#BES2016 Quantitative Ecology SIG events

With just a few days until BES2016 kicks off in Liverpool, here’s a handy guide to the events we have organised for the conference:

Best Practice for Code Archiving

Sunday 11th December 12:00 – 17:00

Interested in how to distribute and archive code? Join Methods in Ecology and Evolution Editor Rob Freckleton, along with several experts with backgrounds in programming and ecology to provide practical discussion of writing and sharing code for your research. All levels of expertise are welcome, especially those just starting out.

The workshop will be introduced by Natalie Cooper who will explain why reproducible code is important and give an overview of the rest of the workshop. We will then have three breakout sessions giving participants practical training in best practice for using code in ecology research. We will focus on quality, functionality, robustness and usability. Breakout groups will be led by code experts Mike Croucher, Laura Graham and Tamora James.

Finally, participants will have the opportunity to input into the development of new guidelines for archiving code for publication, which are currently being developed by the BES journal Methods in Ecology and Evolution. Journal Editor Rob Freckleton will introduce the new guidelines and lead a discussion on how they can best serve the community.

 

Lunch will be available from midday and tea and coffee will be provided.

 

Wikithon: Quantitative Ecology Documentation (QED)

Tuesday 13th December 1:15 – 2:45

Dominic Bennett, Institute of Zoology, London

We’ll be running a WIKITHON workshop at this year’s BES annual meeting conference for our wiki, Quantitative Ecology Documentation. The aim of the wiki is to help foster communication between ecologists on all things computational and quantitative in ecology, a “how I did this in R” pinboard of links, code and empathetic encouragements. Documents on the wiki can be very simple, “best ways to read data into R” very complex, “how to develop your own IBMs”, or even very original, “best ways to relax after extended and frustrating coding sessions”. At the workshop we’ll be demonstrating the new wiki and providing training on how to edit and create new pages. Then, the wikithon will commence! Attendees can write their pages based on a list of suggestions, or you can come up with your own ideas. (Oh plus…. the workshop may be featuring the, highly acclaimed, wikipedia music!)

 

Macroecology and Quantitative SIG joint mixer

Tuesday 13th December: Meet in the registration area at 18:20 or at the Pump House at 18:30

This year there will be a joint social between the quantitative and macroecology groups. We will be meeting at 18:20 in the reception and making our way over as a group. If you’re coming later, the Pump House is 5 mins walk from the conference centre; it can’t be missed! It’s the redbrick building with the large Victorian chimney. Activities include: informal networking, alcohol consumption, awkward standing around plus the possibility of laughter (N.B. please provide your own jokes/gags/amusing anecdotes). Oh, by the way, drinks are on us!

 

Additionally, committee member Robert Salguero-Gómez (University of Sheffield), is running a workshop on Monday 12th DecemberMacro-ecology through the lens of comparative demography.

A handy guide to How to survive the BES Annual Meeting has been provided by Markus Eichhorn. Enjoy!

 

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Meeting report: Point Processes for Ecology June 2016

Much of the data we collect as ecologists can be plotted as dots on a map. These dots might represent the locations of individual trees or plants, or places where more mobile animals have been spotted. Spatial point pattern data like these are widely used to estimate abundance, map species distributions, and to understand movement behaviour and habitat preferences. Ecology has developed a suite of methods for analysing these point pattern data, often by aggregating the points together into counts, or considering the point locations as presences in presence-absence analyses (with workarounds to conjure up appropriate absence records).

Over roughly the same period, the statistics research community has developed a cohesive framework for considering point data: point process models (PPMs). Spatial PPMs consider the entire pattern of dots as arising from some spatial process. This process might be a continuous ‘intensity surface’ describing how many dots we would expected to see in a given area, or some mechanism by which the points interact with one another to generate the pattern.

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From the middle distance, Janine Illian (University of St. Andrews) recaps some of her recent PPM research

 

In the last few years, papers in the ecology literature have started to draw links to these PPM approaches, and apply them to ecological problems. The popular species distribution modelling (SDM) approach MaxEnt is equivalent to a PPM, and many other SDM approaches are similar to PPMs. Spatial capture recapture and density surface models have been developed which use point processes to estimate abundance from observations of individual locations. Point process models have also been applied to infer habitat preferences from telemetry data.

In June of this year, the Quantitative Ecology SIG sponsored a working group meeting to discuss recent advances in ecological PPMs and identify hurdles to the models being used more widely in ecology. The meeting; Point Processes for Ecology: State of the art and next steps (held in Seattle to coincide with the ISEC 2016 conference) brought together 20 experts in PPMs, analysing ecological point data, and developing statistical software. We wanted to unite people working on PPMs in different corners of ecology, so we deliberately invited researchers who hadn’t previously worked together. Judging by the co-authorship network below, I think we did a decent job of that.

