The enormous repetitive Antarctic krill genome reveals environmental adaptations and population insights

Antarctic krill (Euphausia superba) is Earth’smost abundant wild animal, and its enormous biomass is vital to the Southern Ocean ecosystem. Here, we report a 48.01-Gb chromosome-level Antarctic krill genome, whose large genome size appears to have resulted from inter-genic transposable element expansions. Our assembly reveals the molecular architecture of the Antarctic krill circadian clock and uncovers expanded gene families associated with molting and energy metabolism, providing insights into adaptations to the cold and highly seasonal Antarctic environment. Population-level genome re-sequencing from four geographical sites around the Antarctic continent reveals no clear population structure but highlights natural selection associated with environmental variables. An apparent drastic reduction in krill population size 10 mya and a subsequent rebound 100 thousand years ago coincides with climate change events. Our findings uncover the genomic basis of Antarctic krill adaptations to the Southern Ocean and provide valuable resources for future Antarctic research

Complex network characteristics of the planned subway station network in Hangzhou (2005-2022)

The complex network characteristic of the planned subway station system is of great significance to the centrality layout of the existing urban areas. The three phases of the Hangzhou subway plan from 2005-2022 are selected as a case, and the complex network analysis method is used to study the centrality characteristic of the planned subway station system. The study found that with construction, the network density, clustering coefficient, average shortcut distance, all centrality indicators of the network gradually decreased; but in phase Ⅲadjustment, the average shortcut distance, three centrality potential indicators have all rebounded substantially. The newly-added airport rail express line has greatly increased the overall cohesion of the original subway network. The subway station networks of five planning stages all have smaller clustering coefficients and larger average shortcut distances, but none of them have a small-world characteristic, and the scale-free characteristic is still not obvious

Comprehensive Evaluation of Low Nitrogen Tolerance in Oat (<i>Avena sativa</i> L.) Seedlings

In oat production, the over-application of nitrogen (N) fertilizer in fields due to low N fertilizer use efficiency not only increases production costs but also causes environmental pollution. Currently, mining low N-tolerant oat varieties is an important way to promote sustainable agriculture. In this study, 30 oat varieties were grown in a seedling culture with two treatments of normal N (10 mM NH4NO3) and low N (1.25 mM NH4NO3), and the correlations between agronomic traits and plant N content and low N tolerance coefficients and indices were determined, which can be used as indicators for the evaluation of low N-tolerant oat varieties. Coefficient of variation, correlation analysis, principal component analysis, partial least-squares discrimination analysis, random forest analysis, least absolute shrinkage and selection operator regression and model evaluation, and membership function analysis were used for in-depth analysis of these indicators. Plant N content, root–crown ratio, and dry weight of aboveground plant parts were found to be important indicators of low N tolerance in oats. According to the membership function ranking of the 30 selected oat varieties, Jiayan 2, Qingyongjiu 035, and Qingyin 2 had strong tolerance to low N stress and Qingyongjiu 003, Qingyongjiu 021, and Qingyongjiu 016 had poor tolerance to low N stress. Thus, this study provides a reliable and comprehensive method for evaluating the low N tolerance of oat varieties as well as a reference for screening other low N-tolerant plants

Projected changes in near-surface wind speed over Iberian Peninsula and associated atmosphere-ocean oscillations

Trabajo presentado en EGU General Assembly, celebrada en Viena (Austria) del 23 al 27 de mayo de 2022.Near-surface wind speed has been one of the forgotten parts of the climate system due to poor quality of observational data and the challenges in its homogenization. During the last two decades the interest in near-surface wind variability and trends has increased and two main phenomena have been found: the first one is termed ¿stilling¿, indicating a decline of near-surface wind speed between around 1978 and 2010; the other is related to an interruption in the ¿stilling¿ since 2000s, known as a ¿reversal¿ of the wind speed trends at global and regional scales like China, Sweden or Iberian Peninsula, among others. There are uncertainties about the plausible causes of the variability of the near-surface wind speed, but last research pointed to the role played by decadal atmosphere-ocean oscillations. Under this assumption and a climate change context, a new ¿stilling¿ phase is expected for the 21st century. In order to advance in the evaluation and attribution of the causes of the ¿stilling¿ and the ¿reversal¿ phenomena, the main objective of this study is to analyze projected changes in near-surface wind speed at regional scale, e.g. the Iberian Peninsula. The methodology consists in a comparison between observed wind speed data of the Iberian Peninsula and historical simulations from CMIP6 models, followed by a study of wind speed variability and trends of CMIP6 models under low to high greenhouse gas forcing scenarios in the future. The analyses will focus on quantifying the long-term changes in near surface wind speed and their relationship with dominant modes of variability in the Pacific and Atlantic (e.g., the Pacific Decadal Oscillation and the Atlantic Multi-decadal Oscillation