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1. For everything there is a season: Analysing periodic mortality patterns with the cyclomort r package

   https://doi.org/10.1111/2041-210X.13305  

   Gurarie, Eliezer; Thompson, Peter R.; Kelly, Allicia P.; Larter, Nicholas C.; Fagan, William F.; Joly, Kyle; Graham, ed., Laura (October 2019, Methods in Ecology and Evolution)

   Abstract Many important demographic processes are seasonal, including survival. For many species, mortality risk is significantly higher at certain times of the year than at others, whether because resources are scarce, susceptibility to predators or disease is high, or both. Despite the importance of survival modelling in wildlife sciences, no tools are available to estimate the peak, duration and relative importance of these ‘seasons of mortality’.We presentcyclomort, anrpackage that estimates the timing, duration and intensity of any number of mortality seasons with reliable confidence intervals. The package includes a model selection approach to determine the number of mortality seasons and to test whether seasons of mortality vary across discrete grouping factors.We illustrate the periodic hazard function model and workflow of cyclomort with simulated data. We then estimate mortality seasons of two caribouRangifer taranduspopulations that have strikingly different mortality patterns, including different numbers and timing of mortality peaks, and a marked change in one population over time.Thecyclomortpackage was developed to estimate mortality seasons for wildlife, but the package can model any time‐to‐event processes with a periodic component. 

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2. geomorph v4.0 and gmShiny: Enhanced analytics and a new graphical interface for a comprehensive morphometric experience

   https://doi.org/10.1111/2041-210X.13723  

   Baken, Erica K.; Collyer, Michael L.; Kaliontzopoulou, Antigoni; Adams, Dean C. (September 2021, Methods in Ecology and Evolution)

   Abstract Geometric morphometric (GM) tools are essential for meaningfully quantifying and understanding patterns of variation in complex traits like shape. In this field, the breadth of answerable questions has grown dramatically in recent years through the development of new analyses and increased computational efficiency.In this note, we describe the ways in whichgeomorph, a widely usedRpackage for quantifying and analysing GM data, has grown with the field.We presentgeomorph v4.0and describe the ways in which this version has dramatically improved upon previous versions. We also present a new graphical user interface for easy implementation,gmShiny.These contributions positiongeomorphto be the primary tool for GM analyses, particularly those employing a phylogenetic comparative approach. 

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3. SiPhyNetwork : An R package for simulating phylogenetic networks

   https://doi.org/10.1111/2041-210X.14116  

   Justison, Joshua A.; Solis‐Lemus, Claudia; Heath, Tracy A. (May 2023, Methods in Ecology and Evolution)

   Abstract Gene flow is increasingly recognized as an important macroevolutionary process. The many mechanisms that contribute to gene flow (e.g. introgression, hybridization, lateral gene transfer) uniquely affect the diversification of dynamics of species, making it important to be able to account for these idiosyncrasies when constructing phylogenetic models. Existing phylogenetic‐network simulators for macroevolution are limited in the ways they model gene flow.We presentSiPhyNetwork, an R package for simulating phylogenetic networks under a birth–death‐hybridization process.Our package unifies the existing birth–death‐hybridization models while also extending the toolkit for modelling gene flow. This tool can create patterns of reticulation such as hybridization, lateral gene transfer, and introgression.Specifically, we model different reticulate events by allowing events to either add, remove or keep constant the number of lineages. Additionally, we allow reticulation events to be trait dependent, creating the ability to model the expanse of isolating mechanisms that prevent gene flow. This tool makes it possible for researchers to model many of the complex biological factors associated with gene flow in a phylogenetic context. 

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4. popler: An r package for extraction and synthesis of population time series from the long‐term ecological research (LTER) network

   https://doi.org/10.1111/2041-210X.13319  

   Compagnoni, Aldo; Bibian, Andrew J.; Ochocki, Brad M.; Levin, Sam; Zhu, Kai; Miller, Tom E. X.; Ellison, ed., Aaron (November 2019, Methods in Ecology and Evolution)

   Abstract Population dynamics play a central role in the historical and current development of fundamental and applied ecological science. The nascent culture of open data promises to increase the value of population dynamics studies to the field of ecology. However, synthesis of population data is constrained by the difficulty in identifying relevant datasets, by the heterogeneity of available data and by access to raw (as opposed to aggregated or derived) observations.To obviate these issues, we built a relational database,popler, and itsRclient, the library popler.popleraccommodates the vast majority of population data under a common structure, and without the need for aggregating raw observations. The popler R library is designed for users unfamiliar with the structure of the database and with the SQL language. ThisRlibrary allows users to identify, download, explore and cite datasets salient to their needs.We implemented popler as a PostgreSQL instance, where we stored population data originated by the United States Long Term Ecological Research (LTER) Network. Our focus on the US LTER data aims to leverage the potential of this vast open data resource. The database currently contains 305 datasets from 25 LTER sites.popleris designed to accommodate automatic updates of existing datasets, and to accommodate additional datasets from LTER as well as non‐LTER studies.The combination of the online database and theRlibrary popler is a resource for data synthesis efforts in population ecology. The common structure ofpoplersimplifies comparative analyses, and the availability of raw data confers flexibility in data analysis. The popler R library maximizes these opportunities by providing a user‐friendly interface to the online database. 

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5. Convergent evolution of root system architecture in two independently evolved lineages of weedy rice

   https://doi.org/10.1111/nph.15791  

   Wedger, Marshall J.; Topp, Christopher N.; Olsen, Kenneth M. (April 2019, New Phytologist)

   Summary Root system architecture (RSA) is a critical aspect of plant growth and competitive ability. Here we used two independently evolved strains of weedy rice, a de‐domesticated form of rice, to study the evolution of weed‐associatedRSAtraits and the extent to which they evolve through shared or different genetic mechanisms.We characterised 98 two‐dimensional and three‐dimensionalRSAtraits in 671 plants representing parents and descendants of two recombinant inbred line populations derived from two weed × crop crosses. A random forest machine learning model was used to assess the degree to which root traits can predict genotype and the most diagnostic traits for doing so. We used quantitative trait locus (QTL)mapping to compare genetic architecture between the weed strains.The two weeds were distinguishable from the crop in similar and predictable ways, suggesting independent evolution of a ‘weedy’RSAphenotype. Notably, comparativeQTLmapping revealed little evidence for shared underlying genetic mechanisms.Our findings suggest that despite the double bottlenecks of domestication and de‐domestication, weedy rice nonetheless shows genetic flexibility in the repeated evolution of weedyRSAtraits. Whereas the root growth of cultivated rice may facilitate interactions among neighbouring plants, the weedy rice phenotype may minimise below‐ground contact as a competitive strategy. 

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