in 2015 the American Society of Naturalists, Society of Systematic Biologists, and Society for the Study of Evolution had their joint meeting in Brazil – the first time this meeting was held in the tropics. At the time the Marlene Zuk was ASN Vice-President, and she had a brilliant idea for the traditional VP’s symposium that took advantage of the meeting being held in Brazil: examining “Temperate Assumptions”. In outher words, how our ideas about ecology, evolution and behavior have been shaped, and perhaps biased, by the places many scientists historically worked – the temperate regions of the world, especially Europe and North America. Her goal was to have speakers re-examine the assumptions and the examples used and discuss how our ideas and theory would be enriched by a consideration of other systems, taxa, and viewpoints.
Fabiane Mundim (photo by Ernane Vieira Neto)
The invitation to participate coincided perfectly with some work my PhD student Fabiane Mundim had recently completed. Fabiane was interested in doing her thesis work on how climate change would influence plant-herbivore interactions, especially in the tropics. To get me up to speed on the topics my students choose for their thesis we try and do a review or meta-analysis together, so Fabiane started reviewing experimental work investigating if plant-herbivore interactions were altered by different types of environmental changes associated with changing climates. The results were really interesting, and there was a strong tropical-temperate bias, so we put together a talk and I presented the results in the symposium (Fabiane couldn’t make it as she was in the throes of field work). A video of the presentation is here; if you are interested in the data on what is being published in AmNat and the location of the authors you can find the data on Figshare and code to make the maps on Github).
Fast forward a year later and the Special Issue of the American Naturalist based on the symposium is out. You can find Fabiane’s meta-analysis as well as papers on topics ranging from the macroecology of sexual selection to the biogeography of biogeochemistry – lots to think about in all the papers. As for Fabiane’s study, I think it points out some really important shortcomings in both the theoretical frameworks used to study plant-herbiovre interactions in a changing world as well as the data needed to address this issue:
Empirical studies were heavily biased toward temperate systems, so testing predicted changes in tropical plant-herbivore interactions was virtually impossible. Furthermore, most studies investigated the effects of CO2 with limited plant and herbivore species. Irrespective of location, most studies manipulated only one climate change factor despite the fact that different factors can act in synergy to alter responses of plants and herbivores. Finally, studies of belowground plant-herbivore interactions were also rare; those conducted suggest that climate change could have major effects on belowground subsystems.
In sum, our results suggest that there is a major disconnection between the literature proposing how climate change will influence plant-herbivore interactions and the studies testing these predictions. If there are students looking for thesis projects, I think this is paper is a gold mine.
Road cutting through a mixture of natural areas and agriculture in Brazil’s Cerrado (Photo by Emilio Bruna).
Roads and freeways, paved or dirt, can be more than a thoroughfare for moving humans from one place to another.
As UF researchers working in Brazil are learning and documenting, an unintended and ironic consequence of building roads for agricultural expansion is that roads can create the ideal habitat for insects that can be major agricultural pests.
His research, based on four years of field study, focuses on leaf-cutter ants. One of the most iconic and ecologically important species of Latin America, when their populations expand into farmer’s fields they can cause millions of dollars in crop losses each year despite widespread application of highly toxic insecticides.
Ernane Vieira Neto and a leaf-cutter ant nest (Atta sp.) along a roadside in Brazil. A leaf-cutter ant nest this big can consume 500 kg of plant material per year.
A global diversity hotspot about 10 times the size of Florida, this region is responsible for Brazil’s emergence as an agricultural superpower, with approximately 4,600 miles of roads slated for construction in the next two decades.
In the paper, titled “Roads Increase Population Growth Rates of a Native Leaf-cutter Ant in Neotropical Savannahs,” Vieira-Neto and colleagues present data from field surveys demonstrating that the number of ant colonies next to roads increases dramatically when compared to nearby areas of native vegetation. The researchers used mathematical models to show roadsides are the ideal habitat for queens to start their new colonies, which grow very rapidly.
“For population growth, every individual colony and life stage is important,” said Vieira-Neto. “But events that occur so early in the life cycle of a leaf-cutter ant colony, such as successful colony foundation by the ant queen and colony survival as a juvenile, are more prevalent near roads and have relatively more importance for the population than late-life events.”
The researchers predicts that the increasing numbers along new roads of one of the biggest agricultural pests farmers have ever encountered could have major economic effects. In addition, because these insects also are major ecological engineers, their increased numbers will have consequences for other plant and animal species and ecosystems such as nutrient cycling.
“No matter where they are built, roads have unintended consequences for native plants and animals,” Bruna said. “Our results suggest that the impacts of roads on native biodiversity can have not only ecological impacts on other plants and animals, but potentially unexpected economic ones as well.”
The focal species of Vieira-Neto’s study is the leaf-cutter ant Atta laevigata (Photo by Fabiane Mundim).
With an original area of 2 million square km, the Cerrado is Brazil’s second largest biome. Because it is central to Brazil’s agricultural industry, it has a large and rapidly growing road network (Photo by Fabiane Mundim).
