Outcomes of pregnancies complicated by maternal tuberous sclerosis

We present three cases of maternal tuberous sclerosis without major complications in pregnancy and several other patients who delivered with a low risk obstetrician, from this we conclude that maternal tuberous sclerosis may not be as high risk for pregnancy as previously reported in the literature. Tuberous sclerosis (TS) is a genetic disorder that is inherited in an autosomal dominant fashion with variable clinical manifestations including seizures, mental retardation, renal failure and pneumothorax. This case series can aid obstetricians in counseling of patients with this rare disorder

Outcomes of pregnancies complicated by maternal tuberous sclerosis

We present three cases of maternal tuberous sclerosis without major complications in pregnancy and several other patients who delivered with a low risk obstetrician, from this we conclude that maternal tuberous sclerosis may not be as high risk for pregnancy as previously reported in the literature. Tuberous sclerosis (TS) is a genetic disorder that is inherited in an autosomal dominant fashion with variable clinical manifestations including seizures, mental retardation, renal failure and pneumothorax. This case series can aid obstetricians in counseling of patients with this rare disorder

BioTIME: A database of biodiversity time series for the Anthropocene.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL

Restoration of Native Plants Is Reduced by Rodent-Caused Soil Disturbance and Seed Removal

Granivory and soil disturbance are two modes by which burrowing rodents may limit the success of native plant restoration in rangelands. This guild of animals has prolific effects on plant community composition and structure, yet surprisingly little research has quantified the impact of rodents on plant restoration efforts. In this study, we examined the effects of seed removal and soil disturbance by the giant kangaroo rat (Dipodomys ingens) on native plant restoration in a California rangeland. Using experimental exclosures and stratifying restoration plots on and off rodent-disturbed soil, we assessed the individual and combined effects of seed removal and soil disturbance on seedling establishment of four native plant species. Across all species, biotic soil disturbance by kangaroo rats reduced seedling establishment by 19.5% (range = 1-43%), whereas seed removal reduced seedling establishment by only 6.7% (range = 4-12%). Rates of seed removal across species weakly paralleled kangaroo rat dietary preferences. These results indicate the indirect effects of burrowing rodents such as kangaroo rats on native seedling establishment via changes in soil properties may rival or exceed the direct effects of seed removal. © 2015 Society for Range Management. Published by Elsevier Inc. All rights reserved.The Rangeland Ecology & Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information

