The final 2019 issue of Methods in Ecology and Evolution is online now.
You can find out more about our Featured Articles (selected by the Senior Editor) below. We also discuss this month’s Open Access and freely available papers we’ve published in our latest issue (Practical Tools and Applications articles are always free to access, whether you have a subscription or not) .
An Ecological Trait-Data Standard: To make it easier to standardise and harmonise of distributed trait datasets by data providers and data users, Schneider et al. have proposed a standardised vocabulary that can be used for storing and sharing ecological trait data. This article is Open Access.
Clustering and Correlations: In diverse ecosystems, organisms cluster together in a way that makes the frequency distribution of cluster sizes a power law function. Sankaran et al. show that, depending on the strength of positive feedback, power law clustering can occur at any distance from the critical threshold of ecosystem collapse. They show that for systems with strong positive feedback, there may be no loss of power law clustering prior to critical thresholds.
gllvm: There’s been rapid development in tools for multivariate analysis based on fully specified statistical models or ‘joint models’. The R package gllvm offers relatively fast methods to fit GLLVMs via maximum likelihood, along with tools for model checking, visualization and inference. This is a freely available Applications article.
Radio-Tracking for Small Animals: Gottwald et al. present a low‐cost automatic radio‐tracking system built from consumer electronic devices that can locate the position of radio transmitters under field conditions. They provide information on the hardware components, describe mobile and stationary set‐up options, and offer open‐source software solutions. This article is Open Access.
When Can We Trust Population Trends?: This new method compares trends from various samples of ‘complete’ population time series, to see how often these samples correctly estimate the sign (i.e. direction) and magnitude of the complete trend. By giving percentage estimates of reliability for combinations of sampling regimes and lengths, it lets you determine the reliability of species population trends.
Lorelograms and Correlation in Binary Data: The lorelogram is a tool used to identify and describe dependency structures in binary data. It can help guide data aggregation efforts to facilitate independence, or alternatively, to inform appropriate structures for modelling correlated data. Iannarilli et al. introduce this promising tool for quantifying correlation in binary data over space or time to ecologists.
Our only Practical Tools paper this month (Radio-Tracking for Small Animals) has already been covered above. If you’re itching for more articles on field and lab methods, keep an eye on the blog next week. We’ll be wrapping all of our Practical Tools papers to date into a single Virtual Issue for you.
One of this month’s Applications papers (gllvm) has too. But don’t worry, we’ve still got another three to look at.
layeranalyzer: Trond Reitan and Senior Editor Lee Hsiang Liow present layeranalyzer, an R package that uses linear stochastic differential equations as a tool for parametrically describing evolutionary and ecological processes. It can also be used for modelling temporal correlation and Granger causality between two or more time series.
segRDA: With segRDA, Vieira et al. combine split‐moving‐window and piecewise redundancy analysis to let you identify breakpoints and transition zones among ecological communities along environmental gradients. This approach is particularly relevant when species-habitat associations differ among communities.
VoCC: Metrics describing the velocity of climate change have been extensively used in climate -change ecology research and provide useful information for conservation. Multiple extensions to the original concept of climate velocity have been proposed since first presented nearly a decade ago. But software application has been created that brings all these methods together… until now! The R package VoCC provides a comprehensive collection of functions that calculate climate velocity and related metrics from their initial formulation to the latest developments.
Open Access Articles
We’ve got a whopping seven(!) Open Access articles in this month’s issue of Methods in Ecology and Evolution. We’ve already touched on a few of them and now it’s time to take a look at the others.
Diel Activity Patterns: Vazquez et al. explore whether and how activity patterns can be transformed more accurately using two alternative ‘double anchoring’ transformations – equinoctial and average anchoring. These transformations anchor activity time to two chosen anchor points during the study period.
Multi‐Dimensional Grid‐Point Scaling Algorithm: Daniel Gann introduces a new scaling algorithm that aggregates categorical data while simultaneously controlling for information loss by generating a non‐hierarchical, representative, classification system for the aggregated scale.This is the first algorithm that generates data‐driven, scale‐specific classification schemes while conducting spatial data aggregation.
Complementarity and Selection Effects: Clark et al. present an augmentation of the Loreau & Hector selection/complementarity effects that adjusts for incomplete monoculture data. It controls for the bias introduced by using only a subsample of species in monocultures rather than having monocultures of all species.
The Whales on the Cover
This month’s cover image shows a southern right whale (Eubalaena australis) mother and calf pair. It was photographed by a DJI Inspire 1 Pro drone, on their nursing ground in Península Valdés, Argentina. Due to their large body size, baleen whales play an important role in the marine ecosystem. Photographs like this one can be used to measure the body shape of free‐living whales, converting these morphometric measurements to body mass has proven challenging because of the difficulty in weighing live whales.
In ‘Estimating body mass of free‐living whales using aerial photogrammetry and 3D volumetrics‘, Christiansen et al. present a novel non‐invasive approach to estimate the body mass of free‐living whales, by combing aerial photogrammetry data with historical whaling records. The authors provide a detailed description of how to convert body length, width and height (all measured by drones) to body volume and mass, and demonstrate the accuracy of their model compared to alternative models. This tool makes it possible to easily measure and incorporate body mass into studies of free‐living whales, to investigate how body mass has contributed to shaping the ecology and life history of this animal group, and to aid in their conservation.
Photo credit: © Fredrik Christiansen, Aarhus Institute of Advanced Studies