​by Losia Lagisz
 
Get right tools for the right jobs. Surprisingly, decision trees are seldom mentioned in the context of systematic reviews / meta-analyses (I will use the latter term thereafter). An obvious application is to use decision trees to streamline screening of hundreds and thousands of publications found in online databases of academic literature.

​It is easiest to imagine them as a list of interlinked questions, where each answers leads you to the next appropriate questions. More formally, they are a structural representation (usually visual) of a series of decisions that have to be made. When screening literature, we need to assess each paper against all our pre-defined inclusion criteria. These criteria, expressed as a series of questions, naturally form a backbone of a linear decision tree. It is easy to build a decision tree if we break our inclusion criteria according to PICO (or similar) components of our research question. Thus, a generic decision tree for screening literature would look like this:

​by Losia Lagisz

Finding full texts of articles takes time. Especially when if you need to locate hundreds of pdf files and attach them to bibliometric records in a reference manager. Although some reference managers claim to have capacity to automatically locate full texts, the actual retrieval rate can be quite low. For example, in EndNote it can be less than 10% of the records. Zotero seems to be doing much better. Below, I show the most efficient workaround I am currently aware of.

1. Use Zotero desktop.
It is a free reference manager, but you may need to pay for extra storage if you use it extensively. It also has a web-browser counterpart, browser plug-ins that help harvesting citations from webpages, plugins for text processors and cloud-based storage. Overall, Zotero offers great functionality, but it can get quite slow when working with big volumes of data.
​
2. Install Zotero DOI Manager plug-in.
It checks, reformats and fills in missing DOI. Actually, the package is called shortDOI and it can be found at https://github.com/ethanwillis/zotero-scihub/releases. Download the latest release as an .xpi file (in Firefox try to right click on the .xpi file and select "Save As..."). Back in Zotero, select from the top menu: Tools -> add-ons -> Tools for all Add-ons (upper right) -> Install from file. Then point to your downloaded .xpi file. Zotero will ask you to allow it to restart.

3. Find pdf full texts using DOI. Only publicly available full-text files will be found and added to the records (so it may work differently from university and from home, as via university address you will have access to many more pdfs). To run the search, highlight the records you want to find pdfs for and right-click the selection to display the floating menu. From the menu select “Find Available PDFs” (first from the top):

Test workflow
1. Install and set up the DOI Manager plugin in desktop Zotero.
2. Use Scopus to find 74 records of papers published by Shinichi that mention meta-analysis in title, abstracts or keywords: TITLE-ABS-KEY ( meta-analy* )  AND  ( LIMIT-TO ( PREFNAMEAUID ,  "Nakagawa, S.#55949096500" ) ). You can use any other set of records.
3. Export all records to a .ris file and uploaded this file into a new Zotero library: Zotero -> File -> Import -> From file -> select downloaded .ris file -> and ask to place it in new collection. Long DOIs were be automatically updated by the DOI plug-in during the upload.
4. Run automatic Zotero search: highlight all records, right-click and select “Find Available PDFs“. This step is going to take a while, depending on your Internet connection speed and the number of records.
 
I was able to find 42 full texts (Open Access only, since I was not at the university) out of 74, which is quite good. Working from university I could probably get 100% or close.

by Dom Mason

Sometimes, scientists travel far and wide to communicate their hard work (or so I’m told) and further the spread of scientific knowledge. Alas, we didn’t have to travel very far at all to attend the Australasian Evolution Society (AES) 2019 conference. Held at the UNSW Roundhouse in late November, it was a great way to cap off the year that was.

​Being my first conference, I was pleasantly surprised when I saw it was catered. It turns out delicious spreads have an uncanny ability to take your mind off how you forgot to say that one important thing in your talk. Just be careful not to take any pastries before morning tea officially begins – I can say with great confidence that you will be told off. Good food, great talks, amazing people, it seemed to me to be a sort of festival for scientists. On a whole, it reminded me of a music festival. There were unfortunate clashes with who I wanted to see, and friends leaving the group to go to different rooms. People pushing in line… I mean waiting in line, and the excitement of seeing a performance that I didn’t plan to see but still being blown away by them.

And the headlining acts (plenary talks), seamlessly confirmed why they were chosen to speak at this conference. From the humour of using modern scientific methods to find the loch ness monster, to the ethics of using gene drive to reduce or eliminate wild populations, and the importance of the fluctuation of inflammation during pregnancy from an evolutionary perspective. A common theme of bringing together different fields of science for a common goal was clear. It was truly inspiring to be given an insight into the work of not only the distinguished scientists but also early career researchers who gave talks to conclude each day; fortifying that great achievements can arise from novel and creative thinking.
 
