Long-term datasets yield a great deal of information and are increasingly used to inform conservation measures.
In the first video of the new year, Gary Powney and Tom Oliver show how long-term monitoring data on the Speckled Wood butterfly (Pararge aegeria) from the UK monitoring butterfly scheme can be used to assess functional connectivity of the landscape.
In a paper recently published in Methods, Gary Powney, Tom Oliver and colleagues use synchrony between population counts as a new empirical method to assess functional connectivity – the permeability of landscapes given species dispersal attributes. Functional connectivity is important because well-connected metapopulations are expected to be more resistant to stochastic events causing extinction. They use long-term monitoring data on the Speckled Wood butterfly and find that population synchrony is positively correlated with landscape suitability, suggesting that synchrony might be used to measure functional connectivity.
A key finding is that relatively close populations may exchange sufficient migrants for synchronisation, regardless of the matrix suitability. In contrast, more separate populations are synchronised only where the landscape permits functional connectivity, most likely through dispersal between intermediate stepping-stone populations.
This technique might be used to test and prioritise the effectiveness of land management for conservation of species and to mitigate the effects of climate change.
The cover image for the last issue of the year of Methods in Ecology and Evolution is a biological soil crust (BSC), a community which may be composed by mosses, lichens, liveworths fungi and bacteria that are prevalent in drylands worldwide.
Lichen-dominated BSCs (like the one in the image) affect multiple ecosystem functions in those habitats where they are present, including carbon and nitrogen cycling, soil stabilization, and water infiltration and runoff.
The article linked to the image is Randomization tests for quantifying species importance to ecosystem function by Nicholas Gotelli, Werner Ulrich and Fernando Maestre. In the article the authors introduce randomization tests for evaluating the effect of individual species on ecosystem variables measured in multiple plots. This approach is tested using data on ecosystem functioning in lichen-dominated BSC assemblages from central Spain, and further validated using an independent microcosm experiment. The method proposed in this article provides a simple index and statistical test of species importance that can form the basis for additional hypothesis tests and experimental studies of species occurrence and ecosystem functioning.
This BSC-forming lichen community was photographed by Fernando T. Maestre in gypsum outcrops from Sax (South East Spain).
Finally, the issue contains two free Application articles. In the first Conrad Stack, Luke Harmon and Brian O’Meara detail RBrownie, an R package for testing hypotheses about rates of evolutionary change. In the second, Stefan Prost and Christian Anderson present TempNet, a method to display statistical parsimony networks for heterochronous DNA sequence data.