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The extent to which genomic convergence shapes locally adapted phenotypes in different species remains a fundamental question in evolutionary biology. It would help assessing the relative role of historical contingencies versus determinism in evolution. To bring new insights to this debate we set up a framework which aimed to compare the adaptive trajectories of two domesticated mammal species co-distributed in diversified landscapes. We sequenced the genomes of 160 sheep and 161 goats extensively managed along environmental gradients, including temperature, rainfall, seasonality and altitude, to identify genes and biological processes shaping local adaptation. Allele frequencies at adaptive loci were rarely found to vary gradually along environmental gradients, but rather displayed a discontinuous shift at the extremities of environmental clines. Of the more than 430 adaptive genes identified, only 6 were orthologous between sheep and goats and those responded differently to environmental pressures, suggesting different adaptive mechanisms in these two closely related species. Such diversity of adaptive pathways may result from a high number of biological functions involved in adaptation to multiple eco-climatic gradients, and provides more arguments for the role of contingency and stochasticity in adaptation rather than repeatability and determinism.

Coral reefs around the world are under threat from anomalous heat waves that are causing the widespread decline of hard corals. Different coral taxa are known to have different sensitivities to heat, although variation in susceptibilities have also been observed within the same species living in different environments. Characterizing such taxa-specific variations is key to enforcing efficient reef conservation strategies.Here, we combine worldwide-reef-survey data with remote sensed environmental variables to evaluate how local differences in taxa-specific coral cover are associated with past trends of thermal anomalies, as well as of non-heat related conditions. While the association with non-heat related environmental variation was seldom significant, we found that heat stress trends matched local differences in coral cover. Coral taxa were sorted based on the different patterns of associations with heat stress.For branching, tabular and corymbose Acroporidae, reefs exposed to recent heat stress (measured the year before the survey) had lower coral cover than locally expected; and among these reefs, those previously exposed to frequent past heat stress (measured since 1985) displayed relatively higher coral cover, compared to those less frequently exposed. For massive and encrusting Poritidae, and for meandroid Favidae and Mussidae, we observed a negative association of coral cover with recent heat stress; however, unlike with Acroporidae, these associations were weaker and did not vary with past heat exposure. For Pocilloporidae, we found a positive association between coral cover and recent heat stress for reefs frequently exposed to past heat, while we found a negative association at reefs less frequently exposed to past heat. A similar pattern was observed for the branching Poritidae, although the associations were weaker and not statistically significant.Overall, these results show taxa-specific heat association patterns that might correspond to taxa-specific responses to past heat exposure, such as shifts in the assembly of coral communities, evolutionary adaptation or physiological acclimation.

Publisher Copyright: Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. BACKGROUND: Few studies have examined the interactions between individual socioeconomic position and neighbourhood deprivation and the findings so far are heterogeneous. Using a large sample of diverse cohorts, we investigated the interaction effect of neighbourhood socioeconomic deprivation and individual socioeconomic position, assessed using education, on mortality. METHODS: We did a longitudinal multicohort analysis that included six cohort studies participating in the European LIFEPATH consortium: the CoLaus (Lausanne, Switzerland), E3N (France), EPIC-Turin (Turin, Italy), EPIPorto (Porto, Portugal), Melbourne Collaborative Cohort Study (Melbourne, VIC, Australia), and Whitehall II (London, UK) cohorts. All participants with data on mortality, educational attainment, and neighbourhood deprivation were included in the present study. The data sources were the databases of each cohort study. Poisson regression was used to estimate the mortality rates and associations (relative risk, 95% CIs) with neighbourhood deprivation (Q1 being least deprived to Q5 being the most deprived). Baseline educational attainment was used as an indicator of individual socioeconomic position. Estimates were combined using pooled analysis and the relative excess risk due to the interaction was computed to identify additive interactions. FINDINGS: The cohorts comprised a total population of 168 801 individuals. The recruitment dates were 2003-06 for CoLaus, 1989-91 for E3N, 1992-98 for EPIC-Turin, 1999-2003 for EPIPorto, 1990-94 for MCCS, and 1991-94 for Whitehall II. We use baseline data only and mortality data obtained using record linkage. Age-adjusted mortality rates were higher among participants residing in more deprived neighbourhoods than those in the least deprived neighbourhoods (Q1 least deprived neighbourhoods, 369·7 per 100 000 person-years [95% CI 356·4-383·2] vs Q5-most deprived neighbourhoods 445·7 per 100 000 person-years [430·2-461·7]), but the magnitude of the association varied according to educational attainment (relative excess risk due to interaction=0·18, 95% CI 0·08-0·28). The relative risk for Q5 versus Q1 was 1·31 (1·23-1·40) among individuals with primary education or less, but less pronounced among those with secondary education (1·12; 1·04-1·21) and tertiary education (1·16; 1·07-1·27). Associations remained after adjustment for individual-level factors, such as smoking, physical activity, and alcohol intake, among others. INTERPRETATION: Our study suggests that the detrimental health effect of living in disadvantaged neighbourhoods is more pronounced among individuals with low education attainment, amplifying social inequalities in health. This finding is relevant to policies aimed at reducing health inequalities, suggesting that these issues should be addressed at both the individual level and the community level. FUNDING: The European Commission, European Regional Development Fund, the Portugese Foundation for Science and Technology.

Most efforts to understand snakebite burden in Nepal have been localized to relatively small areas and focused on humans through epidemiological studies. We present the outcomes of a geospatial analysis of the factors influencing snakebite risk in humans and animals, based on both a national-scale multi-cluster random survey and, environmental, climatic, and socio-economic gridded data for the Terai region of Nepal. The resulting Integrated Nested Laplace Approximation models highlight the importance of poverty as a fundamental risk-increasing factor, augmenting the snakebite odds in humans by 63.9 times. For animals, the minimum temperature of the coldest month was the most influential covariate, increasing the snakebite odds 23.4 times. Several risk hotspots were identified along the Terai, helping to visualize at multiple administrative levels the estimated population numbers exposed to different probability risk thresholds in one year. These analyses and findings could be replicable in other countries and for other diseases.

Background: The early detection of clusters of infectious diseases such as the SARS-CoV-2-related COVID-19 disease can promote timely testing recommendation compliance and help to prevent disease outbreaks. Prior research revealed the potential of COVID-19 participatory syndromic surveillance systems to complement traditional surveillance systems. However, most existing systems did not integrate geographic information at a local scale, which could improve the management of the SARS-CoV-2 pandemic., Objective: The aim of this study is to detect active and emerging spatiotemporal clusters of COVID-19-associated symptoms, and to examine (a posteriori) the association between the clusters' characteristics and sociodemographic and environmental determinants., Methods: This report presents the methodology and development of the @choum (English: "achoo") study, evaluating an epidemiological digital surveillance tool to detect and prevent clusters of individuals (target sample size, N=5000), aged 18 years or above, with COVID-19-associated symptoms living and/or working in the canton of Geneva, Switzerland. The tool is a 5-minute survey integrated into a free and secure mobile app (CoronApp-HUG). Participants are enrolled through a comprehensive communication campaign conducted throughout the 12-month data collection phase. Participants register to the tool by providing electronic informed consent and nonsensitive information (gender, age, geographically masked addresses). Symptomatic participants can then report COVID-19-associated symptoms at their onset (eg, symptoms type, test date) by tapping on the @choum button. Those who have not yet been tested are offered the possibility to be informed on their cluster status (information returned by daily automated clustering analysis). At each participation step, participants are redirected to the official COVID-19 recommendations websites. Geospatial clustering analyses are performed using the modified space-time density-based spatial clustering of applications with noise (MST-DBSCAN) algorithm., Results: The study began on September 1, 2020, and will be completed on February 28, 2022. Multiple tests performed at various time points throughout the 5-month preparation phase have helped to improve the tool's user experience and the accuracy of the clustering analyses. A 1-month pilot study performed among 38 pharmacists working in 7 Geneva-based pharmacies confirmed the proper functioning of the tool. Since the tool's launch to the entire population of Geneva on February 11, 2021, data are being collected and clusters are being carefully monitored. The primary study outcomes are expected to be published in mid-2022., Conclusions: The @choum study evaluates an innovative participatory epidemiological digital surveillance tool to detect and prevent clusters of COVID-19-associated symptoms. @choum collects precise geographic information while protecting the user's privacy by using geomasking methods. By providing an evidence base to inform citizens and local authorities on areas potentially facing a high COVID-19 burden, the tool supports the targeted allocation of public health resources and promotes testing.

