On the Tail of Reintroduced Canada Lynx: Leveraging Archival Telemetry Data to Model Animal Movement

Post provided by FRANCES E. BUDERMAN

Animal Movement

218 Canada lynx were reintroduced to the San Juan Mountains between 1999 and 2006 with VHF/Argos collars. © Colorado Parks and Wildlife
218 Canada lynx were reintroduced to the San Juan Mountains between 1999 and 2006 with VHF/Argos collars. © Colorado Parks and Wildlife

Animal movement is a driving factor underlying many ecological processes including disease transmission, extinction risk and range shifts. Understanding why, when and how animals traverse a landscape can provide much needed information for landscape-level conservation and management practices.

The theoretical underpinnings for modelling animal movement were developed about seventy years ago. Technological developments followed, with radio-collars initially deployed on large mammals such as grizzly bears and elk. We can now monitor animal movement of a wide variety of species, including those as small as a honeybee, at an unprecedented temporal and spatial scale.

However, location-based data sets are often time consuming and costly to collect. For many species, especially those that are rare and elusive, pre-existing data sets may be the only viable data source to inform management decisions. Continue reading “On the Tail of Reintroduced Canada Lynx: Leveraging Archival Telemetry Data to Model Animal Movement”

Inverse Modelling and IPMs: Estimating Processes from Incomplete Information

Post provided by Edgar J. González

In demography, a set of processes (survival, growth, fecundity, etc.) interacts to produce observable patterns (population size, structure, growth rate, etc.) that change over time. With traditional approaches you follow the individuals of a population over some timespan and track all of these processes.

Demographic patterns and processes (Click to expand)
Demographic patterns and processes (Click to expand)

However, depending on the organism, some processes may be very hard to quantify (e.g. mortality or recruitment in animals or plants with long lifespans). You may have observed the patterns for the organism that you’re studying and, even better, measured some, but not all, of the processes. The question is: can we use this limited information to estimate the processes we couldn’t measure? Continue reading “Inverse Modelling and IPMs: Estimating Processes from Incomplete Information”

Key Technologies Used to Build the plant Package (and Maybe Soon Some Other Big Simulation Models in R)

Post provided by RICH FITZJOHN and DANIEL FALSTER

Our paper in Methods in Ecology and Evolution describes a new software package, plant. plant is an individual-based simulation model that simulates the growth of individual trees, stands of competing plants, or entire metacommunities under a disturbance regime, using common physiological rules and trait-based functional trade-offs to capture differences among species.

Non-Linear Processes and Thousands of Plants

Since the development of gap models in the 1970s (e.g. Botkin 1972), researchers have been using computer simulations to investigate how elements of plant biology interact with competition and disturbance regimes to influence vegetation demography, structure and diversity. Simulating the competitive interactions among many thousands of plants, however, is no easy task.

Despite widespread recognition of the importance of key non-linear processes — such as size-structured competition, disturbance, and trait-based trade-offs — for vegetation dynamics, relatively few researchers have been brave (or daft) enough to try and incorporate such processes into their models. The situation is most extreme in theoretical ecology, where much contemporary theory (e.g. coexistence theory, neutral theory) is still built around completely unstructured populations.

Features of plant

Key processes modelled within the plant package.
Key processes modelled within the plant package.

The plant package attempts to change that by providing an extensible, open source framework for studying trait-, size- and patch-structured dynamics. One thing that makes the plant model significant is the focus on traits. plant is one of several attempts seeking to integrate current understanding about trait based trade-offs into a model of individual plant function (see also Moorcroft et al 2001, Sakschewski et al 2015).

A second feature that makes the plant software significant, is it that is perhaps the first example where a computationally intensive model has been packaged up in a way that enables widespread usage, makes the model more usable and doesn’t  sacrifice speed.

In this post we will describe the key technologies used to build the plant software. Continue reading “Key Technologies Used to Build the plant Package (and Maybe Soon Some Other Big Simulation Models in R)”

Demography Beyond the Population Webinar: Register for Free Now

Webinar logoRegister for FREE for the first ever BES Publishing webinar based on our forthcoming Demography Beyond the Population Special Feature.