BioTIME: A database of biodiversity time series for the Anthropocene

Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)). Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.European Research Council; EU [AdG-250189, PoC-727440, ERC-SyG-2013-610028]; Natural Environmental Research Council [NE/L002531/1]; National Science Foundation [DEB-1237733, DEB-1456729, 9714103, 0632263, 0856516, 1432277, DEB 9705814, BSR-8811902, DEB 9411973, DEB 0080538, DEB 0218039, DEB 0620910, DEB 0963447, DEB-1546686, DEB-129764]; National Science Foundation (LTER) [DEB-1235828, DEB-1440297, DBI-0620409, DEB-9910514, DEB-1237517, OCE-0417412, OCE-1026851, OCE-1236905, OCE-1637396, DEB 1440409, DEB-0832652, DEB-0936498, DEB-0620652, DEB-1234162, DEB-0823293, OCE-9982105, OCE-0620276, OCE-1232779]; Fundacao para a Ciencia e Tecnologia [POPH/FSE SFRH/BD/90469/2012, SFRH/BD/84030/2012, PTDC/BIA-BIC/111184/2009]; Ciencia sem Fronteiras/CAPES [1091/13-1]; Instituto Milenio de Oceanografia [IC120019]; ARC Centre of Excellence [CE0561432]; NSERC Canada; CONICYT/FONDECYT [1160026, ICM PO5-002, 11110351, 1151094, 1070808, 1130511]; RSF [14-50-00029]; Gordon and Betty Moore Foundation [GBMF4563]; Catalan Government; Marie Curie Individual Fellowship [QLK5-CT2002-51518, MERG-CT-2004-022065]; CNPq [306170/2015-9, 475434/2010-2, 403809/2012-6, 561897/2010, 306595-2014-1]; FAPESP (Sao Paulo Research Foundation) [2015/10714-6, 2015/06743-0, 2008/10049-9, 2013/50714-0, 1999/09635-0 e 2013/50718-5]; EU CLIMOOR [ENV4-CT97-0694]; VULCAN [EVK2-CT2000-00094]; DFG [120/10-2]; Polar Continental Shelf Program; CENPES - PETROBRAS; FAPERJ [E-26/110.114/ 2013]; German Academic Exchange Service; New Zealand Department of Conservation; Wellcome Trust [105621/Z/14/Z]; Smithsonian Atherton Seidell Fund; Botanic Gardens and Parks Authority; Research Council of Norway; Conselleria de Innovacio, Hisenda i Economia; Yukon Government Herschel Island-Qikiqtaruk Territorial Park; UK Natural Environment Research Council ShrubTundra Grant [NE/M016323/1]; IPY; Memorial University; ArcticNet; Netherlands Organization for Scientific Research in the Tropics NWO [W84-194]; Ciencias sem Fronteiras and Coordenacao de Pessoal de Nivel Superior (CAPES, Brazil) [1091/13-1]; U.S. Fish and Wildlife Service/State Wildlife federal grant [T-15]; Australian Research Council Centre of Excellence for Coral Reef Studies [CE140100020]; Australian Research Council Future Fellowship [FT110100609]; University of Lodz; NSF DEB [1353139]; Catalan Government fellowships (DURSI) [1998FI-00596, 2001BEAI200208]; MECD Post-doctoral fellowship [EX2002-0022]; FONDECYT [1141037]; FONDAP [15150003]; [SFRH/BD/80488/2011]; [PD/BD/52597/2014]; [REN2000-0278/CCI]; [REN2001-003/GLO]; [CGL2016-79835-P]; [AGAUR SGR-2014453]; [SGR-2017-1005]; [FCT - SFRH / BPD / 82259 / 2011]; [OCE 95-21184]; [OCE-0099226]; [OCE 03-5234]; [OCE-0623874]; [OCE-1031061]; [OCE-1336206]; [DEB-1354563]; [OPP-1440435]12 month embargo; published online: 24 July 2018This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Global Spore Sampling Project: A global, standardized dataset of airborne fungal DNA.

Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world. Each sample represents fungal DNA extracted from 24 m3 of air. We applied a conservative bioinformatics pipeline that filtered out sequences that did not show strong evidence of representing a fungal species. The pipeline yielded 27,954 species-level operational taxonomic units (OTUs). Each OTU is accompanied by a probabilistic taxonomic classification, validated through comparison with expert evaluations. To examine the potential of the data for ecological analyses, we partitioned the variation in species distributions into spatial and seasonal components, showing a strong effect of the annual mean temperature on community composition

BioTIME:a database of biodiversity time series for the Anthropocene

Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of two, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology andcontextual information about each record.Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1 000 000 000 000 cm2).Time period and grain: BioTIME records span from 1874 to 2016. The minimum temporal grain across all datasets in BioTIME is year.Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton, and terrestrial invertebrates to small and large vertebrates.Software format: .csv and .SQ

Are rare species useful species? Obstacles to the conservation of tree diversity in the dry forest zone agro-ecosystems of Mesoamerica

Aim To test the potential to conserve rare dry forest tree and shrub species circa situm.Location Oaxaca, Mexico and Southern Honduras.Methods Local uses (timber, posts and firewood) of species were determined principally through semistructured interviews with 20 rural householders in each of four communities in Honduras and four in Oaxaca. Tree and shrub diversity inventories were carried out in a total of 227 forest patches and parcels of farmland in those eight communities. Species’ conservation priorities were determined using the star system of Hawthorne (1996) and IUCN listings.Results Despite a large number of useful species, remarkably few were also conservation priorities. Useful species were found to be substitutable as is illustrated by Bombacopsis quinata, Cordia alliodora, Guaiacum sanctum and G. coulteri.Conclusions In these areas, circa situm conservation is inhibited by the lack of species that are both rare and useful. Usefulness must be interpreted as a function of substitutability. Natural regeneration provides an abundance of diversity, farmers are unlikely to invest in the management of a species when suitable substitutes are freely available. The key to conserving rare species may be in maintaining or enhancing the value of the landscape elements in which they are found

BioTIME:a database of biodiversity time series for the Anthropocene

Abstract Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km² (158 cm²) to 100 km² (1,000,000,000,000 cm²). Time period and grain: BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format: .csv and .SQL