Growth and the expression of alternative life cycles in the salamander \u3ci\u3eAmbystoma talpoideum\u3c/i\u3e (Caudata: Ambystomatidae)

Complex life cycles (CLCs) contain larval and adult phases that are morphologically and ecologically distinct. Simple life cycles (SLCs) have evolved from CLCs repeatedly in a wide variety of lineages but the processes that may underlie the transition have rarely been identified or investigated experimentally. We examined the influence of larval growth rate on the facultative expression of alternative life cycles (metamorphosis or maturation as gill-bearing adults [= paedomorphosis]) in the salamander Ambystoma talpoideum. We manipulated growth rates by altering the amount of food individuals received throughout larval development. The expression of alternative life cycles in A. talpoideum is influenced by growth via food levels, but the same growth rates at different points in the larval period elicit different responses. Individuals were more likely to metamorphose (i.e. express a CLC) when food levels and growth rates were high later in development and more likely to mature without metamorphosing (SLC) when growth rates were comparatively low during the same point in development. Growth rates at particular points in development, rather than overall larval growth rate, may be an important proximate factor in salamander life-cycle evolution

When do young birds disperse? : Tests from studies of golden eagles in Scotland

Peer reviewedPublisher PD

tRNA functional signatures classify plastids as late-branching cyanobacteria.

BackgroundEukaryotes acquired the trait of oxygenic photosynthesis through endosymbiosis of the cyanobacterial progenitor of plastid organelles. Despite recent advances in the phylogenomics of Cyanobacteria, the phylogenetic root of plastids remains controversial. Although a single origin of plastids by endosymbiosis is broadly supported, recent phylogenomic studies are contradictory on whether plastids branch early or late within Cyanobacteria. One underlying cause may be poor fit of evolutionary models to complex phylogenomic data.ResultsUsing Posterior Predictive Analysis, we show that recently applied evolutionary models poorly fit three phylogenomic datasets curated from cyanobacteria and plastid genomes because of heterogeneities in both substitution processes across sites and of compositions across lineages. To circumvent these sources of bias, we developed CYANO-MLP, a machine learning algorithm that consistently and accurately phylogenetically classifies ("phyloclassifies") cyanobacterial genomes to their clade of origin based on bioinformatically predicted function-informative features in tRNA gene complements. Classification of cyanobacterial genomes with CYANO-MLP is accurate and robust to deletion of clades, unbalanced sampling, and compositional heterogeneity in input tRNA data. CYANO-MLP consistently classifies plastid genomes into a late-branching cyanobacterial sub-clade containing single-cell, starch-producing, nitrogen-fixing ecotypes, consistent with metabolic and gene transfer data.ConclusionsPhylogenomic data of cyanobacteria and plastids exhibit both site-process heterogeneities and compositional heterogeneities across lineages. These aspects of the data require careful modeling to avoid bias in phylogenomic estimation. Furthermore, we show that amino acid recoding strategies may be insufficient to mitigate bias from compositional heterogeneities. However, the combination of our novel tRNA-specific strategy with machine learning in CYANO-MLP appears robust to these sources of bias with high accuracy in phyloclassification of cyanobacterial genomes. CYANO-MLP consistently classifies plastids as late-branching Cyanobacteria, consistent with independent evidence from signature-based approaches and some previous phylogenetic studies

The speed of range shifts in fragmented landscapes

Peer reviewedPublisher PD

Pioneer Venus polarimetry and haze optical thickness

The Pioneer Venus mission provided us with high-resolution measurements at four wavelengths of the linear polarization of sunlight reflected by the Venus atmosphere. These measurements span the complete phase angle range and cover a period of more than a decade. A first analysis of these data by Kawabata et al. confirmed earlier suggestions of a haze layer above and partially mixed with the cloud layer. They found that the haze exhibits large spatial and temporal variations. The haze optical thickness at a wavelength of 365 nm was about 0.06 at low latitudes, but approximately 0.8 at latitudes from 55 deg poleward. Differences between morning and evening terminator have also been reported by the same authors. Using an existing cloud/haze model of Venus, we study the relationship between the haze optical thickness and the degree of linear polarization. Variations over the visible disk and phase angle dependence are investigated. For that purpose, exact multiple scattering computations are compared with Pioneer Venus measurements. To get an impression of the variations over the visible disk, we have first studied scans of the polarization parallel to the intensity equator. After investigating a small subset of the available data we have the following results. Adopting the haze particle characteristics given by Kawabata et al., we find a thickening of the haze at increasing latitudes. Further, we see a difference in haze optical thickness between the northern and southern hemispheres that is of the same order of magnitude as the longitudinal variation of haze thickness along a scan line. These effects are most pronounced at a wavelength of 935 nm. We must emphasize the tentative nature of the results, because there is still an enormous amount of data to be analyzed. We intend to combine further polarimetric research of Venus with constraints on the haze parameters imposed by physical and chemical processes in the atmosphere

