Knowledge of species distributions is essential for informing policies on nature conservation and restoration. However, updating them on a regular basis and doing so in a harmonized manner at the international level is difficult. The European Bird Census Council integrated national monitoring data covering 5 years to update farmland bird distributions and assessed how they changed. We used these data on 50 farmland bird species to generate 10×10 km maps showing their probability of occurrence from 2018 to 2022. We produced these maps with weighted ensemble species distribution models. We also developed models for the previous 5 years and plotted the differences in probabilities of occurrence per 10 × 10-km area between the two periods as calibrated change maps. We evaluated model performance at continental and regional levels and interpreted changes in probability of occurrence in relation to known abundance trends. Models showed good predictive performance (mean AUC ≈ 0.84; mean squared error ≈ 0.13). Change estimates were reliable for 43 species (high accuracy, low bias), and distribution changes were positively correlated with independent abundance trends (Pearson's r ≈ 0.50). Thus, the distribution maps for the two periods accurately captured species' distribution patterns and their temporal changes for all species at the European scale and for the majority of species in all regions except southeastern Europe. Among the 43 species with reliable estimates, predicted occurrences declined for 33 species, increased for nine, and were the same for one species. For most species, the direction of change in distribution was consistent with changes in species overall abundance in the same period, except for four species. Overall, our results indicated a recent contraction of farmland bird distributions in Europe, highlighting the strong capacity of existing bird monitoring networks to provide continent-wide species maps that can be updated regularly.

As human space exploration accelerates, understanding the organism-wide molecular effects of longer spaceflight in mammals becomes increasingly critical. Non-coding RNAs like miRNAs are key to regulating this landscape. We thus analyze 686 small RNA samples of female mice from 13 solid organs at 3 and 8 months of age, after at least 3 weeks on the International Space Station and compare them to earth-bound controls. We observe significant spaceflight effects in systemic tissue remodeling pathways along the Fat-Liver-Pancreas axis and in heart, brain, spleen and thymus. The MIR-17/92 and MIR-1/133 families drive distinct molecular changes through specific gene targeting. Age-dependent changes, smaller in magnitude compared to age-independent changes, primarily involve tissue remodeling through MIR-8, MIR-154 and MIR-15 families in mesenteric adipose tissue, pancreas, and diaphragm. Our findings provide evidence on how spaceflight regulates mammalian gene expression in preparation for interplanetary spaceflight.

The United Nations and European Union have set ambitious conservation goals to halt and reverse declines in biodiversity by protecting 30% of land and sea areas by 2030. Effective conservation planning requires evidence-based spatial prioritization to maximize the coverage of species within designated protected areas. Based on a pan-European database for occurrence and abundance of breeding birds collected in the 2010s, we applied the Zonation algorithm to identify key areas that would maximize the protection of ranges and populations for 435 species of breeding birds across Europe using either continental or national prioritization targets. When 30% of Europe's highest priority terrestrial areas were selected by the algorithm, 49% of species' ranges and 63% of species' populations were protected. When 10% and 30% of the highest priority lands were selected, compared with prioritization using occurrence data, prioritization using abundance data resulted in a higher percentage of species' populations, especially rare and range-restricted species, being represented for protected area coverage. Stratifying prioritization by habitat criteria greatly enhanced habitat-specific conservation efficiency, enabling coverage of over 80% of breeding bird species' populations in tundra, Mediterranean, and coastal habitats with a selection of 10% of the highest priority areas for each. Our prioritization supports international targets adopted under the Kunming-Montreal Global Biodiversity Framework by identifying key areas and providing a roadmap to guide optimal site protection and conservation planning in Europe.

The oral cavity harbours a complex microbial ecosystem and a key interface with the external environment. To gain a broader and more temporally resolved understanding of the oral microbiome, we analysed 1,242 samples from 585 individuals, including specimens from aligners, plaque, and saliva across healthy individuals and patients with caries or periodontitis. We found that clear aligners, worn continuously, provide a notably stable and comprehensive snapshot of oral microbial diversity, capturing 399 species and substantially overlapping with saliva. While only 25 species showed disease-associated differences, functional profiling revealed an extensive biosynthetic capacity, with 41,923 biosynthetic gene clusters organized into 1,786 families. Among these, 103 gene cluster families showed differential abundance in disease states and included both characterized antimicrobials and potentially novel metabolites. This study underscores the value of functional microbiome profiling in advancing precision oral health.

