A dynamical trichotomy for structured populations experiencing positive density-dependence in stochastic environments

Positive density-dependence occurs when individuals experience increased survivorship, growth, or reproduction with increased population densities. Mechanisms leading to these positive relationships include mate limitation, saturating predation risk, and cooperative breeding and foraging. Individuals within these populations may differ in age, size, or geographic location and thereby structure these populations. Here, I study structured population models accounting for positive density-dependence and environmental stochasticity i.e. random fluctuations in the demographic rates of the population. Under an accessibility assumption (roughly, stochastic fluctuations can lead to populations getting small and large), these models are shown to exhibit a dynamical trichotomy: (i) for all initial conditions, the population goes asymptotically extinct with probability one, (ii) for all positive initial conditions, the population persists and asymptotically exhibits unbounded growth, and (iii) for all positive initial conditions, there is a positive probability of asymptotic extinction and a complementary positive probability of unbounded growth. The main results are illustrated with applications to spatially structured populations with an Allee effect and age-structured populations experiencing mate limitation

Extremal measures maximizing functionals based on simplicial volumes

We consider functionals measuring the dispersion of a d-dimensional distribution which are based on the volumes of simplices of dimension k ≤ d formed by k + 1 independent copies and raised to some power δ. We study properties of extremal measures that maximize these functionals. In particular, for positive δ we characterize their support and for negative δ we establish connection with potential theory and motivate the application to space-filling design for computer experiments. Several illustrative examples are presented

The Molecular Clockwork of the Fire Ant Solenopsis invicta

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An ensemble indicator-based density estimator for evolutionary multi-objective optimization

International audienceEnsemble learning is one of the most employed methods in machine learning. Its main ground is the construction of stronger mechanisms based on the combination of elementary ones. In this paper, we employ AdaBoost, which is one of the most well-known ensemble methods, to generate an ensemble indicator-based density estimator for multi-objective optimization. It combines the search properties of five density estimators, based on the hypervolume, R2, IGD+, ε+, and ∆p quality indicators. Through the multi-objective evolutionary search process, the proposed ensemble mechanism adapts itself using a learning process that takes the preferences of the underlying quality indicators into account. The proposed method gives rise to the ensemble indicator-based multi-objective evolutionary algorithm (EIB-MOEA) that shows a robust performance on different multi-objective optimization problems when compared with respect to several existing indicator-based multi-objective evolutionary algorithms

Towards Uniform Online Spherical Tessellations

The problem of uniformly placing N points onto a sphere finds applications in many areas. An online version of this problem was recently studied with respect to the gap ratio as a measure of uniformity. The proposed online algorithm of Chen et al. was upper-bounded by 5.99 and then improved to 3.69, which is achieved by considering a circumscribed dodecahedron followed by a recursive decomposition of each face. We analyse a simple tessellation technique based on the regular icosahedron, which decreases the upper-bound for the online version of this problem to around 2.84. Moreover, we show that the lower bound for the gap ratio of placing up to three points is 1+5√2≈1.618 . The uniform distribution of points on a sphere also corresponds to uniform distribution of unit quaternions which represent rotations in 3D space and has numerous applications in many areas

Chimpanzees overcome the tragedy of the commons with dominance

Competition over common-pool resources (CPR) is a ubiquitous challenge for social animals. Many species face similar dilemmas, yet our understanding of the evolutionary trajectory of CPR social strategies remains unexplored. Here, we provide a first look at the social strategies of our closest living relatives, chimpanzees (Pan troglodytes), in two novel resource dilemma experiments. Dyads of chimpanzees were presented with renewable resource systems, collapsible at a quantity-dependent threshold. Dyads had to continuously resist overconsumption to maximize collective gains. In study 1, dyads of chimpanzees sustained a renewing juice source. Inequality of juice acquisition between partners predicted sustaining success, indicating that one individual dominated the task while the partner inhibited. Dyads in study 2 fed together on accumulating carrot pieces but could end the accumulation any time by grabbing an immediate selfish source of carrots. Dyads with low tolerance were more successful at collectively sustaining the resource than highly tolerant dyads. Further, the dominant individual was more likely to cause collapse in dyads with low tolerance than dyads with high tolerance. These results indicate that chimpanzees use a dominance-based monopolisation strategy moderated by social tolerance to overcome the tragedy of the commons

MicroRNA Expression Is Down-Regulated and Reorganized in Prefrontal Cortex of Depressed Suicide Subjects

<div><h3>Background</h3><p>Recent studies suggest that alterations in expression of genes, including those which regulate neural and structural plasticity, may be crucial in the pathogenesis of depression. MicroRNAs (miRNAs) are newly discovered regulators of gene expression that have recently been implicated in a variety of human diseases, including neuropsychiatric diseases.</p> <h3>Methodology/Principal Findings</h3><p>The present study was undertaken to examine whether the miRNA network is altered in the brain of depressed suicide subjects. Expression of miRNAs was measured in prefrontal cortex (Brodmann Area 9) of antidepressant-free depressed suicide (n = 18) and well-matched non-psychiatric control subjects (n = 17) using multiplex RT-PCR plates. We found that overall miRNA expression was significantly and globally down-regulated in prefrontal cortex of depressed suicide subjects. Using individual tests of statistical significance, 21 miRNAs were significantly decreased at p = 0.05 or better. Many of the down-regulated miRNAs were encoded at nearby chromosomal loci, shared motifs within the 5′-seeds, and shared putative mRNA targets, several of which have been implicated in depression. In addition, a set of 29 miRNAs, whose expression was not pairwise correlated in the normal controls, showed a high degree of co-regulation across individuals in the depressed suicide group.</p> <h3>Conclusions/Significance</h3><p>The findings show widespread changes in miRNA expression that are likely to participate in pathogenesis of major depression and/or suicide. Further studies are needed to identify whether the miRNA changes lead to altered expression of prefrontal cortex mRNAs, either directly (by acting as miRNA targets) or indirectly (e.g., by affecting transcription factors).</p> </div