Category: Statistical methods

Methods papers, Statistical methods

State-and-Transition Models: An Interview with Marie-Josee Fortin

David Warton (University of New South Wales) interviews Marie-Josee Fortin (University of Toronto) about a recent article on state-and-transition models from her group in Methods in Ecology and Evolution. David and Marie-Josee also discuss what motivated her career to date in spatial ecology, and what she sees as the main advances in this area and current challenges in the field.

Continue reading “State-and-Transition Models: An Interview with Marie-Josee Fortin”

Unknown's avatarIndia Stephenson1 Comment
Methods papers, Online extras, Statistical methods, Virtual Issues

Statistical Ecology Virtual Issue

StatEcolVI_WebAdAt the last ISEC, in Montpellier in 2014, an informal survey suggested that Methods in Ecology and Evolution was the most cited journal in talks. This reflects the importance of statistical methods in ecology and it is one reason for the success of the journal. For this year’s International Statistcal Ecology Conference in Seattle we have produced a virtual issue that presents some of our best recent papers which cross the divide between statistics and ecology. They range over most of the topics covered at ISEC, from statistical theory to abundance estimation and distance sampling.

We hope that Methods in Ecology and Evolution will be equally well represented in talks in Seattle, and also – just as in Montpellier – some of the work presented will find its way into the pages of the journal in the future.

Without further ado though, here is a brief overview of the articles in our Statistical Ecology Virtual Issue: Continue reading “Statistical Ecology Virtual Issue”

Unknown's avatarIndia Stephenson1 Comment
Conservation and management, Methods papers, Statistical methods

Bringing Ecologists and Statisticians Together for the Conservation of Endangered Species

Post provided by Cecilia Pinto and Luigi Spezia

The Benefits of High Frequency Data

One of the tagged flapper skates showing the three different kinds of tags. ©Cecilia Pinto
One of the tagged flapper skates showing the three different kinds of tags. ©Cecilia Pinto

High frequency data, like those obtained from individual electronic tags, carries the potential of giving us detailed information on the behaviour of species at the individual level. Such data are particularly useful for marine species, as we can’t observe them directly for long periods of time.

Understanding how individuals use water columns – both at daily and seasonal scales – can help define conservation measures such as restricting fishing activity to reduce by-catch or defining protected areas to help recovering populations or protect spawning and nursery areas. High frequency data have become popular as they give insight to detailed individual foraging behaviour and therefore the specific energetic needs that are linked to reproduction and fitness. Continue reading “Bringing Ecologists and Statisticians Together for the Conservation of Endangered Species”

Unknown's avatarIndia StephensonLeave a comment
Methods papers, Statistical methods

My Entropy ‘Pearl’: Using Turing’s Insight to Find an Optimal Estimator for Shannon Entropy

Post provided by Anne Chao (National Tsing Hua University, Taiwan)

Shannon Entropy

Not quite as precious as my entropy pearl
Not quite as precious as my entropy pearl ©Amboo Who

Ludwig Boltzmann (1844-1906) introduced the modern formula for entropy in statistical mechanics in 1870s. Since its generalization by Claude E. Shannon in his pioneering 1948 paper A Mathematical Theory of Communication, this entropy became known as ‘Shannon entropy’.

Shannon entropy and its exponential have been extensively used to characterize uncertainty, diversity and information-related quantities in ecology, genetics, information theory, computer science and many other fields. Its mathematical expression is given in the figure below.

In the 1950s Shannon entropy was adopted by ecologists as a diversity measure. It’s interpreted as a measure of the uncertainty in the species identity of an individual randomly selected from a community. A higher degree of uncertainty means greater diversity in the community.

Unlike species richness which gives equal weight to all species, or the Gini-Simpson index that gives more weight to individuals of abundant species, Shannon entropy and its exponential (“the effective number of common species” or diversity of order one) are the only standard frequency-sensitive complexity measures that weigh species in proportion to their population abundances. To put it simply: it treats all individuals equally. This is the most natural weighing for many applications. Continue reading “My Entropy ‘Pearl’: Using Turing’s Insight to Find an Optimal Estimator for Shannon Entropy”

Unknown's avatarIndia Stephenson2 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
General, Meetings, Statistical methods

Statistics in Ecology and Environmental Monitoring: A Look Back at the SEEM 2015 Conference

Post provided by Dr Matt Schofield

Matt is an Associate Editor for Methods in Ecology and Evolution. He was the principle organiser of this year’s SEEM conference. His research interests include Bayesian inference and hierarchical modelling, computational methodology, ecological statistics and much more. Matt is based at the University of Otago.

A photo taken during a lunch break at the conference
A photo taken during a lunch break at the conference

The Statistics in Ecology and Environmental Monitoring (SEEM) conference was held in Queenstown, New Zealand on June 22-26, 2015. Queenstown is a resort town in the Southern Alps of New Zealand that looks out on Lake Wakatipu, surrounded by snow-capped mountains. The venue gave a chance to explore some of the natural beauty of New Zealand, with excursions to local ski fields, wineries and various hiking trails.