I’ve got to do some maps for a manuscript, so I’ve been working through different options for mapping in R. Here are some resources I’ve found useful, feel free to add in the comments. Thanks to those of you who have helped with my questions (that means you, Andy)
It’s obviously more complicated than research funding and lifestyle, and across all disciplines the US continues to be THE destination for international research talent. But in concert with a willingness by foreign science agencies to invest in risky projects or build centers of excellence, I think that as the funding for ecological research in the US continues to decline we will see many more people jumping ship for the more sustained funding they can find abroad. So pay attention to @LangForCareers: you now have another good reason for you to start learning Portuguese!
1FAPESP is admittedly unique. But the national agency CNPq and many other state agencies (FAPERJ and FAPEMIG) are also exceptional.
UPDATES 3/11/2015 in response to some questions and comments I received yesterday:
3Note the NSF funding rate in the table is inflated because many directorates have moved to a pre-propsoal format and the funding rate is for the smaller number of full proposals submitted. PS if you really want to be depressed check out the funding rate for postdoctoral fellowship applications.
4via Twitter Nate Sanders was kind enough to remind me his move to Denmark means free health care and college education for his kids. He also gets to watch the Copenhagen Derby. Rub it in, Nate, rub it in!!
Cover photo courtesy of sama0903 (CC BY-NC 2.0): Rio de Janeiro seen from the Pão de Açúcar, from Copacabana beach (far left) to Santos Dumont Airport (far right). The panorama was made from 10 separate photos.
The latest issue of Ecology brings with it a sweet new paper from the Amazon. In it our intrepid team — Heraldo Vasconcelos, Brian Inouye, me, and our former postdoc Thiago Izzo — report on how the identity of ant partners influenced the demography of the myrmecophyte* Maieta guianensis. Props to Thiago for spending many, many, many days in the field, the team that developed the IPMpack package for R that really simplifies the use of Integral Projection Models to study demography, and the National Science Foundation for financial support. And yeah…that’s us featured on the cover, with a great picture by Brian Inouye.
Date: November 18, 2014
To: All UF Graduate Students and Faculty
From: UF George A. Smathers Libraries
RE: New Resource: IR@UF (Institutional Repository at the University of Florida)
New Resource: IR@UF (Institutional Repository at the University of Florida)
IR@UF (Institutional Repository at the University of Florida) is a new resource for graduate students and faculty, among others — a digital archive for the intellectual output of the UF community, including research, news, outreach and educational materials.
It is a central and secure place where any member of the UF community — faculty, students, researchers, etc. — can store, archive, display, showcase, share, highlight and visualize their output.
For a PDF poster about the benefits of IR@UF and how to use it, click on this link:
New video explains what the Institutional Repository at UF is and how it benefits faculty and students
Explaining what an Institutional Repository (IR@UF) is and how it benefits faculty and students has long been a difficult task not only at the University of Florida, but at universities across the United States. The George A. Smathers Libraries have launched a new video and accompanying poster that explains in a graphical and humorous manner what the IR@UF is, what types of content can be uploaded, how to upload content and the benefits of placing materials in the IR@UF.
The $5,000 project was funded by an internal library mini-grant awarded to Scholarly Communications Librarian Christine Fruin and a project team of library faculty and staff. After bids were received from four local designers, Sequential Arts Workshop (SAW) was chosen to conceive, write and illustrate the video and poster in collaboration with the project team. Justine Mara Andersen of SAW was the primary illustrator, designer and animator, with assistance from SAW Executive Director Tom Hart. UF theater students Nazeeh Tarsha and Angelique Rivera lent their vocal talents to the video.
Fruin explained, “A common reaction from non-library folk upon hearing the term ’institutional repository’ is a glazed-eye confusion about what it even is and how it can be used. The term is so clinical and dry, as is often the attempt to describe it. I have often marveled at some of the creative messages, infographics and the like, that have been employed by libraries and other organizations in communicating technical, factual and even legal information. So I thought, ‘hey, why can’t we do that to get people interested in the IR?’ SAW took our list of concepts and points of information and created an entertaining marketing device that I think will get the UF community interested in this wonderful resource we offer them.”
Andersen said “I had no idea when we at SAW started work for the IR@UF that the end result would become one of the projects I am most proud of. It’s obvious to anyone who looks at the animation that it was a labor of love. A spirit of humor, beauty and full color fun runs through all 6 minutes and 40 seconds of the piece. So sit back and enjoy, and if it’s half as much fun to watch as it was to create, then we have all done our jobs. Oh…and if you manage to learn how valuable the IR@UF is while watching it…that’s groovy, too.”
