Currently browsing category

literature

Anne’s top papers of 2016 + 3 she co-wrote

Yesterday, I posted an epic analysis of my scientific reading habits in 2016, but I didn’t tell you about the papers I read last year that made my heart sing. And I didn’t take much time to brag about my own contributions to the scientific literature. So I’m going to rectify that omission today.

My top 3 papers of 2016 are (in no particular order):

Of rocks and social justice. (unsigned editorial) Nature Geoscience 9, 797 (2016) doi:10.1038/ngeo2836

The whole thing is absolutely worth reading (and it’s not behind a paywall) but here’s where it really starts to hit home:

Two main challenges stand in the way of achieving a diverse geoscience workforce representative of society: we need to attract more people who have not been wearing checkered shirts, walking boots and rucksacks since secondary school, and we need to retain them.

Waters, C. N., Zalasiewicz, J., Summerhayes, C., Barnosky, A. D., Poirier, C., Ga?uszka, A., … & Jeandel, C. (2016). The Anthropocene is functionally and stratigraphically distinct from the Holocene. Science, 351(6269), aad2622.

Want an up-to-date, data-rich, and condensed summary of why many scientists think it is time for a new geologic epoch? This is the paper to read.

Wu, Q., Zhao, Z., Liu, L., Granger, D. E., Wang, H., Cohen, D. J., … & Zhang, J. (2016). Outburst flood at 1920 BCE supports historicity of China’s Great Flood and the Xia dynasty. Science, 353(6299), 579-582.

I am a sucker for a good mega-paleo-flood story, and this one ticks all of the right boxes. An earthquake generates a landslide, which dams a river, and then fails, resulting in one of the largest floods of the last 10,000 years and alters the course of Chinese history. Geology, archaeology, and history combine in this compelling story.

Plus, a bonus paper, that was definitely one of the best papers I read in 2016.

Shields, C., and C. Tague (2015), Ecohydrology in semiarid urban ecosystems: Modeling the relationship between connected impervious area and ecosystem productivity, Water Resour. Res., 51, 302–319, doi:10.1002/2014WR016108.

I’m cheating a little bit here, because this paper came out in 2015. But I read this paper in 2015, and then I read it twice more in 2016. That’s how much I like it. Why? Because it’s a really nice illustration of how physically-based models can reveal the complex and unexpected ways that ecosystems and watersheds respond to urban environments. In a semi-arid environment, deep rooted vegetation can take advantage of the bonus water that gets delivered from rooftop downspouts that drain out onto the land. The additional water use boosts net primary productivity, potentially enough to offset the loss of productivity that occurred when parts of the landscape were paved and built upon. But while deep rooted vegetation, native to the semi-arid landscape, can take advantage of the bonus water, grass can’t. It’s a cool story, with implications for the way we develop and manage urban landscapes – and the way we model them. (This paper is open access as of January 1, 2017!)

I was thrilled to be able to contribute to 3 papers in 2016. 

Turner, V.K., Jarden, K.M., and Jefferson, A.J., 2016. Resident perspectives on green infrastructure in an experimental suburban stormwater management programCities and the Environment, 9(1): art. 4.

In 2015, my team published a paper showing how the installation of bioretention cells, rain gardens, and rain barrels on a residential street in the Cleveland area substantially decreased stormwater runoff. This paper represents the other side of the story – the side that is, just as important (if not more so) – how the people on the street responded to the addition of this green infrastructure. In short, getting residents on board with stormwater management is a big challenge that we’re going to face as we scale-up from demonstration projects to widespread deployment of these technologies. (This paper is open access and free to all.)

Bell, C.D., McMillan, S.K., Clinton, S.M., and Jefferson, A.J., 2016. Hydrologic response to stormwater control measures in urban watershedsJournal of Hydrology. Online ahead of print. doi: 10.1016/j.jhydrol.2016.08.049.

