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Aim: Food webs are essential for understanding how ecosystems function, but empirical data on the interactions that make up these ecological networks are lacking for most taxa in most ecosystems. Trait‐based models can fill these data gaps, but their ability to do so has not been widely tested. We test how well these models can extrapolate to new ecological communities both in terms of pairwise predator–prey interactions and higher level food web attributes (i.e. species position, food web‐level properties). Location: Canada, Europe, Tanzania. Time Period: Current. Major Taxa Studied: Terrestrial vertebrates. Methods: We train trait‐based models of pairwise trophic interactions on four independent vertebrate food webs (Canadian tundra, Serengeti, alpine south‐eastern Pyrenees and Europe) and evaluate how well these models predict pairwise interactions and network properties of each food web. Results: We find that, overall, trait‐based models predict most interactions and their absence correctly. Performance was best for training and testing on the same food web (AUC > 0.90) and declined with environmental and phylogenetic distances with the strongest loss of performance for the tundra‐Serengeti ecosystems (AUC > 0.75). Network metrics were less well‐predicted than single interactions by our models with predicted food webs being more connected, less modular, and with higher mean trophic levels than observed. Main Conclusions: Theory predicts that the variability observed in food webs can be explained by differences in trait distributions and trait‐matching relationships. Our finding that trait‐based models can predict many trophic interactions, even in contrasting environments, adds to the growing body of evidence that there are general constraints on interactions and that trait‐based methods can serve as a useful first approximation of food webs in unknown areas. However, food webs are more than the sum of their parts, and predicting network attributes will likely require models that simultaneously predict individual interactions and community constraints. [ABSTRACT FROM AUTHOR]

Who interacts with whom is a key question in community and network ecology. The concept that these interactions may be driven by a match between the traits of consumer and resource species is known as trait‐matching. If trait‐matching would allow for general predictions of interaction structure based on sufficiently few and easily‐measurable traits, then this approach could replace the laborious description of each individual pairwise interaction. To resolve imprints of trait‐matching in a species‐rich tri‐trophic Salix–galler–parasitoid network, and to identify the most relevant traits, we applied five different methods, each approaching the same phenomenon from a different perspective. As traits, we used, body sizes, gall type (position on plant, structure of gall) and phenology, among others, as well as phylogenetic proxies. When jointly applied, the methods demonstrate distinctly different imprints of traits within the two bipartite network elements (Salix–galler versus galler–parasitoid interactions). Of the galler–parasitoid sub‐network's interactions, approximately half were explainable by the species traits used; of the Salix–galler sub‐network's interactions, traits explained at most two‐fifths. Gall type appeared to be the most important structuring trait in both networks. Phylogeny explained as much, or more than did our tested traits, suggesting that traits may be conserved and phylogeny therefore an effective proxy. Overall, the more specialized structure of the Salix–galler network versus the more nested structure of the galler–parasitoid network meant that different methods were more effective at capturing interactions and interaction structure in the different sub‐networks. Thus, our analysis reveals how structuring impacts may vary even between levels within the same multitrophic network, and calls for comparative analyses of trait matching across a wide set of systems and methods. [ABSTRACT FROM AUTHOR]

Root-associated microbes can alleviate plant abiotic stresses, thus potentially supporting adaptation to a changing climate or to novel environments during range expansion. While climate change is extending plant species fundamental niches northward, the distribution and colonization of mutualists (e.g., arbuscular mycorrhizal fungi) and pathogens may constrain plant growth and regeneration. Yet, the degree to which biotic and abiotic factors impact plant performance and associated microbial communities at the edge of their distribution remains unclear. Here, we use root microscopy, coupled with amplicon sequencing, to study bacterial, fungal, and mycorrhizal root-associated microbial communities from sugar maple seedlings distributed across two temperate-to-boreal elevational gradients in southern Québec, Canada. Our findings demonstrate that soil pH, soil Ca, and distance to sugar maple trees are key drivers of root-associated microbial communities, overshadowing the influence of elevation. Interestingly, changes in root fungal community composition mediate an indirect effect of soil pH on seedling growth, a pattern consistent at both sites. Overall, our findings highlight a complex role of biotic and abiotic factors in shaping tree-microbe interactions, which are in turn correlated with seedling growth. These findings have important ramifications for tree range expansion in response to shifting climatic niches. The analysis of root fungal, mycorrhizal, and bacterial communities of tree seedlings sampled across elevation gradients reveals strong effects of edaphic factors on microbial communities and interactions between root microbes and seedling growth. [ABSTRACT FROM AUTHOR]

The three‐dimensional rarity typology proposed by Rabinowitz in 1981, based on geographic range, habitat specificity, and local abundance, is among the most widely used frameworks for describing rarity in ecological and conservation research. While this framework is descriptive and is not meant to explain the causes of rarity, recent advances in ecology may be leveraged to add explanatory power. Here we present a macroecological exploration of rarity and its underlying causes. We propose a modification of Rabinowitz's typology to better distinguish between the dimensions of rarity and the ecological processes that drive them, and explore the conservation implications of our modified framework. We propose to add occupancy (the proportion of occupied sites within a species' range) as a rarity axis, and recast habitat specificity as a cause of rarity, thus yielding a modified classification based on range size, occupancy, and local abundance. Under our framework, habitat specialists are no longer considered rare if they are widespread and abundant; we argue that this modification more accurately identifies truly rare species, as habitat specialists may be common if their habitat is abundant. Finally, we draw on the macroecological and theoretical literature to identify the key processes and associated traits that drive each rarity axis. In this respect, we identify four processes (environmental filtering, movement, demography and interactions), and hypothesise that range size and occupancy are primarily driven by environmental filtering and movement, whereas local abundance is more strongly influenced by demography and interactions. We further use ecological theory to hypothesise the conservation concerns associated with each rarity axis, and propose conservation measures that may be suitable for conserving different types of rare species. Our work may provide a basis for developing hypotheses about the causes of rarity of particular focal taxa or groups, and inform the development of targeted conservation strategies. [ABSTRACT FROM AUTHOR]

