Since November last year I'm hosting the ECCF podcast, a science podcast that covers climate change research, science communication, and gives career advice for grad students and young professionals. Most people I talk to have not had a straightforward career path that led them to the jobs of their dreams. With this podcast, I'm exploring how they did it and what challenges they faced.
I recently uploaded episode number six, finished in my make-shift sound booth at home, thanks to COVID-19, so I thought why not go through each episode, summarize them, and share some lessons learned from creating this podcast.
Episode 1 - Dr. Kristen Weiss (science communicator)
November 21, 2019 (25:57 min)
Kristen is the communications coordinator for the US Long-term Ecological Research (LTER) Network at US Santa Barbara. She is a video producer, photographer, and blogger with an impressive science background. She earned a Ph.D. in policy and natural resource management in Australia and did a science communication postdoc in California. She visited Texas A&M to speak in our departmental seminar series "From Knowledge to Action" about her work at the LTER Network.
Kristen was actually my second interviewee, but because the launch of our podcast lined up well with her participating at an all-female sailing expedition to study ocean pollution, I decided to put her first to advertise the expedition in the outro and the episode description.
While her interview was an improvement over the first one (with Sarah McAnulty below), the episode still had plenty of obstacles. The biggest one was recording the intro, intermission, and outro, to bookend and loosen up the episode. My office was neither quiet or echo-free enough for that, so I booked a one-person, very dark sound booth at the university library for two hours one day after work, thinking that would be plenty to record a few minutes of me reading some text off a screen. Needless to say it wasn't, because the slightest pause, slip of the tongue, mispronunciation of a word, or other proverbial hiccup put me back to the starting line. I learned to cut and paste together good segments, but even then, small changes in volume, pitch, or speed would turn the result into a patchwork of sounds rather than fluent lines of spoken word. An even when everything was recorded in good quality, I sometimes found that what I said didn't quite sound as good as I thought when I wrote it, or I wanted to add one piece of information, and scrap the recording to do it all over again.
Episode 2 - Dr. Sarah McAnulty (Skype A Scientist)
December 23, 2019 (24:31 min)
I was really excited to interview Sarah! She is the founder and Executive Director of Skype A Scientist, a global organization that connects scientists with school teachers for classroom chats about their research, what it means to be a scientist, how they became one, and much more. I've been a participant of Skype A Scientist since early 2018 and talked to over a dozen school classes since then, about my work, myself, the impacts of climate change, and what we can do to adapt. Like Kristen, Sarah was on campus to give a departmental seminar about her work as a squid biologist at the University of Connecticut, and of course to talk about Skype A Scientist, which was also the focus of this podcast episode.
Unlike Sarah, who had been on NPR's "Brains On!" and many other podcasts, this was my first podcast interview ever. So, needless to say I was nervous. I had interviewed people for newspaper articles before, but the technology part here was all new, and the thought of messing up an interview with Sarah McAnulty was a bit terrifying, despite much testing and practicing. First, the microphone I borrowed (an AudioTechnica AT2020+USB, for audiophiles) was uni-directional (a so-called cardioid recording pattern), perfect for one person speaking but not so much for a conversation between two people. I solved it by pointing it upwards, which resulted in some echo from the ceiling, though. Second, Sarah had quite a strong voice, louder than mine, and the mic was positioned closer to her, so during editing I had to painstakingly lower the volume when she spoke and raise it again when I spoke. Apple Garageband is pretty intuitive to use, but this took forever. And third, the fridge at the end of the conference room we recorded in! Barely noticeable during the interview, it left a very annoying buzz on the recording. Garageband doesn't have a noise filter, but thankfully Audacity does, which took care of this. When all was done, we posted the episode two days before Christmas.
Episode 3 - Dr. Jeff Martin (bison researcher)
February 13, 2020 (13:29 min)
At the time of our interview, Jeff was a doctoral student in a department one floor down from me (he just defended, woohoo!). His research on the effects of climate change on bison body size across the Great Plains is amazing, and it overlapped quite a bit with my work on cattle ranching, so naturally I wanted to talk to him.
Thanks to a brand-new Blue Yeti (a Christmas gift from my wife), audio issues were a thing of the past. However, pressed for time, I didn't have a good set of questions when we got together. So as scientists do, we got into the weeds of our work and got sidetracked way past the interests of any listener. Thankfully, Jeff, despite being in the middle of thesis writing, agreed to record the entire interview again, this time with a list of questions, less jargon (we tried), and more commitment to staying on topic. The interview went well, but I made the unfortunate decision to try and make this a shorter episode focused primarily on his research results. That meant I cut out much of him talking about the relationships he had to form with bison ranchers and organizations to get access to grazing land, animals, and fossil records. A big mistake in retrospect, because it was essential to the success of his work and is often undervalued in our pursuit of fast results.
