Code-Based Methods and the Problem of Accessibility

Post provided by Jamie M. Kass, Matthew E. Aiello-Lammens, Bruno Vilela, Robert Muscarella, Cory Merow and Robert P. Anderson

The namesake of our software and founder of the field of biogeography, Alfred Russel Wallace. Photo ©G. W. Beccaloni

The namesake of our software and founder of the field of biogeography, Alfred Russel Wallace. Photo ©G. W. Beccaloni

In ecology, new methods are increasingly being accompanied by code, and sometimes even full command-line software packages (usually in R). This is great, as it makes analyses more reproducible and transparent, which is essential for the development of open science. In an ideal world, code would have informative annotation, generalized functions for multipurpose use, and be written in a legible and consistent manner. After all, the code may be used by ecologists with a wide range of programming experience.

In reality, code is often poorly commented (or not commented at all!), hard to reuse for other projects, and difficult to interpret. To add to that, most code isn’t actively maintained, so users are on their own if they try to commandeer it for new purposes. Further, ecologists with little or no programming knowledge are unlikely to benefit from methods that exist only as poorly documented code. In a positive development, some new methods are accessible through software with graphic user interfaces (GUIs) developed by programmers spending significant time and effort. But too often these end up as tools with flashy controls and insufficient instruction manuals. Continue reading

Editor Recommendation: A Multi-State Species Distribution Modelling Framework for Species Using Distinct Habitats

Post provided by Jana McPherson

© Amélie Augé

© Amélie Augé

Correlative distribution models have become essential tools in conservation, macroecology and ecology more generally. They help turn limited occurrence records into predictive maps that help us get a better sense of where species might be found, which areas might be critical for their protection, how large their range currently is, and how it might change with climate change, urban encroachment or other forms of habitat conversion.

It can be frustrating, however, when species distribution models (and the predictive maps they produce) don’t adequately capture what we already know about the habitat needs of a species. A major challenge to date has been to represent the environmental needs of species that require distinct habitats during different life stages or behavioural states. Rainbow parrotfish (Scarus guacamaia), for example, spend their youth sheltered from predators in mangrove areas before moving onto coral reefs, and European nightjars (Caprimulgus europaeus) breed in heathland but require access to grazed grassland for foraging. Correlative distribution models confronted with occurrence records from both life stages or behavioural modes tend to produce poor predictive maps because they confound these distinct requirements. Continue reading

Multi-State Species Distribution Models: What to do When Species Need Multiple Habitats

Post provided by Jan Engler, Veronica Frans and Amélie Augé

The north, south, east, and west boundaries of a species’ range tell us very little about what is happening inside…

― Robert H. MacArthur (1972, p. 149)

When You Enter the Matrix, Things Become Difficult!

New Zealand sea lion mother and pup. © Amélie Augé

New Zealand sea lion mother and pup. © Amélie Augé

Protecting wildlife calls for a profound understanding of species’ habitat demands to guide concrete conservation actions. Quantifying the relationships between species and their environment using species distribution models (SDMs) has attracted tremendous attention over the past two decades. Usually these species-environment relationships are estimated on coarse spatial scales, using globally-interpolated long-term climate data sets. While they’re useful for studies on large-scale species distributions, these environmental predictors have limited applications for conservation management.

Climatic data were the first environmental information available with global coverage, but a wide range of Earth observation techniques have increased the availability of much finer environmental information. This allows us to quantify species-environment relationships in unprecedented detail. We can now shift the scale that SDMs operate at, resulting in more useful applications in conservation – SDMs now enter the matrix.

This shift in scale brings new challenges, especially for species using multiple distinct habitat types to survive. The landscape matrix, which has been negligible at the broad (global) scale, is hugely important at the fine (local) scale. It is not only that we need to quantify certain habitat types but also need to consider their arrangement in the landscape, which is basically what the landscape matrix is about. But as we enter the matrix, things become difficult. Continue reading

Issue 8.1

Issue 8.1 is now online!

The January issue of Methods is now online!

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.

Continue reading

Biogeography Virtual Issue

Photo © An-Yi Cheng

© An-Yi Cheng

To coincide with the International Biogeography Society’s 2017 conference in Tuscon, Arizona, we have compiled a Virtual Issue that shows off new Methods in Ecology and Evolution articles in the field from a diverse array of authors.

To truly understand how species’ distributions vary through space and time, biogeographers often have to make use of analytical techniques from a wide array of disciplines. As such, these papers cover advances in fields such as evolutionary analysis, biodiversity definitions, species distribution modelling, remote sensing and more. They also reflect the growing understanding that biogeography can include experiments and highlight the increasing number of software packages focused towards biogeography.

This Virtual Issue was compiled by Methods in Ecology and Evolution Associate Editors Pedro Peres-Neto and Will Pearse (both of whom are involved in the conference). All of the articles in this Virtual Issue are free for a limited time and we have a little bit more information about each of the papers included here: Continue reading

Issue 7.4

Issue 7.4 is now online!

The April issue of Methods is now online!

This month’s issue contains two Applications articles and one Open Access article, all of which are freely available.

CPW Photo Warehouse: freely available software that has been customized to identify, archive, and transform photographs into data formats required for statistical analyses. Users navigate a series of point-and-click menu items that allow them to input information from camera deployments, import photos and store data. Images are seamlessly incorporated into the database windows, but are stored separately.

SIMR: An R package that allows users to calculate power for generalized linear mixed models from the lme4 package. The power calculations are based on Monte Carlo simulations. It includes tools for (i) running a power analysis for a given model and design; and (ii) calculating power curves to assess trade-offs between power and sample size.

Continue reading