Using Experimental Methodology to Determine Grassland Response to Climate Change

Posted on April 1, 2019 by Chris Grieves

Post provided by Heather Hager

©Hajnal Kovacs

In the second chapter of Grasslands and Climate Change – Methodology I: Detecting and predicting grassland change – Jonathan 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.

Continue reading →

The Future of Solar Geolocation Tracking is NOW

Posted on June 12, 2018 by Chris Grieves

Post provided by Julia Karagicheva, Theunis Piersma and Eldar Rakhimberdiev

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geolocation tracking devices, we were haunted by the unpleasant feeling of investing in technology which will soon be out of date.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

Posted on May 17, 2018 by Chris Grieves

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).

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

Posted on April 9, 2018 by Chris Grieves

Post provided by Katharina Gerstner

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

Posted on August 4, 2017 by Chris Grieves

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.

Continue reading →

Issue 8.6: How to Measure Natural Selection

Posted on June 8, 2017 by Chris Grieves

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.
Continue reading →

Issue 7.3

Posted on March 31, 2016 by Chris Grieves

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 →

A new tool based on microbial interactions to analyze bipartite networks

Posted on September 14, 2015 by Chris Grieves

Below is a press release about the Methods paper ‘BiMat: a MATLAB package to facilitate the analysis of bipartite networks‘ taken from the Pompeu Fabra University.

The Georgia Institute of Technology has created, together with the Pompeu Fabra University and the University of Canterbury, a new open-access and open-source tool for the study of bipartite networks

The team led by Joshua S. Weitz, Associate Professor at the School of Biology from the Georgia Institute of Technology, has developed BiMat: an open source MATLAB® package for the study of the structure of bipartite ecological networks inspired by real problems in microbiology and with broader applications. Cesar O. Flores, researcher at the School of Physics of the same institute, describes this new tool in an article published in the journal Methods in Ecology and Evolution. Sergi Valverde, Visiting Professor at the Complex Systems Lab from the Pompeu Fabra University, and Timothée Poisot, from the School of Biological Sciences of the University of Canterbury, are involved in the project. Continue reading →

Detecting effects of predators on prey: the method matters

Posted on May 19, 2010 by robfreck

In a paper published online today in Methods in Ecology and Evolution, Malcolm Nicoll and Ken Norris look at a controversial issue, that of detecting effects of predators on bird populations. This is controversial because some predators, especially raptors, were formerly rather scarce, but have become more abundant in recent years – in the case of raptors because organochloride chemicals are not used any more. At the same time mammal predators have also increased in numbers. This has led to suggestions that increases in predators may be a contributory factor to declines in some groups of birds, such as farmland birds, and there has been a great deal of discussion and debate over the issue.

Unfortunately this is a hypothesis that is not very easily addressed, unsurprising given the spatial and temporal scales that may be involved. Experimental approachs would be the ‘gold standard’, but these are difficult. Gradients of predator abundance have to be created by means of barriers or removal, which is expensive, logistically challenging and potentially expensive.

More usually opportunistic, observational evidence has to be relied upon. For example, this might take the form of statistically comparing populations in birds in areas with high numbers of predators with those with low numbers of predators. Whilst more practicable, such studies can suffer from the possibility of confounding: if a third ‘hidden’ variable also varies between sites, then this could generate problems for the interpretation.

The previous literature has presented mixed results: some studies have demonstrated effects of predators on prey populations, others have not. Whether this variation has an ecological basis is not clear.

In this new study, Nicoll & Norris re-evaluate previous observational studies by means of meta-analysis. They look at the effects of the quality of data and the number of predator species studied on the outcome of analyses. Importantly they find that the probability of detecting an effect depends on both the quality of data and the number of predators studied.

There are several implications of this work. Studies with poor quality data and that include small numbers of predators cannot reliably tell whether there are effects of predators or not, they are simply inconclusive. Nicoll & Norris go as far as to say that one should be skeptical about any short-term observational study that reports no effects of predators. They also suggest that the combined effects of predators are likely to be more important than that of any single predator, and that future studies should account for this.

Finally this study highlights the importance of methods in ecology: one cannot interpret evidence unless the method used is shown to be reliable and fit for purpose. Nicoll & Norris’ study is a good example of how re-evaluation of methods can help improve ecological understanding.

Phylogenetic comparative methods

Posted on November 20, 2009 by robfreck

Phylogenetic comparative methods are always an area of hot discussion and lots of methodological development. So I thought it would be useful to highlight some recent papers that have developed new methods in the past year. Please email me or leave a comment if there is anything I have omitted or if something new comes out.

Thomas Hansen and colleagues have introduced a new method for studying adaptation using comparative methods. Their approach is a generalisation of the Ornstein-Uhlenbeck model that allows for adaptive constraints and phylogenetic intertia. They have an R-package SLOUCH which can be used to fit the model.

In Evolution Liam Revell has developed a new approach for data reduction and size correction using phylogenetic approaches – this is often done wrongly as the transformation is commonly applied before phylogenetic analysis, however it should be correctly done at the same time.

A new method in Functional Ecology allows one to test for phylogenetic dependence in complex multivariate data that also incorporate measurement error.

What will prove, I think, to be a very popular method is a new approach for testing for phylogenetic signal and analysing correlates of binary traits, basically a phylogenetic logistic regression by Anthony Ives and Ted Garland. The approach will allow linear modelling of correlates of a binary traits, which has been difficult before.

In a related area, another very important development is in the analysis of speciation and extinction rates when these are affected by a binary trait. FitzJohn et al. have shown how the BiSSE model, developed to do this, can be applied when phylogenies are incompletely resolved.

Likely to be of interest to many using comparative methods is a paper by Richard Smith on the use and misuse of Reduced Major Axis line fitting. He discusses the assumptions of this method, which are not widely appreciated.

In the American Naturalist Marc Lajeunesse has developed methods linking comparative analysis and meta-analysis, basically allowing meta-analysis to be corrected for phylogenetic non-independence.

In Proc B a new method for integrating spatial and phylogenetic dependence has been presented, and in JEB there has been a review of the ‘deadly sins of comparative analysis’ (apologies for self-promotion!).

Just to end with here is another method for explaining adaptation.

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