You can read more about Jeff's work on his website, including many articles about his work he wrote for a general audience.
Episode 4 and 5 - Dr. Jessica Whitehead (North Carolina's Chief Resilience Officer)
March 27 and April 6, 2020 (29:19 min and 38:38 min)
These two episodes were less work for me, because my colleague, Dr. Adrienne Wootten, a climate scientist in Oklahoma, took care of the interview part. Jessica's career path is anything but straight and her day job was nothing short of fascinating, so Adrienne's chat with Jessica was long. So long in fact, that we decided to split the interview into two parts (and still produced the two longest episodes at the time), covering her career path in part one and her day job in part two. We ended part one on a small cliffhanger, and posted them about ten days apart.
Jessica's interview presented two new challenges. One, we needed Jessica's boss' approval for the interview (because she is a federal employee), and two, it was the first one we recorded remotely, not in person (not because of COVID-19, but because of the distance between Oklahoma and North Carolina). Adrienne used Zoom, which records audio and video on the host's computer (set the location under Preferences > Recording). Even better, audio streams from each participant can be saved in separate files (also under Preferences > Recording). This makes fixing issues with quality, volume, or background noise much easier.
In noisy environments, it helps to wear headphones with integrated microphone, like Apple's EarPods, instead of using the computer's microphone, because the headphone mic picks up a person's voice better and reduces the ambient noise. Bluetooth headphones are not a good idea, because they cause delays and chop off the beginning of a person's audio, Adrienne and I found out the hard way. We assume the bluetooth connection enters a kind of power-save mode if a person doesn't talk for a while (which was the case here), and it needs a second to "wake up" when the person does say something. We did not test with bluetooth headphones and only found out after the interview that Adrienne's audio turned out choppy and distorted. So, corded headphones with integrated mic is the way to go.
Thanks to COVID-19, I had to record intro, breaks, and outro from home, which made logistics easier, but recording harder. Even though our apartment is fairly quiet, the occasional train, plane, or car would still torpedo my hard work, in addition to a noticeable echo off the walls. The solution was a make-shift sound booth constructed from a collapsable box and a blanket hung from two lamp posts to reduce the echo. It was inspired by Michael Barbaro's setup for "The Daily" podcast, which, like UCS's "Got Science", Pew Research's "After the Fact" and every other podcast I listen to, had to content with the same problem: working from home. To avoid our neighborhood's noisy A/C units, which slowly woke up from hibernation (we had a very warm March), I recorded mostly in the mornings.
I can't be sure, but I'm just going to tell myself that all this effort made my voice extra crisp and the episode even more fun to listen to.
Episode 6 - Dr. Hailey Wilmer (social rangeland scientist)
May 6, 2020 (38:54 min)
Hailey is a social scientist who studies decision making in rangeland management. With a bachelor's degree from Cornell and a Ph.D. from Colorado State University, she was a postdoctoral fellow with the USDA Northern Plains Climate Hub in Fort Collins, Colorado. She was part of the Collaborative Adaptive Rangeland Management (CARM) project, which is what I wanted to talk to her about. CARM is a large-scale, long-term field study in Colorado that involves ranchers and scientists to study the effects of different rangeland management styles on the health of grasslands and the economic benefits for ranching. It epitomizes the idea of science co-production, the collaboration of scientists and stakeholders to better inform decision making in the real world (Djenontin and Meadow 2018 provide a good "how to" guide).
I wanted to talk to Hailey, because I love her kind of work. It brings together academic researchers, government agencies, NGOs, and ranchers, and combines the strengths of systematic inquiry (you know, scientific research) in a range of disciplines from social science and meteorology to agronomy and ecology, with the expertise of decision makers on the ground.
The episode with Hailey did not really make any trouble, so maybe by now I have aced the Podcast 101. Like Jessica Whitehead, Hailey (a federal employee) had to request her boss' approval (a formality in both cases), and we recorded the episode during a conference in Denver that we both attended back in February. Hailey and I met at the end of a conference day, I brought my Blue Yeti, and we found a quiet room in a corner of the conference hotel. The audio was excellent, and the only mishap you will hear at the beginning, was when we knocked against the table a few times while the mic was recording.
Effective communication is not only important when sharing your research with others. Its objective is to assist collaboration, to make science more applicable and scientists more sensitive to the concerns and values of others. (Srinivas 2017)
Climate change is a huge, complex problem that no one can solve alone, and tackling it means scientists across disciplines have to work together and to understand each other. But that can be difficult for many reasons: different culture and traditions, differences in terminology (or the same terminology but different meanings), or expertises that don't overlap much, to name a few. A social scientist, an ecologist, and a meteorologist might study climate change, but from very different perspectives. In order to help a city planner create green spaces to reduce the urban heat island effect and keep cities livable for an aging population, all need to seamlessly work together.