You don’t need me to rehash the arguments for why scientists should archive and make publicly available the data and code used in their papers — you can read up on those here, here, and here, for starters. As noted by Roche et al., many scientists fail to see the personal benefits to archiving given the potential costs, not the least of which are the time, effort, and money required to do so. To counter these concerns, proponents of public data archiving — including me — are quick to point out the many advantages of doing so: the opportunity for novel collaborations, the public good, meeting funding agency mandates, and what matters most often counts most for scientists in terms of professional advancement and recognition — citations of the archived data and code. To put it bluntly, in our annual evaluations and portfolios for tenure or promotion all of us are asked us to document the “impact of our research program on the field” (e.g., flip to the bottom of p. 16). Citations of datasets and code are an easy and unambiguous way to do so, which is why this has been put forward as an important mechanism by which to increase the number of scientists engaged in open science (see also Whitlock 2011 [sorry, paywalled]). There are plenty of handy guides on how to do so — the DCC has a comprehensive one, as does The Dryad Digital Repository. It’s preety simple, here is Dryad’s suggestion for how to cite data (emphasis theirs):
When citing data found in Dryad, please cite both the original article as well as the Dryad data package. It is recommended that the data package be cited in the bibliography of the original publication so that the link between the publication and data is indexed by third party services. Dryad provides a generic citation string that includes authors, year, title, repository name and the Digital Object Identifier (DOI) of the data package, e.g. Westbrook JW, Kitajima K, Burleigh JG, Kress WJ, Erickson DL, Wright SJ (2011) Data from: What makes a leaf tough? Patterns of correlated evolution between leaf toughness traits and demographic rates among 197 shade-tolerant woody species in a neotropical forest. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.8525
Where am I going with this? I recently had a paper accepted as a Report in in Ecology, and I decided to put my data where my mouth was and archive all our data with Dryad, post the code at GitHub, and get a DOI for the code with Zenodo so it would be citable. This paper also used some of my lab’s data from a prior publication that we had also archived at Dryad, so I followed Dryad’s guidleines and included citations to both the paper and dataset in the Literature Cited. Open Science FTW! Imagine my surprise when I got this email from the Copy Editor preparing to send my manuscript to the printers:
Regarding your inclusion of references to code and data in Literature Cited and elsewhere in the text, we have made the following changes to fit our style: 1) Bruna et al. 2011b has been deleted from Literature Cited. In the one place where it was cited in the text, it now says “see data associated with Bruna et al. 2011”. [EB note: Bruna et al. 2011b is the citation of the dataset archived at Dryad] 2) Bruna 2014 has been deleted from Literature Cited and the URL appears as a footnote where this R code was referenced in the text [EB note: Bruna 2014 is the citation to the code with the DOI] 3) The URL for the data associated with this manuscript now appears in a Data Availability statement at the end of the paper A reference to that appears where the URL was formerly in the paper. [EB note: this refers to Dryad archive of the data collected for this paper]
Indexing services don’t scrape the appendices, data availability statements, or footnotes of papers. In other words: Sorry, Emilio…no citation credit for you! But thanks for being a mensch and archiving your data and code, which by the way we also think is really important. ESA, this isn’t right. You can’t encourage authors to archive data/code — or in the case of Ecological Applications, another journal you publish, actually require it — but take away a major incentive and reward for doing so. But don’t take my word for it: Liza Lester said it best in the February announcement that Ecological Applications would require data arching:
UPDATE (18 October 2014): Resolution! This flew around the twitterverse for 48 hours and has been resolved thanks to Todd Vision from Dryad and J. David Baldwin, the Managing Editor of ESA Publications. The tweet from Ecology EIC Don Strong says it all:
A few years ago I called Stefano Allesina from the University of Chicago to get some insights on a project and we ended up talking about another one of our mutual interests – understanding the factors influencing scientific productivity and impact (my favorite study of his might the analysis of nepotism among Italian academics). I mentioned that I thought engagement in international collaborations might be particularly important, especially in Latin America, and by the way – why don’t I know many Italian ecologists? His response was direct and to the point: “let’s find out!”. The result was this paper — a huge undertaking led by his graduate student Matthew Smith and also had as a co-author Stefano’s Research Assistant Cody Weinberger — that was published today in the open access journal PLoS ONE. It demonstrates international collaboration can influence where your work ends up being published and how much it is cited, but it’s not as simple as that…to find out why, read the paper, blog post on Stefano’s page, press releases (below), and addendum after the release.
Thanks to Matt, Cody, and Stefano – this was a really fun project and I look forward to following up on our results.
CITATION: Smith MJ, Weinberger C, Bruna EM, Allesina S (2014) The Scientific Impact of Nations: Journal Placement and Citation Performance. PLoS ONE 9(10): e109195. doi:10.1371/journal.pone.0109195
Figure Legend: Coauthorship network of all articles published in 55 ecological journals from 2010-2010 that include at least one coauthor from Costa Rica.
GAINESVILLE, Fla. — International collaboration tends to boost the profile of the science for all researchers involved, but collaborating with certain countries provides more of a scientific impact than others.
For college students aiming someday to become scientists, that means the sooner you start thinking globally, the better.
Emilio Bruna , a University of Florida professor of tropical ecology and Latin American studies, teamed up with University of Chicago professor Stefano Allesina and two of his students to study 1.25 million research articles published from 1996 to 2012 in fields ranging from chemistry to psychology. The research will be published online Wednesday in the journal PLOS ONE.
Bruna said the team wanted to study the scientific impact of various countries and how collaborations between diverse groups influenced the likelihood of a research article getting published in leading journals or cited by other scientists.
“Collaborating with scientists in other countries is really hard work,” Bruna said. “From speaking different languages, to dealing with different cultures, to doing science in different places, to just the bureaucratic stuff like getting research permits and finding the money to work internationally.
“There is personal satisfaction, but beyond that, is all this hard work worth it?”
