Motivation The availability of user‐friendly, high‐resolution global environmental datasets is crucial for bioclimatic modelling. For terrestrial environments, WorldClim has served this purpose since 2005, but equivalent marine data only became available in 2012, with pioneer initiatives like Bio‐ORACLE providing data layers for several ecologically relevant variables. Currently, the available marine data packages have not yet been updated to the most recent Intergovernmental Panel on Climate Change (IPCC) predictions nor to present times, and are mostly restricted to the top surface layer of the oceans, precluding the modelling of a large fraction of the benthic diversity that inhabits deeper habitats. To address this gap, we present a significant update of Bio‐ORACLE for new future climate scenarios, present‐day conditions and benthic layers (near sea bottom). The reliability of data layers was assessed using a cross‐validation framework against in situ quality‐controlled data. This test showed a generally good agreement between our data layers and the global climatic patterns. We also provide a package of functions in the R software environment (sdmpredictors) to facilitate listing, extraction and management of data layers and allow easy integration with the available pipelines for bioclimatic modelling. Main types of variable contained Surface and benthic layers for water temperature, salinity, nutrients, chlorophyll, sea ice, current velocity, phytoplankton, primary productivity, iron and light at bottom. Spatial location and grain Global at 5 arcmin (c. 0.08° or 9.2 km at the equator). Time period and grain Present (2000–2014) and future (2040–2050 and 2090–2100) environmental conditions based on monthly averages. Major taxa and level of measurement Marine biodiversity associated with sea surface and epibenthic habitats. Software format ASCII and TIFF grid formats for geographical information systems and a package of functions developed for R software.

Aim Ideally, datasets for species distribution modelling (SDM) contain evenly sampled records covering the entire distribution of the species, confirmed absences and auxiliary ecophysiological data allowing informed decisions on relevant predictors. Unfortunately, these criteria are rarely met for marine organisms for which distributions are too often only scantly characterized and absences generally not recorded. Here, we investigate predictor relevance as a function of modelling algorithms and settings for a global dataset of marine species. Location Global marine. Methods We selected well‐studied and identifiable species from all major marine taxonomic groups. Distribution records were compiled from public sources (e.g., OBIS, GBIF, Reef Life Survey) and linked to environmental data from Bio‐ORACLE and MARSPEC. Using this dataset, predictor relevance was analysed under different variations of modelling algorithms, numbers of predictor variables, cross‐validation strategies, sampling bias mitigation methods, evaluation methods and ranking methods. SDMs for all combinations of predictors from eight correlation groups were fitted and ranked, from which the top five predictors were selected as the most relevant. Results We collected two million distribution records from 514 species across 18 phyla. Mean sea surface temperature and calcite are, respectively, the most relevant and irrelevant predictors. A less clear pattern was derived from the other predictors. The biggest differences in predictor relevance were induced by varying the number of predictors, the modelling algorithm and the sample selection bias correction. The distribution data and associated environmental data are made available through the R package marinespeed and at http://marinespeed.org. Main conclusions While temperature is a relevant predictor of global marine species distributions, considerable variation in predictor relevance is linked to the SDM set‐up. We promote the usage of a standardized benchmark dataset (MarineSPEED) for methodological SDM studies.

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Being able to assess the quality and level of completeness of data has become indispensable in marine biodiversity research, especially when dealing with large databases that typically compile data from a variety of sources. Very few integrated databases offer quality flags on the level of the individual record, making it hard for users to easily extract the data that are fit for their specific purposes. This article describes the different steps that were developed to analyse the quality and completeness of the distribution records within the European and international Ocean Biogeographic Information Systems (EurOBIS and OBIS). Records are checked on data format, completeness and validity of information, quality and detail of the used taxonomy and geographic indications and whether or not the record is a putative outlier. The corresponding quality control (QC) flags will not only help users with their data selection, they will also help the data management team and the data custodians to identify possible gaps and errors in the submitted data, providing scope to improve data quality. The results of these quality control procedures are as of now available on both the EurOBIS and OBIS databases. Through the Biology portal of the European Marine Observation and Data Network (EMODnet Biology), a subset of EurOBIS records—passing a specific combination of these QC steps—is offered to the users. In the future, EMODnet Biology will offer a wide range of filter options through its portal, allowing users to make specific selections themselves. Through LifeWatch, users can already upload their own data and check them against a selection of the here described quality control procedures.Database URL: www.eurobis.org (www.iobis.org; www.emodnet-biology.eu/)

We propose the first correct special-purpose quantum circuits for preparation of Bell diagonal states (BDS), and implement them on the IBM Quantum computer, characterizing and testing complex aspects of their quantum correlations in the full parameter space. Among the circuits proposed, one involves only two quantum bits but requires adapted quantum tomography routines handling classical bits in parallel. The entire class of Bell diagonal states is generated, and several characteristic indicators, namely entanglement of formation and concurrence, CHSH non-locality, steering and discord, are experimentally evaluated over the full parameter space and compared with theory. As a by-product of this work, we also find a remarkable general inequality between “quantum discord” and “asymmetric relative entropy of discord”: the former never exceeds the latter. We also prove that for all BDS the two coincide.

The evolutionary and population demographic history of marine red algae in East Asia is poorly understood. Here, we reconstructed the phylogeographies of two upper intertidal species endemic to East Asia, Gelidiophycus divaricatus and G. freshwateri. Phylogenetic and phylogeographic inferences of 393 mitochondrial cox1, 128 plastid rbcL, and 342 nuclear ITS2 sequences were complemented with ecological niche models. Gelidiophycus divaricatus, a southern species adapted to warm water, is characterized by a high genetic diversity and a strong geographical population structure, characteristic of stable population sizes and sudden reduction to recent expansion. In contrast, G. freshwateri, a northern species adapted to cold temperate conditions, is genetically relatively homogeneous with a shallow population structure resulting from steady population growth and recent equilibrium. The overlap zone of the two species roughly matches summer and winter isotherms, indicating that surface seawater temperature is a key feature influencing species range. Unidirectional genetic introgression was detected at two sites on Jeju Island where G. divaricatus was rare while G. freshwateri was common, suggesting the occurrence of asymmetric natural hybrids, a rarely reported event for rhodophytes. Our results illustrate that Quaternary climate oscillations have left strong imprints on the current day genetic structure and highlight the importance of seawater temperature and sea level change in driving speciation in upper intertidal seaweed species.

Quantum computing promises to be the next disruptive technology, with numerous possible applications and implications for organizations and markets. Quantum computers exploit principles of quantum mechanics, such as superposition and entanglement, to represent data and perform operations on them. Both of these principles enable quantum computers to solve very specific, complex problems significantly faster than standard computers. Against this backdrop, this fundamental gives a brief overview of the three layers of a quantum computer: hardware, system software, and application layer. Furthermore, we introduce potential application areas of quantum computing and possible research directions for the field of information systems.

The quantum singular value transformation is a powerful quantum algorithm that allows one to apply a polynomial transformation to the singular values of a matrix that is embedded as a block of a unitary transformation. This paper shows how to perform the quantum singular value transformation for a matrix that can be embedded as a block of a Hamiltonian. The transformation can be implemented in a purely Hamiltonian context by the alternating application of Hamiltonians for chosen intervals: it is an example of the Quantum Alternating Operator Ansatz (generalized QAOA). We also show how to use the Hamiltonian quantum singular value transformation to perform inverse block encoding to implement a unitary of which a given Hamiltonian is a block. Inverse block encoding leads to novel procedures for matrix multiplication and for solving differential equations on quantum information processors in a purely Hamiltonian fashion.