The integration of ecosystem processes over large spatial extents is critical to predicting whether and how local and global changes may impact biodiversity and ecosystem functions. Yet, there remains an important gap in meta‐ecosystem models to predict multiple functions (e.g. carbon sequestration, elemental cycling, trophic efficiency) across ecosystem types (e.g. terrestrial‐aquatic, benthic‐pelagic). We derive a flexible meta‐ecosystem model to predict ecosystem functions at landscape extents by integrating the spatial dimension of natural systems as spatial networks of different habitat types connected by cross‐ecosystem flows of materials and organisms. We partition the physical connectedness of ecosystems from the spatial flow rates of materials and organisms, allowing the representation of all types of connectivity across ecosystem boundaries. Through simulating a forest‐lake‐stream meta‐ecosystem, our model illustrates that even if spatial flows induced significant local losses of nutrients, differences in local ecosystem efficiencies could lead to increased secondary production at regional scale. This emergent result, which we dub the 'cross‐ecosystem efficiency hypothesis', emphasizes the importance of integrating ecosystem diversity and complementarity in meta‐ecosystem models to generate empirically testable hypotheses for ecosystem functions. [ABSTRACT FROM AUTHOR]

The Arctic is warming at an alarming rate. While changes in plant community composition and phenology have been extensively reported, the effects of climate change on reproduction remain poorly understood. We quantified multidecadal changes in flower density for nine tundra plant species at a low- and a high-Arctic site in Greenland. We found substantial changes in flower density over time, but the temporal trends and drivers of flower density differed both between species and sites. Total flower density increased over time at the low-Arctic site, whereas the high-Arctic site showed no directional change. Within and between sites, the direction and rate of change differed among species, with varying effects of summer temperature, the temperature of the previous autumn and the timing of snowmelt. Finally, all species showed a strong trade-off in flower densities between successive years, suggesting an effective cost of reproduction. Overall, our results reveal region- and taxon-specific variation in the sensitivity and responses of co-occurring species to shared climatic drivers, and a clear cost of reproductive investment among Arctic plants. The ultimate effects of further changes in climate may thus be decoupled between species and across space, with critical knock-on effects on plant species dynamics, food web structure and overall ecosystem functioning. [ABSTRACT FROM AUTHOR]

Background: Infrared thermography (IRT) techniques and full-field deformation calorimetry approaches have profoundly impacted the experimental mechanics community. The way in which granular materials are tested is currently excluded from this trend, as evidenced by the small number of papers in the literature mentioning the use of thermographic cameras. Objective: The objective of this work was to perform a thermomechanical analysis of soft granular systems by distinguishing temperature changes associated with thermoelastic coupling (TEC) and mechanical dissipation (MD). Methods: Cyclic confined compression was applied to different granular systems consisting of ellipsoidal cross-section cylinders made of thermoplastic polyurethane. The temperatures measured using IRT were processed to identify the heat associated with TEC and MD, based on considerations of adiabaticity and thermodynamic cycle completion. Various granular configurations and spatial resolutions of the thermal maps were compared. Results: Strong TEC is revealed around the contact areas between all particles, which can be explained by stress concentrations. Strong MD is found around specific contacts, as well as within some particles, which can be explained by viscosity and friction. TEC data was processed for a granular system comprised of about 600 interparticle contacts, providing statistical information. Conclusions: TEC appears to be a strong coupling in the sense that its intensity is much higher than that of the MD. It is shown that IRT provides valuable information at the local scale, namely the signature of reversible (TEC) and irreversible (MD) mechanical phenomena, both at the interparticle contacts and inside the particles. [ABSTRACT FROM AUTHOR]

Summary: Knowledge about the distribution and local diversity patterns of arbuscular mycorrhizal (AM) fungi are limited for extreme environments such as the Arctic, where most studies have focused on spore morphology or root colonization. We here studied the joint effects of plant species identity and elevation on AM fungal distribution and diversity.We sampled roots of 19 plant species in 18 locations in Northeast Greenland, using next generation sequencing to identify AM fungi. We studied the joint effect of plant species, elevation and selected abiotic conditions on AM fungal presence, richness and composition.We identified 29 AM fungal virtual taxa (VT), of which six represent putatively new VT. Arbuscular mycorrhizal fungal presence increased with elevation, and as vegetation cover and the active soil layer decreased. Arbuscular mycorrhizal fungal composition was shaped jointly by elevation and plant species identity.We demonstrate that the Arctic harbours a relatively species‐rich and nonrandomly distributed diversity of AM fungi. Given the high diversity and general lack of knowledge exposed herein, we encourage further research into the diversity, drivers and functional role of AM fungi in the Arctic. Such insight is urgently needed for an area with some of the globally highest rates of climate change. [ABSTRACT FROM AUTHOR]

Weather and land use can significantly impact mosquito abundance and presence, and by consequence, mosquito-borne disease (MBD) dynamics. Knowledge of vector ecology and mosquito species response to these drivers will help us better predict risk from MBD. In this study, we evaluated and compared the independent and combined effects of weather and land use on mosquito species occurrence and abundance in Eastern Ontario, Canada. Data on occurrence and abundance (245,591 individuals) of 30 mosquito species were obtained from mosquito capture at 85 field sites in 2017 and 2018. Environmental variables were extracted from weather and land use datasets in a 1-km buffer around trapping sites. The relative importance of weather and land use on mosquito abundance (for common species) or occurrence (for all species) was evaluated using multivariate hierarchical statistical models. Models incorporating both weather and land use performed better than models that include weather only for approximately half of species (59% for occurrence model and 50% for abundance model). Mosquito occurrence was mainly associated with temperature whereas abundance was associated with precipitation and temperature combined. Land use was more often associated with abundance than occurrence. For most species, occurrence and abundance were positively associated with forest cover but for some there was a negative association. Occurrence and abundance of some species (47% for occurrence model and 88% for abundance model) were positively associated with wetlands, but negatively associated with urban (Culiseta melanura and Anopheles walkeri) and agriculture (An. quadrimaculatus, Cs. minnesotae and An. walkeri) environments. This study provides predictive relationships between weather, land use and mosquito occurrence and abundance for a wide range of species including those that are currently uncommon, yet known as arboviruses vectors. Elucidation of these relationships has the potential to contribute to better prediction of MBD risk, and thus more efficiently targeted prevention and control measures. [ABSTRACT FROM AUTHOR]

