Short, Multineedle Frequency Domain Reflectometry Sensor Suitable for Measuring Soil Water Content

Time domain reflectometry (TDR) is a well-established electromagnetic technique used to measure soil water content. Time domain reflectometry sensors have been combined with heat pulse sensors to produce thermo-TDR sensors. Thermo-TDR sensors are restricted to having relatively short needles to accurately measure soil thermal properties. Short needle lengths, however, can limit the accuracy of the TDR measurement of soil water content. Frequency domain reflectometry (FDR) sensors are an alternative to TDR sensors that can provide an inexpensive measurement of soil water content. The objective of this study was to determine whether short FDR sensors can accurately measure soil water content. We designed and constructed a short FDR sensor. For four soil types across a range of water contents, temperatures, and salt contents, we measured soil dielectric spectra with the short FDR sensor. A vector network analyzer was used to obtain soil dielectric spectra in the 1-MHz to 3-GHz frequency range. The ideal frequency of a short FDR sensor is the frequency at which the permittivity is not altered by changing temperature or salt content. The 47- to 200-MHz range was an ideal frequency range for measuring soil water content, and 70 MHz was the frequency least influenced by temperature and salt content. The short FDR sensor provided quick, continuous, stable, and cheap measurements of soil water content. Because of the promising performance of the short thermo-FDR sensor in laboratory studies, sensors should be evaluated in future field studies

Co-limitation towards lower latitudes shapes global forest diversity gradients

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers

The Psychological Science Accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

The Psychological Science Accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

Robust range finder through a laser pointer and a webcam

Research partially funded byC ́atedra Concytec en TICs of the National Universityof San Agust ́ın - Peru and the CNPq - BrazilConsejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concyte

A history of the MetaSUB consortium: Tracking urban microbes around the globe.

The MetaSUB Consortium, founded in 2015, is a global consortium with an interdisciplinary team of clinicians, scientists, bioinformaticians, engineers, and designers, with members from more than 100 countries across the globe. This network has continually collected samples from urban and rural sites including subways and transit systems, sewage systems, hospitals, and other environmental sampling. These collections have been ongoing since 2015 and have continued when possible, even throughout the COVID-19 pandemic. The consortium has optimized their workflow for the collection, isolation, and sequencing of DNA and RNA collected from these various sites and processing them for metagenomics analysis, including the identification of SARS-CoV-2 and its variants. Here, the Consortium describes its foundations, and its ongoing work to expand on this network and to focus its scope on the mapping, annotation, and prediction of emerging pathogens, mapping microbial evolution and antibiotic resistance, and the discovery of novel organisms and biosynthetic gene clusters