How Can We Quantify the Strength of Migratory Connectivity?

Technological advancements in the past 20 years or so have spurred rapid growth in the study of migratory connectivity (the linkage of individuals and populations between seasons of the annual cycle). A new article in Methods in Ecology and Evolution provides methods to help make quantitative comparisons of migratory connectivity across studies, data types, and taxa to better understand the causes and consequences of the seasonal distributions of populations.

In a new video, Emily Cohen, Jeffrey Hostetler and Michael Hallworth explain what migratory connectivity is and how the methods in their new article – ‘Quantifying the strength of migratory connectivity‘ – can help you to study it. They also introduce and give a quick tutorial on their new R package MigConnectivity.

This video is based on the article ‘Quantifying the strength of migratory connectivity by Cohen et al.

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Improved and Harmless Demethylation Method for Ecological Epigenetic Experiments

In a new Methods in Ecology and Evolution video, Javier Puy outlines a new method of experimental plant DNA demethylation for ecological epigenetic experiments. While the traditionally-used approach causes underdeveloped root systems and high mortality of treated plants, this new one overcomes the unwanted effects while maintaining the demethylation efficiency. The authors demonstrate its application for ecological epigenetic experiments: testing transgenerational effects of plant–plant competition.

This novel method could be better suited for experimental studies seeking valuable insights into ecological epigenetics. As it’s based on periodical spraying of azacytidine on established plants, it’s suitable for clonal species reproducing asexually, and it opens the possibility of community-level experimental demethylation of plants.

This video is based on the article ‘Improved demethylation in ecological epigenetic experiments: Testing a simple and harmless foliar demethylation application by Puy et al.

Animal Behaviour through a Virtual Lens

Motion vision is an important source of information for many animals. It facilitates an animal’s movement through an environment, as well as being essential for locating prey and detecting predators. However, information on the conditions for motion vision in natural environments is limited.

To address this, Bian et al. have developed an innovative approach that combines novel field techniques with tools from 3D animation to determine how habitat structure, weather and motion vision influence animal behaviour. Their project focuses on Australia’s charismatic dragon lizards, and will place the animals’ motion displays in a visual-ecological context. The application of this approach goes well beyond this topic and the authors suggest the motion graphic technologies is a valuable tool for investigating the visual ecology of animals in a range of environments and at different spatial and temporal scales.

This video is based on the article ‘Integrating evolutionary biology with digital arts to quantify ecological constraints on vision-based behaviour by Bian et al.

A New Way to Study Bee Cognition in the Wild

Understanding how animals perceive, learn and remember stimuli is critical for understanding both how cognition is shaped by natural selection, and how ecological factors impact behaviour.Unfortunately, the limited number of protocols currently available for studying insect cognition has restricted research to a few commercially available bee species, in almost exclusively laboratory settings.
In a new video Felicity Muth describes a simple method she developed with Trenton Cooper, Rene Bonilla and Anne Leonard for testing both lab- and wild-caught bees for their preferences, learning and memory. They hope this method will be useful for students and researchers who have not worked on cognition in bees before. The video includes a tutorial for carrying out the method and describes the data presented in their Methods in Ecology and Evolution article, also titled ‘A novel protocol for studying bee cognition in the wild‘.

This video is based on the article ‘A novel protocol for studying bee cognition in the wild by Muth et al.

 

Conditional Occupancy Design Explained

Occupancy surveys are widely used in ecology to study wildlife and plant habitat use. To account for imperfect detection probability many researchers use occupancy models. But occupancy probability estimates for rare species tend to be biased because we’re unlikely to observe the animals at all and as a result, the data aren’t very informative.

In their new article – ‘Occupancy surveys with conditional replicates: An alternative sampling design for rare species‘ – Specht et al. developed a new “conditional” occupancy survey design to improve occupancy estimates for rare species, They also compare it to standard and removal occupancy study designs. In this video two of the authors, Hannah Specht and Henry Reich, explain how their new conditional occupancy survey design works. 

This video is based on the article ‘Occupancy surveys with conditional replicates: An alternative sampling design for rare species‘ by Specht et al.