Current analyses of metacommunity data largely focus on global attributes across the entire metacommunity, such as mean alpha, beta, and gamma diversity, as well as the partitioning of compositional variation into single estimates of contributions of space and environmental effects and, more recently, possible contributions of species interactions. However, this view neglects the fact that different species and sites in the landscape can vary widely in how they contribute to these metacommunity‐wide attributes. We argue for a new conceptual framework with matched analytics with the goals of studying the complex and interactive relations between process and pattern in metacommunities that is focused on the variation among species and among sites which we call the 'internal structure' of the metacommunity. To demonstrate how the internal structure could be studied, we create synthetic data using a process‐based colonization–extinction metacommunity model. We then use joint species distribution models to estimate how the contributions of space, environment, and biotic interactions driving metacommunity assembly differ among species and sites. We find that this approach to the internal structure of metacommunities provides useful information about the distinct ways that different species and different sites contribute to metacommunity structure. Although it has limitations, our work points at a more general approach to understand how other possible complexities might affect internal structure and might thus be incorporated into a more cohesive metacommunity theory. [ABSTRACT FROM AUTHOR]

Summary: Leaves interact with a wealth of microorganisms. Among these, fungi are highly diverse and are known to contribute to plant health, leaf senescence and early decomposition. However, patterns and drivers of the seasonal dynamics of foliar fungal communities are poorly understood.We used a multifactorial experiment to investigate the influence of warming and tree genotype on the foliar fungal community on the pedunculate oak Quercus robur across one growing season.Fungal species richness increased, evenness tended to decrease, and community composition strongly shifted during the growing season. Yeasts increased in relative abundance as the season progressed, while putative fungal pathogens decreased. Warming decreased species richness, reduced evenness and changed community composition, especially at the end of the growing season. Warming also negatively affected putative fungal pathogens. We only detected a minor imprint of tree genotype and warming × genotype interactions on species richness and community composition.Overall, our findings demonstrate that warming plays a larger role than plant genotype in shaping the seasonal dynamics of the foliar fungal community on oak. These warming‐induced shifts in the foliar fungal community may have a pronounced impact on plant health, plant–fungal interactions and ecosystem functions. [ABSTRACT FROM AUTHOR]

There is an increasingly widespread use of biomarkers in network physiology to evaluate an organism's physiological state. A recent study showed that albumin variability increases before death in chronic hemodialysis patients. We hypothesized that a multivariate statistical approach would better allow us to capture signals of impending physiological collapse/death. We proposed a Moving Multivariate Distance (MMD), based on the Mahalanobis distance, to quantify the variability of the multivariate biomarker profile as a whole from one visit to the next. Biomarker profiles from a visit were used as the reference to calculate MMD at the subsequent visit. We selected 16 biomarkers (of which 11 are measured every 2 weeks) from blood samples of 763 chronic kidney disease patients hemodialyzed at the CHUS hospital in Quebec, who visited the hospital regularly (∼every 2 weeks) to perform routine blood tests. MMD tended to increase markedly preceding death, indicating an increasing intraindividual multivariate variability presaging a critical transition. In survival analysis, the hazard ratio between the 97.5th percentile and the 2.5th percentile of MMD reached as high as 21.1 [95% CI: 14.3, 31.2], showing that higher variability indicates substantially higher mortality risk. Multivariate approaches to early warning signs of critical transitions hold substantial clinical promise to identify early signs of critical transitions, such as risk of death in hemodialysis patients; future work should also explore whether the MMD approach works in other complex systems (i.e., ecosystems, economies), and should compare it to other multivariate approaches to quantify system variability. [ABSTRACT FROM AUTHOR]

There is a rich amount of information in co‐occurrence (presence–absence) data that could be used to understand community assembly. This proposition first envisioned by Forbes (1907) and then Diamond (1975) prompted the development of numerous modelling approaches (e.g. null model analysis, co‐occurrence networks and, more recently, joint species distribution models). Both theory and experimental evidence support the idea that ecological interactions may affect co‐occurrence, but it remains unclear to what extent the signal of interaction can be captured in observational data. It is now time to step back from the statistical developments and critically assess whether co‐occurrence data are really a proxy for ecological interactions. In this paper, we present a series of arguments based on probability, sampling, food web and coexistence theories supporting that significant spatial associations between species (or lack thereof) is a poor proxy for ecological interactions. We discuss appropriate interpretations of co‐occurrence, along with potential avenues to extract as much information as possible from such data. [ABSTRACT FROM AUTHOR]

Understanding how spring phenology influences early life can provide important insights into drivers of future development and survival. We combined unique, long-term data from a bighorn sheep population and satellite-derived phenology indices to quantify the relative importance of maternal and environmental influences on milk composition and lamb overwinter survival. Based on 216 milk samples from 34 females monitored over 6 years, we found that longer snow-free and vegetation growing seasons increased milk fatty acid, iron and lactose concentrations. Structural equation modelling revealed no causality between milk energy content, lamb weaning mass and lamb overwinter survival. Our results suggest that spring conditions can affect milk energy content, but we did not detect any effect on lamb overwinter survival either directly or indirectly through lamb weaning mass. The effect of green-up date on milk composition and energy content suggests that herbivores living in seasonal environments, such as the bighorn sheep, might rely on a strategy intermediate between 'capital' and 'income' breeding when energy demands are high. [ABSTRACT FROM AUTHOR]

