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Landscape genomic analyses associating genetic variation with environmental variables are powerful tools for studying molecular signatures of species' local adaptation and for detecting candidate genes under selection. The development of landscape genomics over the past decade has been spurred by improvements in resolutions of genomic and environmental datasets, allegedly increasing the power to identify putative genes underlying local adaptation in non‐model organisms. Although these associations have been successfully applied to numerous species across a diverse array of taxa, the spatial scale of environmental predictor variables has been largely overlooked, potentially limiting conclusions to be reached with these methods. To address this knowledge gap, we systematically evaluated performances of genotype–environment association (GEA) models using predictor variables at multiple spatial resolutions. Specifically, we used multivariate redundancy analyses to associate whole‐genome sequence data from the plant Arabis alpina L. collected across four neighboring valleys in the western Swiss Alps, with very high‐resolution topographic variables derived from digital elevation models of grain sizes between 0.5 m and 16 m. These comparisons highlight the sensitivity of landscape genomic models to spatial resolution, where the optimal grain sizes were specific to variable type, terrain characteristics, and study extent. To assist in selecting variables at appropriate spatial resolutions, we demonstrate a practical approach to produce, select, and integrate multiscale variables into GEA models. After generalizing fine‐grained variables to multiple spatial resolutions, a forward selection procedure is applied to retain only the most relevant variables for a particular context. Depending on the spatial resolution, the relevance for topographic variables in GEA studies calls for integrating multiple spatial scales into landscape genomic models. By carefully considering spatial resolutions, candidate genes under selection by a more realistic range of pressures can be detected for downstream analyses, with important applied implications for experimental research and conservation management of natural populations.

The vulnerability of alpine environments to climate change presses an urgent need to accurately model and understand these ecosystems. Popularity in the use of digital elevation models (DEMs) to derive proxy environmental variables has increased over the past decade, particularly as DEMs are relatively cheaply acquired at very high resolutions (VHR; <1 m spatial resolution). Here, we implement a multiscale framework and compare DEM-derived variables produced by Light Detection and Ranging (LiDAR) and stereo-photogrammetry (PHOTO) methods, with the aim of assessing their relevance and utility in species distribution modelling (SDM). Using a case study on the arctic-alpine plant, Arabis alpina, in two valleys in the western Swiss Alps, we show that both LiDAR and PHOTO technologies can be relevant for producing DEM-derived variables for use in SDMs. We demonstrate that PHOTO DEMs, up to a spatial resolution of at least 1 m, rivalled the accuracy of LiDAR DEMs, largely owing to the customizability of PHOTO DEMs to the study sites compared to commercially available LiDAR DEMs. We obtained DEMs at spatial resolutions of 6.25 cm–8 m for PHOTO and 50 cm–32 m for LiDAR, where we determined that the optimal spatial resolutions of DEM-derived variables in SDM were between 1 and 32 m, depending on the variable and site characteristics. We found that the reduced extent of PHOTO DEMs altered the calculations of all derived variables, which had particular consequences on their relevance at the site with heterogenous terrain. However, for the homogenous site, SDMs based on PHOTO-derived variables generally had higher predictive powers than those derived from LiDAR at matching resolutions. From our results, we recommend carefully considering the required DEM extent to produce relevant derived variables. We also advocate implementing a multiscale framework to appropriately assess the ecological relevance of derived variables, where we caution against the use of VHR-DEMs finer than 50 cm in such studies.

