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Historical baleen plates indicate that once abundant Antarctic blue and fin whales demonstrated distinct migratory and foraging strategies
<p>Southern hemisphere blue (<em>Balaenoptera musculus intermedia</em>) and fin (<em>Balaenoptera physalus</em>) whales are the largest predators in the Southern Ocean, with similarities in morphology and distribution. Yet, understanding of their life history and foraging is limited due to current low abundances and limited ecological data. To address these gaps, historic Antarctic blue (n = 5) and fin (n = 5) whale baleen plates, collected in 1947–1948 and recently rediscovered in the Smithsonian National Museum of Natural History, were analyzed for bulk (δ<sup>13</sup>C and δ<sup>15</sup>N) stable isotopes. Regular oscillations in isotopic ratios, interpreted as annual cycles, revealed that baleen plates contain approximately six years (14.35 ± 1.20 cm yr<sup>–1</sup>) of life history data in blue whales and four years (16.52 ± 1.86 cm yr<sup>–1</sup>) in fin whales. Isotopic results suggest that: 1) in the 1940s, blue and fin whales fed at the same trophic level but in slightly different habitats, 2) fin whales appear to have had more regular annual migrations, and 3) fin whales may have migrated to ecologically distinct sub-Antarctic waters annually while some blue whales may have resided year-round in the Southern Ocean. These results reveal differences in ecological niche and life history strategies between Antarctic blue and fin whales during a period when their populations were more abundant than today, and before major human-driven climatic changes occurred in the Southern Ocean.</p>
Data and Code: Spatiotemporal Variability of Fin Whale and Blue Whale Calls Detected by Land Seismometers in the Lower St. Lawrence Seaway
<h3>Code</h3> <p><strong>MATLABWhaleDetectionCodeNWA.zip</strong></p> <p>The code used in the manuscript Spatiotemporal Variability of Fin Whale and Blue Whale Calls Detected by Land Seismometers in the Lower St. Lawrence Seaway<em> </em>(Goblot et al., in review)<em> </em>to detect whale calls in seismic waveforms was written by Alexandre Plourde and uploaded here with permission. This .zip file contains 3 folders, ‘Numerical Methods’, ‘Signal Processing’ and ‘Whale Subroutines’, as well as 3 main scripts (x2 for fin and blue whales). </p> <ul> <li>Pre-processing: <ul> <li>Convert .mseed to SAC files and rename with the format: YYYY.MM.DD.NETWORK.STATION..CHANNEL.SAC. Each SAC file must then be placed in a folder named with the format YYYYMMDD, referred to as events (evs) in the code. Each of these folders must then be placed into a single folder known as the events directory (drE) in the code.</li> </ul> </li> </ul> <ul> <li>Processing: Fin whales <ul> <li>Run ‘RecordWhaleNoiseLSZ.m’ for fin whales. This reads through daily SAC files, and computes fin whale power ratio every 120 s. The folder ‘FinWhalePower’ (drP) should now be created. These contain text files with the power ratios (W) for every window at each station.</li> <li>Run ‘createFinWhaleDectectionList.m' to check which 120s time windows have W > threshold (3.0 in our case). These time windows are stored in the matrix FWD.</li> <li>Run 'RecordFinWhaleCallsLSZ.m' to identify individual whale calls within each of the 120s time segments in the FWD matrix. The labelled call times are stored in the matrix FWC.</li> </ul> </li> </ul> <ul> <li>Processing: Blue whales <ul> <li>Run ‘RecordBlueWhalesLSZ.m’ for fin whales. This reads through daily SAC files, and computes fin whale power ratio every 120 s. The folder ‘BlueWhalePower’ (drP) should now be created. These contain text files with the power ratios (W) for every window at each station.</li> <li>Run ‘createBlueWhaleDectectionList.m' to check which 720s time windows have W > threshold (1.5 in our case). These time windows are stored in the matrix BWD.</li> <li>Run 'RecordFinWhaleCallsLSZ.m' to identify individual whale calls within each of the 720s time segments in the BWD matrix. The labelled call times are stored in the matrix BWC.