Patient knowledge of gut microbiota and acceptability of fecal microbiota transplantation in various diseases.

BACKGROUND: Fecal microbiota transplantation (FMT) is now evaluated in various diseases. However, large-scale population treatment may encounter feasibility issues in terms of acceptance. We aim to evaluate patient knowledge of gut microbiota and the acceptability of FMT in various diseases. METHODS: Patients of Carenity's French online community were invited by email to participate in a questionnaire. The following parameters were assessed: patient's principal illness and duration, demographic data, therapeutics, dietary habits, knowledge of gut microbiota, probiotics and FMT, and its acceptability. KEY RESULTS: In total, 877 patients participated in the online questionnaire: 156 with inflammatory bowel disease (17.8%), 127 with rheumatoid arthritis (14.5%), 222 with ankylosing spondylitis (25.3%), 52 with lupus (5.9%), 64 with psoriasis (7.3%), 61 with obesity (7%), and 195 with type 2 diabetes (22.2%). Characteristics of participating patients were similar to those of the entire cohort (n = 23084). Overall, 47.1% (n = 413/877) of patients knew what the microbiota is with no difference among diseases. Knowledge was reported to be developed by patients themselves (203/413; 49.2%) without involving a healthcare professional. If proposed by a healthcare professional, 37.2% (326/877) reported being interested or very interested in undergoing FMT. Factors associated with good acceptability of FMT were the male sex (OR: 1.63, CI95% [1.14 to 2.32]), previous knowledge of FMT (OR: 4.16, CI95% [2.92 to 5.96]), and previous knowledge of gut microbiota (OR: 1.54, CI95% [1.05 to 2.24]). CONCLUSION AND INFERENCES: Knowledge of gut microbiota is still limited in patients' communities and mainly developed by patients themselves, impacting FMT acceptability.

The phyllosphere microbiome of host trees contributes more than leaf phytochemicals to variation in the Agrilus planipennis Fairmaire gut microbiome structure.

The microbiome composition of living organisms is closely linked to essential functions determining the fitness of the host for thriving and adapting to a particular ecosystem. Although multiple factors, including the developmental stage, the diet, and host-microbe coevolution have been reported to drive compositional changes in the microbiome structures, very few attempts have been made to disentangle their various contributions in a global approach. Here, we focus on the emerald ash borer (EAB), an herbivorous pest and a real threat to North American ash tree species, to explore the responses of the adult EAB gut microbiome to ash leaf properties, and to identify potential predictors of EAB microbial variations. The relative contributions of specific host plant properties, namely bacterial and fungal communities on leaves, phytochemical composition, and the geographical coordinates of the sampling sites, to the EAB gut microbial community was examined by canonical analyses. The composition of the phyllosphere microbiome appeared to be a strong predictor of the microbial community structure in EAB guts, explaining 53 and 48% of the variation in fungi and bacteria, respectively. This study suggests a potential covariation of the microorganisms associated with food sources and the insect gut microbiome.

Horizontal gene transfer and recombination analysis of SARS-CoV-2 genes helps discover its close relatives and shed light on its origin.