The team found that, in most cases, collaboration raises the profile of the science, and the more collaborators, the better, in terms of journal publication and number of citations.
For example, Bruna said, collaborations between mathematicians in France and the U.S. tend to end up in higher-profile journals and be cited more than research by scholars from those countries working independently. Similarly, Brazilian and U.S. ecologists who collaborate find their work is cited more frequently than that of scientists from either country working independently.
Bruna said there are a few reasons for the positive effect. Each scientist has his or her own social and professional network, so as collaborators increase, so does the number of people who will see and cite the work. While previous researchers had noted this benefit collaboration, however, Bruna and colleagues found that the effect was even more pronounced as the geographic diversity of collaborators increased.
Another reason might be access to resources that enhance the quality of research – for instance, many funding agencies and universities have funds available for international collaborations, which would allow researchers to gain access to unique field sites or advanced instruments, And, it stands to reason, he said, that work that involves multiple countries also might be broader in scope and hence have broader implications.
“The take-home message for national governments, funding agencies, and universities is that international collaboration can translate into greater scientific visibility, quality and impact,” Bruna said.
“We should be reminding our students to think beyond our borders in terms of questions they want to address as scientists. We’re not just better scientists for working internationally,” Bruna said, “we’re better people for it.”
Additional Comments by Emilio Bruna
Another intriguing finding of our study is that the Global North, although still scientifically dominant, is seeing a drop in citations with the emergence of scientific powers such as China, South Korea and India. In the field of condensed matter physics, for example, the rate of publications and citations for Chinese authors has quintupled in the last 15 years.
Although the benefits of collaboration were clear, we were surprised by some of the more nuanced results. For instance, there was often a paradox between the status of the journals in which scientists were publishing and the number of citations their articles received. Case in point are the Brazilian ecologists, which tend to be publish in lower-tier journals than expected, but their articles get cited more than the others in those journals.
What is behind this paradox? Are the authors underestimating the quality of their work? Is the review processed biased agains authors from certain countries? Are incentives to publish in higher-tier journals lacking? Is language an issue? These articles are cited very frequently, so the scientific community obviously thinks they are of high quality.
Our analyses also revealed cases in which collaboration failed to boost the research profile. Scientists in some fields already are under-cited, and when U.S. researchers collaborate with them they pay a “citation penalty,” with the work cited less than if they had worked independently. It’s important to emphasize that we are not saying the science is better or worse, only that we observed this pattern for some combinations of international collaboration and that we need to understand why that is.
Several years ago I made a personal commitment to Open Science: I try to publish papers on which I am the lead author on in open access journals and I archive data for these papers in Dryad, Figshare and other repositories. Recently I started posting preprints of my manuscripts as well, and I encourage authors submitting to the journal of which I am Editor to do the same. The thing that I had been most hesitant about was posting my code – I’ve been programming for a long time, but I’m not the most elegant of programmers (NB: massive understatement), so to be honest I was a little worried people would mock my efforts. I finally got over that, stumbled through some GitHub tutorials, and as a result you can now go over there to see the code used to do the analyses and generate figures for my two most recent articles, as well as for a few projects in progress.
Although I feel good about having done this, it’s also become clear to me that there is a real opportunity cost to Open Science about which I think we need to be honest with our students. There are actually multiple opportunity costs. One potential one is lost future papers. While I often hear the about the possibility of getting scooped because we post our data, however, concrete examples seem hard to come by and I just don’t buy it. Another is lost status and opportunities: Our profession still prioritizes articles in publications like Science,Nature, or PNAS, so as a candidate on the job market you are still way ahead of the pack if your paper is in one of those journals than if it is in PeerJ or PLoS ONE (I’m not saying that’s right, only that it’s true). I think this is a more legitimate OC, and one that will be with us for a while, unfortunately. The opportunity cost I’m talking about here is more diffuse: the time I devoted to archiving data and code could have been spent on other activities that have greater rewards under the current system. I could have also used the money I spent on archiving fees and publishing in a journal with an OA option to advance ongoing research in the lab.
For my most recent paper I did the math:
Double checking the main dataset and doing some reformatting to prepare it for submission to Dryad: 5 hours (NB: I had already invested a fair amount of time in reorganization of the dataset to get it in line with the suggestions of Borer et al.because I use R for analyses and to generate (many of) the figures. Unfortunately, we didn’t give much thought to data oranization when we originally entered the data, so the result was a very complex and inefficient set of files).
Realizing I probably needed a second file to complement the first one (the main file I was going to upload includes a list of 40 demographic plots, but not the specific locations in the reserve where these plots are located), creating the CSV file using the original data set, thinking there was a mistake in a few of the points, trying to figure it out, and realizing there wasn’t a mistake after all, and preparing the metadata file: 3 hours
Submission of these two files and the metadata to Dryad: 45 minutes
Preparing a figure of these locations (a map, since not everyone is familiar with the layout of trails at the BDFFP): 1 hour
Submission of this map to Figshare: 15 minutes
Getting up the courage to post my code to GitHub, looking over my code, rewriting all the comments and annotations so that someone other than me understood them to the point they could see what I did step-by-step, deciding to take my long inefficient scripts and simplifying them by creating functions to do some of the redundant stuff (which I should have done in the first place), and uploading to GitHub: 25 hours
This is not a trivialamount of time: it’s almost a full week of work spent on archiving data and code for one paper. That was precious time I could have spent preparing for classes, working on other manuscripts, writing grant proposals, going to the gym, staring longingly at the sax I haven’t played in months…whatever. And bear in mind, this quick calculation also doesn’t include any of the one-time financial and time investments that are amortized over multiple submissions, including:
Time spent registering with Dryad
Time spent registering with Figshare
Time spent learning how to use R/MATLAB/Python/whatever for analyses instead of Systat or JMP so that the scripts are available for others to use and reproduce results
Time spent learning to use Git and the RStudio/GitHub tools to that code are available.
