Movement ecology is a cross-disciplinary field. Its main aim is to quantitatively describe and understand how movement relates to individual and population-level processes for resource acquisition and, ultimately, survival. Today the study of movement ecology hinges on two 21st century advances:
Animal-borne devices/tags (biologging science, Hooker et al., 2007) and/or remote sensing technology to quantify movement and collect data from remote or otherwise challenging environments
Computational power sufficient to manipulate, process and analyse substantial volumes of data
Although datasets often involve small numbers of individuals, each individual can have thousands – sometimes even millions – of data points associated with it. Study species have tended to be large birds and mammals, due to the ease of tag attachment. However, the trend for miniaturisation of tags and the development of remote detection technologies (such as radar, e.g. Capaldi et al., 2000), have allowed researchers to track and study ever smaller animals. Continue reading →
All of the articles in this month’s issue of Methods in Ecology and Evolution are free for the whole year. You will not need a subscription to access or download any of them throughout 2017.
Our first issue of this year contains three Applications articles and two Open Access articles. These five papers will be freely available permanently.
– CDMetaPOP: Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.
– Rphylopars: An R implementation of PhyloPars, a tool for phylogenetic imputation of missing data and estimation of trait covariance across species (phylogenetic covariance) and within species (phenotypic covariance). Rphylopars provides expanded capabilities over the original PhyloPars interface including a fast linear-time algorithm, thus allowing for extremely large data sets (which were previously computationally infeasible) to be analysed in seconds or minutes rather than hours.
– ggtree: An R package that provides programmable visualisation and annotation of phylogenetic trees. ggtree can read more tree file formats than other software and allows colouring and annotation of a tree by numerical/categorical node attributes, manipulating a tree by rotating, collapsing and zooming out clades, highlighting user selected clades or operational taxonomic units and exploration of a large tree by zooming into a selected portion.
Our understanding of how biological diversity works has been advanced by a long history of observing species and linking patterns to ecological processes. However, we generally don’t focus as much on those species that aren’t observed, or in other words ‘absent species’. But, can absent species provide valuable information?
To begin learning about dark diversity, there are two important terms that we need to define: ‘species pool’ and ‘focal community’. A ‘species pool’ is a set of species present in a particular region or landscape that can potentially inhabit a particular observed community because of suitable local ecological conditions.
A ‘focal community’ is the set of species that have been observed in a particular region or landscape (this is the ‘observed community’ and can also be referred to as alpha diversity). For a given focal community to become established, the species within it must have overcome dispersal pressures as well as environmental and biotic filters.
The seemingly basic question of whether a population is increasing, decreasing, or stable can be one of the most difficult to answer. Collecting data on rare and elusive species is hard. Imagine trying to detect a handful of fisher or wolverine across hundreds of thousands of acres – it is physically demanding, time consuming and logistically complicated. And that’s just to do it once! To monitor a population for changes, you have to repeat these surveys regularly over many years. The long-term monitoring that is necessary for conservation requires careful planning and a substantial commitment of resources and funding. So before we spend these valuable resources, it’s critical to know whether the data we are collecting can help us to answer our questions. Continue reading →
In case you haven’t seen them, this month we have published a new podcast and video so far.
In our latest video, David Warton, The University of New South Wales, Australia, presents his ‘mvabund’ package on multivariate analysis. What makes this software different from other ones on multivariate analysis, is that it’s all about models that you can fit to your data. David explains how to look at the properties of your data and the common pitfalls in modelling multivariate data. He also goes through how to fit generalised linear models to your data. Do check David’s dancing!
Determining how animals move within their environment is a fundamental knowledge that contributes to effective management and conservation.
In our latest video, David Jacoby and Edd Brooks explain how their paper brings together two disparate and rapid advancing fields: biotelemetry and social networking analyses.
In a paper recently published in Methods, David, Edd and colleagues Darren Croft and David Sims, demonstrate some of the descriptive and quantitative approaches for determining how an animal’s movement interconnects home range habitats. David and colleagues describe the novel application of network analyses to electronic tag data whereby nodes represent locations and edges between nodes, the movements of individuals. They consider both local and global network properties from an
animal movement perspective and simulate the effects of node disruption as a proxy for habitat disturbance.
Network theory is a well-established theoretical framework and its integration into the fast
developing field of animal movement and telemetry might improve significantly how we interpret animal space use from electronically recorded data.
Long-term datasets yield a great deal of information and are increasingly used to inform conservation measures.
In the first video of the new year, Gary Powney and Tom Oliver show how long-term monitoring data on the Speckled Wood butterfly (Pararge aegeria) from the UK monitoring butterfly scheme can be used to assess functional connectivity of the landscape.
In a paper recently published in Methods, Gary Powney, Tom Oliver and colleagues use synchrony between population counts as a new empirical method to assess functional connectivity – the permeability of landscapes given species dispersal attributes. Functional connectivity is important because well-connected metapopulations are expected to be more resistant to stochastic events causing extinction. They use long-term monitoring data on the Speckled Wood butterfly and find that population synchrony is positively correlated with landscape suitability, suggesting that synchrony might be used to measure functional connectivity.
A key finding is that relatively close populations may exchange sufficient migrants for synchronisation, regardless of the matrix suitability. In contrast, more separate populations are synchronised only where the landscape permits functional connectivity, most likely through dispersal between intermediate stepping-stone populations.
This technique might be used to test and prioritise the effectiveness of land management for conservation of species and to mitigate the effects of climate change.