In the U.S., part of the solution to this have been boundary organizations like the USGS Climate Adaptation Science Center network, NOAA's Regional Integrated Sciences and Assessment teams, and the USDA Climate Hubs, that work with natural and cultural resource managers, cities and communities, and farmers and ranchers, to help them adapt to increasing more severe droughts, more unpredictable seasons, and more extreme heat, due to climate change.
For those that don't have one of these centers around (although, they do cover a big chunk of the U.S.), a colleague and I wanted to help people get started. Cait Rottler, a researcher at the USDA Southern Plains Climate Hub in El Reno, Oklahoma, and I hosted a 2-hour workshop for researchers and stakeholders to become better collaborators. We were at the annual meeting of the Society for Range Management, a meeting of rangeland and ecosystem researchers, private sector companies, ranchers, Native American Tribes, and agency staff from the U.S. Fish and Wildlife Service, the Bureau of Land Management, and the Department of Agriculture.
There are many barriers that keep people from working together, for example our limited understanding of on-the-ground decision making (which I wrote about here, here, and here). In this workshop, we wanted to focus on the language barrier that exists within the research community and between researchers and decision makers.
On the left is a quote from a paper about DNA analyses on African skeletons to understand ancient human migration in Africa, published this January in Nature. On the right is a quote about this study from a news article in the science section of the New York Times.
If you're like me, you found the text on the right easier to understand. The text on the left is clearly written for experts like anthropologists, geneticists, and bio-molecular engineers (the research fields of the authors). The text on the right is for an interested, but non-expert audience. It is less specific but uses fewer technical terms and more general phrases that a broader audience can more easily understand. Technical language can convey a concept or message very efficiently, but only to a small group of experts. In research, we often work with peers in our field and thus communicate in ways that exclude a broader audience. Our workshop was intended to help researchers and stakeholders communicate to each other.
Comparing scientific papers and popular science articles raises another issue: how do we present our work. The classic IMRAD structure (Introduction-Methods-Results-And-Discussion) used in scientific journals everywhere is not how we should communicate our work to peers, stakeholders, or indeed anyone.
In our workshop, Cait and I used the Compass Message Box concept to illustrate how research can be reframed for a range of audiences, to describe:
Here is what my research at Texas A&M University may look like, reframed for a broader audience. My advisor, David Briske, our colleague Matt Reeves (U.S. Forest Service in Montana), and I study the impacts of climate change on cattle production in the Great Plains, specifically the consequences of more frequent and intense droughts on grasslands, through the lense of ecology (David and Matt) and a climate science (me). Thanks to other colleagues (John Ritten at the University of Wyoming and Amber Campbell at Kansas State University) we also looked into the economic impacts on ranching and into societal challenges of adapting range management to climate change. In short:
Quite a mouthful! Let's try to look at it in a different way. Most importantly: Who is our audience? Problem, solution, and benefits are different depending on who we talk to, even if the broader issue is the same. Discussing drought with a rancher is very different from discussing drought with an engineer ... or a state legislator.
Next, I broke down our research into the five segments of the Compass Message Box.
What might be the most relevant issue for legislators? Why should they care? Drought has an economic impact on ranching, and with that an economic impact on their state budget and the welfare of their residents.
What are the concrete problems? Clear language is essential, and some context, like comparing future droughts to significant historic ones, could describe the problem more clearly. Depending on the audience, we could adjust our wording to include or exclude certain phrases, such as "climate change". By now, though, many farmers and ranchers recognize climate change in their operations, talk about it, and want answers. So, well-informed legislators (or their staffers) even in conservative states might be okay with talking about it, too.
Now to the consequences, why it should matter to the legislator. Note that the language is more science-y, but because of the context we created previously, most of this should be clear. I focus on economics, because cattle ranching is a multi-billion dollar industry in Texas, and I imagine representatives are most concerned about economic impacts and tax expenses on livestock insurance or flood damage, before thinking about protecting natural habitats and endangered species (which we mention later).
What are my suggestions for solutions? This needs to be phrased carefully to not appear like I'm the expert on this (which we're not). I am merely suggesting solutions that could help the problem from my perspective. Phrasing solutions should take place with a team spirit in mind - I want to help the legislator and their team solve the problem, and I acknowledge that other interests might conflict with mine, and I might not get it my way.
How does all this work benefit Texas and Texans? I try to point out how my proposed solutions can help reduce future costs due to droughts, the problem I stated initially (also, droughts are more concrete than climate change, so I use that) and what else might benefit.
This was only one example we gave our workshop participants. Not all research is relevant for legislators, but might be relevant for or could benefit from input by engineers, sociologists, ecologists, economists, city planners, or policy makers on local, federal, or international levels. What we aimed for was to inspire our participants by the multiple ways their research could be enriched and expanded, and give them some tools for how to do that.
