Anomalous Variability in Antarctic Sea Ice Extents During the 1960s With the Use of Nimbus Data

The Nimbus I, II, and III satellites provide a new opportunity for climate studies in the 1960s. The rescue of the visible and infrared imager data resulted in the utilization of the early Nimbus data to determine sea ice extent. A qualitative analysis of the early NASA Nimbus missions has revealed Antarctic sea ice extents that are signicant larger and smaller than the historic 1979-2012 passive microwave record. The September 1964 ice mean area is 19.7x10 km +/- 0.3x10 km. This is more the 250,000 km greater than the 19.44x10 km seen in the new 2012 historic maximum. However, in August 1966 the maximum sea ice extent fell to 15.9x10 km +/- 0.3x10 km. This is more than 1.5x10 km below the passive microwave record of 17.5x10 km set in September of 1986. This variation between 1964 and 1966 represents a change of maximum sea ice of over 3x10 km in just two years. These inter-annual variations while large, are small when compared to the Antarctic seasonal cycle

Anomalous Variability in Antarctic Sea Ice Extents During the 1960s With the Use of Nimbus Data

The Nimbus I, II, and III satellites provide a new opportunity for climate studies in the 1960s. The rescue of the visible and infrared imager data resulted in the utilization of the early Nimbus data to determine sea ice extent. A qualitative analysis of the early NASA Nimbus missions has revealed Antarctic sea ice extents that are significant larger and smaller than the historic 1979-2012 passive microwave record. The September 1964 ice mean area is 19.7x10(exp 6) sq. km +/- 0.3x10(exp 6) sq. km. This is more the 250,000 sq. km greater than the 19.44x10(exp 6) sq. km seen in the new 2012 historic maximum. However, in August 1966 the maximum sea ice extent fell to 15.9x10(exp 6) sq. km +/- 0.3x10(exp 6) sq. km. This is more than 1.5x10(exp 6) sq. km below the passive microwave record of 17.5x10(exp 6) sq. km set in September of 1986. This variation between 1964 and 1966 represents a change of maximum sea ice of over 3x10(exp 6) sq. km in just two years. These inter-annual variations while large, are small when compared to the Antarctic seasonal cycle

A bi‐organellar phylogenomic study of Pandanales: inference of higher‐order relationships and unusual rate‐variation patterns

We used a bi‐organellar phylogenomic approach to address higher‐order relationships in Pandanales, including the first molecular phylogenetic study of the panama‐hat family, Cyclanthaceae. Our genus‐level study of plastid and mitochondrial gene sets includes a comprehensive sampling of photosynthetic lineages across the order, and provides a framework for investigating clade ages, biogeographic hypotheses and organellar molecular evolution. Using multiple inference methods and both organellar genomes, we recovered mostly congruent and strongly supported relationships within and between families, including the placement of fully mycoheterotrophic Triuridaceae. Cyclanthaceae and Pandanaceae plastomes have slow substitution rates, contributing to weakly supported plastid‐based relationships in Cyclanthaceae. While generally slowly evolving, mitochondrial genomes exhibit sporadic rate elevation across the order. However, we infer well‐supported relationships even for slower evolving mitochondrial lineages in Cyclanthaceae. Clade age estimates across photosynthetic lineages are largely consistent with previous studies, are well correlated between the two organellar genomes (with slightly younger inferences from mitochondrial data), and support several biogeographic hypotheses. We show that rapidly evolving non‐photosynthetic lineages may bias age estimates upwards at neighbouring photosynthetic nodes, even using a relaxed clock model. Finally, we uncovered new genome structural variants in photosynthetic taxa at plastid inverted repeat boundaries that show promise as interfamilial phylogenetic markers.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/33/cla12417-sup-0025-TableS1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/32/cla12417-sup-0017-FigS17.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/31/cla12417-sup-0004-FigS4.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/30/cla12417-sup-0019-FigS19.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/29/cla12417-sup-0020-FigS20.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/28/cla12417_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/27/cla12417-sup-0005-FigS5.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/26/cla12417-sup-0012-FigS12.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/25/cla12417-sup-0007-FigS7.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/24/cla12417-sup-0022-FigS22.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/23/cla12417-sup-0029-TableS5.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/22/cla12417-sup-0010-FigS10.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/21/cla12417-sup-0011-FigS11.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/20/cla12417-sup-0014-FigS14.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/19/cla12417-sup-0002-FigS2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/18/cla12417-sup-0001-FigS1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/17/cla12417.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/16/cla12417-sup-0030-TableS6.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/15/cla12417-sup-0021-FigS21.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/14/cla12417-sup-0023-FigS23.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/13/cla12417-sup-0009-FigS9.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/12/cla12417-sup-0031-TableS7.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/11/cla12417-sup-0006-FigS6.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/10/cla12417-sup-0003-FigS3.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/9/cla12417-sup-0024-FigS24.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/8/cla12417-sup-0008-FigS8.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/7/cla12417-sup-0028-TableS4.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/6/cla12417-sup-0016-FigS16.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/5/cla12417-sup-0013-FigS13.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/4/cla12417-sup-0018-FigS18.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/3/cla12417-sup-0026-TableS2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/2/cla12417-sup-0015-FigS15.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162810/1/cla12417-sup-0027-TableS3.pd

