Statistical and quantitative methods within ecology have increased substantially in recent years. This rise can be attributed both to the growing need to address global environmental change issues, as well as the increase in data sources to address these challenges. Continue reading →
This double-size issue contains six Applications articles (one of which is Open Access) and two Open Access research articles. These eight papers are freely available to everyone, no subscription required.
–Temperature Manipulation: Welshofer et al. present a modified International Tundra Experiment (ITEX) chamber design for year-round outdoor use in warming taller-stature plant communities up to 1.5 m tall.This design is a valuable tool for examining the effects of in situ warming on understudied taller-stature plant communities
–Zoon: The disjointed nature of the current species distribution modelling (SDM) research environment hinders evaluation of new methods, synthesis of current knowledge and the dissemination of new methods to SDM users. The zoon R package aims to overcome these problems by providing a modular framework for constructing reproducible SDM workflows.
–BEIN R Package: The Botanical Information and Ecology Network (BIEN) database comprises an unprecedented wealth of cleaned and standardised botanical data. The bien r package allows users to access the multiple types of data in the BIEN database. This represents a significant achievement in biological data integration, cleaning and standardisation.
Today is the first day of peer review week. One of the issues that many people bring up about the current system of peer review is that there is very little formal training. There are guidance documents available (including the BES Guide to Peer Review), workshops on peer review can be found at some conferences and some senior academics teach their PhD students or post-docs about the process. In general though, peer review training is fairly hard to come by.
This is something that people have told us (the BES publications team) at conferences and through surveys, so we’re doing something about it. From October 2017 until April 2018 Methods in Ecology and Evolution is going to be partnering with the BES Quantitative Ecology Special Interest Group to run a trial Peer Review Mentoring Scheme.
The trial scheme is going to focus on statistical ecology (as we receive a lot of statistical papers at Methods in Ecology and Evolution), but if it goes well, we’ll be looking at other areas of expertise too.
Applications for Mentor and Mentee positions are now open. If you’re an experienced statistical ecologist or evolutionary biologist or an Early Career Researcher in those fields, we’d love to receive an application from you. Continue reading →
BACIPS (Before-After Control-Impact Paired Series) is probably the best-known and most powerful approach to detect and quantify human interventions on ecosystems. In BACIPS designs, Impact and Control sites are sampled simultaneously (or nearly so) multiple times Before and After an intervention. For each sampling survey conducted Before or After, the difference in the sampled response variable (e.g. density) is calculated. Before and After differences are then compared to provide a measure of the effect of the intervention, assuming that the magnitude of the induced change is constant through time. However, many interventions may not cause immediate, constant changes to a system.
We developed a new statistical approach – called Progressive-Change BACIPS (Before-After Control-Impact Paired-Series) – that extends and generalises the scope of BACIPS analyses to time-dependent effects. After quantifying the statistical power and accuracy of the method with simulated data sets, we used marine and terrestrial case studies to illustrate and validate their approach. We found that the Progressive-Change BACIPS works pretty well to estimate the effects of environmental impacts and the time-scales over which they operate.
The following images show the diversity of contexts in which this approach can be undertaken.
Moorea is an island located in French Polynesia. It’s known for its extraordinary marine biodiversity, but also for the great, natural spatial and temporal variability due to recurrent external forces. This place, and the statistical challenges it represents, has provided us with a wealth of inspiration in formulating our Progressive-Change BACIPS approach to environmental impact assessment.
Unlike classic experimental studies like this one, environmental impacts are not (and often should not) be replicated.
Recurrent disturbances such as Crown-of-Thorns Starfish (Acanthaster planci) outbreaks are important drivers of declines and recoveries in coral reef ecosystems. How can we reliably estimate the effect of local human interventions (for example marine protected areas, MPAs) amid such noise?
Here, a scientist is counting fish where a MPA will be implemented using a Diver-Operated Video system. Repeated assessments before enforcement provide an estimate of the spatial variability between the Control and Impact sites in the absence of an effect of the MPA.
A change in the difference in density between the Control and Impact sites after the establishment of the MPA provides an estimate of the local effect of the MPA. This is the BACIPS design.
