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1.
Environ Toxicol Chem ; 38(1): 106-114, 2019 01.
Article in English | MEDLINE | ID: mdl-30284322

ABSTRACT

Physical systems, such as currents and winds, have traditionally been considered responsible for transporting contaminants. Although evidence is mounting that animals play a role in this process through their movements, we still know little about how such contaminant biotransport occurs and the extent of effects at deposition sites. In the present study, we address this question by studying how rhinoceros auklets (Cerorhinca monocerata), a seabird that occurs in immense colonies (∼300 000 pairs at our study site, Teuri Island), affect contaminant levels at their colony and at nearby sites. More specifically, we hypothesize that contaminants are transported and deposited by seabirds at their colony and that these contaminants are passed on locally to the terrestrial ecosystem. To test this hypothesis, we analyzed the concentration of 9 heavy metal and metalloids, as well as δ13 C and δ15 N stable isotopes, in bird tissues, plants, and soil, both within and outside of the colony. The results show that rhinoceros auklets transport marine-derived mercury (Hg), possibly from their wintering location, and deposit Hg via their feces at their breeding site, thereby contaminating plants and soils within the breeding colony. The present study confirms not only that animals can transport contaminants from marine to terrestrial ecosystems, potentially over unexpectedly long distances, but also that bird tissues contribute locally to plant contamination. Environ Toxicol Chem 2019;38:106-114. © 2018 SETAC.


Subject(s)
Charadriiformes/metabolism , Ecosystem , Metals/metabolism , Seawater , Trace Elements/metabolism , Animals , Biological Transport , Environmental Monitoring , Erythrocytes/metabolism , Feces/chemistry , Geography , Islands , Mercury Isotopes , Metalloids/metabolism , Plant Roots/metabolism , Plants/metabolism , Principal Component Analysis , Soil/chemistry
2.
Article in English | MEDLINE | ID: mdl-26952335

ABSTRACT

Many behavioral processes scale with body mass (M) because underlying physiological constraints, such as metabolism, scale with M. A classic example is the maximum duration of dives by breath-hold divers, which scales with M0.25, as predicted from the ratio of oxygen stores (M1.0) to diving oxygen consumption rate (M0.75) - assuming classic scaling relationships for those physiological processes. However, maximum dive duration in some groups of birds does not have a 0.25 scaling exponent. We re-examined the allometric scaling of maximum dive duration in auks to test whether the discrepancy was due to poor data (earlier analyses included data from many different sources possibly leading to bias), phylogeny (earlier analyses did not account for phylogenetic inertia) or physiology (earlier analyses did not analyze physiological parameters alongside behavioral parameters). When we included only data derived from electronic recorders and after accounting for phylogeny, the equation for maximum dive duration was proportional to M0.33. At the same time, myoglobin concentration in small breath-hold divers was proportional to M0.36, implying that muscle oxygen stores were proportional to M1.36, but diving oxygen consumption rate in wing-propelled divers was only proportional to M0.79. Thus, the 99% confidence interval included the exponent of 0.57 predicted from the observed relationships between oxygen stores and consumption rates. In conclusion, auks are not exceptions to the hypothesis that a trade-off between oxygen stores and oxygen utilization drives variation in maximum dive duration. Rather, the scaling exponent for maximum dive duration is higher than expected due to the higher than expected scaling of muscle oxygen stores to body mass.


Subject(s)
Body Weight/physiology , Charadriiformes/physiology , Animals , Basal Metabolism , Diving/physiology , Myoglobin/metabolism , Oxygen , Oxygen Consumption/physiology , Phylogeny , Time Factors
3.
Biol Lett ; 11(10)2015 Oct.
Article in English | MEDLINE | ID: mdl-26510674

ABSTRACT

Inter-seasonal events are believed to connect and affect reproductive performance (RP) in animals. However, much remains unknown about such carry-over effects (COEs), in particular how behaviour patterns during highly mobile life-history stages, such as migration, affect RP. To address this question, we measured at-sea behaviour in a long-lived migratory seabird, the Manx shearwater (Puffinus puffinus) and obtained data for individual migration cycles over 5 years, by tracking with geolocator/immersion loggers, along with 6 years of RP data. We found that individual breeding and non-breeding phenology correlated with subsequent RP, with birds hyperactive during winter more likely to fail to reproduce. Furthermore, parental investment during one year influenced breeding success during the next, a COE reflecting the trade-off between current and future RP. Our results suggest that different life-history stages interact to influence RP in the next breeding season, so that behaviour patterns during winter may be important determinants of variation in subsequent fitness among individuals.


Subject(s)
Animal Migration/physiology , Birds/physiology , Reproduction/physiology , Seasons , Animals , Life Cycle Stages , Telemetry
4.
Ann N Y Acad Sci ; 1163: 343-7, 2009 Apr.
Article in English | MEDLINE | ID: mdl-19456356

ABSTRACT

Adrenoceptors (ARs) are G protein-coupled receptors found throughout the vertebrates. Their pharmacology and preliminary phylogenetic analyses suggest that ARs are classified as alpha(1), alpha(2) (and their subtypes), and beta(1), beta(2), and beta(3). However, the relationships among subtypes of this superfamily, as well as both the pattern and the timing of their diversification, are poorly understood. In addition, fish AR subtypes possess pharmacologies and tissue distributions that only partially overlap with those of their mammalian counterparts, in spite of their apparent orthologous relationships within subtypes. Here we analyze 136 sequences in a range of vertebrates, including fish, to resolve these issues. We show that diversification of ARs occurred during duplication events that occurred within distinct time periods. Each period maps to whole-genome duplication events, two in vertebrates and one in fish. We also show that ARs underwent multiple duplications within these broad windows and that fish ARs underwent extensive gene loss after duplications that promoted their functional divergence with respect to other vertebrates.


Subject(s)
Receptors, Adrenergic/metabolism , Vertebrates/metabolism , Animals , Humans , Phylogeny , Receptors, Adrenergic/classification , Receptors, Adrenergic/genetics
5.
Mol Biol Evol ; 13(3): 494-504, 1996 Mar.
Article in English | MEDLINE | ID: mdl-8742638

ABSTRACT

In order to study the effect of mutation rate heterogeneity on patterns of DNA polymorphism, we simulated samples of DNA sequences with gamma-distributed nucleotide substitution rates in stationary and expanding populations. We find that recent population expansions and mutation rate heterogeneity have similar effects on several polymorphism indicators, like the shape and the mean of the observed pairwise difference distribution, or the number of segregating sites. The inferred size of population expansion thus appears overestimated if nucleotides have dissimilar substitution rates. Interestingly, population expansion and uneven mutation rates have contrasting effects on Tajima's D statistic when acting separately, and the consequence on the associated test of selective neutrality is investigated. The patterns of polymorphism of several human populations analyzed for the mitochondrial control region are examined, mainly showing the difficulty in quantifying the respective contribution of past demographic history and uneven mutation rates from a single sampled evolutionary process. However, substitution rates appear more heterogeneous in the second hypervariable segment of the control region than in the first segment.


Subject(s)
DNA/genetics , Models, Genetic , Mutation , Polymorphism, Genetic , Population Density , Animals , Base Composition , DNA/chemistry , DNA, Mitochondrial/genetics , Demography , Humans , Mathematics , Probability , Time
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