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Sampling on the Ganges and Brahmaputra Rivers

Geohazards in Bangladesh - Sat, 02/04/2017 - 21:51
Chris smiling broadly as he and Humayun buy 11 lbs of Jordibaja, a local Kushtia snack food from the most famous bakery that makes it.

Chris smiling broadly as he and Humayun buy 11 lbs of Jordibaja, a local Kushtia snack food from the most famous bakery that makes it.

From Khulna in the SW, we are heading to Rajshahi on the Ganges River, but first we are stopping at Kushtia, Humayun’s home town. Because the road on the more direct route is supposed to have bad road conditions, we took a longer route, way longer. It wiped out any chance to get to Rajshahi in time for some fieldwork, but it did my districts (states) of Bangladesh visited to 40 out of 64. After many hours on the road, we reached Kushtia and out goal – jordibaja, a fried noodle snack that is only available here. Chris bought ten 500 gram bags, about 11 lbs, at the bakery that makes

Liz in Rajshahi walking back to our group protected by two policewoman that were part of our escort during a quick visit back to our van.

Liz in Rajshahi walking back to our group protected by two policewoman that were part of our escort during a quick visit back to our van.

the best, of course. We then had a late lunch and continued to Rajshahi where we were once again joined by a police escort. Different teams stayed with us until we left the area. After finding our hotel, we all had our first hot water shower since we left Dhaka. Living on boats is great, except for the complete lack of hot water. Once cleaned up, we went to Humayun’s sister for a delicious dinner. After dinner, the commissioner of police, a former student of Humayun’s stopped by. He suggested we visit some of the chars (sandy river islands) close to Rajshahi rather than the places we went

Our police escort watches Chris and Dan measuring spectra on a char (sandy river island) to compare with satellite measurements.

Our police escort watches Chris and Dan measuring spectra on a char (sandy river island) to compare with satellite measurements.

to other years, an hour or more drive away. Chris and Dan checked their satellite images and found that the nearby chars would work, probably dsaving 2-3 hrs of driving.

The next morning, we headed off with out new escort, that included two policewoman. However, that had to switch off when we crossed from one precinct to another. Renting a country boat we crossed the Ganges to the chars. While Dan and Chris (with Humayun) made salinity, moisture and spectroscopic measurements, Liz and I

Dan measures the water content of a small area of quicksand we found while Liz is being sucked in as she explores it.

Dan measures the water content of a small area of quicksand we found while Liz is being sucked in as she explores it.

scouted for the proper sediment samples for her OSL needs. After wandering about the island we found what she wanted and collected a sample. Until now, her studies of the delta did not have any samples from the Ganges itself. For Dan and Chris to get the observations they wanted, we visited several chars before ending up back at the first one for them to study the transition from sandy sediments to rice fields. As soon as the chars have deposits of the right kind of sediments, people start planting crops. If the char continues

Digging out our OSL dating sample of silt on the Ganges. The tape wrapped PVC pipe had been hammered entirely into the outcrop. The sample inside must not be exposed to light or it will be ruined.

Digging out our OSL dating sample of silt on the Ganges. The tape wrapped PVC pipe had been hammered entirely into the outcrop. The sample inside must not be exposed to light or it will be ruined.

to grow and stabilize, they will move there as well. They are great places to live 9 months of the year, but a struggle during the high water of the monsoon season. The islands with migrate, eroding from one side while sediment deposits on the other. The char people have to move frequently as the chars move out from under their homes. Liz and I wandered off and found another place to sample. Now she have both a sand and a silt samples from the Ganges. It only took a few hours to accomplish the more specific tasks of this field program. When we first started visiting chars 12 years ago, we explored then from the morning

Chris and Dan discussing notes on locations to visit based on recent satellite images and entering them into the GPS.

Chris and Dan discussing notes on locations to visit based on recent satellite images and entering them into the GPS.

until dusk. We needed to see and explore all aspects of this new environment for us. Now, we are building on our work with much more focused activities.

Off the river by early afternoon, we drove across country to Bogra near the Jamuna River, as this part of the Brahmaputra is known. We were able to arrive around sunset, avoiding the sometimes frightening driving in the dark. For old times sake, we skipped the new hotel that was booked and stayed at the colorful Parjartan Hotel that we first used

Chris, Dan, and Bulbul, our driver, walking down the embankment at Sirajganj. During the summer, the water level will reach the top of the embankment as the river flow increases by a factor of 10 or more.