Bell, C.D., McMillan, S.K., Clinton, S.M., and Jefferson, A.J., 2016. Characterizing the Effects of Stormwater Mitigation on Nutrient Export and Stream ConcentrationsEnvironmental Management. doi:10.1007/s00267-016-0801-4

I’m thrilled that first author Colin Bell completed his doctorate in 2016 and got two papers out to boot. These papers are the culmination of 5 years of research in Charlotte, North Carolina. In the Journal of Hydrology, we try to disentangle the effects of stormwater management from the overall signal of urbanization across 16 watersheds. It turns out that for the level of stormwater management we see in the real world, it’s not enough to counter-act the effects of impervious surfaces (pavement and rooftops) as a driver of the hydrologic behavior of urban streams. In Environmental Management, we aim to understand the influence of stormwater ponds and wetlands on water quality in the receiving streams. This turns out to be quite tricky, because the placement of stormwater management structures spatially correlates with changes in land use, but based on differences in concentration between stormwater structure outflow and the stream, we show that it should be possible. This echoes the findings from our 2015 paper using water isotopes to understand stormwater management influences at one of the same sites. Colin will have another paper or two coming out of his modeling work in the next year or so, and we’re still analyzing more data from this project, so keep your eyes out for more work along these lines.

Teaching graduate seminars is good for an academic’s reading habits (Anne’s 2016 #365papers in review)

1. Introduction

As a scientist, one of my big challenges is to keep on top of the vast and ever-growing body of scientific knowledge about my research and teaching subjects. I’m not the only one who apparently struggles with this task, or wishes she could do more. on January 1st, 2015, Jacquelyn Gill proposed the #365papers idea, which challenged us up the ante on our reading habits. I choose to interpret the 365 part not as a mandate to read a paper every day, or 365 papers in a year, but simply to record what I’ve read over the course of a year. I tweeted each paper I read, faithfully using the #365papers hashtag, and at the end of 2015, I looked back on what I’d read and did some fairly simple analyses. However, 2015 was an exceptional year for me personally because of the birth of my son, and I wasn’t sure how my results would look in a more “normal” year. Hence, like a good scientist, I decided to collect some more data. I hypothesized that I would read and review more papers when back at work full-time, but I thought that there was some potential that my 2 courses per semester teaching load would decrease my reading during the climax of each term.

2. Methods

Based on what a pain-in-the-neck it was to compile all of the metrics that I wanted to analyze at the end of 2015, I decided to alter my methods from the previous experiment. I created a Google spreadsheet to track my reading, including date read, journal, open access, gender and nationality of first author, and more. I began the year by tweeting and storifying the papers I read, as in 2015, but I abandoned the storify mid-year and ended up being a bit haphazard with the tweeting. I only counted papers that I read fully through the results and discussion sections, so there are quite a few papers that I read large chunks of but didn’t make the list because I didn’t finish. I also counted textbook chapters, government publications, and defense-ready dissertation chapters that I read fully, as well as papers and proposals that I reviewed. I didn’t count the many many pages of student writing for class or thesis proposals or the hundreds of great articles I read from Internet publications, magazines or newspapers. I also didn’t count “popular science” or other fiction and non-fiction books I read.

3. Results and Discussion

The data from 2016 support my hypothesis that having an infant depresses my reading rate, but the effects of my teaching load are the most unexpected result of this year’s analysis. In 2016, my list contained 132 items, which is a 70% increase over the 78 items I read in 2015.

3.1 What types of things did I read?

  • 95 journal articles, including 3 that I co-authored that appeared in press in 2016
  • 16 grant proposals as a reviewer
  • 9 manuscripts as a reviewer
  • 4 academic book chapters
  • 4 dissertation chapters
  • 2 government publications
  • 2 GSA special publications

In every category, I read more than in 2015. I read 169% of the number of journal articles I read the previous year. I more than tripled the number of manuscript reviews I did, but this gibes pretty well with my long-term rate of reviewing. In 2015, I had liberally turned down review requests while on maternity leave. Even though I reviewed more in 2016, the ratio of published articles to reviews increased from 3.3 to 3.8 articles per review. This is good, because one of the things I had worried about in 2015 was that my reviewer service (particularly for proposals) was taking away from keeping up with the published literature.

3.2 When did i read?

Graph showing day of year on x axis and % of papers read on the y-axis. Data are reasonably linear.

Figure 1. Cumulative distribution function of my reading in 2016. Spring semester ended around day 135, and fall semester began around day 240. (This graph may be the nerdiest thing I have ever done. I am so proud of myself.)

I passed my 50% mark on June 21st, so I read at a ever so slightly greater rate in the first half of the year than the second. But my biggest reading gap also occurred early in the year, after which I made up for it in a hurry. I honestly can’t quite remember what was going on there.