Ecologists seek to understand the fitness consequences of variation in physiological markers, under the hypothesis that physiological state is linked to variability in individual condition and life history.Thus, ecologists are often interested in estimating correlations between entire suites of correlated traits, or biomarkers, but sample size limitations often do not allow us to do this properly when large numbers of traits or biomarkers are considered.Latent variables are a powerful tool to overcome this complexity. Recent statistical advances have enabled a new class of multivariate models—multivariate hierarchical modelling (MHM) with latent variables—which allow to statistically estimate unstructured covariances/correlations among traits with reduced constraints on the number of degrees of freedom to account in the model. It is thus possible to highlight correlated structures in potentially very large numbers of traits.Here, we apply MHM to evaluate the relative importance of individual differences and environmental effects on milk composition and identify the drivers of this variation. We ask whether variation in bighorn sheep milk affects offspring fitness.We evaluate whether mothers show repeatable individual differences in the concentrations of 11 markers of milk composition, and we investigate the relative importance of annual variability, maternal identity and morphological traits in structuring milk composition. We then use variance estimates to investigate how a subset of repeatable milk markers influence lamb summer survival.Repeatability of milk markers ranged from 0.05 to 0.64 after accounting for year‐to‐year variations. Milk composition was weakly but significantly associated with maternal mass in June and September, summer mass gain and winter mass loss. Variation explained by year‐to‐year fluctuations ranged from 0.07 to 0.91 suggesting a strong influence of environmental variability on milk composition. Milk composition did not affect lamb survival to weaning.Using joint models in ecological, physiological or behavioural contexts has the major advantage of decomposing a (co)variance/correlation matrix while being estimated with fewer parameters than in a "traditional" mixed‐effects model. The joint models presented here complement a growing list of tools to analyse correlations at different hierarchical levels separately and may thus represent a partial solution to the conundrum of physiological complexity. [ABSTRACT FROM AUTHOR]

Pathogens are embedded in a complex network of microparasites that can collectively or individually alter disease dynamics and outcomes. Endemic pathogens that infect an individual in the first years of life, for example, can either facilitate or compete with subsequent pathogens thereby exacerbating or ameliorating morbidity and mortality. Pathogen associations are ubiquitous but poorly understood, particularly in wild populations. We report here on 10 years of serological and molecular data in African lions, leveraging comprehensive demographic and behavioural data to test if endemic pathogens shape subsequent infection by epidemic pathogens. We combine network and community ecology approaches to assess broad network structure and characterise associations between pathogens across spatial and temporal scales. We found significant non‐random structure in the lion‐pathogen co‐occurrence network and identified both positive and negative associations between endemic and epidemic pathogens. Our results provide novel insights on the complex associations underlying pathogen co‐occurrence networks. [ABSTRACT FROM AUTHOR]

Summary: Arbuscular mycorrhizal (AM) fungi form diverse communities and are known to influence above‐ground community dynamics and biodiversity. However, the multiscale patterns and drivers of AM fungal composition and diversity are still poorly understood.We sequenced DNA markers from roots and root‐associated soil from Plantago lanceolata plants collected across multiple spatial scales to allow comparison of AM fungal communities among neighbouring plants, plant subpopulations, nearby plant populations, and regions. We also measured soil nutrients, temperature, humidity, and community composition of neighbouring plants and nonAM root‐associated fungi.AM fungal communities were already highly dissimilar among neighbouring plants (c. 30 cm apart), albeit with a high variation in the degree of similarity at this small spatial scale. AM fungal communities were increasingly, and more consistently, dissimilar at larger spatial scales. Spatial structure and environmental drivers explained a similar percentage of the variation, from 7% to 25%. A large fraction of the variation remained unexplained, which may be a result of unmeasured environmental variables, species interactions and stochastic processes.We conclude that AM fungal communities are highly variable among nearby plants. AM fungi may therefore play a major role in maintaining small‐scale variation in community dynamics and biodiversity. See also the Commentary on this article by Caruso, 220: 954–956. [ABSTRACT FROM AUTHOR]

Abstract: Within natural communities, different taxa display different dynamics in time. Why this is the case we do not fully know. This thwarts our ability to predict changes in community structure, which is important for both the conservation of rare species in natural communities and for the prediction of pest outbreaks in agriculture. Species sharing phylogeny, natural enemies and/or life‐history traits have been hypothesized to share similar temporal dynamics. We operationalized these concepts into testing whether feeding guild, voltinism, similarity in parasitoid community and/or phylogenetic relatedness explained similarities in temporal dynamics among herbivorous community members. Focusing on two similar datasets from different geographical regions (Finland and Japan), we used asymmetric eigenvector maps as temporal variables to characterize species‐ and community‐level dynamics of specialist insect herbivores on oak (Quercus). We then assessed whether feeding guild, voltinism, similarity in parasitoid community and/or phylogenetic relatedness explained similarities in temporal dynamics among taxa. Species‐specific temporal dynamics varied widely, ranging from directional decline or increase to more complex patterns. Phylogeny was a clear predictor of similarity in temporal dynamics at the Finnish site, whereas for the Japanese site, the data were uninformative regarding a phylogenetic imprint. Voltinism, feeding guild and parasitoid overlap explained little variation at either location. Despite the rapid temporal dynamics observed at the level of individual species, these changes did not translate into any consistent temporal changes at the community level in either Finland or Japan. Overall, our findings offer no direct support for the notion that species sharing natural enemies and/or life‐history traits would be characterized by similar temporal dynamics, but reveal a strong imprint of phylogenetic relatedness. As this phylogenetic signal cannot be attributed to guild, voltinism or parasitoids, it will likely derive from shared microhabitat, microclimate, anatomy, physiology or behaviour. This has important implications for predicting insect outbreaks and for informing insect conservation. We hope that future studies will assess the generality of our findings across plant‐feeding insect communities and beyond, and establish the more precise mechanism(s) underlying the phylogenetic imprint. [ABSTRACT FROM AUTHOR]

