mee-4-2-coverlargeIssue 4.2 is now available online! This month we  include articles on videos and cameras, statistical methods, animal populations, amphibians, distribution modeling, biomass estimations and genetic algorithms. There are also 2 freely available application articles on IPMpack: an R package for integral projection models, and Harmonizing, annotating and sharing data in biodiversity–ecosystem functioning research.

About the cover: The image shows the Yorkshire Dales National Park (YDNP), UK, above the village of Malham after brief, heavy snowfall. It was taken during an April transect survey of curlew (Numenius arquata) and other wader species. Within large areas, such as the YDNP, variables at multiple spatial scales can influence the distribution of bird species. When modeling the distribution of a species, the identification of the important variables, at the correct spatial scales, is important in developing the most reliable models. Models can be complicated by the large number of landscape-scale variables, problems with spatial autocorrelation and the fact that the same variable may influence a species at more than one spatial scale. In “Identifying appropriate spatial scales of predictors in species distribution models with the random forest algorithm” the authors investigated a novel computational method to identify appropriate variables and their spatial scales for predicting population distributions. Analyses of simulated species distributions demonstrated that the technique facilitated the evaluation of multiple spatial scales of multiple variables against each other. This approach was then applied to a real dataset on curlew collected during the field survey mentioned above.
Image by Ute Bradter.