BACKGROUND: The SARS-CoV-2 pandemic is one of  the greatest  global medical and social challenges that have emerged in recent history. Human coronavirus strains discovered during previous SARS outbreaks have been hypothesized to pass from bats to humans using intermediate hosts, e.g. civets for SARS-CoV and camels for MERS-CoV. The discovery of an intermediate host of SARS-CoV-2 and the identification of specific mechanism of its emergence in humans are topics of primary evolutionary importance. In this study we investigate the evolutionary patterns of 11 main genes of SARS-CoV-2. Previous studies suggested that the genome of SARS-CoV-2 is highly similar to the horseshoe bat coronavirus RaTG13 for most of the genes and to some Malayan pangolin coronavirus (CoV) strains for the receptor binding (RB) domain of the spike protein. RESULTS: We provide a detailed list of statistically significant horizontal gene transfer and recombination events (both intergenic and intragenic) inferred for each of 11 main genes of the SARS-CoV-2 genome. Our analysis reveals that two continuous regions of genes S and N of SARS-CoV-2 may result from intragenic recombination between RaTG13 and Guangdong (GD) Pangolin CoVs. Statistically significant gene transfer-recombination events between RaTG13 and GD Pangolin CoV have been identified in region [1215-1425] of gene S and region [534-727] of gene N. Moreover, some statistically significant recombination events between the ancestors of SARS-CoV-2, RaTG13, GD Pangolin CoV and bat CoV ZC45-ZXC21 coronaviruses have been identified in genes ORF1ab, S, ORF3a, ORF7a, ORF8 and N. Furthermore, topology-based clustering of gene trees inferred for 25 CoV organisms revealed a three-way evolution of coronavirus genes, with gene phylogenies of ORF1ab, S and N forming the first cluster, gene phylogenies of ORF3a, E, M, ORF6, ORF7a, ORF7b and ORF8 forming the second cluster, and phylogeny of gene ORF10 forming the third cluster. CONCLUSIONS: The results of our horizontal gene transfer and recombination analysis suggest that SARS-CoV-2 could not only be a chimera virus resulting from recombination of the bat RaTG13 and Guangdong pangolin coronaviruses but also a close relative of the bat CoV ZC45 and ZXC21 strains. They also indicate that a GD pangolin may be an intermediate host of this dangerous virus.

Does diversity beget diversity in microbiomes?

Microbes are embedded in complex communities where they engage in a wide array of intra- and inter-specific interactions. The extent to which these interactions drive or impede microbiome diversity is not well understood. Historically, two contrasting hypotheses have been suggested to explain how species interactions could influence diversity. 'Ecological Controls' (EC) predicts a negative relationship, where the evolution or migration of novel types is constrained as niches become filled. In contrast, 'Diversity Begets Diversity' (DBD) predicts a positive relationship, with existing diversity promoting the accumulation of further diversity via niche construction and other interactions. Using high-throughput amplicon sequencing data from the Earth Microbiome Project, we provide evidence that DBD is strongest in low-diversity biomes, but weaker in more diverse biomes, consistent with biotic interactions initially favouring the accumulation of diversity (as predicted by DBD). However, as niches become increasingly filled, diversity hits a plateau (as predicted by EC).

Chronic patients' satisfaction and priorities regarding medical care, information and services and quality of life: a French online patient community survey.

BACKGROUND: The French healthcare system is evolving to meet the challenges of an aging population, the growing prevalence of chronic diseases, the development of new technologies and the increasing involvement of patients in the management of their disease. The aim of this study is to assess the satisfaction and priorities of chronic patients regarding medical care, information and services and their quality of life. METHODS: A cross-sectional study was conducted from February to March 2018 via the French Carenity platform. Adult patients enrolled in type 1 diabetes, heart failure or obesity communities were invited to answer an online questionnaire. A numeric scale from 0 (meaning not satisfied) to 5 was used to evaluate patients' satisfaction. Patients' priorities were assessed using a ranking question. Patients' satisfaction and priorities have been combined in a matrix to identify patients' expectations. RESULTS: Sixty-seven respondents of each condition answered a questionnaire. The most important and least satisfactory items about medical care are availability and active listening from healthcare providers, as well as access to coordinated and multidisciplinary care. Regarding information and services, respondents mostly expect connected medical devices, in addition to lifestyle and dietary measures. As for the quality of life, respondents fear that their chronic condition will keep impacting their daily mood and ability to do physical activities. CONCLUSIONS: This study shows that chronic patients want to be more actively involved in their care pathway. Patient training and therapeutic patient education programs could help them manage their chronic conditions within a patient-centred healthcare system.

Moderate disturbances accelerate forest transition dynamics under climate change in the temperate-boreal ecotone of eastern North America.