Community ecology aims to understand what factors determine the assembly and dynamics of species assemblages at different spatiotemporal scales. To facilitate the integration between conceptual and statistical approaches in community ecology, we propose Hierarchical Modelling of Species Communities ( HMSC) as a general, flexible framework for modern analysis of community data. While non-manipulative data allow for only correlative and not causal inference, this framework facilitates the formulation of data-driven hypotheses regarding the processes that structure communities. We model environmental filtering by variation and covariation in the responses of individual species to the characteristics of their environment, with potential contingencies on species traits and phylogenetic relationships. We capture biotic assembly rules by species-to-species association matrices, which may be estimated at multiple spatial or temporal scales. We operationalise the HMSC framework as a hierarchical Bayesian joint species distribution model, and implement it as R- and Matlab-packages which enable computationally efficient analyses of large data sets. Armed with this tool, community ecologists can make sense of many types of data, including spatially explicit data and time-series data. We illustrate the use of this framework through a series of diverse ecological examples. [ABSTRACT FROM AUTHOR]

A fundamental goal of ecology is to understand the determinants of species' distributions (i.e., the set of locations where a species is present). Competition among species (i.e., interactions among species that harms each of the species involved) is common in nature and it would be tremendously useful to quantify its effects on species' distributions. An approach to studying the large-scale effects of competition or other biotic interactions is to fit species' distributions models ( SDMs) and assess the effect of competitors on the distribution and abundance of the species of interest. It is often difficult to validate the accuracy of this approach with available data. Here, we simulate virtual species that experience competition. In these simulated datasets, we can unambiguously identify the effects that competition has on a species' distribution. We then fit SDMs to the simulated datasets and test whether we can use the outputs of the SDMs to infer the true effect of competition in each simulated dataset. In our simulations, the abiotic environment influenced the effects of competition. Thus, our SDMs often inferred that the abiotic environment was a strong predictor of species abundance, even when the species' distribution was strongly affected by competition. The severity of this problem depended on whether the competitor excluded the focal species from highly suitable sites or marginally suitable sites. Our results highlight how correlations between biotic interactions and the abiotic environment make it difficult to infer the effects of competition using SDMs. [ABSTRACT FROM AUTHOR]

Surveying ecological communities often means the tedious work of collecting detailed information on each species within each sampling unit (e.g. trap, transect, quadrat). In this paper, we first argue that presence-absence and abundance data are the two extremes of a spectrum of data formats. By counting individuals of each species within a sampling unit until either a predefined (user-defined) number of individuals is reached or all individuals of the species are counted, all intermediate cases can be generated. By independently correlating each intermediate case with the complete abundance data, we show that it is not necessary to count all individuals to recover the patterns of variation characterizing a community data table. When the same procedure is applied in combination with different distance coefficients such as the Hellinger, chord, χ2, percentage difference or modified Gower, or the distance between species profiles, an even lower number of individuals per species need to be counted within a sampling unit for the patterns of variation defining a community to be recovered. By applying the same counting procedure to data collected during a pilot study, we show that the maximum number of individuals that need to be counted within a sampling unit for a species can be estimated from a pilot study containing as little as 3% of randomly selected sampling units throughout the complete survey area. An example of how to apply this new counting method is presented, using data from a boreal forest Carabidae community sampled in northwestern Alberta, Canada. [ABSTRACT FROM AUTHOR]

Intraguild (IG) predation and interspecific competition may affect the settlement and success of species in their habitats. Using data on forest-dwelling hawks from Finland, we addressed the impact of an IG predator, the northern goshawk Accipiter gentilis (goshawk), on the breeding of an IG prey, the common buzzard Buteo buteo. We hypothesized that the subordinate common buzzard avoids breeding in the proximity of goshawks and that interspecific competitors, mainly Strix owls, may also disturb common buzzards by competing for nests and food. Our results show that common buzzards more frequently occupied territories with a low IG predation threat and with no interspecific competitors. We also observed that common buzzards avoided territories with high levels of grouse, the main food of goshawks, possibly due to a risk of IG predation since abundant grouse can attract goshawks. High levels of small rodents attracted interspecific competitors to common buzzard territories and created a situation where there was not only an abundance of food but also an abundance of competitors for the food. These results suggest interplay between top-down and bottom-up processes which influence the interactions between avian predator species. We conclude that the common buzzard needs to balance the risks of IG predation and interference competition with the availability of its own resources. The presence of other predators associated with high food levels may impede a subordinate predator taking full advantage of the available food. Based on our results, it appears that interspecific interactions with dominant predators have the potential to influence the distribution pattern of subordinate predators. [ABSTRACT FROM AUTHOR]

Understanding how habitat structures species assemblages in a community is one of the main goals of community ecology. To relate community patterns to particular factors defining habitat conditions, ecologists often use canonical ordinations such as canonical redundancy analysis (RDA). It is a common practice to use dissimilarity coefficients to perform canonical ordinations through distance-based RDA (db-RDA) or transformationbased RDA (tb-RDA). Dissimilarity coefficients are measures of resemblance where the information about species communities is condensed into a symmetric square matrix of dissimilarities among sites. In this study, we compared 16 of the most commonly used dissimilarity coefficients to evaluate if the species-abundance distribution (SAD) of a community can be used to select an appropriate coefficient. Of these, 11 are designed to be used primarily with abundance data, although they can also be used with presence-absence data, whereas five can only be applied to presence-absence data. Using simulations, we compared the explained variance of RDAs differing only by their coefficients to evaluate how the abundance patterns of communities influence coefficient choice. We found that coefficients are largely equivalent, independently of the community SAD. In light of these findings, we propose the consensus RDA method, a new canonical ordination procedure that performs a consensus of RDAs across several coefficients. This new method focuses on the common relations found by independent RDAs differing only by their dissimilarity coefficients; this ensures the absence of a coefficient-related bias when interpreting the canonical ordination result. Also, because in our simulations the presence-absence data were directly derived from the abundance data, we were able to evaluate if the information in presence-absence data was equivalent to that in abundance data. We found that although some information was lost by converting abundance data into presence-absence, both data formats may be complementary. When applying consensus RDA to abundance and presence-absence data independently, a more complete understanding and interpretation of the ecological patterns is obtained. An ecological example illustrating consensus RDA and the conclusions of our simulations is presented, using Carabidae data collected at the Ecosystem Management Emulating Natural Disturbances (EMEND) project in northwestern Alberta, Canada. [ABSTRACT FROM AUTHOR]