A Novel Technique for Time-Centric Analysis of Massive Remotely-Sensed Datasets

Analyzing massive remotely-sensed datasets presents formidable challenges. The volume of satellite imagery collected often outpaces analytical capabilities, however thorough analyses of complete datasets may provide new insights into processes that would otherwise be unseen. In this study we present a novel, object-oriented approach to storing, retrieving, and analyzing large remotely-sensed datasets. The objective is to provide a new structure for scalable storage and rapid, Internet-based analysis of climatology data. The concept of a “data rod” is introduced, a conceptual data object that organizes time-series information into a temporally-oriented vertical column at any given location. To demonstrate one possible use, we ingest 25 years of Greenland imagery into a series of pure-object databases, then retrieve and analyze the data. The results provide a basis for evaluating the database performance and scientific analysis capabilities. The project succeeds in demonstrating the effectiveness of the prototype database architecture and analysis approach, not because new scientific information is discovered, but because quality control issues are revealed in the source data that had gone undetected for years

Neotypification of \u3ci\u3ePandanus odorifer\u3c/i\u3e the Correct Name for \u3ci\u3eP. odoratissimus\u3c/i\u3e (Pandanaceae)

Pandanus odorifer (Pandanaceae) is an economically important species distributed on coasts from India and Sri Lanka to South China through tropical Asian countries. Pandanus odoratissimus has been widely used as the accepted name for the species, but P. odoratissimus is in reality a superfluous and illegitimate name. No original material of P. odorifer has been traced, and a neotype is designated here for that name

Association of the Calcyon Neuron-Specific Vesicular Protein Gene (CALY) With Adolescent Smoking Initiation in China and California

Although previous investigations have indicated a role for genetic factors in smoking initiation, the underlying genetic mechanisms are still unknown. In 2,339 adolescents from a Chinese Han population in the Wuhan Smoking Prevention Trial (Wuhan, China, 1998–1999), the authors explored the association of 57 genes in the dopamine pathway with smoking initiation. Using a conservative approach for declaring significance, positive findings were further examined in an independent sample of 603 Caucasian adolescents followed for up to 10 years as part of the Children's Health Study (Southern California, 1993–2009). The authors identified 1 single nucleotide polymorphism (rs2298122) in the calcyon neuron-specific vesicular protein gene (CALY) that was positively associated with smoking initiation in females (odds ratio = 2.21, 95% confidence interval: 1.49, 3.27; P = 8.4 × 10−5) in the Wuhan Smoking Prevention Trial cohort, and they replicated the association in females from the Children's Health Study cohort (hazard rate ratio = 2.05, 95% confidence interval: 1.27, 3.31; P = 0.003). These results suggest that the CALY gene may influence smoking initiation in adolescents, although the potential roles of underlying psychological characteristics that may be components of the smoking-initiation phenotype, such as impulsivity or novelty-seeking, remain to be explored

The Chlamydomonas Genome Project, version 6: Reference assemblies for mating-type plus and minus strains reveal extensive structural mutation in the laboratory.

Five versions of the Chlamydomonas reinhardtii reference genome have been produced over the last two decades. Here we present version 6, bringing significant advances in assembly quality and structural annotations. PacBio-based chromosome-level assemblies for two laboratory strains, CC-503 and CC-4532, provide resources for the plus and minus mating-type alleles. We corrected major misassemblies in previous versions and validated our assemblies via linkage analyses. Contiguity increased over ten-fold and >80% of filled gaps are within genes. We used Iso-Seq and deep RNA-seq datasets to improve structural annotations, and updated gene symbols and textual annotation of functionally characterized genes via extensive manual curation. We discovered that the cell wall-less classical reference strain CC-503 exhibits genomic instability potentially caused by deletion of the helicase RECQ3, with major structural mutations identified that affect >100 genes. We therefore present the CC-4532 assembly as the primary reference, although this strain also carries unique structural mutations and is experiencing rapid proliferation of a Gypsy retrotransposon. We expect all laboratory strains to harbor gene-disrupting mutations, which should be considered when interpreting and comparing experimental results. Collectively, the resources presented here herald a new era of Chlamydomonas genomics and will provide the foundation for continued research in this important reference organism

Computational protein design enables a novel one-carbon assimilation pathway.

We describe a computationally designed enzyme, formolase (FLS), which catalyzes the carboligation of three one-carbon formaldehyde molecules into one three-carbon dihydroxyacetone molecule. The existence of FLS enables the design of a new carbon fixation pathway, the formolase pathway, consisting of a small number of thermodynamically favorable chemical transformations that convert formate into a three-carbon sugar in central metabolism. The formolase pathway is predicted to use carbon more efficiently and with less backward flux than any naturally occurring one-carbon assimilation pathway. When supplemented with enzymes carrying out the other steps in the pathway, FLS converts formate into dihydroxyacetone phosphate and other central metabolites in vitro. These results demonstrate how modern protein engineering and design tools can facilitate the construction of a completely new biosynthetic pathway

Computational protein design enables a novel one-carbon assimilation pathway.

We describe a computationally designed enzyme, formolase (FLS), which catalyzes the carboligation of three one-carbon formaldehyde molecules into one three-carbon dihydroxyacetone molecule. The existence of FLS enables the design of a new carbon fixation pathway, the formolase pathway, consisting of a small number of thermodynamically favorable chemical transformations that convert formate into a three-carbon sugar in central metabolism. The formolase pathway is predicted to use carbon more efficiently and with less backward flux than any naturally occurring one-carbon assimilation pathway. When supplemented with enzymes carrying out the other steps in the pathway, FLS converts formate into dihydroxyacetone phosphate and other central metabolites in vitro. These results demonstrate how modern protein engineering and design tools can facilitate the construction of a completely new biosynthetic pathway