Hello world! Like many of us, I've spent 2020 locked away - in my case, writing my book, UNDER THE SKY WE MAKE, which I can't wait to share with you in March 2021.

As I'm wrapping up final edits and fact-checks on the book, I'm looking forward to starting new projects. On the agenda for 2021 will be an occasional newsletter on facing the climate crisis with facts, feelings, and action, where I'll share my latest research, writing, reflections, and projects, as well as what I'm reading, listening to, and enjoying, and answer reader questions. (Don't worry, I won't spam you- I'm aiming for monthly updates).  
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​I'd love to send you the inaugural copy when it launches, and to hear any suggestions for topics you'd like to see covered. Please sign up below. Thanks! 

P.S. For the full scoop on the newsletter, please head over to read more on Substack. 

I remember being confused about what was expected of scientific authorship in grad school. My mentor Pam Matson had a helpful rule of thumb: there are three things you can do to contribute to a scientific paper: (1) have the idea, (2) get the money, and (3) do the work. At least two of these three are required for authorship. (Thus, under this model, a PI who has an idea and gets funding to support a PhD student on that theme would be expected to be a coauthor on all resulting papers.) 

I appreciate having clear guidelines and expectations for authorship, so I was glad to come across the authorship guidelines from the Vancouver Convention. Basically, they recommend 4 criteria for authorship (all four criteria must be met for authorship):

1. Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; AND

2. Drafting the work or revising it critically for important intellectual content; AND

3. Final approval of the version to be published; AND

4. Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

This is the model I aim to follow in my collaborations. Thus, I expect myself and all authors to make a substantial intellectual contribution (#1) and contribute to writing and editing the manuscript (#2). 

I interpret #3 above as the lead (first) author has responsibility to solicit and integrate input from all authors in making revisions, and obtain their approval before sending to the journal. I interpret this responsibility as applying at three stages: 

1.  During drafting of a manuscript, until all authors approve the MS being submitted to the journal; 

2. During peer review, when the lead author takes primary responsibility for addressing comments from peer review, with input from all authors, and gets approval from all authors for the version to re-submit to the journal (this stage repeated as necessary if there is more than one round of peer review); and 

3. During copyediting, when the lead author shares the typeset and corrected final proof with all authors for their approval before submitting for processing and publication. 

I think all three of these stages are important in order to ensure that the last round (approval before publication) is sufficiently met, so that all authors are in a position to take ethical responsibility for the work (#4).  

(See my tips on how to work with revisions suggested by reviewers here.) 

When working on revisions, and especially with large and diffuse author groups, the lead author has to herd the cats and balance between giving everyone opportunity for input, and making decisions about the most appropriate direction for the paper (especially when coauthors or reviewers may have contradictory suggestions). After giving all authors a chance for input, during revisions the lead author might send around a version that incorporates changes suggested and say something like,

“Thanks for all your comments, which have been incorporated in the attached version. I had to balance between suggestions X and Y, which I did by Z; I hope everyone is satisfied with this approach. I would like to submit on X date (eg 1 week in the future). Please reply with either (a) any critical changes needed for accuracy or (b) your approval to submit. Thanks!”

It's especially essential to receive positive affirmation (i.e., a verbal or written OK to submit) from each author for the final version to be published. 

In other words, you don't start out deciding to do a survey, then looking for appropriate research questions to ask and attendant philosophies and theories. For a simple breakdown of how philosophy of knowledge, theory of knowledge, and research style combine to produce research programs, see our 2010 article "Thinking about Knowing"- this could help you write the dreaded "philosophy and theory" sections of a master's thesis, for example.  

Another useful resource is this overview of qualitative research in conservation by Moon et al. 2016, including a helpful list of questions in Table 5 that will help you avoid many common pitfalls. 

2. What are the research questions you want to answer? 

It is essential that you have a manageable number (i.e., not more than three) clearly articulated research questions that guide all further research design. Coming up with a good research question is an art in itself (take a look at The Craft of Research for a whole chapter on how to do this).

In short, my view is that a good research question is grounded in a real-world problem, linked to other research and/or theory in the field, specific enough to be answerable with the resources you have available, and something you are passionate about answering.
 
