QAECO’s favourite papers of 2018

An oldy but a goody. We asked our lab members to nominate papers published in 2018 that they enjoyed. We discussed these in a reading group session, and the nominations are listed here for you to explore as well. Happy reading!

Bron, Payal, Martin & David – reading group hosts

Gerry Ryan

O’Kelly HJ, Rowcliffe JM, Durant S, Milner-Gulland EJ (2018) Experimental estimation of snare detectability for robust threat monitoring. Ecology and Evolution 8: 1778 – 1785.
O’Kelly HJ, Rowcliffe JM, Durant S, Milner-Gulland EJ (2018) Robust estimation of snare prevalence within a tropical forest context using N-mixture models. Biological Conservation 217: 75 – 82.

This pair of papers look at snares — indiscriminate, cheap, pervasive, slow-and-painful death for victims; these things are nasty. They’re also difficult to find, and therefore to remove or understand. The papers explore and apply rigorous ecological monitoring techniques to understand how well rangers and researchers can find snares, target searching for them, and better understand the extent of the threat they pose. There’s also a map that won’t do much to improve Vietnam-Cambodia relations.

Jian Yen

Dietze M.C., et al. (2018) Iterative near-term ecological forecasting: Needs, opportunities, and challenges. Proceedings of the National Academy of Sciences USA 115: 1424–1432.

I stumbled across this paper after reading a book by the same author (Dietze 2017, Ecological Forecasting, Princeton University Press). I highly recommend both the paper and the book. The general premise is simple: we can improve ecology as a discipline by being more like weather forecasters. Make lots of predictions on short timescales, check if these predictions are any good, and update our models accordingly. The paper presents a discussion of ecological, technological, and social challenges that stand in the way of good ecological forecasts. To paraphrase the authors, the time to forecast is now.

Nick Golding

Smith AM, Niemeyer KE, Katz DS et al. (2018). Journal of Open Source Software (JOSS): design and first-year review. PeerJ Computer Science 4:e147

Software written by, and for, researchers is critical to modern science, particularly in quantitative ecology. But the people who write the software don’t get academic credit for their work, even if it enables someone else’s publication in a glamour journal. This paper describes a new journal JOSS, which aims to make it easier for people to get credit for their research software. JOSS also reinvents the review and publication process into a much quicker (usually around a month), cheaper ($6 per paper!) and more collaborative experience. As well as clearly outlining academia’s problem with unrecognised research software, this paper provides a glimpse into what the future of academic publishing could look like.

Saras Windecker

Pedersen EJ, Miller DL, Simpson GL, Ross N. 2018. Hierarchical generalized additive models: an introduction with mgcv. PeerJ Preprints 6:e27320v1

I’ve been trying to actively increase the breadth of statistical models I’m familiar with, to open up new ways of analysing complex data. To this end, I really enjoyed this paper by Eric Pederson and colleagues, because it presented complex models in a way a non-statistician could easily digest. The figures excellently illustrate key concepts such as how a GAM is constructed and how grouping levels can be modelled with different formulations of a hierarchical GAM. In addition, the authors do a fantastic job highlighting the model selection choices that need to be made without the aid of sophisticated tools — namely how knowledge of your system and clearly defined aims will often determine the ‘best’ model for your question.

Esti Palma

Pearson DE, Ortega YK, Eren Ö & Hierro JL (2018) Community assembly theory as a framework for biological invasions. Trends in Ecology & Evolution 33: 313-325.

Pearson and colleagues write about two of my passions: community assembly and plant invasions! They do a terrific job merging those two topics on this very clear and easy-to-follow paper. I especially love their net figures and how they highlight the key role of functional traits and human-driven introduction bias to understand invasive species’ success.

Matthew Rees

Legge, S. (2018). Searching for meaning in the interface between research and management. Pacific Conservation Biology24(3), 222-229.

Feeling disillusioned about the practicalities of researching external management programs in the space of my PhD, I made some tea and found distraction in this article. Legge hauled me away to all the wild landscapes where she has worked – places where “it smells of orange peel that has gone dry in the sun; its red rocks are polished by the sound of diamond doves and the feet of rock wallabies and ningbings”. Beautifully synthesising how individual pieces of research have fitted together to inform large-scale, multi-threat management—these musings hit me with some much-needed perspective. I often reread this piece during days like this; a pocket of optimism about where this career may take me.