Effective biodiversity conservation requires knowledge of species' distributions across large areas, yet prevalence data for marine sessile species is scarce, with traditional variables often unavailable at appropriate temporal and spatial resolutions. As marine organism distributions generally depend on terrain heterogeneity, topographic variables derived from digital elevation models (DEMs) can be useful proxies in ecological modelling, given appropriate spatial resolutions. Here, we use three reef‐building Acropora coral species across the Great Barrier Reef, Australia, in a case study to (1) assess high‐resolution bathymetry DEM sources for accuracy, (2) harness their derived topographic variables for regional coral species distribution models (SDMs), and (3) develop a transferable framework to produce, select and integrate multi‐resolution variables into marine spatial models. For this, we obtained and processed three distinct bathymetric digital depth models that we treat as DEMs, which are available across the GBR extent: (i) Allen Coral Atlas (ACA) at 10 m, (ii) DeepReef at 30 m and (iii) DeepReef at 100 m. We generalised the three DEMs to multiple nested spatial resolutions (15 m–120 m) and derived the same eight topographic variables to assess SDM sensitivity to bathymetry source and spatial resolution. The ACA and DeepReef DEMs shared similar vertical accuracies, each producing topographic variables relevant to marine SDMs. Slope and vector ruggedness measure (VRM), capturing hydrodynamic movement and shelter or exposure, were the most relevant variables in SDMs of all three species. Interestingly, variables at the finest resolution (15 m) were not always the most relevant for producing accurate coral SDMs, with optimal resolutions between 15 and 60 m depending on the variable type and species. Using multi‐resolution topographic variables in SDMs provided nuanced insights into the multiscale drivers of regional coral distributions. Drawing from this case study, we provide a practical and transferable framework to facilitate the adoption of multiscale SDMs for better‐informed conservation and management planning. We investigate the application of multiscale topographic variables obtained from freely available bathymetric digital elevation models (DEMs) for ecological modelling in seascape environments. Using a case study of three Acropora coral species in the Great Barrier Reef, we demonstrate that various spatial resolutions can effectively model coral distributions, thus allowing us to identify the key topographic variables in these models. Integrating multiscale frameworks into generating environmental predictor variables has the potential to improve ecological models, supporting the development of robust and effective marine conservation and management planning.

Summary For most organisms, early life‐history stages are the most sensitive to environmental stress and so transgenerational phenotypic plasticity, whereby the parental environment and offspring environment interact to alter the phenotype of the offspring, is viewed as key to promoting persistence in the face of environmental change. While there has been long‐standing interest in the role of transgenerational plasticity via the maternal line (traditionally the field of maternal effects), increasingly it appears that paternal effects can also play a role. Despite the emerging role of paternal effects in studies of global change, key knowledge gaps remain: first, whether paternal effects act to increase or decrease offspring performance remains largely unexplored; second, the relative roles of maternal and paternal effects are rarely disentangled; and third, the role of environmental variation, a key determinant of the benefits of transgenerational plasticity, has not been explored with regard to paternal effects. Here, we explore all three issues using the marine tubeworm Galeolaria caespitosa, an important habitat‐forming species in southern Australia. We found that both paternal and maternal experiences affected key stages of offspring performance (fertilization and larval development) and, surprisingly, paternal effects were often stronger than maternal effects. Furthermore, we found that paternal effects often reduced offspring performance, especially when environments varied compared with when environments were stable. Our results suggest that, while transgenerational plasticity may play an important role in modifying the impacts of global change, these effects are not uniformly positive. Importantly, paternal effects can be as strong, or stronger, than maternal effects and environmental variability strongly alters the impacts of paternal effects. Lay Summary

Global warming and rising sea temperatures are pushing many reef-building coral species towards extinction. As thermal tolerance in corals is partially heritable, identifying genes under thermal selection is critical for targeted biodiversity management. However, it remains unclear how large breaks in connectivity (>100 km of open sea) affect the spread of adaptive alleles for different coral species in discontinuous reef networks such as the West Indian Ocean (WIO). To address this, we applied a seascape genomics approach to model (i) population connectivity and (ii) thermal adaptive potentials for two keystone coral species, Acropora muricata and Pocillopora damicornis, across the WIO. For both species, corals from the Seychelles were predominantly genetically isolated from corals in Rodrigues and Mauritius, putatively an effect of regional oceanographic barriers. Furthermore, sea currents during reproductive periods better predicted genetic connectivity than did Euclidean distances for both species, highlighting that connectivity models can serve as proxies to understand dispersal potential depending on reproductive strategies. Spatial patterns of neutral genetic variation were best explained by sea surface temperature variability and mean degree heating weeks. When used in genotype– environment association (GEA) analyses, we identified hundreds of loci under putative thermal selection from linked to known heat stress responses. In A. muricata, five Sacsin genes—co- chaperones of the Hsp70 heat-shock protein involved in thermal stress response—were identified, alongside genes related to immune defence, antioxidant response, signalling, and protein folding. In contrast, only the centromere protein V, involved in mitosis, was enriched in P. damicornis. By integrating patterns of gene flow with molecular adaptations to estimate species-specific adaptive potentials, we found that large sea distances and strong oceanographic barriers inhibit the genetic exchange of adapted genotypes across the WIO, providing valuable insights to guide local and regional biodiversity management in this region.

