Month: November 2015

Methods 5th, Publishing Tips & Tricks

A Quickstart Guide for Building Your First R Package

Post Provided By DR IAIN STOTT

Iain is a Postdoctoral Researcher at the Max Planck Institute for Demographic Research and the MaxO Center at the University of Southern Denmark. He is currently working as a part of MaxNetAging, a Research Network on Aging. Iain was one of the presenters at the UK half of the Methods in Ecology and Evolution 5th Anniversary Symposium in April. You can watch his talk, ‘Methods Put to Good Use: Advances in population ecology through studies of transient demography’ here.

If you’re anything like me, you might experience a minor existential crisis weekly. As scientists we question the world around us and, for me, this questioning turns all-too-often inwards to my career. I don’t think that’s unusual: ask any scientist about their ‘Plan B’, and the extent to which it’s thought through is often astonishing (if a café-cum-cocktail bar ever opens in Glasgow’s West End, which specialises in drinks that employ spice blends from around the world and are named after old spice trade routes and trading vessels, then you know I’ve jumped the science ship).

Contributing open-source software is something which has made my work feel a bit more relevant and helped me feel a bit less of an imposter. I’ll explain why that is, give some tips to beginners for building a first R package, and hopefully persuade other (especially early-career) researchers to do the same. Continue reading “A Quickstart Guide for Building Your First R Package”

Unknown's avatarIndia Stephenson4 Comments
Publishing Tips & Tricks

When to Identify Non-Preferred Reviewers

©Nic McPhee
©Nic McPhee

Last month we published a blog post with some tips on selecting preferred reviewers for your manuscript. It was hugely popular (if you haven’t read it yet you can do so here), so we have decided to follow it up with some advice on identifying NON-preferred reviewers (or Author Opposed Reviewers as they are now known on ScholarOne).

Unlike preferred reviewers, you are not required to identify non-preferred reviewers when you submit your paper to Methods. However, in certain cases this option is can be very useful for your manuscript. It is important not to overuse or misuse this feature of the submission system though and the below tips will help you to avoid doing this.

The Golden Rule: Always Explain Why!

It can often be difficult to decide whether to identify someone as an author opposed reviewer. While there are some guidelines that journals can (and do) offer, a lot of the time authors find themselves in the grey area between these. We understand that it is unlikely that every question you have will be answered by our guidance (although we hope that we can address at least a few of them), but there is a way around this: explain why you have made a person a non-preferred reviewer. Continue reading “When to Identify Non-Preferred Reviewers”

Unknown's avatarIndia Stephenson3 Comments
Meetings, Statistical methods, Uncategorized

There’s Madness in our Methods: Improving inference in ecology and evolution

Post provided by JARROD HADFIELD

Last week the Center for Open Science held a meeting with the aim of improving inference in ecology and evolution. The organisers (Tim Parker, Jessica Gurevitch & Shinichi Nakagawa) brought together the Editors-in-chief of many journals to try to build a consensus on how improvements could be made. I was brought in due to my interest in statistics and type I errors – be warned, my summary of the meeting is unlikely to be 100% objective.

True Positives and False Positives

The majority of findings in psychology and cancer biology cannot be replicated in repeat experiments. As evolutionary ecologists we might be tempted to dismiss this because psychology is often seen as a “soft science” that lacks rigour and cancer biologists are competitive and unscrupulous. Luckily, we as evolutionary biologists and ecologists have that perfect blend of intellect and integrity. This argument is wrong for an obvious reason and a not so obvious reason.

We tend to concentrate on significant findings, and with good reason: a true positive is usually more informative than a true negative. However, of all the published positives what fraction are true positives rather than false positives? The knee-jerk response to this question is 95%. However, the probability of a false positive (the significance threshold, alpha) is usually set to 0.05, and the probability of a true positive (the power, beta) in ecological studies is generally less than 0.5 for moderate sized effects. The probability that a published positive is true is therefore 0.5/(0.5+0.05) =91%. Not so bad. But, this assumes that the hypotheses and the null hypothesis are equally likely. If that were true, rejecting the null would give us very little information about the world (a single bit actually) and is unlikely to be published in a widely read journal. A hypothesis that had a plausibility of 1 in 25 prior to testing would, if true, be more informative, but then the true positive rate would be down to (1/25)*0.5/((1/25)*0.5+(24/25)*0.05) =29%. So we can see that high false positive rates aren’t always the result of sloppiness or misplaced ambition, but an inevitable consequence of doing interesting science with a rather lenient significance threshold. Continue reading “There’s Madness in our Methods: Improving inference in ecology and evolution”

Unknown's avatarIndia Stephenson5 Comments
Methods papers, Practical Tools

Why Accurate Stable Isotope Discrimination Factors are so Important: A cautionary tale (involving kea)

Post provided by AMANDA GREER

Stable isotopes as a tool for ecologists

Our research into the foraging ecology of this cheeky parrot (kea: Nestor notabilis) prompted us to develop a simple method to establish discrimination factors © Andruis Pašukonis
Our research into the foraging ecology of this cheeky parrot (kea: Nestor notabilis) prompted us to develop a simple method to establish discrimination factors © Andruis Pašukonis

Isotopes are atoms that have the same number of protons and electrons but differ in their number of neutrons; they are lighter and heavier forms of the same element. Unlike radioactive isotopes, stable isotopes do not decay over time.

The ratio of heavy to light stable carbon (δ13C) and nitrogen (δ15N) isotopes in an animal’s tissues depend on its diet, although offset by a certain amount. This integration of δ13C and δ15N from an animal’s diet into its tissues allows ecologists to use stable isotope analysis to investigate a species’ present and historical diets, food-web structures, niche shifts,  migration patterns and more.   Continue reading “Why Accurate Stable Isotope Discrimination Factors are so Important: A cautionary tale (involving kea)”

Unknown's avatarIndia Stephenson2 Comments
Journal updates

Issue 6.11

Issue 6.11 is now online!

The November issue of Methods is now online!

This month’s issue contains two Applications articles and one Open Access article, all of which are freely available.

– mvMORPH: A package of multivariate phylogenetic comparative methods for the R statistical environment which allows fitting a range of multivariate evolutionary models under a maximum-likelihood criterion. Its use can be extended to any biological data set with one or multiple covarying continuous traits.

– Low-cost soil CO2 efflux and point concentration sensing systems: The authors use commercially available, low-cost and low-power non-dispersive infrared (NDIR) CO2 sensors to develop a soil CO2 efflux system and a point CO2 concentration system. Their methods enable terrestrial ecologists to substantially improve the characterization of CO2 fluxes and concentrations in heterogeneous environments.

This month’s Open Access article comes from Jolyon Troscianko and Martin Stevens. In ‘Image calibration and analysis toolbox – a free software suite for objectively measuring reflectance, colour and pattern‘ they introduce a toolbox that can convert images to correspond to the visual system (cone-catch values) of a wide range of animals, enabling human and non-human visual systems to be modelled. The toolbox is freely available as an addition to the open source ImageJ software and will considerably enhance the appropriate use of digital cameras across multiple areas of biology. In particular, researchers aiming to quantify animal and plant visual signals will find this useful. This article received some media attention upon Early View publication over the summer. You can read the Press Release about it here.

Our November issue also features articles on Population Genetics, Macroevolution, Modelling species turnover, Abundance modelling, Measuring stress and much more. Continue reading “Issue 6.11”

Unknown's avatarIndia StephensonLeave a comment