3. Are surveys the appropriate method to answer your research questions? 

Be sure to consider alternatives and convince yourself that surveys are a good way forward, that will help you answer your research question. If you can directly observe behavior or use existing data to answer your question, that will be easier than designing and carrying out a good survey. On the other hand, if you need to know how people think (attitudes) or feel (values) about something, then you need a survey to ask them directly to find out. 

4. Who is your target population, and how will you sample from them? 

Consider that your sampling design will affect the validity and generalizability of your conclusions (i.e., if you want to do inferential statistical analysis to draw conclusions about significance, you need a random sample that is large enough to be representative). William Trochin has a good, concise overview of sampling and social research design issues on his Research Methods Knowledge Base. 

Issues to consider here include how you identify the target population (what characteristics must they have?), and how you identify them (what criteria will you use to include or exclude participants, and how many do you seek?). Write down all your criteria in your Methods section under Sample Selection. 

5. How will you design your survey? 

Here's a really nice, simple, clear overview of best practices for survey research design by Kelley et al. 2003. This is a great place to start.  

Good tips on survey design, question construction, and administration in a book chapter from "Investigating the Social World" by Russell Schutt. 

6. How will you analyze survey data?

The simplest way is using descriptive statistics- e.g., graphing the distribution of the results in a histogram.

​A more complex way is inferential statistics- using statistical tests to draw conclusion about the likelihood of observations being due to chance, attributing numerical confidence to the results. This is a big topic; to get started, check out this guide from The University of Reading Statistical Service Centre on the analysis of survey data. 

For descriptive data (verbal or written textual responses to open questions), the aim is not to condense them into a number, but to use them to represent and explore different views. Here the process of coding can be helped with qualitative analysis software like NVivo or Atlas.ti. You will chose (and should state in your Methods) whether you are using inductive coding (themes emerge from the data) or deductive (trying to match responses to categories from previous literature or theory), or a combination. 

Whatever analysis approach you take, describe it clearly in your Methods, and explain why you chose it. 

7. Research Ethics

Conducting research with human subjects requires the researcher to take responsibility for considering and minimizing the risks presented to participants, and make sure that clear, prior, informed consent is obtained from your participants (this means your participants understand that their participation in the study is voluntary, they understand any risks that may be presented, and they know that they can end their participation at any time of their choice without penalty). You need to think about how you will protect the privacy of your participants and how to handle their data fairly and with what degree of anonymity. It is good practice to obtain written, signed informed consent before enrolling a participant (this might be ticking a box on the front page of an online survey, or initialing and signing a separate consent form including a copy for them for in-person interviews). 

Be aware that you are responsible for following ethical guidelines in the country where you conduct your research. In the US and Canada among other countries, completion of a formal course in research ethics and approval of a human subjects protocol is often required before conducting survey research.

Here is the human subjects protocol I submitted to Stanford University for my PhD research in 2006- there are lots of helpful questions here to consider. And here is the consent form I used with my study participants.  Feel free to use these as templates for your own research. Answers to the protocol questions can go in the Methods section of your thesis, and the consent form can be modified and used with your study participants. 

In Sweden, research should follow the Swedish Research Council Vetenskapsrådet's  guide to Good Research Practice, with many useful areas to consider. Research conducted for a master's thesis generally does not require a formal application to the regional review board (meets monthly, costs 5000-16000 SEK to review applications, which must be in Swedish). Here is the Swedish law regarding research ethics, for research conducted in Sweden, that presents a sufficient risk or sensitive data.   

However, researchers still have a responsibility to follow good practices. Please be aware that you may be required to demonstrate good practices were followed and informed consent was obtained in order to publish your research results in a peer-reviewed journal. See below for two examples of text published in peer-reviewed articles describing how informed consent was obtained in Sweden. 

