Give me a sample of air and I will tell which species are found from your region: Molecular identification of fungi from airborne spore samples

Fungi are a megadiverse group of organisms, they play major roles in ecosystem functioning and are important for human health, food production and nature conservation. Our knowledge on fungal diversity and fungal ecology is however still very limited, in part because surveying and identifying fungi is time demanding and requires expert knowledge. We present a method that allows anyone to generate a list of fungal species likely to occur in a region of interest, with minimal effort and without requiring taxonomical expertise. The method consists of using a cyclone sampler to acquire fungal spores directly from the air to an Eppendorf tube, and applying DNA barcoding with probabilistic species identification to generate a list of species from the sample. We tested the feasibility of the method by acquiring replicate air samples from different geographical regions within Finland. Our results show that air sampling is adequate for regional‐level surveys, with samples collected >100 km apart varying but samples collected <10 km apart not varying in their species composition. The data show marked phenology, and thus obtaining a representative species list requires aerial sampling that covers the entire fruiting season. In sum, aerial sampling combined with probabilistic molecular species identification offers a highly effective method for generating a species list of air‐dispersing fungi. The method presented here has the potential to revolutionize fungal surveys, as it provides a highly cost‐efficient way to include fungi as a part of large‐scale biodiversity assessments and monitoring programs.     

Ficellomycin: an aziridine alkaloid antibiotic with potential therapeutic capacity

Applied Microbiology and Biotechnology - Ficellomycin is an aziridine antibiotic produced by Streptomyces ficellus, which displays high in vitro activity against Gram-positive bacteria including...     

Testing a mechanistic dispersal model against a dispersal experiment with a wind‐dispersed moss

Wind is the main dispersal agent for a wide array of species and for these species the environmental conditions under which diaspores are released can potentially modify the dispersal kernel substantially. Little is known about how bryophytes regulate spore release, but conditions affecting peristome movements and vibration of the seta may be important. We modelled airborne spore dispersal of the bryophyte species Discelium nudum (spore diameter 25 μm), in four different release scenarios, using a Lagrangian stochastic dispersion model and meteorological data. We tested the model predictions against experimental data on colonization success at five distances (5, 10, 30, 50 and 100 m) and eight directions from a translocated point source during seven two‐day periods. The model predictions were generally successful in describing the observed colonization patterns, especially beyond 10 m. In the laboratory we established spore release thresholds; horizontal wind speed sd > 0.25 m s^?1 induced the seta to vibrate and in relative humidity < 75% the peristome was open. Our dispersal model predicts that the proportion of spores dispersing beyond 100 m is almost twice as large if the spores are released under turbulent conditions than under more stable conditions. However, including release thresholds improved the fit of the model to the colonization data only minimally, with roughly the same amount of variation explained by the most constrained scenario (assuming both vibration of the seta and an open peristome) and the scenario assuming random release. Model predictions under realised experimental conditions suggest that we had a low statistical power to rank the release scenarios due to the lack of measurements of the absolute rate of spore release. Our results hint at the importance of release conditions, but also highlight the challenges in dispersal experiments intended for validating mechanistic dispersal models.     

Food provisioning alters infection dynamics in populations of a wild rodent

While pathogens are often assumed to limit the growth of wildlife populations, experimental evidence for their effects is rare. A lack of food resources has been suggested to enhance the negative effects of pathogen infection on host populations, but this theory has received little investigation. We conducted a replicated two-factor enclosure experiment, with introduction of the bacterium Bordetella bronchiseptica and food supplementation, to evaluate the individual and interactive effects of pathogen infection and food availability on vole populations during a boreal winter. We show that prior to bacteria introduction, vole populations were limited by food availability. Bordetella bronchiseptica introduction then reduced population growth and abundance, but contrary to predictions, primarily in food supplemented populations. Infection prevalence and pathological changes in vole lungs were most common in food supplemented populations, and are likely to have resulted from increased congregation and bacteria transmission around feeding stations. Bordetella bronchiseptica-infected lungs often showed protozoan co-infection (consistent with Hepatozoon erhardovae), together with more severe inflammatory changes. Using a multidisciplinary approach, this study demonstrates a complex picture of interactions and underlying mechanisms, leading to population-level effects. Our results highlight the potential for food provisioning to markedly influence disease processes in wildlife mammal populations.     

How to make more out of community data? A conceptual framework and its implementation as models and software

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.     