Several temperate tree species are expected to migrate northward and colonize boreal forests in response to climate change. Tree migrations could lead to transitions in forest types, but these could be influenced by several non-climatic factors, such as disturbances and soil conditions. We analysed over 10,000 forest inventory plots, sampled from 1970 to 2018 in meridional Québec, Canada, to identify what environmental conditions promote or prevent regional-scale forest transitions. We used a continuous-time multi-state Markov model to quantify the probabilities of transitions between forest states (temperate, boreal, mixed, pioneer) as a function of climate (mean temperature and climate moisture index during the growing season), soil conditions (pH and drainage) and disturbances (severity levels of natural disturbances and logging). We further investigate how different disturbance types and severities impact forests' short-term transient dynamics and long-term equilibrium using properties of Markov transition matrices. The most common transitions observed during the study period were from mixed to temperate states, as well as from pioneer to boreal forests. In our study, transitions were mainly driven by natural and anthropogenic disturbances and secondarily by climate, whereas soil characteristics exerted relatively minor constraints. While major disturbances only promoted transitions to the pioneer state, moderate disturbances increased the probability of transition from mixed to temperate states. Long-term projections of our model under the current environmental conditions indicate that moderate disturbances would promote a northward shift of the temperate forest. Moreover, disturbances reduced turnover and convergence time for all transitions, thereby accelerating forest dynamics. Contrary to our expectation, mixed to temperate transitions were not driven by temperate tree recruitment but by mortality and growth. Overall, our results suggest that moderate disturbances could catalyse rapid forest transitions and accelerate broad-scale biome shifts.

Partitioning plant spectral diversity into alpha and beta components.

Plant spectral diversity - how plants differentially interact with solar radiation - is an integrator of plant chemical, structural, and taxonomic diversity that can be remotely sensed. We propose to measure spectral diversity as spectral variance, which allows the partitioning of the spectral diversity of a region, called spectral gamma (γ) diversity, into additive alpha (α; within communities) and beta (ß; among communities) components. Our method calculates the contributions of individual bands or spectral features to spectral γ-, ß-, and α-diversity, as well as the contributions of individual plant communities to spectral diversity. We present two case studies illustrating how our approach can identify 'hotspots' of spectral α-diversity within a region, and discover spectrally unique areas that contribute strongly to ß-diversity. Partitioning spectral diversity and mapping its spatial components has many applications for conservation since high local diversity and distinctiveness in composition are two key criteria used to determine the ecological value of ecosystems.

Adverse Birth Outcomes as Indicators of Poor Fetal Growth Conditions in a French Newborn Population-A Stratified Analysis by Neighborhood Deprivation Level.

Background: Adverse birth outcomes are related to unfavorable fetal growth conditions. A latent variable, named Favorable Fetal Growth Condition (FFGC), has been defined by Bollen et al., in 2013; he showed that this FFGC latent variable mediates the effects of maternal characteristics on several birth outcomes. Objectives: The objectives of the present study were to replicate Bollen's approach in a population of newborns in Paris and to investigate the potential differential effect of the FFGC latent variable according to the neighborhood socioeconomic level. Methods: Newborn health data were available from the first birth certificate registered by the Maternal and Child Care department of the City of Paris. All newborns (2008-2011) were geocoded at the mother residential census block. Each census block was assigned a socioeconomic deprivation level. Several mothers' characteristics were collected from the birth certificates: age, parity, education and occupational status and the occupational status of the father. Three birth outcomes were considered: birth weight (BW), birth length (BL) and gestational age (GA). Results: Using a series of structural equation models, we confirm that the undirected model (that includes the FFGC latent variable) provided a better fit for the data compared with the model where parental characteristics directly affected BW, BL, and/or GA. However, the strength, the direction and statistical significance of the associations between the exogenous variables and the FFGC were different according to the neighborhood deprivation level. Conclusion: Future research should be designed to assess the how robust the FFGC latent variable is across populations and should take into account neighborhood characteristics to identify the most vulnerable group and create better design prevention policies.

A temporal beta-diversity index to identify sites that have changed in exceptional ways in space-time surveys.