Text about informed consent: "Although the study scope exempted it from Swedish requirements for formal ethical review by an institutional review board, all procedures performed in this study involving human participants were in accordance with the ethical standards of the institution, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Prior, written informed consent was obtained from all individual participants included in the study (See consent form in S1).”​
--Source: Wynes and Nicholas, in second review Feb 2019, PLOS ONE

"According to the Swedish regulations for conducting research on humans, there was no need to seek ethical clearance for this study. All participation was voluntary after informed consent, and the participants could withdraw from the study at any time. In order to protect the participants’ identity, revealing information has been removed from the results such as specific faculty, discipline, gender, ethnicity, and age. Furthermore, before data was analysed, all participants were invited to confirm their own interview transcripts and remove quotations that they did not want to share with others."
--Source: Brodin & Avery, in press

I hope these tips are helpful- happy research! 

Last October, I gave a Sunday morning talk to a group of early-career researchers attending the Earth Systems Governance conference. It was a day-long program on "Developing a career in earth system governance: opening up science." I enjoyed the chance to gather my thoughts and pass along some good advice I've been given (and some earned through experience!).

Thanks very much to Ina Möller, who made a podcast from our conversation. You can have a listen here.

Here's a condensed list and links to resources I've found helpful. Hope they're useful to others! 

It's thesis season! Our LUMES master's students are turning in their last six months of academic blood, sweat and tears (AKA, their theses) in nine short days. 

Just in time- here's a checklist I've developed to help students give appropriate credit to their original sources. This is one of the most common problem areas I see in student writing. Following this checklist will help you contribute to scholarly conversation and avoid problems from unclear citations. 

This checklist aims to serve several purposes: 

1. Demonstrate appropriate research ethics in fairly crediting ideas to their original authors.
2. Give more credibility to your research by grounding it in established literature, and showing where you have added new knowledge.  
3. Help your reader follow your logic and understand your main claim, based on the evidence that supports it.  
4. Follow a well-established format for citation (APA style), to help readers find and understand the sources you have used and the way in which you've used them. 
5. Avoid plagiarism (which is every student's responsibility to avoid- even unintentional plagiarism can carry a penalty of up to six months' suspension at Lund University).  

Comments or corrections welcome. Happy revising! 

I have come to believe that one of the biggest impediments to scientific advancement is writing. This is true in at least two ways. First, writing is often the critical bottleneck standing between the mountains of good ideas on whiteboards, hard drives, and inside people's heads that have not yet found a way to be communicated to a wider audience (both scientific and public). Second, the writing in published papers often does not help (and may actively hinder) the reader's understanding of the research and its implications. 

Nicholas Kristof was more blunt about this in his recent New York Times Op-Ed (with which I largely agree), asserting that PhD programs have "fostered a culture that glorifies arcane unintelligibility while disdaining impact and audience" (ouch!). He cites a related piece by Jill Lepore in the Chronicle of Higher Education, where she describes academia as a "great, heaping mountain of exquisite knowledge surrounded by a vast moat of dreadful prose" (double ouch!).  

I think a fundamental problem here is that, although writing is a skill that can be taught and requires practice to master, writing is rarely taught. I never took a writing course in graduate school. I had professors who spent time correcting and commenting on papers (which I appreciate all the more now that I'm on the other side of the red pen), but I'm not sure I was able to take their specific comments and generalize them into principles of better writing. (I also think I didn't realize how important writing was until after I started editing and reading more papers than I wrote.) 

One way I've tried to teach writing is to develop templates, outlines, and rubrics that spell out a paper's structure, so that students can concentrate on developing and communicating their ideas in a way that will be clear to the reader. 
(I've had interesting discussions with my colleague Ladaea Rylander of the Lund University Academic Support Centre about the risks of templates suppressing creativity, some of which we address in our forthcoming book chapter; my basic conclusion is that I'm very happy for students to ignore these templates and do something creative if they are inspired to do so, but that many seem to benefit from and appreciate them). 

Without further ado, here are some of the resources I've made so far. I hope they're useful, and welcome feedback! 

Writing an academic abstract: a MadLibs (fill-in-the-blank) template adventure.

The Thesis Toolbox- slides from a workshop I gave for 40 master's students from across Lund University to get them started on designing their thesis. 

Template for writing a master's thesis research proposal - use this to structure your ideas, and eventually as the basis for writing your thesis. 

