The quest for trait convergence and divergence in community assembly: are null-models the magic wand?

AbstractUnderstanding the imprint of environmental filtering on community assembly along environmental gradients is a key objective of trait-gradient analyses. Depending on local constraints, this filtering generally entails that species departing from an optimum trait value have lower abundances in the community. The Community-Weighted Mean (CWM) and Variance (CWV) of trait values are then expected to depict the optimum and intensity of filtering, respectively. However, the trait distribution within the regional species pool and its limits can also affect local CWM and CWV values apart from the effect of environmental filtering. The regional trait range limits are more likely to be reached in communities at the extremes of environmental gradients. Analogous to the mid-domain effect in biogeography, decreasing CWV values in extreme environments can then represent the influence of regional trait range limits rather than stronger filtering in the local environment. We name this effect the “Trait-Gradient Boundary Effect” (TGBE). First, we use a community assembly framework to build simulated communities along a gradient from a species pool and environmental filtering with either constant or varying intensity while accounting for immigration processes. We demonstrate the significant influence of TGBE, in parallel to environmental filtering, on CWM and CWV at the extremes of the environmental gradient. We provide a statistical tool based on Approximate Bayesian Computation to decipher the respective influence of local environmental filtering and regional trait range limits. Second, as a case study, we reanalyze the functional composition of alpine plant communities distributed along a gradient of snow cover duration. We show that leaf trait convergence found in communities at the extremes of the gradient reflect an influence of trait range limits rather than stronger environmental filtering. These findings challenge correlative trait-environment relationships and call for more explicitly identifying the mechanisms responsible of trait convergence/divergence along environmental gradients.

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Correction to: Hill-based dissimilarity indices and null models for analysis of microbial community assembly

Microbiome ◽

10.1186/s40168-020-00942-6 ◽

2020 ◽

Vol 8 (1) ◽

Author(s):

Oskar Modin ◽

Raquel Liébana ◽

Soroush Saheb-Alam ◽

Britt-Marie Wilén ◽

Carolina Suarez ◽

...

Keyword(s):

Microbial Community ◽

Community Assembly ◽

Null Models ◽

Microbial Community Assembly

An amendment to this paper has been published and can be accessed via the original article.

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Partitioning of functional diversity reveals the scale and extent of trait convergence and divergence

Journal of Vegetation Science ◽

10.1111/j.1654-1103.2009.01042.x ◽

2009 ◽

Vol 20 (3) ◽

pp. 475-486 ◽

Cited By ~ 170

Author(s):

Francesco de Bello ◽

Wilfried Thuiller ◽

Jan Lepš ◽

Philippe Choler ◽

Jean-Christophe Clément ◽

...

Keyword(s):

Functional Diversity ◽

Trait Convergence ◽

Convergence And Divergence

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Hill-based Dissimilarity Indices and Null Models for Analysis of Microbial Community Assembly

10.21203/rs.3.rs-33130/v1 ◽

2020 ◽

Author(s):

Oskar Modin ◽

Raquel Liebana ◽

Soroush Saheb-Alam ◽

Britt-Marie Wilén ◽

Carolina Suarez ◽

...

Keyword(s):

Microbial Community ◽

Microbial Communities ◽

Community Assembly ◽

Null Model ◽

Amplicon Sequencing ◽

Null Models ◽

Marker Genes ◽

Experimental Systems ◽

Microbial Community Assembly ◽

The Impact

Abstract Background: High-throughput amplicon sequencing of marker genes, such as the 16S rRNA gene in Bacteria and Archaea, provides a wealth of information about the composition of microbial communities. To quantify differences between samples and draw conclusions about factors affecting community assembly, dissimilarity indices are typically used. However, results are subject to several biases and data interpretation can be challenging. The Jaccard and Bray-Curtis indices, which are often used to quantify taxonomic dissimilarity, are not necessarily the most logical choices. Instead, we argue that Hill-based indices, which make it possible to systematically investigate the impact of relative abundance on dissimilarity, should be used for robust analysis of data. In combination with a null model, mechanisms of microbial community assembly can be analyzed. Here, we also introduce a new software, qdiv, which enables rapid calculations of Hill-based dissimilarity indices in combination with null models.Results: Using amplicon sequencing data from two experimental systems, aerobic granular sludge (AGS) reactors and microbial fuel cells (MFC), we show that the choice of dissimilarity index can have considerable impact on results and conclusions. High dissimilarity between replicates because of random sampling effects make incidence-based indices less suited for identifying differences between groups of samples. Determining a consensus table based on count tables generated with different bioinformatic pipelines reduced the number of low-abundant, potentially spurious amplicon sequence variants (ASVs) in the data sets, which led to lower dissimilarity between replicates. Analysis with a combination of Hill-based indices and a null model allowed us to show that different ecological mechanisms acted on different fractions of the microbial communities in the experimental systems.Conclusions: Hill-based indices provide a rational framework for analysis of dissimilarity between microbial community samples. In combination with a null model, the effects of deterministic and stochastic community assembly factors on taxa of different relative abundances can be systematically investigated. Calculations of Hill-based dissimilarity indices in combination with a null model can be done in qdiv, which is freely available as a Python package (https://github.com/omvatten/qdiv). In qdiv, a consensus table can also be determined from several count tables generated with different bioinformatic pipelines.

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Environmental Filtering Influences Functional Community Assembly of Epibenthic Communities

Frontiers in Marine Science ◽

10.3389/fmars.2021.736917 ◽

2021 ◽

Vol 8 ◽

Author(s):

Lauren Sutton ◽

Franz J. Mueter ◽

Bodil A. Bluhm ◽

Katrin Iken

Keyword(s):

Community Assembly ◽

Chukchi Sea ◽

Environmental Filtering ◽

Biotic Interactions ◽

Beaufort Sea ◽

Functional Trait ◽

Functional Community ◽

Trait Convergence ◽

High Trait ◽

Epibenthic Communities

Community assembly theory states that species assemble non-randomly as a result of dispersal limitation, biotic interactions, and environmental filtering. Strong environmental filtering likely leads to local assemblages that are similar in their functional trait composition (high trait convergence) while functional trait composition will be less similar (high trait divergence) under weaker environmental filters. We used two Arctic shelves as case studies to examine the relationship between functional community assembly and environmental filtering using the geographically close but functionally and environmentally dissimilar epibenthic communities on the Chukchi and Beaufort Sea shelves. Environmental drivers were compared to functional trait composition and to trait convergence within each shelf. Functional composition in the Chukchi Sea was more strongly correlated with environmental gradients compared to the Beaufort Sea, as shown by a combination of RLQ and fourth corner analyses and community-weighted mean redundancy analyses. In the Chukchi Sea, epibenthic functional composition, particularly body size, reproductive strategy, and several behavioral traits (i.e., feeding habit, living habit, movement), was most strongly related to gradients in percent mud and temperature while body size and larval development were most strongly related to a depth gradient in the Beaufort Sea. The stronger environmental filter in the Chukchi Sea also supported the hypothesized relationship with higher trait convergence, although this relationship was only evident at one end of the observed environmental gradient. Strong environmental filtering generally provides a challenge for biota and can be a barrier for invading species, a growing concern for the Chukchi Sea shelf communities under warming conditions. Weaker environmental filtering, such as on the Beaufort Sea shelf, generally leads to communities that are more structured by biotic interactions, and possibly representing partitioning of resources among species from intermediate disturbance levels. We provide evidence that environmental filtering can structure functional community composition, providing a baseline of how community function could be affected by stressors such as changes in environmental conditions or increased anthropogenic disturbance.

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