What is Beta Diversity?

Post provided by Dr Andrés Baselga

Dr Andrés Baselga

A key property of biodiversity is that it is not evenly distributed around the world. In other words, different sites are usually  home to different biological communities. Quantifying the differences among biological communities is a major step towards understanding how and why biodiversity is distributed in the way it is.

The term beta diversity was introduced by R.H. Whittaker in 1960. He defined it as “the extent of change in community composition, or degree of community differentiation, in relation to a complex-gradient of environment, or a pattern of environments”. In his original paper, Whittaker proposed several ways to quantify beta diversity. In its simplest form (which we will call strict sense or multiplicative beta diversity), beta diversity is defined as the ratio between gamma (regional) and alpha (local) diversities (Whittaker, 1960; Jost, 2007). Therefore, it is the effective number of distinct compositional units in the region (Tuomisto, 2010). Essentially, beta diversity quantifies the number of different communities in the region. So it’s clear that beta diversity does not only account for the relationship between local and regional diversity, but also informs about the degree of differentiation among biological communities. This is because alpha and gamma diversities are different if (and only if) the biological communities within the region are different.

It’s easy to demonstrate how beta diversity varies from the minimum to the maximum differentiation of local assemblages in a region. For simplicity, we will quantify biological diversity as species richness (number of species), but it’s important to remember that alpha, beta and gamma diversities can also be defined to account for richness and relative abundances (see Jost, 2007 for a detailed explanation). When local assemblages are all identical (minimum differentiation), alpha diversity equals gamma diversity, and beta diversity equals 1 (figure below).

beta1

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International Day for Biological Diversity 2015

Happy International Day for Biological Diversity everyone!

As you may know, today (Friday 22 May) is the United Nations Day for Biodiversity and we are celebrating by highlighting some of the best papers that have been published on biodiversity in Methods in Ecology and Evolution. This is by no means an exhaustive list and you can find many more articles on similar topics on the Wiley Online Library (remember, if you are a member of the BES, you can access all Methods articles free of charge).

If you would like to learn more about the International Day for Biological Diversity, you may wish to visit the Convention on Biological Diversity website, follow them on Twitter or check out today’s hashtag: #IBD2015.

Without further ado though, here are a few of the best Methods papers on Biological Diversity:

Methods Cover - August 2012Biodiversity Soup

We begin with an Open Access article from one of our Associate Editors, Douglas Yu (et al.). This article was published in the August issue of 2012 and focuses on the metabarcoding of arthropods. The authors present protocols for the extraction of ecological, taxonomic and phylogenetic information from bulk samples of arthropods. They also demonstrate that metabarcoding allows for the precise estimation of pairwise community dissimilarity (beta diversity) and within-community phylogenetic diversity (alpha diversity), despite the inevitable loss of taxonomic information.

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Issue 6.5

Issue 6.5 is now online!

The May issue of Methods is now online!

We have two freely available articles this month: one Application and one Open Access Article.

rSPACE: An open-source R package for implementing a spatially based power analysis for designing monitoring programs. This method incorporates information on species biology and habitat to parameterize a spatially explicit population simulation.

Tim Lucas et al. provide this month’s Open Access article: A generalised random encounter model for estimating animal density with remote sensor data. The authors have developed a Generalised Random Encounter Model (gREM) to estimate absolute animal density from count data from both camera traps and acoustic detectors. They show that gREM produces accurate estimates of absolute animal density for all combinations of sensor detection widths and animal signal widths. This model is applicable for count data obtained in both marine and terrestrial environments, visually or acoustically. It could be used for big cats, sharks, birds, echolocating bats, cetaceans and much more. Continue reading “Issue 6.5”

The Delphi Technique: Unleashing the Power of Structured Collaboration in Anonymity

Post provided by Nibedita Mukherjee (author of The Delphi technique in ecology and biological conservation)

The quirky nature of decision making

Two heads are often better than one in decision making. Several heads might have an even higher probability of being better than one. However, people in a group often have different modes of thinking or problem solving, alternate reference frames, subjective biases and varying levels or domains of expertise. How do we harness these messy thought processes and channel them for effective decision-making for biodiversity management?

© Henry Martin (The New Yorker Collection/The Cartoon Bank)
© Henry Martin (The New Yorker Collection/The Cartoon Bank)

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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.