</li> </ul> </li> </ul> <h3>Data</h3> <p>The whale detection code was applied to seismic waveform data downloaded through the EarthScope Consortium Web Services (<a href="https://service.iris.edu/" target="_blank" rel="noopener">https://service.iris.edu/</a>), including the following seismic network: CN (Natural Resources Canada, 1975). All whale calls were detected using the characteristic reccurence interval method (MATLABWhaleDetectionCodeNWA.zip).</p> <p><strong>Table S2</strong></p> <p><strong>WhaleDetectionsFeb2020Jan2022LSZ.mat</strong></p> <ul> <li>This dataset contains the center time of fin whale and blue whale detections and calls, from land 6 seismometers (CNQ, ICQ, SMQ, SNFQ, PMAQ, RISQ) in the Lower St-Lawrence Seaway between February 2020 and January 2022. <ul> <li>FWD_ <ul> <li>Column 1: list of fin whale detections (2 minute time window with presence)</li> <li>Column 2: corresponding station label</li> </ul> </li> <li>BWD_ <ul> <li>Column 1: list of blue whale detections (12 minute time window with presence)</li> <li>Column 2: corresponding station label</li> </ul> </li> <li>FWC_ <ul> <li>Column 1: list of individual ~1s fin whale calls</li> <li>Column 2: corresponding station label</li> </ul> </li> <li>BWC_ <ul> <li>Column 1: list of individual ~8s blue whale calls</li> <li>Column 2: corresponding station label</li> </ul> </li> <li>stadir: list of stations and labels (1-6)</li> </ul> </li> </ul> <p><strong>Table S3</strong></p> <p>a)<strong> MonthlyBlueWhaleDetectionsOct2015Jan2022.csv</strong> and b) <strong>MonthlyFinWhaleDetectionsOct2015Jan2022.csv</strong></p> <ul> <li> <div> <div> <div> <p>Number of monthly a) fin whale detections and b) blue whale detections from October 2015 to January 2022. Empty cells indicate periods when stations were not operating. Quiet day detections are included.</p> <p>Note the Oct 2015-Feb 2020 catalogue is from Plourde and Nedimović (2022) and includes up to 14 stations throughout this period from the following seismic networks: CN (Natural Resources Canada, 1975) and C8 (Natural Resources Canada, 2002). The Feb 2020-Jan 2022 catalogue is from Goblot et al. (in review) and includes the same stations from Table S1.</p> </div> </div> </div> </li> </ul> <h3>Additional</h3> <p><strong>Movie S1</strong></p> <p><strong>LSLSWhales.mp4</strong></p> <ul> <li>This movie contains an audiovisual representation of a series of fin whale calls and blue whale calls detected by 2 land seismometers in the Lower St-Lawrence Seaway. The fin whale detection was recorded by land seismometer CNQ (Côte-Nord) on Dec 12 2021 from 18:19:40 to 18:21:40. The blue whale detection was recorded by land seismometer SNFQ (Sainte-Félicité) on Aug 22 2021 from 05:36:00 to 05:48:00.</li> <li>The MATLAB soundsc(x) function was applied to seismic waveform data with fin whale and a blue whale calls. The signal with the fin whale detection is bandpassed from 18-21 Hz and the blue whale signal is bandpassed from 16-18 Hz. These signals were sped up 1000x in order to make them audible.</li> <li>The audio file was then uploaded to veed.io to produce a frequency response visualization of the whale calls.</li> <li>More audiovisuals can be viewed <a href="https://seismicsoundscapes.myportfolio.com/" target="_blank" rel="noopener">here</a>.</li> </ul>
Figure 2 in Variability in blue whale acoustic behavior off southern California
Figure 2. The percent of singular A (orange), singular B (blue), and D (green) call detections, and single (purple) and repetitive (maroon) AB phrase detections that occurred out of the total number of monthly detections at each of the four sites. Monthly detection totals are listed at the top of each bar. Periods shaded in gray indicate times when there was no data at that site.
Figure 3 in Variability in blue whale acoustic behavior off southern California
Figure 3. Residual plots of monthly variability for singular A (diamonds), singular B (squares), and D (circles) call detections (left panels), and single (upright triangles) and repetitive (downward triangles) AB phrase detections (right panels).