BACKGROUND: Rapid access to a trauma centre for severely injured road accident victims, conceptualised as the Golden Hour, links access time to definitive treatment within 1 hour of trauma with reduced risks of morbidity and mortality. Access times have not been studied in Switzerland. The aim of this work was to model the transport time by ambulance of seriously injured road traffic accident victims to one of the 12 trauma centres in Switzerland and to investigate whether this time influenced mortality., METHODS: Isochronous travel curves in 10-minute increments were modelled around each of the 12 Swiss trauma centres to assess travel times at the Swiss national level, based on the shortest travel time from the location of a serious road accident to the nearest trauma centre. We used the national database of the Federal Roads Office, which provided the geolocation of these accidents occurring between 2011 and 2017. The association between mortality and transport time to the nearest trauma centre was then analysed., RESULTS: The current distribution of trauma centres allowed access time within the Golden Hour for accidents occurring on the Swiss plateau, but the time was more prolonged in the Alps or the Jura. An association existed between mortality and prehospital transport time from the site of an accident to the nearest trauma centre. For each additional 10-minute isochrone, an average increase of 0.4% in mortality was observed., CONCLUSION: This work showed an adequate distribution of trauma centres in Switzerland and suggests a positive relationship between transport time to the nearest trauma centre and mortality. The numerous confounding factors not systematically collected in publicly available databases limit the robustness of our results. This study confirms the importance of having a national trauma registry to allow quality analyses to guide public health decisions.

BackgroundThe COVID-19 pandemic has affected billions of people around the world both directly through the infection itself and indirectly through its economic, social and sanitary impact. Collecting data over time is essential for the understanding of the disease spread, the incidence of COVID19-like symptoms, the level and dynamics of immunity, as well as the long-term impact of the pandemic.ObjectiveThe objective of the study was to set up a longitudinal follow-up of adult participants of serosurveys carried out in the Canton of Geneva, Switzerland, during the COVID-19 pandemic.MethodsSerosurvey participants were invited to create an account on the dedicated digital platform Specchio-COVID19 (https://www.specchio-covid19.ch/). Upon registration, an initial questionnaire assessed socio-demographic and lifestyle characteristics (including housing conditions, physical activity, diet, alcohol and tobacco consumption), anthropometry, general health, and experience related to COVID-19 (symptoms, COVID-19 test results, quarantines, hospitalizations). Weekly, participants were invited to fill in a short questionnaire with updates on self-reported COVID-19-compatible symptoms, SARS-CoV-2 infection testing and vaccination. A more detailed questionnaire about mental health, well-being, risk perception, and changes in working conditions was proposed monthly. Supplementary questionnaires were proposed at regular intervals to assess more in depth the impact of the pandemic on physical and mental health, vaccination adherence, health care consumption and changes in health behaviors. At baseline, serology testing allowed to assess the spread of SARS-CoV-2 infection among the general population and subgroups of workers. Additionally, seropositive participants and a sample of randomly selected participants were invited for serologic testing at regular intervals in order to monitor both the seropersistance of anti-SARS-CoV-2 antibodies and the seroprevalence of anti-SARS-CoV-2 antibodies in the population of the Canton of Geneva.Ethics and disseminationThe study was approved by the Cantonal Research Ethics Commission of Geneva, Switzerland (CCER Project ID 2020-00881). Results will be disseminated in a variety of ways, via the Specchio-COVID19 platform, social media posts, press releases, and through regular scientific dissemination methods (open-access articles, conferences).Article summaryStrengths and limitationsThis is a large study with a diversified recruitment among the general population and mobilized workers. It will contribute to obtain a clearer picture of the impact of the COVID-19 pandemic, for both the general population and targeted subpopulations.A major strength of the study is the combined use of serological testing and questionnaires. While regular serological testing will help us to model evolution of the pandemic, self-reported data on socioeconomic characteristics, COVID-19-compatible symptoms, and general and mental health will allow us to monitor the progression of the COVID-19 pandemic as well as to thoroughly analyze its effects on several dimensions of health.The longitudinal component of the study will provide insight into the extent and duration of immunity, as well as the long-term impact of the pandemic and the sanitary, social and economic measures associated with it.The main limitation is that Specchio-COVID19 is based on self-reports with a risk of information bias. However, considering the pandemic context, participants are generally engaged to participate and to contribute to COVID-19 research. Further, at least half of the sample is based on random selection in the general population.The study is primarily being conducted online, which may limit the generalizability of the findings, especially for the elderly and vulnerable populations, although internet access is extensive in Switzerland. Nonetheless, participants can use paper questionnaires to contribute to the major assessments.

This study assessed the spatial dependence of daily tobacco consumption and how it is spatially impacted by individual and neighborhood socioeconomic determinants, and tobacco consumption facilities before and after a smoke-free implementation. Individual data was obtained from the Bus Sante ', a cross-sectional survey in Geneva. Spatial clusters of high and low tobacco consumption were assessed using Getis-Ord Gi*. Daily tobacco consumption was not randomly clustered in Geneva and may be impacted by tobacco consumption facilities independently of socioeconomic factors and a smoking ban. Spatial analysis should be considered to highlight the impact of smoke-free policies and guide public health interventions.

Background Obesity and obesity-related diseases represent a major public health concern. Recently, studies have substantiated the role of sugar-sweetened beverages (SSBs) consumption in the development of these diseases. The fine identification of populations and areas in need for public health intervention remains challenging. This study investigates the existence of spatial clustering of SSB intake frequency (SSB-IF) and body mass index (BMI), and their potential spatial overlap in a population of adults of the state of Geneva using a fine-scale geospatial approach. Methods We used data on self-reported SSB-IF and measured BMI from residents aged between 20 and 74 years of the state of Geneva (Switzerland) that participated in the Bus Santé cross-sectional population-based study (n = 15,423). Getis-Ord Gi spatial indices were used to identify spatial clusters of SSB-IF and BMI in unadjusted models and models adjusted for individual covariates (education level, gender, age, nationality, and neighborhood-level median income). Results We identified a significant spatial clustering of BMI and SSB-IF. 13.2% (n = 2034) of the participants were within clusters of higher SSB-IF and 10.7% (n = 1651) were within clusters of lower SSB-IF. We identified overlapping clusters of SSB-IF and BMI in specific areas where 11.1% (n = 1719) of the participants resided. After adjustment, the identified clusters persisted and were only slightly attenuated indicating that additional neighborhood-level determinants influence the spatial distribution of SSB-IF and BMI. Conclusions Our fine-scale spatial approach allowed to identify specific populations and areas presenting higher SSB-IF and highlighted the existence of an overlap between populations and areas of higher SSB-IF associated with higher BMI. These findings could guide policymakers to develop locally tailored interventions such as targeted prevention campaigns and pave the way for precision public health delivery.