I had hypothesized that teaching would depress my reading rate, but in fact the opposite phenomenon is observed, as my least literary months were during the summer. I think part of the explanation is that I was teaching a graduate level class each semester, and in these classes I like to focus a lot on getting the students engaged with the primary literature. The end result of that is that I read a lot too. More on that effect in a bit.

Comparison of 2016 to 2015 is provocative. As in 2015, I traveled a lot in June, so that was a good reason for my reading rate to be low. In 2015, I’d suggested that my reading rate went down in the summer because of a more mobile baby, but it appears to be a broader pattern. Maybe something about working for 3 months for free was a disincentive to doubling-down on the reading?

Line graph of reading rate per month for 2 years.

Figure 2. In order to compare 2016 data to 2015, I aggregated my reading into monthly bins.

 

3.3 Why did I read what I did?

New for 2016, I kept track of why I read each paper. Things tagged “general” are those that I read to keep up with a field, while things tagged “research” were those I read in pursuit of a particular paper or proposal. (Or at least that was the intent, I’m not 100% sure I remembered that distinction each and every time.)

Pie graph showing a big blue slice for teaching (48%), ~1/4 each for general and research, and tiny slivers for public engagement and service.

Figure 3. The primary reason I read each paper in 2016. Yes, I know pie graphs are bad, but I like how colorful it is.

I’m really surprised by what a big chunk of my reading budget was occupied by papers read for teaching in 2016. I knew this fall that the only way I was reliably getting reading done was for class, but I didn’t expect it to be nearly half of my total reading this year.

This may go a long way to explaining why my reading rates were higher during the academic year when I was teaching than not. Maybe I’m actually a slacker about reading for research? But it is also important to note that this excludes all forms of reviews and dissertation chapters, which were 22% of my total reading load this year. So maybe I just need a different pie graph next year that factors those reviews and chapters in.

3.4 Who wrote the things I read?

I read 31 articles with women first authors in 2016, and 71 articles with men first authors. (This count excludes the reviews, dissertation chapters and an unsigned editorial.)  That gives me a rate of 30%, which is almost identical to what I reported in 2015. As I said then, this rate “is actually better than the 20% of US earth science faculty positions filled by women, though lower than the 40+% of geoscience PhDs awarded to women.” Of the 102 items where I can reveal authorship, 93 unique author names appeared, so I didn’t tend to read the oeuvre of any particular scientist this year. (Or if I did, that scientist doesn’t always publish as first author.) My rate of unique first authors was similar for women and men.

I also analyzed the country of affiliation for the first authors I read, and the results surprised me. 79% of the articles I read had a US first author, and the only other countries from which I read more than a couple of first-authored papers were Canada, the UK, and Australia. In some ways, I can see, given my area of research, why there would be a US bias in my reading habits, as I need to particularly pay attention to things that inform my understanding of my field research areas, but I didn’t expect the bias to be that substantial. I might make more of a concerted effort this next year to read papers coming out of Europe and non-Western countries, because there’s a lot to be learned outside of the US bubble. (I didn’t record nationality in 2015.)

3.5 How did I get access to the things I read?

18% of the published articles I read were open access (available through the publisher website). That’s lower than what I reported at the end of 2015, but I also discussed how holding a baby and reading on an iPad made me favor open access articles that year. In general, I think open access publishing is clearly the dominant direction that scientific publishing is moving over the next decade, so I’d be surprised if 18% weren’t a decadal minimum for me. I suspect that the number of articles I read in one particular paywalled journal is what is depressing my rate for 2016.

While officially open access articles are still very much a minority of my reading diet, 45% of the articles I read were freely available on the web in some form, either via the publisher, or on an author website, ResearchGate, or “in the wild” via someone’s existing upload (not counting SciHub), often as part of a course webpage. Of those routes to access, those “in the wild” uploads were the ones I most commonly found, though my sense is that ResearchGate is becoming a major player in the sharing of scientific papers.

I’m also happy that one of the three papers I coauthored this year is available from the open access journal that published it. Want to know what homeowners thought about a project to install rain gardens and bioretention cells into their neighborhood? You can read about what we found in Cities and the Environment with no paywall to stand in your way.  I’d like to move to a far higher percentage of open access publishing over the next few years.