Since this was a workshop and not a lecture, now was our audience's turn to apply some of what they just learned.
Taking a page from a workshop for scientists about communicating with the media that I had hosted a few years ago, we had planned an interactive practice session. We split our audience into groups of three, such that – ideally – no two people in one group knew each other (or at least didn't work in the same field). Then we gave assignments to each of them:
Person 1: Ask person 2 general questions and more specific follow-ups about their work and their professional background, challenges they are facing and how to overcome them
Person 2: Answer these questions in a way that uses as little jargon and technical language as possible
Person 3: Observe the other two and recognize what they do right and wrong
After about 4 minutes, we asked each group to wrap up and for person 3 to briefly share their observations with the other two in their group. Then everyone rotated into a new role, and we started over. We rotated 3 times, then re-shuffled all groups and rotated another 3 times, so that everyone was in each role twice, but each time with different partners. If we had more time, we could have repeated this process again.
During the practice part, Cait and I went around the room and listened in on how everyone was doing. Some participants really struggled finding the right words and cutting down on jargon (ranchers and federal agency officials as much as researchers). Cait and I were worried about what we were putting people through, whether our approach actually made sense, or if this activity would actually deter them from working in interdisciplinary groups, given how hard it.
Thankfully, that didn't happen.
Participants really liked the workshop and thanked us for putting this together. Most agreed, that yes, it was difficult to talk across disciplinary boundaries, and because of that they rarely do it. However, this workshop pushed them out of their comfort zone and to talking across disciplinary boundaries. It also helped them see their work and the value it has from someone else's perspective and understood how their work was important to others, which felt very motivating. Not least, one person said, and others agreed, that they found new potential collaborators in researchers they normally wouldn't talk to, but probably should.
Let's talk for a minute about generational collaboration in research.
This morning, before going back to coding, I met with two younger research scientists and their boss, a senior professor. They do ecological systems modeling in the Department of Wildlife and Fisheries, one floor down from my office. One of their projects tries to understand the seasonal movement of the Invasive Sugarcane Aphid, a bug that damages crops, with the goal of creating forecasts and warnings for farmers who can then apply pesticides more targeted. Their work is not too different from what we do, so they were interested in learning about what we do. We had a wonderful, three hour long conversation about our project and theirs, and only stopped because, despite the jaffa cakes they brought, we eventually got hungry for lunch.
The way the three described their work made me think about how different generations often approach problems differently. The two researchers are much younger than their boss and probably grew up in a time when computers were ubiquitous in colleges and maybe even schools. They know who to code, run models, and build web interfaces for users to get information over the internet. The professor, on the other hand, did his early research using punch cards (if you're under 20: punch cards). A simple calculation of data, not more than a few lines of code in today's world, would require a stack of punch cards that needed to be inserted in a machine and took minutes to process. The obvious comparison for me – thanks to this week's 50th anniversary of the moon landing – is that of the Apollo spacecraft computer to the super computers we carry around today in our pockets as smartphones.
Their situation reminded me of my own. They're are young tech wizards, bursting with ideas and enthusiasm. The professor, much like my supervisor, has decades of wisdom and the accumulated expertise of thousands of books and papers he read and wrote over the years.
Much like interdisciplinary teams, inter-generational teams, in my opinion, can be incredibly innovative and efficient, but only if we allow ourselves to admit that we need each other. Us young(-ish) folks are tech geeks, fluent in R, NCL, Python, and GitHub, and full of ideas for tools and gadgets, but often lack the experience and context what to innovate for. We like to make cool stuff for cool stuff's sake. Our supervisors, on the other hand, might lack some technical skills, but they know much better what problems need to be addressed.
And that's a wrap. This was one week of work, and it was fun for me to write. If you found it insightful and/or fun to read, please feel free to drop me a note, and I might do this again in the future (maybe during a conference or workshop).
Once a month, I get a special email from the National Oceanic and Atmospheric Administration's Office of Communication in Washington, D.C. As a federal agency, part of NOAA's job is to provide environmental information to the public. To do that, NOAA has data portals, like ncei.noaa.gov, and issues forecasts, warnings, advisories, and general press releases, for example through its website www.noaa.gov and via email, which are often published by media outlets. NOAA also holds press calls with their own scientists for journalists to learn about and discuss current topics that relate to weather and climate. And that's what this special email was about. This morning was such a press call, and I attended as listener.
Today's call discussed the recent heat wave in Europe (June set a new record there as the hottest recorded June ever, surpassing the previous record by almost 1ºC or 1.8ºF) and conditions and outlook in the U.S. For me as a researcher and science blogger, these calls are really interesting. They're a good way to learn about current developments in the fields of weather and climate, and they're great to experience how scientists and journalists interact, what vocabulary, jargon, and graphics are common, to track what information makes it into the news, and to understand the news cycle in general.