Obesity, a global health concern, is associated with alterations in the gut microbiome, yet its spatial dynamics across the gastrointestinal (GI) tract remain poorly understood. This study provides the first comprehensive analysis of the spatial microbiome in individuals with obesity, encompassing samples from the stomach, peritoneum, jejunum (50 cm and 150 cm post-Treitz), and feces before and after bariatric surgery. Using 16 S rRNA sequencing, we analyzed microbial composition and diversity after computational decontamination in 172 high-quality samples from 51 participants. Our results reveal significant differences in alpha diversity across GI sites, with stool samples exhibiting the highest diversity, which decreased post-surgery. The presence of microbial DNA in traditionally sterile compartments, such as the peritoneum and stomach, suggests potential microbial-host interactions warranting further exploration. Contaminants, including Nitrotoga sp., were identified in low-biomass samples and excluded using computational decontamination, emphasizing the need for rigorous controls. This study establishes a foundation for spatial microbiome analysis in obesity, highlighting the impact of bariatric surgery and the importance of advanced multi-omics approaches to unravel host-microbiome dynamics.

The Swiss Common Breeding Bird Monitoring ("Monitoring Häufige Brutvögel" MHB) is a long-term study organized by the Swiss Ornithological Institute. Its main goal is to collect data for estimating breeding population trends of relatively abundant and widespread species. Since 1999, 267 one-km squares laid out in a mostly systematic grid across all of Switzerland have been surveyed annually by skilled, mostly volunteer ornithologists. The sampling sites thus cover a wide range of typical Western European habitats, and an altitudinal range from 250 up to 2750 m above sea level. Bird populations are recorded using a simplified territory mapping protocol with two visits per square above the timberline and three elsewhere. Surveys are conducted during the breeding season (mid-April to early July) along a square-specific transect route that does not change over the years. A typical transect route is between 4 and 6 km long, and each visit usually lasts 3 to 4 h. The location of all visually or acoustically detected birds is recorded on topographical maps or using a smartphone app. Records that meet predefined criteria in terms of species-specific breeding period and observed behavior are retained for the subsequent step of territory delimitation. This is done automatically for most species by the program Autoterri since 2022 and was done manually before, with subsequent checks by an expert. This process finally results in an estimate of the total number of detected territories per species, square and year. The design also explicitly generates detection histories, consisting of two to three numbers that represent the number of territories found to be occupied during each respective visit, enabling the analysis with binomial N-mixture and site-occupancy models. The dataset currently covers the breeding seasons from 1999 to 2024 and includes 6852 site-by-year combinations with estimates of detected territory numbers. It covers 162 of the 166 bird species recorded at least once as potential breeders, excluding four species to prevent potential disturbance at nesting sites. Besides informing about population trends, data from the Swiss Common Breeding Bird Monitoring were used to illustrate several methodological developments in N-mixture, occupancy and related models and to answer scientific and applied questions. With its clearly defined survey method, the largely systematic distribution of its survey sites, and the long timespan covered, it is likely that this dataset will continue to make important contributions in biological and biostatistical research. Herewith, we make the annually updated data set available with a CC BY 4.0 license, allowing researchers and conservationists to use and analyze the data for their own research and conservation efforts.

The human microbiome, distributed across various anatomical sites, holds promise for identifying diagnostic biomarkers and therapeutic targets in disease. In inflammatory bowel disease (IBD), including ulcerative colitis (UC), interactions between the gut and oral microbiomes are crucial for understanding disease mechanisms and guiding interventions. The IMAGINE study sequenced 1,931 specimens from saliva, plaque, stool, and other sources in patients and healthy controls. Here, we assess whether the oral (saliva/plaque) or gut microbiota provides greater diagnostic potential in IBD and examine shared dysregulation across sample types. Among 177 oral samples (102 healthy, 75 IBD) and 92 stool samples (57 healthy, 35 IBD), we identified 240 distinct strains in plaque, 229 in saliva, and 231 in stool, with 46 strains present in all three. Saliva showed a significantly higher average effect size (0.2) than stool (0.04) and plaque (0.06). Notably, Actinomyces sp., Bifidobacterium dentium, and Veillonella parvula exhibited increased effect sizes, suggesting their potential as diagnostic markers or therapeutic targets. These findings indicate that microbiome profiling in IBD may improve diagnostics and treatment strategies. ### Competing Interest Statement JMS declares consultant honorary from Akero, Alentis, Alexion, Altimmune, Astra Zeneca, 89Bio, Bionorica, Boehringer Ingelheim, Gilead Sciences, GSK, HistoIndex, Ipsen, Inventiva Pharma, Madrigal Pharmaceuticals, Kriya Therapeutics, Lilly, MSD Sharp & Dohme GmbH, Novartis, Novo Nordisk, Pfizer, Roche, Sanofi, Siemens Healthineers; speaker honorarium from AbbVie, Boehringer Ingelheim, Gilead Sciences, Ipsen Novo Nordisk, Madrigal Pharmaceuticals, Stockholder options: Hepta Bio.