AIM: This paper presents the statistical bases for temporal beta-diversity analysis, a method to study changes in community composition through time from repeated surveys at several sites. Surveys of that type are presently done by ecologists around the world. A temporal beta-diversity Index (TBI) is computed for each site, measuring the change in species composition between the first (T1) and second surveys (T2). TBI indices can be decomposed into losses and gains; they can also be tested for significance, allowing one to identify the sites that have changed in composition in exceptional ways. This method will be of value to identify exceptional sites in space-time surveys carried out to study anthropogenic impacts, including climate change. INNOVATION: The null hypothesis of the TBI test is that a species assemblage is not exceptionally different between T1 and T2, compared to assemblages that could have been observed at this site at T1 and T2 under conditions corresponding to H0. Tests of significance of coefficients in a dissimilarity matrix are usually not possible because the values in the matrix are interrelated. Here, however, the dissimilarity between T1 and T2 for a site is computed with different data from the dissimilarities used for the T1-T2 comparison at other sites. It is thus possible to compute a valid test of significance in that case. In addition, the paper shows how TBI dissimilarities can be decomposed into loss and gain components (of species, or abundances-per-species) and how a B-C plot can be produced from these components, which informs users about the processes of biodiversity losses and gains through time in space-time survey data. MAIN CONCLUSION: Three applications of the method to different ecological communities are presented. This method is applicable worldwide to all types of communities, marine, and terrestrial. R software is available implementing the method.

Premature Adult Death and Equity Impact of a Reduction of NO2, PM10, and PM2.5 Levels in Paris-A Health Impact Assessment Study Conducted at the Census Block Level.

Background: To support environmental policies aiming to tackle air pollution, quantitative health impact assessments (HIAs) stand out as one of the best decision-making tools. However, no risk assessment studies have quantified or mapped the health and equity impact of air pollution reduction at a small spatial scale. Objectives: We developed a small-area analysis of the impact of air pollution on "premature" death among an adult population over 30 years of age to quantify and map the health and equity impact related to a reduction of air pollution. Methods: All-cause mortality data of an adult population (>30 years) from January 2004 to December 2009 were geocoded at the residential census block level in Paris. Each census block was assigned socioeconomic deprivation levels and annual average ambient concentrations of NO2, PM10, and PM2.5. HIAs were used to estimate, at a small-area level, the number of "premature" deaths associated with a hypothetical reduction of NO2, PM10, and PM2.5 exposure. In total, considering global dose response function for the three pollutants and socioeconomic deprivation specific dose response function, nine HIAs were performed for NO2 and six and four HIAs for PM10 and PM2.5, respectively. Finally, a clustering approach was used to quantify how the number of "premature" deaths could vary according to deprivation level. Results: The number of deaths attributable to NO2, PM10, and PM2.5 exposure were equal to 4301, 3209, and 2662 deaths, respectively. The most deprived census blocks always appeared as one of the groups most impacted by air pollution. Our findings showed that "premature" deaths attributable to NO2 were not randomly distributed over the study area, with a cluster of excess "premature" deaths located in the northeastern area of Paris. Discussion: This study showed the importance of stratifying an environmental burden of disease study on the socioeconomic level, in order to take into consideration the modifier effect of socioeconomic status on the air pollution-mortality relationship. In addition, we demonstrated the value of spatial analysis to guide decision-making. This shows the need for tools to support priority-setting and to guide policymakers in their choice of environmental initiatives that would maximize health gains and reduce social inequalities in health.

Astronomical and atmospheric impacts on deep-sea hydrothermal vent invertebrates.

Ocean tides and winter surface storms are among the main factors driving the dynamics and spatial structure of marine coastal species, but the understanding of their impact on deep-sea and hydrothermal vent communities is still limited. Multidisciplinary deep-sea observatories offer an essential tool to study behavioural rhythms and interactions between hydrothermal community dynamics and environmental fluctuations. Here, we investigated whether species associated with a Ridgeia piscesae tubeworm vent assemblage respond to local ocean dynamics. By tracking variations in vent macrofaunal abundance at different temporal scales, we provide the first evidence that tides and winter surface storms influence the distribution patterns of mobile and non-symbiotic hydrothermal species (i.e. pycnogonids Sericosura sp. and Polynoidae polychaetes) at more than 2 km depth. Local ocean dynamics affected the mixing between hydrothermal fluid inputs and surrounding seawater, modifying the environmental conditions in vent habitats. We suggest that hydrothermal species respond to these habitat modifications by adjusting their behaviour to ensure optimal living conditions. This behaviour may reflect a specific adaptation of vent species to their highly variable habitat.

