The handbook for standardised field and laboratory measurements in terrestrial climate-change experiments and observational studies

Climate change is a worldwide threat to biodiversity and ecosystem structure, functioning, and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate‐change impacts across the soil–plant–atmosphere continuum. An increasing number of climate‐change studies is creating new opportunities for meaningful and high‐quality generalisations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re‐use, synthesis, and upscaling. Many of these challenges relate to a lack of an established “best practice” for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km <sup>2</sup> resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km <sup>2</sup> pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

A muon-track reconstruction exploiting stochastic losses for large-scale Cherenkov detectors

IceCube is a cubic-kilometer Cherenkov telescope operating at the South Pole. The main goal of IceCube is the detection of astrophysical neutrinos and the identification of their sources. High-energy muon neutrinos are observed via the secondary muons produced in charge current interactions with nuclei in the ice. Currently, the best performing muon track directional reconstruction is based on a maximum likelihood method using the arrival time distribution of Cherenkov photons registered by the experiment\u27s photomultipliers. A known systematic shortcoming of the prevailing method is to assume a continuous energy loss along the muon track. However at energies >1 TeV the light yield from muons is dominated by stochastic showers. This paper discusses a generalized ansatz where the expected arrival time distribution is parametrized by a stochastic muon energy loss pattern. This more realistic parametrization of the loss profile leads to an improvement of the muon angular resolution of up to 20% for through-going tracks and up to a factor 2 for starting tracks over existing algorithms. Additionally, the procedure to estimate the directional reconstruction uncertainty has been improved to be more robust against numerical errors

Interaction of biological systems with static and ELF electric and magnetic fields

Although background levels of atmospheric electric and geomagnetic field levels are extremely low, over the past several decades, human beings and other life forms on this planet have been subjected to a dramatically changing electromagnetic milieu. An exponential increase in exposure to electromagnetic fields has occurred, largely because of such technological advances as the growth of electrical power generation and transmission systems, the increased use of wireless communications, and the use of radar. In addition, electromagnetic field generating devices have proliferated in industrial plants, office buildings, homes, public transportation systems, and elsewhere. Although significant increases have occurred in electromagnetic field strenghths spanning all frequency ranges, this symposium addresses only the impact of these fields at static and extremely low frequencies (ELF), primarily 50 and 60 Hz. This volume contains the proceedings of the symposium entitled /open quotes/Interaction of biological systems with static and ELF electric and magnetic fields/close quotes/. The purpose of the symposium was to provide a forum for discussions of all aspects of research on the interaction of static and ELF electromagnetic fields with biological systems. These systems include simple biophysical models, cell and organ preparations, whole animals, and man. Dosimetry, exposure system design, and artifacts in ELF bioeffects research were also addressed, along with current investigations that examine fundamental mechanisms of interactions between the fields and biological processes. Papers are indexed separately

Imputation of genotypes from low density (50,000 markers) to high density (700,000 markers) of cows from research herds in Europe, North America, and Australasia using 2 reference populations

Combining data from research herds may be advantageous, especially for difficult or expensive-to-measure traits (such as dry matter intake). Cows in research herds are often genotyped using low-density single nucleotide polymorphism (SNP) panels. However, the precision of quantitative trait loci detection in genome-wide association studies and the accuracy of genomic selection may increase when the low-density genotypes are imputed to higher density. Genotype data were available from 10 research herds: 5 from Europe [Denmark, Germany, Ireland, the Netherlands, and the United Kingdom (UK)], 2 from Australasia (Australia and New Zealand), and 3 from North America (Canada and the United States). Heifers from the Australian and New Zealand research herds were already genotyped at high density (approximately 700,000 SNP). The remaining genotypes were imputed from around 50,000 SNP to 700,000 using 2 reference populations. Although it was not possible to use a combined reference population, which would probably result in the highest accuracies of imputation, differences arising from using 2 high-density reference populations on imputing 50,000-marker genotypes of 583 animals (from the UK) were quantified. The European genotypes (n=4,097) were imputed as 1 data set, using a reference population of 3,150 that included genotypes from 835 Australian and 1,053 New Zealand females, with the remainder being males. Imputation was undertaken using population-wide linkage disequilibrium with no family information exploited. The UK animals were also included in the North American data set (n=1,579) that was imputed to high density using a reference population of 2,018 bulls. After editing, 591,213 genotypes on 5,999 animals from 10 research herds remained. The correlation between imputed allele frequencies of the 2 imputed data sets was high (>0.98) and even stronger (>0.99) for the UK animals that were part of each imputation data set. For the UK genotypes, 2.2% were imputed differently in the 2 high-density reference data sets used. Only 0.025% of these were homozygous switches. The number of discordant SNP was lower for animals that had sires that were genotyped. Discordant imputed SNP genotypes were most common when a large difference existed in allele frequency between the 2 imputed genotype data sets. For SNP that had =20% discordant genotypes, the difference between imputed data sets of allele frequencies of the UK (imputed) genotypes was 0.07, whereas the difference in allele frequencies of the (reference) high-density genotypes was 0.30. In fact, regions existed across the genome where the frequency of discordant SNP was higher. For example, on chromosome 10 (centered on 520,948 bp), 52 SNP (out of a total of 103 SNP) had =20% discordant SNP. Four hundred and eight SNP had more than 20% discordant genotypes and were removed from the final set of imputed genotypes. We concluded that both discordance of imputed SNP genotypes and differences in allele frequencies, after imputation using different reference data sets, may be used to identify and remove poorly imputed SNP

Treatment with LL-37 Peptide Enhances Antitumor Effects Induced by CpG Oligodeoxynucleotides Against Ovarian Cancer

There is an urgent need for innovative therapies against ovarian cancer, one of the leading causes of death from gynecological cancers in the United States. Immunotherapy employing Toll-like receptor (TLR) ligands, such as CpG oligodeoxynucleotides (CpG-ODN), may serve as a potentially promising approach in the control of ovarian tumors. The CpG-ODN requires intracellular delivery into the endosomal compartment, where it can bind to TLR9 in order to activate the immune system. In the current study, we aim to investigate whether the antimicrobial polypeptide from the cathelicidin family, LL-37, could enhance the immunostimulatory effects of CpG-ODN by increasing the uptake of CpG-ODN into the immune cells, thus enhancing the antitumor effects against ovarian cancer. We found that treatment with the combination of CpG-ODN and LL-37 generated significantly better therapeutic antitumor effects and enhanced survival in murine ovarian tumor-bearing mice compared with treatment with CpG-ODN or LL-37 alone. We also observed that treatment with the combination of CpG-ODN and LL-37 enhanced proliferation and activation of natural killer (NK) cells, but not CD4+ or CD8+ T cells, in the peritoneal cavity. Furthermore, in vivo antibody depletion experiments indicated that peritoneal NK cells played a critical role in the observed antitumor effects. Thus, our data suggest that the combination of CpG-ODN with LL-37 peptide may lead to the control of ovarian tumors through the activation of innate immunity