Species-level Data Research Articles

Length–Weight Relationships of Commercial Species in the Eastern Australian Sea Cucumber Fishery

Biological data, such as length–weight relationships, are essential for the management and stewardship of harvested individuals. Sea cucumbers are a lucrative industry globally but many of the associated fisheries lack species-level biological data, which reduces the effectiveness of any management strategy. The Queensland Sea Cucumber Fishery (QSCF) on the Great Barrier Reef is managed through various controls: primarily catch limits, effort limits, zoning, and size restrictions. Over 20 species may be harvested but there is a lack of comprehensive biological data for many of these species, particularly important life history characteristics. This study addresses this knowledge gap by assessing 2621 individual length–weight relationships of key-target sea cucumber species associated with the fishery across the range of the distribution of the species and covering a variety of habitats, depths, sampling times, and management zones. Linear models with log transformations were used to analyse the relationships between length and weight. Results revealed significant positive relationships for all assessed species, with Holothuria atra having the clearest relationship between length and weight (R2 = 0.45). Only negative allometric relationships were observed, as is the case for many species of holothurians. Despite challenges associated with measuring and weighing these soft and elastic animals, results will be useful for understanding length–weight dynamics across species. This research underscores the importance of robust biological data for the effective management of sea cucumber fisheries and ultimately reef health.

Eco-phylogenetic study of Trebouxia in southern Africa reveals interbiome connectivity and potential endemism in a green algal lichen photobiont.

Southern Africa is a biodiversity hotspot rich in endemic plants and lichen-forming fungi. However, species-level data about lichen photobionts in this region are minimal. We focused on Trebouxia (Chlorophyta), the most common lichen photobiont, to understand how southern African species fit into the global biodiversity of this genus and are distributed across biomes and mycobiont partners. We sequenced Trebouxia nuclear ribosomal ITS and rbcL of 139 lichen thalli from diverse biomes in South Africa and Namibia. Global Trebouxia phylogenies incorporating these new data were inferred with a maximum likelihood approach. Trebouxia biodiversity, biogeography, and mycobiont-photobiont associations were assessed in phylogenetic and ecological network frameworks. An estimated 43 putative Trebouxia species were found across the region, including seven potentially endemic species. Only five clades represent formally described species: T. arboricola s.l. (A13), T. cf. cretacea (A01), T. incrustata (A06), T. lynniae (A39), and T. maresiae (A46). Potential endemic species were not significantly associated with the Greater Cape Floristic Region or desert. Trebouxia species occurred frequently across multiple biomes. Annual precipitation, but not precipitation seasonality, was significant in explaining variation in Trebouxia communities. Consistent with other studies of lichen photobionts, the Trebouxia-mycobiont network had an anti-nested structure. Depending on the metric used, ca. 20-30% of global Trebouxia biodiversity occurs in southern Africa, including many species yet to be described. With a classification scheme for Trebouxia now well established, tree-based approaches are preferable over "barcode gap" methods for delimiting new species.

A novel computational approach for the mining of signature pathways using species co-occurrence networks in gut microbiomes

BackgroundAdvances in metagenome sequencing data continue to enable new methods for analyzing biological systems. When handling microbial profile data, metagenome sequencing has proven to be far more comprehensive than traditional methods such as 16s rRNA data, which rely on partial sequences. Microbial community profiling can be used to obtain key biological insights that pave the way for more accurate understanding of complex systems that are critical for advancing biomedical research and healthcare. However, such attempts have mostly used partial or incomplete data to accurately capture those associations.MethodsThis study introduces a novel computational approach for the identification of co-occurring microbial communities using the abundance and functional roles of species-level microbiome data. The proposed approach is then used to identify signature pathways associated with inflammatory bowel disease (IBD). Furthermore, we developed a computational pipeline to identify microbial species co-occurrences from metagenome data at various granularity levels.ResultsWhen comparing the IBD group to a control group, we show that certain co-occurring communities of species are enriched for potential pathways. We also show that the identified co-occurring microbial species operate as a community to facilitate pathway enrichment.ConclusionsThe obtained findings suggest that the proposed network model, along with the computational pipeline, provide a valuable analytical tool to analyze complex biological systems and extract pathway signatures that can be used to diagnose certain health conditions.