Human and natural controls of the variation in aboveground tree biomass in African dry tropical forests.

Understanding the anthropogenic and natural controls that affect the patterns, distribution, and dynamics of terrestrial carbon is crucial to meeting climate change mitigation objectives. We assessed the human and natural controls over aboveground tree biomass density in African dry tropical forests, using Zambia's first nationwide forest inventory. We identified predictors that best explain the variation in biomass density, contrasted anthropogenic and natural sites at different spatial scales, and compared sites with different stand structure characteristics and species composition. In addition, we evaluated the effects of different management and conservation practices on biomass density. Variation in biomass density was mostly determined by biotic processes, linked with both species richness and dominance (evenness), and to a lesser extent, by land use, environmental controls, and spatial structure. Biomass density was negatively associated with tree species evenness and positively associated with species richness for both natural and human-modified sites. Human influence variables (including distance to roads, distance to town, fire occurrence, and the population on site) did not explain substantial variation in biomass density in comparison to biodiversity variables. The relationship of human activities to biomass density in managed sites appears to be mediated by effects on species diversity and stand structure characteristics, with lower values in human-modified sites for all metrics tested. Small contrasts in carbon density between human-modified and natural forest sites signal the potential to maintain carbon in the landscape inside but also outside forestlands in this region. Biodiversity is positively related to biomass density in both human and natural sites, demonstrating potential synergies between biodiversity conservation and climate change mitigation. This is the first evidence of positive outcomes of protected areas and participatory forest management on carbon storage at national scale in Zambia. This research shows that understanding controls over biomass density can provide policy relevant inputs for carbon management and on ecological processes affecting carbon storage.

The Willow Microbiome Is Influenced by Soil Petroleum-Hydrocarbon Concentration with Plant Compartment-Specific Effects.

The interaction between plants and microorganisms, which is the driving force behind the decontamination of petroleum hydrocarbon (PHC) contamination in phytoremediation technology, is poorly understood. Here, we aimed at characterizing the variations between plant compartments in the microbiome of two willow cultivars growing in contaminated soils. A field experiment was set-up at a former petrochemical plant in Canada and after two growing seasons, bulk soil, rhizosphere soil, roots, and stems samples of two willow cultivars (Salix purpurea cv. FishCreek, and Salix miyabeana cv. SX67) growing at three PHC contamination concentrations were taken. DNA was extracted and bacterial 16S rRNA gene and fungal internal transcribed spacer (ITS) regions were amplified and sequenced using an Ion Torrent Personal Genome Machine (PGM). Following multivariate statistical analyses, the level of PHC-contamination appeared as the primary factor influencing the willow microbiome with compartment-specific effects, with significant differences between the responses of bacterial, and fungal communities. Increasing PHC contamination levels resulted in shifts in the microbiome composition, favoring putative hydrocarbon degraders, and microorganisms previously reported as associated with plant health. These shifts were less drastic in the rhizosphere, root, and stem tissues as compared to bulk soil, probably because the willows provided a more controlled environment, and thus, protected microbial communities against increasing contamination levels. Insights from this study will help to devise optimal plant microbiomes for increasing the efficiency of phytoremediation technology.

Understanding the Spatio-Temporal Response of Coral Reef Fish Communities to Natural Disturbances: Insights from Beta-Diversity Decomposition.

