3,968 research outputs found

    Studies of the Mexican Deltocephalinae : New Species of Eutettix and Two Allied New Genera (Homoptera: Cicadellidae)

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    Author Institution: Department of Zoology, The Ohio State University, Columbus, Ohio 43210Two new genera, Alladanus and Cozadanus, and sixteen new species of Deltocephalinae (leafhoppers) are described from Mexico. Twelve species, all new, are described and placed in the genus Eutettix Van Duzee: E. contorqus, E. lanceolatus, E. dentatus, E. alvadus, E. chelatus, E. spinus, E. pedus, E. divergens, E. krameri, E. guevarai, E. transversus, and E. ortegai. Two new species, A, cephalatus and A. mexellus, are described and placed in the new genus Alladanus, of which A. cephalatus is the genotype. Two new species, C. globosus and C. serratus, are described and placed in the new genus Cozadanus, of which C. globosus is the genotype

    A Preliminary Note on Egg Production from Milk-Fed Mosquitoes

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    Author Institution: Department of Zoology and Entomology, The Ohio State University, Columbus 1

    Metatranscriptomic Analysis of Sulfur Oxidation Genes in the Endosymbiont of Solemya Velum

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    Thioautotrophic endosymbionts in the Domain Bacteria mediate key sulfur transformations in marine reducing environments. However, the molecular pathways underlying symbiont metabolism and the extent to which these pathways are expressed in situ are poorly characterized for almost all symbioses. This is largely due to the difficulty of culturing symbionts apart from their hosts. Here, we use pyrosequencing of community RNA transcripts (i.e., the metatranscriptome) to characterize enzymes of dissimilatory sulfur metabolism in the model symbiosis between the coastal bivalve Solemya velum and its intracellular thioautotrophic symbionts. High-throughput sequencing of total RNA from the symbiont-containing gill of a single host individual generated 1.6 million sequence reads (500 Mbp). Of these, 43,735 matched Bacteria protein-coding genes in BLASTX searches of the NCBI database. The taxonomic identities of the matched genes indicated relatedness to diverse species of sulfur-oxidizing Gammaproteobacteria, including other thioautotrophic symbionts and the purple sulfur bacterium Allochromatium vinosum. Manual querying of these data identified 28 genes from diverse pathways of sulfur energy metabolism, including the dissimilatory sulfite reductase (Dsr) pathway for sulfur oxidation to sulfite, the APS pathway for sulfite oxidation, and the Sox pathway for thiosulfate oxidation. In total, reads matching sulfur energy metabolism genes represented 7% of the Bacteria mRNA pool. Together, these data highlight the dominance of thioautotrophy in the context of symbiont community metabolism, identify the likely pathways mediating sulfur oxidation, and illustrate the utility of metatranscriptome sequencing for characterizing community gene transcription of uncultured symbionts

    A Preliminary Note on Some Nutritional Requirements for Reproduction in Female Aedes Aegypti

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    Author Institution: Department of Zoology and Entomology, The Ohio State University, Columbus 1

    Microbial community structure and function on sinking particles in the North Pacific Subtropical Gyre

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    Sinking particles mediate the transport of carbon and energy to the deep-sea, yet the specific microbes associated with sedimenting particles in the ocean's interior remain largely uncharacterized. In this study, we used particle interceptor traps (PITs) to assess the nature of particle-associated microbial communities collected at a variety of depths in the North Pacific Subtropical Gyre. Comparative metagenomics was used to assess differences in microbial taxa and functional gene repertoires in PITs containing a preservative (poisoned traps) compared to preservative-free traps where growth was allowed to continue in situ (live traps). Live trap microbial communities shared taxonomic and functional similarities with bacteria previously reported to be enriched in dissolved organic matter (DOM) microcosms (e.g., Alteromonas and Methylophaga), in addition to other particle and eukaryote-associated bacteria (e.g., Flavobacteriales and Pseudoalteromonas). Poisoned trap microbial assemblages were enriched in Vibrio and Campylobacterales likely associated with eukaryotic surfaces and intestinal tracts as symbionts, pathogens, or saprophytes. The functional gene content of microbial assemblages in poisoned traps included a variety of genes involved in virulence, anaerobic metabolism, attachment to chitinaceaous surfaces, and chitin degradation. The presence of chitinaceaous surfaces was also accompanied by the co-existence of bacteria which encoded the capacity to attach to, transport and metabolize chitin and its derivatives. Distinctly different microbial assemblages predominated in live traps, which were largely represented by copiotrophs and eukaryote-associated bacterial communities. Predominant sediment trap-assocaited eukaryotic phyla included Dinoflagellata, Metazoa (mostly copepods), Protalveolata, Retaria, and Stramenopiles. These data indicate the central role of eukaryotic taxa in structuring sinking particle microbial assemblages, as well as the rapid responses of indigenous microbial species in the degradation of marine particulate organic matter (POM) in situ in the ocean's interior.Gordon and Betty Moore Foundation (Grant 3777)Agouron Institute (AI-MO9.12.1)National Science Foundation (U.S.). Center for Microbial Oceanography: Research and Education (EF0424599)Simons Foundation (Award 329108)National Science Foundation (U.S.) (Postdoctoral Research Fellowship in Biology DBI-1202684

