Why whales are big but not bigger : physiological drivers and ecological limits in the age of ocean giants

This research was funded in part by grants from the National Science Foundation (IOS-1656676, IOS-1656656; OPP-1644209 and 07-39483), the Office of Naval Research (N000141612477), and a Terman Fellowship from Stanford University. All procedures in USA were conducted under approval of the National Marine Fisheries Service (Permits 781-1824, 16163, 14809, 16111, 19116, 15271, 20430), Canada DFO SARA/MML 2010-01/SARA-106B, National Marine Sanctuaries (MULTI-2017-007), Antarctic Conservation Act (2009-014, 2015-011) and institutional IACUC committee protocols. Fieldwork, data collection and data processing for M. densirostris were funded by the Office of Naval Research grants N00014-07-10988, N00014-07-11023, N00014-08-10990, N00014-18-1-2062, and 00014-15-1-2553, and the U.S. Strategic Environmental Research and Development Program Grant SI-1539. PLT gratefully acknowledges funding from funding the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland). MASTS is funded by the Scottish Funding Council (HR09011) and contributing institutions.The largest animals are marine filter feeders, but the underlying mechanism of their large size remains unexplained. We measured feeding performance and prey quality to demonstrate how whale gigantism is driven by the interplay of prey abundance and harvesting mechanisms that increase prey capture rates and energy intake. The foraging efficiency of toothed whales that feed on single prey is constrained by the abundance of large prey, whereas filter-feeding baleen whales seasonally exploit vast swarms of small prey at high efficiencies. Given temporally and spatially aggregated prey, filter feeding provides an evolutionary pathway to extremes in body size that are not available to lineages that must feed on one prey at a time. Maximum size in filter feeders is likely constrained by prey availability across space and time.PostprintPeer reviewe

The stranding anomaly as population indicator: the case of Harbour Porpoise <i>Phocoena phocoena</i> in North-Western Europe

Ecological indicators for monitoring strategies are expected to combine three major characteristics: ecological significance, statistical credibility, and cost-effectiveness. Strategies based on stranding networks rank highly in cost-effectiveness, but their ecological significance and statistical credibility are disputed. Our present goal is to improve the value of stranding data as population indicator as part of monitoring strategies by constructing the spatial and temporal null hypothesis for strandings. The null hypothesis is defined as: small cetacean distribution and mortality are uniform in space and constant in time. We used a drift model to map stranding probabilities and predict stranding patterns of cetacean carcasses under H-0 across the North Sea, the Channel and the Bay of Biscay, for the period 1990-2009. As the most common cetacean occurring in this area, we chose the harbour porpoise <i>Phocoena phocoena</i> for our modelling. The difference between these strandings expected under H-0 and observed strandings is defined as the stranding anomaly. It constituted the stranding data series corrected for drift conditions. Seasonal decomposition of stranding anomaly suggested that drift conditions did not explain observed seasonal variations of porpoise strandings. Long-term stranding anomalies increased first in the southern North Sea, the Channel and Bay of Biscay coasts, and finally the eastern North Sea. The hypothesis of changes in porpoise distribution was consistent with local visual surveys, mostly SCANS surveys (1994 and 2005). This new indicator could be applied to cetacean populations across the world and more widely to marine megafauna

Incorporating non-equilibrium dynamics into demographic history inferences of a migratory marine species

ELC was supported while writing this paper by a EU Horizon 2020 Marie Slodowska Curie Fellowship, project BEHAVIOUR-CONNECT, by a Newton Fellowship from the Royal Society of London and Bayesian statistical training was supported by National Science Foundation (award DEB- 1145200). Laboratory analyses conducted by ELC were funded by a small grant from the British Ecological Society 5076 / 6118 and Bayesian analysis was supported by training from the National Science Foundation under Grant No. DEB-1145200. OEG was supported by the Marine Alliance for Science and Technology for Scotland (MASTS) funded by the Scottish Founding Council (grant reference HR09011). Genetic data from the South African right whale samples were generated by MB and PJP with the support of UC Berkeley, University of Stockholm and University of Groningen. Computational Biology analyses were supported by the University of St Andrews Bioinformatics Unit which is funded by a Wellcome Trust ISSF award.Understanding how dispersal and gene flow link geographically separated populations over evolutionary history is challenging, particularly in migratory marine species. In southern right whales (SRWs, Eubalaena australis), patterns of genetic diversity are likely influenced by the glacial climate cycle and recent history of whaling. Here we use a dataset of mitochondrial DNA (mtDNA) sequences (n=1,327) and nuclear markers (17 microsatellite loci, n=222) from major wintering grounds to investigate circumpolar population structure, historical demography, and effective population size. Analyses of nuclear genetic variation identify two population clusters that correspond to the South Atlantic and Indo-Pacific ocean basins that have similar effective breeder estimates. In contrast, all wintering grounds show significant differentiation for mtDNA, but no sex-biased dispersal was detected using the microsatellite genotypes. An approximate Bayesian computation (ABC) approach with microsatellite markers compared scenarios with gene flow through time, or isolation and secondary contact between ocean basins, while modeling declines in abundance linked to whaling. Secondary-contact scenarios yield the highest posterior probabilities, implying that populations in different ocean basins were largely isolated and came into secondary contact within the last 25,000 years, but the role of whaling in changes in genetic diversity and gene flow over recent generations could not be resolved. We hypothesis that these findings are driven by factors that promote isolation, such as female philopatry, and factors that could promote dispersal, such oceanographic changes. These findings highlight the application of ABC approaches to infer connectivity in mobile species with complex population histories and currently low levels of differentiation.PostprintPeer reviewe