Understanding how communities respond to natural disturbances is fundamental to assess the mechanisms of ecosystem resistance and resilience. However, ecosystem responses to natural disturbances are rarely monitored both through space and time, while the factors promoting ecosystem stability act at various temporal and spatial scales. Hence, assessing both the spatial and temporal variations in species composition is important to comprehensively explore the effects of natural disturbances. Here, we suggest a framework to better scrutinize the mechanisms underlying community responses to disturbances through both time and space. Our analytical approach is based on beta diversity decomposition into two components, replacement and biomass difference. We illustrate this approach using a 9-year monitoring of coral reef fish communities off Moorea Island (French Polynesia), which encompassed two severe natural disturbances: a crown-of-thorns starfish outbreak and a hurricane. These disturbances triggered a fast logistic decline in coral cover, which suffered a 90% decrease on all reefs. However, we found that the coral reef fish composition remained largely stable through time and space whereas compensatory changes in biomass among species were responsible for most of the temporal fluctuations, as outlined by the overall high contribution of the replacement component to total beta diversity. This suggests that, despite the severity of the two disturbances, fish communities exhibited high resistance and the ability to reorganize their compositions to maintain the same level of total community biomass as before the disturbances. We further investigated the spatial congruence of this pattern and showed that temporal dynamics involved different species across sites; yet, herbivores controlling the proliferation of algae that compete with coral communities were consistently favored. These results suggest that compensatory changes in biomass among species and spatial heterogeneity in species responses can provide further insurance against natural disturbances in coral reef ecosystems by promoting high levels of key species (herbivores). They can also allow the ecosystem to recover more quickly.

Thirty-year recovery of mollusc communities after nuclear experimentations on Fangataufa atoll (Tuamotu, French Polynesia).

A 30-year study of temporal changes in gastropod community structure on the reefs of a Pacific Ocean atoll (Fangataufa, Tuamotu Archipelago) subjected to atmospheric nuclear tests during the 1960s offered the opportunity for an otherwise impossible field experiment that could help ecologists understand mollusc primary succession. Reef molluscs were partly or entirely wiped out by the heat of the nuclear tests and the reefs were recolonized by ocean larvae. On all reefs, community composition before the tests was very different from what it evolved to afterwards. A new method of analysis was developed to study the temporal variation in community composition before versus after the tests (temporal beta diversity). Analyses showed that community compositions diverged through time among the reefs. Only some species can survive the harsh conditions of supralittoral zones, so the same species recolonized them; environmental filtering controlled the development of the new communities. In the reef flat and edge zones, differences in community composition seem to be the result of neutral stochastic colonization by larvae coming from the open ocean. All reefs developed a community composition quite different from that before the nuclear tests.

Using phylogenetic information and chemical properties to predict species tolerances to pesticides.

Direct estimation of species' tolerance to pesticides and other toxic organic substances is a combinatorial problem, because of the large number of species-substance pairs. We propose a statistical modelling approach to predict tolerances associated with untested species-substance pairs, by using models fitted to tested pairs. This approach is based on the phylogeny of species and physico-chemical descriptors of pesticides, with both kinds of information combined in a bilinear model. This bilinear modelling approach predicts tolerance in untested species-compound pairs based on the facts that closely related species often respond similarly to toxic compounds and that chemically similar compounds often have similar toxic effects. The three tolerance models (median lethal concentration after 96 h) used up to 25 aquatic animal species and up to nine pesticides (organochlorines, organophosphates and carbamates). Phylogeny was estimated using DNA sequences, while the pesticides were described by their mode of toxic action and their octanol-water partition coefficients. The models explained 77-84% of the among-species variation in tolerance (log10 LC50). In cross-validation, 84-87% of the predicted tolerances for individual species were within a factor of 10 of the observed values. The approach can also be used to model other species response to multivariate stress factors.

Oxidative stress modulates the expression of genes involved in cell survival in ΔF508 cystic fibrosis airway epithelial cells.

Although cystic fibrosis (CF) pathophysiology is explained by a defect in CF transmembrane conductance regulator (CFTR) protein, the broad spectrum of disease severity is the consequence of environmental and genetic factors. Among them, oxidative stress has been demonstrated to play an important role in the evolution of this disease, with susceptibility to oxidative damage, decline of pulmonary function, and impaired lung antioxidant defense. Although oxidative stress has been implicated in the regulation of inflammation, its molecular outcomes in CF cells remain to be evaluated. To address the question, we compared the gene expression profile in NuLi-1 cells with wild-type CFTR and CuFi-1 cells homozygous for ΔF508 mutation cultured at air-liquid interface. We analyzed the transcriptomic response of these cell lines with microarray technology, under basal culture conditions and after 24 h oxidative stress induced by 15 µM 2,3-dimethoxy-1,4-naphtoquinone. In the absence of oxidative conditions, CuFi-1 gene profiling showed typical dysregulated inflammatory responses compared with NuLi-1. In the presence of oxidative conditions, the transcriptome of CuFi-1 cells reflected apoptotic transcript modulation. These results were confirmed in the CFBE41o- and corrCFBE41o- cell lines as well as in primary culture of human CF airway epithelial cells. Altogether, our data point to the influence of oxidative stress on cell survival functions in CF and identify several genes that could be implicated in the inflammation response observed in CF patients.