Note also that the cost could have been even higher if I had published in, for example, PLoS ONE
Granted, the cost could also have been lower. I could have reduced the price US$200 by publishing in PeerJ or by $600 if I had published in Biotropica, which waives page charges for ATBC members. In addition, the time spent on these tasks will decrease as I become a better programmer and because in the future datasets we collect will be well organized at the start, diminishing the need for reorganization at the time of deposition. Still, this past week was a reminder of what I see as being the major hurdle to overcome when trying to convince others that we should strive for Open Science: it is a major pain in the ass and is really expensive, in terms of both the money and amount of time required. Without a better system of incentives from the community for archiving data and code, 35 hours and $690 may be too much effort and money for most people. We need to recognize that reality and identify creative ways to change the current system, because let’s get real – telling people “you should because it’s the right thing to do” and assuming that’s enough just isn’t going to cut it (not that a compliment from Ethan isn’t reward enough for me, but I already have tenure, so…). We also really need to teach our students how to do this now; it’s much easier if you develop good habits early. Finally, it’s also important for me to remember that it will get cheaper and cheaper every time I do it (e.g., preparing metadata was a snap this time because I used the template from my prior submissions to Dryad).
Regardless, let’s be mindful when advocating Open Science – it’s hard, expensive, and comes with both accounting and opportunity costs. If we want to make Open Science the norm, we need to find ways to minimize these actual and opportunity costs, not just promote incentives for doing engaging in OS. We need to stop telling people “You should” and get better at telling people “Here’s how”.
[edited 4 September 2014 @ 9:44 pm for clarity and to correct some typos]
[upated 10 September 2014 @ 9:06 am for clarity and after one hour was spent on activities 7 and 8]
I started posting data from papers to Dryad and elsewhere a while back, but I finally made a commitment too start posting the code used to manipulate, analyze, and plot the data as well. Since my code generally sucks (meaning it can be is inefficient and ugly), I thought I would post to GitHub instead of as a text file in the paper’s online supplement to allow others to improve it if they want to use it. My first attempt is here; this follows an earlier posting of the java code for a smartphone guide to the trees of the UF campus. Please don’t mock the n00b.
I’ve used some version control platforms before as part of a collaboration with another group, but there is definitely a learning curve. After posting a request on twitter for some suggestions I heard mainly crickets, but here are two places people suggested a newcomer to GitHub could go to learn to use it. [Edit: also go check out the suggestions in this post at Dynamic Ecology]
I just wanted to give a shout out to a great open-access journal that fills a much needed empty niche for field biologists — lists of biological inventories and notes on the geographic distribution of any taxon. The journal’s name is Checklist: Journal of Species Lists and Distributions.
My collaborators and I were tired of writing variations of the following sentence in the methods section of our papers: “the reserve where we work has a full complement of regional mastofauna, but low diversity and density of small mammals (unpubl. data)”. When we discovered CheckList we took our survey data and trapping data, did some analyses, submitted it, and now have a paper we can cite instead. The reviews were speedy and helpful, including suggestions for alternative analyses and presentations of the data. Submission was a snap and the pdfs of the paper look really sharp – see for yourself.
This journal would be a great outlet for students that generate a species list as part of their work and need practice writing and revising a paper, biological reserves and the researchers who work there, or even for faculty who want to include data collection and the writing of their paper in their ecology field courses. I also think it could play an important role for researchers in biogeography and macroecology by getting species distribution data peer-reviewed and indexed, rather than relying on unpublished data.
“Publicação científica e rede de interações de autoria na America Latina”
2 de junho de 2014 – 11h
Auditorio 2 do Centro Didático
Dr. Emilio Bruna, editor chefe da Biotropica, estudou a publicação dos melhores jornais da área de Ecologia e descreve o perfil das autorias e as mudanças de produtividade que ocorreram em 18 países da America Latina nas últimas décadas. Nessa palestra ele descreve também a estrutura de rede de co-autorias e como a colaboração internacional influenciou a qualidade das revistas onde os artigos foram publicados e quanto eles foram citados.
This semester I taught a 1-unit workshop on scientific publication for graduate students. As part of the workshop we studied how bias — geographic, institutional, gender, etc. — could influence the likelihood of getting published.
In all my grad classes I assign a group project, and this year’s was a follow-up to the discussion on bias. I asked students to review the gender composition of the editorial boards of 10 journals and see how well women were represented among the Subject Editors as well as the ‘editorial leadership’ (i. e., Associate Editors, Editors-in-Chief). This was actually something I’d started looking into last year with my former student Irina Skinner after the following twitter exchange with Jonathan Eisen:
Irina and I never got around to finishing, so the students picked up where we left off and then expanded the project by adding several new journals and quantifying the editorial board composition all the way back to to 1985.