Co-authorship network of workshop attendees – links between people indicated they had previously published papers together. Most of the workshop attendees hadn’t worked together before and were meeting one another for the first time.

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Co-authorship network of workshop attendees. Links between people indicate they had previously published papers together. Most of the workshop attendees hadn’t worked together before and were meeting for the first time.

After kicking off the meeting with the usual introductions and presentations of our own PPM interests, we had an open discussion of what we thought is stopping ecologists from using these advances in their work. This brainstorming session led to a whole lot of messy scribbling on blackboards and, after the chalk dust had settled, we arrived at two broad areas that most needed work to advance ecological PPMs: increasing understanding, and developing tools.

Increasing Understanding

One of the major barriers to uptake of PPMs in ecology is a lack of familiarity with the PPM literature. Despite the high level of statistical literacy in ecology, and ecologists’ wide uptake of similar statistical approaches, most of the ecologists we had spoken with are not at all familiar with PPMs. Getting the message out there with ‘explainer’ papers in the ecological literature is one way of doing that. These sorts of papers have been hugely effective for communicating new methods in the world of species distribution modelling, and a recent paper (by some of the workshop attendees) has done the same to communicate PPM methods to SDM researchers.

We reckon there’s plenty of space for more PPM explainer papers in other areas of ecology, and we settled on a couple of key topics. These include: the benefits of interpreting and explicitly modelling species presence/absence data as arising abundances, rather than some loosely defined probability of presence (a fundamental principle of the PPM approach); ways in which different data types (such as counts, presence/absence surveys and camera trap data) can be combined into a single analysis using PPMs; and the methods that have been developed in the statistical literature for evaluating point pattern models and data.

Developing Tools

Understanding how PPMs work and why they are useful is a critical first step for helping ecologists use these methods. However new methods are useful if ecologists have the tools to apply them. In the case of PPMs, there’s some work to be done making software both available and usable for ecologists. Whilst there is already some great software out there for modelling of point patterns (such as the spatstat and INLA R packages), most of this is targeted at statisticians. Developing software that fits ecologists’ needs, and can be used to answer ecological questions would help us to overcome the technical barriers to PPM uptake.

Specifically, there’s a need to be able to fit PPMs to large, broad-scale ecology datasets efficiently, so a comparison of current and novel methods in that area would be useful. Providing a user-friendly interface to existing and new PPM methods in R (the lingua franca of quantitative ecology) would also be helpful. Linking up a package like that with the ‘explainer’ papers on data integration and model evaluation would ease the route into PPM modelling for ecologists.

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Just some of the scribbling on one of many blackboards.

After defining these broad areas for future work, we started fleshing and setting up some of these projects, and even broke some ground writing manuscripts. Hopefully it won’t be long before the co-authorship network becomes a lot more connected. As well as working on these projects, we’re also very keen to hold more events on ecological PPMs in the future; both more working groups and symposia that so that more people can join us. So keep an eye out for more PPM events and papers in the near future!

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The nearest we got to a group photo; relaxing in the sun at Gasworks Park, Seattle

Links round-up: 09/09/2016

We now have a new logo! In the spirit of openness, Nick Golding has shared the code he used to create these logos: network image and triangulation image

Methods in Ecology and Evolution brought out a Statistical Ecology Virtual Issue to go along with this summer’s International Statistical Ecology Conference.

There is now a package to interface with the > 1000 geoalgorithms from QGIS within R: RQGIS. Jamie Afflerbach has written a more general spatial analysis in R tutorial.

QAEco have written about their favourite R packages to use for ecological data analysis – let them know your favourite packages in the comments.

Events

Last day to register for the BES Macroecology SIG’s Early Career Event (NB, will be very general and not just for macroecologists, or even ecologists), 16th September 2016, London.

Challenges and Opportunities of analysing ecological citizen science data, 10th October 2016, Cambridge.

Courses

Applied Bayesian modelling for ecologists and epidemiologists. 24-29 October 2016. PR Statistics, Loch Lomond, Scotland.

Geometric morphometrics in R. 23-27 January 2017. Transmitting Science, Barcelona, Spain.

Data analysis in ecology. Online 5 week course provided by University of Oxford from 2nd November 2016.

Jobs

Postdoc at Ghent University, Belgium: Scaling up functional biodiversity research.