Gut microbiome strain-sharing within isolated village social networks.

When humans assemble into face-to-face social networks, they create an extended social environment that permits exposure to the microbiome of others, thereby shaping the composition and diversity of the microbiome at individual and population levels1-6. Here we use comprehensive social network mapping and detailed microbiome sequencing data in 1,787 adults within 18 isolated villages in Honduras7 to investigate the relationship between network structure and gut microbiome composition. Using both species-level and strain-level data, we show that microbial sharing occurs between many relationship types, notably including non-familial and non-household connections. Furthermore, strain-sharing extends to second-degree social connections, suggesting the relevance of a person's broader network. We also observe that socially central people are more microbially similar to the overall village than socially peripheralpeople. Among 301 people whose microbiome was re-measured 2 years later, we observe greater convergence in strain-sharing in connected versus otherwise similar unconnected co-villagers. Clusters of species and strains occur within clusters of people in village social networks, meaning that social networks provide the social niches within which microbiome biology and phenotypic impact are manifested.

Climate and ecology predict latitudinal trends in sexual selection inferred from avian mating systems.

Sexual selection, one of the central pillars of evolutionary theory, has powerful effects on organismal morphology, behaviour, and population dynamics. However, current knowledge about geographical variation in this evolutionary mechanism and its underlying drivers remains highly incomplete, in part because standardised data on the strength of sexual selection is sparse even for well-studied organisms. Here, we use information on mating systems-including the incidence of polygamy and extra-pair paternity-to estimate the intensity of sexual selection in 10,671 (>99.9%) bird species distributed worldwide. We show that avian sexual selection varies latitudinally, peaking at higher latitudes, although the gradient is reversed in the world's most sexually selected birds-specialist frugivores-which are strongly associated with tropical forests. Phylogenetic models further reveal that the strength of sexual selection is explained by temperature seasonality coupled with a suite of climate-associated factors, including migration, diet, and territoriality. Overall, these analyses suggest that climatic conditions leading to short, intense breeding seasons, or highly abundant and patchy food resources, increase the potential for polygamy in birds, driving latitudinal gradients in sexual selection. Our findings help to resolve longstanding debates about spatial variation in evolutionary mechanisms linked to reproductive biology and also provide a comprehensive species-level data set for further studies of selection and phenotypic evolution in the context of global climatic change.