Spatio‐temporal scaling of biodiversity in acoustic tropical bird communities

Automated analysis of acoustic communities is a rapidly emerging approach for the characterization and monitoring of biodiversity. To evaluate its utility, we should verify that such ‘bioacoustics’ can accurately detect ecological signal in spatiotemporal acoustic data. Targeting the ‘Biological Dynamics of Forest Fragments Project’ sites in Brazil, we ask: What is the relative contribution of the spatial, temporal and habitat dimension to variation in bird acoustic communities in a previously fragmented tropical rainforest? Does the functional diversity of bird communities scale similarly to space and time as does species diversity, when both are recorded by bioacoustics means? Overall, is the imprint of landscape fragmentation 30 years ago still audible in the present‐day soundscape? We sampled forty‐four sites in secondary forest and 107 sites in old‐growth forest, resulting in 11 000 h of audio recordings. We detected 60 bird species with satisfactory precision and recovered a linear log–log relation between sampling time and species diversity. Sites in primary forest host more species than sites in secondary forest, but the difference decreased with sampling time, as the slope was slightly higher in secondary than primary forests. Functional diversity, as exposed by vocalizing birds, accumulates faster than does species diversity. The similarity among local communities decreases with distance in both time and space, but stability in time is remarkably high: two acoustic samples from the same site one year (or more) apart prove more similar than two samples taken at the same time but from sites situated just a few hundred meters apart. These findings suggest that habitat modification can be heard as a long‐lasting imprint on the soundscape of regenerating habitats and identify soundscape–area and soundscape–time relations as a promising tool for biodiversity research, applied biomonitoring and restoration ecology.     

Forest and connectivity loss drive changes in movement behavior of bird species

In a rapidly changing world, it is important to understand how environmental modifications by humans affect species behavior. This is not a simple task, since we need to deal with a multitude of species and the different external contexts that affect their behavior. Here, we investigate how interpatch short-distance movements of 73 common forest bird species can be predicted by forest cover and forest isolation. We modeled bird movement as a function of environmental covariates, species traits – body mass and feeding habit – and phylogenetic relationships using Joint Species Movement Models. We used field data collected in forest edges and open pastures of six 600 × 600 m plots in the Atlantic Forest biodiversity hotspot. We found that birds fly larger distances and visit more forest patches and remnant trees with decreasing forest cover. Increasing landscape isolation results in larger flight distances, and it increases the use of trees as stepping-stones for most species. Our results show that birds can adjust their behavior as a response to spatial modification in resource distribution and landscape connectivity. These adjusted behaviors can potentially contribute to ecosystem responses to habitat modification.     

SPIKEPIPE: A metagenomic pipeline for the accurate quantification of eukaryotic species occurrences and intraspecific abundance change using DNA barcodes or mitogenomes

The accurate quantification of eukaryotic species abundances from bulk samples remains a key challenge for community ecology and environmental biomonitoring. We resolve this challenge by combining shotgun sequencing, mapping to reference DNA barcodes or to mitogenomes, and three correction factors: (a) a percent‐coverage threshold to filter out false positives, (b) an internal‐standard DNA spike‐in to correct for stochasticity during sequencing, and (c) technical replicates to correct for stochasticity across sequencing runs. The SPIKEPIPE pipeline achieves a strikingly high accuracy of intraspecific abundance estimates (in terms of DNA mass) from samples of known composition (mapping to barcodes R² = .93, mitogenomes R² = .95) and a high repeatability across environmental‐sample replicates (barcodes R² = .94, mitogenomes R² = .93). As proof of concept, we sequence arthropod samples from the High Arctic, systematically collected over 17 years, detecting changes in species richness, species‐specific abundances, and phenology. SPIKEPIPE provides cost‐efficient and reliable quantification of eukaryotic communities.     

Habitat fragmentation and species diversity in competitive communities

Habitat loss is one of the key drivers of the ongoing decline of biodiversity. However, ecologists still argue about how fragmentation of habitat (independent of habitat loss) affects species richness. The recently proposed habitat amount hypothesis posits that species richness only depends on the total amount of habitat in a local landscape. In contrast, empirical studies report contrasting patterns: some find positive and others negative effects of fragmentation per se on species richness. To explain this apparent disparity, we devise a stochastic, spatially explicit model of competitive species communities in heterogeneous habitats. The model shows that habitat loss and fragmentation have complex effects on species diversity in competitive communities. When the total amount of habitat is large, fragmentation per se tends to increase species diversity, but if the total amount of habitat is small, the situation is reversed: fragmentation per se decreases species diversity.     

Eco-evolutionary metapopulation dynamics and the spatial scale of adaptation

We construct a model that combines extinction-colonization dynamics with the dynamics of local adaptation in a network of habitat patches of dissimilar qualities. We derive a deterministic approximation for the stochastic model that allows the calculation of patch-specific incidences of occupancy and levels of adaptation at steady state. Depending on (i) the strength of local selection, (ii) the amount of genetic variance, (iii) the demographic cost of maladaptation, (iv) the spatial scale of gene flow, and (v) the amount of habitat heterogeneity, the model predicts adaptation at different spatial scales. Local adaptation is predicted when there is much genetic variance and strong selection, while network-level adaptation occurs when the demographic cost of maladaptation is low. For little genetic variance and high cost of maladaptation, the model predicts network-level habitat specialization in species with long-range migration but an intermediate scale of adaptation (mosaic specialization) in species with short-range migration. In fragmented landscapes, the evolutionary dynamics of adaptation may both decrease and enhance metapopulation viability in comparison with no evolution. The model can be applied to real patch networks with given sizes, qualities, and spatial positions of habitat patches.