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The ability of climatic niche models to predict species extinction risks can be hampered if niches are incompletely quantified. This can occur when niches are estimated considering only currently available climatic conditions, disregarding the fact that climate change can open up portions of the fundamental niche that are currently inaccessible to species. Using a new metric, we estimate the prevalence of potential situations of fundamental niche truncation by measuring whether current ecological niche limits are contiguous to the boundaries of currently available climatic conditions for 24,944 species at the global scale in both terrestrial and marine realms and including animals and plants. We show that 12,172 (~49%) species are showing niche contiguity, particularly those inhabiting tropical ecosystems and the marine realm. Using niche expansion scenarios, we find that 86% of species showing niche contiguity could have a fundamental niche potentially expanding beyond current climatic limits, resulting in lower-yet still alarming-rates of predicted biodiversity loss, particularly within the tropics. Caution is therefore advised when forecasting future distributions of species presenting niche contiguity, particularly towards climatic limits that are predicted to expand in the future., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Mounting evidence points to the need for high-resolution climatic data in biodiversity analyses under global change. As we move to finer resolution, other factors than climate, including other abiotic variables and biotic interactions play, however, an increasing role, raising the question of our ability to predict community composition at fine scales. Focusing on two lineages of land plants, bryophytes and tracheophytes, we determine the relative contribution of climatic, non-climatic environmental drivers, spatial effects, community architecture and composition of one lineage to predict community composition of the other lineage, and how our ability to predict community composition varies along an elevation gradient. The relationship between community composition of one lineage and 68 environmental variables at 2-25 m spatial resolution, architecture and composition of the other lineage, and spatial factors, was investigated by hierarchical and variance partitioning across 413 2x2m plots in the Swiss Alps. Climatic data, although significant, contributed less to the model than any other variable considered. Community composition of one lineage, reflecting both direct interactions and unmeasured (hidden) abiotic factors, was the best predictor of community composition of the other lineage. Total explained variance substantially varied with elevation, underlining the fact that the strength of the species composition-environment relationship varies depending on environmental conditions. Total variance explained increased towards high elevation up to 50 %, with an increasing importance of spatial effects and vegetation architecture, pointing to increasing positive interactions and aggregated species distribution patterns in alpine environments. In tracheophytes, an increase of the contribution of non-climatic environmental factors was also observed at high elevation, in line with the hypothesis of a stronger environmental control under harsher conditions. Further improvements of our ability to predict changes in plant community composition may involve the implementation of historical variables and higher-resolution climatic data to better describe the microhabitat conditions actually experienced by organisms., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

We present forecasts of land-use/land-cover (LULC) change for Switzerland for three time-steps in the 21 st century under the representative concentration pathways 4.5 and 8.5, and at 100-m spatial and 14-class thematic resolution. We modelled the spatial suitability for each LULC class with a neural network (NN) using > 200 predictors and accounting for climate and policy changes. We improved model performance by using a data augmentation algorithm that synthetically increased the number of cells of underrepresented classes, resulting in an overall quantity disagreement of 0.053 and allocation disagreement of 0.15, which indicate good prediction accuracy. These class-specific spatial suitability maps outputted by the NN were then merged in a single LULC map per time-step using the CLUE-S algorithm, accounting for LULC demand for the future and a set of LULC transition rules. As the first LULC forecast for Switzerland at a thematic resolution comparable to available LULC maps for the past, this product lends itself to applications in land-use planning, resource management, ecological and hydraulic modelling, habitat restoration and conservation., (© 2024. The Author(s).)

Genetic monitoring of populations currently attracts interest in the context of the Convention on Biological Diversity but needs long-term planning and investments. However, genetic diversity has been largely neglected in biodiversity monitoring, and when addressed, it is treated separately, detached from other conservation issues, such as habitat alteration due to climate change. We report an accounting of efforts to monitor population genetic diversity in Europe (genetic monitoring effort, GME), the evaluation of which can help guide future capacity building and collaboration towards areas most in need of expanded monitoring. Overlaying GME with areas where the ranges of selected species of conservation interest approach current and future climate niche limits helps identify whether GME coincides with anticipated climate change effects on biodiversity. Our analysis suggests that country area, financial resources and conservation policy influence GME, high values of which only partially match species' joint patterns of limits to suitable climatic conditions. Populations at trailing climatic niche margins probably hold genetic diversity that is important for adaptation to changing climate. Our results illuminate the need in Europe for expanded investment in genetic monitoring across climate gradients occupied by focal species, a need arguably greatest in southeastern European countries. This need could be met in part by expanding the European Union's Birds and Habitats Directives to fully address the conservation and monitoring of genetic diversity., (© 2024. The Author(s).)

Bacteria colonize the body of macroorganisms to form associations ranging from parasitic to mutualistic. Endosymbiont and gut symbiont communities are distinct microbiomes whose compositions are influenced by host ecology and evolution. Although the composition of horizontally acquired symbiont communities can correlate to host species identity (i.e. harbor host specificity) and host phylogeny (i.e. harbor phylosymbiosis), we hypothesize that the microbiota structure of vertically inherited symbionts (e.g. endosymbionts like Wolbachia ) is more strongly associated with the host species identity and phylogeny than horizontally acquired symbionts (e.g. most gut symbionts). Here, using 16S metabarcoding on 336 guts from 24 orthopteran species (grasshoppers and crickets) in the Alps, we observed that microbiota correlated to host species identity, i.e. hosts from the same species had more similar microbiota than hosts from different species. This effect was ~5 times stronger for endosymbionts than for putative gut symbionts. Although elevation correlated with microbiome composition, we did not detect phylosymbiosis for endosymbionts and putative gut symbionts: closely related host species did not harbor more similar microbiota than distantly related species. Our findings indicate that gut microbiota of studied orthopteran species is more correlated to host identity and habitat than to the host phylogeny. The higher host specificity in endosymbionts corroborates the idea that-everything else being equal-vertically transmitted microbes harbor stronger host specificity signal, but the absence of phylosymbiosis suggests that host specificity changes quickly on evolutionary time scales., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Society for Microbial Ecology.)