Taxonomic Data Objects for Communicating the Meaning of Species Names

A central problem in biodiversity data science remains the inability to precisely aggregate observations that originate from the same species. Current approaches still rely heavily on the ‘Genus species’ pair of Linnaean taxonomy to label and group data. However, such binomial species names do not alone contain enough information to distinguish variation in a name’s conceptual usage (i.e., meaning) across time, place, or investigator. This “species name-to-meaning” problem is well known, but no robust and scalable solutions yet exist (Berendsohn 1995Bisby 2000, Sutherland et al. 2000, Page 2007, Franz and Sterner 2018, Upham et al. 2021, Sterner et al. 2023, Sterner et al. 2020, Beach et al. 1993). The problem is widespread especially for well-studied groups like mammals, for which 45% more species are now recognized than 30 years ago, including many species splits and rearrangements (Burgin et al. 2018, Mammal Diversity Database 2024). To address this problem, we here propose to digitally package and sign the relevant taxonomic data associated with a given species name usage to form a ‘Taxonomic Data Object’ (TDO). These TDOs are conceptually similar to 'secundus' references (i.e., species name sec. author, Berendsohn 1995) but differ in being machine readable and thus operational from the perspective of high-throughput data science. TDOs aim to move from analog secundus references, which require a human to track meaning by reading the cited article, to a digital and machine-actionable taxonomic reference. Versioned TDOs that are digitally signed using hash algorithms (e.g., md5 or sha256, see Elliott et al. 2023) will allow for precisely communicating, with verified data provenance from sender to receiver, certain aspects of what a species name means according to a given authority at a given time. Example TDO contents include DarwinCore terms (e.g., scientificName, namePublishedIn, nameAccordingTo, nomenclaturalStatus (Darwin Core Maintenance Group 2021)) as well as meaning-rich digital assets like geographic range maps (e.g., GeoJSON format), exemplar DNA sequences (e.g., FASTA format or National Center for Biotechnology Information (NCBI) accession number), holotype specimen information (e.g., catalog number, type locality coordinates), and taxonomic treatment texts (including material citations, e.g., as digitized and extracted by Plazi TreatmentBank, Agosti and Egloff 2009; see Fig. 1). We discuss pilot examples comparing global bat species according to the v1.2 vs. v1.11 taxonomies of the Mammal Diversity Database (Sep 2020 vs. Apr 2023), showing how TDOs enable the reliable tracking of taxonomic meaning for the 63 bat species affected by splits during this period. We posit that widespread use of TDOs will enable the traceable exchange of taxonomic information across a variety of existing platforms, providing a path for accurate species-level data aggregation at global scales, at least for well-studied taxa.

The bacterial and yeast microbiota in livestock forages in Hungary

BackgroundAlong bacteria, yeasts are common in forages and forage fermentations as spoilage microbes or as additives, yet few studies exist with species-level data on these fungi’s occurrence in feedstuff. Active dry yeast and other yeast-based products are also common feed additives in animal husbandry. Here, we aimed to characterize both fermented and non-fermented milking cow feedstuff samples from Hungary to assess their microbial diversity in the first such study from Central Europe.ResultsWe applied long-read bacterial metabarcoding to 10 fermented and 25 non-fermented types of samples to assess bacterial communities and their characteristics, surveyed culturable mold and yeast abundance, and identified culturable yeast species. Fermented forages showed the abundance of Aerococcaceae, Bacillaceae, Brucellaceae, Lactobacillaceae, Staphylococcaceae, and Thermoactinomycetaceae, non-fermented ones had Cyanothecaceae, Enterobacteriaceae, Erwiniaceae, Gomontiellaceae, Oxalobacteraceae, Rhodobiaceae, Rickettsiaceae, and Staphylococcaceae. Abundances of bacterial families showed mostly weak correlation with yeast CFU numbers, only Microcoleaceae (positive) and Enterococcaceae and Alcaligenaceae (negative correlation) showed moderate correlation. We identified 14 yeast species, most commonly Diutina rugosa, Pichia fermentans, P. kudriavzevii, and Wickerhahomyces anomalus. We recorded S. cerevisiae isolates only from animal feed mixes with added active dry yeast, while the species was completely absent from fermented forages. The S. cerevisiae isolates showed high genetic uniformity.ConclusionOur results show that both fermented and non-fermented forages harbor diverse bacterial microbiota, with higher alpha diversity in the latter. The bacterial microbiome had an overall weak correlation with yeast abundance, but yeasts were present in the majority of the samples, including four new records for forages as a habitat for yeasts. Yeasts in forages mostly represented common species including opportunistic pathogens, along with a single strain of Saccharomyces used as a feed mix additive.

Landscape change and alien invasions drive shifts in native lady beetle communities over a century.