Living in deprived neighbourhoods may have biological consequences, but few studies have assessed this empirically. We examined the association between neighbourhood deprivation and allostatic load, a biological marker of wear and tear, taking into account individual's socioeconomic position. We analysed data from three cohort studies (CoLaus-Switzerland; EPIPorto-Portugal; Whitehall II-UK) comprising 16,364 participants. We defined allostatic load using ten biomarkers of dysregulated metabolic, cardiovascular, and inflammatory systems (body mass index; waist circumference; total, high and low density lipoprotein cholesterol; triglycerides; glucose; systolic and diastolic blood pressure; C-reactive protein). Mixed Poisson regression models were fitted to examine associations with neighbourhood deprivation (in quintiles, Q1-least deprived as reference). After adjustment for confounding variables, participants living in the most deprived quintile had 1.13 times higher allostatic load than those living in the least deprived quintile (Relative Risk, RR, for Q2 RR = 1.06, 95% CI 1.03-1.09; Q3 = 1.06, 1.03-1.10; Q4 = 1.09, 1.06-1.12; Q5 = 1.13, 1.09-1.16). This association was partially modified by individual's socioeconomic position, such that the relative risk was higher in participants with low socioeconomic position (Q5 vs Q1 1.16, 1.11-1.22) than those with high socioeconomic position (Q5 vs Q1 1.07, 1.01-1.13). Neighbourhood deprivation is associated with biological wear and tear, suggesting that neighbourhood-level interventions may yield health gains. Living in deprived neighbourhoods may have biological consequences, but few studies have assessed this empirically. We examined the association between neighbourhood deprivation and allostatic load, a biological marker of wear and tear, taking into account individual's socioeconomic position. We analysed data from three cohort studies (CoLaus-Switzerland; EPIPorto-Portugal; Whitehall II-UK) comprising 16,364 participants. We defined allostatic load using ten biomarkers of dysregulated metabolic, cardiovascular, and inflammatory systems (body mass index; waist circumference; total, high and low density lipoprotein cholesterol; trig lycerides; glucose; systolic and diastolic blood pressure; C-reactive protein). Mixed Poisson regression models were fitted to examine associations with neighbourhood deprivation (in quintiles, Q1-least deprived as reference). After adjustment for confounding variables, participants living in the most deprived quintile had 1.13 times higher allostatic load than those living in the least deprived quintile (Relative Risk, RR, for Q2 RR = 1.06, 95%CI 1.03-1.09; Q3 = 1.06, 1.03-1.10; Q4 = 1.09, 1.06-1.12; Q5 = 1.13, 1.09-1.16). This association was partially modified by individual's socioeconomic position, such that the relative risk was higher in participants with low socioeconomic position (Q5 vs Q11.16, 1.11-1.22) than those with high socioeconomic position (Q5 vs Q1 1.07, 1.11-1.13). Neighbourhood deprivation is associated with biological wear and tear, suggesting that neighbourhood-level interventions may yield health gains.

BACKGROUND The early detection of clusters of infectious diseases such as the SARS-CoV-2–related COVID-19 disease can promote timely testing recommendation compliance and help to prevent disease outbreaks. Prior research revealed the potential of COVID-19 participatory syndromic surveillance systems to complement traditional surveillance systems. However, most existing systems did not integrate geographic information at a local scale, which could improve the management of the SARS-CoV-2 pandemic. OBJECTIVE The aim of this study is to detect active and emerging spatiotemporal clusters of COVID-19–associated symptoms, and to examine (a posteriori) the association between the clusters’ characteristics and sociodemographic and environmental determinants. METHODS This report presents the methodology and development of the @choum (English: “achoo”) study, evaluating an epidemiological digital surveillance tool to detect and prevent clusters of individuals (target sample size, N=5000), aged 18 years or above, with COVID-19–associated symptoms living and/or working in the canton of Geneva, Switzerland. The tool is a 5-minute survey integrated into a free and secure mobile app (CoronApp-HUG). Participants are enrolled through a comprehensive communication campaign conducted throughout the 12-month data collection phase. Participants register to the tool by providing electronic informed consent and nonsensitive information (gender, age, geographically masked addresses). Symptomatic participants can then report COVID-19–associated symptoms at their onset (eg, symptoms type, test date) by tapping on the @choum button. Those who have not yet been tested are offered the possibility to be informed on their cluster status (information returned by daily automated clustering analysis). At each participation step, participants are redirected to the official COVID-19 recommendations websites. Geospatial clustering analyses are performed using the modified space-time density-based spatial clustering of applications with noise (MST-DBSCAN) algorithm. RESULTS The study began on September 1, 2020, and will be completed on February 28, 2022. Multiple tests performed at various time points throughout the 5-month preparation phase have helped to improve the tool’s user experience and the accuracy of the clustering analyses. A 1-month pilot study performed among 38 pharmacists working in 7 Geneva-based pharmacies confirmed the proper functioning of the tool. Since the tool’s launch to the entire population of Geneva on February 11, 2021, data are being collected and clusters are being carefully monitored. The primary study outcomes are expected to be published in mid-2022. CONCLUSIONS The @choum study evaluates an innovative participatory epidemiological digital surveillance tool to detect and prevent clusters of COVID-19–associated symptoms. @choum collects precise geographic information while protecting the user’s privacy by using geomasking methods. By providing an evidence base to inform citizens and local authorities on areas potentially facing a high COVID-19 burden, the tool supports the targeted allocation of public health resources and promotes testing. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/30444

Inadequate sodium and potassium dietary intakes are associated with major, yet preventable, health consequences. Local public health interventions can be facilitated and informed by fine-scale geospatial analyses. In this study, we assess the existence of spatial clustering (i.e., an unusual concentration of individuals with a specific outcome in space) of estimated sodium (Na), potassium (K) intakes, and Na:K ratio in the Bus Santé 1992–2018 annual population-based surveys, including 22,495 participants aged 20–74 years, residing in the canton of Geneva, using the local Moran’s I spatial statistics. We also investigate whether socio-demographic and food environment characteristics are associated with identified spatial clustering, using both global ordinary least squares (OLS) and local geographically weighted regression (GWR) modeling. We identified clear spatial clustering of Na:K ratio, Na, and K intakes. The GWR outperformed the OLS models and revealed spatial variations in the associations between explanatory and outcome variables. Older age, being a woman, higher education, and having a lower access to supermarkets were associated with higher Na:K ratio, while the opposite was seen for having the Swiss nationality. Socio-demographic characteristics explained a major part of the identified clusters. Socio-demographic and food environment characteristics significantly differed between individuals in spatial clusters of high and low Na:K ratio, Na, and K intakes. These findings could guide prioritized place-based interventions tailored to the characteristics of the identified populations.

Background Evidence suggests that the built environment can influence the intensity of physical activity. However, most of the studies do not consider the geographic context of this association. Studies assessing the spatial dependence of physical activity are limited by an aggregated geographic scale or self-reported physical activity. We aimed to assess individual spatial dependence of objectively measured moderate and vigorous physical activity (MVPA) and describe the characteristics of the built environment among spatial clusters of MVPA. Methods Cross-sectional data from the second follow-up of CoLaus|PsyCoLaus (2014-2017), a longitudinal population-based study of the Lausanne area (Switzerland), was used to objectively measure daily MVPA using accelerometers. We ran Local Moran’s I to assess the spatial dependence of MVPA. This method compares the behavior (MVPA) of participants to that of other individuals located in the same neighborhood. It classifies individuals into four categories: high MVPA clusters, low MVPA clusters, low MVPA outliers in high MVPA clusters, and high MVPA outliers in low MVPA clusters. Additionally, the characteristics of the built environment observed in the clusters based on raw MVPA and MVPA adjusted for socioeconomic and demographic factors were described. Results Data from 1,889 participants (median age 63 years, 55% women) were used. The geographic distribution of MVPA and the characteristics of the built environment among clusters were similar for raw and adjusted MVPA. In the adjusted model, we found a low concentration of individuals within spatial clusters of high MVPA (median: 36.9 mins; 3% of the studied population) and low MVPA (median: 10.1 mins; 2% of the studied population). Yet, clear differences were found in both models between clusters regarding the built environment; High MVPA clusters were located in areas with a higher density of parks, recreational, public, and commercial & industrial areas, preferential pedestrian zones, population density, cycling pathways, public transport accessibility and interconnected streets than low MVPA clusters. Conclusions Although with few individuals within clusters, MVPA clusters were identified. The built environment may influence spatial patterns of MVPA independently of socioeconomic and demographic factors. Interventions in the built environment should be considered to promote physically active behaviors in urban areas.

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

International audience; Anomalous heat waves are causing a major decline of hard corals around the world and threatening the persistence of coral reefs. There are, however, reefs that have been exposed to recurrent thermal stress over the years and whose corals appear to have been tolerant against heat. One of the mechanisms that could explain this phenomenon is local adaptation, but the underlying molecular mechanisms are poorly known. In this work, we applied a seascape genomics approach to study heat stress adaptation in three coral species of New Caledonia (southwestern Pacific) and to uncover the molecular actors potentially involved. We used remote sensing data to characterize the environmental trends across the reef system, and sampled corals living at the most contrasted sites. These samples underwent next generation sequencing to reveal single nucleotide polymorphisms (SNPs), frequencies of which were associated with heat stress gradients. As these SNPs might underpin an adaptive role, we characterized the functional roles of the genes located in their genomic region. In each of the studied species, we found heat stress-associated SNPs located in proximity of genes involved in pathways well known to contribute to the cellular responses against heat, such as protein folding, oxidative stress homeostasis, inflammatory and apoptotic pathways, and DNA damage-repair. In some cases, the same candidate molecular targets of heat stress adaptation recurred among species. Together, these results underline the relevance and the power of the seascape genomics approach for the discovery of adaptive traits that could allow corals to persist across wider thermal ranges.

