Posted by: oikosasa | June 4, 2014

Editor’s Choice June

DriesPapers published in Oikos should meet the principal criteria to generate synthesis in ecology. Synthesis can be created in different ways and definitively obtained when long-term data sets, novel analytical tools and good hypotheses are merged. The first editor’s choice for the June issue is the paper by Karen Lone and colleagues on multi-predator landscapes of fear. Motivated by challenges to manage large carnivores in Scandinavia in relation to human conflict, the authors used an extensive dataset containing Lidar data, behavioural data and hunting information to demonstrate the interactive impact of multiple predators on predation risk of a single prey species. By means of this integrative approach, the authors demonstrate a predation risk from humans and lynx on roe deer in areas with a high vegetation cover, but an additive impact in more rocky locations. As such, the study demonstrates the complexity of predator-prey interactions in real landscapes, and clearly emphasises the need and value of individual-based ecology to understand interactions in (simplified) foodwebs.

Oikos has decided to highlight meta-analysis papers because of their principal role to create synthesis in ecology.  Chris Lortie will be Editor-in-Chief for this category of papers (look out for his editorial in the August issue). Meta-analysis papers will be published OA for three months after publication. Ward and colleagues tested the performance of time-series forecasting models for natural animal populations based on more than 200 datasets of vertebrate surveys. Such a meta-analysis is considered essential because of the increasing demand to forecast population dynamics under different global change scenarios. While forecasting approaches using non-mechanistic statistical models have greatly evolved the last decades in population biology, still a limited amount of such models are commonly used. By performing a statistical competition experiment, the authors tested the predictive performance of 49 different forecasting models and found simple models to behave well after all, although increasing model complexity fitted time series better in case of species with cyclic population dynamics.

Editor’s choice papers are free online for three months!

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