The results? The title of the post sums them up, but things appear to be getting better – least for some journals. You can read (and leave comments on) the manuscript we just submitted for publication and posted at the PeerJ Preprint server. But since you’ve gotten this far, I’ll leave you with one figure:
All the data will be archived at the Dryad Digital Repository when the Manuscript is accepted.
*As an aside, this was the first experience I’ve had depositing a manuscript in a preprint archive – part of the workshop focused on enhancing the impact of your science, so we went through all of the steps including prepping the data / metadata for archiving and blogging about the process. Our preprint is at PeerJ Preprints, and I can’t say enough about how easy the process was and how slick the interface and tools are. I’ll definitely be submitting a manuscript there soon.
They failed to control—statistically or in their sampling—for the type of institution where their focal researchers were based. Given differences in obligations and resources, scientists are likely to have very different relationships between pre- and postdoctoral productivity if they are based at large research universities, smaller colleges focused on undergraduates, or government research institutes.
They neglected to correct for the fact that not all researchers, even those at the same institution, devote the same proportion of their time to research. I think they should have scaled productivity by Full-time Equivalent (FTE), since FTE defines how much time you devote to research, and hence your productivity.
They pooled researchers from different countries in their analyses without including national identity as a factor in their model. Without explicitly considering the influence of national identity it is difficult to determine whether their results are widely applicable (BTW, they didn’t give a complete list of countries from which researchers were selected or the sample sizes of authors from each country).
Correcting for the type of institution where researchers work: It doesn’t make sense to include the type of institution where you work as a factor because this is actually a consequence of your pre-PhD publication record, not a driver of your post-PhD success. In their words, “productive scientists will clearly be better than unproductive ones at securing positions at research-intensive institutions and at devoting more time to research.”. Translation: the reason you didn’t get a job at an R1 is because you weren’t productive enough in grad school to get one. Suffice it to say that the job market must operate way differently in Australia than other places.
Productivity should be scaled by FTE: They didn’t respond to this criticism.
One should consider the effects of the country in which a research is based: Their response was “If one wanted to include country as a random effect, would one use the country (or countries) where a researcher was born and raised, the country where he or she received his or her PhD, or the country (or countries) where he or she was subsequently employed?” The answer to their question is “yes”, but for starters Employed, since this context in which someone’s productivity is evaluated and which in part motivates it. That they didn’t have the replication to do so suggests their sampling was inadequate to draw they general conclusions they put forward. By the way, the issue of author origin vs. author location of employment is something people doing scientometric work struggle with all the time, and they have to justify their choices in the papers or at least explore the implications of these different options (e.g., here).
Not particularly satisfying you say? Don’t worry – their concluding argument for why their work is sound is that it was recommended on Faculty of 1000 and a “popular synopsis” (i.e., blog post) they wrote about it has had 15,000 reads. QED!
Scientometrics is challenging and requires careful design, sampling, and analysis. The data collection and statistical issues Laurance et al. avoided in favor of “simplicity” are struggled with all the time in the pages of Scientometrics or the Journal of Information Science. Given that their conclusions could be used to make decisions that affect the future of students with which we work, I wish they had struggled with them a little bit more.
We used Bayesian genetic analyses to characterize parentage and propagule dispersal in Heliconia acuminata L. C. Richard (Heliconiaceae), a common Amazonian understory plant that is pollinated and dispersed by birds. We studied these processes in two continuous forest sites and three 1-ha fragments in Brazil’s Biological Dynamics of Forest Fragments Project. These sites showed variation in the density of H. acuminata.Ten microsatellite markers were used to genotype flowering adults and seedling recruits and to quantify realized pollen and seed dispersal distances, immigration of propagules from outside populations, and reproductive dominance among parents. We tested whether gene dispersal is more dependent on fragmentation or density of reproductive plants.
Dr. Marina Cortes
The answer? You;’l have to read the paper to find out, but it really calls into question a dominant paradigm about how habitat fragmentation influences plant population genetic structure.
Dra. Marina is now a postdoc at UNESP, and you can find out more about her work here.
We’ve been given 48 hours to provide feedback on UF’s new proposed OA policy. Since I didn’t see the email until this morning, it’s really 24 hours. The draft documents are below – any thoughts?
Each University of Florida faculty member who voluntarily complies with this policy grants to the University a nonexclusive, irrevocable, worldwide license to exercise any and all rights under copyright law pertaining to each of his or her authored or co‐authored scholarly journal articles that are published in any medium. This license does not transfer copyright ownership or authorize a use that interferes with the rights of the author or co‐authors. Copyright ownership remains with the author(s) of the articles.
To accomplish this, faculty members are encouraged to deposit an electronic copy of each scholarly journal article according to the terms of applicable copyright agreements, if any. In the absence of a mandate by a grant funding agency to deposit articles in a specific public access repository, faculty are encouraged to deposit scholarly journal articles in the UF Institutional Repository (IR@UF) and/or in a relevant subject based open access repository.