Landscape patterns influence a range of ecological processes at multiple spatial scales. Landscape pattern metrics are often used to study the patterns that result from the linear and nonlinear interactions between spatial aggregation and abundance of habitat., However, many class-level pattern metrics are highly correlated with habitat abundance, making their use as a measure of habitat fragmentation problematic., We argue that a class-level pattern metric should be (1) able to differentiate landscapes across a range of spatial aggregations, and (2) independent of habitat abundance, if it is to be used to distinguish between effects of habitat amount and fragmentation., Based on these criteria and using both simulated and actual landscapes, we evaluated 64 class-level pattern metrics. These metrics were reclassified into four groups based on their correlation with aggregation and abundance., Among all these metrics, nine were considered robust for fragmentation measurements, which cover most of the characteristics that define pattern, including core area, shape, proximity / isolation, contrast, and contagion / interspersion., Optimal metrics for individual studies will depend on both biological rationales and statistically robust metrics that are appropriate for achieving each study objectives. [ABSTRACT FROM AUTHOR]

High resolution CMOS image sensor demand is driven by consumer applications like mobile phone or digital still camera. To maintain the image quality, we have to save the signal to noise ratio (SNR) despite the number of photons reduction gathered by the pixel. In this paper, we present how back-side illumination technology could help to recover signal and how to optimize the process and device in order to reduce the noise. A quantum efficiency larger than 70% is targeted to justify efforts done on BSI process development. We also have to pay attention to pixel to pixel crosstalk coming from free carrier diffusion. To overcome this parasitic phenomenon, deep trench isolation (DTI) should be considered in order to significantly reduce crosstalk between two neighboring pixels. The second main noise contributor related to BSI process is the dark current signal. Dark current less than 1 aA per pixel at room temperature is mandatory to save the image quality at low light level. Therefore, all the Si-SiO2 interfaces at the pixel side walls have to be processed without any process damage to reduce as much as possible the surface defects. On top of that, side wall implantation and side wall dielectric fabrication have been optimized to reduce this noise source. The pixel layout has to be fully optimized also to collect and store charges properly. With respect to the 3D pixel shape, a new fully depleted pinned photodiode with vertical charge storage and no lag has been developed. (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

Ground beetle (Carabidae) assemblages are speciose and frequently employed as indicators of ecosystem function. It is thus important to understand the factors that affect their spatial distributions so as to better interpret how ecosystem variation influences the structure of their assemblages. We evaluated how anthropogenic disturbances, habitat heterogeneity, and spatial autocorrelation (unmeasured spatially structured habitat variables and/or dispersal limitation) influence the distribution of carabids on a mature boreal forest landscape. We worked with a large sample of carabids from 194 sites from a near-regular grid covering 70 km2. Data about forest floor cover, vegetation structure, soil drainage, and topography were associated with each site. We modelled the structure of carabid assemblages using these variables together with Moran's eigenvector maps (MEM) as spatial constraints. Overall, our model explained about half of the variation in ground beetle assemblages. Forest floor cover, soil drainage, and vegetation structure were the principal factors useful for explaining carabid assemblages. The spatial patterns described by the MEMs for the ground beetle assemblages seem to result from spatial autocorrelation in soil drainage, floor cover, topography, and vegetation structure; however, this spatial autocorrelation independently and uniquely explained only 1.4% of the variation in assemblages. This was much less important than the explanatory power of the environmental variables considered; e.g. ground cover descriptors and vegetation structure by themselves accounted, respectively, for 12.1 and 4.5% of the variation in the carabid data. The spatial distribution of ground beetles in undisturbed forest was only mildly affected by surrounding anthropogenic disturbances, but clearly small patches were invaded by species characteristic of open habitat. We conclude that to help conserve ground beetle diversity at the landscape scale in boreal forests, mature forest patches should be large and connected to other patches and the surrounding forest. [ABSTRACT FROM AUTHOR]

Larval dispersal is a crucial factor for fish recruitment. For fishes with relatively small-bodied larvae, drift has the potential to play a more important role than active habitat selection in determining larval dispersal; therefore, we expect small-bodied fish larvae to be poorly associated with habitat characteristics. To test this hypothesis, we used as model yellow perch (Perca flavescens), whose larvae are among the smallest among freshwater temperate fishes. Thus, we analysed the habitat association of yellow perch larvae at multiple spatial scales in a large shallow fluvial lake by explicitly modelling directional (e.g. due to water currents) and non-directional (e.g. due to aggregation) spatial patterns. This allowed us to indirectly assess the relative roles of drift (directional process) and potential habitat choice on larval dispersal. Our results give weak support to the drift hypothesis, whereas yellow perch show a strong habitat association at unexpectedly small sizes, when compared to other systems. We found consistent non-directional patterns in larvae distributions at both broad and medium spatial scales but only few significant directional components. The environmental variables alone (e.g. vegetation) generally explained a significant and biologically relevant fraction of the variation in fish larvae distribution data. These results suggest that (i) drift plays a minor role in this shallow system, (ii) larvae display spatial patterns that only partially covary with environmental variables, and (iii) larvae are associated to specific habitats. By suggesting that habitat association potentially includes an active choice component for yellow perch larvae, our results shed new light on the ecology of freshwater fish larvae and should help in building more realistic recruitment models. [ABSTRACT FROM AUTHOR]