Jutta Beher

Cinner J (2018) How behavioural science can help conservation. Science 362: 889-890

This paper is a great intro/overview of key cognitive biases and group-dynamic effects that can impact human interaction (e.g. planning and communicating conservation efforts) in ways that are counterproductive. Knowing about these effects and thinking about how to counteract or make use of them, is interesting, and hopefully helpful. It is written well (=easy to understand), and is quite short. I hope I can infect others with the interest to know more about these things with this paper! Also: It is the kind of paper I had envisioned to write, but then was talked into doing a lit review…

Jane Elith

Dormann CF, Bobrowski M, Dehlin DM et al (2018). Biotic interactions in species distribution modelling: 10 questions to guide interpretation and avoid false conclusions. Global Ecology and Biogeography, 27(9), 1004–1016.

This paper grew out of a meeting organised by the first and last authors, Carsten Dormann and Casper Kraan. Carsten is well known for his comprehensive papers tackling major issues in species modelling. I particularly enjoyed this for its advice to modellers using co-occurrence patterns to infer biotic interactions. Because it can be challenging to work out whether species associations are due to biotic interactions or other things, the authors detail ten questions that help guide modellers through a rigorous thought-process and analytical approach to help them make sound conclusions from their models.

Bronwyn Hradsky

Neilson EW, Avgar T, Burton AC, Broadley K, Boutin S (2018) Animal movement affects interpretation of occupancy models from camera-trap surveys of unmarked animals. Ecosphere 9: e02092

This paper uses a neat simulation model to tackle some questions that have been buzzing in the back of my brain for years: what does “occupancy” mean in a camera trapping context? How is it influenced by home range size and mobility?  Neilson et al. show that adjusting for imperfect detection can lead to biased estimates if animals have large home ranges. The direction of bias depends on the species’ movement speed (positive if the animals move quickly, negative if they move slowly). They emphasis that the interpretation of “occupancy” depends on the processes underlying the detection history, including movement and density (which may change between survey seasons or regions), and suggest the importance of exploring spatial and temporal correlations inherent in this type of data.  Although the authors don’t come up with definitive solutions to these problems, the subsequent citing papers also make interesting reading.

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What is HPC and why would I use it?

—————————————————————————————————————————————-Given the recent focus of the coding club sessions on all things boab and HPC, we thought a post on what-the-H is HPC would do us all some good. So, read on if you’re curious, confused or confident. There’s something in it for everyone.

Do you dread the word big data? Does parallel computing make your palms sweaty? For those of you trying to convince yourselves you’re braver than that, let’s see how you roll with…high performance computing, servers, slurm! Yikes!


You are not alone. Almost everyone in QAECO and the School of Biosciences is grappling with these very fears.

So, what is so scary? We’re all scientists after all and are trained to take on the new and beat it into submission with experiments and theory. Well for a start, we don’t understand the terminology used in this space and find it difficult to articulate what we want to do with it.“It” is the great unknown, which makes it scary.

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Kickstarting the year with HGAMs

To start off Reading Group for 2019, we dove headfirst into 43 brilliant pages on hierarchical generalised additive models (HGAMs) by Pederson et al. 2018, a pre-print titled Hierarchical generalised additive models: an introduction with mgcv. Although at first intimidated by the subject matter and length of the reading, we found that the paper presented rather complicated statistical models in a series of extremely approachable explanations and R code. Talk about speaking our language! So, what are HGAMs, when might we use them instead of other models such as nonlinear models, and what else did we take away from this reading?

IMG_4423 2

“And this is what a GAM is!” Saras’ happy scribbling during reading group.

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Philosophical discussions in the lab: Žižek criticises ideological ecology

In a recent reading group, QAECO discussed a criticism of ecology from the contemporary philosopher Slavoj Žižek, as represented in two online resources:

Slavoj Žižek [photo by By Amrei-Marie, from Wikimedia Commons]

Žižek is a strongly left-leaning critic of societal issues, who thinks many of society’s problems stem from an era of ideology. Žižek views ecology as one such ideology, believing that ecology “takes real problems and mystifies them”. He contends that ideologies provide an escape from real societal challenges and are a hindrance to true social progression. What makes him view ecology in such a light?

