This is a guest post by Elita Baldridge (@elitabaldridge). She is a graduate student in our group who has been navigating the development of a chronic illness during graduate school. She is sharing her story to help spread awareness of the challenges faced by graduate students with chronic illnesses. She wrote an excellent post on the PhDisabled blog about the initial development of her illness that I encourage you to read first.
During my time as a Ph.D. student, I developed a host of bizarre, productivity eating symptoms, and have been trying to make progress on my dissertation while also spending a lot of time at doctors’ offices trying to figure out what is wrong with me. I wrote an earlier blog post about dealing with the development of a chronic illness as a graduate student at the PhDisabled Blog.
When the rheumatologist handed me a yellow pamphlet labeled “Fibromyalgia”, I felt a great sense of relief. My mystery illness had a diagnosis, so I had a better idea of what to expect. While chronic, at least fibromyalgia isn’t doing any permanent damage to joints or brain. However, there isn’t a lot known about it, the treatment options are limited, and the primary literature is full of appallingly small sample sizes.
There are many symptoms which basically consisting of feeling like you have the flu all the time, with all the associated aches and pains. The worst one for me, because it interferes with my highly prized ability to think, is the cognitive dysfunction, or, in common parlance, “fibro fog”. This is a problem when you are actively trying to get research done, as sometimes you remember what you need to do, but can’t quite figure out how navigating to your files in your computer works, what to do with the mouse, or how to get the computer on. I frequently finish sentences with a wave of my hand and the word “thingy”. Sometimes I cannot do simple math, as I do not know what the numbers mean, or what to do next. Depending on the severity, the cognitive dysfunction can render me unable to work on my dissertation as I simply cannot understand what I am supposed to do. I’m not able to drive anymore, due to the general fogginess, but I never liked driving that much anyway. Sometimes I need a cane, because my balance is off or I cannot walk in a straight line, and I need the extra help. Sometimes I can’t be in a vertical position, because verticality renders me so dizzy that I vomit.
I am actually doing really well for a fibromyalgia patient. I know this, because the rheumatologist who diagnosed me told me that I was doing remarkably well. I am both smug that I am doing better than average, because I’m competitive that way, and also slightly disappointed that this level of functioning is the new good. I would have been more disappointed, only I had a decent amount of time to get used to the idea that whatever was going on was chronic and “good” was going to need to be redefined. My primary care doctor had already found a medication that relieved the aches and pains before I got an official diagnosis. Thus, before receiving an official diagnosis, I was already doing pretty much everything that can be done medication wise, and I had already figured out coping mechanisms for the rest of it. I keep to a strict sleep schedule, which I’ve always done anyway, and I’ve continued exercising, which is really important in reducing the impact of fibromyalgia. I should be able to work up my exercise slowly so that I can start riding my bicycle short distances again, but the long 50+ mile rides I used to do are probably out.
Fortunately, my research interests have always been well suited to a macroecological approach, which leaves me well able to do science when my brain is functioning well enough. I can test my questions without having to collect data from the field or lab, and it’s easy to do all the work I need to from home. My work station is set up right by the couch, so I can lay down and rest when I need to. I have to be careful to take frequent breaks, lest working too long in one position cause a flare up. This is much easier than going up to campus, which involves putting on my healthy person mask to avoid sympathy, pity, and questions, and either a long bus ride or getting a ride from my husband. And sometimes, real people clothes and shoes hurt, which means I’m more comfortable and spending less energy if I can just wear pajamas and socks, instead of jeans and shoes.
Understand that I am not sharing all of this because I want sympathy or pity. I am sharing my experience as a Ph.D. student developing and being diagnosed with a chronic illness because I, unlike many students with any number of other short term or long term disabling conditions, have a lot of support. Because I have a great deal of family support, departmental support, and support from the other Weecologists and our fearless leaders, I should be able to limp through the rest of my Ph.D. If I did not have this support, it is very likely that I would not be able to continue with my dissertation. If I did not have support from ALL of these sources, it is also very likely that I would not be able to continue. While I hope that I will be able contribute to science with my dissertation, I also think that I can contribute to science by facilitating discussion about some of the problems that chronically ill students face, and hopefully finding solutions to some of those problems. To that end, I have started an open GitHub repository to provide a database of resources that can help students continue their training and would welcome additional contributions. Unfortunately, there doesn’t seem to be a lot. Many medical Leave of Absence programs prevent students from accessing university resources- which also frequently includes access to subsidized health insurance and potentially the student’s doctor, as well as removing the student from deferred student loans.
I have fibromyalgia. I also have contributions to make to science. While I am, of course, biased, I think that some contribution is better than no contribution. I’d rather be defined by my contributions, rather than my limitations, and I’m glad that my university and my lab aren’t defining me by my limitations, but are rather helping me to make contributions to science to the best of my ability.
As some of you may know, I’ve been working with Michael Angilletta for the past year on organizing a Gordon Research Conference. I announced the mentoring program that is affiliated with the conference last week, but here is the official info on the conference itself. Please forgive a little repetition from the mentoring program post.