Figure 4 in Variability in blue whale acoustic behavior off southern California
Figure 4. Proportion of song consisting of each type per month at the inshore and offshore sites. Only months that contained identifiable song are included. No song was identified at the offshore sites in December 2009. Months when no data were available are marked in dark gray (Table 1).
Figure 1 in Variability in blue whale acoustic behavior off southern California
Figure 1. Percent of all song bouts recorded at the inshore and offshore sites comprised of the two blue whale phrase types between September 2009 and August 2010.
Figure 8 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 8. Results for the long-term approach to future status. Equilibrium abundance relative to carrying capacity is shown for Sobs ¼ 10 and a range of multipliers of current levels of 2013 vessels. The model was projected forward 100 yr for each posterior sample under a constant multiplier (x-axis value). Model trajectories are shown as filled gray areas representing the 0.95, 0.75, 0.5, 0.25, and 0.05 posterior percentiles. The probability that the population is depleted (i.e., below 60% of K) is shown as a curved line. The solid vertical line denotes the median ratio of vessels in 2050 to 2013, i.e., the multiplier in 2050 estimated by our vessel model.
Figure 7 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 7. Results of the short-term approach to future status. Future ship strikes, abundances, and abundances relative to carrying capacity for Sobs ¼ 10 are shown for three mitiga2013 tion cases (columns). Model trajectories are shown as filled gray areas representing the 0.95, 0.75, 0.5, 0.25, and 0.05 posterior percentiles. "Status quo" means no additional mitigation, "mitigation" refers to halving the ship strikes after 2013, and "none" is a complete elimination of future ship strikes. The horizontal lines at 0.6 denote the level below which the population is considered depleted.
Figure 4 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 4. Posterior densities for the abundance relative to carrying capacity in 2013 for Sobs ¼ 10 (top) and Sobs ¼ 35 (bottom) and the two priors for r. The vertical line at 0.6 2013 2013 denotes the level below which the population is considered depleted.
Figure 6 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 6. Absolute abundance, the abundance estimates and anthropogenic mortalities for Sobs ¼ 10 and the two priors for r. The rectangles at the bottom denote total estimated mor2013 talities (median catches + median strikes) for each year. The five abundance estimates (points) are shown with their 95% confidence intervals (bars). Model trajectories are shown as filled gray areas representing the 0.95, 0.75, 0.5, 0.25, and 0.05 posterior percentiles.
Figure 2 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 2. Results of the vessel model. The points are data from worldwide statistics for vessels over 100 gross tons from Lloyd's of London, as used in Laist et al. (2001). Model trajectories are shown as filled gray areas representing the 0.95, 0.75, 0.5, 0.25, and 0.05 posterior percentiles.
Figure 1 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 1. Prior and marginal posterior probability distributions for the parameters of the theta-logistic population dynamics model for Sobs ¼ 10 and both priors for r (columns).
Figure 3 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 3. Results of the ship strike model. Predicted ship strikes for the uninformative prior for r and observed ship strikes in 2013 as 10 or 35. Annual trajectories (panels A and B) are shown as filled gray areas representing the 0.95, 0.75, 0.5, 0.25, and 0.05 posterior percentiles. Panels C and D show the posterior distributions of strikes in 2013 (histogram) as well as the Poisson likelihood (line).
Figure 5 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 5. Trajectories for Abundance relative to carrying capacity for Sobs ¼ 10 and both 2013 priors for r. Model trajectories are shown as filled gray areas representing the 0.95, 0.75, 0.5, 0.25, and 0.05 posterior percentiles. The horizontal lines at 0.6 denote the level below which the population is considered depleted.
Supporting Data for: Ocean-wide conservation genomics of blue whales suggest new Northern Hemisphere subspecies
Open the record for dataset details and reuse information.
Historical baleen plates indicate that once abundant Antarctic blue and fin whales demonstrated distinct migratory and foraging strategies
Open the record for dataset details and reuse information.