Species spatial distributions are the result of population demography, behavioral traits, and species interactions in spatially heterogeneous environmental conditions. Hence the composition of species assemblages is an integrative response variable, and its variability can be explained by the complex interplay among several structuring factors. The thorough analysis of spatial variation in species assemblages may help infer processes shaping ecological communities. We suggest that ecological studies would benefit from the combined use of the classical statistical models of community composition data, such as constrained or unconstrained multivariate analyses of site-by-species abundance tables, with rapidly emerging and diversifying methods of spatial pattern analysis. Doing so allows one to deal with spatially explicit ecological models of beta diversity in a biogeographic context through the multiscale analysis of spatial patterns in original species data tables, including spatial characterization of fitted or residual variation from environmental models. We summarize here the recent progress for specifying spatial features through spatial weighting matrices and spatial eigenfunctions in order to define spatially constrained or scale-explicit multivariate analyses. Through a worked example on tropical tree communities, we also show the potential of the overall approach to identify significant residual spatial patterns that could arise from the omission of important unmeasured explanatory variables or processes. [ABSTRACT FROM AUTHOR]

Habitat heterogeneity and dispersal limitation are widely considered to be the two major mechanisms in determining tree species distributions. However, few studies have quantified the relative importance of these two mechanisms at different life stages of trees. Moreover, rigorous quantification of the effects of dominant tree species in determining species distributions has seldom been explored. In the present study, we tested the hypothesis that the distribution of tree species is regulated by different mechanisms at different life history stages. In particular, we hypothesised that dispersal limitation regulates the distribution of trees at early life stages and that environmental factors control the distribution of trees as they grow, because of niche differentiation resulting from environmental filtering. To test this, trees in 400-m2 quadrats in a 20-ha plot in Xishuangbanna, southwest China were grouped into four classes on the basis of the diameter at breast height (DBH) that roughly represent different stages in the life history of trees. A neighbourhood index was computed to represent a neutral spatial autocorrelation effect. We used both biotic (dominant species) and abiotic (topography and soil) predictor variables to model the distribution of each target species while controlling for spatial autocorrelation within each of the DBH classes. To determine which factors played the largest role in regulating target species distribution, the simulated annealing method was used in model selection based on Akaike information criterion (AIC) values. The results showed that the relative importance of neutral and niche processes in regulating species distribution varied across life stages. The neutral neighbourhood index played the most important role in determining the distributions of small trees (1 cm ≤ DBH ≤ 10 cm), and dominant species, as biotic environmental predictor variables, were the next most important regulators for trees of this size. Environmental predictor variables played the most important role in determining the distributions of large trees (10 cm ≤ DBH). This finding builds on previous research into the relative importance of neutral and niche processes in determining species distributions regardless of life stages or DBH classes. [ABSTRACT FROM AUTHOR]

Aims We compare performance of ecosystem classification maps and provincial forest inventory data derived from air photography in reflecting ground beetle (Coleoptera: Carabidae) biodiversity patterns that are related to the forest canopy mosaic. Our biodiversity surrogacy model based on remotely sensed tree canopy cover is validated against field-collected ground data. Methods We used a systematic sampling grid of 198 sites, covering 84 km2 of boreal mixedwood forest in northwestern Alberta, Canada. For every site, we determined tree basal area, characterized the ground beetle assemblage and obtained corresponding provincial forest inventory and ecosystem classification information. We used variation partitioning, ordination and misclassification matrices to compare beetle biodiversity patterns explained by alternative databases and to determine model biases originating from air photo-interpretation. Important Findings Ecosystem classification data performed better than canopy cover derived from forest inventory maps in describing ground beetle biodiversity patterns. The biodiversity surrogacy models based on provincial forest inventory maps and field survey generally detected similar patterns but inaccuracies in air photo-interpretation of relative canopy cover led to differences between the two models. Compared to field survey data, air photo-interpretation tended to confuse two Picea species and two Populus species present and homogenize stand mixtures. This generated divergence in models of ecological association used to predict the relationship between ground beetle assemblages and tree canopy cover. Combination of relative canopy cover from provincial inventory with other geo-referenced land variables to produce the ecosystem classification maps improved biodiversity predictive power. The association observed between uncommon surrogates and uncommon ground beetle species emphasizes the benefits of detecting these surrogates as a part of landscape management. In order to complement conservation efforts established in protected areas, accurate, high resolution, wide ranging and spatially explicit knowledge of landscapes under management is primordial in order to apply effective biodiversity conservation strategies at the stand level as required in the extensively harvested portion of the boreal forest. In development of these strategies, an in-depth understanding of vegetation is key. [ABSTRACT FROM PUBLISHER]

The mountain pine beetle ( Dendroctonus ponderosae, MPB) has killed millions of lodgepole pine ( Pinus contorta) trees in Western Canada, and recent range expansion has resulted in attack of jack pine ( Pinus banksiana) in Alberta. Establishment of MPB in the Boreal forest will require use of jack pine under a suite of environmental conditions different from those it typically encounters in its native range. Lodgepole and jack pine seedlings were grown under controlled environment conditions and subjected to either water deficit or well watered conditions and inoculated with Grosmannia clavigera, a MPB fungal associate. Soil water content, photosynthesis, stomatal conductance, and emission of volatile organic compounds (VOCs) were monitored over the duration of the six-week study. Monoterpene content of bark and needle tissue was measured at the end of the experiment. β-Phellandrene, the major monoterpene in lodgepole pine, was almost completely lacking in the volatile emission profile of jack pine. The major compound in jack pine was α-pinene. The emission of both compounds was positively correlated with stomatal conductance. 3-Carene was emitted at a high concentration from jack pine seedlings, which is in contrast to monoterpene profiles of jack pine from more southern and eastern parts of its range. Fungal inoculation caused a significant increase in total monoterpene emission in water deficit lodgepole pine seedlings right after its application. By 4 weeks into the experiment, water deficit seedlings of both species released significantly lower levels of total monoterpenes than well watered seedlings. Needle tissue contained lower total monoterpene content than bark. Generally, monoterpene tissue content increased over time independent from any treatment. The results suggest that monoterpenes that play a role in pine-MPB interactions differ between lodgepole and jack pine, and also that they are affected by water availability. [ABSTRACT FROM AUTHOR]