Application Deadline: June 22, 2014
When and Where: July 20-25 2014 at the University of New England, Biddeford Maine
Conference Topic: Many of the impacts humans have on nature affect patterns and processes at multiple spatial, temporal, or organizational scales. Thus predicting the response of nature to human impacts is challenging because changes in one scale can have profound impacts on patterns and processes at other scales of nature. Because ecology has traditionally been focused on patterns and processes at single scales, we have few approaches that allow us to understand cross-scale feedbacks that can influence the patterns and processes we are interested in predicting. The Gordon Research Conference on ‘Unifying Ecology Across Scales: the role of nutrients, metabolism, and physiology’ is a small conference focused on exploring how the availability, acquisition, and transference of energy and nutrients can link patterns and processes across spatial, organizational, and temporal scales. Our goal is to provide a venue for people interested in this topic to discuss the current state of the field and discuss how to promising avenues of future research. Research interests of participants span the diverse areas of ecology, evolution, and physiology, but are united in an interest to use energy and nutrients to unify different areas and approaches to ecology.
What is a Gordon Research Conference?: Gordon Research Conferences (GRC) are well known in some fields, but the number of ecology related GRCs is low, so many of us haven’t heard of one before. A Gordon Research Conference is a small conference ( < 200 people) focused on a specific topic. In our case, the topic is trying to link patterns and processes across scales using nutrients, metabolism, and physiology. Speakers at GRCs are by invite only, but there is a poster session almost every afternoon for attendees to present their research. The poster session is not just for the junior people to present. Well known senior people tack up posters and stand by them too.
The structure of a GRC is also pretty unique. Talks occur in the mornings and evenings, leaving the afternoons free for informal discussions, formation of collaborations, and recreational activities (our conference site has kayaking as well as other organized opportunities). Attendees all sleep in the same dorm and eat at the same cafeteria, further creating opportunities for interactions and discussions.
Applying to attend: Registration is now open.
GRC’s have a unique approach to the application process. You have to submit an application which the conference chairs (that’s me and Michael Angilletta) can then decide to accept or reject. Then you’ll get an ‘invitation’ to actually register. Don’t let the fear of rejection stop you from applying though. We have historically had space for everyone who wants to come.
Special events for graduate students and postdocs: We have a Gordon Research Seminar (GRS) associated with our conference focused on “understanding the drivers of biological systems by integrating metabolism, physiology, and macroecology”. Gordon Research Seminars provide opportunities for graduate students and postdocs to present their research and network with their peers and a small number of senior scientists mentors before the main conference. Feedback from people who have attended these has been universally positive. In fact, when we didn’t have these one year, there was a huge outcry to bring them back. You have to apply for the GRS separately from the GRC. The conference chairs for the GRS are Sarah Supp and Sarah Diamond. The GRS registration process is also currently open. Dates for the GRS are July 19-20, 2014.
This year we are also excited to announce we have a mentoring program at the conference that graduate students and postdocs who plan on attending the conference can apply for. We have limited slots for this (approximately 20). Details can be found here.
Who is Speaking?: To (hopefully) get you even more excited about attending, here is the list of session topics, speakers, and discussion leaders for the conference. UPDATED: We’ve added a number of lightning talks (short talks). Those speakers have now been added below. If you want titles as well, the full schedule for the conference (with talk titles) is available here
Session Topic 1: Developing Unified Theories of Ecology
Leader Name: Pablo Marquet
Session Topic 2: Macrophysiology Meets Macroecology
Leader Name: Lauren Buckley
Session Topic 3: Biogeography of Environmental Tolerance
Leader Name: Jennifer Sunday
Lightning Talks: Lacy Chick / Richard Feldman
Session Topic 4: Metabolic Adaptation to Changing Environments
Leader Name: Craig White
Session Topic 5: Mechanistic Basis of Macroecological Patterns
Leader Name: Brian Enquist
Session Topic 6: Linking Organismal Traits to Community Dynamics
Leader Name: Elena Litchman
Session Topic 7: Using Stoichiometry to Link Organisms and Ecosystems
Leader Name: Susan Kilham
Session Topic 8: Predicting Diversity across Scales
Leader Name: Brian McGill
Session Topic 9: Integrating Ecological Processes at the Macroscale
Leader Name: James Brown
The British Ecological Society has announced that will now allow the submission of papers with preprints (formal language here). This means that you can now submit preprinted papers to Journal of Ecology, Journal of Animal Ecology, Methods in Ecology and Evolution, Journal of Applied Ecology, and Functional Ecology. By allowing preprints BES joins the Ecological Society of America which instituted a pro-preprint policy last year. While BES’s formal policy is still a little more vague than I would like*, they have confirmed via Twitter that even preprints with open licenses are OK as long as they are not updated following peer review.
Preprints are important because they:
- Speed up the progress of science by allowing research to be discussed and built on as soon as it is finished
- Allow early career scientists to establish themselves more rapidly
- Improve the quality of published research by allowing a potentially large pool reviewers to comment on and improve the manuscript (see our excellent experience with this)
BES getting on board with preprints is particularly great news because the number of ecology journals that do not allow preprints is rapidly shrinking to the point that ecologists will no longer need to consider where they might want to submit their papers when deciding whether or not to post preprints. The only major blocker at this point to my mind is Ecology Letters. So, my thanks to BES for helping move science forward!
