Stop, think, and beware of default options

Post provided by Paula Pappalardo (with contributions from Elizabeth Hamman, Jim Bence, Bruce Hungate & Craig Osenberg)

Esta publicación también está disponible en español.

You spent months carefully collecting data from articles addressing your favorite scientific question, you have dozens of articles neatly arranged on a spreadsheet, you found software or code to analyze the data, and then daydream about how your publication will be the most cited in your field while making cool plots. If that sounds familiar, you have probably done a meta-analysis. Meta-analysis uses statistical models to combine data from different publications to answer a specific question.

What you may not have realized when going down the meta-analysis rabbit hole, is that small, seemingly inconsequential, choices can greatly affect your results. If you want to know about one of them lurking behind the scenes… read on!

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Para, piensa, y ten cuidado con las configuraciones por defecto

Post escrito por Paula Pappalardo (con aportes de Elizabeth Hamman, Jim Bence, Bruce Hungate & Craig Osenberg)

This post is also available in English.

Pasaste meses laboriosamente colectando datos de artículos científicos acerca de tu pregunta favorita, tienes decenas de artículos perfectamente organizados en una base de datos, ya encontraste el programa o código para analizar los datos, y entonces imaginas como tu publicación va a ser la más citada en tu campo de investigación mientras haces unos gráficos lindísimos. Si esto te suena familiar, seguramente has hecho un meta-análisis. Un meta-análisis usa modelos estadísticos para combinar datos de distintas publicaciones para responder a una pregunta específica.

Lo que quizás no te diste cuenta mientras navegabas los pasos del meta-análisis, es que pequeñas decisiones (a veces pareciendo de muy poca importancia) pueden tener grandes efectos en los resultados. Si quieres saber más acerca de una de estas decisiones en particular… ¡sigue leyendo!

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Speeding Up Systematic Reviews: This New Method for Automated Keyword Selection Will Save You Time

Post provided by ELIZA GRAMES

The number of studies published every year in ecology and evolutionary biology has increased rapidly over the past few decades. Each new study contributes more to what we know about a topic, adding nuance and complexity that helps improve our understanding of the natural world. To make sense of this wealth of evidence and get closer to a complete picture of the world, researchers are increasingly turning to systematic review methods as a way to synthesise this information.

What is a Systematic Review?

Systematic reviews, first developed in public health fields, take an experimental design approach to reviewing the literature. They treat the search for primary studies as a transparent and reproducible data gathering process. The rigorous methods used in systematic reviews make them a trusted form of evidence synthesis. Researchers use them to summarise the state of knowledge on a topic and make policy and practice recommendations. Continue reading

Using Experimental Methodology to Determine Grassland Response to Climate Change

Post provided by Heather Hager

©Hajnal Kovacs

In the second chapter of Grasslands and Climate ChangeMethodology I: Detecting and predicting grassland changeJonathan Newman and I take an in-depth look at the experimental methodology that has been used to determine how grassland ecosystems will respond to climate change. When we set out, we were interested in knowing, for example, the magnitudes and types of treatments applied, plot sizes, replication, study durations, and types of response variables that were measured and by how many studies. For simplicity(!), we focused on three treatment types: changes in atmospheric carbon dioxide levels, changes in temperature (mean, minimum, maximum), and changes in precipitation (increases, decreases, timing).

Using the methods of a formal systematic review, we identified 841 relevant studies, for which we extracted information on study location and experimental methodology. There were some surprises, both good and bad. For instance, mean and median plot sizes were actually larger than we had expected. On the other hand, numbers of true experimental replicates were low. Although many of the study methods were well reported, some areas lacked critical detail such as descriptions of (at least) the dominant plant species in the study area.

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The Future of Solar Geolocation Tracking is NOW

Post provided by Julia Karagicheva, Theunis Piersma and Eldar Rakhimberdiev

Black-tailed godwit with leg-mounted solar geolocator. ©Jan van de Kam

Black-tailed godwit with leg-mounted solar geolocator. ©Jan van de Kam

Working on FLightR, the package for analysis of data obtained from solar geolocation tracking devices, we were haunted by the unpleasant feeling of investing in technology which will soon be out of date. Until now solar geolocators have been popular in ornithological studies. This is because they’re small, light-weight (< 1/3 g) tracking devices that can be deployed even on miniature birds, such as swallows and warblers. They’ve also been the longest-lasting data loggers, with the most storage space and, of course, the most affordable ones.

Are Solar Geolocators Finished?

There are apparent drawbacks of using this technique though. To begin with, solar geolocation simply does not work for some species. You can’t use it to study birds living in dense tropical forests or in cavities, because of the light-pattern bias. For the same reason, it doesn’t provide fantastic results in light-polluted areas. Data from geolocators cannot be retrieved remotely, and this is why you need to have high recapture rates for the species you’re studying.   Continue reading

Editor Recommendation: The Ecologist’s Field Guide to Sequence-Based Identification of Biodiversity

Post provided by Pierre M Durand

A fossilized species of the diatom Thalassiosira. B. A species of the dinoflagellate Prorocentrum. Image provided by A. Ndhlovu).