The process by which sheared suspensions go through a dramatic change in viscosity is known as discontinuous shear thickening. Although well-characterized on the macroscale, the microscopic mechanisms at play in this transition are still poorly understood. Here, by developing new experimental procedures based on quartz-tuning fork atomic force microscopy, we measure the pairwise frictional profile between approaching pairs of polyvinyl chloride and cornstarch particles in solvent. We report a clear transition from a low-friction regime, where pairs of particles support a finite normal load, while interacting purely hydrodynamically, to a high-friction regime characterized by hard repulsive contact between the particles and sliding friction. Critically, we show that the normal stress needed to enter the frictional regime at nanoscale matches the critical stress at which shear thickening occurs for macroscopic suspensions. Our experiments bridge nano and macroscales and provide long needed demonstration of the role of frictional forces in discontinuous shear thickening. Shear thickening characterizes liquid suspensions of particles that reversibly solidify subject to stress. Here, Comtet et al . show that shear thickening occurs at the transition from lubricated contacts to frictional contacts at a single-particle level, which can be linked to the change in macroscopic rheology.

Angiotensin-converting enzyme 2 (ACE2) is an endogenous counter-regulator of the renin–angiotensin hormonal cascade. We assessed whether plasma ACE2 concentrations were associated with greater risk of death or cardiovascular disease events. We used data from the Prospective Urban Rural Epidemiology (PURE) prospective study to conduct a case-cohort analysis within a subset of PURE participants (from 14 countries across five continents: Africa, Asia, Europe, North America, and South America). We measured plasma concentrations of ACE2 and assessed potential determinants of plasma ACE2 levels as well as the association of ACE2 with cardiovascular events. We included 10 753 PURE participants in our study. Increased concentration of plasma ACE2 was associated with increased risk of total deaths (hazard ratio [HR] 1·35 per 1 SD increase [95% CI 1·29–1·43]) with similar increases in cardiovascular and non-cardiovascular deaths. Plasma ACE2 concentration was also associated with higher risk of incident heart failure (HR 1·27 per 1 SD increase [1·10–1·46]), myocardial infarction (HR 1·23 per 1 SD increase [1·13–1·33]), stroke (HR 1·21 per 1 SD increase [1·10–1·32]) and diabetes (HR 1·44 per 1 SD increase [1·36–1·52]). These findings were independent of age, sex, ancestry, and traditional cardiac risk factors. With the exception of incident heart failure events, the independent relationship of ACE2 with the clinical endpoints, including death, remained robust after adjustment for BNP. The highest-ranked determinants of ACE2 concentrations were sex, geographic ancestry, and body-mass index (BMI). When compared with clinical risk factors (smoking, diabetes, blood pressure, lipids, and BMI), ACE2 was the highest ranked predictor of death, and superseded several risk factors as a predictor of heart failure, stroke, and myocardial infarction. Increased plasma ACE2 concentration was associated with increased risk of major cardiovascular events in a global study. Canadian Institute of Health Research, Heart & Stroke Foundation of Canada, and Bayer.

