10.5061/DRYAD.PVMCVDNNB
Neveceralova, Petra
0000-0003-0823-3311
Charles University
Carroll, Emma
University of Auckland
Steel, Debbie
Oregon State University
Vermeulen, Els
0000-0002-3667-1290
University of Pretoria
Elwen, Simon
Stellenbosch University
Hulva, Pavel
Charles University
Population changes in a whale breeding ground revealed by citizen science
noninvasive genetics unique microsatellite profiles of southern right
whales
Dryad
dataset
2022
cetacean
Citizen science
noninvasive genetics
sloughed skin
Southern Africa
southern right whale
FOS: Biological sciences
Charles University
https://ror.org/024d6js02
grant number 1140217
Charles University
2022-05-19T00:00:00Z
2022-05-19T00:00:00Z
en
https://doi.org/10.1016/j.gecco.2022.e02141
53997 bytes
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Historical exploitation, and a combination of current anthropogenic
impacts, such as climate change and habitat degradation, impact the
population dynamics of marine mammalian megafauna. Right whales (Eubalaena
spp.) are large cetaceans recovering from hunting, whose reproductive and
population growth rate appear to be impacted by climate change. We apply
noninvasive genetic methods to monitor southern right whale (E. australis,
SRW) and test the application of noninvasive genetics to minimise the
observer effects on the population. Our aim is to describe population
structure, and interdecadal and interannual changes to assess species
status in the Great Acceleration period of Anthropocene. As a basis for
population genetic analyses, we collected samples from sloughed skin
during post-migration epidermal moult. Considering the
exploration-exploitation dilemma, we collaborated with whale-watching
companies, as part of a citizen science approach and to reduce ad hoc
logistic operations and biopsy equipment. We used mitochondrial and
microsatellite data and population genetic tools. We report for the first
time the genetic composition and differentiation of the Namibian portion
of the range. Population genetic parameters suggest that South Africa
hosts the largest population. This corresponds with higher estimates of
current gene flow from Africa compared to older samples. We have observed
considerable interannual variation in population density at the breeding
ground and an interdecadal shift in genetic variability, evidenced by an
increase in the point estimate inbreeding. Clustering analyses confirmed
differentiation between the Atlantic and Indo-Pacific, presumably
originating during the ice ages. We show that population monitoring of
large whales, essential for their conservation management, is feasible
using noninvasive sampling within non-scientific platforms. Observed
patterns are concurrent to changes of movement ecology and decline in
reproductive success of the South African population, probably reflecting
a large-scale restructuring of pelagic marine food webs.
The majority of samples used in this study were obtained noninvasively by
collecting sloughed skin from whale watching boats conducting commercial
trips during the austral winters of 2016 – 2018 in the area of Gansbaai
and Walker Bay, South Africa. Pieces of skin were spotted in the water,
picked up by a dip net and transferred with sterile tweezers to a tube
containing 96% ethanol. Additional samples were collected from a research
boat by remote biopsy using a crossbow and Cetadart darts (Lambertsen,
1987). All samples were stored at − 18 °C. Another 32 biopsy samples were
available in archive held by University of Pretoria Mammal Research
Institute Whale Unit. These samples were collected in two different
regions, South Africa and Namibia, between 2003 and 2013. Tissue was
pulverised in liquid nitrogen and DNA was extracted using either the
QIAGEN DNeasy Blood & Tissue Kit or the GENEAID Genomic DNA Mini
Kit. Seventeen microsatellite loci were grouped into multiplexes and
amplified in 10 μl PCR reactions (Carroll et al., 2015). Multi-locus
microsatellite genotyping was done according to sample type. For
noninvasive samples, a multi-tube approach (Taberlet et al., 1996) was
attempted, with each DNA extraction being amplified at all loci up to
three times. For biopsy samples, all loci were amplified once. Sex was
determined by amplification of the male specific SRY gene, multiplexed
with an amplification of the ZFY/ZRX region as a positive control (Aasen
and Medrano, 1990, Gilson et al., 1998). An approximately 550 base pair
fragment of the left hypervariable domain of mtDNA control region adjacent
to the Pro-tRNA gene was amplified according to Baker et al. (1999). The
resulting PCR product was purified by either QIAGEN QIAquick PCR
Purification Kit or GENEAID GenepHlow PCR Cleanup Kit and sequenced using
BigDye chemistry on a 3130 Genetic Analyzer (Applied Biosystems).
Chromatograms were visualized and edited in Geneious Prime v2020.2.4 (©
Biomatters Ltd.). For the microsatellite data, quality filtering, allele
calling and binning was performed in the program Genemapper 5 (Applied
Biosystems). For samples where loci were run more than once, the final
genotype was constructed by choosing the highest quality allele calls for
each locus, as determined by the quality score in Genemapper. Any samples
where the allele calls disagreed between runs were removed from the
dataset. Genotypes that failed to amplify for seven or more loci were
considered poor quality and were removed from the dataset. Genotype error
rates were calculated per allele (Pompanon et al., 2005) using the
internal control samples amplified in every PCR and replicate samples. We
report the completeness of the final dataset in terms of number of loci
per sample. First, genotypes within a year were reconciled to identify the
number of unique whales sampled per austral winter season. Then, unique
genotypes across years were compared to understand between year recaptures
and the total number of whales sampled over the survey period. Cervus
3.0.7 was used to identify these within and between years genotype matches
(Kalinowski et al., 2007) with the minimum number of matching loci set to
at least eight. Pairs of genotypes that matched at eight loci but
mismatched at up to three loci were reviewed and repeated if necessary to
verify the individual’s identity or difference (Constantine et al., 2012).
This dataset contains 190 unique genotypes of southern right whales
collected in South Africa. Additional samples were added by Carroll et
al., 2020, which can be downloaded at
https://datadryad.org/stash/dataset/doi:10.5061/dryad.vv5347p