Chris, Dan, and Bulbul, our driver, walking down the embankment at Sirajganj. During the summer, the water level will reach the top of the embankment as the river flow increases by a factor of 10 or more.

in 2005. It is literally painted the colors of the rainbow, as well as having more character, even if everything is not quite working. This was the hotel where my room once had electric outlets of 4 different shapes, requiring every adapter I had to recharge my equipment. Now I always bring an outlet strip so I only need one adapter.

We had planned to go north to Gaibandha, but a new satellite overpass showed that we could get all the data we needed farther south at Sirajganj. We could cut out a day. As it turns out, this was fortuitious. I have a family

Humayun walks to the country boat we rented at Sirajganj to bring us across the river to the chars.

Humayun walks to the country boat we rented at Sirajganj to bring us across the river to the chars.

emergency and have to return to the U.S. From Sirajganj we could return to Dhaka, rather than stay at Tangail. Chris and the others can do the rest of the field work as day trips from Dhaka. It is more driving for them, but will enable be to catch the evening flight back to the U.S. We packed up and headed to the embankment at Sirajganj, which protects the city from the shifts in the Jamuna River. We walked down the embankment (the river level is about 7 m or 23 feet higher during the summer monsoon season). We headed for a large char that

Liz examines an outcrop on the large char across from Sirajganj while looking for appropriate sediments to sample. Wherever the conditions are right, the chars are planted with crops while the bare sand remains exposed in the younger parts of the char.

Liz examines an outcrop on the large char across from Sirajganj while looking for appropriate sediments to sample. Wherever the conditions are right, the chars are planted with crops while the bare sand remains exposed in the younger parts of the char.

we first visited in 2005. It has grown and become attached to other chars. It also has much more agriculture, they are growing rice, peanuts, lentils, corn and more. The complex history of changes in the char provides lots of different sediment types for Chris and Dan and plent of cut bank surfaces for Liz to get a good silt sample. A few hours of exploring, sampling, measuring and we were done. Since it is Friday, the Muslim holy day and the weekend here, traffic is light until we reach Dhaka. Near the university and our hotel, the streets are packed with people and rickshaws. Still we manage to get to the university to drop off equipment and for me to get 7

Liz measures the position of the hammered in sampling tube before we dig out and collect our last sample, a silt from the Jamuna (Brahmaputra) River.

Liz measures the position of the hammered in sampling tube before we dig out and collect our last sample, a silt from the Jamuna (Brahmaputra) River.

GPS receivers that finally have to be returned to UNAVCO after 10 years. This is the last of the 11 we were lent in 2007 by them. They provide geodetic data and services for NSF and allowed us multiple extensions that enabled us to get this much needed data for so long. It is the basis for our paper on the potential earthquake hazard in Bangladesh as we can see the slow motion of the surface (0-17 mm/y) that indicates the buildup of strain in the earth. Then back to our hotel to meet Dhiman and have a final dinner together before an Uber takes me to the airport. It is sad to leave early, but I

A local farmer shows Liz the peanuts he is growing on the char (behind them). Peanuts and lentils are common winter, or rabi, crops on the higher, drier parts of the char. The freshest peanuts we ever ate.

A local farmer shows Liz the peanuts he is growing on the char (behind them). Peanuts and lentils are common winter, or rabi, crops on the higher, drier parts of the char. The freshest peanuts we ever ate.

am needed at home and they can carry on without me for the last few days. They will visit the confluence of the Ganges and Brahmaputra Rivers, and the Padma, as the combined river is called. For me, my critical goals for this trip were accomplished.

Microbial community segmentation with R

Chasing Microbes in Antarctica - Thu, 02/02/2017 - 18:39

In my previous post I discussed our recent paper in ISME J, in which we used community structure and flow cytometry data to predict bacterial production.  The insinuation is that if you know community structure, and have the right measure of physiology, you can make a decent prediction of any microbial ecosystem function.  The challenge is that community structure data, which often has hundreds or thousands of dimensions (taxa, OTUs, etc.), is not easily used in straightforward statistical models.   Our workaround is to reduce the community structure data from many dimensions to a single categorical variable represented by a number.  We call this process segmentation.

You could carry out this dimension reduction with pretty much any clustering algorithm; you’re simply grouping samples with like community structure characteristics on the assumption that like communities will have similar ecosystem functions.  We  use the emergent self organizing map (ESOM), a neural network algorithm, because it allows new data to be classified into an existing ESOM.  For example, imagine that you are collecting a continuous time series of microbial community structure data.  You build an ESOM to segment your first few years of data, subsequent samples can be quickly classified into the existing model.  Thus the taxonomic structure, physiological, and ecological characteristics of the segments are stable over time.  There are other benefits to use an ESOM.  One is that with many samples (far more than we had in our study), the ESOM is capable of resolving patterns that many other clustering techniques cannot.

