[MARMAM] Oligocene mysticetes from Australasia and the Early Miocene fossil gap

[Felix Marx]

Dear colleagues,


please find below the abstract and link to our recently published, open
access paper on a quantitative comparison of the Oligocene baleen whale
assemblages from Australasia, and a discussion of the global Early Miocene
gap in the mysticete fossil record.


Marx F G, Fitzgerald E M G, and Fordyce R E. 2019. Like phoenix from the
ashes: how modern baleen whales arose from a fossil ‘dark age’. Acta
Palaeontol Pol, 64: published online.


Link: https://www.app.pan.pl/article/item/app005752018.html

Abstract: The evolution of baleen whales (Mysticeti), the largest animals
on Earth, was punctuated by a pivotal turnover event. Following their
emergence around 36 million years (Ma), mysticetes diversified into a
disparate range of toothed and toothless species until 23 Ma, but then
nearly vanished from the global fossil record for the next five million
years. Following this early Miocene “dark age”, toothless mysticetes
spectacularly reappeared around 18–17 Ma, whereas toothed mysticetes had
gone entirely extinct. Here, we suggest that this turnover event reflects a
change in mysticete habitat occupancy. Using the well-sampled record of
Australasia as a case study, we show that Oligocene pre-“dark age”
mysticetes formed distinct coastal and offshore assemblages, dominated by
small (2–4 m), ecologically disparate toothed species, and larger (5–6 m)
toothless filter feeders, respectively. Environmental change around the
Oligocene–Miocene boundary led to the decline of the endemic coastal
assemblages, leaving nearshore deposits virtually devoid of mysticetes.
Filter feeders persisted offshore and subsequently re-invaded coastal
habitats during the mid-Miocene Climatic Optimum, thus establishing the
modern, cosmopolitan mysticete fauna.
Kind regards,

Felix Marx
_

*Felix G. Marx* PhD | FNRS Postdoctoral Fellow

*University of Liège, Belgium
*Royal Belgian Institute of Natural Sciences, Brussels, Belgium
*Monash University, Melbourne, Australia
*Museums Victoria, Melbourne, Australia

Address: Institut royal des Sciences naturelles de Belgique
D.O. Terre et Histoire de la Vie, Evolution de la Paléobiosphère
29 rue Vautier, 1000 Brussels, Belgium
Phone: +32 (0)488 897314


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[MARMAM] New article: Epizootic effect and aftermath in a pilot whale population

[Philippe Verborgh]

Good afternoon,
We apologise for cross posting and are pleased to share our new article: 
Verborgh, P., P. Gauffier, C. Brévart, J. Giménez, R. Esteban, M. Carbou, E. 
Debons, and R. de Stephanis. 2019. Epizootic effect and aftermath in a pilot 
whale population. Aquatic Conserv. Mar. Freshw. Ecosyst.:1–9. 
DOI:10.1002/aqc.3082
Abstract:1. Over the last three decades, emerging infectious diseases have 
resulted in large mortalities in wild populations.2. Different strains of 
Morbillivirus have infected cetaceans all over the world and caused at least 
seven epizootics since the 1980s, but few data exist on their effect at the 
population level.3. The demographic effect of a morbillivirus epizootic was 
studied on a well‐monitored resident population of long‐finned pilot whales in 
the Strait of Gibraltar.4. Results show decreases in population size and 
apparent survival rate, especially in males, as well as negative population 
growth rates during the epizootic and the following years.5. Although different 
anthropogenic and natural factors may have acted in conjunction, the epizootic 
was most likely the cause of this observed decline.6. This epizootic, and 
potential future ones, may put the population's future at even greater risk, 
and their habitat is threatened by increasing anthropogenic stress.
The article can be accessed freely in the following link: 
https://rdcu.be/bzBCPOr by request at my email: philippeverborgh(a)gmail.com
Thank you,Philippe Verborgh and co-authors

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[MARMAM] Course on stable isotope analysis

[Oliver Hooker]