SEEM conferences have been organized by members of the Statistics group at the University of Otago since 1993. The first SEEM conference was held in Dunedin, New Zealand and conferences were then held regularly (every 3 years) until 2002. The last SEEM conference, in 2007, also served as the EURING (European Union for Bird Ringing) technical meeting. With nearly ten years passing since 2007, we had a smaller conference of around 50 attendees this year. There was an engaging atmosphere during the meeting and productive discussion followed each of the 40 talks. The SEEM 2015 meeting maintained the tradition of previous SEEM conferences with delegates from across a broad spectrum of statistical ecology coming together to discuss research. Continue reading “Statistics in Ecology and Environmental Monitoring: A Look Back at the SEEM 2015 Conference”

Unknown's avatarIndia StephensonLeave a comment
Meetings, Methods 5th, Statistical methods

Ten Top Tips for Reviewing Statistics: A Guide for Ecologists

post provided by Dr Mark Brewer.

Mark is a statistician with Biomathematics & Statistics Scotland, based in Aberdeen. His main statistical research interests are Species Distribution Modelling, Compositional Data Analysis, Bayesian Mixture Modelling and Bayesian Ordinal Regression. Mark 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, ‘Model Selection and the Cult of AIC’ here.

The level of statistical analysis in ecology journals is far higher than in most other disciplines. Ecological journals lead the way in the development of statistical methodology, necessitated by challenging practical problems involving complex data sets. As a statistician, publishing also in hydrology, soil science, social science and forensic science journals, I’ve found papers in those areas are much more likely to only use well-established methods than papers in ecology.

Here’s the big question though: why then do I have the most difficulty with ecological journals when it comes to statistical analyses? Let’s be clear here: when I say “difficulty”, I mean I receive reviews which are just plain wrong. Most statisticians I’ve spoken to who work in ecology have anecdotes from reviews which demonstrate a lack of understanding by the non-statistician reviewer (including the all-too-frequent “perhaps you should consult a statistician”). So, why the apparent disconnect?

The difference seems to be in how non-statisticians in different disciplines treat the statistics in a paper. In many subject areas, reviewers are almost deferential to the statistical analysis; in ecology, reviewers can be forthright in their condemnation, often without justification. Reviewers have every right to question the statistical analysis in a paper, but the authors have the exact same right to expect a high quality review from a genuine expert in the field. Has ecology become blasé about statistics? Continue reading “Ten Top Tips for Reviewing Statistics: A Guide for Ecologists”

Unknown's avatarIndia Stephenson21 Comments
Methods papers, Statistical methods

Traits, community ecology and demented accountants

McGill et al. (2006) argued that community ecology had lost its way. Shipley (2010) accused community ecologists of acting like a bunch of demented accountants. Strong words – so what’s the issue exactly?  And what can we do about it?

Dannymanic Image
Doing some end-of-financial-year field work? © Dannymanic

Their beef was that when studying groups of species and their environmental association, ecologists often were not thinking enough about the reasons for variation across species. (In this post we’ll focus on variation in abundance or in environmental response of abundance across species. We’re interpreting “abundance” loosely – counts, biomass, 1-0, whatever.)  While alternative methods are more readily available nowadays, “accountancy” is still common.

Continue reading “Traits, community ecology and demented accountants”

Unknown's avatardavidwarton4 Comments
Methods papers, Statistical methods

Understanding and Presenting YOUR Data

A Beginner’s Guide to Data Exploration and Visualisation with R
by Elena N. Ieno and Alain F. Zuur

A Beginner's Guide to Data ExplorationIn 2010 Alain Zuur, Elena Ieno and Chris Elphick published a paper in Methods in Ecology and Evolution entitled ‘A protocol for data exploration to avoid common statistical problems‘ (Volume 1, Issue 1). Little did they know at the time that this paper would become one of the journal’s all-time top downloaded and top cited papers, with a total of 22,472 downloads between 2010 and 2014.

Based on this success they decided to extend the material in the paper into a book.

Zuur and his colleagues at Highland Statistics ltd. give about 25 five-day statistics courses per year. Their typical audience consists of biological scientists at the post-graduate and post-doctoral levels. Early on in each course they have the following conversation with the participants:

Speaker: “Do you review submitted manuscripts for journals?”
Audience: “Yes.”
Speaker: “Do you like the statistical part of these manuscripts?”
Audience: “No!”
Speaker: “Do you understand the statistical part?”
Audience: “Not always.”

What if there were ways you could make reviewing your paper easier and more enjoyable for reviewers? What if making your manuscript easier to understand and nicer to read would increase the likelihood of your work being published?

A Beginner’s Guide to Data Exploration and Visualisation with R explains how you can do exactly that! Alain Zuur and Elena Ieno use ecological datasets to discuss the data exploration and visualisation tools you can use to make your paper simpler for readers and reviewers to understand. The authors also explain how to visualise the results of statistical models, an important aspect of scientific papers. Continue reading “Understanding and Presenting YOUR Data”

Unknown's avatarIndia StephensonLeave a comment
General, Journal updates, Methods papers, Online extras, Statistical methods

boral: R package for multivariate data analysis in Ecology

In this video Francis Hui introduces boral, a new R package he developed for Bayesian analysis of multivariate data in ecology. It uses Bayesian MCMC estimation to fit latent variable models for unconstrained ordination (read the MEE paper, Model-based approaches to unconstrained ordination, for details), and for multi-species inference while accounting for inter-species correlation: Download boral from CRAN Read the MEE paper Model-based approaches to … Continue reading boral: R package for multivariate data analysis in Ecology

Unknown's avatarSamantha Ponton1 Comment