Issue 7.8 is now online!
This month’s issue contains two Applications articles and two Open Access articles, all of which are freely available.
– Plant-O-Matic: A free iOS application that combines the species distribution models with the location services built into a mobile device to provide users with a list of all plant species expected to occur in the 100 × 100 km geographic grid cell corresponding to the user’s location.
– RClone: An R package built upon
genclone software which includes functions to handle clonal data sets, allowing:
- Checking for data set reliability to discriminate multilocus genotypes (MLGs)
- Ascertainment of MLG and semi-automatic determination of clonal lineages (MLL)
- Genotypic richness and evenness indices calculation based on MLGs or MLLs
- Describing several spatial components of clonality
The two most common approaches for analysing count data are to use a generalized linear model (GLM), or transform data, and use a linear model (LM). Recently, there have been claims that LM more reliably maintains control of type I error rates in tests for no association, while seemingly losing little in power. Associate Editor David Warton et al. make three points about this issue in the first Open Access article in this month’s issue – ‘Three points to consider when choosing a LM or GLM test for count data‘.
The second Open Access article in this month’s issue comes from Michael May et al. In ‘A Bayesian approach for detecting the impact of mass-extinction events on molecular phylogenies when rates of lineage diversification may vary‘ the authors present a novel method for detecting the impact of mass-extinction events on molecular phylogenies, even in the presence of tree-wide diversification-rate variation and in the absence of additional information from the fossil record.
For a limited time, there are two more freely available article in our August issue. Both are included in the Statistical Ecology Virtual Issue, which was published in June. The articles deal with optimizing survey efforts and experimentally derived likelihoods.
This month’s cover image shows two male sleepy lizards (Tiliqua rugosa) fighting. Fights in these long-lived lizards allow males to exclude others from their core home range, and to follow their monogamous female partners throughout the breeding season. Since this species is the main host for some local ticks, it is also a suitable model system for studying the effects of host-behaviour on parasite transmission. Identifying the ecological factors that shape the structure of lizards’ social networks is important both for understanding their biology and for disease ecology. Separating the contributions of ecological constraints and social preference is a general challenge in social networks studies (i.e. did two animals meet because they had to share a resource or because they were attracted to each other?).
Spiegel et al. present a new method for analysing social networks and teasing apart these contributions in the associated article – ‘Socially interacting or indifferent neighbours? Randomization of movement paths to tease apart social preference and spatial constraints‘. After validating the method with synthetic datasets obtained from computer simulations they use the lizards tracking dataset to explore these questions and demonstrate the utility of their method. They found that lizards show strong conspecific attraction, interacting more frequently and with more neighbours than expected by chance. Note, however, that these interactions are not necessarily friendly, as the two males in the picture remind us.
Photo © Dale Burzacott 2015