Stable Isotope Mixing Models using SIBER, SIAR, MixSIAR (SIMM05)
https://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm05/
This course will be delivered by Dr Andrew Parnell and Dr Andrew Jackson
(authors of the SIBER, SIAR and MixSIAR packages) form the 10th - 14th June
2019 in Glasgow City Centre. Course overview: This course will cover the
concepts, technical background and use of stable isotope mixing models
(SIMMs) with a particular focus on running them in R and will suit anyone
using stable isotopes to study marine mammals. Recently SIMMs have become a
very popular tool for quantifying food webs and thus the diet of predators
and prey in an ecosystem. Starting with only basic understanding of
statistical models, we will cover the do’s and don’ts of using SIMMs with a
particular focus on the widely used package SIAR and the more advanced
MixSIAR. Participants will be taught some of the advanced features of these
packages, which will enable them to produce a richer class of output, and
are encouraged to bring their own data sets and problems to study during
the round-table discussions. Monday 10th – Classes from 09:30 to 17:30
Basic concepts. Module 1: Introduction; why use a SIMM? Module 2: An
introduction to bayesian statistics. Module 3: Differences between
regression models and SIMMs. Practical: Revision on using R to load data,
create plots and fit statistical models. Round table discussion:
Understanding the output from a Bayesian model. Tuesday 11th – Classes from
09:30 to 17:30 Understanding and using SIAR. Module 4: Do’s and Don’ts of
using SIAR. Module 5: The statistical model behind SIAR. Practical: Using
SIAR for real-world data sets; reporting output; creating richer summaries
and plots. Round table discussion: Issues when using simple SIMMs.
Wednesday 12th – Classes from 09:30 to 17:30 SIBER and MixSIAR. Module 6:
Creating and understanding Stable Isotope Bayesian Ellipses (SIBER). Module
7: What are the differences between SIAR and MixSIAR? Practical: Using
MixSIAR on real world data sets; benefits over SIAR. Round table
discussion: When to use which type of SIMM. Thursday 13th – Classes from
09:30 to 17:30 Advanced SIMMs. Module 8: Using MixSIAR for complex data
sets: time series and mixed effects models. Module 9: Source grouping: when
and how? Module 10: Building your own SIMM with JAGS. Practical: Running
advanced SIMMs with JAGS. Round table discussion: Bring your own data set.
Friday 14th – Classes from 09:30 to 16:00 Bring your own data set. Please
email oliverhoo...@prstatistics.com with any questions. Check out our
sister sites, www.PRstatistics.com  (Ecology
and Life Sciences) www.PRinformatics.com 
(Bioinformatics and data science) www.PSstatistics.com
 (Behaviour and cognition)

1.   June 10th – 14th 2019

STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR (SIMM04)

Glasgow, Scotland, Dr. Andrew Parnell, Dr. Andrew Jackson

www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm04/



2.   June 10th – 14th 2019

INTRODUCTION TO PYTHON FOR BIOLOGISTS (IPYB06)

Glasgow, Scotland, Dr. Martin Jones

http://www.prinformatics.com/course/introduction-to-python-for-biologists-ipyb06/



3.   June 17th – 21st 2019

ANALYSING ENVIRONMENTAL ADAPTATION USING LANDSCAPE GENETICS (EDAP01)

Glasgow, Dr. Matt Fitzpatrick

https://www.prstatistics.com/course/analysing-environmental-adaptation-using-landscape-genetics-edap01



4.   June 17th – 21st 2019

ADVANCED PYTHON FOR BIOLOGISTS (APYB03)

Glasgow, Scotland, Dr. Martin Jones

www.prinformatics.com/course/advanced-python-biologists-apyb03/



5.   June 24th – 28th 2019

MICROBIOME DATA ANALYSIS USING QIIME2 (MBQM01)

Glasgow, Scotland, Dr. Yoshiki Vazquez Baeza, Dr. Antonio Gonzalez Pena

https://www.prinformatics.com/course/microbiome-data-analysis-using-qiime2-mbqm01/



6.   June 24th – 28th 2019

DATA VISUALISATION AND MANIPULATION USING PYTHON (DVMP01)

Glasgow, Scotland, Dr. Martin Jones

http://www.prinformatics.com/course/data-visualisation-and-manipulation-using-python-dvmp01/



