An immature female blue-tailed damselfly (Ischnura elegans) (Image Credit: Charles J Sharp [CC BY-SA 4.0])
Signatures of local adaptation along environmental gradients in a range-expanding damselfly (Ischnura elegans) (2018) Dudaniec et al., Molecular Ecology http://doi:10.1111/mec.14709
Terrestrial organisms aren’t always stationary entities, they often move around the landscape searching for food, potential mates, or more ideal environments. Over time, these movements may introduce the species into new environments, as some change allows the species to expand their historical range.
An interesting aspect of this shifting of the species range is how the organisms at the edge of the distribution are maladapted to the novel environments, as most of the species will be adapted to conditions at the core of the species range. To overcome this, they must adapt to the new conditions. Successful adaptation is dependent on changes in gene frequencies away from the historical genotypes, with an increase in genes that promote survival in the new habitats. The authors in this study used molecular techniques to identify genes that new environments might select for.
Species associations will change as the climate rises. So how can we attempt to predict these changes (Image Credit: Charles J Sharp, CC BY-SA 4.0)
Using joint species distribution models for evaluating how species-to-species associations depend on the environmental context (2017) Tikhonov et al, Methods in Ecology and Evolution, DOI: https://doi.org/10.1111/2041-210X.12723
Statistical modelling is a crucial part of ecology. Being able to provide an (admittedly simplified) mathematical description of the relationship between species abundance, range or density and the surrounding environment is a huge help in taking proactive steps to manage an ecosystem, or predicting species numbers in other areas.
Historically models have used environmental variables to explain population or evolutionary developments in species. When modelling a single species, many ecologists have taken into account that the presence of other species (for example competitors or predators) may influence the presence of this single species. This has led to the rise of joint species distribution models (JSDMs), which take into account environmental variables, as well as the interactions between certain species. These models have become increasingly useful, and with environmental change now being the norm in many ecosystems, this week’s authors produced one such model that accounts for changes in species interactions in the face of changing environmental factors.