*Which is why I waited 3 weeks for clarification before posting.
Graduate Student and Postdoctoral Mentoring Program
Gordon Research Conference: Unifying Ecology across Scales
ADDED BELOW: Who can apply is added under financial support (why it’s where will make more sense when you read it)
Time and Place:
July 19-25, 2014 at the University of New England in Biddeford, Maine
Ecological patterns and processes occur at multiple scales of space, time, and organization. This complexity makes predicting ecological responses challenging because changes in one scale can have profound impacts on patterns and processes at other scales. Because subdisciplines have traditionally focused on one or two scales, we have few approaches that enable us to predict the connections and feedbacks across scales that shape biodiversity. This Gordon Research Conference, titled “Unifying ecology across scales: the roles of nutrients, metabolism, and physiology” will bring a small group of experts together to explore how the flow of energy and nutrients can be used to understand patterns and processes across scales. Research interests of the participants will span diverse areas of ecology, evolution, and physiology, but are united by the goal of using energetics and stoichiometry to unify subdisciplines of ecology. The schedule includes a 5-day research conference (co-chaired by Morgan Ernest & Michael Angilletta) preceded by a 2-day research seminar oriented toward students and postdocs (co-chaired by Sarah Supp & Sarah Diamond).
The National Science Foundation will support a mentoring program at this conference aimed at graduate students and postdoctoral researchers. This program will provide participants with the following opportunities: 1) presenting their research as either a short ~10 minute ‘lightning’ talk during the Gordon Research Conference or a full-length 30 minute talk during the Gordon Research Seminar, 2) one-on-one interactions with a more senior researcher at the conference who will serve as a career mentor, and 3) group discussions on topics pertaining to success as an early-career scientist. Applicants must commit to attending the 2-day seminar and the 5-day conference.
Graduate students and postdocs accepted into the program will receive up to $1000 for registration fees and up to $300 for travel expenses. Registration for all events includes meals and housing.
ADDED: While all current graduate students and postdocs are encouraged to apply, financial support is slightly restricted for non-US residents. We cannot fund foreign travel for non US citizens, but can reimburse for travel expenses incurred within the US. Both US and non-US students/postdocs qualify for the registration fees funds. We are allowed for pay for foreign travel for US Citizens.
How to Apply:
Graduate students or postdoctoral researchers interested in participating in the conference mentoring program should send their current curriculum vitae and an abstract of their proposed talk for the conference (≤ 250 words) to Morgan Ernest at email@example.com. Both items should be combined in a single PDF file.
Deadline: 5 pm EST on Feb 1, 2014
For more information:
Gordon Research Conference
Email: Morgan Ernest (firstname.lastname@example.org) or Michael Angilletta (email@example.com)
Gordon Research Seminar
Email: Sarah Supp (firstname.lastname@example.org) or Sarah Diamond (email@example.com)
This is a guest post by Dan McGlinn, a weecology postdoc (@DanMcGlinn on Twitter). It is a Research Summary of: McGlinn, D.J., X. Xiao, and E.P. White. 2013. An empirical evaluation of four variants of a universal species–area relationship. PeerJ 1:e212 http://dx.doi.org/10.7717/peerj.212. These posts are intended to help communicate our research to folks who might not have the time, energy, expertise, or inclination to read the full paper, but who are interested in a <1000 general language summary.
It is well established in ecology that if the area of a sample is increased you will in general see an increase in the number species observed. There are a lot of different reasons why larger areas harbor more species: larger areas contain more individuals, habitats, and environmental variation, and they are likely to cross more barriers to dispersal – all things that promote more species to be able to exist together in an area. We typically observe relatively smooth and simple looking increases in species number with area. This observation has mystified ecologists: How can a pattern that should be influenced by many different and biologically idiosyncratic processes appear so similar across scales, taxonomic groups, and ecological systems?
Recently a theory was proposed (Harte et al. 2008, Harte et al. 2009) which suggests that detailed knowledge of the complex processes that influence the increase in species number may not be necessary to accurately predict the pattern. The theory proposes that ecological systems tend to simply be in their most likely configuration. Specifically, the theory suggests that if we have information on the total number of species and individuals in an area then we can predict the number of species in smaller portions of that area.
Published work on this new theory suggests that it has potential for accurately predicting how species number changes with area; however, it has not been appreciated that there are actually four different ways that the theory can be operationalized to make a prediction. We were interested to learn
- Can the theory accurately predict how species number changes with area across many different ecological systems, and
- Do the different versions of the theory consistently perform better than others
To answer these questions we needed data. We searched online and made requests to our colleagues for datasets that documented the spatial configuration of ecological communities. We were able to pull together a collection of 16 plant community datasets. The communities spanned a wide range of systems including hyper-diverse, old-growth tropical forests, a disturbance prone tropical forest, temperate oak-hickory and pine forests, a Mediterranean mixed-evergreen forest, a low diversity oak woodland, and a serpentine grassland.
Fig 1. A) Results from one of the datasets, the open circles display the observed data and the lines are the four different versions of the theory we examined. B) A comparison of the observed and predicted number of species across all areas and communities we examined for one of the versions of the theory.
