Friday, March 16, 2018

Tips for helping people to find your journal articles (and be able to read them)

After years of working on a project and getting it accepted for publication at a journal, it can be heartbreaking when no one reads it.

The two biggest barriers are usually: finding out about it, and having it behind a paywall. Since open-source publishing usually costs extra, I don't always have funding to do it. But here are tips on overcoming both barriers.

Helping people discover that your article exists:
People mostly find my research either through Google Scholar or Researchgate, although occasionally ORCID brings people in. Researchgate is easy to edit manually to add entries (but don't upload the full-text there publicly, see the section below for important legal considerations), and both ORCID and Google Scholar do a good job pulling articles directly from the journals (usually within a few weeks of publication). However! If ORCID or Google Scholar is missing any of your research you think should be listed, you can manually add entries there too (in Google go to your profile and hit the gray + above the list of articles, in ORCID hit "+ add works"). Note that blogs and other non-peer-reviewed sources will show up in Google Scholar if someone cites the source.

That helps scientists find your articles. But for anything you really hope will have an impact, sit down and make a communications plan, ideally when you're first designing the research in conjunction with key stakeholders and communications experts. Who do you hope will read the article, and what do you hope they will do as a result? Once you have your key audiences, consider whether writing a blog or two would help get people get interested (and get clear on the point of the paper), and enlist help in getting the message to the right people. The reason doing this early is so important is that you may actually write a different paper once you know what your intended audience currently thinks and cares about, and what may motivate them to take action.

OK, hopefully you've verified your research is all discoverable, but what if people want to actually read it? Most journals don't let you share the final version of the article at all (unless it's open-source), and they also don't let you host even a submitted / pre-formatted version on Researchgate. So here's the two-part trick I use:

Helping people access your article:
First, get a personal web site of some kind (there are plenty of free options, but it's important it's a personal site and not a repository like researchgate; I use which is crusty but very cheap - $36 for life).

Next, double-check the legal agreement for any publishers you want to share your content from (this is critical: this blog is not legal advice or a substitute for doing your homework on licensing for your articles). Most publishers grant permission to share a "submitted" version of the article on the author's personal web site (but nowhere else), and the ones that don't (or have an embargo) often grant it upon request (this just happened with me and Cambridge University Press). This is often called "self-archiving" or "green open access". So once you have verified permission, upload the files to your web site.

Then set up a "publications" page on your web site, which will help Google discover it. Google has instructions on how to do this and I have an example you can copy if desired here:
Usually once I add the entry to this page linking to the new pdf, Google Scholar finds it within about 3 weeks. The main thing is naming the web page "publications.html" and linking to the PDF via the article title.

Finally, people often request papers via Researchgate even though the PDF is already discoverable via Google Scholar. This is annoying since you usually can't legally host your paper there. But what you can do is create a redirect document in Word and save to pdf, and host that redirect document in Researchgate (e.g. see this example I made). That way it shows up as 'full text available' and people click through to the paper.

Of course, none of this ensures that your paper will be clearly written and compelling, but hopefully you're all over that, right?

Thursday, March 1, 2018

March 2018 Science Journal Article Summary


It has been a hectic month so I haven't read much science. I'm including two articles on beef sustainability (one exciting case study, and one much broader review), as well as a new paper of mine that was finally published after an epic 14 month review. My paper looks at how information about CbD 2.0 spread within TNC and beyond, and while it's long and dense I'd encourage you to at least check out the summary below for tips on how to aid "knowledge diffusion" and how to study it.

Stanley et al. 2018 is a paper arguing that proper grazing management may be able to make beef a net carbon sink. They don't go quite that far, but it's a reasonable extrapolation. While this is an encouraging case study and we should look carefully at how to apply it, there are some really important caveats to interpreting this more broadly. Specifically, they found using "adaptive multi-paddock (AMP)" grazing for the finishing phase of cattle instead of feeding them grain resulted in a sink of ~6.7 kg CO2e / kg carcass weight, compared to a source of ~6.1 kg CO2e / kg for feedlot beef. The study is designed well, and soil C improvements were measured empirically over 4 years, in three types of soil in the Upper Midwest. That being said, there are a few big issues that challenge the narrative of "carbon positive beef" being possible at wide scales:
  1. The soil sequestration here (3.6 Mg C / ha / yr) is much higher than is typically reported (although some studies have shown similar rates).
  2. These rates would diminish over time; it's not clear how fast the soil would saturate but high rates like this would be most likely in early years after improving management of highly degraded soils.
  3. This study was on alfalfa pasture (which fixes N); it's unlikely these results would apply to unfertilized rangelands
  4. The study did not include soil nitrous oxide emissions which are often substantial in leguminous pastures.
  5. Finally, the grass-finished beef took up twice as much space as the feedlot beef. That could be good from a perspective of prevent conversion of grasslands by keeping them in production, but it also means that if we scaled up grass-finished beef at this density, we'd have to find twice as much land to graze cattle on, which could drive conversion. It would also likely raise costs for producers and consumers.

Garnett et al. 2017 ("Grazed and Confused") is a very thoughtful review of the climate change / GHG impact of ruminants (largely cattle). Their first key findings is that even with good grazing ruminants still have high net GHG emissions. They also note sequestering soil carbon often has trade-offs with methane and nitrous oxide. Finally, as demand for animal protein rises sharply there is likely to be both land conversion and increasing GHGs as a result. These have all been reported widely in other studies, but it's a nice summary. On the one hand, it's hard to pull out quantitative results from this paper. On the other, it does a great job of covering the various arguments and counterpoints around cattle and carbon, and presenting the data in a value-neutral tone. Anyone interested in this topic should at least skim the 8-page summary.

