometry. Noise from instrumentation was hypothesized to be a mixture of thermal noise, 1/f noise, and electric or magnetic interference in the instrument. Parametric power spectral density estimation was conducted to derive the power distribution of noise from instrumentation with respect to frequencies. As expected, the experimental results show that noise from instrumentation contains 1/f noise and prominent periodic components in addition to thermal noise. These periodic components imply that the mass spectrometers used in this study may not be completely shielded from the internal or external electrical noise sources. However, according to a simulation study of human plasma mass spectra, noise from instrumentation does not seem to affect mass spectra significantly. In conclusion, analysis of noise from instrumentation using stochastic signal processing here provides an intuitive perspective on how to quantify noise in mass spectrometry through spectral modeling.


2019 ◽  
Vol 103 (1) ◽  
pp. 13-29 ◽  
Author(s):  
Sarah L. Becker ◽  
John T. Finn ◽  
Ashleigh J. Novak ◽  
Andy J. Danylchuk ◽  
Clayton G. Pollock ◽  
...  

2017 ◽  
Vol 34 (1) ◽  
pp. 207-223 ◽  
Author(s):  
Dorian Cazau ◽  
Julien Bonnel ◽  
Joffrey Jouma’a ◽  
Yves le Bras ◽  
Christophe Guinet

AbstractThe underwater ambient sound field contains quantifiable information about the physical and biological marine environment. The development of operational systems for monitoring in an autonomous way the underwater acoustic signal is necessary for many applications, such as meteorology and biodiversity protection. This paper develops a proof-of-concept study on performing marine soundscape analysis from acoustic passive recordings of free-ranging biologged southern elephant seals (SES). A multivariate multiple linear regression (MMLR) framework is used to predict the measured ambient noise, modeled as a multivariate acoustic response, from SES (depth, speed, and acceleration) and environmental (wind) variables. Results show that the acoustic contributions of SES variables affect mainly low-frequency sound pressure levels (SPLs), while frequency bands above 3 kHz are less corrupted by SES displacement and allow a good measure of the Indian Ocean soundscape. Also, preliminary results toward the development of a mobile embedded weather sensor are presented. In particular, wind speed estimation can be performed from the passive acoustic recordings with an accuracy of 2 m s−1, using a rather simple multiple linear model.


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