Postdoc and PhD positions available in the Pinsky Lab at Rutgers University, New Jersey: Metapopulation dynamics and population genomics.

Several Assistant Professor positions at University of Zurich, Switzerland.

Two PhD positions in the Pearse Lab, Utah State University: (1) ecological and/or evolutionary modelling, (2) plant ecology and fieldwork.

Call for Catalyst Postdocs at sDiv, Leipzig, Germany is now open.

Spatial Scientist and GIS analyst positions available in the Land Use and Ecosystem Services Science Group at Forest Research, Roslin, Scotland.

Links round-up: 17/06/2016

Events

People, politics and the planet: any questions? A debate on UK environmental policy in the aftermath of the EU referendum. 21st July 2016 at Royal Geographical Society (with IBG), London.

Registration and abstract submission is now live for the BES 2016 Annual Meeting. 11-14th December 2016, Liverpool.

Courses

Bayesian integrated population modelling using BUGS and JAGS. 12-16th December 2016 at Swiss Ornithological Institute.

Importing data into R Webinar. 22nd June 2016. Online, provided by RStudio.

Introduction to Bayesian hierarchical modelling using R. 23-16th August 2016, Loch Lomond, Glasgow.

Jobs

Senior Research Associate/Research Associate at Lancaster University. Computational environmental science (models in the cloud).

Postdoc at Centre for Macroecology, Evolution and Climate, Copenhagen. Community and ecosystem ecology.

 

Links round-up: 20/05/2016

Miller et al. have put together a review of the use of metrics and null models in community phylogenetics. They review a total of 278 metric/null model combinations and find that these are in fact 72 true unique combinations. They also find that the choice of null model is more influential over type I error rates than the choice of metric. The paper comes with an accompanying R package – metricTester – which allows for testing of method performance.

Lefcheck presents a new R package – piecewiseSEM – which is a structural equation modelling package designed with its uses in ecology, evoluation and systematics in mind. The paper contains two worked examples including code.

Events

Statistical Ecology Research Festival. 7th June, University of Kent, Canterbury.

IALE UK 2016 Conference: landscape characterisation – methods and applications in landscape ecology. 7-9th September, University of Reading.

Courses

Genetic data analysis using R. 16-20th August, Isle of Cumbrae, Scotland.

The use of phylogenies in the study of macroevolution. 19-23rd August,  Facilities of the CRIP at Els Hostalets de Pierola, Barcelona.

There’s also still time to sign up for our Data Management in R course on Monday (23rd May) at Charles Darwin House in London.

Jobs

Postdoctoral research assistant at University of Oxford. Human modified tropical forests.

Postdoc at CIBIO-UE, University of Évora. Modelling food web architectures under climate change.

Reader/Senior Lecturer/Lecturer at Queens University Belfast. Three positions: global change biology, agro-ecoinformatics and genetics and molecular biology.

Research Associate at CEH, Wallingford. Ecological modelling of pathogens threatening humans, animals, plants and ecosystems.

Data management in R course

There are still a few days left to sign up for our data management in R course. It’s next Monday (23rd May) at Charles Darwin House in London.

Sign up here!

This event is aimed towards participants with a basic knowledge of R who want to learn more about how to import and manage data within R. Participants will learn about a) how to get data into R (e.g. reading in from databases, other programmes and spatial data), b) how to manipulate single datasets (e.g. data formats, reshaping, sorting, outlier checks), c) how to work with multiple datasets (e.g. SQL in R) and d) methodologies for efficient data management in R (e.g. storing metadata, version control and workflows). Participants will need to bring their own laptops with an up to date version of R installed.

Links round-up: 08/04/2016

The Stan website now has a section detailing case studies – these are intended to reflect best practices in Bayesian methodology and Stan programming. Users can contribute their own case studies. On a related note, Hiroki ITÔ has translated some of the code from Kéry and Schaub’s Bayesian Population Analysis to Stan (chapters 3 – 9 so far, with the rest currently in the works).

Noam Ross has put together some crowdsourced resources on reproducible project organisation. Contains lots of useful links to further advice and discussion on project directory organisation.

SESYNC issue a call for proposals for collaborative & interdisciplinary team-based research projects.

Courses

Advances in DNA taxonomy, 8th – 11th August 2016, Loch Lomond, Scotland.

Jobs

PhD at Center for Macroecology, Evolution and Climate in Copenhagen. Using citizen science to examine behavior, resource use, biodiversity, and distributions of ants in Denmark.

Water resources model developer at James Hutton Institute, Aberdeen.