Clear graphics are essential, and ahead of time NOAA publishes a PDF with presentation slides that their researchers discuss on the call. These figures could end up in Tweets or Facebook posts (with citation of course), so communicating a clear message is key. Short summary statements in the slides can also get copied into tweets, or make headlines or highlights in an article. Here are some examples:
But good graphics are only half the story. Answering essential questions with confidence and good language is also key in these calls. What, where, when, why, who cares, and so on, without diving into methodological details or listing all the limitations of the results (although, touching on them might not be a bad idea).
Being too much of a scientist (i.e., going on and on about minute details and using too much jargon) you could run the risk of "losing" a person, or even worse, make them misunderstand and misinterpret important information, and then unknowingly misinform millions of people. One of the journalists on the call, Seth Borenstein, writes for the Associated Press, and his reporting from today (all accurate by what I could tell) was published by the Washington Post, several regional news organizations in the U.S., and even an Italian news website.
After 45 minutes, I got back to my own research, made some more progress, and at the end of the day (literally, 5.45 pm) finally got some graphic results myself. They're not quite ready for sharing, yet, but they generally suggest that in the next decades, drought years similar to 2011 or 2012 could occur much more frequently, with extremely dry or wet years representing up to five years per decade in the Southern Plains, especially after the 2050s, and one to two years in the Northern Plains.
I still have a lot more analysis ahead of me, most importantly to understand what this means for ranchers, but this is a very important and valuable step.
Here are Friday, Monday, Tuesday, and Wednesday. And if you wonder what this about, here is the intro blog post.
Getting my script from yesterday to work almost went into day three. Almost. At 5.17 pm, after writing, testing, and debugging 983 lines of code, all errors and typos were corrected, and the script worked like a charm. Sadly, there is not muchto show, yet (also because I have to double-check the results). So in place of graphs and maps, this is what my two monitors looked like for most of today and yesterday.
The one the left has Safari running R Studio, which I use to write code and manage files. The one on the right has three blue Terminal windows up and a data viewing app. Terminal is a Mac OS tool that emulates a command-line interface, which I use to tell the computer which files to run and to see some results. The fourth window, the data viewer, is Panoply, a very handy app by NASA to view NetCDF data, the type of data I work with. It comes in handy when I check results.
Despite the looks, my computer doesn't actually do much work. All of my commands and every line of code are sent 360 miles north to the South Central Climate Adaptation Science Center at the University of Oklahoma. There, all our data and most of my code is stored on a data server. Folks there also have NCL and several other programming languages, which makes our life here a lot easier.
A good day always becomes better when it ends well. On the third Wednesday of every month, the Texas A&M Postdoc Association organizes a "networking event," a fun hangout with fellow postdocs to chat over snacks and drinks at a bar or restaurant in town, courtesy of the organization. It's a good way to meet peers and make friends, to bring up workplace problems, or just to talk nerdy to fellow nerds. I always enjoy these gatherings! However, today I had to pass it up for something even better – a dinner at an Italian restaurant with my wife.
Here are Thursday, Monday, and Tuesday. And if you wonder what this about, here is the intro blog post.
A quick note about the heatwave that is bound to hit many parts of the U.S. starting Thursday. If you live between Oklahoma and New England, it will get much warmer than usual in the next few days. Please avoid staying outside for long periods of time, and if you do, make sure you take a water bottle, put on a cap, and try to stay out of direct sunlight.
If you want to know how climate change is changing the odds for heatwaves like this, check out yesterday's episode of the "Got Science" podcast by the Union of Concerned Scientists.
Every Tuesday and Thursday morning, I join a group of colleagues for what we coined "The Write Stuff," a writing group. We meet down the hall from my office in a conference room with large windows that overlook a beautiful garden, and spend two hours not chatting (mostly), but working on whatever everyone is working on. It sounds banal, but it's incredibly effective. The peer pressure of "Everyone else is working!" really makes you push through and avoid distractions. Also, the room is a pleasant change from my windowless office situation.
My goal for today was to write a script that analyzed rainfall projections for the next 80 years (2020 to 2099) and find years with extremely high and extremely low amounts of rainfall in the Great Plains. We found previously that rainfall variability is very different across the Great Plains. For example, in the Southern Plains, annual rainfall can vary a lot more than in the Northern Plains. Now we were interested in whether these super dry and super wet years will occur more or less often in the future. Specifically, we wanted to see if the frequency of years and the number of consecutive years with rainfall of more than 20 percent above and below the decadal average will change over time.