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Wanting to learn about Species Distribution Modelling? Consider enrolling in our online subject! – running again soon (Jul/Oct 2018)

Are you interested in modelling? Are you a graduate student, and your project involves studying species distributions? Or maybe you are a research professional or a manager wanting to expand your quantitative skills?

Species distribution modelling is one of the most highly cited areas of ecological research. And it is not just about research; species distribution models are also very useful for supporting a wide range of environmental decisions. So why not learn more about them?

At the University of Melbourne, we run a graduate subject on Species Distribution Modelling, delivered entirely online. The subject is offered to externals through the university’s Community Access Program (CAP). Through this program, you may choose to study in either assessed or non-assessed mode (costs are 3696AUD for non-assessed mode; 4612 for assessed mode). The subject runs this year from 23 July to 21 October (final assessments due around mid Nov).

The subject covers species distribution modelling from two different angles, ecophysiological models and correlative models (GLMs, Maxent, BRTs…), and consists of video lectures and guided computer practicals in R. The content emphasises an understanding of the problem, the data, and the model, and provides practical skills in fitting the models. The subject team includes Mike Kearney and Jane Elith, two internationally recognised experts in the field!

Tempted? Get in touch if you are; we will be happy to answer your queries. Please email José, the subject coordinator (

For information about the subject and the CAP program see:

Please spread the word through your networks!! Thanks!

The SDM subject team,

Mike, Jane, Guru and José

José Lahoz-Monfort


Enquiries about the application process should be directed to or the 13MELB phone line.

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Grappling with reproducibility in science?

As a lab, we’ve made it a priority to increase the standards of our code to align with best practices for reproducibility and repeatability of our science. In keeping with this goal, this week in reading group Saras Windecker and Hannah Fraser lead a discussion on the British Ecological Society’s Guide to Reproducible Code in Ecology and Evolution, measures on how we can implement these guidelines in our research and the barriers that limit their uptake within the QAEco group. Here is a brief summary of that discussion.

The BES guide details workflow and project structure, version control, and techniques for defensive coding. While many of us already implement all or some of these suggestions into our workflow, it is by no means universal. Moreover, the QAEco group has a steady intake of new students, for whom these skills are, for the most part, completely new.

Whether a beginner or a veteran at maintaining ‘good’ workflows, we found over the course of the discussion that there are two major barriers to the uptake of reproducibility recommendations: lack of availability of resources/time, and fear/sense of intimidation to taking the plunge in to the great unknown of workflows, version control and GitHub!

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Qaeco’s favourite papers of 2017

We asked our lab members to nominate a paper published in 2017 that they had enjoyed. Recommendations ranged from the skill-based (scientific writing, reproducible coding, camera-trapping) to global reviews (plant traits, climate change, size-based models) and some great case studies (questionable psychologists, waterbirds at Lake Eyre, Finnish foxes).  We hope you find them as interesting as we did!

– Kate & Bron, hosts of QAECO Reading Group

Natasha Cadenhead

Doubleday, Z.A. & Connell, S.D. (2017) Publishing with objective charisma: breaking science’s paradoxTrends in Ecology & Evolution32, 803-805.

At the risk of sounding a little too Eat, Pray, Love, 2017 was a year in which I decided to try and actively improve my scientific writing. Not only is there an inherent joy to reading a well-written paper, but it makes the scientific message within that much clearer. Doubleday & Connell’s (thankfully, eloquent) paper recognises the problem with much of scientific writing – we spend a lot of our time doing it, but we’re never taught how to do it in an engaging way. They run through some steps for bringing out that charismatic “Ingredient X” in your writing, without falling prey to sensationalism. On this topic (although less science-focused) I would also recommend anything by the excellent Helen Sword.

Dave Duncan

Watson, D.M., Doerr, V.A.J., Banks, S.C., Driscoll, D.A., van der Ree, R., Doerr, E.D. & Sunnucks, P. (2017) Monitoring ecological consequences of efforts to restore landscape-scale connectivity. Biological Conservation, 206, 201–209.

My favourite paper from this year is the culmination of a monitoring framework I saw presented by one of the authors back in about 2015.  The article sets out a framework for thinking about the design of monitoring activities for projects whose intention is to restore connectivity at landscape scales.

Now, you might be saying to yourself: does the world really need another monitoring framework? Sadly, apparently yes. Well that and some kind of institutional revolution on the other side of which we actually implement some of these great ideas.

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