    Individual phenotypic variation reduces interaction strengths in a consumer–resource system

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    Natural populations often show variation in traits that can affect the strength of interspecific interactions. Interaction strengths in turn influence the fate of pairwise interacting populations and the stability of food webs. Understanding the mechanisms relating individual phenotypic variation to interaction strengths is thus central to assess how trait variation affects population and community dynamics. We incorporated nonheritable variation in attack rates and handling times into a classical consumer–resource model to investigate how variation may alter interaction strengths, population dynamics, species persistence, and invasiveness. We found that individual variation influences species persistence through its effect on interaction strengths. In many scenarios, interaction strengths decrease with variation, which in turn affects species coexistence and stability. Because environmental change alters the direction and strength of selection acting upon phenotypic traits, our results have implications for species coexistence in a context of habitat fragmentation, climate change, and the arrival of exotic species to native ecosystems

    Socio-Economic Instability and the Scaling of Energy Use with Population Size

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    The size of the human population is relevant to the development of a sustainable world, yet the forces setting growth or declines in the human population are poorly understood. Generally, population growth rates depend on whether new individuals compete for the same energy (leading to Malthusian or density-dependent growth) or help to generate new energy (leading to exponential and super-exponential growth). It has been hypothesized that exponential and super-exponential growth in humans has resulted from carrying capacity, which is in part determined by energy availability, keeping pace with or exceeding the rate of population growth. We evaluated the relationship between energy use and population size for countries with long records of both and the world as a whole to assess whether energy yields are consistent with the idea of an increasing carrying capacity. We find that on average energy use has indeed kept pace with population size over long time periods. We also show, however, that the energy-population scaling exponent plummets during, and its temporal variability increases preceding, periods of social, political, technological, and environmental change. We suggest that efforts to increase the reliability of future energy yields may be essential for stabilizing both population growth and the global socio-economic system

    The combined effects of reactant kinetics and enzyme stability explain the temperature dependence of metabolic rates

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    A mechanistic understanding of the response of metabolic rate to temperature is essential for understanding thermal ecology and metabolic adaptation. Although the Arrhenius equation has been used to describe the effects of temperature on reaction rates and metabolic traits, it does not adequately describe two aspects of the thermal performance curve (TPC) for metabolic rate—that metabolic rate is a unimodal function of temperature often with maximal values in the biologically relevant temperature range and that activation energies are temperature dependent. We show that the temperature dependence of metabolic rate in ectotherms is well described by an enzyme-assisted Arrhenius (EAAR) model that accounts for the temperature-dependent contribution of enzymes to decreasing the activation energy required for reactions to occur. The model is mechanistically derived using the thermodynamic rules that govern protein stability. We contrast our model with other unimodal functions that also can be used to describe the temperature dependence of metabolic rate to show how the EAAR model provides an important advance over previous work. We fit the EAAR model to metabolic rate data for a variety of taxa to demonstrate the model’s utility in describing metabolic rate TPCs while revealing significant differences in thermodynamic properties across species and acclimation temperatures. Our model advances our ability to understand the metabolic and ecological consequences of increases in the mean and variance of temperature associated with global climate change. In addition, the model suggests avenues by which organisms can acclimate and adapt to changing thermal environments. Furthermore, the parameters in the EAAR model generate links between organismal level performance and underlying molecular processes that can be tested for in future work
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