More Like this

1. Conductive Silk‐Based Composites Using Biobased Carbon Materials

   https://doi.org/10.1002/adma.201904720  

   López Barreiro, Diego ; Martín‐Moldes, Zaira ; Yeo, Jingjie ; Shen, Sabrina ; Hawker, Morgan J. ; Martin‐Martinez, Francisco J. ; Kaplan, David L. ; Buehler, Markus J. ( September 2019 , Advanced Materials)

   There is great interest in developing conductive biomaterials for the manufacturing of sensors or flexible electronics with applications in healthcare, tracking human motion, or in situ strain measurements. These biomaterials aim to overcome the mismatch in mechanical properties at the interface between typical rigid semiconductor sensors and soft, often uneven biological surfaces or tissues for in vivo and ex vivo applications. Here, the use of biobased carbons to fabricate conductive, highly stretchable, flexible, and biocompatible silk‐based composite biomaterials is demonstrated. Biobased carbons are synthesized via hydrothermal processing, an aqueous thermochemical method that converts biomass into a carbonaceous material that can be applied upon activation as conductive filler in composite biomaterials. Experimental synthesis and full‐atomistic molecular dynamics modeling are combined to synthesize and characterize these conductive composite biomaterials, made entirely from renewable sources and with promising applications in fields like biomedicine, energy, and electronics.

    

   more » « less
2. North Temperate Lakes LTER: Phytoplankton - Trout Lake Area 1984 - 2006

   https://doi.org/10.6073/pasta/e876543ebe841bf7608f800a6cfb357e  

   Magnuson, John ; Carpenter, Stephen ; Stanley, Emily ( January 2023 , Environmental Data Initiative)

   Phytoplankton samples from the seven northern Wisconsin LTER lakes in the Trout Lake area (Allequash, Big Muskellunge, Crystal, Sparkling, and Trout lakes and bog lakes 27-02 [Crystal Bog], and 12-15 [Trout Bog]) are collected six times per year at the deep hole sampling station at the same time as our other limnological sampling is conducted. We use a peristaltic pump and tubing, collecting a separate sample from the epilimnion, metalimnion and hypolimnion for most of the lakes. For 27-2 Bog Lake, which is only 2m deep, we collect one 0-2m composite sample. The samples are preserved with Lugols iodine solution. We create a single hypsometrically pooled composite sample per lake from subsamples of the strata samples. The pooled samples are sent to PhycoTech, Inc., a private lab specializing in phytoplankton analysis, to be made into permanent slide mounts. The slide mounts, 3 slides per sample, are archived at the University of Wisconsin - Madison Zoology Museum Phytoplankton are identified to species using an inverted microscope (Utermohl technique) and are reported as natural unit (i.e., colonies, filaments, or single cells) densities per mL, cell densities per mL, and algal biovolume densities per mL. Multiple entries for the same species on the same date may be due to different variants or vegetative states - (e.g., colonial or attached vs. free cell.) Biovolumes for individual cells of each species are determined during the counting procedure by obtaining cell measurements needed to calculate volumes for geometric solids (e.g., cylinders, spheres, truncated cones) corresponding to actual cell shapes. Biovolume concentrations are then computed by mulitplying the average cell biovolume by the cell densities in the water sample. Note that one million cubicMicrometers of biovolume PerMilliliter of water are equal to a biovolume concentration of one cubicMillimeterPerMilliliter. Assuming a cell density equal to water, a cubicMillimeterPerMilliliter of biovolume converts to a biomass concentration of one milligramPerLiter. Sampling Frequency: 6 samples per year Number of sites: 7 

   more » « less
3. North Temperate Lakes LTER: Phytoplankton - Madison Lakes Area 1995 - current

   https://doi.org/10.6073/pasta/bd03330e83fc52a5442bb39e131c95e9  

   Magnuson, John J. ; Carpenter, Stephen R. ; Stanley, Emily H. ( January 2022 , Environmental Data Initiative)

