Alessandro Filazzola & Christopher Lortie tell us about their new article ‘A call for clean code to effectively communicate science‘, which provides a series of recommendations and a suite of tools that can be used to help support scientists to produce cleaner code. Can you clearly understand the code that you have written? What about if you gave it to a colleague? Or a reviewer? … Continue reading How to write clean code
Post provided by Martin Beal, Steffen Oppel, Jonathan Handley, Richard Phillips, Paulo Catry, and Maria Dias.
Identifying areas around the world that can best contribute to the conservation of wild animals is a major challenge. Historically, this required conducting extensive surveys in the field, but with the advent of miniature tracking technology we can now follow animals and allow them to indicate which areas they depend on most. In this collaborative post, international researchers from ISPA – Instituto Universitário in Lisbon, the Royal Society for the Protection of Birds, BirdLife International, and British Antarctic Survey present a new conservation tool as outlined in the paper “track2KBA: An R package for identifying important sites for biodiversity from tracking data” recently published in Methods in Ecology and Evolution.
Continue reading “A new tool to identify important sites for conservation using tracking data”
Post provided by: Salvador Herrando-Pérez
If you use genetics to differentiate populations, the new package smartsnp might be your new best friend. Written in R language and available from GitHub and CRAN, this package performs principal component analysis with control for genetic drift, projects ancient samples onto modern genetic space, and tests for population differences in genotypes. The package can load big datasets and run complex stats in the blink of an eye.
In this post, Salvador Herrando-Pérez discusses the features of this new package which is fully described in the new paper “smartsnp, an R package for fast multivariate analyses of big genomic data” recently published in Methods in Ecology & Evolution.
Continue reading “Smart genetic analysis made fast and easy”
Midori Yajima graduated from an MSc in Ecology with a project on palaeoecology and decided to join the online workshop Data Manipulation and Statistical Analysis in Palaeoecology: A Masterclass in R, set up by the Palaeoecology Special Interest Group (PalaeoSIG). In this post, Midori discusses some highlights from the workshop and emphasises the importance of a research community when navigating the programming realm.
Continue reading “Data manipulation and statistical analysis in palaeoecology: an unexpected journey”Earlier this year, the BES Movement Ecology Special Interest Group held a competition to find the best animal movement maps in four categories: ‘pretty’, ‘nerdy’, ‘dynamic’ and ‘RMap’ (for maps produced entirely using R).
The results of the vote are in, and the winner of the RMap Category is Pratik Gupte from the University of Groningen, who used R to create this beautiful map of elephant movements across thermal landscapes. Here, we asked Pratik for the story behind the elephant map.
Continue reading “Mapping Animal Movement in R: The Science and the Art”
To celebrate the 10th Anniversary of the launch of Methods in Ecology and Evolution, we are highlighting an article from each volume to feature in the Methods.blog. For Volume 8, we have selected ‘ggtree: an r package for visualization and annotation of phylogenetic trees with their covariates and other associated data‘ by Yu et al. (2016).
In this post, the authors share their inspiration behind the ggtree package for R and present new resources of ggtree and a series of other related packages.
The team publishing the ggtree paper is working in the field of emerging infectious diseases. Particularly the corresponding author Tommy Lam (TL) has been advocating the integration of different biological and epidemiological information in the studies of fast-evolving viral pathogens. The lead author Guangchuang Yu (GY) joined The University of Hong Kong to pursue his doctorate degree under the supervision of TL and Yi Guan (co-author in the paper), as he was very curious about the application of genomics and phylogenetics in the study of emerging infectious diseases.
Continue reading “10th Anniversary Volume 8: Phylogenetic tree visualization with multivariate data”Ignasi Bartomeus and colleagues share the story behind their recent Methods article ‘cxr: A toolbox for modelling species coexistence in R’.
This post recalls the journey on how we ended up developing cxr (acronym for CoeXistence relationships in R), an R package for quantifying interactions among species and their coexistence relationships. In other words, it provides tools for telling apart the situations in which different species can persist together in a community from the cases in which one species completely overcomes another.
Continue reading “Creating a package to infer species coexistence”
This post is available in English
مدلسازی توزیع گونهها به تخمین و برآورد ارتباط بین مجموعهای از نقاط حضور گونه با متغیرهای زیستمحیطی مرتبط می پردازد. یکی از مراحل اساسی این فرایند، ارزیابی قدرت مدل برای پیشبینی مکانهایی است که احتمال حضورگونه در آنجا وجود دارد. این کار اغلب با ارزیابی پیشبینی انجام شده در مجموعهای ازنقاط که در فرآیند مدلسازی مورد استفاده قرار نگرفته اند (نقاط آزمایشی) صورت میگیرد.
مطالعات پیشین بر این نکته تاکید دارند که به منظور ارزیابی معتبر، نقاط آزمایشی باید مستقل از نقاط آموزشی باشند، این درحالیست که داده مستقل واقعی به ندرت در دسترس می باشد. به همین دلیل، در فرایند مدلسازی معمولا دادههای موجود را به دو قسمت دادههای آموزشی (برای کالیبره کردن مدل) و داده های آزمایشی (برای ارزیابی دقت مدل) تقسیم میکنند، این استراتژی میتواند چند قسمتی هم باشد (برای مثال اعتبارسنجی متقاطع یا cross-validation). از آنجاییکه این تقسیم بندی معمولا بصورت تصادفی انجام میشود، بنابراین گاهی اوقات نقاط آزمایشی در فواصل نزدیک به نقاط آموزشی قرار میگیرند. شکل زیر این مساله را به خوبی نشان می دهد که در آن نقاط آزمایشی به رنگ قرمز و نقاط آموزشی آبی هستند. اما آیا این مساله میتواند مشکلی ایجاد کند؟ Continue reading “اعتبارسنجی متقاطع مکانی در مدلسازی توزیع گونهها”
The Robert May Prize is awarded annually for the best paper published in Methods in Ecology and Evolution by an Early Career Researcher. We’re delighted to announce that the 2017 winner is Jonathan Henshaw, for his article ‘A unified measure of linear and nonlinear selection on quantitative traits‘.
The standard approach to quantifying natural selection, developed by Lande and Arnold, does not allow for comparable metrics between linear (i.e. selection on the mean phenotype) and nonlinear (i.e. selection on all other aspects of the phenotypic distribution, including variance and the number of modes) selection gradients. Jonathan Henshaw’s winning submission provides the first integrated measure of the strength of selection that applies across qualitatively different selection regimes (e.g. directional, stabilizing or disruptive selection). Continue reading “2017 Robert May Prize Winner: Jonathan Henshaw”
The Robert May Prize is awarded annually for the best paper published in Methods in Ecology and Evolution by an Early Career Researcher. We’re delighted to announce that the 2016 winner is Gabriella Leighton, for her article ‘Just Google it: assessing the use of Google Images to describe geographical variation in visible traits of organisms‘.
‘Just Google it’ marks an important step in converting ecology to an armchair science. Many species (e.g. owls, hawks, bears) are difficult, time-consuming, expensive and even dangerous to observe. It would be a lot easier if we didn’t have to spend time, energy and risk lives having to observe organisms in the field! Continue reading “2016 Robert May Prize Winner: Gabriella Leighton”
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