BACKGROUND The etiology of Parkinson's disease (PD) remains unknown. To approach the issue of PD's risk factors from a new perspective, we hypothesized that coupling the geographic distribution of PD with spatial statistics may provide new insights into environmental epidemiology research. The aim of this case-control study was to examine the spatial dependence of PD prevalence in the Canton of Geneva, Switzerland (population = 474,211). METHODS PD cases were identified through Geneva University Hospitals, private neurologists and nursing homes medical records (n = 1115). Controls derived from a population-based study (n = 12,614) and a comprehensive population census dataset (n = 237,771). All individuals were geographically localized based on their place of residence. Spatial Getis-Ord Gi* statistics were used to identify clusters of high versus low disease prevalence. Confounder-adjustment was performed for age, sex, nationality and income. Tukey's honestly significant difference was used to determine whether nitrogen dioxide and particulate matters PM10 concentrations were different within PD hotspots, coldspots or neutral areas. RESULTS Confounder-adjustment greatly reduced greatly the spatial association. Characteristics of the geographic space influenced PD prevalence in 6% of patients. PD hotspots were concentrated in the urban centre. There was a significant difference in mean annual nitrogen dioxide and PM10 levels (+3.6 μg/m3 [p

The tick Ixodes ricinus is the vector of various pathogens, including Chlamydiales bacteria, which potentially cause respiratory infections. In this study, we modeled the spatial distribution of I. ricinus and associated Chlamydiales over Switzerland from 2009 to 2019. We used a total of 2,293 ticks and 186 Chlamydiales occurrences provided by a Swiss Army field campaign, a collaborative smartphone application, and a prospective campaign. For each tick location, we retrieved from Swiss federal data sets the environmental factors reflecting the topography, climate, and land cover. We then used the Maxent modeling technique to estimate the suitability of particular areas for I. ricinus and to subsequently build the nested niche of Chlamydiales bacteria. Results indicate that I. ricinus habitat suitability is determined by higher temperature and normalized difference vegetation index (NDVI) values, lower temperature during the driest months, and a higher percentage of artificial and forest areas. The performance of the model was improved when extracting the environmental variables for a 100-m radius buffer around the sampling points and when considering the climatic conditions of the 2 years previous to the sampling date. Chlamydiales bacteria were favored by a lower percentage of artificial surfaces, drier conditions, high precipitation during the coldest months, and short distances to wetlands. From 2009 to 2018, we observed an extension of areas suitable to ticks and Chlamydiales, associated with a shift toward higher altitude. The importance of considering spatiotemporal variations in the environmental conditions for obtaining better prediction was also demonstrated., IMPORTANCE Ixodes ricinus is the vector of pathogens including the agent of Lyme disease, the tick-borne encephalitis virus, and the less well-known Chlamydiales bacteria, which are responsible for certain respiratory infections. In this study, we identified the environmental factors influencing the presence of I. ricinus and Chlamydiales in Switzerland and generated maps of their distribution from 2009 to 2018. We found an important expansion of suitable areas for both the tick and the bacteria during the last decade. Results also provided the environmental factors that determine the presence of Chlamydiales within ticks. Distribution maps as generated here are expected to bring valuable information for decision makers in controlling tick-borne diseases in Switzerland and establishing prevention campaigns. The methodological framework presented could be used to predict the distribution and spread of other host-pathogen pairs to identify environmental factors driving their distribution and to develop control or prevention strategies accordingly.

As anomalous heat waves are causing the widespread decline of coral reefs worldwide, there is an urgent need to identify coral populations tolerant to thermal stress. Heat stress adaptive potential is the degree of tolerance expected from evolutionary processes and, for a given reef, depends on the arrival of propagules from reefs exposed to recurrent thermal stress. For this reason, assessing spatial patterns of thermal adaptation and reef connectivity is of paramount importance to inform conservation strategies.In this work, we applied a seascape genomics framework to characterize the spatial patterns of thermal adaptation and connectivity for coral reefs of New Caledonia (Southern Pacific). In this approach, remote sensing of seascape conditions was combined with genomic data from three coral species. For every reef of the region, we computed a probability of heat stress adaptation, and two indices forecasting inbound and outbound connectivity. We then compared our indicators to field survey data, and observed that decrease of coral cover after heat stress was lower at reefs predicted with high probability of adaptation and inbound connectivity. Last, we discussed how these indicators can be used to inform local conservation strategies and preserve the adaptive potential of New Caledonian reefs.

Materials to reproduce the results of the paper "Evaluating urban greening scenarios for urban heat mitigation: a spatially-explicit approach". Detailed instructions of the steps to reproduce the results can be found in the `README.md` of github.com/martibosch/lausanne-greening-scenarios. Citation Bosch, M., Locatelli, M., Hamel, P., Jaligot, R., Chenal, J., and Joost, S. 2020. "Evaluating urban greening scenarios for urban heat mitigation: a spatially-explicit approach". Preprint available atbioRxiv.10.1101/2020.11.09.373779 If using any of the following files, the sources must be acknowledged accordingly: `invest-calibrated-params.json`: based on the calibration by Bosch et al. [1]. `ref-et.tif`: obtained using the minimum, average and maximum temperature datasets of the copyrighted Spatial Climate Analyses of MeteoSwiss [2]. `station-t.csv`: the temperature observations correspond to monitoring stations operated by Agrometeo, the Federal roads office (ASTRA), the Federal office for the environment (BAFU), the General directorate for the environment of the Canton of Vaud (DGE), and the Federal Institute of Forest, Snow and Landscape Research (WSL) [3]. See the file `station-locations.csv` for more details. Acknowledgments With the support of the École Polytechnique Fédérale de Lausanne (EPFL) References Bosch, M., Locatelli, M., Hamel, P., Remme, R. P., Chenal, J., and Joost, S. 2020. "A spatially-explicit approach to simulate urban heat islands in complex urban landscapes". Under review in Geoscientific Model Development. 10.5194/gmd-2020-174 Frei, C., 2014. Interpolation of temperature in a mountainous region using nonlinear profiles and non‐Euclidean distances. International Journal of Climatology, 34(5), pp.1585-1605. 10.1002/joc.3786 Rebetez, M., von Arx, G., Gessler, A., Pannatier, E.G., Innes, J.L., Jakob, P., Jetel, M., Kube, M., Nötzli, M., Schaub, M. and Schmitt, M., 2018. Meteorological data series from Swiss long-term forest ecosystem research plots since 1997. Annals of Forest Science, 75(2), p.41. 10.1007/s13595-018-0709-7

Background In order to provide efficient public health decisions making, it is crucial to obtain reliable and recent data on the state of health of the population. For that purpose, a web-platform for the dynamic monitoring of the health status and well-being of the population is being developed in the Geneva canton. Methods Using a dedicated website, recruitment will be carried out over 5 years so as to enroll up to 20 000 volunteers, resident in Geneva and aged ≥ 18 years, followed-up for at least 10 years. Once connected to the website, participants will fill a general self-administered questionnaire on their socio-demographic and lifestyle characteristics, anthropometry, health status, physical activity and diet. Environmental, behavioral and occupational exposures will also be evaluated via more specific questionnaires. Current addresses of residence will be geocoded and linked to geographical databases to passively gather information on noise, air pollution, green areas, and other exposures. Surveillance of health events will be implemented via yearly self-administered on line questionnaires and potentially via passive linkage to medical databases (medical file) and health registries with the participants' consent. For a subsample of volunteers, biochemical samples and biomarkers will be collected. Results The pilot study shows that the project is feasible, potentially cost-effective but requires innovative methodologies for ensuring long term follow-up. Different communication strategies used for recruitment and long-term participation need to be implemented ensuring trust from participants, different levels of health literacy and the need of justice. Conclusions Specchio is a new project aimed at setting up a digital longitudinal health study in Geneva. Challenges concerns the determinants of participation, recruitment and attrition, quality of data and ethics. Long-term funding by the Directorate General of Health Geneva is currently under evaluation. Key messages This digital longitudinal health study will enable dynamic monitoring of the health status and well-being of Geneva residents and will enable efficient public health decision making. Specchio is a new project funded by the Directorate General of Health Geneva.