3.6 When were the papers written?

Figure 3. Date of publication of papers read in 2016. Note that the very last paper I read in 2016 had a 2017 publication date to it. The oldest paper I read was published in 1953.

Figure 4. Date of publication of papers read in 2016. Note that the very last paper I read in 2016 had a 2017 publication date to it. The oldest paper I read was published in 1953.

 

The results for 2016 are pretty consistent with 2015, and as I said at the time, they are about what I expect to see for someone “keeping up with the field.” I read the most papers that were published in 2016, and the half life of my reading habits is 2 years (so 50% of the publications I read were published in 2014 or thereafter). That’s the same median publication date I reported for 2015, but, interestingly the weighted average of my reading actually moved backwards in time. In 2016, the weighted average publication date was 2006, which is 4 years older than it was in 2015. This is a function of the heavier tale on my distribution as I revisited classic papers for teaching purposes.

3.7 What were the top 5 journals I read?

  1.  Science (19 articles)
  2. Geomorphology (7 articles)
  3. Nature (6 articles)
  4. Water Resources Research (5 articles)
  5. (tie) Freshwater Science and GSA Bulletin (4 articles)

As the year progressed, I had the sneaking suspicion that I was reading a lot more Science than usual, but the results blow me away.  (Science didn’t even make my top 5 list in 2015.) There are a few factors at work here. First, I joined AAAS, so I could go straight from the e-Table of Contents to a digital version of the journal without the hassle of logging in through my university. Thus, there was a lower barrier to reading articles than in the past. Second, I worked on a proposal focused on science education and discovered that Science has published some pretty heavy hitting articles in that field. Third, since I was teaching Fluvial Geomorphology fall semester and we were reading and discussing multiple articles every week, I was revisiting some heavy hitting papers that had been published in the journal over the last few decades. The elevation of Geomorphology and Nature in the standings this year also is an effect of teaching Fluvial Geomorphology I think. Freshwater Science got a boost from a really nice special issue focused on urban ecosystems early in 2016. Water Resources Research is the only hold-over from 2015 to 2016 on my list. I can’t wait to see what 2017 brings.

3.8 How many journals did I read from in 2016?

49.

Boom.

49. If you were giving me the side-eye for reading only 5 articles from Water Resources Research last year (and fewer than that from other major hydrology journals), please pause and reflect that the number of journals that I read from is more than 50% of the number of papers I read. Working on urban aquatic systems and fluvial geomorphology forces me to read broadly, because I am staying abreast of new knowledge hydrology, engineering, ecology, planning, geography and more. Also, this total doesn’t count the manuscript reviews I did, which were for journals much more in line with my hydrological and geomorphological expertise.

3.9 Where did I find all those articles?

New for 2016, I also kept track of where the articles I read first attracted my gaze. 19% of them were tagged “already known”, which are mostly things I was revisiting for teaching purposes and sometimes for research. 17% came to my attention via e-tables of contents, and 9% were identified as part of my backlog from 2015 and prior. In terms of search, my most common search tool was Google Scholar, generating 17% of my reads, and I really didn’t read much I found on Web of Science or other search tools. My preference for Google Scholar has a lot to do with how easy it is to use without having to log in through our library website, even though I really like some of the snazzy tools that Web of Science provides. Other ways I found papers included Twitter (4), colleagues, students, author websites, other people’s syllabi (teaching papers!), and conference talks. And of course a reviewer suggested a paper that my previous reading had missed. Thanks, reviewer!

3.10 What did I read about?

Every article I read I tagged with a primary topic and an optional secondary topic. The topics were chosen from a semi-controlled vocabulary (i.e., I tried to be consistent but wasn’t always). Once again, the data show the clear influence of my Fluvial Geomorphology teaching on my reading in 2016, with a probable secondary effect of my Urban Hydrology teaching, although that’s more difficult to disentangle from my research reading.

Based on primary topic alone, I read:

  • geomorphology (45)
  • urban hydrology (30)
  • science education (7)
  • hydrology (other than urban) (6)
  • diversity/women in science (5)
  • climate science and climate change (3)
  • public engagement and science communication (3)
  • water quality (2)
  • geology/tectonics (1)
  • social science (1)

If you add in the secondary topics (where only about half of papers had were tagged as having one), climate science and climate change jumps into the 3rd position, which makes a lot of sense as I’d be inclined to read articles that talked about the effects of climate on urban aquatic systems and geomorphic processes. Water quality jumps up to tied with science education, and ecology enters the rankings at that same spot as well. Here again, I think we’re seeing a synergy of hydrology and geomorphology and their interactions with other fields of research. In addition to ecology, a few other topics showed up only as a secondary topic. These included policy, land use, archaeology, modeling, and human impacts, and all of these are certainly cognate topics to my research.