Standard and easily accessible cross-thematic spatial databases are key resources in ecological research. In Switzerland, as in many other countries, available data are scattered across computer servers of research institutions and are rarely provided in standard formats (e.g., different extents or projections systems, inconsistent naming conventions). Consequently, their joint use can require heavy data management and geomatic operations. Here, we introduce SWECO25, a Swiss-wide raster database at 25-meter resolution gathering 5,265 layers. The 10 environmental categories included in SWECO25 are: geologic, topographic, bioclimatic, hydrologic, edaphic, land use and cover, population, transportation, vegetation, and remote sensing. SWECO25 layers were standardized to a common grid sharing the same resolution, extent, and geographic coordinate system. SWECO25 includes the standardized source data and newly calculated layers, such as those obtained by computing focal or distance statistics. SWECO25 layers were validated by a data integrity check, and we verified that the standardization procedure had a negligible effect on the output values. SWECO25 is available on Zenodo and is intended to be updated and extended regularly., (© 2024. The Author(s).)

Different host species associate with distinct gut microbes in mammals, a pattern sometimes referred to as phylosymbiosis. However, the processes shaping this host specificity are not well understood. One model proposes that barriers to microbial transmission promote specificity by limiting microbial dispersal between hosts. This model predicts that specificity levels measured across microbes is correlated to transmission mode (vertical vs. horizontal) and individual dispersal traits. Here, we leverage two large publicly available gut microbiota data sets (1490 samples from 195 host species) to test this prediction. We found that host specificity varies widely across bacteria (i.e., there are generalist and specialist bacteria) and depends on transmission mode and dispersal ability. Horizontally-like transmitted bacteria equipped with traits that facilitate switches between host (e.g., tolerance to oxygen) were found to be less specific (more generalist) than microbes without those traits, for example, vertically-like inherited bacteria that are intolerant to oxygen. Altogether, our findings are compatible with a model in which limited microbial dispersal abilities foster host specificity., (© 2023 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.)

The Anthropocene is characterized by a rapid pace of environmental change and is causing a multitude of biotic responses, including those that affect the spatial distribution of species. Lagged responses are frequent and species distributions and assemblages are consequently pushed into a disequilibrium state. How the characteristics of environmental change-for example, gradual 'press' disturbances such as rising temperatures due to climate change versus infrequent 'pulse' disturbances such as extreme events-affect the magnitude of responses and the relaxation times of biota has been insufficiently explored. It is also not well understood how widely used approaches to assess or project the responses of species to changing environmental conditions can deal with time lags. It, therefore, remains unclear to what extent time lags in species distributions are accounted for in biodiversity assessments, scenarios and models; this has ramifications for policymaking and conservation science alike. This perspective piece reflects on lagged species responses to environmental change and discusses the potential consequences for species distribution models (SDMs), the tools of choice in biodiversity modelling. We suggest ways to better account for time lags in calibrating these models and to reduce their leverage effects in projections for improved biodiversity science and policy., Competing Interests: The authors declare to have no conflicts of interest., (© 2023 The Authors. Journal of Biogeography published by John Wiley & Sons Ltd.)

AbstractSpecies' distributions can take many different forms. For example, fat-tailed or skewed distributions are very common in nature, as these can naturally emerge as a result of individual variability and asymmetric environmental tolerances, respectively. Studying the basic shape of distributions can teach us a lot about the ways climatic processes and historical contingencies shape ecological communities. Yet we still lack a general understanding of how their shapes and properties compare to each other along gradients. Here, we use Bayesian nonlinear models to quantify range shape properties in empirical plant distributions. With this approach, we are able to distil the shape of plant distributions and compare them along gradients and across species. Studying the relationship between distribution properties, we revealed the existence of broad macroecological patterns along environmental gradients-such as those expected from Rapoport's rule and the abiotic stress limitation hypothesis. We also find that some aspects of the shape of observed ranges-such as kurtosis and skewness of the distributions-could be intrinsic properties of species or the result of their historical contexts. Overall, our modeling approach and results untangle the general shape of plant distributions and provide a mapping of how this changes along environmental gradients.

Predicting the presence or absence (occurrence-state) of species in a certain area is highly important for conservation. Occurrence-state can be assessed by network models that take suitable habitat patches as nodes, connected by potential dispersal of species. To determine connections, a connectivity threshold is set at the species' maximum dispersal distance. However, this requires field observations prone to underestimation, so for most animal species there are no trustable maximum dispersal distance estimations. This limits the development of accurate network models to predict species occurrence-state. In this study, we performed a sensitivity analysis of the performance of network models to different settings of maximum dispersal distance. Our approach, applied on six amphibian species in Switzerland, used habitat suitability modelling to define habitat patches, which were linked within a dispersal distance threshold to form habitat networks. We used network topological measures, patch suitability, and patch size to explain species occurrence-state in habitat patches through boosted regression trees. These modelling steps were repeated on each species for different maximum dispersal distances, including a species-specific value from literature. We evaluated mainly the predictive performance and predictor importance among the network models. We found that predictive performance had a positive relation with the distance threshold, and that almost none of the species-specific values from literature yielded the best performance across tested thresholds. With increasing dispersal distance, the importance of the habitat-quality-related variable decreased, whereas that of the topology-related predictors increased. We conclude that the sensitivity of these models to the dispersal distance parameter stems from the very different topologies formed with different movement assumptions. Most reported maximum dispersal distances are underestimated, presumably due to leptokurtic dispersal distribution. Our results imply that caution should be taken when selecting a dispersal distance threshold, considering higher values than those derived from field reports, to account for long-distance dispersers., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ortiz-Rodríguez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: Bronchiolitis is the leading cause of hospitalization in children under one year of age, with annual epidemics. Since the onset of the SARS-CoV-2 coronavirus disease pandemic (COVID-19), there has been a change in the transmission of other respiratory viruses. Our aim in this paper was to describe how COVID-19 had affected the distribution of acute bronchiolitis in our country., Methods: We conducted a retrospective descriptive study of the cases of bronchiolitis treated in a sample of Spanish hospitals belonging to four autonomous communities. A chi-square test and Student's t- test were used to compare epidemiological and demographic variables between patients attending the hospital with bronchiolitis during January 2021-June 2021 with patients attending the hospital in the previous three years (2018-2020)., Results: We analyzed 6,124 cases of bronchiolitis (58.8% males and 41.2% females). The mean age was 0.5 years (SD: 0.4). In 2020, we observed a decrease of bronchiolitis cases compared to 2019 of 67%. During 2020 and 2021, the epidemic season started in January-February and peaked in June. During the first half of 2021, the highest percentage of admissions for bronchiolitis associated with RSV infection was observed in hospitals in central Spain corresponding to the Autonomous Community of Madrid (78.5% of admissions)., Conclusions: The COVID-19 pandemic significantly modifies the seasonality of bronchiolitis. In our country, the flow and distribution of the disease are not uniform. It starts in the center of Spain and ends on the coast.

