A simple model for predicting snow albedo decay using observations from the Community Collaborative Rain, Hail, and Snow-Albedo (CoCoRAHS-Albedo) Network

The albedo of seasonal snow cover plays an important role in the global climate system due to its influence on Earth’s radiation budget and energy balance. Volunteer CoCoRaHS-Albedo observers collected 3,249 individual daily albedo, snow depth, and density measurements using standardized techniques at dozens of sites across New Hampshire, USA over four winter seasons. The data show that albedo increases rapidly with snow depth up to ~ 0.14 m. Multiple linear regression models using snowpack age, snow depth or density, and air temperature provide reasonable approximations of surface snow albedo during times of albedo decay. However, the linear models also reveal systematic biases that highlight an important non-linearity in snow albedo decay. Modeled albedo values are reasonably accurate within the range of 0.6 to 0.9, but exhibit a tendency to over-estimate lower albedo values and under-estimate higher albedo values. We hypothesize that rapid reduction in high albedo fresh snow results from a decrease in snow specific surface area, while during melt-events the presence of liquid water in the snowpack accelerates metamorphism and grain growth. We conclude that the CoCoRaHS-Albedo volunteer observer network provides useful snow albedo, depth, and density measurements and serves as an effective model for future measurement campaigns

New Hampshire Coastal Flood Risk Summary Part 1: Science

The New Hampshire Coastal Flood Risk Summary – Part 1: Science provides a synthesis of the state of the science relevant to coastal flood risks in New Hampshire. Specifically, this document provides updated projections of sea-level rise, coastal storms, groundwater rise, precipitation, and freshwater flooding for coastal New Hampshire. This information is intended to serve as the scientific foundation for the companion New Hampshire Coastal Flood Risk Summary - Part II: Guidance for Using Scientific Projections and is intended to inform coastal land use planning and decision-making

Effect of conjugated linoleic acid on testosterone levels in vitro and in vivo after an acute bout of resistance exercise.

The purposes of the present study were to investigate the effect of conjugated linoleic acid (CLA) supplementation on testosterone levels in vitro on a cell line derived from Leydig cells (R2C) and in vivo in the blood of physically active subjects before and after a resistance exercise bout. In vitro R2C cells were treated with different CLA concentrations (0-30 μM) for 24 and 48 hours. After treatment, supernatant media were tested to determine testosterone secretion. The CLA increased the testosterone secretion only after 48 hours. In vivo, 10 resistance-trained male subjects, in a double-blind placebo-controlled and crossover study design were randomized for 3 weeks of either 6 g·d⁻¹ CLA or placebo. Blood was drawn pre and post each resistance exercise bout to determine the total testosterone and sex hormone-binding globulin (SHBG) levels. No significant differences were observed for total testosterone or SHBG pre and post each resistance exercise bout; although after the resistance exercise bouts, total testosterone increased moderately (effect size = moderate), whereas after CLA supplementation, there was a large increase in total testosterone (effect size = large). CLA supplementation induced an increase in testosterone levels in Leydig cells in vitro after 48 hours but not in vivo before and after a resistance exercise bout. These findings suggest that CLA supplementation may promote testosterone synthesis through a molecular pathway that should be investigated in the future, although this effect did not have an anabolic relevance in our in vivo model

Evaluation of a loop-mediated isothermal amplification method for the detection of listeria monocytogenes in dairy food

Objective of the present study was to test the performances of a loop-mediated isothermal amplification (LAMP)-based method for the detection of Listeria monocytogenes, with particular focus on the dairy products. The specificity of the method was evaluated on 42 different Listeria spp. strains from collections, food and environmental samples. 100% (32 of 32) of the L. monocytogenes strains were correctly recognised, and none of other 10 Listeria spp. strains was misidentified. The sensitivity was evaluated on four L. monocytogenes strains from different sources. The instrument was able to detect 10-400 CFU/mL. The ability to detect low initial numbers of L. monocytogenes (0.3- 0.7 Log CFU/g) was also evaluated, in duplicate, in pasteurised milk (whole and skimmed) and dairy samples (fresh ricotta, crescenza, mascarpone, mozzarella, cottage cheese, cream cheese, taleggio, gorgonzola). The analysis was performed after 18, 24 and 48 h of incubation, and was coupled with the count of L. monocytogenes in the broth. Microbial loads were insufficient to achieve a positive result after 18 and 24 h in most of the samples; after 48 h, all the products, except taleggio and one gorgonzola sample, were identified as positive; the sensitivity of the method when applied to contaminated dairy foods was about 5 Log CFU/g. The LAMP method tested can be considered a very useful tool, as it is a costeffective and easy-functioning method. The preliminary data obtained should be confirmed with a validation process taking into account different food typologies

Patterns and Perceptions of Climate Change in a Biodiversity Conservation Hotspot

Quantifying local people's perceptions to climate change, and their assessments of which changes matter, is fundamental to addressing the dual challenge of land conservation and poverty alleviation in densely populated tropical regions To develop appropriate policies and responses, it will be important not only to anticipate the nature of expected changes, but also how they are perceived, interpreted and adapted to by local residents. The Albertine Rift region in East Africa is one of the world's most threatened biodiversity hotspots due to dense smallholder agriculture, high levels of land and resource pressures, and habitat loss and conversion. Results of three separate household surveys conducted in the vicinity of Kibale National Park during the late 2000s indicate that farmers are concerned with variable precipitation. Many survey respondents reported that conditions are drier and rainfall timing is becoming less predictable. Analysis of daily rainfall data for the climate normal period 1981 to 2010 indicates that total rainfall both within and across seasons has not changed significantly, although the timing and transitions of seasons has been highly variable. Results of rainfall data analysis also indicate significant changes in the intra-seasonal rainfall distribution, including longer dry periods within rainy seasons, which may contribute to the perceived decrease in rainfall and can compromise food security. Our results highlight the need for fine-scale climate information to assist agro-ecological communities in developing effective adaptive management

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Putting the capital ‘A’ in CoCoRAHS: an experimental programme to measure albedo using the Community Collaborative Rain, Hail & Snow (CoCoRaHS) Network

The Community Collaborative Rain, Hail & Snow (CoCoRaHS) Network is a community‐based network of weather observers and the largest provider of daily precipitation observations in the USA. In this study, we embrace the CoCoRaHS mission to use low‐cost measurement tools, provide training and education, and utilize an interactive website to create the first volunteer snow albedo network to collect high‐quality albedo data for research and education applications. We trained a sub‐set of 18 CoCoRaHS observers in the state of New Hampshire to collect albedo, snow depth, and snow density between 23 November 2011 and 15 March 2012. At less than $700 per observer, CoCoRAHS data measured using an Apogee MP‐200 pyranometer fall within ±0.05 of albedo values collected from a Kipp and Zonen CMA6 at local solar noon. CoCoRAHS values range from 0.99 for fresh snow to 0.34 for shallow, aged snow. Snow‐free albedo ranges from 0.09 to 0.39, depending on the underlying ground cover. In the 2011/2012 dataset, albedo increases logarithmically with snow depth and decreases linearly with snow density. The latter relationship is inferred to be a proxy for increasing snow grain size as snowpack ages and compacts, supported by spectral albedo measurements collected with an Analytical Spectral Devices FieldSpec 4 spectrometer. Copyright © 2013 John Wiley & Sons, Ltd