A fossilized species of the diatom Thalassiosira. B. A species of the dinoflagellate Prorocentrum. (Image provided by A. Ndhlovu).

As any reader of Methods in Ecology and Evolution will know, advances in technologies and methodologies used by ecologists and evolutionary biologists are never-ending. Coupled with the tendency for researchers to become ever more specialised, this means that keeping up to date with all the advances is challenging at best. Occasionally, new advances revolutionise the kinds of questions we ask and encourage us to develop new approaches to answer them. One of these huge advances emerged from the ‘-omics’ revolution.

The application of -omics methodologies to evolution and ecology has been particularly rapid. These technologies usually aren’t part of the basic science education in these fields – it’s more usual for computational biologists to cross over to ecology and evolution than the other way around. The review by Simon Creer and colleagues ’The ecologist’s field guide to sequence-based identification of biodiversity’ helps bridge this gap. It’s not too technical, but sufficiently detailed, and it provides a very handy overview of how genomics, transcriptomics and their meta-analyses can be applied to evolutionary ecology. The paper is filled with enormously helpful workflows, pointers, examples and, as the title suggests, is a guide for those who are not experts in sequence based technologies. Continue reading

Meta-Analysis: How to Increase the Reach of Your Research and Make it Longer Lasting

Post provided by Katharina Gerstner

Like each coral, every single primary research study contributes to the larger picture.  © Wise Hok Wai Lum

Like each coral, every single primary research study contributes to the larger picture. © Wise Hok Wai Lum

Quantitative syntheses of primary research studies (meta-analysis) are being used more and more in ecological and evolutionary research. So knowing the basics of how meta-analysis works is important for every researcher. Meta-analytical thinking also encourages us scientists to see each single primary research study as a substantial contribution to a larger picture.

To be included in a meta-analysis, relevant primary research studies must be easy to find and basic information about the methods and results must be thoroughly, clearly and transparently reported. Moreover, papers with accessible data are the most useful for meta-analyses. Many published papers provide this information, but it’s not unusual for essential data to be omitted. Studies that are missing these details can’t be used in meta-analyses, which limits their reach. Continue reading

Issue 8.8

Issue 8.8 is now online!

The August issue of Methods is now online!

This issue contains two Applications articles and two Open Access articles. These four papers are freely available to everyone, no subscription required.

 Paco: An R package that assesses the phylogenetic congruence, or evolutionary dependence, of two groups of interacting species using both ecological interaction networks and their phylogenetic history.

 Open MEE: Open Meta-analyst for Ecology and Evolution (Open MEE) addresses the need for advanced, easy-to-use software for meta-analysis and meta-regression.It offers a suite of advanced meta-analysis and meta-regression methods for synthesizing continuous and categorical data, including meta-regression with multiple covariates and their interactions, phylogenetic analyses, and simple missing data imputation.

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Issue 8.6: How to Measure Natural Selection

Issue 8.6 is now online!

The April issue of Methods, which includes our latest Special Feature – ‘How to Measure Natural Selection – is now online!

Understanding how and why some individuals survive and reproduce better than others, the traits that allow them to do so, the genetic basis of those traits, and the signatures of past and present selection in patterns of variation in the genome remain at the top of the research agenda for evolutionary biology. This Special Feature – Guest Edited by Jeff Conner, John Stinchcombe and Joanna Kelley – draws together a collection of seven papers that highlight new methodological and conceptual approaches to meeting this agenda.

Three of the ‘How to Measure Natural Selection’ papers – Franklin and Morrissey, Thomson and Hadfield, and Hadfield and Thomson – clarify unresolved aspects of the literature in meaningful and important ways. Following on from this Hermisson and Pennings; Lotterhos et al.; and Villanueva‐Cañas et al. tackle the genomic results of evolution by natural selection: namely, how we can detect natural selection from genomic data? Finally, Wadgymar et al. address the issue of how much we know about the underlying loci or agents of selection.

To use the Editors’ own words, the articles in this issue “deal with how we can detect selection in a way that can be used to predict evolutionary responses, how selection affects the genome, and how selection and genetics underlie adaptive differentiation.”

All of the articles in the ‘How to Measure Natural Selection‘ Special Feature will be freely available for a limited time.
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Issue 7.3

Issue 7.3 is now online!

The March issue of Methods is now online!

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

METAGEAR: A comprehensive, multifunctional toolbox with capabilities aimed to cover much of the research synthesis taxonomy: from applying a systematic review approach to objectively assemble and screen the literature, to extracting data from studies, and to finally summarize and analyse these data with the statistics of meta-analysis.

Universal FQA Calculator: A free, open-source web-based Floristic Quality Assessment (FQA) Calculator. The calculator offers 30 FQA data bases (with more being added regularly) from across the United States and Canada and has been used to calculate thousands of assessments. Its growing repository for site inventory and transect data is accessible via a REST API and represents a valuable resource for data on the occurrence and abundance of plant species. Continue reading