To facilitate such deposit, faculty members are encouraged to seek to amend terms of future publication agreements to retain the right to use their own work, as well as to retain the right to deposit such work in an open access scholarly repository for public access.
This policy only applies to scholarly journal articles completed after the effective date of this policy and while the author is a member of the University of Florida faculty. Faculty members who deposit their work voluntarily or in accordance with a funding agency mandate should submit an electronic “Notice of Publication” to the Smathers Libraries.
As I read this it doesn’t do much except place a greater admin burden on researchers. What do you think? The full documents, FAQ, and a handy/confusing flow chart are here
PS Until recently we had an OA fund that we could tap into to cover the charge of APCs. That fund is tapped out and there has been little movement to continue it, despite widespread support on campus. My feeling is that fund did more to encourage OA publishing than any other activity on campus.
Bill Laurance and colleagues just published a really interesting paper in the October issue of Bioscience in which they analyzed the pre- and post-PhD publication records of 182 “academics” (faculty members?) from around the world. There is a very nice write up of the results and a link to the paper by co-author Corey Bradshaw, of ConservationBytes fame, here. Their conclusion?
The most important determinant of your ‘long’-term (10-year) publication success is how many papers you’ve written by the time you’ve completed your PhD. This effect increases markedly if we take the number of papers you’ve published three years after PhD completion as a predictor.
I read this paper with great enthusiasm and am inclined to believe the result, even if I disagree with some of their take-home messages for academic hiring practices (see below). I also agree with them that 1) publications are the coin of the realm and 2) we should be encouraging students to publish early (and training them to do so). However, I have a few nagging questions about the data and analyses I haven’t yet gotten decent answers to (I wrote Bill and Posted at ConservationBytes, but no answer yet). In light of the commentary I’ve seen on twitter I’d like to put these questions out there in the hopes they’ll be answered (or at the very least will cause others to pause before fully embracing the conclusions). I sense that some of these issues could be readily addressed with some quick analyses, while others might require more data collection.
Why their analyses might be fundamentally flawed (or not…) or at least not as broadly applicable as they suggest (unless they are).
1) They didn’t sample properly. Well, maybe they did, but we can’t tell because they don’t tell us anything about how the “academics” were selected. Were they selected randomly from national CV databases? By selecting universities and then faculty within a department? The directories of academic societies? How did they choose the countries to include? Were they pooling faculty members, postdocs, research scientists – all of whom have different career demands and time to devote to publication? (NB: on first read I assumed they meant faculty members, since they “incorporated the effects of postdoctoral productivity” and focused on universities to find focal subjects). Scientometric research is no different from ecological work in that how you collect the data will influence your results. Without knowing how the study subjects were chosen, or even what career tracks were included, we can’t evaluate how general their results truly are.
2) They failed to control for the type of institution where their focal researchers (=faculty) are based. Faculty at different kinds of institutions – major research universities, small liberal arts colleges, government or private research institutes, regional state universities – would not be expected to have the same research productivity (indeed, I’d be surprised if they did). If they collected data from faculty at a diversity of school categories, does the trend hold up irrespective of institution type? I doubt it would.
3) They failed to control for Full-time Equivalent (FTE). Even at a primarily research institution like mine (an “RU/VH”, according to the Carnegie Classification System) , the proportion of FTE devoted to research can vary from 10-100%. The correct dependent variable they should have used is the number of publications produced by a faculty member per % of FTE devoted to research. Does the relationship fall apart when correcting for Research FTE?
4) They failed to include “country” as a factor in their model. The study includes faculty from around the world, and they suggest the results are broadly applicable, but they fail to back this up with any stats. Most of my academic experience is in two countries – the US and Brazil. These countries have vastly different academic cultures, educational programs, resources, expectations, and motivational structures. It may very well be that pre- and post publication trends are similar in these vastly different systems, but I’m going to hold off buying how global this effect is until they rerun the models with “country” as an effect in the model. As an aside, how many faculty came from each country? Without seeing some sample sizes, it’s tough to evaluate if the effect might have been driven by just a few countries.
What do I think this means for their results? My sense is that institutional category and % of FTE devoted to research are probably at least as important as pre-hire publication record, and maybe even more so. I think the effect may well be consistent for faculty in different countries, but the magnitude of the effect will vary geographically. If so, all of these would takes a fair amount of the air out of their results. But it may very well be that they can (or even did) test for some of these things, in which case their results stand. Honestly, I don’t care either way, because I think the results would be interesting regardless. I just wish they were as careful collecting and reporting their data and as thorough with their scientometric analyses as they are in their exceptional ecological ones.
PS. Thinking about these issues made me wish they had archived their data and code so I could just go and look up the answers myself. Like this group, who analyzed publication patterns by ecologists with a dataset of over 2000 papers that is freely available at Dryad.
PPS. From p. 821:
If one is comparing different candidates for academic or research jobs, simply tallying the number of early-career publications (at some standardized point in one’s career, such as 3 years post-PhD) appears to be an effective way to identify prospective rising stars.
Oh boy. Let’s leave this one for another day.
UPDATE (12/20): Neither Corey nor Bill responded to my emails or posts on Corey’s blog asking about these issues, so I had to go old school and submit a letter to Bioscience. It and their reply are in press.