This hour long webinar will begin at 1pm (GMT) on Tuesday 1 March. It highlights some of the excellent articles soon to be published in the British Ecological Society journals Special Feature entitled “Demography Beyond the Population”. The Special Feature is a collaborative effort including articles in all six BES journals. This is the first time such a large ecological collaboration has been attempted worldwide. Using a cross-journal approach has allowed us to highlight the strongly interdisciplinary nature of the field of demography to its fullest potential as well as to lay down the foundations for future directions at the interface of ecology, evolution, conservation biology and human welfare. The webinar has several international speakers and will discuss the articles in the Special Feature and the implications for demography research going forward. Continue reading “Demography Beyond the Population Webinar: Register for Free Now”

Issue 7.1

Issue 7.1 is now online!

The January issue of Methods is now online!

As always, the first issue of the year is our sample issue. You can access all of the articles online free of charge. No subscription or membership is required!

We have two Open Access articles and two Applications papers in our January issue.

– Recognizing False Positives: Environmental DNA (eDNA) is increasingly used for surveillance and detection of species of interest in aquatic and soil samples. A significant risk associated with eDNA methods is potential false-positive results due to laboratory contamination. To minimize and quantify this risk, Chris Wilson et al. designed and validated a set of synthetic oligonucleotides for use as species-specific positive PCR controls for several high-profile aquatic invasive species.

– BiMat: An open-source MATLAB package for the study of the structure of bipartite ecological networks. BiMat enables both multiscale analysis of the structure of a bipartite ecological network – spanning global (i.e. entire network) to local (i.e. module-level) scales – and meta-analyses of many bipartite networks simultaneously. The authors have chosen to make this Applications article Open Access.

Gemma Murray et al. provide this month’s second Open Access article. In ‘The effect of genetic structure on molecular dating and tests for temporal signal‘ the authors use simulated data to investigate the performance of several tests of temporal signal, including some recently suggested modifications. The article shows that all of the standard tests of temporal signal are seriously misleading for data where temporal and genetic structures are confounded (i.e. where closely related sequences are more likely to have been sampled at similar times). This is not an artifact of genetic structure or tree shape per se, and can arise even when sequences have measurably evolved during the sampling period.

Our January issue also features articles on Monitoring, Population Ecology, Genetics, Evolution, Community Ecology, Diversity and more. Continue reading “Issue 7.1”

Methods in Ecology and Evolution 2015: The Year in Review

Happy New Year! We hope that you all had a wonderful Winter Break and that you’re ready to start 2016. We’re beginning the year with a look back at some of our highlights of 2015. Here’s how last year looked at Methods in Ecology and Evolution.

The Articles

We published some amazing articles in 2015, too many to mention them all here. However, we would like to say a massive thank you to all of the authors, reviewers and editors who contributed to the journal last year. Without your hard work, knowledge and generosity, the journal would not be where it is today. We really appreciate all of your time and effort. THANK YOU!

mee312268_CoverOpportunities at the Interface between Ecology and Statistics

There was only one Special Feature in the journal this year, but it was a great one. Arising from the 2013 Eco-Stats Symposium at the University of New South Wales and guest edited by Associate Editor David Warton, Opportunities at the Interface between Ecology and Statistics was one of the highlights of 2015 for us. It consists of seven articles written collaboratively by statisticians and ecologists and highlights the benefits of cross-disciplinary partnerships. Continue reading “Methods in Ecology and Evolution 2015: The Year in Review”

Maximising the Exposure of Your Research: Search Engine Optimisation and why it matters

This post is an outcome of the ‘Maximising the Exposure of Your Research’ Workshop at the BES 2015 Annual Meeting in Edinburgh (UK). If you’re interested in joining us for our 2016 Annual Meeting in Liverpool (UK), you can find some more information and pre-register HERE.

© Got Credit
© Got Credit

In recent years there has been a significant increase in the number of academic articles published. At the same time, readers are changing how they find content, tending towards a point of entry at article level as opposed to journal level. These two factors mean that it is increasingly necessary for authors to make their articles easy for relevant readers to find. Search Engine Optimisation (SEO) is one of the best ways to do this.

While writing your paper, there are a few things that you can do to optimise it for search engines, such as Google Scholar. The tips below focus on three areas that are prioritised by search engines when looking for content. Following these tips will help you to maximise the exposure of your research. Continue reading “Maximising the Exposure of Your Research: Search Engine Optimisation and why it matters”

Issue 6.12

Issue 6.12 is now online!