4. Conclusions

The most surprising conclusion of this year’s study was the dramatic effect of teaching on my reading. I am teaching much less in 2017 than I did in 2016 (and I don’t expect an infant to be the reason), so I am profoundly curious what my reading rates, reasons, and patterns will look like over the next year. If I ever finish this blog post, I’ve already got two papers queued up to read (thanks, Twitter!).

I’d like to do a better job in the next year of paying attention to multiple dimensions of diversity in my reading, at least in a qualitative sense. I don’t know what percent of women first-authored papers exist in the geosciences, though a cross-disciplinary analysis found 0.42 papers by women authors for every 1 paper by men for US-based authors, suggesting my 30% is pretty much what you’d expect. There’s also some fascinating work on gender bias in the publication process at AGU journals, in terms of submission, acceptance, and reviewing, that was presented at GSA in 2016 and should be out in article form this year. But gender is the easy diversity axis to pick at, along with nationality of author affiliation (which I noted above that I’m not doing well at), and there are also issues of race, ethnicity, sexuality, affiliation type, professional rank and more that may be subtly affecting what I and others read. Collecting data on these intersecting axes is difficult, and I try to read the science I do because of the subject matter not the author, but I need to be aware of how subconscious bias may be leading me to favor some papers over others.

Finally, a much less surprising conclusion is that given a data set, even of dubious scientific value, the scientific mind will not be able to resist the temptation to dive in, analyze the heck out of it, and then share the results with the world. While my data over 2 or 3 or 10 years will never rise above the level of anecdata, imagine if many scientists started carefully tracking their reading habits. What a valuable dataset that would be, adding an incredible richness to our understanding of how scientific knowledge propagates. If you saw the #365papers hashtag pop up on Twitter or elsewhere on January 1 and thought that you couldn’t possibly reach that goal, so why try, I encourage you to take a different tack and use the concept as a vehicle for reflection through an academic version of life-logging. Or maybe we could even call it research.

5. Acknowledgements

Thanks as ever to Jacquelyn Gill for getting this whole thing started and for being a role model for an engaged academic in so many ways. Thanks to Meghan Duffy and Josh Drew for nerding out about your own stats, and much gratitude to all the #365papers participants in 2015-2017 for solidarity, tweeting your reading to keep me inspired, and for important conversations about work life balance. Finally, a special debt of gratitude to my family for putting up with me and all my nerdery.

Looking back at the Upper Mississippi River, moving forward

A student and I are working on finishing a project that has lingered for too many years: a careful analysis of the cumulative effects of river management on islands in the lower part of Pool 6 of the Mississippi River, near my hometown of Winona, Minnesota. There will be a MS thesis soon and hopefully a journal manuscript shortly to follow that, but for now, I’m enjoying discovering new and old research and resources on “the father of waters.”

First, check out this 17-minute silent film on the 1927 Mississippi River flood:


For more information on the film made by the Signal Corps in the 1930s, head here: http://archive.org/details/mississippi_flood_1927

Then, check out this 2012 publication from the USGS on “A Brief History and Summary of the Effects of River Engineering and Dams on the Mississippi River System and Delta.”

Finally, there’s a paper just out in Geophysical Research Letters by Frans et al. titled “Are climatic or land cover changes the dominant cause of runoff trends in the Upper Mississippi River Basin?.”

And that’s my afternoon reading sorted.

New report: Challenges and Opportunities in the Hydrologic Sciences

The “blue book” has been updated and you can read and download a pre-publication PDF on the National Academies’ website for free. I’ve just been listening to a CUAHSI webinar summarizing the report, and I was please to see that a lot of the questions I’m interested in were highlighted by the committee that updated the report. For instance, there was specific mention of urban hydrology (and how changes to flowpaths and quantity alter water quality), the co-evolution of hydrology, landscapes, and life, and the need to understand the controls on the low flow extent of streams. I’ll be reading sections of this report in coming months, and if you want to get a sense of the state of hydrologic science, you would probably do well to start here too.