Rhythms and community dynamics of a hydrothermal tubeworm assemblage at main endeavour field - a multidisciplinary deep-sea observatory approach.

The NEPTUNE cabled observatory network hosts an ecological module called TEMPO-mini that focuses on hydrothermal vent ecology and time series, granting us real-time access to data originating from the deep sea. In 2011-2012, during TEMPO-mini's first deployment on the NEPTUNE network, the module recorded high-resolution imagery, temperature, iron (Fe) and oxygen on a hydrothermal assemblage at 2186 m depth at Main Endeavour Field (North East Pacific). 23 days of continuous imagery were analysed with an hourly frequency. Community dynamics were analysed in detail for Ridgeia piscesae tubeworms, Polynoidae, Pycnogonida and Buccinidae, documenting faunal variations, natural change and biotic interactions in the filmed tubeworm assemblage as well as links with the local environment. Semi-diurnal and diurnal periods were identified both in fauna and environment, revealing the influence of tidal cycles. Species interactions were described and distribution patterns were indicative of possible microhabitat preference. The importance of high-resolution frequencies (<1 h) to fully comprehend rhythms in fauna and environment was emphasised, as well as the need for the development of automated or semi-automated imagery analysis tools.

Statistical methods for temporal and space-time analysis of community composition data.

This review focuses on the analysis of temporal beta diversity, which is the variation in community composition along time in a study area. Temporal beta diversity is measured by the variance of the multivariate community composition time series and that variance can be partitioned using appropriate statistical methods. Some of these methods are classical, such as simple or canonical ordination, whereas others are recent, including the methods of temporal eigenfunction analysis developed for multiscale exploration (i.e. addressing several scales of variation) of univariate or multivariate response data, reviewed, to our knowledge for the first time in this review. These methods are illustrated with ecological data from 13 years of benthic surveys in Chesapeake Bay, USA. The following methods are applied to the Chesapeake data: distance-based Moran's eigenvector maps, asymmetric eigenvector maps, scalogram, variation partitioning, multivariate correlogram, multivariate regression tree, and two-way MANOVA to study temporal and space-time variability. Local (temporal) contributions to beta diversity (LCBD indices) are computed and analysed graphically and by regression against environmental variables, and the role of species in determining the LCBD values is analysed by correlation analysis. A tutorial detailing the analyses in the R language is provided in an appendix.

Genetic structure of the white-footed mouse in the context of the emergence of Lyme disease in southern Québec.

The white-footed mouse (Peromyscus leucopus) has expanded its northern limit into southern Québec over the last few decades. P. leucopus is a great disperser and colonizer and is of particular interest because it is considered a primary reservoir for the spirochete bacterium that causes Lyme disease. There is no current information on the gene flow between mouse populations on the mountains and forest fragments found scattered throughout the Montérégie region in southern Québec, and whether various landscape barriers have an effect on their dispersal. We conducted a population genetics analysis on eleven P. leucopus populations using eleven microsatellite markers and showed that isolation by distance was weak, yet barriers were effective. The agricultural matrix had the least effect on gene flow, whereas highways and main rivers were effective barriers. The abundance of ticks collected from mice varied within the study area. Both ticks and mice were screened for the presence of the spirochete bacterium Borrelia burgdorferi, and we predicted areas of greater risk for Lyme disease. Merging our results with ongoing Lyme disease surveillance programs will help determine the future threat of this disease in Québec, and will contribute toward disease prevention and management strategies throughout fragmented landscapes in southern Canada.