The transhumance system, which consists in moving animals to high mountain pastures during summer, plays a considerable role in preserving both local biodiversity and traditions, as well as protecting against natural hazard. In cows, particularly, milk production is observed to decline as a response to food shortage and climatic stress, leading to atypical lactation curves that are barely described by current lactation models. Here, we relied on 5 million monthly milk records from over 200 000 Braunvieh and Original Braunvieh cows to devise a new model accounting for transhumance, and test the influence of environmental, physiological and morphological factors on cattle productivity. Counter to expectations, environmental conditions in the mountain showed a globally limited impact on milk production during transhumance, with cows in favourable conditions producing only 10% more compared with cows living in detrimental conditions, and with precipitation in spring and altitude revealing to be the most production-affecting variables. Conversely, physiological factors such as lactation number and pregnancy stage presented an important impact over the whole lactation cycle with 20% difference in milk production, and alter the way animals respond to transhumance. Finally, the considered morphological factors (cow height and foot angle) presented a smaller impact during the whole lactation cycle (10% difference in milk production). The present findings help to anticipate the effect of climate change and to identify problematic environmental conditions by comparing their impact with the effect of factors that are known to influence lactation.

The tick Ixodes ricinus is the vector of various pathogens, including Chlamydiales bacteria, potentially causing respiratory infections. In this study, we modelled the spatial distribution of I. ricinus and associated Chlamydiales over Switzerland from 2009 to 2019. We used a total of 2293 ticks and 186 Chlamydiales occurrences provided by a Swiss Army field campaign, a collaborative smartphone application and a prospective campaign. For each tick location, we retrieved from Swiss federal datasets the environmental factors reflecting the topography, climate and land cover. We then used the Maxent modelling technique to estimate the suitability for I. ricinus and to subsequently build the nested niche of Chlamydiales bacteria. Results indicate that I. ricinus high habitat suitability is determined by higher temperature and vegetation index (NDVI) values, lower temperature during driest months and a higher percentage of artificial and forests areas. The performance of the model was increased when extracting the environmental variables for a 100 m-radius buffer around the sampling points and when considering the data over the two years previous sampling date. For Chlamydiales bacteria, the suitability was favoured by lower percentage of artificial surfaces, driest conditions, high precipitation during coldest months and short distances to wetlands. From 2009 to 2018, we observed an extension of tick and Chlamydiales suitable areas, associated with a shift towards higher altitude. The importance to consider spatio-temporal variations of the environmental conditions for obtaining better prediction was also demonstrated.ImportanceIxodes ricinus is the vector of pathogens, including the agent of Lyme disease, the tick borne encephalitis virus and the less known Chlamydiales bacteria at the origin of some respiratory infections. In this study, we identified the environmental factors influencing the presence of I. ricinus and Chlamydiales in Switzerland and generated maps of their distribution from 2009 to 2018. We found an important expansion of suitable areas for both the tick and the bacteria during the last decade. Results provided also the environmental factors that determine the presence of Chlamydiales within ticks. Distribution maps as generated here are expected to bring valuable informations for decision-makers to control tick-borne diseases in Switzerland and establish prevention campaigns. The methodological framework presented could be used to predict the distribution and spread of other host-pathogen couples, to identify environmental factors driving their distribution and to develop control or prevention strategies accordingly.

Ixodes ricinus is the vector of pathogens including the agent of Lyme disease, the tick-borne encephalitis virus, and the less well-known Chlamydiales bacteria, which are responsible for certain respiratory infections. In this study, we identified the environmental factors influencing the presence of I. ricinus and Chlamydiales in Switzerland and generated maps of their distribution from 2009 to 2018. We found an important expansion of suitable areas for both the tick and the bacteria during the last decade. Results also provided the environmental factors that determine the presence of Chlamydiales within ticks. Distribution maps as generated here are expected to bring valuable information for decision makers in controlling tick-borne diseases in Switzerland and establishing prevention campaigns. The methodological framework presented could be used to predict the distribution and spread of other host-pathogen pairs to identify environmental factors driving their distribution and to develop control or prevention strategies accordingly., The tick Ixodes ricinus is the vector of various pathogens, including Chlamydiales bacteria, which potentially cause respiratory infections. In this study, we modeled the spatial distribution of I. ricinus and associated Chlamydiales over Switzerland from 2009 to 2019. We used a total of 2,293 ticks and 186 Chlamydiales occurrences provided by a Swiss Army field campaign, a collaborative smartphone application, and a prospective campaign. For each tick location, we retrieved from Swiss federal data sets the environmental factors reflecting the topography, climate, and land cover. We then used the Maxent modeling technique to estimate the suitability of particular areas for I. ricinus and to subsequently build the nested niche of Chlamydiales bacteria. Results indicate that I. ricinus habitat suitability is determined by higher temperature and normalized difference vegetation index (NDVI) values, lower temperature during the driest months, and a higher percentage of artificial and forest areas. The performance of the model was improved when extracting the environmental variables for a 100-m radius buffer around the sampling points and when considering the climatic conditions of the 2 years previous to the sampling date. Chlamydiales bacteria were favored by a lower percentage of artificial surfaces, drier conditions, high precipitation during the coldest months, and short distances to wetlands. From 2009 to 2018, we observed an extension of areas suitable to ticks and Chlamydiales, associated with a shift toward higher altitude. The importance of considering spatiotemporal variations in the environmental conditions for obtaining better prediction was also demonstrated. IMPORTANCE Ixodes ricinus is the vector of pathogens including the agent of Lyme disease, the tick-borne encephalitis virus, and the less well-known Chlamydiales bacteria, which are responsible for certain respiratory infections. In this study, we identified the environmental factors influencing the presence of I. ricinus and Chlamydiales in Switzerland and generated maps of their distribution from 2009 to 2018. We found an important expansion of suitable areas for both the tick and the bacteria during the last decade. Results also provided the environmental factors that determine the presence of Chlamydiales within ticks. Distribution maps as generated here are expected to bring valuable information for decision makers in controlling tick-borne diseases in Switzerland and establishing prevention campaigns. The methodological framework presented could be used to predict the distribution and spread of other host-pathogen pairs to identify environmental factors driving their distribution and to develop control or prevention strategies accordingly.

Anomalous heat waves are causing a major decline of hard corals around the world and threatening the persistence of coral reefs. There are, however, reefs that had been exposed to recurrent thermal stress over the years and whose corals appeared tolerant against heat. One of the mechanisms that could explain this phenomenon is local adaptation, but the underlying molecular mechanisms are poorly known.In this work, we applied a seascape genomics approach to study heat stress adaptation in three coral species of New Caledonia (southwestern Pacific) and to uncover molecular actors potentially involved. We used remote sensing data to characterize the environmental trends across the reef system, and sampled corals living at the most contrasted sites. These samples underwent next generation sequencing to reveal single-nucleotide-polymorphisms (SNPs) of which frequencies associated with heat stress gradients. As these SNPs might underpin an adaptive role, we characterized the functional roles of the genes located in their genomic neighborhood.In each of the studied species, we found heat stress associated SNPs notably located in proximity of genes coding for well-established actors of the cellular responses against heat. Among these, we can mention proteins involved in DNA damage-repair, protein folding, oxidative stress homeostasis, inflammatory and apoptotic pathways. In some cases, the same putative molecular targets of heat stress adaptation recurred among species.Together, these results underscore the relevance and the power of the seascape genomics approach for the discovery of adaptive traits that could allow corals to persist across wider thermal ranges.

1.SummaryThe transhumance system, which consists in moving animals to high mountain pastures during summer, plays a considerable role in preserving both local biodiversity and traditions, as well as protecting against natural hazard. In cows, particularly, milk production is observed to decline as a response to food shortage and climatic stress, leading to atypical lactation curves that are barely described by current lactation models. Here, we relied on five million monthly milk records from over 200,000 Braunvieh and Original Braunvieh cows to devise a new model accounting for transhumance, and test the influence of environmental, physiological, and morphological factors on cattle productivity. Counter to expectations, environmental conditions in the mountain showed a globally limited impact on milk production during transhumance, with cows in favourable conditions producing only 10% less compared to cows living in adverse conditions, and with precipitation in spring and altitude revealing to be the most production-affecting variables. Conversely, physiological factors as lactation number and pregnancy stage presented an important impact over the whole lactation cycle with 20% difference in milk production, and may therefore alter the way animals respond to transhumance. Finally, the considered morphological factors (cow height and foot angle) presented a smaller impact during the whole lactation cycle (10% difference in milk production). The present findings can help farmers to establish sustainable strategies for alleviating the negative effects of transhumance on productivity and preserving this important livestock practice.