Understanding causes of insect population declines is essential for the development of successful conservation plans, but data limitations restrict assessment across spatial and temporal scales. Museum records represent a source of historical data that can be leveraged to investigate temporal trends in insect communities. Native lady beetle decline has been attributed to competition with established alien species and landscape change, but the relative importance of these drivers is difficult to measure with short-term field-based studies. We assessed distribution patterns for native lady beetles over 12 decades using museum records, and evaluated the relative importance of alien species and landscape change as factors contributing to changes in communities. We compiled occurrence records for 28 lady beetle species collected in Ohio, USA, from 1900 to 2018. Taxonomic beta-diversity was used to evaluate changes in lady beetle community composition over time. To evaluate the relative influence of temporal, spatial, landscape, and community factors on the captures of native species, we constructed negative binomial generalized additive models. We report evidence of declines in captures for several native species. Importantly, the timing, severity, and drivers of these documented declines were species-specific. Land cover change was associated with declines in captures, particularly for Coccinella novemnotata which declined prior to the arrival of alien species. Following the establishment and spread of alien lady beetles, processes of species loss/gain and turnover shifted communities toward the dominance of a few alien species beginning in the 1980s. Because factors associated with declines in captures were highly species-specific, this emphasizes that mechanisms driving population losses cannot be generalized even among closely related native species. These findings also indicate the importance of museum holdings and the analysis of species-level data when studying temporal trends in insect populations.

Species-level, metagenomic and proteomic analysis of microbe-immune interactions in severe asthma.

The airway microbiome in severe asthma has not been characterised at species-level by metagenomic sequencing, nor have the relationships between specific species and mucosal immune responses in 'type-2 low', neutrophilic asthma been defined. We performed an integrated species-level metagenomic data with inflammatory mediators to characterise prevalence of dominant potentially pathogenic organisms and host immune responses. Sputum and nasal lavage samples were analysed using long-read metagenomic sequencing with Nanopore and qPCR in two cross-sectional adult severe asthma cohorts, Wessex (n = 66) and Oxford (n = 30). We integrated species-level data with clinical parameters and 39 selected airway proteins measured by immunoassay and O-link. The sputum microbiome in health and mild asthma displayed comparable microbial diversity. By contrast, 23% (19/81) of severe asthma microbiomes were dominated by a single respiratory pathogen, namely H. influenzae (n = 10), M. catarrhalis (n = 4), S. pneumoniae (n = 4) and P. aeruginosa (n = 1). Neutrophilic asthma was associated with H. influenzae, M. catarrhalis, S. pneumoniae and T. whipplei with elevated type-1 cytokines and proteases; eosinophilic asthma with higher M. catarrhalis, but lower H. influenzae, and S. pneumoniae abundance. H. influenzae load correlated with Eosinophil Cationic Protein, elastase and IL-10. R. mucilaginosa associated positively with IL-6 and negatively with FGF. Bayesian network analysis also revealed close and distinct relationships of H. influenzae and M. catarrhalis with type-1 airway inflammation. The microbiomes and cytokine milieu were distinct between upper and lower airways. This species-level integrated analysis reveals central, but distinct associations between potentially pathogenic bacteria and airways inflammation in severe asthma.

A trait-based approach to quantify ecosystem services delivery potentials in the Sundarbans mangrove forest of Bangladesh

An ecosystem’s potential to deliver goods and services, primarily determined by the functional traits of the species, is crucial for assessing its health and conservation value. This study uses a trait-based approach to evaluate the spatial and temporal variation in the ecosystem services delivery potentials (ESDPs) of the Sundarbans mangrove. We analyzed abundance data from 81 permanent sample plots (PSPs), spread over different saline zones, collected between 1986 and 2014, paired with species-specific plant functional traits. Seventeen traits were examined, with species-level data sourced from secondary literature, linking traits to ecosystem services. Study revealed that plant height, specific leaf area, and root length are key traits for assessing ESDPs. The Sundarbans’ ESDPs varied spatially across different saline zones but remained stable over time. Notably, ESDPs were significantly higher in low saline zones compared to ESDPs in high saline zones. This spatial variation is partly explained by differences in plant species composition among saline zones and the relatively stable species composition over time. Results from mixed effect models showed that PSP as a random factor for all four models is attributed to the nested effect. The study highlights the value of functional traits in ecosystem service assessments, providing a robust method to predict how changes in biodiversity and environmental conditions affect service delivery. The observed trend of decreasing ESDPs with increasing salinity offers insights into the potential impacts of sea-level rise on mangrove forest functions. These findings are essential for developing conservation strategies and policies to preserve the Sundarbans’ ecological integrity and support local livelihoods. This research advocates for a trait-based framework as a critical tool for the sustainable management of mangrove ecosystems globally.