Across the different communities we found that the theory was generally quite accurate at predicting the number of species (Fig 1 above), and that one of the versions of the theory was typically better than the others in terms of the accuracy of its predictions and the quantity of information it required to make predictions. There were a couple of noteworthy exceptions in our results. The low diversity oak woodland and the serpentine grassland both displayed unusual patterns of change in richness. The species in the serpentine grassland were more spatially clustered than was typically observed in the other communities and thus better described by the versions of the theory that predicted stronger clustering. Abundance in the oak woodland was primarily distributed across two species whereas the other 5 species where only observed once or twice. This unusual pattern of abundance resulted in a rather unique S-shaped relationship between the number of species and area and required inputting the observed species abundances to accurately model the pattern.
The two key findings from our study were
- The theory provides a practical tool for accurately predicting the number of species in sub-samples of a given site using only information on the total number of species and individuals in that entire area.
- The different versions of the theory do make different predictions and one appears to be superior
Of course there are still a lot of interesting questions to address. One question we are interested in is whether or not we can predict the inputs of the theory (total number of species and individuals for a community) using a statistical model and then plug those predictions into the theory to generate accurate fine-scaled predictions. This kind of application would be important for conservation applications because it would allow scientists to estimate the spatial pattern of rarity and diversity in the community without having to sample it directly. We are also interested in future development of the theory that provides predictions for the number of species at areas that are larger (rather than smaller) than the reference point which may have greater applicability to conservation work.
The accuracy of the theory also has the potential to help us understand the role of specific biological processes in shaping the relationship between species number and area. Because the theory didn’t include any explicit biological processes, our findings suggest that specific processes may only influence the observed relationship indirectly through the total number of species and individuals. Our results do not suggest that biological processes are not shaping the relationship but only that their influence may be rather indirect. This may be welcome news to practitioners who rely on the relationship between species number and area to devise reserve designs and predict the effects of habitat loss on diversity.
Harte, J., A. B. Smith, and D. Storch. 2009. Biodiversity scales from plots to biomes with a universal species-area curve. Ecology Letters 12:789–797.
Harte, J., T. Zillio, E. Conlisk, and A. B. Smith. 2008. Maximum entropy and the state-variable approach to macroecology. Ecology 89:2700–2711.
Doing science in academia involves a lot of rejection and negative feedback. Between grant agencies single digit funding rates, pressure to publish in a few "top" journals all of which have rejection rates of 90% or higher , and the growing gulf between the number of academic jobs and the number of graduate students and postdocs , spending even a small amount of time in academia pretty much guarantees that you’ll see a lot of rejection. In addition, even when things are going well we tend to focus on providing as much negative feedback as possible. Paper reviews, grant reviews, and most university evaluation and committee meetings are focused on the negatives. Even students with awesome projects that are progressing well and junior faculty who are cruising towards tenure have at least one meeting a year where someone in a position of power will try their best to enumerate all of things you could be doing better . This isn’t always a bad thing  and I’m sure it isn’t restricted to academia or science (these are just the worlds I know), but it does make keeping a positive attitude and reasonable sense of self-worth a bit… challenging.
One of the things that I do to help me remember why I keep doing this is my Why File. It’s a file where I copy and paste reminders of the positive things that happen throughout the year . These typically aren’t the sort of things that end up on my CV. I have my CV for tracking that sort of thing and frankly the number of papers I’ve published and grants I’ve received isn’t really what gets me out of bed in the morning. My Why File contains things like:
- Email from students in my courses, or comments on evaluations, telling me how much of an impact the skills they learned have had on their ability to do science
- Notes from my graduate students, postdocs, and undergraduate researchers thanking me for supporting them, inspiring them, or giving them good advice
- Positive feedback from mentors and people I respect that help remind me that I’m not an impostor
- Tweets from folks reaffirming that an issue or approach I’m advocating for is changing what they do or how they do it
- Pictures of thank you cards or creative things that people in my lab have done
- And even things that in a lot of ways are kind of silly, but that still make me smile, like screen shots of being retweeted by Jimmy Wales or of Tim O’Reilly plugging one of my papers.
If you’ve said something nice to me in the past few years be it in person, by email, on twitter, or in a handwritten note, there’s a good chance that it’s in my Why File helping me keep going at the end of a long week or a long day. And that’s the other key message of this post. We often don’t realize how important it is to say thanks to the folks who are having a positive influence on us from time to time. Or, maybe we feel uncomfortable doing so because we think these folks are so talented and awesome that they don’t need it, or won’t care, or might see this positive feedback as silly or disingenuous. Well, as Julio Betancourt once said, "You can’t hug your reprints", so don’t be afraid to tell a mentor, a student, or a colleague when you think they’re doing a great job. You might just end up in their Why File.
What do you do to help you stay sane in academia, science, or any other job that regularly reminds you of how imperfect you really are?
 This idea that where you publish not what you publish is a problem, but not the subject of this post.
 There are lots of great ways to use a PhD, but unfortunately not everyone takes that to heart.
 Of course the people doing this are (at least sometimes) doing so with the best intentions, but I personally think it would be surprisingly productive to just say, "You’re doing an awesome job. Keep it up." every once in a while.