There are many ways to construct an ESOM.  I haven’t tried a Python-based approach, although I’m keen to explore those methods.  For the ISME J paper I used the Kohonen package in R, which has a nice publication that describes some applications and is otherwise reasonably well documented.  To follow this tutorial you can download our abundance table here.  Much of the inspiration, and some of the code for this analysis, follows the (retail) customer segmentation example given here.

For this tutorial you can download a table of the closest estimated genomes and closest completed genomes (analogous to an abundance table) here.  Assuming you’ve downloaded the data into your working directory, fire up Kohonen and build the ESOM.

## Kohonen needs a numeric matrix edge.norm <- as.matrix(read.csv('community_structure.csv', row.names = 1)) ## Load the library library('kohonen') ## Define a grid. The bigger the better, but you want many fewer units in the grid ## than samples. 1:5 is a good ballpark, here we are minimal. som.grid <- somgrid(xdim = 5, ydim=5, topo="hexagonal") ## Now build the ESOM! It is worth playing with the parameters, though in ## most cases you will want the circular neighborhood and toroidal map structure. som.model.edges <- som(edge.norm,                  grid = som.grid,                  rlen = 100,                  alpha = c(0.05,0.01),                  keep.data = TRUE,                  n.hood = "circular",                  toroidal = T)

Congratulations!  You’ve just constructed your first ESOM.  Pretty easy.  You’ve effectively clustered the samples into the 25 units that define the ESOM.  You can visualize this as such:

plot(som.model.edges, type = 'mapping', pch = 19)

There are the 25 map units, with the toroid split and flattened into 2D.  Each point is a sample (row in the abundance table), positioned in the unit that best reflects its community structure.  I’m not going to go into any depth on the ESOM algorithm, which is quite elegant, but the version implemented in the Kohonen package is based on Euclidean distance.  How well each map unit represents the samples positioned within it is represented by the distance between the map unit and each sample.  This can be visualized with:

plot(som.model.edges, type = 'quality', pch = 19, palette.name = topo.colors)

Units with shorter distances in the plot above are better defined by the samples in those units than units with long distances.  What distance is good enough depends on your data and objectives.

The next piece is trickier because there’s a bit of an art to it.  At this point each sample has been assigned to one of the 25 units in the map.  In theory we could call each map unit a “segment” and stop here.  It’s beneficial however, to do an additional round of clustering on the map units themselves.  Particularly on large maps (which clearly this is not) this will highlight major structural features in the data.  Both k-means and hierarchical clustering work fairly well, anecdotally k-means seems to work better with smaller maps and hierarchical with larger maps, but you should evaluate for your data.  Here we’ll use k-means.  K-means requires that you specify the number of clusters in advance, which is always a fun chicken and egg problem.  To solve it we use the within-clusters sum of squares method:

wss.edges <- (nrow(som.model.edges$codes)-1)*sum(apply(som.model.edges$codes,2,var)) for (i in 2:15) {   wss.edges[i] <- sum(kmeans(som.model.edges$codes, centers=i)$withinss) } plot(wss.edges,      pch = 19,      ylab = 'Within-clusters sum of squares',      xlab = 'K')

Here’s where the art comes in.  Squint at the plot and try to decide the inflection point.  I’d call it 8, but you should experiment with whatever number you pick to see if it makes sense downstream.

We can make another plot of the map showing which map units belong to which clusters:

k <- 8 som.cluster.edges <- kmeans(som.model.edges$codes, centers = k) plot(som.model.edges,      main = '',      type = "property",      property = som.cluster.edges$cluster,      palette.name = topo.colors) add.cluster.boundaries(som.model.edges, som.cluster.edges$cluster)

Remember that the real shape of this map is a toroid and not a square.  The colors represent the final “community segmentation”; the samples belong to map units, and the units belong to clusters.  In our paper we termed these clusters “modes” to highlight the fact that there are real ecological properties associated with them, and that (unlike clusters) they support classification.  To get the mode of each sample we need to index the sample-unit assignments against the unit-cluster assignments.  It’s a little weird until you get your head wrapped around it:

som.cluster.edges$cluster[som.model.edges$unit.classif] [1] 5 7 7 5 2 7 5 3 7 5 2 6 1 1 1 7 5 4 7 7 5 7 7 7 7 7 7 1 4 4 4 4 7 7 7 6 6 6 6 1 1 1 7 5 5 5 1 1 1 5 5 7 7 4 8 7 7 4 7 8 [61] 7 7 7 7 6 5 6 7 7 7 6 4 6 5 4 4 6 2 1 1 1 1 1 4 1 4 4 4

A really important thing to appreciate about these modes is that they are not ordered or continuous.  Mode 4 doesn’t necessarily have more in common with mode 5 say, than with mode 1.  For this reason it is important to treat the modes as factors in any downstream analysis (e.g. in linear modeling).  For our analysis I had a dataframe with bacterial production, chlorophyll concentration, and bacterial abundance, and predicted genomic parameters from paprica.  By saving the mode data as a new variable in the dataframe, and converting the dataframe to a zoo timeseries, it was possible to visualize the occurrence of modes, model the data, and test the pattern of modes for evidence of succession.  Happy segmenting!