First record of the water mite species Arrenurus (Arrenurus) munovus Cook, 1980 from Belize, including the description of the female (Arrenuridae, Hydrachnidia, Acari)

We provide the description of the so far unknown female of Arrenurus munovus Cook 1980 as well as additional morphological data for the male. This is the first record of the species since its description from Southern Mexico and is extending the known distribution about 370 km east to the south-eastern of the peninsula de Yucatan. This is the first record of an Arrenurus species from Belize, as well as the first species level data on the Belizean freshwater mite fauna.

Macroevolution of the plant-hummingbird pollination system.

Plant-hummingbird interactions are considered a classic example of coevolution, a process in which mutually dependent species influence each other's evolution. Plants depend on hummingbirds for pollination, whereas hummingbirds rely on nectar for food. As a step towards understanding coevolution, this review focuses on the macroevolutionary consequences of plant-hummingbird interactions, a relatively underexplored area in the current literature. We synthesize prior studies, illustrating the origins and dynamics of hummingbird pollination across different angiosperm clades previously pollinated by insects (mostly bees), bats, and passerine birds. In some cases, the crown age of hummingbirds pre-dates the plants they pollinate. In other cases, plant groups transitioned to hummingbird pollination early in the establishment of this bird group in the Americas, with the build-up of both diversities coinciding temporally, and hence suggesting co-diversification. Determining what triggers shifts to and away from hummingbird pollination remains a major open challenge. The impact of hummingbirds on plant diversification is complex, with many tropical plant lineages experiencing increased diversification after acquiring flowers that attract hummingbirds, and others experiencing no change or even a decrease in diversification rates. This mixed evidence suggests that other extrinsic or intrinsic factors, such as local climate and isolation, are important covariables driving the diversification of plants adapted to hummingbird pollination. To guide future studies, we discuss the mechanisms and contexts under which hummingbirds, as a clade and as individual species (e.g. traits, foraging behaviour, degree of specialization), could influence plant evolution. We conclude by commenting on how macroevolutionary signals of the mutualism could relate to coevolution, highlighting the unbalanced focus on the plant side of the interaction, and advocating for the use of species-level interaction data in macroevolutionary studies.

MicroPredict: predicting species-level taxonomic abundance of whole-shotgun metagenomic data using only 16S amplicon sequencing data

BackgroundThe importance of the human microbiome in the analysis of various diseases is emerging. The two main methods used to profile the human microbiome are 16S rRNA gene sequencing (16S sequencing) and whole-genome shotgun sequencing (WGS). Owing to the full coverage of the genome in sequencing, WGS has multiple advantages over 16S sequencing, including higher taxonomic profiling resolution at the species-level and functional profiling analysis. However, 16S sequencing remains widely used because of its relatively low cost. Although WGS is the standard method for obtaining accurate species-level data, we found that 16S sequencing data contained rich information to predict high-resolution species-level abundances with reasonable accuracy.ObjectiveIn this study, we proposed MicroPredict, a method for accurately predicting WGS-comparable species-level abundance data using 16S taxonomic profile data.MethodsWe employed a mixed model using two key strategies: (1) modeling both sample- and species-specific information for predicting WGS abundances, and (2) accounting for the possible correlations among different species.ResultsWe found that MicroPredict outperformed the other machine learning methods.ConclusionWe expect that our approach will help researchers accurately approximate the species-level abundances of microbiome profiles in datasets for which only cost-effective 16S sequencing has been applied.