Western Indian Ocean blue whale dataset
<p>The analysis of the large volumes of data resulting from continuous and long-term monitoring of blue whales unmistakably benefits from the automated detection of target signals. Automatic detection methods must be reliable and robust to gather statistically relevant elements and contribute to answering blue whale ecological unknowns. Therefore, systematic performance analysis of detection and classification methods developed for the passive context is crucial.</p> <p>These datasets were annotated to support my Ph.D work <em>Detection and classification in passive acoustic contexts: Application to blue whale low-frequency signals</em>. They are based on recordings from Ocean Bottom Seismometers (RR41 and RR48) deployed during the <a href="http://www.rhum-rum.net/en/">RHUM-RUM</a> experiment, in the western Indian Ocean. All RHUM-RUM recordings are freely available from the <a href="http://seismology.resif.fr/">RESIF</a> data center, under the code name YV (<a href="https://doi.org/10.15778/RESIF.YV2011">https://doi.org/10.15778/RESIF.YV2011</a>). Find more information on RHUM-RUM on <a href="https://www.researchgate.net/project/RHUM-RUM">Researchgate</a>.</p> <p>All blue whales calls within the provided acoustic recordings were manually annotated using the software <a href="http://ravensoundsoftware.com">Raven Pro 1.5</a>. The analyst selected boxes describing the begin and end times and, minimum and maximum frequencies of each call (Dataset 1) or each unit (Dataset 2).</p> <p><br> <strong>Dataset 1 - Antarctic blue whale calls</strong><br> Contains:</p> <ul> <li>Sound file <em>RR48_2013_D151.wav</em> where Antarctic blue whale calls are recorded continuously for more than 21 hours (from 01:20 to 22:40); </li> <li>Annotation file <em>Annotation_RR48_2013_D151.txt</em> with the box information of 845 Antarctic blue whale calls (+ some other interfering events); and,</li> <li>Call time of arrivals estimated from events detected by the stochastic matched filter and corresponding whale location in the file <em>Localisation_RR48_2013_D151.txt</em>.</li> </ul> <p>This dataset supports research presented in:<br> L. Bouffaut, R. Dréo, V. Labat, A. Boudraa and G. Barruol “Passive stochastic matched filter for antarctic blue whale call detection,” in J. Acoust. Soc. Am, vol. 144, no. 2, pp. 955-965 (2018). DOI: <a href="https://doi.org/10.1121/1.5050520">10.1121/1.5050520</a></p> <p>Additional information:<br> - Detailed information on this dataset on my <a href="https://leabouffaut.home.blog/2020/01/22/antarctic-blue-whale-dataset/">personal website</a> <br> - Stochastic matched filter package on <a href="https://leabouffaut.github.io/SMF_package/ ">Github</a> DOI: <a href="https://doi.org/10.5281/zenodo.3613787">10.5281/zenodo.3613787</a><br> - Localization method research paper on <a href="https://www.researchgate.net/publication/322570729_Antarctic_Blue_Whale_localization_with_Ocean_Bottom_Seismometers_in_Southern_Indian_Ocean">Researchgate</a> | <a href="https://doi.org/10.1016/j.dsr2.2018.04.005">Deep sea research paper</a> </p> <p><strong>Dataset 2 - Blue whale call units</strong><br> Contains:</p> <ul> <li>Sound files <em>RR41_2013_D132.wav</em>, <em>RR41_2013_D135.wav</em>, and <em>RR48_2013_D138.wav</em>,</li> <li>Corresponding annotation file <em>Annotation.txt</em> with box information of various blue whale call units from Antarctic blue whales, Madagascar pygmy blue whales and P-calls (+ some other interfering events).</li> </ul> <p>In total this dataset contains more than 4000 annotated units.</p> <p>This dataset supports research presented in:<br> L. Bouffaut, S.Madhusudhana, V. Labat, A. Boudraa and H. Klinck, “Automated blue whale song transcription across variable acoustic contexts,” in IEEE OCEANS’19 Marseille, student poster competition, France, pp. 2-7 (2019) DOI: <a href="https://doi.org/10.1109/OCEANSE.2019.8867471">10.1109/OCEANSE.2019.8867471</a><br> who received the First Prize and Norman Miller Award and was therefore also published in the IEEE OES Beacon Newsletter (September 2019 vol. 8, no. 3, pp. 44-49)</p> <p>Detailed information on this dataset on my <a href="https://leabouffaut.home.blog/2020/01/22/blue-whale-call-units-dataset/">personal website</a>.</p>
Blue Whale Skeleton
a simple blue whale skeleton. made with Grease Pencil in Blender. no details. Source: Objaverse 1.0 / Sketchfab