 

Always more

Side trip to Hiron Point, Sundarbans

Geohazards in Bangladesh - Tue, 01/31/2017 - 10:32
Our group returns on the country boat, the M.V. Sundari, from their morning fieldwork.

Our group returns on the country boat, the M.V. Sundari, from their morning fieldwork.

My critical equipment repairs were now done. Chris and Dan still had several days of work in the area, but Humayun and I were interested in traveling to Hiron Point near the coast in the Sundarban Mangrove Forest. We want to take advantage of being so close to We hoped we could do it in a day, with the tides and broad open channel to the south, it would take two, too much for Chris to spare. We worked out that Humayun, Liz and I could take Bachchu’s smaller boat, the M.B. Mowali. Mowali are the honey collectors in the Sundarban and Bawali are the wood cutters.

Chris measuring the reflectance spectra of the ground while some local woman look on.

Chris measuring the reflectance spectra of the ground while some local woman look on.

Before we leave, we have one day with Chris and the others. After, Matt and Tanjil, our forest guide from 2015 who stayed with us for a day, departed, I went out with them to Polders 32 and 31 for their afternoon run. They are making soil salinity measurements to see if it is possible to determine soil salinity from satellite imagery. Saline soils are a large problem in this part of Bangladesh. We took the country boat to shore and scouted for the appropriate place. At each one Chris and Dan laid out a grid of probes to measure salinity and moisture

Dan measuring the salinity of the soil.

Dan measuring the salinity of the soil.

content. Kingston and Zahan did similar measurements at the surface and at the root level. As always, we attracted a crowd of onlookers curious as to what these foreigners were doing.

Later, after dinner, the M.B. Mowali arrived and our group split once again. We traveled to the edge of the Sundarbans that night, to pick up our guide and our armed guard for the tigers. The Mowali is much smaller. I

Chris providing a detailed explanation of what he is doing in English to people who only speak Bangla.

Chris providing a detailed explanation of what he is doing in English to people who only speak Bangla.

haven’t seen her since she was renovated. Now there is one cabin, which Liz got, and a larger room for Humayun, myself and our guide. In the early morning we headed south. Once the fog lifted and we entered smaller channels, we started seeing deer and monkeys on the banks and in the forest. We stopped in a small side channel and had lunch before crossing the over 10-km wide estuary in our speed boat, a 40-min ride. I could see that a lot on fresh land had grown at the mouth of the channel with the forest station and our GPS since the

Liz gets photographed with two young girls. Blonde women doing field work is not that common here.

Liz gets photographed with two young girls. Blonde women doing field work are not that common here.

last time I was here, two years ago.

We brought along lots of extra equipment in case anything had broken down. Humayun and I worked on downloading the GPS data while Liz and the guide went for a walk and climbed the observation tower. They got to see deer, wild boar and a monitor lizard, while Humayun and I sat in a dark room. As usual, we struggled to remember how to connect and download data exacerbated my unfamiliarity with the Windows OS on the PC we were using.

The M.B. Mowali, our home for the next two days for the run to Hiron Point and back.

The M.B. Mowali, our home for the next two days for the run to Hiron Point and back.

Eventually, we got it right and were happy to see that the system was working perfectly, data files for every day since I last visited. Obviously, because we had brought all the equipment along, we didn’t need it. We downloaded all the data and then changed the SIM card in the modem. We had set up cellular communications when we installed the station, but the signal was too weak to every collect any data. Now there is a good signal here from a different cell phone company. When we get back we will have UNAVCO check to see if it works. In any case, we now have enough data to measure the subsidence here.  The sinking of the land exacerbates the impact of rising sea level. Only the vast sediment supply of the delta counters it to maintain the land. And that is at risk from human intervention.

Humayun having tea in the morning on the Mowali.

Humayun having tea in the morning on the Mowali.

