Policy on Publishing Code: Encouraging Good Practice to Ensure Quality

Following on from our sponsorship of the Guide to Reproducible Code in Ecology and Evolution and our collaboration with rOpenSci, we have now released a new policy on publishing code. The main objective of this policy is to make sure that high quality code is readily available to our readers.

We’ve set out four key principles to help achieve this, as well as explaining what code outputs we publish, giving some examples of things that make it easier to review code, and giving some advice on how to store code once it’s been published. Below is a summary of some highlights of the policy, but you can find it in full on the Methods in Ecology and Evolution website. Continue reading

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A Guide to Reproducible Code in Ecology and Evolution

Post provided by Natalie Cooper and Pen-Yuan Hsing

Cover image by David J. Bird

The way we do science is changing — data are getting bigger, analyses are getting more complex, and governments, funding agencies and the scientific method itself demand more transparency and accountability in research. One way to deal with these changes is to make our research more reproducible, especially our code.

Although most of us now write code to perform our analyses, it’s often not very reproducible. We’ve all come back to a piece of work we haven’t looked at for a while and had no idea what our code was doing or which of the many “final_analysis” scripts truly was the final analysis! Unfortunately, the number of tools for reproducibility and all the jargon can leave new users feeling overwhelmed, with no idea how to start making their code more reproducible. So, we’ve put together the Guide to Reproducible Code in Ecology and Evolution to help. Continue reading

Making Your Research Reproducible with R

Post provided by Laura Graham

tweetReproducible research is important for three main reasons. Firstly, it makes it much easier to revisit a project a few months down the line, for example when making revisions to a paper which has been through peer review.

Secondly, it allows the reader of a published article to scrutinise your results more easily – meaning it is easier to show their validity. For this reason, some journals and reviewers are starting to ask authors to provide their code.

Thirdly, having clean and reproducible code available can encourage greater uptake of new methods. It’s much easier for users to replicate, apply and improve on methods if the code is reproducible and widely available

Throughout my PhD and Postdoctoral research, I have aimed to ensure that I use a reproducible workflow and this generally saves me time and helps to avoid errors. Along the way I’ve learned a lot through the advice of others, and trial and error. In this post I have set out a guide to creating a reproducible workflow and provided some useful tips. Continue reading

Achieving Reproducibility in Research

Earlier this month Leila Walker attended a panel discussion imparting ‘Practical Tips for Reproducible Research’, as part of the Annual Meeting of the Macroecology Special Interest Group (for an overview of the meeting as a whole check out this Storify). The session and subsequent drinks reception was sponsored by Methods in Ecology and Evolution. Here, Leila reports back on the advice offered by the panel members.

For anyone interested in viewing further resources from the session, please see here. Also, you may like to consider attending the best practice for code archiving workshop at the 2016 BES Annual Meeting. Do you have any tips for making your research reproducible? Comment on this post or email us and let us know!

This year’s Annual Meeting of the Macroecology SIG was the biggest yet, with around 75 attendees and even representation across the PhD, post-doc and faculty spectrum. The panel discussion aimed to consider what reproducibility means to different people, identify the reproducibility issues people struggle with, and ultimately provide practical tips and tools for how to achieve reproducible research. Each of the participants delivered a short piece offering their perspective on reproducibility, with plenty of opportunity for discussion during the session itself and in the poster and wine reception that followed.

Attendees enjoy a wine reception (sponsored by MEE) whilst viewing posters and reflecting on the Reproducible Research panel discussion. Photo credit: Leila Walker

Attendees enjoy a wine reception (sponsored by MEE) whilst viewing posters and reflecting on the Reproducible Research panel discussion. Photo credit: Leila Walker

Continue reading

New Associate Editors

Today we are welcoming three new Associate Editors to Methods in Ecology and Evolution: Nick Golding (University of Melbourne, Australia), Rachel McCrea (University of Kent, UK) and Francesca Parrini (University of the Witwatersrand, South Africa). They have all joined on a three-year term and you can find out more about them below.