Fisher et al. 2018 ("Knowledge diffusion within a large conservation organization and beyond") looks at how people find information about innovations and share them, specifically the spread of Conservation by Design 2.0 (CbD 2.0). We review how earlier versions of CbD spread from TNC (looking at published science articles and expert interviews), then use tons of varied data to look at CbD 2.0. I wrote a blog about the paper here:
and the full paper is at:
but here's a summary of what we learned:
  1. Sending repeated broadly-targeted communications (e.g. all-staff email / newsletters / etc.) that make it easy for recipients to find out more worked better than more narrowly focused communications (e.g. plenary talks, emails from executives).
  2. Expert interviews revealed several factors to promote diffusion: bringing in partners early to develop and test methods, committing up front to sustain support for the planning methods, having in-person workshops, using peer-review and shared learning, providing financial support, explaining how the methods address existing needs planners already have, and the existence of a support and learning network like the conservation coaches network (CCNET). 
  3. Organizations may wish to use internal data to identify staff likely to play a key role in diffusing so that they can encourage that process (the paper has details on how, with more forthcoming in an upcoming paper)
  4. Working with academics on publications represents a potential way to get the word out with relatively low effort for organizations (academics I have worked with in other contexts are often very interested in data no one else has access to, and have published cool papers from those data). 
  5. For scientists interested in this topic, we learned a lot about how to study knowledge diffusion, and share tips for researchers (e.g. thinking about image-blocking, legal and privacy constraints, distinguishing internal and external website visits, etc.).

Fisher, J. R. B., Montambault, J., Burford, K. P., Gopalakrishna, T., Masuda, Y. J., Reddy, S. M. W., … Salcedo, A. I. (2018). Knowledge diffusion within a large conservation organization and beyond. PLoS ONE, 13(3), 1–24.

Garnett T., Godde C., Muller A., Röös E., Smith P., de Boer I.J.M., Ermgassen E., Herrero M., van Middelaar C., Schader C. and van Zanten H. (2017). Grazed and confused? Ruminating on cattle, grazing systems, methane, nitrous oxide, the soil carbon sequestration question. Food Climate Research Network, University of Oxford

Stanley, P. L., Rowntree, J. E., Beede, D. K., DeLonge, M. S., & Hamm, M. W. (2018). Impacts of soil carbon sequestration on life cycle greenhouse gas emissions in Midwestern USA beef finishing systems. Agricultural Systems, 162(November 2017), 249–258.

Share the good news: a paper on improving "knowledge diffusion"

Ever feel like you missed out on a super cool Kickstarter project and you can’t believe no one told you about it? Amidst the fire hose of blogs, podcasts, social media, and more, how can we help good ideas get noticed, get shared, “go viral,” and make change happen?

That’s the question that a few scientists at The Nature Conservancy (TNC) decided to tackle back in 2014 ( Scientists usually don’t get to tell others what to do, and we don’t have many celebrity advocates or adorable cat videos to explain our research. So to influence others we often have to be creative, “lead by intrigue,” and hope our message catches on. But for a new idea to go viral, it helps to understand how it spreads from person to person.

Our first journal article on this research (published in PLoS ONE, taps into a huge array of different data sources including tracking web page activity, TNC employee data, and more traditional detailed surveys to give us some initial clues about how people are learning about innovations and sharing them with others. Going this deep with different kinds of data to explore diffusion is novel, and we learned some cool tricks other scientists may want to use!

Scientists call the way that new ideas spread “diffusion of innovations.” The process includes learning about and considering a new idea, trying it out, and telling others about it (not necessarily in that order).

Some innovations are new technology or practices (e.g., seven science innovations changing conservation, We focused on a more conceptual example: the spread of the new scientific principles and planning methodology at TNC: Conservation by Design AKA CbD, We asked how TNC staff and others received this new information, sought to learn more, and shared it.

CbD dates back 20 years and we saw lots of interest in it from beyond TNC in published science articles. Experts we interviewed said that ideas spread when you bring in partners early, invest in training and support, and do several other things which TNC did from the beginning).

We didn't find a silver bullet for communications that got people to seek out more information. But simple broad communications like short articles in internal newsletters and webinars to all staff worked best to promote seeking more information about CbD (as shown in the figure below, which tracks how many people went to a web site to learn about CbD in response to different events). The more venues through which someone heard about the new ideas in CbD 2.0, the more likely they were to share, so repetition was key.

There were several other factors that made people more likely to share information. Some were obvious, like people whose job included training others in conservation planning methods. Others were less obvious, e.g. people who took more online trainings (not limited to conservation) were more likely to share information about CbD 2.0.

We also learned that even with all the data available to us, there were still some surprising limitations. For example, Google Trends, much touted as a “Big Data” approach to track public interest in different topics, turned out to have unreliable data. Plus, it’s not specific enough: TNC’s “conservation by design” gets searched for less than a private company with the same name. So searches for “our” CbD got lost.

Most of my research tries to find how much information we need to make the right decisions without wasting time on unnecessary analysis. With the findings of this new paper, we have new insights into how we can share those tips and avoid either wasting time or making the wrong call.

So the next time you miss out on that sweet Kickstarter project, let me know, and let’s see if we can figure out how to better prepare for the next one.

Fisher, J. R. B., Montambault, J., Burford, K. P., Gopalakrishna, T., Masuda, Y. J., Reddy, S. M. W., … Salcedo, A. I. (2018). Knowledge diffusion within a large conservation organization and beyond. PLoS ONE, 13(3), 1–24.