Characterization of pediatric urinary microbiome at species-level resolution indicates variation due to sex, age, and urologic history

Recently, associations between recurrent urinary tract infections (UTI) and the urinary microbiome (urobiome) composition have been identified in adults. However, little is known about the urobiome in children. We aimed to characterize the urobiome of children with species-level resolution and to identify associations based on UTI history. Fifty-four children (31 females and 21 males) from 3 months to 11 years of age participated in the study. Catheterized urine specimens were obtained from children undergoing a clinically indicated voiding cystourethrogram. To improve the analysis of the pediatric urobiome, we used a novel protocol using filters to collect biomass from the urine coupled with synthetic long-read 16S rRNA gene sequencing to obtain culture-independent species-level resolution data. We tested for differences in microbial composition between sex and history of UTIs using non-parametric tests on individual bacteria and alpha diversity measures. We detected bacteria in 61% of samples from 54 children (mean age 40.7 months, 57% females). Similar to adults, urobiomes were distinct across individuals and varied by sex. The urobiome of females showed higher diversity as measured by the inverse Simpson and Shannon indices but not the Pielou evenness index or number of observed species (p=0.05, p=0.04, p=0.35, and p=0.11, respectively). Additionally, several species were significantly overrepresented in females compared to males, including those from the genera Anaerococcus, Prevotella, and Schaalia (p=0.03, 0.04, and 0.02, respectively). Urobiome diversity increased with age, driven mainly by males. Comparison of children with a history of 1, 2, or 3+ UTIs revealed that urobiome diversity significantly decreases in the group that experienced 3+ UTIs as measured by the Simpson, Shannon, and Pielou indices (p=0.03, p=0.05, p=0.01). Several bacteria were also found to be reduced in abundance. In this study, we confirm that urobiome can be identified from catheter-collected urine specimens in infants as young as 3 months, providing further evidence that the pediatric bladder is not sterile. In addition to confirming variations in the urobiome related to sex, we identify age-related changes in children under 5 years of age, which conflicts with some prior research. We additionally identify associations with a history of UTIs. Our study provides additional evidence that the pediatric urobiome exists. The bacteria in the bladder of children appear to be affected by early urologic events and warrants future research.

Density data for Lake Erie benthic invertebrate assemblages from 1930 to 2019.

Benthic invertebrates are important trophic links in food webs and useful bioindicators of environmental conditions, but long-term benthic organism abundance data across broad geographic areas are rare and historic datasets are often not readily accessible. This dataset provides densities of benthic macroinvertebrates collected from 1930 to 2019 during surveys in Lake Erie, a Laurentian Great Lake. The surveys were funded by the governments of the United States and Canada to investigate the status and changes in the benthic community. From the total of 21 lake-wide and basin-wide benthic surveys conducted in Lake Erie from 1929 to 2019, we were able to acquire data for 17 surveys, including species-level data for 10 surveys and data by higher taxonomic groups for seven surveys. Our amassed Lake Erie dataset includes data from 11 surveys (including five with species-level data) conducted in the western basin in 1930-2019, seven surveys (six with species-level data) in the central basin, and eight surveys (seven with species-level data) in the eastern basin (1973-2019). This Lake Erie dataset represents the most extensive temporal dataset of benthic invertebrates available for any of the Laurentian Great Lakes. Benthic samples were collected using Ponar or Shipek bottom dredges and taxa densities were calculated as individuals per square meter using the area of the dredge. Density data are provided for taxa in the Annelida, Arthropoda, Mollusca, Cnidaria, Nemertea, and Platyhelminthes phyla. Current taxonomy was used for most groups but, in a few cases, older taxonomic names were used for consistency with historical data. Analysis of this dataset indicates that eutrophication, water quality improvement, and dreissenid introduction were the major drivers of changes in the benthic community in the western basin, while hypoxia was a major factor in the central basin, and dreissenid introduction was the most important driver in the eastern basin. Considering the rarity of high taxonomic resolution long-term benthic data for lake ecosystems, this dataset could be useful to explore broader aspects of ecological theory, including effects of eutrophication, hypoxia, invasive species, and other factors on community organization, phylogenetic and functional diversity, and spatial and temporal scales of variation in community structure. In addition, the dataset could be useful for studies on individual species, including abundance and distribution, species co-occurrence, and how the patterns of dominance and rarity change over space and time. Use of this dataset for academic or educational purposes is encouraged as long as this data paper is properly cited.

