Virtual Issue: Ecological Statistics are Methods too

Methods in Ecology and Evolution has been publishing papers on statistical ecology since its inception in 2010. Since the last ISEC meeting, we have published many more papers, of an increasing quality and influence. This Virtual Issue brings together some of those papers - but also misses out many more that will be just as interesting.

The papers chosen show the range of statistical issues that have been covered in MEE: movement ecology, distributions, abundance, dynamics, capture/recapture, as well as papers on how we should interpret our results. MEE also publishes applications, which outline recent developments in implementations of methods, for example new software and packages, and a couple of these are included in this Virtual Issue.

I hope these papers will prove to be stimulating, and show the range of statistical subjects covered in MEE. I also hope it will encourage you to explore other papers published in MEE, and to submit your best papers on statistical ecology to Methods in Ecology and Evolution.

Bob O’Hara, Senior Editor

Standard Papers


Movement ecology

The effectiveness of Bayesian state-space models for estimating behavioural states from movement paths

Estimating individual animal movement from observation networks

Indicators & measures of biodiversity
A general theory of multimetric indices and their properties

New biodiversity measure that includes consistent interspecific and intraspecific components

Species distribution models
A new statistical framework for the quantification of covariate associations with species distributions

Fitting complex ecological point process models with integrated nested Laplace approximation

Abundance
Indexing butterfly abundance whilst accounting for missing counts and variability in seasonal pattern

Calibrating indices of avian density from non-standardized survey data: making the most of a messy situation

Population dynamics
Estimating density dependence and latent population trajectories with unknown observation error

Population dynamics of species-rich ecosystems: the mixture of matrix population models approach

Capture/recapture
Hierarchical spatial capture–recapture models: modelling population density in stratified populations

Varying effort in capture–recapture studies

Interpreting Results
Using commonality analysis in multiple regressions: a tool to decompose regression effects in the face of multicollinearity

A general and simple method for obtaining R2 from generalized linear mixed-effects models

Applications

marked: an R package for maximum likelihood and Markov Chain Monte Carlo analysis of capture–recapture data

Cheddar: analysis and visualisation of ecological communities in R

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