Sharing the same stage, so to speak, as these researchers and esteemed professors was a great experience, especially if you were fortunate enough to keep their crowd for your talk. This unity projected a real sense of community. To me, this was confirmed during casual discussions, where I heard about exciting new projects or funny asides about trivial scientific concepts. I would deem these interactions to be the best part of the conference; getting to know scientists and other students on a casual level. It was like having a backstage pass to your favourite festival, being able to stand next to the shoulders of giants. And when people I look up to told me that I did well in my talk, it made the experience that one bit better.

If I didn’t spend too much time at the cheese platter during the breaks, I was talking to people about their studies. And to my surprise, I was approached by a student during lunch and asked a question about my talk. It was a great feeling to have someone interested in my study and being able to explain concepts that for me have become second nature. One last thing I can’t ignore is the quality and diversity of our labs talks. It seems we may have every evolutionary biology field covered (except phylogeny but I’m not too sure even phylogeneticists have that covered). With all this in mind, I would have to say this conference was a hit and I’m keen for the next one! I just have to save for a ticket, wait for the line-up, see which of my friends are going then plan my outfit.

by Hamza Anwer

I’ve always told people that straight roads don’t make good drivers. Why? Because, in the context of life, a straight road is an illusion, it doesn’t exist. While this analogy may sound overly dramatic, I’ve always held it in great regards. I hardwired this belief into me, because I knew there will be times when I would have no choice but to display resilience and think about long-term success over short-term satisfaction.  My resilience was on show the minute I ruptured my anterior cruciate ligament playing football. The anterior cruciate ligament runs through the middle of the knee, providing rotational stability to the joint. My foot got stuck in the mud when I went to change direction, as a result, there was a twist with excessive force, and I heard a loud pop. I was on the floor in agony, and had to be carried off the field. I couldn’t walk but out of pure resilience and emotional adrenaline, I drove myself to the hospital. I had an MRI and it confirmed what I had feared the most (see my MRI scan below). ACL injuries are so dreaded because of the lengthy process is takes to come back from them (minimum 6-9 months of hard work for a full recovery).

Following surgery, I took the steps to heal, physically, mentally, and emotionally. I didn’t want to make excuses, I just wanted to put my head down and work knowing it would pay off… and it did, my resilience worked wonders. It seemed so long ago that I was on crutches, unable to walk, but I feel stronger than ever, and my PhD is in a good place. There are good times ahead and I’m excited for what the future holds.

Straight roads don’t make good drivers… so, when you come at an unexpected turn, take some time to reflect, and invest on what you need to do to continue your journey. You will always be better for it.

by Losia Lagisz and Joanna Rutkowska

For the occasion, we decided to make a poster that can be used to promote EcoEvoRxiv. The poster summarises  already submitted preprints and gives basic info about EcoEvoRxiv. Feel free to use the poster (pdf file)!

by Losia Lagisz and Shinichi Nakagawa

A recent paper by Brady et al. (2019) gives an excellent overview of  biological maladaptation. The 9 main scenarios of biological maladaptation are explained by using an archery metaphor. Accompanying figure (below), illustrates how combinations of characteristics of the environments and populations (in the figure columns) can lead to 3 types the maladaptive effects (in the figure rows).

​So, how this picture could be translated into academic (mal-)adaptation? Imagine, the arrows are your publications that will ultimately allow you to obtain an academic job (“the target”). This academic job could be having a relatively secure and fulfilling permanent research position – that's the “bull’s eye” of your target.
 
Now let’s consider how could the 9 academic maladaptation scenarios look like (in the same arrangement as in the original figure above):

​Do any of these scenarios sound familiar? Can they help you to avoid academic maladaptation?

by Dom Mason

Before I arrived as an intern in the I-DEEL lab, Shinichi purchased four completely automated experimental boxes from Zantiks Ltd – a behavioural research equipment company. Sent all the way from Cambridge, the boxes arrived soon after I began working at Garvan Institute of Medical Research.

These new ‘Skinner boxes’ were to be utilised in a variety of zebrafish experiments, providing experimental standardisation and requiring minimal set up. The boxes can perform behavioural assays involving tracking, feeding and light stimuli. They are equipped to record video and have plastic inserts to modify the zebrafish arena. Fish are tracked and recorded by an infrared camera to ensure light (or lack thereof) does not impact data collection. Tracking data can then be exported as .csv files for analysis.