Cynthia Barnett, award winning water journalist and author, to speak at UNC Charlotte

Cynthia Barnett

Cynthia Barnett (photo supplied by Ms. Barnett)

I’m excited to announce that Cynthia Barnett will be speaking on campus next week. She’s an outstanding thinker and writer about water conservation, particularly as it pertains to the eastern United States, where our sense of water-richness has lulled us into complacency.

From the press release:

Award-winning journalist and author Cynthia Barnett will visit UNC Charlotte to discuss water ethic for America at 7 p.m., Wednesday, Sept. 21, in the College of Health and Human Services, Room 128.

Barnett’s talk is the first stop for a tour about the book “Blue Revolution: Unmaking America’s Water Crisis,” scheduled for national release Sept. 20. “Blue Revolution” is said to be the first book to call for a national water ethic. Barnett uses the Catawba River as an example to illustrate the important role that water plays in America’s energy supply. The book combines investigative reporting with solutions from across the country and the globe to show how communities and nations have come together in a shared ethic to reduce consumption and live within their water means.

Barnett also is the author of “Mirage: Florida and the Vanishing Water of the Eastern U.S.” A veteran journalist, she won the national Sigma Delta Chi prize for investigative magazine reporting and a gold medal for best nonfiction in Florida book awards.  A book signing follows this free, public presentation, which is cosponsored by the UNC Charlotte Ethics Center, IDEAS Center and the Department of Geography and Earth Sciences.

BlueRevolutionCoverCynthia will also be available to meet with students and faculty in CHHS 128 from 4 to 5 pm. Please stop by, say hi, and ask your water questions.

I’m currently devouring a copy of Cynthia’s new book, so look for a review of the book here or elsewhere in the coming weeks.

New paper: Seasonal versus transient snow and the elevation dependence of climate sensitivity in maritime mountainous regions

Snowline near Skykomish, Washington (photo on Flickr by RoguePoet, used under Creative Commons)

Snowline near Skykomish, Washington (photo on Flickr by RoguePoet, used under Creative Commons)

Jefferson, A. 2011. Seasonal versus transient snow and the elevation dependence of climate sensitivity in maritime mountainous regions, Geophysical Research Letters, 38, L16402, doi:10.1029/2011GL048346.

Abstract:

In maritime mountainous regions, the phase of winter precipitation is elevation dependent, and in watersheds receiving both rain and snow, hydrologic impacts of climate change are less straightforward than in snowmelt-dominated systems. Here, 29 Pacific Northwest watersheds illustrate how distribution of seasonal snow, transient snow, and winter rain mediates sensitivity to 20th century warming. Watersheds with >50% of their area in the seasonal snow zone had significant (? ? 0.1) trends towards greater winter and lower summer discharge, while lower elevations had no consistent trends. In seasonal snow-dominated watersheds, runoff occurs 22–27 days earlier and minimum flows are 5–9% lower than in 1962, based on Sen’s slope over the period. Trends in peak streamflow depend on whether watershed area susceptible to rain-on-snow events is increasing or decreasing. Delineation of elevation-dependent snow zones identifies climate sensitivity of maritime mountainous watersheds and enables planning for water and ecosystem impacts of climate change.

Bacteria in the sky, making it rain, snow, and hail

ResearchBlogging.orgCross-posted at Highly Allochthonous

Even though we all think of the freezing point of water as 0 °C, very pure water remains a liquid until about -40 °C. Water crystallizes to ice in the presence of tiny nucleation particles in the atmosphere. These particles can be sea spray, soot, dust … and bacteria.

Bacteria are particularly good at ice nucleation (IN), causing it to occur at temperatures as high as -2 °C. As Ed Yong described 3 years ago:

Ice-forming bacteria like Pseudomonas syringae rely on a unique protein that studs their surfaces. Appropriately known as ice-nucleating protein, its structure mimics the surface of an ice crystal. This structure acts as a template that forces neighbouring water molecules into a pattern which matches that of an ice lattice. By shepherding the molecules into place, the protein greatly lowers the amount of energy needed for ice crystals to start growing.