The environmental niche concept describes the distribution of a taxon in the environment and can be used to understand community dynamics, biological invasions, and the impact of environmental changes. The uses and applications are still restricted in microbial ecology, largely due to the complexity of microbial systems and associated methodological limitations. The development of shotgun metagenomics and metatranscriptomics opens new ways to investigate the microbial niche by focusing on the metabolic niche within the environmental space. Here, we propose the metabolic niche framework, which, by defining the fundamental and realised metabolic niche of microorganisms, has the potential to not only provide novel insights into habitat preferences and the metabolism associated, but also to inform on metabolic plasticity, niche shifts, and microbial invasions., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Epiphytes offer an appealing framework to disentangle the contributions of chance, biotic and abiotic drivers of species distributions. In the context of the stress-gradient theory, we test the hypotheses that (i) deterministic (i.e., non-random) factors play an increasing role in communities from young to old trees, (ii) negative biotic interactions increase on older trees and towards the tree base, and (iii) positive interactions show the reverse pattern. Bryophyte species distributions and abiotic conditions were recorded on a 1.1 ha tropical rainforest canopy crane site. We analysed co-occurrence patterns in a niche modelling framework to disentangle the roles of chance, abiotic factors and putative biotic interactions among species pairs. 76% of species pairs resulted from chance. Abiotic factors explained 78% of non-randomly associated species pairs, and co-occurrences prevailed over non-coincidences in the remaining species pairs. Positive and negative interactions mostly involved species pairs from the same versus different communities (mosses versus liverworts) and life forms, respectively. There was an increase in randomly associated pairs from large to small trees. No increase in negative interactions from young to old trees or from the canopy to the base was observed. Our results suggest that epiphytic bryophyte community composition is primarily driven by environmental filtering, whose importance increases with niche complexity and diversity. Biotic interactions play a secondary role, with a very marginal contribution of competitive exclusion. Biotic interactions vary among communities (mosses versus liverworts) and life forms, facilitation prevailing among species from the same community and life form, and competition among species from different communities and life forms., (© 2023 Wiley-VCH GmbH. Published by John Wiley & Sons Ltd.)

Monitoring of terrestrial and aquatic species assemblages at large spatial scales based on environmental DNA (eDNA) has the potential to enable evidence-based environmental policymaking. The spatial coverage of eDNA-based studies varies substantially, and the ability of eDNA metabarcoding to capture regional biodiversity remains to be assessed; thus, questions about best practices in the sampling design of entire landscapes remain open. We tested the extent to which eDNA sampling can capture the diversity of a region with highly heterogeneous habitat patches across a wide elevation gradient for five days through multiple hydrological catchments of the Swiss Alps. Using peristaltic pumps, we filtered 60 L of water at five sites per catchment for a total volume of 1800 L. Using an eDNA metabarcoding approach focusing on vertebrates and plants, we detected 86 vertebrate taxa spanning 41 families and 263 plant taxa spanning 79 families across ten catchments. For mammals, fishes, amphibians and plants, the detected taxa covered some of the most common species in the region according to long-term records while including a few more rare taxa. We found marked turnover among samples from distinct elevational classes indicating that the biological signal in alpine rivers remains relatively localised and is not aggregated downstream. Accordingly, species compositions differed between catchments and correlated with catchment-level forest and grassland cover. Biomonitoring schemes based on capturing eDNA across rivers within biologically integrated catchments may pave the way toward a spatially comprehensive estimation of biodiversity., (© 2023. The Author(s).)

The processes governing soil bacteria biogeography are still not fully understood. It remains unknown how the importance of environmental filtering and dispersal differs between bacterial taxonomic and functional biogeography, and whether their importance is scale-dependent. We sampled soils across the Tibet plateau, with distances among plots ranging from 20 m to 1550 km. Taxonomic composition of bacterial community was characterized by 16S amplicon sequencing and functional community composition by qPCR targeting 9 functional groups involved in N dynamics. Factors representing climate, soil and plant community were measured to assess different facets of environmental dissimilarity. Both bacterial taxonomic and functional dissimilarities were more related to abiotic dissimilarity than biotic (vegetation) dissimilarity or distance. Taxonomic dissimilarity was mostly explained by differences in soil pH and mean annual temperature (MAT), while functional dissimilarity was linked to differences in soil N and P availabilities and N:P ratio. Soil pH and MAT remained the main determinants of taxonomic dissimilarity across spatial scales. In contrast, the explanatory variables of N-related functional dissimilarity varied across the scales, with soil moisture and organic matter having the highest role across short distances (<~330 km), and available P, N:P ratio and distance being important over long distances (>~660 km). Our results demonstrate how biodiversity dimension (taxonomic versus functional aspects) and spatial scale influence the factors driving soil bacterial biogeography., (© 2023 John Wiley & Sons Ltd.)

Since the late 1990s, Nature's Contributions to People (NCPs; i.e. ecosystem services) were used as a putative leverage for fostering nature preservation. NCPs have largely been defined and mapped at the landscape level using land use and cover classifications. However, NCP mapping attempts based directly on individual species are still uncommon. Given that species shape ecosystems and ultimately deliver NCPs, mapping NCPs based on species distribution data should deliver highly meaningful results. This requires first establishing a census of the species-to-NCP relationships. However, datasets quantifying these relationships across several species and NCPs are rare. Here, we fill this gap by compiling literature and expert knowledge to establish the relationships of 1816 tracheophyte and 250 vertebrate species with 17 NCPs in the Swiss Alps. We illustrated the 31,098 identified species-NCP relationships for the two lineages and discuss why such a table is a key initial step in building spatial predictions of NCPs directly from species data, e.g. to ultimately complement spatial conservation planning., (© 2023. The Author(s).)

Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect the outcomes of ecological models used to infer the geographic distribution of species and diversity. There is a vast heterogeneity of methods and approaches to assess and measure spatial bias; this paper aims at addressing the spatial component of data-driven biases in species distribution modelling, and to propose potential solutions to explicitly test and account for them. Our major goal is not to propose methods to remove spatial bias from the modelling procedure, which would be impossible without proper knowledge of all the processes generating it, but rather to propose alternatives to explore and handle it. In particular, we propose and describe three main strategies that may provide a fair account of spatial bias, namely: (i) how to represent spatial bias; (ii) how to simulate null models based on virtual species for testing biogeographical and species distribution hypotheses; and (iii) how to make use of spatial bias - in particular related to sampling effort - as a leverage instead of a hindrance in species distribution modelling. We link these strategies with good practice in accounting for spatial bias in species distribution modelling., (© 2023. The Author(s).)

Understanding the drivers of infection risk helps us to detect the most at-risk species in a community and identify species whose intrinsic characteristics could act as potential reservoirs of pathogens. This knowledge is crucial if we are to predict the emergence and evolution of infectious diseases. To date, most studies have only focused on infections caused by a single parasite, leaving out co-infections. Yet, co-infections are of paramount importance in understanding the ecology and evolution of host-parasite interactions due to the wide range of effects they can have on host fitness and on the evolutionary trajectories of parasites. Here, we used a multinomial Bayesian phylogenetic modelling framework to explore the extent to which bird ecology and phylogeny impact the probability of being infected by one genus (hereafter single infection) or by multiple genera (hereafter co-infection) of haemosporidian parasites. We show that while nesting and migration behaviours influenced both the probability of being single- and co-infected, species position along the slow-fast life-history continuum and geographic range size were only pertinent in explaining variation in co-infection risk. We also found evidence for a phylogenetic conservatism regarding both single- and co-infections, indicating that phylogenetically related bird species tend to have similar infection patterns. This phylogenetic signal was four times stronger for co-infections than for single infections, suggesting that co-infections may act as a stronger selective pressure than single infections. Overall, our study underscores the combined influence of hosts' evolutionary history and attributes in determining infection risk in avian host communities. These results also suggest that co-infection risk might be under stronger deterministic control than single infection risk, potentially paving the way toward a better understanding of the emergence and evolution of infectious diseases., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Mountains are hotspots of biodiversity and ecosystem services, but they are warming about twice as fast as the global average. Climate change may reduce alpine snow cover and increase vegetation productivity, as in the Arctic. Here, we demonstrate that 77% of the European Alps above the tree line experienced greening (productivity gain) and <1% browning (productivity loss) over the past four decades. Snow cover declined significantly during this time, but in <10% of the area. These trends were only weakly correlated: Greening predominated in warmer areas, driven by climatic changes during summer, while snow cover recession peaked at colder temperatures, driven by precipitation changes. Greening could increase carbon sequestration, but this is unlikely to outweigh negative implications, including reduced albedo and water availability, thawing permafrost, and habitat loss.

Protists are abundant and play key trophic functions in soil. Documenting how their trophic contributions vary across large environmental gradients is essential to understand and predict how biogeochemical cycles will be impacted by global changes. Here, using amplicon sequencing of environmental DNA in open habitat soil from 161 locations spanning 2600 m of elevation in the Swiss Alps (from 400 to 3000 m), we found that, over the whole study area, soils are dominated by consumers, followed by parasites and phototrophs. In contrast, the proportion of these groups in local communities shows large variations in relation to elevation. While there is, on average, three times more consumers than parasites at low elevation (400-1000 m), this ratio increases to 12 at high elevation (2000-3000 m). This suggests that the decrease in protist host biomass and diversity toward mountains tops impact protist functional composition. Furthermore, the taxonomic composition of protists that infect animals was related to elevation while that of protists that infect plants or of protist consumers was related to soil pH. This study provides a first step to document and understand how soil protist functions vary along the elevational gradient., (© 2021 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.)

Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non-native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non-native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series, even more exciting results can be expected, especially about range shifts. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Despite their importance for biodiversity and ecosystem services, wetlands are among the most threatened ecosystems globally. The conservation of many migratory waterbirds depends on the conservation of a network of key sites along their flyways. However, the suitability of these sites is changing under climate change, and it is important that management of individual sites in the network adapts to these changes. Using bioclimatic models that also account for changes in inundation, we found that projected climate change will reduce habitat suitability for waterbirds at 57.5% of existing Critical Sites within Africa-Eurasia, varying from 20.1% in Eastern Europe to 87.0% in Africa. African and Middle East sites are particularly threatened, comprising 71 of the 100 most vulnerable sites. By highlighting priority sites for conservation and classifying Critical Sites into Climate Change Adaptation Strategy (CCAS) classes, our results can be used to support the climate change adaptation of both individual sites and the entire site network., (© 2021 John Wiley & Sons Ltd.)

Many species distribution models (SDMs) are built with precise but geographically restricted presence-absence data sets (e.g., a country) where only a subset of the environmental conditions experienced by a species across its range is considered (i.e., spatial niche truncation). This type of truncation is worrisome because it can lead to incorrect predictions e.g., when projecting to future climatic conditions belonging to the species niche but unavailable in the calibration area. Data from citizen-science programs, species range maps or atlases covering the full species range can be used to capture those parts of the species' niche that are missing regionally. However, these data usually are too coarse or too biased to support regional management. Here, we aim to (1) demonstrate how varying degrees of spatial niche truncation affect SDMs projections when calibrated with climatically truncated regional data sets and (2) test the performance of different methods to harness information from larger-scale data sets presenting different spatial resolutions to solve the spatial niche truncation problem. We used simulations to compare the performance of the different methods, and applied them to a real data set to predict the future distribution of a plant species (Potentilla aurea) in Switzerland. SDMs calibrated with geographically restricted data sets expectedly provided biased predictions when projected outside the calibration area or time period. Approaches integrating information from larger-scale data sets using hierarchical data integration methods usually reduced this bias. However, their performance varied depending on the level of spatial niche truncation and how data were combined. Interestingly, while some methods (e.g., data pooling, downscaling) performed well on both simulated and real data, others (e.g., those based on a Poisson point process) performed better on real data, indicating a dependency of model performance on the simulation process (e.g., shape of simulated response curves). Based on our results, we recommend to use different data integration methods and, whenever possible, to make a choice depending on model performance. In any case, an ensemble modeling approach can be used to account for uncertainty in how niche truncation is accounted for and identify areas where similarities/dissimilarities exist across methods., (© 2021 by the Ecological Society of America.)