During the last 20 years, ecologists discovered the importance of including spatial relationships in models of species distributions. Among the latest developments in modelling how species are spatially structured are eigenfunction-based spatial filtering methods such as Moran's eigenvector maps (MEM) and principal coordinates of neighbour matrices (PCNM). Although these methods are very powerful and flexible, they are only suited to study distributions resulting from non-directional spatial processes. The asymmetric eigenvector map (AEM) framework, a new eigenfunction-based spatial filtering method, fills this theoretical gap. AEM was specifically designed to model spatial structures hypothesized to be produced by directional spatial processes. Water currents, prevailing wind on mountainsides, river networks, and glaciations at historical time scales are some of the situations where AEM can be used. This paper presents three applications of the method illustrating different combinations of: sampling schemes (regular and irregular), data types (univariate and multivariate), and spatial scales (metres, kilometres, and hundreds of kilometres). The applications include the distribution of a crustacean ( Atya) in a river, bacterial production in a lake, and the distribution of the copepodite stages of a crustacean on the Atlantic oceanic shelf. In each application, a comparison is made between AEM, MEM, and PCNM. No environmental components were included in the comparisons. AEM was a strong predictor in all cases, explaining 59.8% for Atya distribution, 51.4% of the bacterial production variation, and 38.4% for the copepodite distributions. AEM outperformed MEM and PCNM in these applications, offering a powerful and more appropriate tool for spatial modelling of species distributions under directional forcing and leading to a better understanding of the processes at work in these systems. [ABSTRACT FROM AUTHOR]

This paper proposes a new way of using forward selection of explanatory variables in regression or canonical redundancy analysis. The classical forward selection method presents two problems: a highly inflated Type I error and an overestimation of the amount of explained variance. Correcting these problems will greatly improve the performance of this very useful method in ecological modeling. To prevent the first problem, we propose a two-step procedure. First, a global test using all explanatory variables is carried out. If, and only if, the global test is significant, one can proceed with forward selection. To prevent overestimation of the explained variance, the forward selection has to be carried out with two stopping criteria: (1) the usual alpha significance level and (2) the adjusted coefficient of multiple determination (Ra²) calculated using all explanatory variables. When forward selection identifies a variable that brings one or the other criterion over the fixed threshold, that variable is rejected, and the procedure is stopped. This improved method is validated by simulations involving univariate and multivariate response data. An ecological example is presented using data from the Bryce Canyon National Park, Utah, USA. [ABSTRACT FROM AUTHOR]

New European Directive 2006/7/EC concerning the management of bathing water quality introduces the concept of 'active management of bathing water sanitary quality' which could lead to a temporary bathing prohibition in case of short term pollution. For the last three bathing seasons, Veolia has carried out in experimental mode this 'active management' concept at more than one hundred bathing sites with various characteristics. Results confirm the high level of microbiological pollution observed in sewer overflows during rainy periods, which is the main cause of bathing water quality deterioration. An on-line treatment solution has been successfully tested. This solution may be used in dense urban areas. [ABSTRACT FROM AUTHOR]

Human-mediated geomorphic degradation of streams and rivers is a serious environmental problem with negative effects on aquatic biota and social infrastructure. Billions of dollars are spent for stream restoration in the USA alone, but it is still unknown how algal diversity is affected by these efforts. In this investigation, we studied a geomorphically stable and heterogeneous reach and two degraded and homogeneous reaches of Batavia Kill, a highland stream in New York, USA. Spatial surveys of algae and geomorphic conditions were conducted in all three reaches for 2 years. After the first year of study, one of the two unstable reaches was subjected to a large-scale streambed restoration. Species–area relationships (SAR) were examined for the first time in local algal communities of stream periphyton. Alpha- and gamma-diversity, which represent the species richness at a sample and reach level, respectively, and cell density, were also explored. In all reaches, SAR were fitted with semi-log models, which revealed that the rate of increase of species richness with area, i.e. algal beta-diversity, was significantly higher in the geomorphically stable reach than in the two degraded reaches. Gamma-diversity followed the same trend, whereas alpha-diversity and cell density were significantly higher in the unstable reaches. Restoration significantly increased the heterogeneity of conditions, including depth and particle size. From all studied community descriptors, restoration had a benign influence on algal beta- and gamma-diversity; however, beta-diversity remained the highest in the stable reference reach and this difference was significant. Our results provide guidelines for the use of periphytic algae in future bioassessments of stream bank restoration. Community properties such as species richness and organismal density, which are common metrics of ecosystem health, may be inappropriate in stream restoration surveys; instead diversity measures, often overlooked in applied ecology, e.g. beta-diversity, should be given full consideration. [ABSTRACT FROM AUTHOR]

The optimization of the small and large signal performances of a radio frequency (RF)-LDMOS is presented via the achievement of a novel LDMOS architecture. Specific process steps are introduced into a 0.25-µm BiCMOS technology and precisely described to realize a fully salicided gate RF-LDMOS architecture. Significant improvement is obtained on the small-signal—fT and Fmax—and power performances while maintaining good dc characteristics. [ABSTRACT FROM AUTHOR]

Two cases of massive pulmonary embolism, confirmed by angiographic or necropsy findings, were remarkable by the absence of arterial hypoxaemia. The various mechanisms responsible for arterial hypoxaemia in pulmonary embolism are discussed. It is suggested that in patients with massive pulmonary embolism a markedly decreased cardiac output might account for the absence of arterial hypoxaemia. In the light of these two cases the finding of a normal PaO2 does not rule out the diagnosis of pulmonary embolism. [ABSTRACT FROM AUTHOR]