Two assumptions were important for us going into this. We assumed that ranchers are used to some degree of year-to-year variability - they could handle some wet and dry years. But the really bad ones, especially when several occur back to back, like the droughts around 2012 or in the late 1980s, would be a real challenge. Because of that, we chose a threshold of 20 percent above or below the decadal average. It's an arbitrary value, really, and we'll change it once we find a more meaningful number that's based on previous studies. But for now we'll run with it. We also used an average that will change every decade, instead of one that runs from 2020 through 2099. Why? Because of our second thought: whichever way things will change, even if it continues to get drier, ranchers will find ways to adapt to a new normal over time, just like they have in the past. Using something like a running average will account for this.
Now, of course a drought is more severe the hotter it is. So looking at rainfall without temperature will only give us half the picture. But for now, it is the first step to understand the effect of climate change (and climate variability) on ranching. We will repeat this process with temperature, and eventually with a suitable drought index that combines temperature and rainfall.
Once we had this figured out, the real challenge was writing the script, telling the computer what to do. I am using a programming language called NCL, which stands for NCAR Command Language (and NCAR is short for National Center for Atmospheric Research in Boulder, Colorado – we really know how to make things complicated). NCL is a programming language specifically for climate and model data, and widely used around the world. I had written a script a few weeks ago that did something very similar, only with monthly data that were compared to rainfall observations, and three thresholds, 10, 20, and 40 percent, instead of one. So this should be similar, but simpler. It's always easier to have a foundation to work from than to start from scratch, because some parts stay almost always the same. Most scripts have three parts: (1) open a data file and extract the necessary variables, (2) process the data in a certain way, and (3) save the result in a new data file. Some scripts create graphs or maps instead of data files, or in addition to it.
Writing a script is like giving a blind person directions for where to go. The computer knows basic operating rules, but it doesn't know what you want to do. It knows pre-defined commands that are hard-wired into the language, like how to open one or more files and how to add or subtract, and basic rules, for example don't divide by zero. But from there it is up to the programmer to make sure the computer does what it should. The smallest typo, a comma instead of a period or a space where there shouldn't be one, can crash the program, or worse, give out incorrect results without anyone noticing. I went step by step, wrote some code, ran it, checked the result, debugged if necessary, ran it again, checked again, wrote some more, ran it, checked it, and so on, until eventually, the script was complete.
Or rather, will be complete. This process can take all day, or longer. After 687 lines of code and eight hours of staring at a screen, I was square-eyed and decided to call it a day and unwind on a long run.
Tomorrow is another day.
Here are Wednesday and Monday, and if you wonder what this about, here is the intro blog post.
The nice thing about working at a big university is there is always something happening, even during summer break.
This morning, a professor from Ethiopia, Dr. Seifu Tilahun, who was visiting the college, gave a seminar about irrigation challenges in Ethiopia at the Borlaug Institute, one building over from my office. It's always fascinating to learn about research in other countries, and to discuss common ideas and challenges. Similar to the U.S., water quality in agricultural areas is a big problem in Ethiopia. Heavy rainfall washes crop fertilizer into streams and lakes and pollutes the groundwater, often the only source of drinking water, especially in rural areas. Practices that can reduce erosion and over-fertilizing, like no-till farming, are known and available, but adoption in the real world takes a long time, no matter how much they make sense to ecologists and economists.
Back in my office, I had to sort out two things before I get started with coding. The first involved paperwork and some physical exercise, two things I got used to quickly in a large department like mine. I needed to register for a coding workshop on campus in August, but I didn't know how pay for it. Most faculty have work credits cards, but for some reason I didn't. So, a quick walk to our business admins in another building, and a few signatures later I had a temporary credit card and could register for the workshop (sadly, I'll have to return it tomorrow).
The second involved Dr. Cait Rottler, a fellow postdoc in Oklahoma with the Agricultural Research Service, the research branch of the U.S. Department of Agriculture. Cait and I are planning a science communication workshop at a rangeland conference next February in Colorado. Good communication is important in research, so that scientists from different fields understand each other and work well together. Cait and I both work in climate change adaptation and know what a challenge this is. More than probably most areas, climate change is one where collaboration between disciplines is key to get things done, from engineering to social sciences to economics and ecology. And our workshop will help with that – or at least that's what we think. Today was the deadline to submit proposals – and with most things that have a deadline, we submitted it in time, but only just :-) We should find out in September if our workshop concept got accepted.
Eventually, after a late lunch and much later than I had hoped, I sat down to work on my data analysis. I only had about three hours before my day was over, which isn't enough to start coding. But that was enough time sketch things out and get started. It's important to know the bigger picture and to develop smaller goals, before starting to write the code to get there. That's what I did today, and tomorrow I will home in on this more.
Here is Tuesday. Wonder what this is about? Here's the intro blog post.
High school students on Skype a Scientist have asked me a few times what an average day looks like for me. But it's hard to find an "average" day, so what I'll do instead is describe an average week. This week should fit pretty nicely.