Soil bacteria are largely missing from future biodiversity assessments hindering comprehensive forecasts of ecosystem changes. Soil bacterial communities are expected to be more strongly driven by pH and less by other edaphic and climatic factors. Thus, alkalinisation or acidification along with climate change may influence soil bacteria, with subsequent influences for example on nutrient cycling and vegetation. Future forecasts of soil bacteria are therefore needed. We applied species distribution modelling (SDM) to quantify the roles of environmental factors in governing spatial abundance distribution of soil bacterial OTUs and to predict how future changes in these factors may change bacterial communities in a temperate mountain area. Models indicated that factors related to soil (especially pH), climate and/or topography explain and predict part of the abundance distribution of most OTUs. This supports the expectations that microorganisms have specific environmental requirements (i.e., niches/envelopes) and that they should accordingly respond to environmental changes. Our predictions indicate a stronger role of pH over other predictors (e.g. climate) in governing distributions of bacteria, yet the predicted future changes in bacteria communities are smaller than their current variation across space. The extent of bacterial community change predictions varies as a function of elevation, but in general, deviations from neutral soil pH are expected to decrease abundances and diversity of bacteria. Our findings highlight the need to account for edaphic changes, along with climate changes, in future forecasts of soil bacteria., (© 2021. The Author(s).)

One key hypothesis explaining the fate of exotic species introductions posits that the establishment of a self-sustaining population in the invaded range can only succeed within conditions matching the native climatic niche. Yet, this hypothesis remains untested for individual release events. Using a dataset of 979 introductions of 173 mammal species worldwide, we show that climate-matching to the realized native climatic niche, measured by a new Niche Margin Index (NMI), is a stronger predictor of establishment success than most previously tested life-history attributes and historical factors. Contrary to traditional climatic suitability metrics derived from species distribution models, NMI is based on niche margins and provides a measure of how distant a site is inside or, importantly, outside the niche. Besides many applications in research in ecology and evolution, NMI as a measure of native climatic niche-matching in risk assessments could improve efforts to prevent invasions and avoid costly eradications.

Objectives: Anosmia/hyposomia have been described as early signs of COVID-19 infection in adults, including young asymptomatic patients who commonly refer olfactory disfunction as their only clinical manifestation. Very few studies involving paediatric age patients have been published until now. This study aims to determine the presence of olfactory dysfunction in children with COVID-19 infection through the use of a self-reported questionnaire and a new olfactory screening tool., Methods: Nested case-control study. All paediatric patients screened by reverse transcription polymerase chain reaction (RT-PCR) and Anti-SARS-CoV-2 antibodies for COVID-19 infection, during the study period (March-May 2020), were asked to respond to a questionnaire about symptoms of olfactory disfunction. Patients above six years old also performed an odor identification test based on seven odorants (Kradeo®). This test was designed based on our cultural context and eating habits., Results: 126 patients were recruited, including 33 with COVID-19 infection. 15% of the infected children referred anosmia and/or dysgeusia on the questionnaire, all of them were older than eleven years. The results of the odor test (69 patients) revealed subtle disturbances in the infected group (mostly misrecognition of odorants). Median odorant recognition was 3 odors [Interquartile range (IQR) 2-4] in case group and 4 [IQR 3-5] in controls. Male patients showed significantly larger disturbances than girls in both groups (p = 0.03)., Conclusion: Self-referred prevalence of olfactory disfunction in our sample of infected children is lower than that described in adults, especially among the youngest ones, maybe due to immature development of angiotensin-converting enzyme 2 (ACE2) receptors expressed in nasal mucosa. Nevertheless, one month after infection, subtle disturbances (misrecognition of odors) were identified among the infected children. This screening olfactory test provides a hygienic, user-friendly tool, suitable for screening children older than six years of age., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Assessing the degree to which climate explains the spatial distributions of different taxonomic and functional groups is essential for anticipating the effects of climate change on ecosystems. Most effort so far has focused on above-ground organisms, which offer only a partial view on the response of biodiversity to environmental gradients. Here including both above- and below-ground organisms, we quantified the degree of topoclimatic control on the occurrence patterns of >1,500 taxa and phylotypes along a c. 3,000 m elevation gradient, by fitting species distribution models. Higher model performances for animals and plants than for soil microbes (fungi, bacteria and protists) suggest that the direct influence of topoclimate is stronger on above-ground species than on below-ground microorganisms. Accordingly, direct climate change effects are predicted to be stronger for above-ground than for below-ground taxa, whereas factors expressing local soil microclimate and geochemistry are likely more important to explain and forecast the occurrence patterns of soil microbiota. Detailed mapping and future scenarios of soil microclimate and microhabitats, together with comparative studies of interacting and ecologically dependent above- and below-ground biota, are thus needed to understand and realistically forecast the future distribution of ecosystems., (© 2020 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

The extent to which species can balance out the loss of suitable habitats due to climate warming by shifting their ranges is an area of controversy. Here, we assess whether highly efficient wind-dispersed organisms like bryophytes can keep-up with projected shifts in their areas of suitable climate. Using a hybrid statistical-mechanistic approach accounting for spatial and temporal variations in both climatic and wind conditions, we simulate future migrations across Europe for 40 bryophyte species until 2050. The median ratios between predicted range loss vs expansion by 2050 across species and climate change scenarios range from 1.6 to 3.3 when only shifts in climatic suitability were considered, but increase to 34.7-96.8 when species dispersal abilities are added to our models. This highlights the importance of accounting for dispersal restrictions when projecting future distribution ranges and suggests that even highly dispersive organisms like bryophytes are not equipped to fully track the rates of ongoing climate change in the course of the next decades.

Biological invasions are a major driver of human-induced global environmental change. This makes monitoring of potential spread, population changes and control measures necessary for guiding management. We illustrate the value of integrated methods (species distribution modelling (SDM), plant population monitoring and questionnaires) for monitoring and assessing invasions of Heracleum mantegazzianum (giant hogweed) over time in Switzerland. SDMs highlighted the potential spread of the species, uncovered ecological mechanisms underlying invasions and guided monitoring at a regional level. We used adaptive and repeat plant sampling to monitor invasive population status and changes, and assess the effectiveness of H. mantegazzianum management over three periods (2005, 2013 and 2018) within the pre-Alps, Vaud. We also conducted questionnaire surveys with managers and the public. Multiscale modelling, and integrating global and regional SDMs, provided the best predictions, showing that H. mantegazzianum can potentially invade large parts of Switzerland, especially below 2 000 m a.s.l. Over time, populations of invasive H. mantegazzianum in the Vaud pre-Alps have declined, which is most likely due to a sharp rise in management uptake post 2007 (7% of municipalities before 2007 to 86% in 2018). The level of known invasive populations has decreased by 54% over time. Some municipalities have even successfully eradicated H. mantegazzianum within their borders. However, a few areas, particularly in the rural, higher-altitude municipalities, where management was not implemented effectively, populations have expanded, which could hamper control efforts at lower altitudes. We provide encouraging evidence that control measures can be effective in reducing plant invasions with long-term commitment, as well as a good template for using integrated methodological approaches to better study and monitor invasive alien species.