 

Why Soft Sweeps from Standing Genetic Variation are More Likely than You May Think

We coined the term “soft sweeps” in 2005. The term has since become widely used, though not everyone uses the term in the same way. As part of the ‘How to Measure Natural Selection‘ Special Feature in Methods in Ecology and Evolution, we attempt to clarify what “soft sweep” means and doesn’t mean. For example, not every sweep from standing genetic variation is necessarily a soft sweep.
In the review paper we also show under what conditions soft sweeps are likely (e.g., high population-wide mutation rate, multi-locus selection target). Finally, we describe relevant examples in fruitflies, humans and microbes and we discuss future research directions.
The video focuses on one aspect of the paper, which is illustrated in figure 3: “Why soft sweeps from standing genetic variation are more likely than you may think.”

This video is based on the Open Access article ‘Soft sweeps and beyond: understanding the patterns and probabilities of selection footprints under rapid adaptation by Hermisson and Pennings in the ‘How to Measure Natural Selection‘ Special Feature.

 

‘Size’ and ‘Shape’ in the Measurement of Multivariate Proximity

Ordination and clustering methods are widely applied to ecological data that are non-negative (like species abundances or biomasses). These methods rely on a measure of multivariate proximity that quantifies differences between the sampling units (e.g. individuals, stations, time points), leading to results such as:

  1. Ordinations of the units, where interpoint distances optimally display the measured differences
  2. Clustering the units into homogeneous clusters
  3. Assessing differences between pre-specified groups of units (e.g. regions, periods, treatment–control groups)

In this video, Michael Greenacre introduces his new article, ‘‘Size’ and ‘Shape’ in the Measurement of Multivariate Proximity’, published in Methods in Ecology and Evolution, May 2017. In the context of species abundances, for example, he explains how much a chosen proximity measure captures the difference in “size” between two samples, i.e. difference in overall abundances, and differences in “shape”, i.e. differences in compositions or relative abundances.  He shows that the popular Bray-Curtis dissimilarity inevitably includes a part of the “size” difference in its measurement of multivariate proximity.

This video is based on the article ‘‘Size’ and ‘shape’ in the measurement of multivariate proximity‘ by Michael Greenacre.

Assessment of Stream Health with DNA Metabarcoding

Following on from last week’s press release ‘How Clean are Finnish Rivers?’, Vasco Elbrecht et al. have produced a video to explain the methods in ‘Assessing strengths and weaknesses of DNA metabarcoding-based macroinvertebrate identification for routine stream monitoring‘.

In this video, the authors explore the potential of DNA metabarcoding to access stream health using macroinvertebrates. They compared DNA and morphology-based identification of bulk monitoring samples from 18 Finnish stream ecosystems. DNA-based methods show higher taxonomic resolution and similar assessment results as currently used morphology-based methods. Their study shows that the tested DNA-based methods integrate well with current approaches, but further optimisation and validation of DNA metabarcoding methods is encouraged.

This video is based on the article ‘Assessing strengths and weaknesses of DNA metabarcoding-based macroinvertebrate identification for routine stream monitoring‘ by Elbrecht et al.

 

Digitizing Historical Land-use Maps with HistMapR

Habitat destruction and degradation represent serious threats to biodiversity, and quantification of land-use change over time is important for understanding the consequences of these changes to organisms and ecosystem service provision.

Historical land-use maps are important for documenting how habitat cover has changed over time, but digitizing these maps is a time consuming process. HistMapR is an R package designed to speed up the digitization process, and in this video we take an example map to show you how the method works.

Digitization is fast, and agreement with manually digitized maps of around 80–90% meets common targets for image classification. We hope that the ability to quickly classify large areas of historical land use will promote the inclusion of land-use change into analyses of biodiversity, species distributions and ecosystem services.

This video is based on the Applications article ‘HistMapR: Rapid digitization of historical land-use maps in R‘ by Auffret et al. This article is freely available to anyone (no subscription required).

The package is hosted on GitHub and example scripts can be downloaded from Figshare.