Cris Jurinitz, a recent PhD from the University of São Paulo I co-advised with Alexandre Oliveira, has just published one of her thesis chapters in Biotropica. In it, she describes how early-stage survival of two shade-tolerant species is affected by canopy openness, litter depth, ontogenetic stage, and conspecific neighborhood in the understories of secondary forest fragments in the Brazilian Atlantic Forest. It’s a really nice study, and you can find the final version here. Congratulations, Dra. Cris!
Jurinitz, C. F., E. M. Bruna, and A. A. Oliveira. 2013. Synergistic effects of canopy openness, litter depth and ontogeny on seedling performance in forest fragments. Biotropica 45(6): 728-736.
Photo: USP’s Alexandre Oliveira (L) and UF’s Emilio Bruna (R) with their student Dr. Cris Jurinitz in her Atlantic Forest research sites.
Jack Payne is the Vice-President of Food and Agricultural Sciences at UF and he is a great guy – we’re luck to have him. He’s fought for us at the state and national level and is very progressive as university administrators go. But this morning he sent this email to his faculty
Please see memo below from Cathy Wotecki, USDA Chief Scientiest and Under Secretary for REE, which is the office through which our funds flow from USDA. I have concerns about the memo. On the surface it all sounds wonderful – sharing data and feeding the world, but the federally mandated open access rule, to me, has serious complications. Basically, the law claims that if your research was funded by federal dollars, you must make your results available independent of publishing in a peer-reviewed journal, etc. So, how do we protect “truth?” What stops bad data from being released to the public? There are many more implications along this line of reasoning. Also, what about any intellectual property that may be involved in the research? More importantly, the argument being used is that the public pays for the research through their taxes and is therefore entitled to the results. But I ask what public? Once the data becomes public, it will be the citizens of the world who will have access to the results, raising national security issues. Anyway, just some of my thoughts. This will become a huge issue in the coming months as university scientists become more aware of the implications. I do know that the National Academies are meeting next week to discuss this new federal requirement. Soon, AAU, APLU and others should be weighing in on the matter as well as the various professional organizations.
Kudos for seeking faculty input and putting this issue on the radar of researchers who may not be thinking about it. But I’m afraid my response may not have been as convincing as it could have been because I didn’t address any of his concerns regarding biosecurity or intellectual property. Any suggestions? Please post below in the comments.
Jack, The benefits of making data open far outweigh any perceived costs. I lay out some of these benefits out in a recent editorial for a journal of which I am an Editor (http://tinyurl.com/3wqehzw), see also this story in Science: http://tinyurl.com/ykodmu9). The benefits include:
1) Making data (and code used for analyses) publicly available allows others to check your results. Transparency improves science because it catches mistakes, the consequences of which can be tremendous. See this example from economics: http://tinyurl.com/c3jzz27
2) Data can be used in meta-analyses or to address questions not originally envisioned by the people who collected them. I provide an example related to climate change in my editorial.
3) Papers that make data available freely are cited more than papers that don’t. This means they have a greater impact (Piowar et al. 2007. Sharing detailed research data is associated with increased citation rate. PLoS One 2: e308). Link: http://tinyurl.com/ydc3356
4) Many data archiving sites, such as the NSF-supported Data Dryad, allow for an embargo period (typically 1 year post-publication) before data are released to the public. See http://datadryad.org/ . These sites also have datasets in citable formats with DOIs, so researchers will continue to get credit for data collection via citation.
5) Finally, the loss of datasets is a tremendous waster of intellectual effort and public funding. We have an responsibility to spend the public’s funds wisely, and if one’s data die in a filing cabinet or on a hard drive we have essentially wasted taxpayer money.
This train has left the station, we’re just playing catch-up at this point. Indeed, many prestigious journals now require data used in a paper be archived and freely available for the data to be published. There are some legitimate concerns, but have been suitably dealt with in many other places. IFAS needs to encourage its researchers to archive their data in publicly available archives because it’s the ethical thing to do, will make our science more robust, and increase its impact tremendously in both the short and long-term.
PS I practice what I preach. The data for five recent papers my lab has published are freely available for reuse by others at http://tinyurl.com/dxnj2ca.
Emilio has been awarded a Science Without BordersSpecial Visiting Researcher Fellowship from the Brazilian government. This three year award will allow Emilio to continue working with Dr. Heraldo Vasconcelos from the Univerisdade Federal de Uberlândia to understand how herbivores influence Cerrado plant demography.
Science Without Borders is an ambitious program launched by President Dilma Rousseff to consolidate Brazil as a global center of science and technology. They plan to do this in three ways. First, increasing the presence of students, scientists and industry personnel from Brazil in international institutions of excellence – basically, they pay all costs, including tuition, room and board, and insurance – for students or postdocs to spend a year abroad. Second, they encourage young and talented Brazilian researchers currently working abroad to return to Brazil for a while to work with investigators at Brazilian institutions on joint projects. They also fund foreign scientists to spend up to three months a year in Brazil working on collaborative research projects, teaching, and training students. Finally, they promote the internationalization of universities and research centers in Brazil by encouraging the establishment of international partnerships.