Biology subjects

Andersen, T.

Publications and source records attributed to Andersen, T..

3 recordsLinked to original sources

bioRxiv2021

The effect of periodic disturbances and carrying capacity on the significance of selection and drift in complex bacterial communities

Understanding how periodical disturbances affect the community assembly processes is vital for predicting temporal dynamics in microbial communities. The effect of dilutions as disturbances are poorly understood. We used a marine bacterial community to investigate the effect of disturbance (+/-) and carrying capacity (high/low) over 50 days in a dispersal-limited 2x2 factorial crossover study in triplicates. The communitys disturbance regime was crossed halfway. We modelled the rate of change in community composition between replicates and used this rate to quantify selection and ecological drift. The disturbed communities increased in Bray-Curtis similarity with 0.011{+/-}0.0045 (Period 1) and 0.0092{+/-}0.0080 day-1 (Period 2), indicating that selection dominated community assembly. The undisturbed communities decreased in similarity at a rate of -0.015{+/-}0.0038 day-1 in Period 1 and were stable in Period 2 at 0.00050{+/-}0.0040 day-1, suggesting drift structured community assembly. Interestingly, carrying capacity had minor effects on community dynamics. This study is the first to show that stochastic effects are suppressed by periodical disturbances resulting in exponential growth periods due to density-independent biomass loss and resource input. The increased contribution of selection as a response to disturbances implies that ecosystem prediction is achievable.

ecology↗

bioRxiv2021

Neural networks and extreme gradient boosting predict multiple thresholds and trajectories of microbial biodiversity responses due to browning

Ecological association studies often assume monotonicity such as between biodiversity and environmental properties although there is growing evidence that non-monotonic relations dominate in nature. Here we apply machine learning algorithms to reveal the non-monotonic association between microbial diversity and an anthropogenic induced large scale change, the browning of freshwaters, along a longitudinal gradient covering 70 boreal lakes in Scandinavia. Measures of bacterial richness and evenness (alpha diversity) showed non-monotonic trends in relation to environmental gradients, peaking at intermediate levels of browning. Depending on the statistical methods, variables indicative for browning could explain 5% of the variance in bacterial community composition (beta diversity) when applying standard methods assuming monotonic relations and up to 45 % with machine learning methods (i.e. extreme gradient boosting and feed-forward neural networks) taking non-monotonicity into account. This non-monotonicity observed at the community level was explained by the complex interchangeable nature of individual taxa responses as shown by a high degree of non-monotonic responses of individual bacterial sequence variants to browning. Furthermore, the non-monotonic models provide the position of thresholds and predict alternative bacterial diversity trajectories in boreal freshwater as a result of ongoing climate and land use changes, which in turn will affect entire ecosystem metabolism and likely greenhouse gas production.

microbiology↗

bioRxiv2020

Evaluating geographic variation within molecular operational taxonomic units (OTUs) using network analyses in Scandinavian lakes

Operational taxonomic units (OTUs) are usually treated as if they are internally uniform in environmental metabarcoding studies of microbial and macrobial eukaryotes, even when the OTUs are being used to infer biogeographic patterns. The OTUs constructed by the program Swarm have underlying network topologies in which nodes represent amplicons and edges represent 1 nucleotide differences between nodes. Such networks can be exploited to search for biogeographic patterns within each OTU. To do this, here we used an available protistan metabarcoding dataset consisting of the hypervariable V4 region of the 18S rRNA locus amplified from 77 lakes collected across Norway and Sweden. The 82 most abundant and wide-spread OTUs constructed by Swarm were evaluated using shortest path, assortativity, and geographical analyses. We found that while pairs of amplicons from the same lake were usually connected directly to each other within the OTUs, these pairs of amplicons from the same lake did not form assortative clusters within the OTUs, and amplicons were not more connected with other amplicons occurring in neighboring lakes than expected by chance. This new approach to looking at within-OTU is applicable to other metabarcoding datasets and we provide code to perform these analyses.

microbiology↗