AbstractThe identification of targetomes remains a challenge given the pleiotropic effect of miRNAs, the limited effects of miRNAs on individual targets, and the sheer number of estimated miRNA–target gene interactions (MTIs), which is around 44,571,700. Currently, targetome identification for single miRNAs relies on computational evidence and functional studies covering smaller numbers of targets. To ensure that the targetome analysis could be experimentally verified by functional assays, we employed a systematic approach and explored the targetomes of four miRNAs (miR-129-5p, miR-129-1-3p, miR-133b, and miR-873-5p) by analyzing 410 predicted target genes, both of which were previously associated with Parkinson’s disease (PD). After performing 13,536 transfections, we validated 442 of the 705 putative MTIs (62,7%) through dual luciferase reporter assays. These analyses increased the number of validated MTIs by at least 2.1-fold for miR-133b and by a maximum of 24.3-fold for miR-873-5p. Our study contributes to the experimental capture of miRNA targetomes by addressing i) the ratio of experimentally verified MTIs to predicted MTIs, ii) the sizes of disease-related miRNA targetomes, and iii) the density of MTI networks. A web service to support the analyses on the MTI level is available online (https://ccb-web.cs.uni-saarland.de/utr-seremato), and all the data have been added to the miRATBase database (https://ccb-web.cs.uni-saarland.de/miratbase).

Single-cell RNA sequencing (RNA-seq) has revolutionized our understanding of cell biology, developmental and pathophysiological molecular processes, paving the way toward novel diagnostic and therapeutic approaches. However, most of the gene regulatory processes on the single-cell level are still unknown, including post-transcriptional control conferred by microRNAs (miRNAs). Like the established single-cell gene expression analysis, advanced computational expertise is required to comprehensively process newly emerging single-cell miRNA-seq datasets. A web server providing a workflow tailored for single-cell miRNA-seq data with a self-explanatory interface is currently not available. Here, we present SingmiR, enabling the rapid (pre-)processing and quantification of human miRNAs from noncoding single-cell samples. It performs read trimming for different library preparation protocols, generates automated quality control reports and provides feature-normalized count files. Numerous standard and advanced analyses such as dimension reduction, clustered feature heatmaps, sample correlation heatmaps and differential expression statistics are implemented. We aim to speed up the prototyping pipeline for biologists developing single-cell miRNA-seq protocols on small to medium-sized datasets. SingmiR is freely available to all users without the need for a login at https://www.ccb.uni-saarland.de/singmir.

Wildlife and zoonotic diseases are increasingly impacting human society, the food chain, and wildlife; therefore, proactive mitigation tools for predicting large-scale risk of the relevant pathogens are urgently needed. Birds and bats are large-scale disease reservoirs and transmitters. However, holistic understanding for which bird and bat species act as reservoirs for pathogens remains understudied. Here, we test the extent to which the features related to the mobile species and local climate identify reservoir hosts for the 18 most-sampled pathogens across Europe. Species with slower pace of life (i.e., larger bodied and longer lived), sedentary species, and forest species had high pathogen prevalence. Temperature was the most important predictor for pathogen prevalence, but its effects varied in different directions. Overall, host species traits and climatic gradients robustly predicted pathogen prevalence, especially for non-vector-transmitted pathogens. We offer a data-driven basis for developing targeted interventions to mitigate impacts of zoonotic diseases, particularly in the face of climate change.

