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1. Rapid growth and defence evolution following multiple introductions

   https://doi.org/10.1002/ece3.5275  

   van Boheemen, Lotte A. ; Bou‐Assi, Sarah ; Uesugi, Akane ; Hodgins, Kathryn A. ( June 2019 , Ecology and Evolution)

   Rapid adaptation can aid invasive populations in their competitive success. Resource allocation trade‐off hypotheses predict higher resource availability or the lack of natural enemies in introduced ranges allow for increased growth and reproduction, thus contributing to invasive success. Evidence for such hypotheses is however equivocal and tests among multiple ranges over productivity gradients are required to provide a better understanding of the general applicability of these theories.

   Using common gardens, we investigated the adaptive divergence of various constitutive and inducible defence‐related traits between the native North American and introduced European and Australian ranges, while controlling for divergence due to latitudinal trait clines, individual resource budgets, and population differentiation, using >11,000 SNPs.

   Rapid, repeated clinal adaptation in defence‐related traits was apparent despite distinct demographic histories. We also identified divergence among ranges in some defence‐related traits, although differences in energy budgets among ranges may explain some, but not all, defence‐related trait divergence. We do not identify a general reduction in defence in concert with an increase in growth among the multiple introduced ranges as predicted trade‐off hypotheses.

   Synthesis: The rapid spread of invasive species is affected by a multitude of factors, likely including adaptation to climate and escape from natural enemies. Unravelling the mechanisms underlying invasives' success enhances understanding of eco‐evolutionary theory and is essential to inform management strategies in the face of ongoing climate change.

   This article has been awarded Open Materials, Open Data, Preregistered Research Designs Badges. All materials and data are publicly accessible via the Open Science Framework athttps://doi.org/10.6084/m9.figshare.8028875.v1,https://github.com/lotteanna/defence_adaptation,https://doi.org/10.1101/435271.

    

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2. Spatial and ontogenetic variance in local densities modify selection on demographic traits

   https://doi.org/10.1111/1365-2435.14335  

   Mutz, Jessie ; Inouye, Brian D. ( April 2023 , Functional Ecology)

   Local density can affect individual performance by altering the strength of species interactions. Within many populations, local densities vary spatially (individuals are patchily distributed) or change across life stages, which should influence the selection and eco‐evolutionary feedback because local density variance affects mean fitness and is affected by traits of individuals. However, most studies on the evolutionary consequences of density‐dependent interactions focus on populations where local densities are relatively constant through time and space.

   We investigated the influence of spatial and ontogenetic variance in local densities within an insect population by comparing a model integrating both types of local density variance with models including only spatial variance, only ontogenetic variance, or no variance. We parameterized the models with experimental data, then used elasticity and invasion analyses to characterize selection on traits that affect either the local density an individual experiences (mean clutch size) or individuals' sensitivity to density (effect of larval crowding on pupal mass).

   Spatial and ontogenetic variance reduced population elasticity to effects of local density by 76% and 34% on average, respectively.

   Spatial variance modified selection and adaptive dynamics by altering the tradeoff between density‐dependent and density‐independent vital rates. In models including spatial variance, strategies that maximized density‐dependent survival were favoured over fecundity‐maximizing strategies even at low population density, counter to predictions of density‐dependent selection theory. Furthermore, only models that included spatial variance, thus linking the scales of oviposition and density‐dependent larval survival, had an evolutionarily stable clutch size.

   Ontogenetic variance weakened selection on mean clutch size and sensitivity to larval crowding by disrupting the relationship between trait values and performance during critical life stages.

   We demonstrate that local density variance can strongly modify selection at empirically observed interaction strengths and identify mechanisms for the effects of spatial and ontogenetic variance. Our findings reveal the potential for local density variance to mediate eco‐evolutionary feedback by shaping selection on demographically important traits.

   Read the freePlain Language Summaryfor this article on the Journal blog.

    

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3. The Locations of Features in the Mass Distribution of Merging Binary Black Holes Are Robust against Uncertainties in the Metallicity-dependent Cosmic Star Formation History

   https://doi.org/10.3847/1538-4357/acbf51  

   van Son, L. A. C. ; de Mink, S. E. ; Chruślińska, M. ; Conroy, C. ; Pakmor, R. ; Hernquist, L. ( May 2023 , The Astrophysical Journal)

   New observational facilities are probing astrophysical transients such as stellar explosions and gravitational-wave sources at ever-increasing redshifts, while also revealing new features in source property distributions. To interpret these observations, we need to compare them to predictions from stellar population models. Such models require the metallicity-dependent cosmic star formation history ($\mathit{}(Z,z)$) as an input. Large uncertainties remain in the shape and evolution of this function. In this work, we propose a simple analytical function for$\mathit{}(Z,z)$. Variations of this function can be easily interpreted because the parameters link to its shape in an intuitive way. We fit our analytical function to the star-forming gas of the cosmological TNG100 simulation and find that it is able to capture the main behavior well. As an example application, we investigate the effect of systematic variations in the$\mathit{}(Z,z)$parameters on the predicted mass distribution of locally merging binary black holes. Our main findings are that (i) the locations of features are remarkably robust against variations in the metallicity-dependent cosmic star formation history, and (ii) the low-mass end is least affected by these variations. This is promising as it increases our chances of constraining the physics that govern the formation of these objects (https://github.com/LiekeVanSon/SFRD_fit/tree/7348a1ad0d2ed6b78c70d5100fb3cd2515493f02/).