If you read my About Me page or my Research page, you know I study how climate change affects cattle production in the U.S. Great Plains, a large agricultural region in the central US, between Canada, Mexico and the Gulf Coast, the Rocky Mountains, and the Mississippi. I study data to understand how future changes in temperature and rainfall affect where and how well natural vegetation grows in the Great Plains. Because we're concerned about ranching, I'm not so much interested in shrubland and forests, but mostly grassland, which ranchers use as feed for their cattle.
I'm mostly a data analyst, and our first goal is to publish our work in scientific journals so other researchers can read about it and use it in their own work. These journals are like newspapers for scientists, except they're much harder to understand. We also go to scientific conferences a few times a year to present our work, meet colleagues, and learn about their research (and we get to see some fascinating places, too). We just finished working on two papers, about how past droughts have affected cow numbers in the Great Plains and how grasslands in the Great Plains will change in the future, and we submitted them to two journals for review. It'll probably take a month or so until we hear back from them.
As one of the leaders in our project, I am also interested in the bigger picture, and I am responsible to determine what to do next. Last week, after we finished our second paper, my postdoctoral advisor and I brainstormed about what to do next.
One thing we are trying to understand is what our projections mean for ranchers and their operations. Our data are really just millions of numbers, for every year from 2020 to 2099 arranged in a raster grid across the Great Plains. They can be really abstract if you don't organize them in a smart way.
That's what I'll do this week, plus dealing with smaller things that occur each day.
Every year on the last Saturday of September, the University of Oklahoma hosts a five kilometer run, the Fun Run. Every year around 650 runners participate, and each of them have their own goal. Some just want to push their strollers in more of a five kilometer walk and have a good time, some enjoy the community of runners and maybe push themselves a little. And some switch to race mode, eat pasta the night before, put on their Dri-Fit running clothes and their GPS watches with heart rate monitor, and run like they’re trying to set a new world record.
I fall into this last category.
I’ve been running for about 13 years now, ever since I started college and my class schedule and homework made it difficult for regular wrestling practice. Running is something I can do on my own, at my own pace, whenever I like it, and wherever I like it. I most enjoy running in the morning, through parks and side streets, when the air is crisp and cool. There is nothing more beautiful than to start the day with a run. I like hearing birds chirp, and I watch the world around me slowly wake up. It motivates me, it floods my brain with fresh air and energizes me for the day ahead.
I didn’t use to care much about pace, or technique, or food, or racing, until I realized I was actually quite good at it. Four of my five Fun Runs I finished among the first ten. My first half marathon in 2015 I finished twelfth out of over 1,100 starters. And in my first marathon this year, in Oklahoma City, I finished 37th out of 2,200. I only signed up to run a half marathon, but because Mr. Geography lost his sense of direction … whatever. I ended up running the full marathon.
Finishing my dissertation and applying for jobs is all I can think about these days. And as I was running this year’s Fun Run, I noticed it felt a lot like working towards my defense and applying for a job. Think about it: You learn new things, delve into new techniques, push yourself to the limit, practice and improve for a really long time, and eventually it comes down to meeting expectations and doing better than your competition.
At the Fun Run, I lined up at the front of the race with a group of other fast runners, and we quickly pulled away from the rest of the field. By the first corner, I was in ninth place. I overtook a guy who started out too fast and couldn’t keep his pace, and another one who also couldn’t keep up with the rest. About two miles in, another runner, let’s call him Dr. Evil, came breathing up my neck. I tried to shrug him off, but he slowly inched his way past me. Energized by him, though, I up’d my pace and was now breathing up his neck! He overtook another person in a blue long-sleeve jacket, I followed. Why do you wear long-sleeve in a race?! Eventually I caught up with Dr. Evil, and we ran side-by-side for like half a mile, unable to pull away, unwilling to give in. Things stayed that way until the final stretch when both of us were overtaken by our fashion genius from earlier. Dang it! What’s more, Dr. Evil suddenly unleashed his last reserves, pulled away, and finished 10 seconds ahead of me in fifth place.
Losing on the final stretch, I’m sure we’ve all been there. But even more than outpacing our competition, running teaches you a lot about life and mastering challenges. I was disappointed that I wasn’t as fast as Dr. Evil or Calvin Klein, but in the end trying to keep up with them made me run faster and improve my time from last year by 30 seconds. This challenge made me become better. In grad school it’s often easy to be disappointed by comparing ourselves to others. But the key is to recognize our own personal growth instead of being put down because we didn’t finish first.
Other people’s victories are not my losses. And my losses don’t mean I’m unfit.
Running a marathon is no small thing, but neither is finishing a thesis or getting a job. It requires perseverance and a lot of outside support to achieve either of these. You have to manage your resources to make it to the finish line. Just like a cheering crowd can incite me to keep running when my feet hurt and my muscles are on fire, so can friends and family help us get through hours of tedious number crunching or stressful job interviews.