Data and Code: Detecting Blue Whale Calls in the Northeast Pacific Using Seismic Systems (Undergraduate Thesis)
<p><strong>SeismoData.ipynb</strong>: This Jupyter notebook is adapted from seismosocialdistancing.ipynb created by Thomas Lecocq, Fred Massin and Claudio Satriano. SeismoData.ipynb was used to retrieve seismic waveform data from the Incorporated Research Institutions for Seismology (IRIS) Data Management Center (DMC) (https://ds.iris.edu/ds/ nodes/dmc/) and convert files from miniSEED to SAC format. It was also used to preview waveform and spectrogram plots.</p> <p><strong>BlueWhaleDetectionResults_J53A_Dec132011.mat</strong>: This .mat file summarizes whale detection results from OBS J53A on December 13th 2011. The objective was to calibrate a detection algoritm created for Northwest Atlantic blue whale A calls by Plourde and Nedimovic (2022), so that it can target Northeast Pacific blue whale B calls using seismometers off Washington and California. Three tests were performed to find optimal parameters. <em>BlueWhaleDetections_J53A_Test1</em><strong> </strong>are the detection results of a control that uses Northwest Atlantic blue whale parameters (16.25-18Hz frequency and 68-78s period ranges). <em>BlueWhaleDetections_J53A_Test2</em> <strong> </strong>are the detection results using Northeast Pacific blue whale B call parameters (14-17Hz frequency and 45-55s period ranges). <em>BlueWhaleDetections_J53A_Test2 </em>are the detection results using Northeast Pacific blue whale B call and C call parameters (10.5-12Hz and 14-17Hz frequency and 45-55s period ranges). <em>BlueWhaleDetections_J53A_SCC</em> are the 95% probability detection results from the Wilcock and Hilmo (2021) blue whale catalogue created using spectrogram cross-correlation. </p> <p><strong>NEPBlueWhaleMATLABcodes.zip</strong>: Contains scripts to run the recurrence interval power ratio method created by Plourde and Nedimovic (2022), adjusted to detect Northeast Pacific blue whale B calls and plot waveforms/spectrograms. First run <em>DetectBlueWhales.m </em>to calculate the recurrence power ratio every 12 minutes, then run C<em>reateBlueWhaleDetectionList.m </em>to classify detections with high power ratios and likely blue whale call detections.</p> <p><strong>BlueWhaleDetectionResults_CapeMendocino_Dec15to292014.mat</strong>: This .mat file summarizes the blue whale detection results from 2 OBS (FS02D and FS07D) and 1 land seismometer (CM09A) in close proximity, using Test 2 parameters. Note if there are less than 3 BWD in a given day, these are likely false detections.</p>
Data from: Circumpolar diversity and geographic differentiation of mtDNA in the critically endangered Antarctic blue whale (Balaenoptera musculus intermedia)
The Antarctic blue whale (Balaenoptera musculus intermedia) was hunted to near extinction between 1904 and 1972, declining from an estimated initial abundance of more than 250,000 to fewer than 400. Here, we describe mtDNA control region diversity and geographic differentiation in the surviving population of the Antarctic blue whale, using 218 biopsy samples collected under the auspices of the International Whaling Commission (IWC) during research cruises from 1990–2009. Microsatellite genotypes and mtDNA sequences identified 166 individuals among the 218 samples and documented movement of a small number of individuals, including a female that traveled at least 6,650 km or 131° longitude over four years. mtDNA sequences from the 166 individuals were aligned with published sequences from 17 additional individuals, resolving 52 unique haplotypes from a consensus length of 410 bp. From this minimum census, a rarefaction analysis predicted that only 72 haplotypes (95% CL, 64, 86) have survived in the contemporary population of Antarctic blue whales. However, haplotype diversity was relatively high (0.968±0.004), perhaps as a result of the longevity of blue whales and the relatively recent timing of the bottleneck. Despite the potential for circumpolar dispersal, we found significant differentiation in mtDNA diversity (FST = 0.032, p<0.005) and microsatellite alleles (FST = 0.005, p<0.05) among the six Antarctic Areas historically used by the IWC for management of blue whales.
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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