An extensive database on the traits and occurrences of amphibian species in Turkey

Amphibians are the most endangered taxa among vertebrates, and they face many threats during their complex life cycles. The species’ life history traits and occurrence database help understand species responses against ecological factors. Consequently, the species-level-trait database has gained more prominence in recent years as a useful tool for understanding the dimensions of communities, assembly processes of communities, and conserving biodiversity at the ecosystem level against environmental changes. However, in Turkey, there are deficiencies in the knowledge of the ecological traits of amphibians compared to other vertebrate taxa, as most studies have focused on their distribution or taxonomic status. Consequently, there is a need to create such a database for future research on all known extant amphibians in Turkey. We compiled a species-level data set of species traits and occurrences for all amphibians in Turkey using 436 literature sources. We completed 36 trait categories with 5611 occurrence data for 37 amphibian species in Turkey. This study provides an open, useful, and comprehensive database for macroecological and conservation studies on amphibians in Turkey.

P1205 Features of the gut microbiota that associate with clinical outcomes of fecal microbiota transplantation in Ulcerative Colitis: a systematic review and meta-analysis

Abstract Background Evidence continues to accumulate highlighting the potential of fecal microbiota transplantation (FMT) to induce remission in patients with ulcerative colitis (UC). However, rational donor and recipient selection strategies and predictive biomarkers are needed to increase its efficacy. This systematic review provides a comprehensive evaluation of the current literature on microbial factors of FMT donors and UC recipients that relate to clinical outcomes. Methods The MEDLINE, Embase and Cochrane databases were systematically searched through April 2023 for relevant studies. The quality of studies and risk of bias was analyzed with Joanna Briggs tools and a compound critical appraisal-score. Additionally, species-level data from two randomized controlled trials (TURN and FOCUS) were re-analyzed from a compositional perspective. Results Out of 2983 citations identified, 47 met the inclusion criteria, of which 20 fulfilled quality appraisal. Higher clinical response rates were associated with higher bacterial alpha-diversity of stools of UC recipients at baseline and following FMT, and with higher FMT donor alpha-diversity. Engraftment of the donors’ microbiota was often reported but could not be clearly linked to clinical response, possibly because not every donor has an ideal microbiome. Taxa most frequently reported to be related to response included members of the Lachnospiraceae family (e.g., Eubacterium rectale, Blautia obeum) and Oscillospiraceae family (e.g., Faecalibacterium prausnitzii, Ruminococcus bromii) whereas members of the Proteobacteria and Fusobacteria phyla and Ruminococcus gnavus were reported to correlate to non-response. Low virome richness and low Caudovirales bacteriophages at baseline as well as a decrease of Candida levels following FMT, were associated with clinical response. Compositional analyses showed that a clinical response is associated with a shift away from a low diversity, Bacteroides2-enterotype-like composition towards one of high diversity either dominated by various butyrate producers, the Christensenellaceae-Methanobrevibacter trophic network or a high diversity composition with abundant but not excessive levels of Prevotella copri. Conclusion In this systematic review we found distinctive features of microbial profiles of both donors and UC recipients to relate to clinical response to FMT. The predictive value of microbial markers should be further explored in future clinical studies to move towards a personalized FMT approach and delineate ‘super-donor’ profiles.

