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Register a new userAverage Sequence dissimilarity under simple multi-species coalescent
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Joseph Heled
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We show how to analytically derive the average sequence dissimilarity (ASD) within and between species under a simplified multi-species coalescent setup.
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We introduce a new Wright-Fisher type model for seed banks incorporating simultaneous switching, which is motivated by recent work on microbial dormancy. We show that the simultaneous switching mechanism leads to a new jump-diffusion limit for the scaled frequency processes, extending the classical Wright-Fisher and seed bank diffusion limits. We further establish a new dual coalescent structure with multiple activation and deactivation events of lineages. While this seems reminiscent of multiple merger events in general exchangeable coalescents, it actually leads to an entirely new class of coalescent processes with unique qualitative and quantitative behaviour. To illustrate this, we provide a novel kind of condition for coming down from infinity for these coalescents using recent results of Griffiths.
Mediterranean ecosystems such as those found in California, Central Chile, Southern Europe, and Southwest Australia host numerous, diverse, fire-adapted micro-ecosystems. These micro-ecosystems are as diverse as mountainous conifer to desert-like chaparral communities. Over the last few centuries, human intervention, invasive species, and climate warming have drastically affected the composition and health of Mediterranean ecosystems on almost every continent. Increased fuel load from fire suppression policies and the continued range expansion of non-native insects and plants, some driven by long-term drought, produced the deadliest wildfire season on record in 2018. As a consequence of these fires, a large number of structures are destroyed, releasing household chemicals into the environment as uncontrolled toxins. The mobilization of these materials can lead to health risks and disruption in both human and natural systems. This article identifies drivers that led to a structural weakening of the mosaic of fire-adapted ecosystems in California, and subsequently increased the risk of destructive and explosive wildfires throughout the state. Under a new climate regime, managing the impacts on systems moving out-of-phase with natural processes may protect lives and ensure the stability of ecosystem services.
Computational inference of dated evolutionary histories relies upon various hypotheses about RNA, DNA, and protein sequence mutation rates. Using mutation rates to infer these dated histories is referred to as molecular clock assumption. Coalescent theory is a popular class of evolutionary models that implements the molecular clock hypothesis to facilitate computational inference of dated phylogenies. Cancer and virus evolution are two areas where these methods are particularly important. Methodologically, phylogenetic inference methods require a tree space over which the inference is performed, and geometry of this space plays an important role in statistical and computational aspects of tree inference algorithms. It has recently been shown that molecular clock, and hence coalescent, trees possess a unique geometry, different from that of classical phylogenetic tree spaces which do not model mutation rates. Here we introduce and study a space of discrete coalescent trees, that is, we assume that time is discrete, which is inevitable in many computational formalisations. We establish several geometrical properties of the space and show how these properties impact various algorithms used in phylogenetic analyses. Our tree space is a discretisation of a known time tree space, called t-space, and hence our results can be used to approximate solutions to various open problems in t-space. Our tree space is also a generalisation of another known trees space, called the ranked nearest neighbour interchange space, hence our advances in this paper imply new and generalise existing results about ranked trees.
Existing sequence alignment algorithms use heuristic scoring schemes which cannot be used as objective distance metrics. Therefore one relies on measures like the p- or log-det distances, or makes explicit, and often simplistic, assumptions about sequence evolution. Information theory provides an alternative, in the form of mutual information (MI) which is, in principle, an objective and model independent similarity measure. MI can be estimated by concatenating and zipping sequences, yielding thereby the normalized compression distance. So far this has produced promising results, but with uncontrolled errors. We describe a simple approach to get robust estimates of MI from global pairwise alignments. Using standard alignment algorithms, this gives for animal mitochondrial DNA estimates that are strikingly close to estimates obtained from the alignment free methods mentioned above. Our main result uses algorithmic (Kolmogorov) information theory, but we show that similar results can also be obtained from Shannon theory. Due to the fact that it is not additive, normalized compression distance is not an optimal metric for phylogenetics, but we propose a simple modification that overcomes the issue of additivity. We test sever
Niche and neutral theory are two prevailing, yet much debated, ideas in ecology proposed to explain the patterns of biodiversity. Whereas niche theory emphasizes selective differences between species and interspecific interactions in shaping the community, neutral theory supposes functional equivalence between species and points to stochasticity as the primary driver of ecological dynamics. In this work, we draw a bridge between these two opposing theories. Starting from a Lotka-Volterra (LV) model with demographic noise and random symmetric interactions, we analytically derive the stationary population statistics and species abundance distribution (SAD). Using these results, we demonstrate that the model can exhibit three classes of SADs commonly found in niche and neutral theories and found conditions that allow an ecosystem to transition between these various regimes. Thus, we reconcile how neutral-like statistics may arise from a diverse community with niche differentiation.
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