STOCHASTIC WEALTH DYNAMICS AND RISK MANAGEMENT AMONG A POOR POPULATION

The literature on economic growth and development has focused considerable attention on questions of risk management and the possibility of multiple equilibria associated with poverty traps. We use herd history data collected among pastoralists in southern Ethiopia to study stochastic wealth dynamics among a very poor population. These data yield several novel findings. Although covariate rainfall shocks plainly matter, household-specific factors, including own herd size, account for most observed variability in wealth dynamics. Despite longstanding conventional wisdom about common property grazing lands, we find no statistical support for the tragedy of the commons hypothesis. It appears that past studies may have conflated costly self-insurance with stocking rate externalities. Such self-insurance is important in this setting because weak livestock markets and meager social insurance cause wealth to fluctuate largely in response to biophysical shocks. These shocks move households between multiple dynamic wealth equilibria toward which households converge following nonconvex path dynamics. The lowest equilibrium is consistent with the notion of a poverty trap. These findings have broad implications for the design of development and relief strategies among a poor population extraordinarily vulnerable to climatic shocks.common property, covariate risk, Ethiopia, idiosyncratic risk, poverty traps, social insurance, Risk and Uncertainty, O1, Q12,

Engineering stochasticity in gene expression

Stochastic fluctuations (noise) in gene expression can cause members of otherwise genetically identical populations to display drastically different phenotypes. An understanding of the sources of noise and the strategies cells employ to function reliably despite noise is proving to be increasingly important in describing the behavior of natural organisms and will be essential for the engineering of synthetic biological systems. Here we describe the design of synthetic constructs, termed ribosome competing RNAs (rcRNAs), as a means to rationally perturb noise in cellular gene expression. We find that noise in gene expression increases in a manner proportional to the ability of an rcRNA to compete for the cellular ribosome pool. We then demonstrate that operons significantly buffer noise between coexpressed genes in a natural cellular background and can even reduce the level of rcRNA enhanced noise. These results demonstrate that synthetic genetic constructs can significantly affect the noise profile of a living cell and, importantly, that operons are a facile genetic strategy for buffering against noise

Ethics and Deep Learning

This article appears as chapter 21 of Prince (2023, Understanding Deep Learning); a complete draft of the textbook is available here: http://udlbook.com. This chapter considers potential harms arising from the design and use of AI systems. These include algorithmic bias, lack of explainability, data privacy violations, militarization, fraud, and environmental concerns. The aim is not to provide advice on being more ethical. Instead, the goal is to express ideas and start conversations in key areas that have received attention in philosophy, political science, and the broader social sciences.Comment: Copyright in this Work has been licensed exclusively to The MIT Press, https://mitpress.mit.edu, which will be releasing the final version to the public in 2023. All inquiries regarding rights should be addressed to The MIT Press, Rights and Permissions Departmen

Synthetic control of a fitness tradeoff in yeast nitrogen metabolism

Background: Microbial communities are involved in many processes relevant to industrial and medical biotechnology, such as the formation of biofilms, lignocellulosic degradation, and hydrogen production. The manipulation of synthetic and natural microbial communities and their underlying ecological parameters, such as fitness, evolvability, and variation, is an increasingly important area of research for synthetic biology. Results: Here, we explored how synthetic control of an endogenous circuit can be used to regulate a tradeoff between fitness in resource abundant and resource limited environments in a population of Saccharomyces cerevisiae. We found that noise in the expression of a key enzyme in ammonia assimilation, Gdh1p, mediated a tradeoff between growth in low nitrogen environments and stress resistance in high ammonia environments. We implemented synthetic control of an endogenous Gdh1p regulatory network to construct an engineered strain in which the fitness of the population was tunable in response to an exogenously-added small molecule across a range of ammonia environments. Conclusion: The ability to tune fitness and biological tradeoffs will be important components of future efforts to engineer microbial communities