USDA photo of ice on flowers

Ice on fruit tree flowers. There because of bacteria? (USDA photo)

The fact that bacteria like P. syringae nucleate ice crystals has been known for decades. They can be used for gee-whiz science demonstrations, and, at a much larger scale, as one method for creating artificial snow. On the flip side, the presence of P. syringae is also also makes plants more likely to be frost damaged at temperatures just below freezing. Only in the last several years, though, has the role of bacteria in producing precipitation from the atmosphere begun to be appreciated.

First, Brent Christner and colleagues discovered that every freshly fallen snow sample they collected, even in Antarctica, contained these ice nucleating bacteria. In the resulting 2008 Science paper, they noted:

The samples analyzed were collected during seasons and in locations (e.g., Antarctica) devoid of deciduous plants, making it likely that the biological IN we observed were transported from long distances and maintained their ice-nucleating activity in the atmosphere…our results indicate that these particles are widely dispersed in the atmosphere, and, if present in clouds, they may have an important role in the initiation of ice formation, especially when minimum cloud temperatures are relatively warm.

Then researchers in the Amazon rainforest discovered that primary biological aerosol (PBA) particles, including plant fragments, fungal spores…and yes, bacteria, were a dominant contributor to ice nucleation in clouds above the rainforest. (Even the though the Earth surface is hot in the Amazon, high enough in the troposphere, it’s still below freezing.) As Pöschl and colleagues reported in Science in 2010:

Measurements and modeling of IN concentrations during AMAZE-08 suggest that ice formation in Amazon clouds at temperatures warmer than –25°C is dominated by PBA particles… Moreover, the supermicrometer particles can also act as “giant” [cloud condensation nuclei] CCN, generating large droplets and inducing warm rain without ice formation.

The latest contribution to the growing understanding of bacteria’s role in precipitation was recently presented at the American Society of Microbiology meeting. Alexander Michaud studied hailstones that fell on his Montana State University campus, and as reported by the BBC:

He analysed the hailstones’ multi-layer structure, finding that while their outer layers had relatively few bacteria, the cores contained high concentrations. “You have a high concentration of ‘culturable’ bacteria in the centres, on the order of thousands per millilitre of meltwater,” he told the meeting.

What all of this adds up to is that we now know that bacteria and other biological particles are prevalent in the atmosphere around the world and are stimulating multiple forms of precipitation. As a hydrologist, I think I can wrap my head around this. But what’s really wild is the feedback between biological productivity and precipitation and the possibility that the ice nucleating bacteria moving in the atmosphere may be an evolutionary trait.

Precipitation stimulated by ice nucleation above an ecosystem where the bacteria or other biological particles were emitted sustains the ecosystem that created those particles. As Pöschl et al write:

Accordingly, the Amazon Basin can be pictured as a biogeochemical reactor using the feedstock of plant and microbial emissions in combination with high water vapor, solar radiation, and photo-oxidant levels to produce [secondary organic aerosols] SOA and PBA particles (31, 32). The biogenic aerosol particles serve as nuclei for clouds and precipitation, sustaining the hydrological cycle and biological reproduction in the ecosystem.

Or, in discussion of the recent hailstone findings [from the BBC]:

Dr Christner, also present at the meeting, said the result was another in favour of the bio-precipitation idea – that the bacteria’s rise into clouds, stimulation of precipitation, and return to ground level may have evolved as a dispersal mechanism. … “We know that biology influences climate in some way, but directly in such a way as this is not only fascinating but also very important.”

Tara Smith lolbacteria

and ur rainz and ur hailz (image created by Tara Smith on the Aetiology blog)

Christner, B., Morris, C., Foreman, C., Cai, R., & Sands, D. (2008). Ubiquity of Biological Ice Nucleators in Snowfall Science, 319 (5867), 1214-1214 DOI: 10.1126/science.1149757

Pöschl U, Martin ST, Sinha B, Chen Q, Gunthe SS, Huffman JA, Borrmann S, Farmer DK, Garland RM, Helas G, Jimenez JL, King SM, Manzi A, Mikhailov E, Pauliquevis T, Petters MD, Prenni AJ, Roldin P, Rose D, Schneider J, Su H, Zorn SR, Artaxo P, & Andreae MO (2010). Rainforest aerosols as biogenic nuclei of clouds and precipitation in the Amazon. Science (New York, N.Y.), 329 (5998), 1513-6 PMID: 20847268