 There is often a goal to the negativity, e.g., helping a paper or person reach their maximum potential, but again I think we tend to undervalue the consequences of this negativity in terms of motivation [4b].
[4b] Hmm, apparently I should write a blog post on this since it now has two footnotes worth of material.
 I use a Markdown file, but a simple text file or a MS Word document would work just fine as well for most things.
Sam Scheiner published a piece recently on ecology’s lack of engagement with theory. Frankly, the title pretty much tells you his conclusion “The ecological literature: an idea free distribution”, but if you want to know more, either read the original piece (it’s short) or EEB & Flow’s nice write up on it. The empirical-theoretical divide is a topic I’ve been pondering for a while. A long time ago (I was a postdoc), in a galaxy far far away (New Mexico), I read an awesome book called “The Making of the Atomic Bomb”*. It’s a wonderful history on the discovery of the atom and the race to harness its energy in the midst of World War II. In the book, a tight interaction between theorists and empiricists is portrayed, with empiricists pouring over the latest theories trying to figure out how to test them and theorists pouring over the latest results trying to understand what they might mean theoretically. It’s a gripping tale. In contrast to the scientific process portrayed in the book, ecology lacks the same tight integration between theoretical development and empirical testing. What is going on in ecology that might be impeding this scientific give and take? I have some ideas, though they are admittedly from the perspective of an empirical ecologist.
1) Empiricists and math literacy. This is the one that will have the theoreticians nodding vigorously. In ecology, empiricists often lack a basic level of comfort and literacy with math. In my graduate level class, we read a lot of primary literature. Some of those papers are math heavy. Without fail, my students see an equation and freeze up. They don’t even know how to think about what that equation might mean. And – let’s be honest here – it’s not just students that this happens to. As I tell my students, math is another language. You don’t necessarily need to be able to speak it fluently, but to be a literate scientist you at least need to be able to ask where the bathroom is. I’d say that right now, many empiricists can’t ask for the bathroom. If we’re going to bridge the empirical-theoretical divide, empiricists need to get more comfortable with seeing and interpreting equations.
2) Theoreticians and ecological literacy. This is the one that will have the empiricists nodding. Theory papers are often more focused on the mathematical aspects of the theory than the ecological meaning of the assumptions, variables, parameters, and predictions. I don’t think it’s a coincidence that some of the theories that have received the most empirical attention were formulated by people with a strong empirical component to their research; examples include: R* coexistence theory (Tilman, long-term field experiments at Cedar Creek), Metabolic Theory of Ecology (Brown, long-term field experiments at Portal), neutral theory (Hubbell, long-term research at Barro Colorado Island), and Chessonian coexistence (Chesson, long-term field experiments in SE Arizona)**. These authors have tried to communicate their theories in biological terms. Given the limited math literacy of empiricists, we need theorists to be better at communicating the ecology captured by the math in order to get empiricists engaged with the theory. Even though the most precise and concise way of providing directions to the bathroom is to provide a latitude, longitude, and datum, it’s really better to tell someone to take a left on the Champs Elysees.
3) Communication between empiricists and theoreticians. Given the two points above, it should come as no surprise that we have relatively limited communication between the groups. All sorts of pathologies can arise when two groups don’t know how to communicate to each other. For example, we have separate theory sessions at the annual Ecological Society of America meetings! I’ve always found that odd. Like theory is its own subdiscipline studying things of little relevance to the other population, community, and ecosystem ecologists at the meeting! If we are not communicating, then empiricists are unaware of relevant theories and theoreticians are unaware of new empirical developments that can improve existing theory or point towards the need for new theories. Without communication, our intellectual progress is severely hampered. We end up with piles of data that are only used for understanding a specific system at a specific point in time. We also end up with piles of theories that serve as little more than mathematical ornaments, because they have not been tested. Maybe I’m alone in this, but I think this is something that needs to be remedied.
4) Testing theories is hard. In ecology, testing theories is often hard. It’s rare that a theory will make predictions that simply require us to document that X impacts Y (e.g., does fire impact nitrogen levels in soils?). Coexistence theories like those developed by Peter Chesson are a great example of this problem. The storage effect and stabilizing vs. equalizing mechanisms for coexistence are big complex concepts that require a lot of thought and effort to test in useful ways. We need a class of creative empiricists, who can engage actively with theory, assess the key aspects of the theory that are testable, and figure out how to design those tests. We also need theorists who communicate broadly about the key predictions of their models, important underlying assumptions, and explicitly describe what good tests of their theories would entail, so that empiricists are correctly testing those models.
So, assuming that a better integration of theory and empirical research is desired, how do we accomplish it? Honestly, I don’t have a prescription for fixing this right now. But I do think there are some key elements that we need to be thinking about:
1) More context specific exposure to mathematics for our undergrads and grads. Shipping them off to Calculus 101 in the Mathematics Department and hoping they pick it up there is clearly not working.