Coral reefs are suffering a major decline due to the environmental constraints imposed by climate change. Over the last 20 years, three major coral bleaching events occurred in concomitance of anomalous heat waves, provoking a severe loss of coral cover world-wide. Recent works, however, reported of reefs at which recurrent bleaching events resulted in reduced sensitivity to thermal stresses. Adaptation has been suggested to be responsible for this phenomenon. The conservation strategies for preserving the reefs, as they are conceived now, can not cope with global climatic shifts. In this regard, researchers advocated the set-up of a preservation framework to reinforce coral adaptive potential. The main obstacle to this approach is that studies focusing on coral adaptation usually concern a couple of contrasted reefs and their results are therefore hard to generalize at the scale of a reef system. In this work, we ran a seascape genomics analysis to study adaptation of a flagship coral species of the Ryukyu Archipelago (Japan). By associating genotype frequencies with descriptors of historical environmental conditions, we discovered six polymorphisms that might elicit resistance against thermal stress and calculated the probability of presence of these putative adaptive traits across the whole study area. Furthermore, the seascape genomics method allowed us to calculate a connectivity model based on sea surface currents and calibrated on genetic data. These results were used to compute, for every reef of the Ryukyu Archipelago, indexes describing corals adaptive and connective potential. This information can be extremely useful for preservation, since it provides an objective information on how the adaptive potential distributes and disperse across the reef system. Finally, we provide two examples of how this information can be implemented in conservation strategies commonly used such as the establishment of marine protected areas and coral nurseries. Together, the results of our work advocate the value of genetic analyses for empowering preservation efforts dedicated to the protection of coral reef from warming oceans.

International audience; In the face of the growing challenges brought about by human activities, effective planning and decision-making in biodiversity and ecosystem conservation, restoration, and sustainable development are urgently needed. Ecological models can play a key role in supporting this need and helping to safeguard the natural assets that underpin human wellbeing and support life on land and below water (United Nations Sustainable Development Goals; SDG 15 & 14). The urgency and complexity of safeguarding forest (SDG 15.2) and mountain ecosystems (SDG 15.4), for example, and halting decline in biodiversity (SDG 15.5) in the Anthropocene requires a re-envisioning of how ecological models can best support the comprehensive assessments of biodiversity and its change that are required for successful action. A key opportunity to advance ecological modeling for both predictive and explanatory purposes arises through a collaboration between ecologists and the Earth observation community, and a close integration of remote sensing and species distribution models. Remote sensing products have the capacity to provide continuous spatiotemporal information about key factors driving the distribution of organisms, therefore improving both the use and accuracy of these models for management and planning. Here we first survey the literature on remote sensing data products available to ecological modelers interested in improving predictions of species range dynamics under global change. We specifically explore the key biophysical processes underlying the distribution of species in the Anthropocene including climate variability, changes in land cover, and disturbances. We then discuss potential synergies between the ecological modeling and remote sensing communities, and highlight opportunities to close the data and conceptual gaps that currently impede a more effective application of remote sensing for the monitoring and modeling of ecological systems. Specific attention is given to how potential collaborations between the two communities could lead to new opportunities to report on progress towards global agendas - such as the Agenda 2030 for sustainable development of the United Nations or the Post-2020 Global Biodiversity Framework of the Convention for Biological Diversity, and help guide conservation and management strategies towards sustainability.

A key challenge in the design of effective survey questionnaires is to write questions that respondents can understand consistently. Recommendations in the questionnaire design literature propose the use of respondents’ own terminology to facilitate comprehension and the response process. In this paper, we propose an innovative questionnaire development method to construct items using respondents’ own terminology. On the basis of statistical analyses of answers to an open-ended question asked in a survey measuring attitudes to biodiversity (N = 351), we first identified the words that respondents associate most frequently with the concept of ‘biodiversity’. We then designed new attitude measures composed of the words identified as being central to representations about biodiversity. These items were tested in another survey using a different sample (N = 467). The results show that the attitude items designed on the basis of a social representation method satisfied validity and reliability quality criteria.

To understand the geographical and temporal spread of SARS-CoV-2 during the first documented wave of infection in the state of Vaud, Switzerland, we analyzed clusters of positive cases using the precise residential location of 33,651 individuals tested (RT-PCR) between January 10 and June 30, 2020. We used a prospective Poisson space-time scan statistic (SaTScan) and a Modified Space–Time Density-Based Spatial Clustering of Application with Noise (MST-DBSCAN) to identify both space-time and transmission clusters, and estimated cluster duration, transmission behavior (emergence, growth, reduction, etc.) and relative risk. For each cluster, we computed the number of individuals, the median age of individuals and their viral load. Among the 1684 space-time clusters identified, 457 (27.1%) were significant (p ≤ 0.05), such that they harbored a higher relative risk of infection within the cluster than compared to regions outside the cluster. Clusters lasted a median of 11 days (IQR 7–13) and included a median of 12 individuals per cluster (IQR 5–20). The majority of significant clusters (n = 260; 56.9%) had at least one person with an extremely high viral load (>1 billion copies/ml). Those clusters were considerably larger (median of 17 infected individuals, p < 0.001) than clusters with individuals showing a viral load below 1 million copies/ml (median of three infected individuals). The highest viral loads were found in clusters with the lowest average age group considered in the investigation, while clusters with the highest average age had low to middle viral load. In 20 significant clusters, the viral load of the three first cases was below 100,000 copies/ml, suggesting that subjects with fewer than 100,000 copies/ml may still be contagious. Notably, the dynamics of transmission clusters made it possible to identify three diffusion zones, which predominantly differentiated between rural and urban areas, the latter being more prone to persistence and expansion, which may result in the emergence of new clusters nearby. The use of geographic information is key for public health decision makers in mitigating the spread of the SARS-CoV-2 virus. This study suggests that early localization of clusters may help implement targeted protective measures limiting the spread of the virus., Graphical abstract Unlabelled Image

Vast, pristine ecosystems and their biodiversity are vanishing globally at frightening speed, but many large tracts of wilderness have not yet been systematically inventoried and important natural populations of threatened species remain poorly characterized. The forest-savanna ecotone of the Eastern Central African Republic (CAR) is one such poorly studied area. Using camera traps, transect walks and collected fecal samples, we provide the first quantitative survey of chimpanzees (Pan troglodytes) in this region previously classified as a highly important chimpanzee conservation unit. In contrast to species distribution models and expert predictions, we did not find any evidence of chimpanzees in the large and remote forest blocks west of the Chinko River despite considerable search effort. Our study thus highlights the limitations of relying solely on remote sensing data to predict the presence or absence of endangered species and illustrates the necessity of extensive field surveys to accurately assess occurrence and density in remote areas. However, we did discover a sizeable and reproducing population of chimpanzees east of the Chinko River. Based on a density of 0.81chimpanzees/km2 in closed canopy forest that we inferred from nest count data, we estimate 910 weaned chimpanzees to inhabit the Chinko Nature Reserve (CNR) and further predict additional 2700 individuals in adjacent, unmanaged hunting zones and reserves. According to microsatellite data, these chimpanzees genetically cluster with P. t. schweinfurthii populations in East Africa. Conservation action and appropriate management plans are urgently needed to protect this important population and to prevent heavily-armed nomadic pastoralists from the Sahel, illegal miners, as well as elephant and meat poachers, from irretrievably destroying the natural vegetation and local biodiversity of the area.