The human microbiome emerges as a promising reservoir for diagnostic markers and therapeutics. Since host-associated microbiomes at various body sites differ and diseases do not occur in isolation, a comprehensive analysis strategy highlighting the full potential of microbiomes should include diverse specimen types and various diseases. To ensure robust data quality and comparability across specimen types and diseases, we employ standardized protocols to generate sequencing data from 1931 prospectively collected specimens, including from saliva, plaque, skin, throat, eye, and stool, with an average sequencing depth of 5.3 gigabases. Collected from 515 patients, these samples yield an average of 3.7 metagenomes per patient. Our results suggest significant microbial variations across diseases and specimen types, including unexpected anatomical sites. We identify 583 unexplored species-level genome bins (SGBs) of which 189 are significantly disease-associated. Of note, the existence of microbial resistance genes in one specimen was indicative of the same resistance genes in other specimens of the same patient. Annotated and previously undescribed SGBs collectively harbor 28,315 potential biosynthetic gene clusters (BGCs), with 1050 significant correlations to diseases. Our combinatorial approach identifies distinct SGBs and BGCs, emphasizing the value of pan-body pan-disease microbiomics as a source for diagnostic and therapeutic strategies. In this large-scale metagenomics study encompassing 3,483 human host-derived samples from seven body sites, researchers identify 583 unreported single-genome bins and report 314 metagenome-disease as well as 814 biosynthetic gene-disease associations.

This deliverable shows, using farmland birds as a demonstrative case study, how the existing European network of bird monitoring schemes could be used to regularly update the distribution of terrestrial breeding birds across the whole of EU and neighbouring countries. In addition, it shows how changes in distribution could be assessed on frequent intervals suitable for informing on the achievement of EU environmental policy targets.

Summary In Europe, population estimates of breeding birds are produced nationally and are periodically compiled at EU or pan-European scales. Until now, no other source was available to explore the robustness of these estimates. In this study, we compared population sizes reported in the latest edition of the European Red List of Birds (ERLoB) with those produced using data from the second European Breeding Bird Atlas (EBBA2) to assess their consistency and determine parameters behind variability in population estimates that deserve further attention in the future. In general, European population estimates derived from summing local abundance data from EBBA2 were similar to those obtained from ERLoB, although for some species they differed considerably, particularly in those distributed mainly in southern Europe. National population estimates from EBBA2 also did not differ markedly from those in ERLoB. However, we found that EBBA2 provided larger national population sizes than ERLoB for widespread species, suggesting that spatial information is more relevant for properly assessing their population size than for localised species. Our analysis also showed that, in general, population estimates based on robust methodological protocols (e.g. complete counts, statistical inference) contributed to reducing differences between ERLoB and EBBA2 values. Interestingly, EBBA2 and ERLoB estimates were quite similar for species classified in Europe as “Threatened” or “Near Threatened”, whereas the values for “Least Concern” species were consistently different between these two sources. Our results indicate which type of species would benefit from additional efforts to improve national population estimates and their consistency across countries, issues that are of paramount importance for guiding conservation strategies in Europe.

Species respond dynamically to climate change and exhibit time lags. Consequently, species may not occupy their full climatic niche during range shifting. Here, we assessed climate niche tracking during recent range shifts of European and United States (US) birds. Using data from two European bird atlases and from the North American Breeding Bird Survey between the 1980s and 2010s, we analysed range overlap and climate niche overlap based on kernel density estimation. Phylogenetic multiple regression was used to assess the effect of species morphological, ecological and biogeographic traits on range and niche metrics. European birds shifted their ranges north and north-eastwards, US birds westwards. Range unfilling was lower than expected by null models, and niche expansion was more common than niche unfilling. Also, climate niche tracking was generally lower in US birds and poorly explained by species traits. Overall, our results suggest that dispersal limitations were minor in range shifting birds in Europe and the USA while delayed extinctions from unfavourable areas seem more important. Regional differences could be related to differences in land use history and monitoring schemes. Comparative analyses of range and niche shifts provide a useful screening approach for identifying the importance of transient dynamics and time-lagged responses to climate change. This article is part of the theme issue ‘Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere’.

Understanding human, animal, and environmental microbiota is essential for advancing global health and combating antimicrobial resistance (AMR). We investigate the oral and gut microbiota of 48 animal species in captivity, comparing them to those of wildlife animals. Specifically, we characterize the microbiota composition, metabolic pathways, AMR genes, and biosynthetic gene clusters (BGCs) encoding the production of specialized metabolites. Our results reveal a high diversity of microbiota, with 585 novel species-level genome bins (SGBs) and 484 complete BGCs identified. Functional gene analysis of microbiomes shows diet-dependent variations. Furthermore, by comparing our findings to wildlife-derived microbiomes, we observe the impact of captivity on the animal microbiome, including examples of converging microbiome compositions. Importantly, our study identifies AMR genes against commonly used veterinary antibiotics, as well as resistance to vancomycin, a critical antibiotic in human medicine. These findings underscore the importance of the 'One Health' approach and the potential for zoonotic transmission of pathogenic bacteria and AMR. Overall, our study contributes to a better understanding of the complexity of the animal microbiome and highlights its BGC diversity relevant to the discovery of novel antimicrobial compounds. Here the authors assess 71 fecal and saliva samples of 48 different zoo animal species, uncovering 585 unreported microbial genomes and revealing 484 complete biosynthetic gene clusters, while comparing the results to wildlife samples.