Venomous animals use venom, a complex biofluid composed of unique mixtures of proteins and peptides, for either predation or defense. Bumblebees, which occur in various habitats due to their unique thermoregulatory properties, mainly use venom for defense. Herein, we conducted an exploratory analysis of the venom composition of a bumblebee species ( Bombus pascuorum ) along an elevation gradient in the western Swiss Alps using shot-gun proteomic approaches to assess whether their defense mechanism varies along the gradient. The gradient was characterized by high temperatures and low humidity at low elevations and low temperatures and high humidity at high elevations. Venom composition is changing along the elevation gradient, with proteomic variation in the abundances of pain-inducing and allergenic proteins. In particular, the abundance of phospholipase A 2 -like, the main component of bumblebee venom, gradually decreases toward higher elevation (lower temperature), suggesting venom alteration and thus a decrease in bumblebee defense towards harsher environments. Larger datasets may complement this study to validate the observed novel trends., Competing Interests: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Biodiversity conservation requires modeling tools capable of predicting the presence or absence (i.e., occurrence-state) of species in habitat patches. Local habitat characteristics of a patch ( lh ), the cost of traversing the landscape matrix between patches (weighted connectivity [ wc ]), and the position of the patch in the habitat network topology ( nt ) all influence occurrence-state. Existing models are data demanding or consider only local habitat characteristics. We address these shortcomings and present a network-based modeling approach, which aims to predict species occurrence-state in habitat patches using readily available presence-only records.For the tree frog Hyla arborea in the Swiss Plateau, we delineated habitat network nodes from an ensemble habitat suitability model and used different cost surfaces to generate the edges of three networks: one limited only by dispersal distance (Uniform), another incorporating traffic, and a third based on inverse habitat suitability. For each network, we calculated explanatory variables representing the three categories ( lh , wc , and nt ). The response variable, occurrence-state, was parametrized by a sampling intensity procedure assessing observations of comparable species over a threshold of patch visits. The explanatory variables from the three networks and an additional non-topological model were related to the response variable with boosted regression trees.The habitat network models had a similar fit; they all outperformed the non-topological model. Habitat suitability index ( lh ) was the most important predictor in all networks, followed by third-order neighborhood ( nt ). Patch size ( lh ) was unimportant in all three networks.We found that topological variables of habitat networks are relevant for the prediction of species occurrence-state, a step-forward from models considering only local habitat characteristics. For any habitat patch, occurrence-state is most prominently influenced by its habitat suitability and then by the number of patches in a wide neighborhood. Our approach is generic and can be applied to multiple species in different habitats., Competing Interests: None declared., (© 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Mountains, representing storehouses of biodiversity, endemism and threatened species, are biodiversity hotspots of great conservation importance. However, increasing evidence indicates that mountain species throughout the world are responding to climate change, past or contemporary, by shifting their geographic distributions and patterns of genetic diversity, potentially affecting their adaptive capacity and increasing risk of extinction. Using the iconic high-elevation frog Nanorana parkeri as indicator, we showed how spatial analyses of climatic stability combined with genetic data allow unravelling amphibian responses to past and future climate changes on 'the roof of the world'-the Qinghai-Tibetan Plateau. We found that areas along the Yarlung Tsangpo Valley were climatically more stable relative to other regions, apparently serving as a large climatic refugium during Quaternary glaciations, but that these areas will likely be affected by future climate change. As populations closer to Quaternary refugia usually had higher genetic diversity, current genetic diversity can be explained in the largest part by distance to historically stable areas, outweighing other historical and contemporary factors. Along with the dynamics of suitable range, a fluctuating habitat fragmentation supported the pattern of historical changes in genetic diversity (N e ) over time. Our results emphasize strong relationships between amphibian genetic diversity, past range dynamics and where to preserve suitable habitats in the face of future climate changes. More generally, our findings highlighted a central role of refugia during Quaternary climatic fluctuations, and how isolation from refugia may have modulated amphibian genetic diversity across the Qinghai-Tibetan Plateau., (© 2019 The Authors. Journal of Animal Ecology © 2019 British Ecological Society.)

Archaeorhizomycetes, a widespread fungal class with a dominant presence in many soil environments, contains cryptic filamentous species forming plant-root associations whose role in terrestrial ecosystems remains unclear. Here, we apply a correlative approach to identify the abiotic and biotic environmental variables shaping the distribution of this fungal group. We used a DNA sequencing dataset containing Archaeorhizomycetes sequences and environmental variables from 103 sites, obtained through a random-stratified sampling in the Western Swiss Alps along a wide elevation gradient (>2,500 m). We observed that the relative abundance of Archaeorhizomycetes follows a "humped-shaped" curve. Fitted linear and quadratic generalized linear models revealed that both climatic (minimum temperature, precipitation sum, growing degree-days) and edaphic (carbon, hydrogen, organic carbon, aluminum oxide, and phyllosilicates) factors contribute to explaining the variation in Archaeorhizomycetes abundance. Furthermore, a network inference topology described significant co-abundance patterns between Archaeorhizomycetes and other saprotrophic and ectomycorrhizal fungal taxa. Overall, our results provide strong support to the hypothesis that Archaeorhizomycetes in this area have clear ecological requirements along wide, elevation-driven abiotic and biotic gradients. Additionally, correlations to soil redox parameters, particularly with phyllosilicates minerals, suggest Archaeorhizomycetes might be implied in biological rock weathering. Such soil taxa-environment studies along wide gradients are thus a useful complement to latitudinal field observations and culture-based approaches to uncover the ecological roles of cryptic soil organisms.