My initial goal was to implement two behavioural conditioning assays using the boxes – appetitive learning (food reward) and aversive learning (undesirable stimuli). As scripts are required to run the automation, the first challenge was to understand the code that drives the boxes. I wasn’t much of a programmer before tinkering with the scripts; fast-forward 6 months, and I’m still not much of a programmer. In saying that, I did get some practice modifying the base scripts which Zantiks provided.

Eventually, the scripts were suitable to begin pilot experiments. While it would be i-deel (😉) to implement both aversive and appetitive learning trials, we decided to focus solely on aversive learning due to time constraints involved in getting the fish to learn.

They say you should never work with children or animals. I don’t know who they are, but they are not wrong.

Many mornings and afternoons have been spent toiling over which settings would yield the best results; and whether these results can be replicated. A key lesson learned was to give heed to all aspects of the experimental process provided by the literature. Once we included an acclimation period at the beginning of the assays, our confidence in the boxes reached an all-time high.

The next set of assays will set out to determine the variance in preference with different colour combinations – if there is any preference at all. And once we produce a consistent output of ‘significant’ results, other lab members can include Zantiks assays (quite easily) into their own work!

by Susi Zajitschek

Sharing our knowledge with the world is important, not only in scientific articles and specialized conferences. Why always wait for the media to cover scientific advancements, if we’re the experts? 

The Public Engagement Team at the Garvan Insitutue of Medical Research has recently organised a series of seminars and workshops, in which they were addressing how to effectively communicate science. I am here sharing my main insights for both visual presentations (i.e. talks) as well as written science communications (blogs, outreach articles).
 
1. Know your audience!
This has been brought up as a key point multiple times. Different expectations and levels of background knowledge demand that every talk is tailored for its specific audience. For example, a talk on dietary supplements would look very different if delivered to a group of diabetic adults, compared to a group of school kids. Similarly, a blog entry aimed at a wide audience may be kept simpler than an outreach article that is published for a well-educated (but non-expert) readership. 

2. Keep it simple!
We work in an environment where those around us understand perfectly well what we’re working on, and why this is so important. However, when prompted try to tell our grandmother in under two minutes what it is that we do, we tend to struggle!

It is impossible to convey all of “your science” within a single talk, or one article. As a rule of thumb, narrow it down – decide on ONE key message, which you can summarize in a single sentence, before you start drafting your talk or article. Only present the information that is most relevant to your audience.

Related to this: de-jargonize. Big or complicated words don’t make you look smart, but it’ll annoy your audience if they can’t follow what you’re saying. Keep in mind that even commonplace words such as significance or theory may have very different meanings in the scientific versus the public domain. 

While some technical terminology may be necessary – explain it well, and do it multiple times (differently). Avoid acronyms.

Use examples, analogies, metaphors, anecdotes to make your research relevant and accessible. Relate to people using stories. Be authentic and honest, telling a bit about yourself might help the audience to connect. 

3. Be confident & enthusiastic
Passion spreads – so if you want the audience to be excited about your research, use your body language, engage with the audience, and make eye contact. Speak clearly and slowly (despite the passion). Never fear pausing. Apparently the use of planned pauses conveys greater competence in a presenter, and it gives your audience some time to process and understand some of your more complex concepts. 

To keep your readers engaged, bear in mind that today’s reading audience does not have much time, and is easily bored and distracted. Therefore, start with the exciting bits! Bring up your main message first, and follow journalism’s rule of the 5W’s: Who – What – When – Where  – Why.  Only then present important details, and background follows last, opposite to what you’re used to from your standard scientific publication.

Practical hints
- Design your 1 sentence key message before doing anything else
- Check out how complicated your language is: use the De-jargonizer at http://scienceandpublic.com/  to identify where you could do better
- Practise! In from of the mirror, with adult family members, with 5year olds.  

by Alfredo Sánchez-Tójar and Nick a P. Moran

This January, we (Alfredo and Nick) escaped Germany’s cold dark winter to visit Sydney and the I-DEEL. Our plan was to learn more about systematic reviews and meta-analyses. Did we accomplish our goal? No doubt about it.
Let us first introduce ourselves. We are both postdoctoral researchers at Bielefeld University, conducting meta-analyses to understand why individuals differ. Both of our projects are part of a large collaborative research centre named the NC3; and it was thanks to their support that we could go to the I-DEEL and learn from world-leading meta-analysts in ecology and evolution. Our plan was simple, get there, learn, learn, learn and, well, enjoy the amazing Sydney coffee and the weather.