    

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4. MetaboDirect: an analytical pipeline for the processing of FT-ICR MS-based metabolomic data

   https://doi.org/10.1186/s40168-023-01476-3  

   Ayala-Ortiz, Christian ; Graf-Grachet, Nathalia ; Freire-Zapata, Viviana ; Fudyma, Jane ; Hildebrand, Gina ; AminiTabrizi, Roya ; Howard-Varona, Cristina ; Corilo, Yuri E. ; Hess, Nancy ; Duhaime, Melissa B. ; et al ( February 2023 , Microbiome)

   Microbiomes are now recognized as the main drivers of ecosystem function ranging from the oceans and soils to humans and bioreactors. However, a grand challenge in microbiome science is to characterize and quantify the chemical currencies of organic matter (i.e., metabolites) that microbes respond to and alter. Critical to this has been the development of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), which has drastically increased molecular characterization of complex organic matter samples, but challenges users with hundreds of millions of data points where readily available, user-friendly, and customizable software tools are lacking.

   Here, we build on years of analytical experience with diverse sample types to develop MetaboDirect, an open-source, command-line-based pipeline for the analysis (e.g., chemodiversity analysis, multivariate statistics), visualization (e.g., Van Krevelen diagrams, elemental and molecular class composition plots), and presentation of direct injection high-resolution FT-ICR MS data sets after molecular formula assignment has been performed. When compared to other available FT-ICR MS software, MetaboDirect is superior in that it requires a single line of code to launch a fully automated framework for the generation and visualization of a wide range of plots, with minimal coding experience required. Among the tools evaluated, MetaboDirect is also uniquely able to automatically generate biochemical transformation networks (ab initio) based on mass differences (mass difference network-based approach) that provide an experimental assessment of metabolite connections within a given sample or a complex metabolic system, thereby providing important information about the nature of the samples and the set of microbial reactions or pathways that gave rise to them. Finally, for more experienced users, MetaboDirect allows users to customize plots, outputs, and analyses.

   Application of MetaboDirect to FT-ICR MS-based metabolomic data sets from a marine phage-bacterial infection experiment and aSphagnumleachate microbiome incubation experiment showcase the exploration capabilities of the pipeline that will enable the research community to evaluate and interpret their data in greater depth and in less time. It will further advance our knowledge of how microbial communities influence and are influenced by the chemical makeup of the surrounding system. The source code and User’s guide of MetaboDirect are freely available through (https://github.com/Coayala/MetaboDirect) and (https://metabodirect.readthedocs.io/en/latest/), respectively.

    

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5. Fast and efficient Rmap assembly using the Bi-labelled de Bruijn graph

   https://doi.org/10.1186/s13015-021-00182-9  

   Mukherjee, Kingshuk ; Rossi, Massimiliano ; Salmela, Leena ; Boucher, Christina ( May 2021 , Algorithms for Molecular Biology)

   Genome wide optical maps are high resolution restriction maps that give a unique numeric representation to a genome. They are produced by assembling hundreds of thousands of single molecule optical maps, which are called Rmaps. Unfortunately, there are very few choices for assembling Rmap data. There exists only one publicly-available non-proprietary method for assembly and one proprietary software that is available via an executable. Furthermore, the publicly-available method, by Valouev et al. (Proc Natl Acad Sci USA 103(43):15770–15775, 2006), follows the overlap-layout-consensus (OLC) paradigm, and therefore, is unable to scale for relatively large genomes. The algorithm behind the proprietary method, Bionano Genomics’ Solve, is largely unknown. In this paper, we extend the definition of bi-labels in the paired de Bruijn graph to the context of optical mapping data, and present the first de Bruijn graph based method for Rmap assembly. We implement our approach, which we refer to asrmapper, and compare its performance against the assembler of Valouev et al. (Proc Natl Acad Sci USA 103(43):15770–15775, 2006) and Solve by Bionano Genomics on data from three genomes:E. coli, human, and climbing perch fish (Anabas Testudineus). Our method was able to successfully run on all three genomes. The method of Valouev et al. (Proc Natl Acad Sci USA 103(43):15770–15775, 2006) only successfully ran onE. coli. Moreover, on the human genomermapperwas at least 130 times faster than Bionano Solve, used five times less memory and produced the highest genome fraction with zero mis-assemblies. Our software,rmapperis written in C++ and is publicly available under GNU General Public License athttps://github.com/kingufl/Rmapper.

    

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