A longstanding question in ecology concerns the prediction of the fate of mountain species under climate change, where climatic and geomorphic factors but also endogenous species characteristics are jointly expected to control species distributions. A significant step forward would single out reliably landscape effects, given their constraining role and relative ease of theoretical manipulation. Here, we address population dynamics in ecosystems where the substrates for ecological interactions are mountain landscapes subject to climate warming. We use a minimalist model of metapopulation dynamics based on virtual species (i.e. a suitable assemblage of focus species) where dispersal processes interact with the spatial structure of the landscape. Climate warming is subsumed by an upward shift of species habitat altering the metapopulation capacity of the landscape and hence species viability. We find that the landscape structure is a powerful determinant of species survival, owing to the specific role of the predictably evolving connectivity of the various habitats. Range shifts and lags in tracking suitable habitat experienced by virtual species under warming conditions are singled out in different landscapes. The range of parameters is identified for which these virtual species (characterized by comparable viability thus restricting their possible fitnesses and niche widths) prove unable to cope with environmental change. The statistics of the proportion of species bound to survive is identified for each landscape, providing the temporal evolution of species range shifts and the related expected occupation patterns. A baseline dynamic model for predicting species fates in evolving habitats is thus provided., Competing Interests: The authors have declared that no competing interests exist.

The questions of how much abiotic environment contributes to explain species distributions, and which abiotic factors are the most influential, are key when projecting species realized niches in space and time. Here, we show that answers to these questions can be obtained by using species' ecological indicator values (EIVs). By calculating community averages of plant EIVs (397 plant species and 3988 vegetation plots), we found that substituting mapped environmental predictors with site EIVs led to a doubling of explained variation (22.5% to 44%). EIVs representing light and soil showed the highest model improvement, while EIVs representing temperature did not explain additional variance, suggesting that current temperature maps are already fairly accurate. Therefore, although temperature is frequently reported as having a dominant effect on species distributions over other factors, our results suggest that this might primarily result from limitations in our capacity to map other key environmental factors, such as light and soil properties, over large areas.

Demand for models in biodiversity assessments is rising, but which models are adequate for the task? We propose a set of best-practice standards and detailed guidelines enabling scoring of studies based on species distribution models for use in biodiversity assessments. We reviewed and scored 400 modeling studies over the past 20 years using the proposed standards and guidelines. We detected low model adequacy overall, but with a marked tendency of improvement over time in model building and, to a lesser degree, in biological data and model evaluation. We argue that implementation of agreed-upon standards for models in biodiversity assessments would promote transparency and repeatability, eventually leading to higher quality of the models and the inferences used in assessments. We encourage broad community participation toward the expansion and ongoing development of the proposed standards and guidelines.

Soil is one of the most complex systems on Earth, functioning at the interface between the lithosphere, biosphere, hydrosphere, and atmosphere and generating a multitude of functions. Moreover, soil constitutes the belowground environment from which plants capture water and nutrients. Despite their great importance, soil properties are often not sufficiently considered in other disciplines, especially in spatial studies of plant distributions. Most soil properties are available as point data and, to be used in spatial analyses, need to be generalised over entire regions (i.e. digital soil mapping). Three categories of statistical approaches can be used for such purpose: geostatistical approaches (GSA), predictive-statistical approaches (PSA), and hybrid approaches (HA) that combine the two previous ones. How then to choose the best approach in a given soil study context? Does it depend on the soil properties to be spatialized, the study area's characteristics, and/or the availability of soil data? The main aims of this study was to review the use of these three approaches to derive maps of soil properties in relation to the soil parameters, the study area characteristics, and the number of soil samples. We evidenced that the approaches that tend to show the best performance for spatializing soil properties were not necessarily the ones most used in practice. Although PSA was the most widely used, it tended to be outperformed by HA in many cases, but the latter was far less used. However, as the study settings were not always properly described and not all situations were represented in the set of papers analysed, more comparative studies would be needed across a wider range of regions, soil properties, and spatial scales to provide robust conclusions on the best spatialization methods in a specific context., Competing Interests: The authors have declared that no competing interests exist.

Interactions between plants and bacteria in the non-rhizosphere soil are rarely assessed, because they are less direct and easily masked by confounding environmental factors. By studying plant vegetation alliances and soil bacterial community co-patterning in grassland soils in 100 sites across a heterogeneous mountain landscape in the western Swiss Alps, we obtained sufficient statistical power to disentangle common co-occurrences and weaker specific interactions. Plant alliances and soil bacterial communities tended to be synchronized in community turnover across the landscape, largely driven by common underlying environmental factors, such as soil pH or elevation. Certain alliances occurring in distinct, local, environmental conditions were characterized by co-occurring specialist plant and bacterial species, such as the Nardus stricta and Thermogemmatisporaceae. In contrast, some generalist taxa, like Anthoxanthum odoratum and 19 Acidobacteria species, spanned across multiple vegetation alliances. Meta-scale analyses of soil bacterial community composition and vegetation surveys, complemented with local edaphic measurements, can thus prove useful to identify the various types of plant-bacteria interactions and the environments in which they occur.

Understanding the mechanisms by which the abiotic and biotic requirements of species, or ecological niches, change over time is a central issue in evolutionary biology. Niche evolution is poorly understood at both the macroecological and macroevolutionary scales, as niches can shift over short periods of time but appear to change more slowly over longer timescales. Although reconstructing past niches has always been a major concern for palaeontologists and evolutionary biologists, only a few recent studies have successfully determined the factors that affect niche evolution. Here, we compare the evolution of climatic niches in four main groups of terrestrial vertebrates using a modelling approach integrating both palaeontological and neontological data, and large-scale datasets that contain information on the current distributions, phylogenetic relationships and fossil records for a total of 11,465 species. By reconstructing historical shifts in geographical ranges and climatic niches, we show that niche shifts are significantly faster in endotherms (birds and mammals) than in ectotherms (squamates and amphibians). We further demonstrate that the diversity patterns of the four clades are directly affected by the rate of niche evolution, with fewer latitudinal shifts in ectotherms.

