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.

Microphone Backpacks for Individual-level Acoustic Recordings

To understand the factors shaping vocal communication, we need reliable information about the communicating individuals on different levels. First, vocal behaviour should be recorded from undisturbed animals in meaningful settings. Then we have to separate and assign the individuals’ vocalisations. Finally, the precise timing of vocal events needs to be stored.

Microphone backpacks allow researchers to record the vocal behaviour of individual animals in naturalistic settings – even in acoustically challenging environments! In the video below, Lisa Gill, Nico Adreani and Pietro D’Amelio demonstrate the lightweight radio-transmitter microphone backpacks that have been developed and built at the Max Planck Institute for Ornithology, Seewiesen, Department of Behavioural Neurobiology. They show the attachment and setup of this system in detail, evaluate its behavioural effects, and discuss what makes it so useful for studying vocal communication, especially in small animals.

This video is based on the article ‘A minimum-impact, flexible tool to study vocal communication of small animals with precise individual-level resolution‘ by Gill et al.


Decoupling Functional and Phylogenetic Dissimilarity between Organisms

Francesco de Bello describes the main elements of the method he has recently published in Methods in Ecology and Evolution. The method aims at decoupling and combining functional trait and phylogenetic dissimilarities between organisms. This allows for a more effective combination of non-overlapping information between phylogeny and functional traits. Decoupling trait and phylogenetic information can also uncover otherwise hidden signals underlying species coexistence and turnover, by revealing the importance of functional differentiation between phylogenetically related species.

In the video Francesco visually represents what the authors think their tool is doing with the data so you can see its potential. This method can provide an avenue for connecting macro-evolutionary and local factors affecting coexistence and for understanding how complex species differences affect multiple ecosystem functions.

This video is based on the article ‘Decoupling phylogenetic and functional diversity to reveal hidden signals in community assembly‘ by de Bello et al.


The Field Guide to Sequence-Based Identification of Biodiversity: An Interview with Simon Creer

In a new Methods in Ecology and Evolution podcast, Georgina Brennan (Bangor University) interviews Simon Creer (Bangor University) about his article ‘The ecologist’s field guide to sequence-based identification of biodiversity‘. They talk about about where the idea for the paper came from, what it’s aim are and who will benefit from it. We hear how new sequences can improve and enhance current biomonitoring programmes (and make them quicker and cheaper).

To find out more about Sequence-based Identification of Biodiversity, read the Open Access Methods in Ecology and Evolution article ‘The ecologist’s field guide to sequence-based identification of biodiversity‘.