Quantifying effectiveness and best practices for bumblebee identification from photographs

Understanding pollinator networks requires species level data on pollinators. New photographic approaches to identification provide avenues to data collection that reduce impacts on declining bumblebee species, but limited research has addressed their accuracy. Using blind identification of 1418 photographed bees, of which 561 had paired specimens, we assessed identification and agreement across 20 bumblebee species netted in Montana, North Dakota, and South Dakota by people with minimal training. An expert identified 92.4% of bees from photographs, whereas 98.2% of bees were identified from specimens. Photograph identifiability decreased for bees that were wet or matted; bees without clear pictures of the abdomen, side of thorax, or top of thorax; bees photographed with a tablet, and for species with more color morphs. Across paired specimens, the identification matched for 95.1% of bees. When combined with a second opinion of specimens without matching identifications, data suggested a similar misidentification rate (2.7% for photographs and 2.5% specimens). We suggest approaches to maximize accuracy, including development of rulesets for collection of a subset of specimens based on difficulty of identification and to address cryptic variation, and focused training on identification that highlights detection of species of concern and species frequently confused in a study area.

Leveraging data from a private recreational fishing application to begin to understand potential impacts from offshore wind development

Abstract The development of offshore wind energy in the United States necessitates a sound understanding of trade-offs across ocean uses. Location data on private recreational fishing have been a glaring gap in understanding how society uses marine resources, despite its economic importance. In this study, we use a novel data set to start to fill that knowledge gap. We employ a flexible restricted likelihood spatial scan statistic on data from Fish Rules, a smartphone application, which provides georeferenced species-level regulations, to understand whether species-level data of user queries are clustered spatially. Originally developed for epidemiological studies of disease clusters, the flexible scan statistic employed in this study uses a Bernoulli likelihood ratio test to assess the size, number, and significance of clusters in presence/absence data for recreational species. We use a second data set of known fishing locations to validate that the clusters identify private recreational fishing activity. We then discuss the analysis in the context of wind lease areas in the region, highlighting its value in supporting management decision-making. The results suggest that Fish Rules data identify areas with a high likelihood of being private angler fishing locations and can assess differential impacts of offshore wind development on private recreational fishing activities.

Downed deadwood habitat heterogeneity drives trophic niche diversity of soil-dwelling animals

Habitat heterogeneity is one of the important drivers of biodiversity, but the underlying mechanisms are still vague. Increasing habitat heterogeneity often coincides with greater habitat space and/or greater food availability for organisms, but it is unclear whether and how these components are related to habitat selection. Downed dead wood (i.e., dead wood laying on the ground) is an important but understudied component of dead plant matter that creates spatial habitat heterogeneity for soil fauna on the ground. To unravel the role of dead wood for providing niche dimensionality for soil fauna via variance in resource use, we sampled Collembola communities from moss growing on bark and from bark on the logs of two tree species (pedunculate oak and Norway spruce) and from soil next to the logs. We assessed habitat selection of Collembola species combining abundance data with trophic position data using stable isotope ratios (i.e., δ13C and δ15N). Based on the Bray-Curtis dissimilarity, Collembola community composition differed significantly among the three habitats (i.e., moss, bark and soil). Collembola community-weighted mean δ13C and δ15N values also differed among the three habitats (average δ13C values of moss: −25.94‰, bark: −25.30‰, soil: −25.60‰; average δ15N values of moss: −4.80‰, bark: −3.83‰, soil: −5.11‰), partly reflecting isotopic differences of the habitats themselves (δ13C of moss: −29.83‰, bark: −28.26‰, soil: −29.04‰; δ15N of moss: −7.59‰, bark: −4.18‰, soil: −7.84‰). These findings indicate that Collembola depend on food sources derived from the habitats they inhabit at least at the community level. Collembola community-weighted variance of both δ13C and δ15N values ranked as bark > moss > soil. Species-level data suggested that the bark community included both bark-specific food specialists as well as species which likely use bark only as a temporary habitat based on their morphological traits supporting high mobility. These findings together indicate that the trophic niche variation of the Collembola community is larger in bark than in soil. Our results stress the importance of downed dead wood as a source of habitat heterogeneity, which in turn promotes soil animal diversity, likely via heterogeneity in food sources. Furthermore, the presence of dead wood on the ground could have consequences for organic matter processing by the soil animal community through sustaining a larger trophic niche variation even at a small spatial scale.