Geology is destiny: globally mapping permeability by rock type

Cross-posted at Highly Allochthonous

ResearchBlogging.org

Permeability (the ease with which a fluid moves through a material) is the ultimate goal of many hydrogeologic investigations, because without that information it is impossible to quantify subsurface water and heat flow rates or understand contaminant transport. Yet permeability is notoriously difficult to quantify, both at the local-scale and the landscape-scale. Permeability varies over 13 orders of magnitude across rock and sediment types, because of differences in pore sizes, geometry, and connectedness. Loose gravel could have permeability as high as 10-7 m2, but unfractured igenous and metamorphic rocks could be as low as 10-20 m2. The diagram below is an example of the sort of relationship between rock type and permeability shown near the beginning of every major hydrogeology textbook.

Typical ranges of permeability for different rock types, usually based on hydraulic measurements made at wells.

Typical ranges of permeability for different rock types, usually based on hydraulic measurements made at wells.

Most of the time, hydrogeologists are happy to just to get permeability to within an order of magnitude or two. Knowing permeability is not just useful for those interested in in water supply problems and transport of contaminants. For scientists who model watersheds or land-atmosphere interactions in climate models, being able to easily estimate landscape-scale permeability would be incredibly helpful.

In a new paper in Geophysical Research Letters, scientists from Canada, Germany, the Netherlands, and the US have just done a big favor for those scientists. Gleeson et al. (2010) compiled the first regional-scale maps of permeability for the North American continent and the terrestrial globe. They are interested in permeability in the uppermost 100 m of the subsurface, but below the water table, where all pore spaces are saturated with water. They defined regional-scale as greater than 5 km, because they wanted to avoid influences by things like individual fractures. Using previously published hydrogeologic models, in which permeability was calibrated against groundwater flow, tracers, or heat fluxes, Gleeson and colleagues identified permeability values for 230 hydrogeologic units, grouping them into seven “hydrolithologic” categories, by rock type.

The scientists compared the permeability values from the models to the expected permeabilities for each rock type based on smaller-scale measurements (like those used to make the graph above), and they found reasonably good correspondence. They also examined whether permeability values within each hydrolithologic category were correlated with the scale of the model used to generate them. They found that permeability was scale-independent above 5 km, except in carbonates, where large karst features may result in changing permeability with increasing area.

Using pre-existing geologic maps for North America and the world, Gleeson and colleagues divided the Earth into their hydrolithologic categories. For each category, they calculated the geometric mean of the modeled permeability values, and applied that mean permeability to all of the map units in that category. The resultant maps show the distribution of permeability across the land surface.

Portion of Figure 3c from Gleeson et al. (2010, Geophysical Research Letters).

Portion of Figure 3c from Gleeson et al. (2010, Geophysical Research Letters) showing the permeability distribution across North America. North of the dashed line is continuous permafrost and in that region, the map likely significantly over-estimates permeability.

The global map uses a single geology dataset, so there are no weird boundaries in the data, but it is of coarse resolution. The North American map (shown above) is at much finer resolution (75 km2 mean polygon area, with 262,111 polygons), but it has a few odd edges that correspond to state and national borders. The authors point to these boundary problems in their discussion of caveats, along with the problems associated with permafrost, deep unsaturated zones in arid areas, and deep weathering in the tropics. In addition, the use of a single permeability value for each category will necessarily lump together some terrains with similar rock types but differing geologic histories and resultant permeabilities (e.g., the High and Western Cascades in Oregon).

The work of Gleeson and colleagues represents an important first step in translating regional-scale geologic data into permeability fields. These maps will be useful for continental-scale and larger earth system models and for data sparse regions. Their methodology also raises some interesting possibilities for subdividing the hydrolithologic categories in areas where there are more hydrogeologic model data available, but where there hasn’t been comprehensive hydrogeologic modeling. Finally, their finding that regional-scale model values are in accord with the ranges reported in every hydrogeology textbook is a significant confirmation of the fall-back position of many students of hydrogeology: “If you have no data from wells in your field area, use a textbook to estimate permeability from the rock type.”

Gleeson, T., Smith, L., Moosdorf, N., Hartmann, J., Dürr, H., Manning, A., van Beek, L., & Jellinek, A. (2011). Mapping permeability over the surface of the Earth Geophysical Research Letters, 38 (2) DOI: 10.1029/2010GL045565