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A Dog’s Nose Knows: The Science is in on Wildlife Sniffer Dogs

Below is a press release about the Methods paper, ‘An assessment of the effects of habitat structure on the scat finding performance of a wildlife detection dog, taken from Science for Wildlife:

Badger the Wildlife Sniffer Dog

Scientists have for the first time tested wildlife detection dogs to see how they perform in different habitats, and the results are very impressive.

Wildlife sniffer dogs are trained to find the scats (poo) or scent of hard to find wildlife species. As threatened species continue to drop in numbers, they become much harder to find and conserve. Detection dogs are a potential solution to that problem.

Despite their amazing skills the use of sniffer dogs by wildlife management agencies is still limited, partly because there are many factors that might impact the dogs’ performance. One well-toted theory states that dogs might not perform well in thicker vegetation, compared to open areas. The lead author of the new study, Dr Kellie Leigh from Science for Wildlife, explains “Scent is heavier than air so it pools and gets caught up in vegetation and depressions, rather than dispersing from its source. That means the dogs might have more trouble finding the scent in some areas.”

Working together with professional dog trainer Martin Dominick from K9-Centre Australia, Dr Leigh ran an experiment with Badger, an Australian Shepherd trained to find the scat of spotted-tailed quolls. The quolls are the largest marsupial predator on mainland Australia and are becoming very hard to find in some areas. Over 120 searches, Badger scoured for quoll scats in three different Australian habitats, from open grassland to thick vegetation, under both winter and summer conditions. Continue reading “A Dog’s Nose Knows: The Science is in on Wildlife Sniffer Dogs”

Issue 6.4: Opportunities at the Interface Between Ecology and Statistics

Issue 6.4 is now online!

© Chun-Huo Chiu and Ching-Wen Cheng

The April issue of Methods, which includes our latest Special Feature: “Opportunities at the Interface Between Ecology and Statistics” is now online!

Opportunities ar the Interface Between Ecology and Statistics is a collection of eight articles which arose from the Eco-Stats Symposium at the University of New South Wales (Australia) in July 2013.This Symposium was designed to be a collaborative forum for researchers with interests in ecology and statistics. It brought together internationally recognised leaders in these two fields (such as Jane Elith, Trevor Hastie, Anne Chao and Shirley Pledger) – many of whom have contributed articles to this Special Feature.

The Eco-Stats Symposium was arranged around five special topics, all of which are represented in this issue of Methods. Those five topics are:

In his Editorial for the Special Feature, Guest Editor David Warton suggests that one of the reasons for the success of Methods in Ecology and Evolution may be that it provides a forum for statisticians and ecologists to interact. The articles in this issue, and the conference that gave rise to them, show that these interactions can provide significant benefits for both groups.

There will be another Eco-Stats Symposium at the University of New South Wales in December of this year (8-10 December, 2015).
For more details on this, please click here.
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2014 Robert May Prize Winner: Laure Gallien

The Robert May Prize is awarded annually for the best paper published in Methods by a young author at the start of their research career. We’re delighted to announce that the 2014 winner is Laure Gallien, for her article ‘Identifying the signal of environmental filtering and competition in invasion patterns – a contest of approaches from community ecology.

Today, biological invasions are of major concern for maintaining biodiversity. However, understanding what drives the success of invasive species at the scale of the community remains a challenge. Two processes have been described as main drivers of the coexistence between invasive and native species: environmental filtering and competitive interactions. However, recent reviews have shown that competitive interactions are rarely detected, and thus their importance as drivers of invasion success placed under question. But can this be due to pure methodological issues? Using a simulation model of community assembly, Laure and co-authors (Marta Carboni and Tamara Münkemüller) show that the infrequent detection of competition can arise from three important methodological shortcomings, and provide guidelines for future studies of invasion drivers at the scale of the community.

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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”

Issue 6.3

Issue 6.3 is now online!

The March issue of Methods is now online!

We have three freely available Applications articles in this issue. Anyone can access these with no subscription required and no charge to download.

TR8: This R package was built to provide plant scientists with a simple tool for retrieving plant functional traits from freely accessible online traitbases.

StereoMorph: A new R package for the rapid and accurate collection of 3D landmarks and curves using two standard digital cameras.

MotionMeerkat: A new standalone program that identifies motion events from a video stream. This tool reduces the time needed to review videos and accommodates a variety of inputs.

This month we have a total of FIVE Open Access articles. That makes eight articles in this issue of Methods in Ecology and Evolution that you can read for free!

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