Background The local social and physical environment influences health outcomes and individual behaviour. It remains unknown if the environmental influence is independent of individual socioeconomic status (SES). We studied the spatial distribution of mammography screening uptake in the Swiss urban population of Geneva and determined its independence from SES. Methods We used individual-level geo-referenced data (n = 5 002) from the participants in the Bus Santé study, a population-based cross-sectional study ongoing in Geneva since 1992. Data from 1992 to 2014 have been included in this study. Local indicators of spatial association (LISA) were calculated and used to assess the spatial dependence of mammography uptake (defined as having had a mammography in the past). We report unadjusted spatial clusters; adjusted for neighbourhood income and individual educational attainment; and for demographic variables (age and Swiss nationality). Furthermore, we evaluated the association between the distance to the nearest screening centre and the identified spatial clusters. Results Mammography uptake was not randomly distributed, with spatial clusters overlapping with those of SES. Spatial clusters were reduced to 56.2% of their initial size (n = 1,033) after adjustment for SES variables. Adjustment for age and nationality further reduced the proportion of individuals exhibiting spatially-dependent behaviour (to 36.5% of the initial size). Distance to the nearest screening centre was not associated with the spatial distribution of mammography uptake. Conclusions High definition spatial distribution studies using analysis of individual data allow identifying spatial clusters which are not based on pre-determined administrative units (e.g. postal code) but rather on individual behaviour. Persistent spatial clusters after adjustment for SES and demographic confounders suggest additional area-level determinants influencing the spatial distribution of mammography uptake. Key messages High definition spatial studies can help uncover new patterns of health outcomes distribution independent of SES and based on individual behaviour, rather than administrative units. While SES explains a great proportion of the spatial distribution of mammography uptake, other still elusive factors may be contributing to the observed spatial inequalities in mammography uptake.

samβada is a genome-environment association software, designed to search for signatures of local adaptation. However, pre- and postprocessing of data can be labour-intensive, preventing wider uptake of the method. We have now developed R.SamBada, an r-package providing a pipeline for landscape genomic analysis based on samβada, spanning from the retrieval of environmental conditions at sampling locations to gene annotation using the Ensembl genome browser. As a result, R.SamBada standardizes the landscape genomics pipeline and eases the search for candidate genes of local adaptation, enhancing reproducibility of landscape genomic studies. The efficiency and power of the pipeline is illustrated using two examples: sheep populations from Morocco with no evident population structure and Lidia cattle from Spain displaying population substructuring. In both cases, R.SamBada enabled rapid identification and interpretation of candidate genes, which are further discussed in the light of local adaptation. The package is available in the r CRAN package repository and on GitHub (github.com/SolangeD/R.SamBada).

Advances in high-throughput sequencing have promoted the collection of reference genomes and genome-wide diversity. However, the assessment of genomic variation among populations has hitherto mainly been surveyed through single-nucleotide polymorphisms (SNPs) and largely ignored the often major fraction of genomes represented by transposable elements (TEs). Despite accumulating evidence supporting the evolutionary significance of TEs, comprehensive surveys remain scarce. Here, we sequenced the full genomes of 304 individuals of Arabis alpina sampled from four nearby natural populations to genotype SNPs as well as polymorphic long terminal repeat retrotransposons (polymorphic TEs; i.e. presence/absence of TE insertions at specific loci). We identified 291,396 SNPs and 20,548 polymorphic TEs, comparing their contributions to genomic diversity and divergence across populations. Few SNPs were shared among populations and overall showed high population-specific variation, whereas most polymorphic TEs segregated among populations. The genomic context of these two classes of variants further highlighted candidate adaptive loci having a putative impact on functional genes. In particular, 4.96% of the SNPs were identified as non-synonymous or affecting start/stop codons. In contrast, 43% of the polymorphic TEs were present next to Arabis genes enriched in functional categories related to the regulation of reproduction and responses to biotic as well as abiotic stresses. This unprecedented dataset, mapping variation gained from SNPs and complementary polymorphic TEs within and among populations, will serve as a rich resource for addressing microevolutionary processes shaping genome variation. This article is protected by copyright. All rights reserved.

An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. The implementation of this approach requires the sampling phase to consider the complexity of environmental settings and the burden of logistic constraints. These important aspects are often underestimated in the literature dedicated to sampling strategies.In this study, we computed simulated genomic datasets to run against actual environmental data in order to trial landscape genomics experiments under distinct sampling strategies. These strategies differed by design approach (to enhance environmental and/or geographic representativeness at study sites), number of sampling locations and sample sizes. We then evaluated how these elements affected statistical performances (power and false discoveries) under two antithetical demographic scenarios.Our results highlight the importance of selecting an appropriate sample size, which should be modified based on the demographic characteristics of the studied population. For species with limited dispersal, sample sizes above 200 units are generally sufficient to detect most adaptive signals, while in random mating populations this threshold should be increased to 400 units. Furthermore, we describe a design approach that maximizes both environmental and geographical representativeness of sampling sites and show how it systematically outperforms random or regular sampling schemes. Finally, we show that although having more sampling locations (between 40 and 50 sites) increase statistical power and reduce false discovery rate, similar results can be achieved with a moderate number of sites (20 sites). Overall, this study provides valuable guidelines for optimizing sampling strategies for landscape genomics experiments.

Samples of 191 animals from 18 different Brazilian locally adapted swine genetic groups were genotyped using Illumina Porcine SNP60 BeadChip in order to identify selection signatures related to the monthly variation of Brazilian environmental variables. Using BayeScan software, 71 SNP markers were identified as FST outliers and 60 genotypes (58 markers) were found by Samβada software in 371 logistic models correlated with 112 environmental variables. Five markers were identified in both methods, with a Kappa value of 0.073 (95% CI: 0.011–0.134). The frequency of these markers indicated a clear north–south country division that reflects Brazilian environmental differences in temperature, solar radiation, and precipitation. Global spatial territory correlation for environmental variables corroborates this finding (average Moran's I = 0.89, range from 0.55 to 0.97). The distribution of alleles over the territory was not strongly correlated with the breed/genetic groups. These results are congruent with previous mtDNA studies and should be used to direct germplasm collection for the National gene bank.

AdaptMap consortium., [Background]: Since goat was domesticated 10,000 years ago, many factors have contributed to the differentiation of goat breeds and these are classified mainly into two types: (i) adaptation to different breeding systems and/or purposes and (ii) adaptation to different environments. As a result, approximately 600 goat breeds have developed worldwide; they differ considerably from one another in terms of phenotypic characteristics and are adapted to a wide range of climatic conditions. In this work, we analyzed the AdaptMap goat dataset, which is composed of data from more than 3000 animals collected worldwide and genotyped with the CaprineSNP50 BeadChip. These animals were partitioned into groups based on geographical area, production uses, available records on solid coat color and environmental variables including the sampling geographical coordinates, to investigate the role of natural and/or artificial selection in shaping the genome of goat breeds., [Results]: Several signatures of selection on different chromosomal regions were detected across the different breeds, sub-geographical clusters, phenotypic and climatic groups. These regions contain genes that are involved in important biological processes, such as milk-, meat- or fiber-related production, coat color, glucose pathway, oxidative stress response, size, and circadian clock differences. Our results confirm previous findings in other species on adaptation to extreme environments and human purposes and provide new genes that could explain some of the differences between goat breeds according to their geographical distribution and adaptation to different environments., [Conclusions]: These analyses of signatures of selection provide a comprehensive first picture of the global domestication process and adaptation of goat breeds and highlight possible genes that may have contributed to the differentiation of this species worldwide., Authors are grateful to all breeders and AdaptMap members who provided data to the initiative (http://www.goatadaptmap.org/) that are described in Stella et al.. The authors from the University of Milan are grateful to Stefano Frattini who was supported by the GenHome project, for supporting coordinating meetings. Support for Francesca Bertolini was provided by State of Iowa, hatch and Ensminger funds. Financial support provided in part by the Illumina Greater Good grant is appreciated.

PurposeLocal physical and social environment has a defining influence on individual behaviour and health-related outcomes. However, it remains undetermined if its impact is independent of individual socioeconomic status. In this study, we evaluated the spatial distribution of mammography adherence in the state of Geneva (Switzerland) using individual-level data and assessed its independence from socioeconomic status (SES).MethodsGeo-referenced individual-level data from the population-based cross-sectional Bus Santé study (n = 5,002) were used to calculate local indicators of spatial association (LISA) and investigate the spatial dependence of mammography adherence. Spatial clusters are reported without adjustment; adjusted for neighbourhood income and individual educational attainment; and demographic factors (age and Swiss nationality). The association between adjusted clusters and the proximity to the nearest screening centre was also evaluated.ResultsMammography adherence was not randomly distributed throughout Geneva with clusters geographically coinciding with known SES distributions. After adjustment for SES indicators, clusters were reduced to 56.2% of their original size (n = 1,033). Adjustment for age and nationality further reduced the number of individuals exhibiting spatially dependent behaviour (36.5% of the initial size). The identified SES-independent hot spots and cold-spots of mammography adherence were not explained by proximity to the nearest screening centre.ConclusionsSES and demographic factors play an important role in shaping the spatial distribution of mammography adherence. However, the spatial clusters persisted after confounder adjustment indicating that additional neighbourhood-level determinants could influence mammography adherence and be the object of targeted public health interventions.