7.   July 1st – 5th 2019

BIOACOUSTICS FOR ECOLOGISTS: HARDWARE, SURVEY DESIGN AND DATA ANALYSIS
(BIAC01)

Glasgow, Scotland, Dr. Paul Howden-Leach

https://www.prstatistics.com/course/bioacoustics-for-ecologists-hardware-survey-design-and-data-analysis-biac01/



8.   July 8th – 12th 2019

INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING USING R (IBHM03)

Glasgow, Scotland, Dr. Andrew Parnell

https://www.psstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm03/



9.   July 29th – August 2nd 2019

INTRODUCTION TO SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (ISPE01)

Glasgow, Scotland, Dr. Jakub Nowosad

https://www.prstatistics.com/course/introduction-to-spatial-analysis-of-ecological-data-using-r-ispe01/



10.September 2nd – 6th 2019

APPLIED METHOD

[MARMAM] New Paper: Aerial surveys for Antarctic minke whales reveal sea ice dependent distribution patterns

[Helena Herr]

Dear all,

I am pleased to announce the recent publication of our paper in Ecology and 
Evolution::

Herr H, Kelly N, Dorschel B, Huntemann M, Kock K-H, Lehnert LS, Siebert U, 
Viquerat S, Williams R, Scheidat M (2019) Aerial surveys for Antarctic minke 
whales (Balaenoptera bonaerensis) reveal sea ice dependent distribution 
patterns. Ecol Evol. 2019;00:1–19. https://doi.org/10.1002/ece3.5149


Abstract
This study investigates the distribution of Antarctic minke whales (AMW) in 
relation to sea ice concentration and variations therein. Information on AMW 
densities in the sea ice-covered parts of the Southern Ocean is required to 
contextualize abundance estimates obtained from circumpolar shipboard surveys 
in open waters, suggesting a 30% decline in AMW abundance. Conventional 
line-transect shipboard surveys for density estimation are impossible in 
ice-covered regions, therefore we used ice- breaker-supported helicopter 
surveys to obtain information on AMW densities along gradients of 0%–100% of 
ice concentration. We conducted five helicopter surveys in the Southern Ocean, 
between 2006 and 2013. Distance sampling data, satellite-de- rived sea-ice 
data, and bathymetric parameters were used in generalized additive models 
(GAMs) to produce predictions on how the density of AMWs varied over space and 
time, and with environmental covariates. Ice concentration, distance to the ice 
edge and distance from the shelf break were found to describe the distribution 
of AMWs. Highest densities were predicted at the ice edge and through to medium 
ice concentrations. Medium densities were found up to 500 km into the ice edge 
in all concentrations of ice. Very low numbers of AMWs were found in the 
ice-free waters of the West Antarctic Peninsula (WAP). A consistent 
relationship between AMW dis- tribution and sea ice concentration weakens the 
support for the hypothesis that vary- ing numbers of AMWs in ice-covered waters 
were responsible for observed changes in estimated abundance. The potential 
decline in AMW abundance stresses the need for conservation measures and 
further studies into the AMW population status. Very low numbers of AMWs 
recorded in the ice-free waters along the WAP support the hypothesis that this 
species is strongly dependent on sea ice and that forecasted sea ice changes 
have the potential of heavily impacting AMWs.


The open access paper is available at: 
https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.5149 
 

Please do not hesitate to contact me if you have any questions.

Kind regards

Helena 


 

--





Dr. Helena Herr

Centrum für Naturkunde – CeNak – Center of Natural History
Martin-Luther-King-Platz 3 / Room 243b
20146 Hamburg - Germany
phone +49 (0) 40 42838 1560
email: helena.h...@uni-hamburg.de
www.cenak.uni-hamburg.de 


Alfred Wegener Institute
Helmholtz Centre for Polar and Marine Research
Section Polar Biological Oceanography
AG Ecophysiology of Pelagic Key Species
Am Handelshafen 12 / Building E, Room 2390
27570 Bremerhaven - Germany
phone: +49 (0) 471 4831 2360
email: helena.h...@awi.de

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