Progressive-Change BACIPS uses these data to inform the form of the final model. Many models can be tested such as step-change, linear, asymptotic or logistic models – whatever that seems appropriate. This coral reef application was just one of the many possibilities to measure environmental impacts that our tool can reveal when applied to BACIPS data.
We have also applied it to other study contexts – such as the effect of highway construction on the abundance of birds. Here is an Andean condor (Vultur gryphus) flying away after the passage of a car.
This method is also well suited to forest ecosystems, for example to study the effect of increasing tourist visitation on this ancient Araucaria (Araucaria araucana) forest in Chile.
As long as data collected before and after, inside and outside the impacted area, exist Progressive-Change BACIPS is an excellent statistical approach to estimate the effects of environmental impacts.
Evelyn Chrystalla ‘E.C.’ Pielou (February 20, 1924 – July 16, 2016) – a towering figure in ecology – was a key pioneer in the incorporation of statistical rigor into biogeography and ecology. She devised many important statistical hypotheses tests for spatial arrangements and patterns ranging in scale from individual plants in a field through to elevational zonation of vegetation to ranges of groups of species distributed over regional through to continental-scale ranges. Her research has provided the impetus for biogeographical analyses for generations.
She published ten books, including several long after her formal retirement in 1988. Her book Biogeography (1979) is a masterpiece. It covers historical biogeography (including inferences from cladograms, which were just beginning to be a hot topic at that time) and ecological biogeography with keen insight and treats topics like long-distance dispersal (that had largely been the subject of just-so stories) with her characteristic statistical rigor. Her books on mathematical ecology have a strong emphasis on models of spatial pattern and ways to estimate biodiversity, and her methods – including the famous Pielou‘s evenness index – are still widely used.Continue reading →
This month’s issue contains four Applications articles and two Open Access articles, all of which are freely available.
– iNEXT: The R package iNEXT (iNterpolation/EXTrapolation) provides simple functions to compute and plot the seamless rarefaction and extrapolation sampling curves for the three most widely used members of the Hill number family (species richness, Shannon diversity and Simpson diversity).
– camtrapR: A new toolbox for flexible and efficient management of data generated in camera trap-based wildlife studies. The package implements a complete workflow for processing camera trapping data.
– rotl: An R package to search and download data from the Open Tree of Life directly in R. It uses common data structures allowing researchers to take advantage of the rich set of tools and methods that are available in R to manipulate, analyse and visualize phylogenies.
– Fluctuating-temperature chamber: A design for economical, programmable fluctuating-temperature chambers based on a relatively small commercially manufactured constant temperature chamber modified with a customized, user-friendly microcontroller.
This month’s issue contains two Applications articles and two Open Access articles, all of which are freely available.
– Plant-O-Matic: A free iOS application that combines the species distribution models with the location services built into a mobile device to provide users with a list of all plant species expected to occur in the 100 × 100 km geographic grid cell corresponding to the user’s location.
– RClone: An R package built upon genclone software which includes functions to handle clonal data sets, allowing:
Checking for data set reliability to discriminate multilocus genotypes (MLGs)
Ascertainment of MLG and semi-automatic determination of clonal lineages (MLL)
Genotypic richness and evenness indices calculation based on MLGs or MLLs
Describing several spatial components of clonality
This month’s issue contains one Applications article and two Open Access articles, all of which are freely available.
– POPART: An integrated software package that provides a comprehensive implementation of haplotype network methods, phylogeographic visualisation tools and standard statistical tests, together with publication-ready figure production. The package also provides a platform for the implementation and distribution of new network-based methods.
Michalis Vardakis et al. provide this month’s first Open Access article. In ‘Discrete choice modelling of natal dispersal: ‘Choosing’ where to breed from a finite set of available areas‘ the authors show how the dispersal discrete choice model can be used for analysing natal dispersal data in patchy environments given that the natal and the breeding area of the disperser are observed. This model can be used for any species or system that uses some form of discrete breeding location or a certain degree of discretization can be applied.