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Background: Although the infant gut microbiota has been extensively studied, comprehensive assessment on the microbiota determinants including technical variables has not been performed in large infant cohorts., Methods: We studied the effect of 109 variables on the 16S rRNA gene amplicon-based gut microbiota profiles of infants sampled longitudinally from three weeks to two years of life in the Finnish HELMi birth cohort. Spot faecal samples from both parents were included for intra-family analyses, totalling to 7657 samples from 985 families that were evaluated for beta-diversity patterns using permutational multivariate analysis on Bray-Curtis distances, and differential abundance testing and alpha-diversity for variables of interest. We also assessed the effect of different taxonomic levels and distance methods., Findings: In time point-specific models, the largest share of variation explained, up to 2-6%, were seen in decreasing order for the DNA extraction batch, delivery mode and related perinatal exposures, defecation frequency and parity/siblings. Variables describing the infant gastrointestinal function were continuously important during the first two years, reflecting changes in e.g., feeding habits. The effect of parity/siblings on infant microbiota was modified by birth mode and exposure to intrapartum antibiotics, exemplifying the tight interlinkage of perinatal factors relevant for infant microbiota research. In total, up to 19% of the biological microbiota variation in the infant gut could be explained. Our results highlight the need to interpret variance partitioning results in the context of each cohort's characteristics and microbiota processing., Interpretation: Our study provides a comprehensive report of key factors associated with infant gut microbiota composition across the two first years of life in a homogenous cohort. The study highlights possible important future research areas and confounding factors to be considered., Funding: This research was supported by Business Finland, Academy of Finland, Foundation for Nutrition Research and the Doctoral Program in Microbiology and Biotechnology, University of Helsinki, Finland., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

1. Characterisation of biodiversity is typically based on taxonomic approaches, while much less is known about other related aspects. Functional trait diversity is one such component of biodiversity that has not been addressed rigorously in ecological research until recently. We tested the congruence between taxonomic- and trait-based approaches, and examined how spatial configuration, local abiotic environmental factors and biotic effects interact to influence taxonomic- and trait-based characterisation of freshwater fish assemblages. 2. Fish assemblage data were compiled for 124 lakes in southern Finland. Variance partitioning in both linear regression analyses and redundancy analysis was used to quantify the relative contribution of spatial and environmental variables to taxonomic and functional trait diversity and structure. Additionally, a null model analysis was used to test for the potential effects of interspecific segregation and biotic interactions on the co-occurrence of species. 3. The species pool was relatively poor. However, trait-based classification of species indicated that most species belonged to unique functional entities, which suggested low redundancy in species composition. Correlation analysis indicated a very strong relationship between species richness (SR) and the number of unique trait combinations (UTC). Ecoregion-level heterogeneity in SR and UTC were well represented in a relatively small group of randomly selected lakes ( c. 30 lakes). Multiple regressions indicated moderate roles for abiotic environmental variables (i.e. lake surface area, depth, total phosphorous, colour and pH) in determining SR, UTC and the distribution of single trait categories, whereas geographical location was not generally influential. 4. Redundancy analysis revealed similar patterns to those of diversity analyses for taxonomic and associated trait-based structure, emphasising the effect of abiotic environmental variables and the negligible effect of geographical position. 5. Co-occurrence analysis indicated significant checkerboard distribution at the whole assemblage level, but interspecific segregation proved to be of relatively minor importance in the constrained analyses, where species pair combinations within trait category groups were evaluated. 6. Our results suggest that taxonomic- and trait-based patterns of boreal lake fish assemblages are strongly interrelated. Environmental filtering through the effects of local abiotic variables seems to have the most prominent role in determining trait-based assemblage patterns among lakes, which may also be secondarily shaped by biotic interactions. 7. From the applied perspective, it may not necessarily matter whether traditional taxonomic or more novel trait-based approaches are used in characterising spatial patterns in boreal fish assemblages. However, trait-based approaches may provide complementary information which cannot be directly revealed by taxonomic data. [ABSTRACT FROM AUTHOR]

1. Biodiversity–environment relationships are increasingly well-understood in the context of species richness and species composition, whereas other aspects of biodiversity, including variability in functional diversity (FD), have received rather little rigorous attention. For streams, most studies to date have examined either taxonomic assemblage patterns or have experimentally addressed the importance of species richness for ecosystem functioning. 2. I examined the relationships of the functional biodiversity of stream macroinvertebrates to major environmental and spatial gradients across 111 boreal headwater streams in Finland. Functional biodiversity encompassed functional richness (FR – the number of functional groups derived from a combination of functional feeding groups and habit trait groups), FD – the number of functional groups and division of individuals among these groups, and functional evenness (FE – the division of individuals among functional groups). Furthermore, functional structure (FS) comprised the composition and abundance of functional groups at each site. 3. FR increased with increasing pH, with additional variation related to moss cover, total nitrogen, water colour and substratum particle size. FD similarly increased with increasing pH and decreased with increasing canopy cover. FE decreased with increasing canopy cover and water colour. Significant variation in FS was attributable to pH, stream width, moss cover, substratum particle size, nitrogen, water colour with the dominant pattern in FS being related to the increase of shredder-sprawlers and the decrease of scraper-swimmers in acidic conditions. 4. In regression analysis and redundancy analysis, variation in functional biodiversity was not only related to local environmental factors, but a considerable proportion of variability was also attributable to spatial patterning of environmental variables and pure spatial gradients. For FR, 23.4% was related to pure environmental effects, 15.0% to shared environmental and spatial effects and 8.0% to spatial trends. For FD, 13.8% was attributable to environmental effects, 15.2% to shared environmental and spatial effects and 5% to spatial trends. For FE, 9.0% was related to environmental variables, 12.7% to shared effects of environmental and spatial variables and 4.5% to spatial variables. For FS, 13.5% was related to environmental effects, 16.9% to shared environmental and spatial effects and 15.4% to spatial trends. 5. Given that functional biodiversity should portray variability in ecosystem functioning, one might expect to find functionally rather differing ecosystems at the opposite ends of major environmental gradients (e.g. acidity, stream size). However, the degree to which variation in the functional biodiversity of stream macroinvertebrates truly portrays variability in ecosystem functioning is difficult to judge because species traits, such as feeding roles and habit traits, are themselves strongly affected by the habitat template. 6. If functional characteristics show strong responses to natural environmental gradients, they also are likely to do so to anthropogenic environmental changes, including changes in habitat structure, organic inputs and acidifying elements. However, given the considerable degree of spatial structure in functional biodiversity, one should not expect that only the local environment and anthropogenic changes therein are responsible for this variability. Rather, the spatial context, as well as natural variability along environmental gradients, should also be explicitly considered in applied research. [ABSTRACT FROM AUTHOR]