Generic Paper Outline, Or, What Goes Where in a Scientific Paper? Start here when you have to write up a thesis or journal article and fill it out as you go along. 

Finally, here's a long and somewhat cheeky guide to common problems I see in student writing, and suggested ways to overcome them. 

Winegrowers and winemakers have many options to adapt to warming climates. Growers are experimenting with new wine regions, cooler locations within existing regions (such as moving from warmer valleys to cooler hillsides), trying new varieties better suited to warmer conditions, and farming methods that provide more shade on the fruit. Winemakers can use approaches including alcohol removal and acid addition to improve wine balance. Steps like these can go a long way towards preserving great wines under climate change.

Ultimately, though, there are economic and biophysical limits to this adaptation. There are also cultural limitations: the know-how and sense of place that growers cultivate along with the land over generations of family farming is not easily moved, and consumers have come to expect a distinct flavor profile from wines from their preferred regions. Great wine is grown, not made; it reflects its place of origin. If the climate changes even a little bit, local knowledge and skills that have taken generations to hone can become less relevant, even in familiar territory.

But the changes we’re facing in climate are not small ones. Under our current trajectory of fossil fuel use, scientists project that the global average temperature will increase 4.7 to 8.6°F (2.6 to 4.8°C) over the next few generations. Even the low end of this range would be the difference in annual average temperatures between the winegrowing regions of Napa and Fresno today. Currently, Cabernet grapes from cooler Napa are worth more than 10 times as much as those from Fresno- a difference of over $3,000 a ton. 

I find writing grant proposals to be one of the most challenging tasks in science. I might go so far as to say that it’s my least favorite part of my job (well, right up there with submitting travel receipts). 

I take some comfort from the fact that I struggled with writing papers in grad school, but I now mostly enjoy paper writing once I’m actually sitting down to write them. I like posing a question and finding an (inevitably incomplete but sometimes intriguing) answer, and seeing the cool story that my data tell. I attribute this evolution to help from mentors and having put in the time and effort myself to gain the experience that makes the whole process more fun. But writing proposals for me is still agonizing, stressful, and slow. How do you write something compelling based not on data but on conjectures? It's a tricky business.  

Of course, you need funding to carry out research, to ask and answer the questions you think are most interesting and important. So I'm working on gaining more experience in the hopes of improving my grantwriting skills (and, maybe someday, my enjoyment of the process). Here are some approaches, resources, and tips I've found helpful along the way.  

Perhaps the most helpful thing for me has been to start serving on proposal review committees. Much like becoming a reviewer for journal articles, it's so much easier to see shortcomings (and admire strengths) in other people's writing, and to start to develop from that my own understanding of what makes a proposal good. Reviewing proposals is a "service" task that's part of being a good academic community member, but I've personally benefitted a lot from it in learning about the grant review process and getting ideas for how to write better grants. Instead of agonizing over every word of your own proposal, it's extremely helpful to go through ten or 50 proposals at once and see what stands out for you in writing a clear, compelling proposal.

Most programs that give out funding need subject experts to review proposals. These include federal agencies like NSF, NASA, and EPA in the US, or national agencies like Formas and VR in Sweden, as well as coordinated programs like the European Commission's Horizon 2020 program. There are also many programs that need reviewers for graduate fellowships (like the National Science Foundation Graduate Research Fellowship Program, which solicited reviewers in August 2014- keep an eye out for next year), or student sections of scientific societies (like the American Geophysical Union) who give out awards and fellowships. 

I would suggest that aspiring grantwriting pros seek out opportunities for reviewing proposals, including: 

• Make sure you've registered your interest with the relevant grants officers to serve as a reviewer for proposals in your field. You can sometimes do this electronically, for example, at this EU website for registering as an expert for service as a panel reviewer for Horizon 2020 and other actions. 
• Tell your mentors that you're looking to serve on review panels, and ask for their suggestions for opportunities that would fit your expertise. 
• You can always contact funding program officers directly (in person at conferences, or by phone or email) to ask how you can get involved as a reviewer. 
• Look for opportunities to serve as a reviewer while still in graduate school- for example, in reviewing undergraduate research proposals or conference presentations at your local institution. 
  