Patients receiving in-centre hemodialysis are at high risk of exposure to SARS-CoV-2 and death if infected. One dose of the BNT162b2 SARS-CoV-2 vaccine is efficacious in the general population, but responses in patients receiving hemodialysis are uncertain. We obtained serial plasma from patients receiving hemodialysis and health care worker controls before and after vaccination with 1 dose of the BNT162b2 mRNA vaccine, as well as convalescent plasma from patients receiving hemodialysis who survived COVID-19. We measured anti–receptor binding domain (RBD) immunoglobulin G (IgG) levels and stratified groups by evidence of previous SARS-CoV-2 infection. Our study included 154 patients receiving hemodialysis (135 without and 19 with previous SARS-CoV-2 infection), 40 controls (20 without and 20 with previous SARS-CoV-2 infection) and convalescent plasma from 16 patients. Among those without previous SARS-CoV-2 infection, anti-RBD IgG was undetectable at 4 weeks in 75 of 131 (57%, 95% confidence interval [CI] 47% to 65%) patients receiving hemodialysis, compared with 1 of 20 (5%, 95% CI 1% to 23%) controls (p < 0.001). No patient with nondetectable levels at 4 weeks developed anti-RBD IgG by 8 weeks. Results were similar in non-immunosuppressed and younger individuals. Three patients receiving hemodialysis developed severe COVID-19 after vaccination. Among those with previous SARS-CoV-2 infection, median anti-RBD IgG levels at 8 weeks in patients receiving hemodialysis were similar to controls at 3 weeks (p = 0.3) and to convalescent plasma (p = 0.8). A single dose of BNT162b2 vaccine failed to elicit a humoral immune response in most patients receiving hemodialysis without previous SARS-CoV-2 infection, even after prolonged observation. In those with previous SARS-CoV-2 infection, the antibody response was delayed. We advise that patients receiving hemodialysis be prioritized for a second BNT162b2 dose at the recommended 3-week interval.

Recent efforts have been devoted to the link between responses to non-physical stressors and immune states in animals, mostly using human and other vertebrate models. Despite evolutionary relevance, comparatively limited work on the appraisal of predation risk and aspects of cognitive ecology and ecoimmunology has been carried out in non-chordate animals. The present study explored the capacity of holothuroid echinoderms to display an immune response to both reactive and anticipatory predatory stressors. Experimental trials and a mix of behavioural, cellular and hormonal markers were used, with a focus on coelomocytes (analogues of mammalian leukocytes), which are the main components of the echinoderm innate immunity. Findings suggest that holothuroids can not only appraise threatening cues (i.e. scent of a predator or alarm signals from injured conspecifics) but prepare themselves immunologically, presumably to cope more efficiently with potential future injuries. The responses share features with recently defined central emotional states and wane after prolonged stress in a manner akin to habituation, which are traits that have rarely been shown in non-vertebrates, and never in echinoderms. Because echinoderms sit alongside chordates in the deuterostome clade, such findings offer unique insights into the adaptive value and evolution of stress responses in animals.

HIV remission can be achieved in some people, called post-treatment HIV controllers, after antiretroviral treatment discontinuation. Treatment initiation close to the time of infection was suggested to favor post-treatment control, but the circumstances and mechanisms leading to this outcome remain unclear. Here we evaluate the impact of early (week 4) vs. late (week 24 post-infection) treatment initiation in SIVmac 251 -infected male cynomolgus macaques receiving 2 years of therapy before analytical treatment interruption. We show that early treatment strongly promotes post-treatment control, which is not related to a lower frequency of infected cells at treatment interruption. Rather, early treatment favors the development of long-term memory CD8 + T cells with enhanced proliferative and SIV suppressive capacity that are able to mediate a robust secondary-like response upon viral rebound. Our model allows us to formally demonstrate a link between treatment initiation during primary infection and the promotion of post-treatment control and provides results that may guide the development of new immunotherapies for HIV remission. HIV remission has been seen in people living with HIV after the cessation of antiretroviral therapy and is termed post treatment control. Here Passaes and colleagues present an SIV model that shows early initiation of antiretroviral therapy after SIV infection is linked to improved post treatment control upon cessation of antiviral therapy and associates with the expansion of an enhanced memory pool of CD8 + T cells‘.