2) Better communication between theorists and empiricists. There’s lots of ways to work on this. In our group, we house my empirically minded students with Ethan’s more quantitative students and also run joint lab meetings. We’ve been pleased with the results, but how to scale this up to whole programs is less clear to me. Another possibility is a series of workshops or even a center whose mission is to bring together theoreticians and empiricists interested in similar questions. The one thing I do know is that this isn’t something we can just fix through the literature. The current barriers are such that we will need venues for in-person exchanges as the two groups learn each other’s languages.
3) Broad conversations about how we test (and improve) theories. As a field, we’ve spent a lot of time talking about how to rigorously test cause-effect relationships and assessing whether patterns in nature are real or can be explained by null models. Our conversations about how to create a good dynamic for designing theory, rigorously testing it, and using the empirical results to improve the theory, has – as far as I am aware – not been very vigorous in ecology.
Addressing these key elements might not create a “Golden Age of Ecology”, but I steadfastly believe that no single approach is sufficient for addressing the complicated questions facing ecology. In that context, improving how theoreticians and empiricists interact can only be a plus.
* Note to the NSA, who undoubtedly had a red light go off somewhere when that precise combination of words crossed their giga-computers sucking in the internet: “The Making of the Atomic Bomb” by Richard Rhodes is a history book, not a how-to manual.
**I think the fact that all of them have long-term field programs is very very interesting, but a topic for another day.
I have to admit I’m a superhero movie junkie. In particular, we watch the Avengers movie a lot in our household. I mean… a lot. Sometimes I really wish I was Natasha Romanoff (aka the Black Widow) from the Avengers. That would be rad. I could use my tricky spy interrogation skills to get program officers to tell me how to alter my proposal to get funded. I could use my wicked fighting skills to take down anyone acting inappropriately towards my students. Yeah, it would be awesome.
Except that every superhero story has the following message: with great power comes great responsibility.
We don’t think about that duality much in the professoriate. I think because typically we spend so many years with so little power as graduate students and postdocs. Even as an untenured faculty member, we often focus on being at the mercy of senior faculty and administrators upon whom our job prospects depend. Even once we’re tenured, we often don’t think in terms of ‘power’ beyond the interfaculty dynamics within a department because faculty increasingly have less say in the governance of universities.
But the truth is, even though we don’t think we have power, we do. We have a lot of it. Over the undergrads in our courses whose futures depend on what they learn (and the grades they earn) in our classes. Over the graduate students and postdocs in our labs whose futures and everyday experiences depend directly on how we treat them. On the graduate students in our graduate programs who need us on their committees or need to take a specific course from us to be successful in their research or career path. Over the students and postdocs who are networking at meetings to connect with potential collaborators, mentors, etc. Over anyone whose papers and grants we are reviewing. We have a lot of power over the fates of a lot of people. And with great power comes great responsibility.
If you read a lot of blogs or participate in Twitter, you will have seen the growing number of posts on gender discrimination and sexual harassment that people (including people in ecology & evolution) have experienced**. Some of those experiences are sheer predatory behavior by people purposefully abusing their power. Some of it seems like people who don’t recognize that they have power that can be abused. And sometimes these incidents arise because someone is having a bad day – at home, at work, whatever – and in that unhappy space people put down others thoughtlessly or even purposefully to feel better about themselves. But the truth, so eloquently stated by one of my favorite bloggers Odyssey is that “Power doesn’t give a shit about your personal life”. It also doesn’t care if you don’t realize you have that power. Just because you don’t realize you have power over others doesn’t mean it doesn’t exist. You still have the responsibility that goes with it. These horrifying stories of gender discrimination and sexual harassment are clear abuses of power and it is important as a community that we deal with this. We also need to remember that they are not the only way to abuse power. Stories about abuses of power should serve as an important moment for all of us, men and women, junior and senior, to reflect on the power we do have and ponder using it wisely. I promise you someone out there will be grateful you did.
**If you don’t know what I’m referring to, I would strongly recommend going to read these key posts/articles: DNLee a postdoc, and prominent blogger, called a whore for saying no to a guest blog request, A writer approached a prominent scientific blogger about work and received a creepifying interaction for her troubles, a scientist from the ecology/evolution neck of the woods talks poignantly about her experiences with sexual harrassment, and the twitter outpouring of women expressing how sexual harassment has made them doubt themselves and their abilities.
Academic publishing is in a dynamic state these days with large numbers of new journals popping up on a regular basis. Some of these new journals are actively experimenting with changing traditional approaches to publication and peer review in potentially important ways. So, I thought I’d provide a quick introduction to some of the new kids on the block that I think have the potential to change our approach to academic publishing.
PeerJ is in some ways a fairly standard PLOS One style open access journal. Like PLOS One they only publish primary research (no reviews or opinion pieces) and that research is evaluated only on the quality of the science not on its potential impact. However, what makes PeerJ different (and the reason that I’m volunteering my time as an associate editor for them) is their philosophy that in the era of the modern web it should it should be both cheap and easy to publish scientific papers:
We aim to drive the costs of publishing down, while improving the overall publishing experience, and providing authors with a publication venue suitable for the 21st Century.
