DOI: 10.5061/dryad.pvmcvdnnb
title: Population changes in a whale breeding ground revealed by citizen science noninvasive genetics unique microsatellite profiles of southern right whales

description: 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.
description: 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).
description: 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