Background Different production systems of livestock animals influence various factors, including the gut microbiota.Methods We investigated whether changing the conditions from barns to free-range chicken farming impacts the microbiome over the course of three weeks. We compared the stool microbiota of chicken from industrial barns after introducing them either in community or separately to a free-range environment.Results Over the six time points, 12 taxa-mostly lactobacilli-changed significantly. As expected, the former barn chicken cohort carries more resistances to common antibiotics. These, however, remained positive over the observed period. At the end of the study, we collected eggs and compared metabolomic profiles of the egg white and yolk to profiles of eggs from commercial suppliers. Here, we observed significant differences between commercial and fresh collected eggs as well as differences between the former barn chicken and free-range chicken.Conclusion Our data indicate that the gut microbiota can undergo alterations over time in response to changes in production systems. These changes subsequently exert an influence on the metabolites found in the eggs. The preliminary results of our proof-of-concept study motivate larger scale observations with more individual chicken and longer observation periods.

Climate change has been associated with both latitudinal and elevational shifts in species’ ranges. The extent, however, to which climate change has driven recent range shifts alongside other putative drivers remains uncertain. Here, we use the changing distributions of 378 European breeding bird species over 30 years to explore the putative drivers of recent range dynamics, considering the effects of climate, land cover, other environmental variables, and species’ traits on the probability of local colonisation and extinction. On average, species shifted their ranges by 2.4 km/year. These shifts, however, were significantly different from expectations due to changing climate and land cover. We found that local colonisation and extinction events were influenced primarily by initial climate conditions and by species’ range traits. By contrast, changes in climate suitability over the period were less important. This highlights the limitations of using only climate and land cover when projecting future changes in species’ ranges and emphasises the need for integrative, multi-predictor approaches for more robust forecasting.

Species' range shifts and local extinctions caused by climate change lead to community composition changes. At large spatial scales, ecological barriers, such as biome boundaries, coastlines, and elevation, can influence a community's ability to shift in response to climate change. Yet, ecological barriers are rarely considered in climate change studies, potentially hindering predictions of biodiversity shifts. We used data from two consecutive European breeding bird atlases to calculate the geographic distance and direction between communities in the 1980s and their compositional best match in the 2010s and modeled their response to barriers. The ecological barriers affected both the distance and direction of bird community composition shifts, with coastlines and elevation having the strongest influence. Our results underscore the relevance of combining ecological barriers and community shift projections for identifying the forces hindering community adjustments under global change. Notably, due to (macro)ecological barriers, communities are not able to track their climatic niches, which may lead to drastic changes, and potential losses, in community compositions in the future.

In 2019, researchers from the EAT-Lancet Commission developed the 'Planetary Health (PH) diet'. Specifically, they provided recommendations pertaining to healthy diets derived from sustainable food systems. Thus far, it has not been analysed how such a diet affects the human intestinal microbiome, which is important for health and disease development. Here, we present longitudinal genome-wide metagenomic sequencing and mass spectrometry data on the gut microbiome of healthy volunteers adhering to the PH diet, as opposed to vegetarian or vegan (VV) and omnivorous (OV) diets. We obtained basic epidemiological information from 41 healthy volunteers and collected stool samples at inclusion and after 2, 4, and 12 weeks. Individuals opting to follow the PH diet received detailed instructions and recipes, whereas individuals in the control groups followed their habitual dietary pattern. Whole-genome DNA was extracted from stool specimens and subjected to shotgun metagenomic sequencing (~3 GB per patient). Conventional bacterial stool cultures were performed in parallel and bacterial species were identified with matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. We analysed samples from 16 PH, 16 OV, and 9 VV diet patterns. The α-diversity remained relatively stable for all dietary groups. In the PH group, we observed a constant increase from 3.79% at inclusion to 4.9% after 12 weeks in relative abundance of Bifidobacterium adolescentis. Differential PH abundance analysis highlighted a non-significant increase in possible probiotics such as Paraprevotella xylaniphila and Bacteroides clarus. The highest abundance of these bacteria was observed in the VV group. Dietary modifications are associated with rapid alterations to the human gut microbiome, and the PH diet led to a slight increase in probiotic-associated bacteria at ≥4 weeks. Additional research is required to confirm these findings.