• You can of course also ask close mentors and colleagues to share successful grants with you- it's extremely helpful to have good models to help structure your thinking.
• For mentors - remember to suggest opportunities to review proposals for your students and early-career colleagues, and to share your successful grants and tips for writing them!

I recently attended a proposal-writing workshop for early-career scientists at Lund University held by Dan Csontos, a former Nature editor who is now running his own scientific writing consulting business called Elevate Scientific. This was a really helpful overview of suggested structures and strategies for proposal writing. You can see the Storify compilation of all the tips that I Tweeted from the workshop here. 

One especially helpful suggestion from Dan was to start research proposals with just four sentences, articulating the background, statement of need, purpose or objective, and impact for your project. Starting here can really help you keep your focus and see the integration between sections in a proposal.  

I've found that it's also critical to develop figures right from the start, and to refine and integrate these with the text as you go along. (Sometimes it's easier to start with a mind map or simple box-and-arrow diagram than with text.)   

Here's my interpretation of Dan's four core sentences, illustrated with examples from a successful proposal that was generously shared by my colleague Nick Magliocca at SESYNC. (See how helpful it is to have good models? Thanks, Nick!)

1.     Background- why is this topic important, relevant, timely? What is the current state of the field?

Example: “In an increasingly teleconnected world, rural populations are undergoing rapid changes in both their livelihoods and land uses, with associated impacts on ecosystems, global biogeochemistry, and climate change.”

2.     Statement of need- what critical question/aspect remains unknown? Linking to and narrowing down from the general background question above.

Example: “Thus, a challenge in land systems science is to explain these shifts [or land-livelihood sustainability transitions (LLSTs)] in terms of the actors and processes operating within coupled human-environment systems, and produce actionable insights that can help navigate sustainability transitions in these systems.”

3.     Purpose/objective- what specifically do you want to do in this proposed work? Use active verbs (discover, explain, develop, synthesize, characterize).

Example: “This project will develop a geo-information and simulation architecture to support synthesis of local knowledge within a global context and advance scientific understanding of land-livelihood sustainability transitions (LLSTs) around the world.”

4.     Impact-  Why would achieving your stated purpose be important? What academic, theoretical, and practical use would it serve? How would the world be a better place if you achieved your stated research purpose beyond your wildest expectations? (Please don’t say, “This work would have important policy/theoretical implications”- rather, state exactly what those might be.)

Example: “This project could link across several SESYNC research themes, and produce collaborative activities such as the development of a synthesis project and/or workshop on integrating meta-analysis and modeling for cross-site comparison and synthesis.”    

Bonus tip! Dan also recommended the book "Scientific Writing and Communication: Papers, Proposals, and Presentations," by Angelika Hoffman, as a practical, accessible, one-stop shop for grantwriting. Sounds like a good investment.  

Another huge help in learning how to write proposals has been mentoring students and postdocs in their proposal writing. As any teacher knows, sometimes the greatest learning comes through teaching. Trying to explain how to structure a master's thesis proposal or a travel grant has really helped me articulate what works and what doesn't in explaining proposed research. It's also spurred me to come up with some resources for my students to try to help them structure their thoughts in writing research proposals. While these weren't designed to submit to funding agencies, I think having a clear research structure on paper (which clarifies the logic in your head as well) is still helpful in articulating the logic and making a compelling case for the research, and these could be used for grant proposals as well.  

The first is a "dream abstract" template, to be personalized with fill-in-the-blanks for a specific case. The idea is to imagine the whole research project from the start, to have a clear idea of what you're trying to do (it takes surprising focus to actually answer the research question you intended). I've run a workshop with master's students where students starting their theses first spent about 20 minutes working on their own draft individually (they had also been given the template ahead of time, but most wanted to change it after listening to the presentation I gave). Then they worked in groups of four, spending about 20 minutes each reading it aloud to the group and getting feedback from their fellow students (which was really perceptive). The students who attended the workshop said they found this process helpful to jump-start their thinking. It could be a good way to get over the horrible "blank screen, blank mind" stage of starting something new.  