   Phytoplankton samples for the 4 southern Wisconsin LTER lakes (Mendota, Monona, Wingra, Fish) have been collected for analysis by LTER since 1995 (1996 Wingra, Fish) when the southern Wisconsin lakes were added to the North Temperate Lakes LTER project. Samples are collected as a composite whole-water sample and are preserved in gluteraldehyde. Composite sample depths are 0-8 meters for Lake Mendota (to conform to samples collected and analyzed since 1990 for a UW/DNR food web research study), and 0-2 meters for the other three lakes. A tube sampler is used for the 0-8 m Lake Mendota samples; samples for the other lakes are obtained by collecting water at 1-meter intervals using a Kemmerer water sampler and compositing the samples in a bucket. Samples are taken in the deep hole region of each lake at the same time and location as other limnological sampling. Phytoplankton samples are analyzed by PhycoTech, Inc., a private lab specializing in phytoplankton analyses (see data protocol for procedures). Samples for Wingra and Fish lakes are archived but not routinely counted. Permanent slide mounts (3 per sample) are prepared for all analyzed Mendota and Monona samples as well as 6 samples per year for Wingra and Fish; the slide mounts are archived at the University of Wisconsin - Madison Zoology Museum. Phytoplankton are identified to species using an inverted microscope (Utermohl technique) and are reported as natural unit (i.e., colonies, filaments, or single cells) densities per mL, cell densities per mL, and algal biovolume densities per mL. Multiple entries for the same species on the same date may be due to different variants or vegetative states - (e.g., colonial or attached vs. free cell.) Biovolumes for individual cells of each species are determined during the counting procedure by obtaining cell measurements needed to calculate volumes for geometric solids (e.g., cylinders, spheres, truncated cones) corresponding to actual cell shapes. Biovolume concentrations are then computed by mulitplying the average cell biovolume by the cell densities in the water sample. Note that one million cubicMicrometers of biovolume PerMilliliter of water are equal to a biovolume concentration of one cubicMillimeterPerMilliliter. Assuming a cell density equal to water, a cubicMillimeterPerMilliliter of biovolume converts to a biomass concentration of one milligramPerLiter. Sampling Frequency: bi-weekly during ice-free season from late March or early April through early September, then every 4 weeks through late November; sampling is conducted usually once during the winter (depending on ice conditions). Number of sites: 4 Several taxonomic updates have been made to this dataset February 2013, see methods for details. 

   more » « less
4. Biomass losses resulting from insect and disease invasions in US forests

   https://doi.org/10.1073/pnas.1820601116  

   Fei, Songlin ; Morin, Randall S. ; Oswalt, Christopher M. ; Liebhold, Andrew M. ( January 2019 , Proceedings of the National Academy of Sciences)

   Worldwide, forests are increasingly affected by nonnative insects and diseases, some of which cause substantial tree mortality. Forests in the United States have been invaded by a particularly large number (>450) of tree-feeding pest species. While information exists about the ecological impacts of certain pests, region-wide assessments of the composite ecosystem impacts of all species are limited. Here we analyze 92,978 forest plots distributed across the conterminous United States to estimate biomass loss associated with elevated mortality rates caused by the 15 most damaging nonnative forest pests. We find that these species combined caused an additional (i.e., above background levels) tree mortality rate of 5.53 TgC per year. Compensation, in the form of increased growth and recruitment of nonhost species, was not detectable when measured across entire invaded ranges but does occur several decades following pest invasions. In addition, 41.1% of the total live forest biomass in the conterminous United States is at risk of future loss from these 15 pests. These results indicate that forest pest invasions, driven primarily by globalization, represent a huge risk to US forests and have significant impacts on carbon dynamics. 

   more » « less
5. Host biology, ecology and the environment influence microbial biomass and diversity in 101 marine fish species

   https://doi.org/10.1038/s41467-022-34557-2  

   Minich, Jeremiah J. ; Härer, Andreas ; Vechinski, Joseph ; Frable, Benjamin W. ; Skelton, Zachary R. ; Kunselman, Emily ; Shane, Michael A. ; Perry, Daniela S. ; Gonzalez, Antonio ; McDonald, Daniel ; et al ( December 2022 , Nature Communications)

   Abstract Fish are the most diverse and widely distributed vertebrates, yet little is known about the microbial ecology of fishes nor the biological and environmental factors that influence fish microbiota. To identify factors that explain microbial diversity patterns in a geographical subset of marine fish, we analyzed the microbiota (gill tissue, skin mucus, midgut digesta and hindgut digesta) from 101 species of Southern California marine fishes, spanning 22 orders, 55 families and 83 genera, representing ~25% of local marine fish diversity. We compare alpha, beta and gamma diversity while establishing a method to estimate microbial biomass associated with these host surfaces. We show that body site is the strongest driver of microbial diversity while microbial biomass and diversity is lowest in the gill of larger, pelagic fishes. Patterns of phylosymbiosis are observed across the gill, skin and hindgut. In a quantitative synthesis of vertebrate hindguts (569 species), we also show that mammals have the highest gamma diversity when controlling for host species number while fishes have the highest percent of unique microbial taxa. The composite dataset will be useful to vertebrate microbiota researchers and fish biologists interested in microbial ecology, with applications in aquaculture and fisheries management. 

   more » « less