Could we use the plants in this swamp forest to predict the diversity of other species?
Local communities and regional biotas are built of hundreds, if not thousands, of species. Most of these species are small-bodied and discreet lifeforms. So it’s no wonder that naturalists have almost always focused their attention on conspicuous species of their particular liking. Why plants then? Well, plants are practical and efficient. They “stand still and wait to be counted”, as the eminent population biologist John Harper put it. No matter the weather, from spring to autumn. There are enough plant species to show contrasts between sites, and yet they can usually be identified to species level in the field.
You Can’t Predict the Diversity of Beetles from Lichens… Can You?
The BES Microbial Ecology Special Interest Group is running a workshop today (Thursday 2 November) on Novel Tools for Microbial Ecology. To compliment this workshop, Xavier Harrison has edited a Virtual Issue of the best Methods in Ecology and Evolution articles on advances in methods of studying microbial evolution and ecology from the past few years.
Advances in Next-Generation Sequencing (NGS) technology now allow us to study associations between hosts and their microbial communities in unprecedented detail. However, studies investigating host-microbe interactions in the field of ecology and evolution are dominated by 16S and ITS amplicon sequencing. While amplicon sequencing is a useful tool for describing microbial community composition, it is limited in its ability to quantify the function(s) performed by members of those communities. Characterising function is vital to understanding how microbes and their hosts interact, and consequently whether those interactions are adaptive for, or detrimental to, the host. The articles in this Virtual Issue cover a broad suite of approaches that allow us to study host-microbe and microbe-microbe interactions in novel ways.
One of my main areas of study is Periphyton developed in microcosms. For those of you who don’t know, Periphyton is a green biofilm that you may notice in some (not very clean) swimming pools and is composed mainly of algae, bacteria, fungi, meiofauna and detritus. I started studying Periphyton because my Masters thesis involved developing a model in freshwater systems and after that I wanted to look into their spatial distribution.
I wanted to find an opportunity to connect my study system with two of my passions: space travel (I used to watch Star Trek and also I thoroughly enjoyed Space: The Final Frontier for Ecological Theory by Peter Kareiva) and tropical rainforests (which I developed a fondness for while watching Tarzan). I thought I could use Periphyton as a model system to test ecological theory, with a complexity similar to tropical forest as suggested by Lowe .
The study of the spatial structure of Periphyton was not as easy as space travel in Star Trek (for one thing they have a warp drive and I don’t!). I wanted to compare spatial models and data, but the methods that were available weren’t very well-suited to what I wanted to do, so I was not sure of how to begin. In the end, I decided to launch my first microcosms experiment and in the first photos I took of Periphyton’s spatial structure I saw they were like clouds, algae clouds. Continue reading →
This month’s issue contains two Applications article and one Open Access article, all of which are freely available.
– LEA: This R package enables users to run ecological association studies from the R command line. It can perform analyses of population structure and genome scans for adaptive alleles from large genomic data sets. The package derives advantages from R programming functionalities to adjust significance values for multiple testing issues and to visualize results.
–PIPITS: An open-source stand-alone suite of software for automated processing of Illumina MiSeq sequences for fungal community analysis. PIPITS exploits a number of state of the art applications to process paired-end reads from quality filtering to producing OTU abundance tables.
Giovanni Strona and Joseph Veech provide this month’s Open Access article. Many studies have focused on nestedness, a pattern reflecting the tendency of network nodes to share interaction partners, as a method of measuring the structure of ecological networks. In ‘A new measure of ecological network structure based on node overlap and segregation‘ the authors introduce a new statistical procedure to measure both this kind of structure and the opposite one (i.e. species’ tendency against sharing interacting partners).