The second is a research design matrix, to go through the process of operationalizing research topics into specific variables. (Recommended reading here: Chapters 3 & 4 of The Craft of Research, by Booth et al.). You can find this matrix on Slide #50 of the talk I presented at the Thesis Toolbox workshop, illustrated with the example of a master's thesis by LUMES alum Kyle Clark, which we worked together to turn into a published paper. 

Finally, the most extensive document is a Research Proposal Template that I made for the master's students that I supervise. This is intended to help them develop their own 8-10 page research plans over the fall, so they're ready to conduct their research in the spring semester. The proposal starts with the dream abstract and contains sections for research context, questions, design, ethics and philosophy, as well as communication and implications. 

I hope these tips are helpful to ease some of the pain of writing proposals- I'd love to hear your tips for suggested approaches and resources! 

What if the secret to writing successful research proposals were to go back to the basic lessons your fourth grade teacher taught you about writing? It can't possibly be that simple, can it? 

I just had a lovely dinner with my smart & wise friend Harriet Bulkeley. One of many good pieces of advice she gave me (this one picked up by joining a conversation she overheard on a train!) is to think over the answer to four things before beginning a research proposal or project: 

1. What do I want to do?
2. Who do I want to do it with? 
3. Where do I want to do it?  
4. Why do I want to do it? 

I said this sounded like a great way to teach research design to students, but as we discussed more, I realized researchers at every level could probably benefit from this advice, myself included. She noted that many people can only answer one of these questions when they approach a university research office or a funding agency with a research idea. They might hope that the answers will get clarified in working through the project, but this is rarely the case. In projects that haven't clarified these key points at the outstart are likely to get bogged down in these issues through the course of research. A great reminder to think through the basics before committing your precious and limited time. 

I just read a New York Times article (posted by @eric_mazur*) that inspired me to post last year's final exam for my new students on the first day of our Earth Systems Science class. I have always shared last year's final as a teaching tool in the weeks before the exam, because I think it's the best study guide for students to work through it on their own or in small groups as they prepare. (Plus, it removes any possibility for cheating, which could be a temptation if last year's students are expected to keep old exams private after getting them returned.) I post just the exam for a week or so, and then post a compilation of the best student answers from the previous year to give an idea of what an excellent exam would look like. My reasoning is that I want all students who work hard to do well on the exam, and they will do their best if they have a realistic model to work with. After all, the most important thing I'm trying to teach is not facts, but a way of thinking, in particular, using data to support claims; the more exposure students get to this, the better.  

However, this article by Benedict Carey just made me think about exams in a new way- as "learning devices" that can be "the key to studying, rather than the other way around." Psychological research has shown that pretesting can change the way we think, helping to prepare our brains to better receive, process, and hold on to relevant information when it appears. Testing, it turns out, is a powerful way to overcome the "fluency illusion"- thinking that we know something better than we do, because we study it in a vacuum where no competing plausible ideas exist. When presented with challenging competing ideas on a test, we're forced to reason our way through them to show we've really learned. 

The article describes initial research by Elizabeth Ligon Bjork (who heads the fantastically named "Learning and Forgetting Lab" at UCLA) and Nicholas Soderstrom, who presented psychology students with pretests. They found that pretesting increased their final exam scores by 10% (which can be a difference between a grade of C and B in the American grading system, for example). The researchers didn't give their students the final exam on the first day, because they didn't want them to be overwhelmed. I'm not asking my students to sit down and take a 3 hour exam - just posting it for them as a study resource. I hope they find it useful- stay tuned! 

* Walk down memory lane: The first time I learned anything about teaching (the horribly pedagogic-sounding but very important field of pedagogy) was as a "Kindergarten Through Infinity" fellow as a master's student at the University of Wisconsin-Madison. This was an NSF K-12 program that matched STEM grad students (who brought science content knowledge) with primary and secondary school teachers (who were expert teachers) to design learning activities for students ages 5 through 18. It was here that I first heard about and was inspired by Eric Mazur, the Harvard physics professor who turned his teaching upside-down when he realized his traditional lectures weren't producing deep learning, even for extremely bright students. His solution was the Peer Instruction method. This was the first time I heard about Think-Pair-Share and other teaching techniques I'm still using.