It became clear from the start that the following equation would be key, and we had better understand it well:
yij = b0 + si + uii + eij

With Shinichi there, that was an easy task. We met Shinichi regularly, carefully planning which analyses we needed to understand and do, and how to get there step by step. The final outcome: we learned and understood how to run bivariate multilevel meta-analyses in a Bayesian framework, which we are now using for several ongoing projects.

Parallel to our stats discussions with Shinichi, we had the opportunity to meet many of the members of the  I-DEEL team to learn more about the strategies and techniques they use to conduct thorough, reproducible and efficient systematic reviews and meta-analyses. Thanks particularly to:

• Losia Lagisz, for showing us how to efficiently build phylogenetic trees in R for our meta-analyses, and giving us lots of tips on how to conduct systematic reviews,
• Rose O’Dea, for showing us the gold standard for keeping meta-analysis databases well organized, reproducible and easy to work with,
• Yong Zhi Foo, for showing us his strategy for efficient full-text screenings using Google Forms,
• Dan Noble, for sharing some Rmarkdown tricks to make neat and beautiful supplementary materials,
• And everyone else for making it a wonderful collaborative and engaging lab.

We would like to say thank you to all the people from the I-DEEL for their time, help, and support (also for an amazing farewell cake – ping Rose O’Dea). We hope to visit you again soon!

For updates about our projects, follow us in twitter: @ASanchez_Tojar, @NC3Niche

We all heard about Open Science, and particularly Plan S, which has been announced in Europe last year (read more here). On 14th February 2019, I had an opportunity to be a panellist during discussion on what it all could mean for Australia. The panel discussion was organised by Springer Nature as a part of the ALIA conference, which is the main meeting for the librarians and information specialists in Australia and New Zealand (I realised these are mostly lovely middle-aged ladies, although they said more men are starting to join this profession with the new technologies, closing the “gender gap”…)
 
The discussion panel itself was made of different stakeholders and actors in scholarly communication, including: Director of Policy and Integrity ARC, Institutional Engagement Manager and Head of Data Publishing from Springer Nature from Springer Nature, Associate Librarian from Scholarly Information Services & Campus Libraries VU, and me as “the centrally important view of the researcher” (that’s at least how my presence was justified…)
 
After a short introduction we had to answer three pre-determined questions:

1. “Is Plan S the right plan for ANZ in the short term? And long term?”
2. “What is the role of institutional repositories in a scholarly publishing system that is moving towards gold open access as the preferred model for funders and authors?”
3. “Outline an example of an open scholarship or open data initiative and why this underlines the benefits of open research?”

 
We did not reach a strong conclusion on any of these questions, but there were a few emerging insights (at least for me):

• “Open access” is a general term encompassing publications that are freely available and permanently archived in a public repository or from more traditional publishers and licensed in way that allows broad use and reuse. While Plan S requires all publicly funded research outcomes to be immediately made available to the public and for the benefit of the public, it also places restrictions where and how these outcomes have to be published.
• Depositing in institutional repositories is currently mandatory in most of the Australian research institutions and is also the preferred option for freely sharing the research outputs. Plan S acknowledges the role of repositories for archiving research, but does not see it as the main publishing venue. Importantly, institutional repositories and many other free non-profit repositories (like preprint servers) are not likely to be compliant with Plan S requirements.
• Another concern is related to academic freedom – the right of academics to decide where to publish their findings and the impacts on the researchers themselves. Especially in the early stage of Plan S, there will be not many journals fully compliant with the requirements, and thus reduced choice of publishing venues. This may mean having to publish in less reputable or less impactful journals than the researchers would otherwise submit their work to. Such restrictions may strain international collaborations and also affect career prospects of researchers.
• Plan S would also negatively affect research societies and their role in fostering good quality research and research careers. Many societies earn the bulk of their income from the subscription-based journals they publish. Flipping to publishing in a full open access model requires significant financial resources and many societies will not be able to afford this. If they don’t flip, they may lose on submissions, reputation and income (for more details read this opinion).
• It is not clear whether under Plan S there will be savings in the overall research costs. If not-for-profit publishers and repositories get marginalised, the overall bill might be actually higher, with the costs shifting from the reading/access fees to publishing fees (and it is not quite clear how the later will be covered).
• Finally, change to Open Access and Open Science should not be rushed. Taking time will allow figuring out the safest path for transition for the publishers and researchers. Changing the mindsets of academics via education, not enforcement, will be an important factor. It will also be easier with new generation of young scientists joining academia, more ready to embrace open science.