The pricing model is really interesting. Instead of a flat fee per paper PeerJ uses a lifetime author memberships. For $99 (total for life) you can publish 1 paper/year. For $199 you can publish 2 papers/year and for $299 you can publish unlimited papers for life. Every author has to have a membership so for a group of 5 authors publishing in PeerJ for the first time it would cost $495, but that’s still about 1/3 of what you’d pay at PLOS One and 1/6 of what you’d pay to make a paper open access at a Wiley journal. And that same group of authors can publish again next year for free. How can they publish for so much less than anyone else (and whether it is sustainable) is a bit of open question, but they have clearly spent a lot of time (and serious publishing experience) thinking about how to automate and scale publication in an affordable manner both technically and in terms things like typesetting (since single column text no attempt to wrap text around tables and figures is presumably much easier to typeset). If you “follow the money” as Brian McGill suggests then the path may well lead you to PeerJ.
Other cool things about PeerJ:
- Optional open review (authors decide whether reviews are posted with accepted manuscripts, reviewers decide whether to sign reviews)
- Ability to comment on manuscripts with points being given for good comments.
- A focus on making life easy for authors, reviewers, and editors, including a website that is an absolute joy compared to interact with and a lack of rigid formatting guidelines that have to be satisfied for a paper to be reviewed.
We want authors spending their time doing science, not formatting. We include reference formatting as a guide to make it easier for editors, reviewers, and PrePrint readers, but will not strictly enforce the specific formatting rules as long as the full citation is clear. Styles will be normalized by us if your manuscript is accepted.
Now there’s a definable piece of added value.
Faculty of 1000 Research
Faculty of 1000 Research‘s novelty comes from a focus on post-publication peer review. Like PLOS One & PeerJ it reviews based on quality rather than potential impact, and it has a standard per paper pricing model. However, when you submit a paper to F1000 it is immediately posted publicly online, as a preprint of sorts. They then contact reviewers to review the manuscript. Reviews are posted publicly with the reviewers names. Each review includes a status designation of “Approved” (similar to Accept or Minor Revisions), “Approved with Reservations” (similar to Major Revisions), and “Not Approved” (similar to Reject). Authors can upload new versions of the paper to satisfy reviewers comments (along with a summary/explanation of the changes made), and reviewers can provide new reviews and new ratings. If an article receives two “Approved” ratings or one “Approved” and two “Approved with Reservations” ratings then it is considered accepted. It is then identified on the site as having passed peer review, and is indexed in standard journal databases. The peer review process is also open to anyone, so if you want to write a review of a paper you can, no invite required.
It’s important to note that the individuals who are invited to review the paper are recommended by the authors. They are checked to make sure that they don’t have conflicts of interest and are reasonably qualified before being invited, but there isn’t a significant editorial hand in selecting reviewers. This could be seen as resulting in biased reviews, since one is likely to select reviewers that may be biased towards liking you work. However, this is tempered by the fact that the reviewers name and review are publicly attached to the paper, and therefore they are putting their scientific reputation on the line when they support a paper (as argued more extensively by Aarssen & Lortie 2011).
In effect, F1000 is modeling a system of exclusively post-publication peer review, with a slight twist of not considering something “published/accepted” until a minimum number of positive reviews are received. This is a bold move since many scientists are not comfortable with this model of peer review, but it has the potential to vastly speed up the rate of scientific communication in the same way that preprints do. So, I for one think this is an experiment worth conducting, which is why I recently reviewed a paper there.
Oh, and ecologists can currently publish there for free (until the end of the year).
Frontiers in X
I have the least personal experience with the Frontiers’ journals (including the soon to launch Frontiers in Ecology & Evolution). Like F1000Research the ground breaking nature of Frontiers is in peer review, but instead of moving towards a focus on post-publication peer review they are attempting to change how pre-publication review works. They are trying to make review a more collaborative effort between reviewers and authors to improve the quality of the paper.
As with PeerJ and F1000Research, Frontiers is open access and has a review process that focuses on “the accuracy and validity of articles, not on evaluating their significance”. What makes Frontiers different is their two step review process. The first step appears to be a fairly standard pre-publication peer review, where “review editors” provide independent assessments of the paper. The second step (the “Interactive Review phase”) is where the collaboration comes in. Using an “Interactive Review Forum” the authors and all of the reviewers (and if desirable the associate editor and even the editor in chief for the subdiscipline) work collaboratively to improve the paper to the point that the reviewers support its publication. If disagreements arise the associate editor is tasked with acting as a mediator in the conversation. If a paper is eventually accepted then the reviewers names are included with the paper and taken as indicating that they sign off on the quality of the paper (see Aarssen & Lortie 2011 for more discussion of this idea; reviewers can withdraw from the process at any point in which case their names are not included).
I think this is an interesting approach because it attempts to make the review process a friendlier and more interactive process that focuses on quickly converging through conversation on acceptable solutions rather than slow long-form exchanges through multiple rounds of conventional peer review that can often end up focusing as much on judging as improving. While I don’t have any personal experiences with this system I’ve seen a number of associate editors talk very positively about the process at Frontiers.
This post isn’t intended to advocate for any of these particular journals or approaches. These are definitely experimental and we may find that some of them have serious limitations. What I do advocate for is that we conduct these kinds of experiments with academic publishing and support the folks who are taking the lead by developing and test driving these systems to see how they work. To do anything else strikes me as accepting that current academic publishing practices are at their global optimum. That seems fairly unlikely to me, which makes the scientist in me want to explore different approaches so that we can find out how to best evaluate and improve scientific research.