Running my first marathon was a unexpected challenge that I really wasn’t prepared for. But that’s life sometimes. Things can take unexpected turns, be harder and take longer than we anticipate. My dissertation certainly is, and getting into the job market will be, too. But knowing that I’m good at what I’m doing, that I enjoy running and believe in my own abilities, combined with the encouragement of those around me, made me achieve something that I had no idea I was able to do.
For the last two years I have been studying decision making in winter wheat farming in the Southern Great Plains. I want to help forecasters provide seasonal climate forecasts for farmers that do a better job of warning farmers of bad conditions, such as drought, extreme rainfall, or heat.
Now, seasonal forecasts are nothing new. The National Weather Service has been issuing them for decades. But farmers don’t use them very much because they are hard to understand and overall don’t contain the sort of information farmers need to make decisions.
So all we need are better tailored forecasts and crop failure is a thing of the past? Unfortunately that’s not quite the case.
Hailey Wilmer, a Ph.D. graduate from Colorado State University who currently works as a postdoc at the USDA Northern Plains Climate Hub in Ft. Collins, Colorado, and María Fernández-Giménez, a professor at CSU, studied ranchers in Colorado, New Mexico, and Arizona to gain deeper insights into the social dimensions of ranching decisions related to drought. The two researchers found that besides the weather forecast, decisions are often shaped by many factors, for example traditions, personalities, relationships and interaction with fellow ranchers, risk aversion, or financial goals of the individual rancher.
Conducting 38 interviews with male and female ranchers, Wilmer and her co-author found four reoccurring patterns of how these social factors affect decisions and adaptive actions to mitigate drought on the ranch.
1. Security over profit
Some ranchers, learning from peers and past experiences, prioritized maintaining a financially viable ranch over the long run by not overstocking their ranch in good times and maintaining feed and a minimum number of “seed cattle” even through bad droughts. “If you will stock conservatively when the severe droughts hit you will be able to stay longer and maintain your seed stock to where everyone else has already sold their seed stock or they are all leasing additional pastures somewhere else,” as one New Mexico rancher put it.
2. Facing drought with efficiency
To prepare for bad times, some ranchers use good times to build financial buffers that would carry them through droughts. During drought, they reduce the number of cattle or change grazing patterns so that existing grassland vegetation lasts longer. Although these ranchers tried to avoid risk, if they saw other ranchers succeed with a risky decision, they were inclined to try it, too. In times of need ranchers also help out each other, share expertise, or find additional forage. When the quantity of cattle went down, improving their quality was the top priority for most of these ranchers.
3. Diversified income
Not all ranchers were ranchers all their lives. Some bought ranches after retiring from another career, knowing it is a great risk. During drought, they relied on a range of income, for example on their pension, and they seem to prefer playing it safe. “I think we’ve decided that we’re going to play defense as far as the climate risk goes, as opposed to try[ing] to maximize stocking or to continue to grow or expand the operation,” explained one rancher. They also plan ahead, for example by using weather and climate data to bump up or reduce stocking rates. “We don’t like to do crisis management. We like to sort of prepare.”
4. Living with the “new normal”
The largest group of ranchers, thirteen, seem to have mastered the art of drought management, and was not shy to show it. They boasted experimental approaches to drought management, savvy business management practices, emphasized their successful careers as quality cattle producers and natural resource stewards, all while not relying on consultants or agricultural extension. “Trying something new” and “not being stuck in a rut” were their guiding principles. If drought forces them to reduce their herd, these ranchers, like many of their peers, try to improve quality. “If drought is going to cut me back two hundred calves or three hundred calves, or whatever the number is, I have to make that up with quality.” All this, however, seemed to be essential, as many of these ranchers said living in drought for them is the “new normal”. “Well, we kind of been in a drought ever since we’ve had this place.”
These findings show that decisions in the real world are often a lot more complex than we as scientists think. And it is a particular struggle for those of us who work in boundary organizations understand both scientists and users and to help both sides understand each other and facilitate collaborations. “This paper pushed me toward looking at how different groups ‘know what they know’ and how that influences not just management practices, but also how we interact and set goals,” says Wilmer.
Despite the limitations of this study — small sample sizes, for example, always make it difficult to generalize results to a larger population — it showed me how diverse and complicated the world of agriculture is, and how little we understand of it. Quantitative or technological approaches are not always enough to make a positive change in agricultural decision-making. If we want to help farmers and ranchers, not only do we need to know how to create better forecasts, but also how important these forecasts are among everything else that plays a role in the real world of farming and ranching.
Hailey Wilmer and María Fernández-Giménez (2015): Rethinking rancher decision-making: a grounded theory of ranching approaches to drought and succession management. The Rangeland Journal, 37, 517-528.
Photo: Toni Klemm