Special Features

5th Anniversary of Methods in Ecology and Evolution

Editor: Rob Freckleton

Special Feature in Volume 7 Issue 6

To celebrate the 5th anniversary of Methods in Ecology and Evolution, we held a symposium in 2015, jointly hosted between London and Calgary. Streamed live, and with talks recorded and hosted here, the symposium showcased the range of methods that we had published across our discipline and involved many of our authors and members of our editorial board. A selection of the authors who gave talks at the symposium have contributed articles to this special feature.

Demography Beyond the Population

Guest Editors: Alden Griffith, Rob Salguero-Gómez, Jessica Metcalf, Cory Merrow, Sean McMahon and Dylan Childs

Special Feature in Volume 7 Issue 2

This exciting collaborative and interdisciplinary special feature integrates novel lines of research in the vast field of demography that directly interact with other ecological and evolutionary disciplines. The goal of the special feature - to highlight the interdisciplinary potential of demography - is further emphasised by the fact that its articles are spread among all six journals of the British Ecological Society. Our goal is to make aware both demographers and non-demographers alike that there is much to be gained by linking demography to other disciplines and scales in ecology and evolution. The Special Feature is based on a British Ecological Society symposium that was held in March 2015 and is the first time all six BES journals have collaborated to produce a joint special feature.

New Opportunities at the Interface between Ecology and Statistics

Guest Editor: David Warton

Special Feature in Volume 6 Issue 4

Cross-disciplinary research can be a highly productive pursuit, leading to the development of entirely new ideas as well as finding new ways to look at old problems. A particularly exciting example of what can be achieved is when ecologists and statisticians work together. Perhaps, one of the reasons for the success of Methods in Ecology and Evolution is that it provides a forum for researchers from these two disciplines to interact. This Special Feature arose from a two-day Ecological Statistics Symposium designed to provide an opportunity for ecologists and statisticians to meet and discuss common issues and opportunities for collaboration in July 2013 meeting at the Univesity of New South Wales, Australia. It consists of an introduction by the Guest Editor, David Warton, and seven articles written by statisticians and ecologists on topics such as 'presence-only and point pattern analysis', 'maximum entropy estimation in ecology', 'visualising multivariate data' and more.

Modelling Demographic Processes in Marked Populations: Proceedings of the EURING 2013 analytical meeting

Guest Editors: Charles M. Francis, Richard J. Barker and Evan G. Cooch

Special Feature in Volume 5, Issue 12

Joint Special Feature in MEE Volume 5, Issue 12 and the open access journal Ecology and Evolution.

This Special Feature brings together 31 papers presented at the EURING 2013 technical conference, that collectively cover many of the latest developments in the analysis of data from marked individuals to estimate demographic parameters, such as survival, recruitment, nest success, density, population size and movement.

Unifying Fossils and Phylogenies for Comparative Analyses of Diversification and Trait Evolution

Guest Editors: Luke Harmon and Graham Slater

Special Feature in Volume 4, Issue 8

The five papers in this Special Feature tackle a disparate range of topics in macroevolutionary research, from time calibration of trees to modelling phenotypic evolution. All are united, however, in implementing novel phylogenetic approaches to understand macroevolutionary pattern and process in or using the fossil record. This Special Feature highlights the benefits that may be reaped by integrating data from living and extinct species and, we hope, will spur further integrative work by empiricists and theoreticians from both sides of the macroevolutionary divide.