ObjectiveTo identify populations and areas presenting higher consumption of sugar-sweetened beverages (SSB) and their overlap with populations and areas presenting higher body mass index (BMI).DesignCross-sectional population-based study.SettingState of Geneva, Switzerland.Participants15,767 non-institutionalized residents aged between 35 and 74 years (20 and 74 since 2011) of the state of Geneva, Switzerland.Main outcome measuresSpatial indices of sugar-sweetened beverage intake frequency and body mass index. Median regression analysis was used to control for characteristics of patients.ResultsThe SSB intake frequency and the BMI were not randomly distributed across the state. Among the 15,423 participants retained for the analyses, 2,034 (13.2%) were within clusters of high SSB intake frequency and 1,651 (10.7%) was within clusters of low SSB intake frequency, 11,738 (76.1%) showed no spatial dependence. We also identified clusters of BMI, 4,014 (26.0%) participants were within clusters of high BMI and 3,591 (23.3%) were within clusters of low BMI, 7,818 (50.7%) showed no spatial dependence. We found that clusters of SSB intake frequency and BMI overlap in specific areas. 1,719 (11.1%) participants were within high SSB intake frequency and high BMI clusters. After adjustment for covariates (education level, gender, age, nationality, and the median income of the area), the identified clusters persisted and were only slightly attenuated.ConclusionA fine-scale spatial approach allows identifying specific populations and areas presenting higher SSB consumption and, for some areas, higher SSB consumption associated with higher BMI. These findings could guide legislators to develop targeted interventions such as prevention campaigns and pave the way for precision public health.What is already known on this topicThe consumption of sugar-sweetened beverages (SSBs) is an important contributory factor of obesity and obesity-related diseases.SSB consumption varies according to socioeconomic status, which could explain the higher prevalence of obesity in specific areas.SSB taxation faces resistance in many countries due to its potential regressive nature.What this study addsThe spatial analysis of individual-level SSB consumption in the state of Geneva provides a clear identification of populations and areas presenting higher SSB consumption and, for some areas, higher SSB consumption along with higher body mass index (BMI).The results demonstrate the persistence of SSB clustering in the geographic space after adjusting for education level, gender, nationality, age, and neighborhood-level median income.The findings provide guidance for future public health interventions to reduce SSB consumption by better targeting vulnerable populations.

Occurrence of bacteria belonging to the order Chlamydiales was investigated for the first time in common toad (Bufo bufo) tadpole populations collected from 41 ponds in the Geneva metropolitan area, Switzerland. A Chlamydiales-specific Real-Time PCR was used to detect and amplify the Chlamydiales 16S rRNA-encoding gene from the tails of 375 tadpoles. We found the studied amphibian populations to be infected by “Chlamydia-like organisms” (CLOs) attributable to the genera Similichlamydia, Neochlamydia, Protochlamydia and Parachlamydia (belonging to the family Parachlamydiaceae), Simkania (family Simkaniaceae) and Estrella (family Criblamydiaceae); additionally, DNA from the genus Thermoanaerobacter (family Thermoanaerobacteriaceae) was detected. A global autocorrelation analysis did not reveal a spatial structure in the observed CLOs infection rates, and association tests involving land cover characteristics did not evidence any clear effect on CLOs infection rates in B. bufo. Despite preliminary, these results suggest a random and ubiquitous distribution of CLOs in the environment, which would support the biogeographical expectation “everything is everywhere” for the concerned microorganisms and their amoeba vectors.

Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine-scale models to evaluate environmental heterogeneity may help detecting adaptation to micro-habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata. The two gene pools identified, experiencing limited gene flow along a 1-km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine-scale topography. Using a large panel of DEM-derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high-resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.

INTRODUCTION: Daytime sleepiness is highly prevalent in the general adult population and has been linked to an increased risk of workplace and vehicle accidents, lower professional performance and poorer health. Despite the established relationship between noise and daytime sleepiness, little research has explored the individual-level spatial distribution of noise-related sleep disturbances. We assessed the spatial dependence of daytime sleepiness and tested whether clusters of individuals exhibiting higher daytime sleepiness were characterized by higher nocturnal noise levels than other clusters. DESIGN AND METHODS: Population-based cross-sectional study, in the city of Lausanne, Switzerland. Sleepiness was measured using the Epworth Sleepiness Scale (ESS) for 3697 georeferenced individuals from the CoLaus|PsyCoLaus cohort (period = 2009-2012). We used the sonBASE georeferenced database produced by the Swiss Federal Office for the Environment to characterize nighttime road traffic noise exposure throughout the city. We used the GeoDa software program to calculate the Getis-Ord Gi* statistics for unadjusted and adjusted ESS in order to detect spatial clusters of high and low ESS values. Modeled nighttime noise exposure from road and rail traffic was compared across ESS clusters. RESULTS: Daytime sleepiness was not randomly distributed and showed a significant spatial dependence. The median nighttime traffic noise exposure was significantly different across the three ESS Getis cluster classes (p

Background: Goat populations that are characterized within the AdaptMap project cover a large part of the worldwide distribution of this species and provide the opportunity to assess their diversity at a global scale. We analysed genome-wide 50K single nucleotide polymorphism (SNP) data from 144 populations to describe the global patterns of molecular variation, compare them to those observed in other livestock species, and identify the drivers that led to the current distribution of goats., Results: A high degree of genetic variability exists among the goat populations studied. Our results highlight a strong partitioning of molecular diversity between and within continents. Three major gene pools correspond to goats from Europe, Africa and West Asia. Dissection of sub-structures disclosed regional gene pools, which reflect the main post-domestication migration routes. We also identified several exchanges, mainly in African populations, and which often involve admixed and cosmopolitan breeds. Extensive gene flow has taken place within specific areas (e.g., south Europe, Morocco and Mali-Burkina Faso-Nigeria), whereas elsewhere isolation due to geographical barriers (e.g., seas or mountains) or human management has decreased local gene flows., Conclusions: After domestication in the Fertile Crescent in the early Neolithic era (ca. 12,000 YBP), domestic goats that already carried differentiated gene pools spread to Europe, Africa and Asia. The spread of these populations determined the major genomic background of the continental populations, which currently have a more marked subdivision than that observed in other ruminant livestock species. Subsequently, further diversification occurred at the regional level due to geographical and reproductive isolation, which was accompanied by additional migrations and/or importations, the traces of which are still detectable today. The effects of breed formation were clearly detected, particularly in Central and North Europe. Overall, our results highlight a remarkable diversity that occurs at the global scale and is locally partitioned and often affected by introgression from cosmopolitan breeds. These findings support the importance of long-term preservation of goat diversity, and provide a useful framework for investigating adaptive introgression, directing genetic improvement and choosing breeding targets.

The spatial structure of the environment (e.g. the configuration of habitat patches) may play an important role in determining the strength of local adaptation. However, previous studies of habitat heterogeneity and local adaptation have largely been limited to simple landscapes, which poorly represent the multiscale habitat structure common in nature. Here, we use simulations to pursue two goals: (i) we explore how landscape heterogeneity, dispersal ability and selection affect the strength of local adaptation, and (ii) we evaluate the performance of several genotype-environment association (GEA) methods for detecting loci involved in local adaptation. We found that the strength of local adaptation increased in spatially aggregated selection regimes, but remained strong in patchy landscapes when selection was moderate to strong. Weak selection resulted in weak local adaptation that was relatively unaffected by landscape heterogeneity. In general, the power of detection methods closely reflected levels of local adaptation. False-positive rates (FPRs), however, showed distinct differences across GEA methods based on levels of population structure. The univariate GEA approach had high FPRs (up to 55%) under limited dispersal scenarios, due to strong isolation by distance. By contrast, multivariate, ordination-based methods had uniformly low FPRs (0-2%), suggesting these approaches can effectively control for population structure. Specifically, constrained ordinations had the best balance of high detection and low FPRs and will be a useful addition to the GEA toolkit. Our results provide both theoretical and practical insights into the conditions that shape local adaptation and how these conditions impact our ability to detect selection.