UPDATE: Fixed link to the Faculty of 1000 Research paper that I reviewed. Thanks Jeremy!
UPDATE 2: Added a missing link to Faculty of 1000 Research’s main site.
UPDATE 3: Fixed the missing link to Frontiers in Ecology & Evolution. Apparently I was seriously linking challenged this morning.
It’s job season. It’s that time of year again when our young scientists pour over a wide variety of job ads and ask themselves that critically important question: do I apply?
In some ways, this is the most critical step in the entire job application process. Yes, your job packet is important. There’s the goldilocks problem of conveying your awesome in the cover letter but worrying about sounding conceited. There’s writing your CV. There’s thinking about the institution your application is going to and what it values. Yadda yadda yadda. There are lots of great resources to get advice on these things. No, I’m here to talk about one of the lesser discussed issues of the job packet: Choosing to send an application in.
I’m going to give my advice through a little story. It’s a story only one other person knows in its complete form.
Many years ago, I was a young post-doc desperately applying for jobs. I had interviews, but no offers. My postdoc funding was running out (again) and I was pretty demoralized. I saw the following job ad:
ASSISTANT PROFESSOR — SPATIAL ECOLOGY
Department of Biology and Ecology Center
Utah State University
The Department of Biology (http://www. biology.usu.edu) and the Ecology Center (http://www.usu.edu/ecology) at Utah State University seek a tenure-track assistant professor in spatial ecology. Candidates must have a Ph.D. or equivalent in biology, ecology, or a related field; show evidence of the ability to sustain an extramurally funded research program; and be able to teach effectively at the undergraduate and graduate levels. Postdoctoral experience is preferred. We seek an ecologist investigating the effects of global change on the patterns, processes, and mechanisms of the spatial distributions of populations and communities. The research must complement current ecological and evolutionary research at USU. We prefer a person that can collaborate with one or more projects in landscape ecology, conservation biology, pollination biology, invasion ecology, and ecosystem ecology and modeling. Applicants with the ability to integrate mechanisms at the organismal level with patterns and predictions of range shifts at the regional to global scales will be given favorable consideration. The teaching assignment is open depending on research specialty. Deadline: Feb 1, 2004.
The description had little overlap with what I did. I didn’t (and still don’t) do spatial distributions of anything. I didn’t do (on my own or in collaboration) any work on landscape ecology, applied conservation biology, pollination biology, invasion ecology, or ecosystem ecology or modeling. I didn’t do range shifts at any scale. My work was in the realm of understanding how global change impacts communities and I do compare community structure and dynamics across space and time. I did feel like I could make an argument that I integrated organismal level mechanisms with higher levels of biological organization. I also felt like my research was well suited for collaborating broadly with people doing landscape ecology, conservation biology, etc. In short, this job ad was clearly not a perfect match for me but I felt like I could make an argument that I fit pieces of what they were looking for. I decided to go ahead and apply. My references sent in my letters of recommendation. But as the deadline approached, I had a serious case of imposter syndrome. I wasn’t a perfect fit for that job ad and all the rejections were really damaging my limited self-esteem. Why apply for something that was pretty much guaranteed to give me yet another rejection? So I didn’t send in my application. You heard me, my letters went in, but I did not apply.
A little while later, one of my references contacted me. Someone at USU had contacted them because my application was missing and they were worried it had gotten lost in transit. I muttered something about that being strange, assured my letter writer that I would get on that. I was too embarrassed to admit I hadn’t sent it (this is the part that only one other person knew). So I sent it immediately so I could say I did.
How did it end? I am now a tenured faculty member at Utah State University.
There’s a couple of morals from this tale:
1) By not sending in my application, I was rejecting myself for that job. Plain and simple. End of story. By rejecting myself, I almost caused myself to lose a job.
2) the job ad doesn’t have to be a perfect match for you to be a good match for the department. You’d think the job ad accurately described what a department was looking for, but a department is not a monolithic entity. Ever leave a committee meeting frustrated by the conflicting advice you received on your proposal/coursework plan/thesis? Imagine writing something that incorporated the impassioned feedback from 20+ committee members. That’s the job ad. Since the job ad is imperfect, this means your perfect (or imperfect) fit with it is an unreliable indicator of whether or not you should apply. Do you see something in the ad that reflects what you do? Is it a job you’re interested in? Then apply.
When I give this advice to students, I often hear, “But won’t they get mad/irritated/think poorly of me for wasting their time?” Maybe, but they won’t remember you. I have been on a number of search committees. There are always applications that have no relevance to the job description. I’ve seen medical cellular-molecular types applying for organismal evolutionary positions and landscape hydrologists applying for wildlife animal population ecology positions. I can’t remember the names of any of them. The search committee may giggle, but they’ll never remember it was you.
And, just to be clear, I’m not advocating completely ignoring the job ad. Even though no one would classify me as a spatial ecologist, there were definitely aspects of that job ad that fit me. I’m just saying: don’t be scared off by an imperfect fit.