The December issue of Methods is now online! 

Our final issue of 2015 contains one Applications article and two Open Access articles, all of which are freely available.

– stagePOP: A tool for predicting the deterministic dynamics and interactions of stage-structured populations (i.e. where the life cycle consists of distinct stages, for example eggs, juveniles and reproductive adults). The continuous-time formulation enables stagePop to easily simulate time-varying stage durations, overlapping generations and density-dependent vital rates.

Julia Cherry et al. provide one of this month’s Open Access articles. In ‘Testing sea-level rise impacts in tidal wetlands: a novel in situ approach‘ the authors describe the use of experimental weirs that manipulate water levels to test sea-level rise impacts in situ and at larger spatial scales. This new method can provide more robust estimates of sea-level rise impacts on tidal wetland processes. This article was accompanied by a press release when it was published in Early View. You can read more about this article here.

Our September issue also features articles on Biodiversity, Demography, Predator-Prey Interactions, Animal Communication and much more. Continue reading “Issue 6.12”

A Quickstart Guide for Building Your First R Package

Post Provided By DR IAIN STOTT

Iain is a Postdoctoral Researcher at the Max Planck Institute for Demographic Research and the MaxO Center at the University of Southern Denmark. He is currently working as a part of MaxNetAging, a Research Network on Aging. Iain was one of the presenters at the UK half of the Methods in Ecology and Evolution 5th Anniversary Symposium in April. You can watch his talk, ‘Methods Put to Good Use: Advances in population ecology through studies of transient demography’ here.

If you’re anything like me, you might experience a minor existential crisis weekly. As scientists we question the world around us and, for me, this questioning turns all-too-often inwards to my career. I don’t think that’s unusual: ask any scientist about their ‘Plan B’, and the extent to which it’s thought through is often astonishing (if a café-cum-cocktail bar ever opens in Glasgow’s West End, which specialises in drinks that employ spice blends from around the world and are named after old spice trade routes and trading vessels, then you know I’ve jumped the science ship).

Contributing open-source software is something which has made my work feel a bit more relevant and helped me feel a bit less of an imposter. I’ll explain why that is, give some tips to beginners for building a first R package, and hopefully persuade other (especially early-career) researchers to do the same. Continue reading “A Quickstart Guide for Building Your First R Package”

There’s Madness in our Methods: Improving inference in ecology and evolution

Post provided by JARROD HADFIELD

Last week the Center for Open Science held a meeting with the aim of improving inference in ecology and evolution. The organisers (Tim Parker, Jessica Gurevitch & Shinichi Nakagawa) brought together the Editors-in-chief of many journals to try to build a consensus on how improvements could be made. I was brought in due to my interest in statistics and type I errors – be warned, my summary of the meeting is unlikely to be 100% objective.

True Positives and False Positives

The majority of findings in psychology and cancer biology cannot be replicated in repeat experiments. As evolutionary ecologists we might be tempted to dismiss this because psychology is often seen as a “soft science” that lacks rigour and cancer biologists are competitive and unscrupulous. Luckily, we as evolutionary biologists and ecologists have that perfect blend of intellect and integrity. This argument is wrong for an obvious reason and a not so obvious reason.

We tend to concentrate on significant findings, and with good reason: a true positive is usually more informative than a true negative. However, of all the published positives what fraction are true positives rather than false positives? The knee-jerk response to this question is 95%. However, the probability of a false positive (the significance threshold, alpha) is usually set to 0.05, and the probability of a true positive (the power, beta) in ecological studies is generally less than 0.5 for moderate sized effects. The probability that a published positive is true is therefore 0.5/(0.5+0.05) =91%. Not so bad. But, this assumes that the hypotheses and the null hypothesis are equally likely. If that were true, rejecting the null would give us very little information about the world (a single bit actually) and is unlikely to be published in a widely read journal. A hypothesis that had a plausibility of 1 in 25 prior to testing would, if true, be more informative, but then the true positive rate would be down to (1/25)*0.5/((1/25)*0.5+(24/25)*0.05) =29%. So we can see that high false positive rates aren’t always the result of sloppiness or misplaced ambition, but an inevitable consequence of doing interesting science with a rather lenient significance threshold. Continue reading “There’s Madness in our Methods: Improving inference in ecology and evolution”