Nick Golding

Nick Golding

Nick Golding

“I develop statistical models and software for mapping the distributions of species and diseases. I’m particularly interested in tools that make it easy for researchers to add more mechanistic structure into their correlative models (and vice versa) so that they can use all available information when making predictions. I also develop software and other tools to bring research communities together and help them advance ecology by enabling and incentivising reproducible and extensible research.”

Nick has recently had an article published in Methods in Ecology and Evolution (currently in Early View). In ‘Fast and flexible Bayesian species distribution modelling using Gaussian processes‘ Nick and his co-author (Bethan Purse) introduce Gaussian process (GP) models and their application to species distribution modelling (SDM), illustrate how ecological knowledge can be incorporated into GP SDMs via Bayesian priors and formulate a simple GP SDM that can be fitted efficiently. The article is Open Access, so it’s freely available to everyone.

Rachel McCrea

Rachel McCrea

Rachel McCrea

“I am a NERC research fellow and lecturer in statistics at the University of Kent.  My particular areas of interest include capture-recapture modelling, multistate models, modelling population dynamics and methods of model assessment.  My research is motivated by interesting discussions with ecologists and I strive to find innovative, but practical statistical solutions to ecological questions.”

Rachel is one of the authors of Analysis of Capture-Recapture Data (along with Byron Morgan). The book covers the many modern developments of capture-recapture (and related) methods and will be of interest to researchers and graduate students in statistics, ecology and demography. It contains 130 exercises designed to complement and extend the text and help readers to assimilate the material.

Francesca Parrini

Francesca Parrini

Francesca Parrini

“My broad research interests lie in the ecology and behaviour of mammalian herbivores, their interaction with biotic and abiotic factors and the integration of factors governing decisions at the small foraging scale and factors governing decisions at the landscape level. As such, my research lies at the interface of remote sensing, behavioural ecology and conservation. Recently I have become interested in the application of graph theory and network analysis to ecological settings, in particular to study the spatio-temporal structure of animal movement patterns.”

Last year Francesca had her article (co-authored with Maria Miranda) ‘Congruence between species phylogenetic and trophic distinctiveness‘ published in Biodiversity and Conservation. In this paper the authors investigate the relationship between species’ phylogenetic history and patterns of resource use. They show that there is congruence between species phylogenetics and interaction distinctiveness and propose that this relationship could provide a possible novel approach to the conservation of ecosystem diversity.

We are thrilled to welcome Nick, Rachel and Francesca to the Associate Editor Board and we look forward to working with them over the coming years.

Towards a More Reproducible Ecology

The following post has been provided by Dr Nick Isaac.

Nick is organising the OpenData and Reproducibility Workshop at Charles Darwin House, London on 21 April 2015 (more information below). He is also an Associate Editor for Methods in Ecology and Evolution.

Macro_finalThe open science movement has been a major force for change in how research is conducted and communicated. Reproducibility lies at the heart of the open science agenda. It’s a broad topic, covering how data are shared, interpreted and reported.

Reproducibility has been advanced by a coalition of publishers (who have been embarrassed by a series of high-profile retractions), funding agencies keen that data should be re-useable after the life of a grant, and young researchers taking a more collaborative attitude than previous generations.

There is now a vast range of tools and platforms to help scientists share data and other materials (e.g. Dryad, Github, Figshare) and to create efficient and reproducible workflows (e.g. Sweave, Markdown, Git and, of course, R). There’s even a MOOC (Massive Open Online Course) in Reproducible Research, run out of Johns Hopkins University.

Ecology has lagged behind wet-lab biology and other disciplines in the adoption of reproducibility concepts and there are few examples of ecological studies that are truly reproducible. To address this, we’re running a one-day workshop at Charles Darwin House, London on Tuesday 21 April entitled OpenData & Reproducibility Workshop: the Good Scientist in the Open Science era. Continue reading