Asexual taxa often have larger ranges than their sexual progenitors, particularly in areas affected by Pleistocene glaciations. The reasons given for this 'geographical parthenogenesis' are contentious, with expansion of the ecological niche or colonisation advantages of uniparental reproduction assumed most important in case of plants. Here, we parameterized a spread model for the alpine buttercup Ranunculus kuepferi and reconstructed the joint Holocene range expansion of its sexual and apomictic cytotype across the European Alps under different simulation settings. We found that, rather than niche broadening or a higher migration rate, a shift of the apomict's niche towards colder conditions per se was crucial as it facilitated overcoming of topographical barriers, a factor likely relevant for many alpine apomicts. More generally, our simulations suggest potentially strong interacting effects of niche differentiation and reproductive modes on range formation of related sexual and asexual taxa arising from their differential sensitivity to minority cytotype disadvantage., (© 2018 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.)

In the version of this Article originally published, in Fig. 3a the first boundary was incorrectly labelled the "K/T boundary"; it should have read the "K/Pg boundary". The two equations in the main text were incorrectly omitted from the HTML. In the description of the posterior distribution of an ancestral state, the normal distribution was incorrectly described as being "assigned as prior to the node value"; it should have read "assigned as calibration to the node value". In the associated equation (the second equation in the text), the denominator of the last term was incorrectly given as "Node prior"; it should have read "Node calibration". In the same equation, the numerator of the third term on the right-hand side of the equation contained incorrect superscript notation on the x and this is shown in the full equation in the notice below.In the Acknowledgements, the following two sentences were incorrectly omitted: "The authors thank the Vital-IT facilities of the Swiss Institute of Bioinformatics for the computational support" and "This work was funded by the University of Lausanne and the Swiss National Science Foundation (CRSIII3-147630) to N.S." In the Author contributions section, the first sentence was incorrectly given as "J.R. designed the study. J.R., N.S. and D. Silvestro designed the methodology and ran the analyses"; it should have read "J.R., D.S. and N.S. designed the study and the methodology". In the Supplementary Information, all three instances of the word "prior" were incorrect and should have read "calibration".These errors have now been corrected in all versions of the Article.

Improving biodiversity predictions is essential if we are to meet the challenges posed by global change. As knowledge is key to feed models, we need to evaluate how debated theory can affect models. An important ongoing debate is whether environmental constraints limit the number of species that can coexist in a community (saturation), with recent findings suggesting that species richness in many communities might be unsaturated. Here, we propose that biodiversity models could address this issue by accounting for a duality: considering communities as unsaturated but where species composition is constrained by different scale-dependent biodiversity drivers. We identify a variety of promising advances for incorporating this duality into commonly applied biodiversity modelling approaches and improving their spatial predictions., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Drug exposure during pregnancy constitutes a major legal issue and a public health concern. Drug and metabolite determination in biological matrices from mother and newborn is an objective indication of prenatal drug exposure. However, limited data are available regarding the interpretation of these analytical results in terms of window of detection and degree of exposure. We collected paired maternal hair, meconium, placenta, and umbilical cord from 727 mother-newborn dyads. We analyzed these specimens by liquid chromatography-tandem mass spectrometry for the determination of cocaine, opioids, methadone, and amphetamines, and compared the analytical results from the four different matrices. The cases were divided in non-exposure, low, and frequent exposure, based on maternal hair concentrations and segmental analysis by trimesters. For cocaine, 62 cases tested positive in hair, 9 in meconium, 6 in placenta and 7 in umbilical cord. In the case of opioids, 14 maternal hair cases were positive, 11 meconium and umbilical cord and 9 placenta samples. For methadone, 11 cases were positive in hair, 9 in meconium and 6 in placenta and umbilical cord. For amphetamines, 18 cases were positive according to maternal hair, but all meconium, placenta, and umbilical cord tested negative. Maternal hair was the most sensitive specimen to detect drug exposure during pregnancy. Meconium, placenta, and umbilical cord tested positive if hair concentrations showed frequent drug use during the whole pregnancy, especially during the third trimester. Meconium, placenta, and umbilical cord also tested positive for morphine and metabolites, if this drug was administered during labour and delivery. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

Background: Premature infants have lower short-term immune responses to vaccination than term infants, but patterns of antibody persistence in preterm infants over longer periods are not well established. This study assessed the persistence of antibody response to the 13-valent pneumococcal conjugate vaccine (PCV13) in formerly preterm versus term infants., Methods: In total, 100 preterm and 100 term infants received PCV13 with routine vaccines at ages 2, 3, 4 and 12 months. Serotype-specific anticapsular immunoglobulin G (IgG)-binding antibodies and opsonophagocytic activity were determined 1 and 2 years after the last PCV13 dose., Results: At 1 and 2 years after the last vaccination (toddler dose), IgG geometric mean concentrations (GMCs) for all serotypes had declined from levels measured 1 month after the toddler dose but remained above pretoddler dose levels. IgG GMCs were significantly lower in preterm than term subjects for a majority of serotypes at both follow-up time points. IgG GMCs increased in both groups for some serotypes from the 1-year to 2-year follow-up, whereas others declined. Opsonophagocytic activity results supported the IgG results., Conclusions: The routine (3 + 1) vaccination schedule is likely to offer long-term protection against invasive pneumococcal disease in preterm infants and should be initiated regardless of gestational age or weight at birth, without delay of the toddler dose.

A fundamental goal of ecological research is to understand and model how processes generate patterns so that if conditions change, changes in the patterns can be predicted. Different approaches have been proposed for modelling species assemblage, but their use to predict spatial patterns of species richness and other community attributes over a range of spatial and temporal scales remains challenging. Different methods emphasize different processes of structuring communities and different goals. In this review, we focus on models that were developed for generating spatially explicit predictions of communities, with a particular focus on species richness, composition, relative abundance and related attributes. We first briefly describe the concepts and theories that span the different drivers of species assembly. A combination of abiotic processes and biotic mechanisms are thought to influence the community assembly process. In this review, we describe four categories of drivers: (i) historical and evolutionary, (ii) environmental, (iii) biotic, and (iv) stochastic. We discuss the different modelling approaches proposed or applied at the community level and examine them from different standpoints, i.e. the theoretical bases, the drivers included, the source data, and the expected outputs, with special emphasis on conservation needs under climate change. We also highlight the most promising novelties, possible shortcomings, and potential extensions of existing methods. Finally, we present new approaches to model and predict species assemblages by reviewing promising 'integrative frameworks' and views that seek to incorporate all drivers of community assembly into a unique modelling workflow. We discuss the strengths and weaknesses of these new solutions and how they may hasten progress in community-level modelling., (© 2015 Cambridge Philosophical Society.)