We had tea and cookies with the forest ranger and then headed back before low tide trapped us in the channel. As things went well, we stopped on the newly emerged char land and Liz and I walked around examining the sediments, surprisingly sandy for a tidal estuary. Back in the speed boat, we crossed the broad channel and then paused to watch the sunset on the water. Once on the Mowali, we sailed to where we would spend the night in the Mangrove Forest and now I got to see deer and boar on

Sundarban Mangrove Forest at low tide.

Sundarban Mangrove Forest at low tide.

the way before darkness descended. There was even a herd of 9 or 10 just across from where we rejoined the Mowali.

In the morning, we started heading north. Because it was very foggy, we stayed in smaller channels for a few hours before entering the main channel of the Pussur River. I spent the early morning before breakfast watching the forest go by and spotted a few more

One of the many chital, or spotted deer, we saw along the way.

One of the many chital, or spotted deer, we saw along the way.

deer. By noon we were out of the Sundarbans and ready to drop off our guard. I actually hadn’t seen him for the entire trip. We continued past the Rampal power plant. This a coal-fired plant being built less than 20 km from the Sundarbans. Most of the coal for it will likely be transported up the Pussur River through the Sundarbans. It is the subject of a lot of protests, including the hartal we had last week, but they are not likely to stop it from being built. A short time later we met up with the Bawali and

Getting into the speedboat to sail across the channel to Hiron Point.

moved back across. Then, work here being done, both ships sailed up to Khulna for the night. Tomorrow morning we disembark for the next phase of the trip.

Having tea with the forest ranger after completing our work.

Al fresco dinner on the Mowali.

Sunset over the Sundarbans and one of the many ships plying the waterway.

Equipment repairs in SW Bangladesh

Geohazards in Bangladesh - Tue, 01/31/2017 - 04:53
Having a breakfast of an omelet and paratha while waiting at the ferry ghat (dock) at Mawa.

Having a breakfast of an omelet and paratha while waiting at the ferry ghat (dock) at Mawa.

After a night in Dhaka, our group temporarily split up. Chris and Dan headed to Khulna in the SW at 4 am to avoid the hartal (general strike) that was planned for 6am-2pm. Liz and I stayed in Dhaka for a day. I spent it mostly editing material for a new project. The next day Liz, Humayun, my partner from Dhaka University, and I followed the others to Khulna, crossing the Padma (combined Ganges and Brahmaputra) River by ferry at Mawa. After waiting an hour, Humayun used a connection from a former student to get us on the next

Mofizur removing the antenna and antenna mount from the listing GPS pillar while I watch from the side.

Mofizur removing the antenna and antenna mount from the listing GPS pillar while I watch from the side.

ferry, a fast one. It is impressive how much the river has silted up since the last time I crossed here. Another few hours and we arrived at our compaction meter site SE of Khulna. We picked up one of the 4 sons from the family that takes care of the site. Mofizur, the second son, now a student at Chittagong University, is returning home for the first time in 6 months. Making the weekly measurements has been passed along from the oldest to youngest sons. It made for a great welcoming by the Islam family when we arrived mid-afternoon.

Me sighting through the optical level to get the relative elevations of the 6 optical fiber compaction wells.

Me sighting through the optical level to get the relative elevations of the 6 optical fiber compaction wells.

The last time I was here, the river adjacent to the site was being dredge and widened. It had gone from 200 m wide to just a few and was now too small for boats except at high tide. The widening cut into the bank that held our instruments. While the engineer tried to leave us enough room, it clearly didn’t work. The pillar that holds the GPS antenna is tilting badly towards the stream. They have secured it with ropes to keep it from completely falling over. We got hold of a ladder and removed the unusable antenna. Mofizur climbed up, afraid that I weighed too much for the fragile system. Next, Humayun and I surveyed the monuments for the compaction meter wells. We had to dig out the sediments

Liz measures and describing the sediments that have accumulated over the base of the wells since they were installed in 2011.

Liz measuring and describing the sediments that have accumulated over the base of the wells since they were installed in 2011.

covering the base. Liz measured the thicknesses, which were 4-7 inches. We could clearly see the finely layered sediments deposited from before the river was enlarged to the thick muds that accumulated afterwards. The sedimentation rate had clearly increased due to the river widening. The survey will give us the relative heights of the wells. When we get back we will compare it to earlier measurement to see if the wells have shifted, too. Without the GPS we cannot determine the absolute elevations. Our last task was to measure the lengths of the optical fibers in the wells. We brought along a new laptop to work with the electronic distance meter (EDM), but we found the recharger was still in Dhaka. We had forgotten it. With a dead battery and no way to recharge it, the measurements will have to wait until Humayun can send the recharger.

LunchKHLC

Mr. Islam serves some fish to Humayun, Liz (taking photo) and myself in their courtyard as part of the feast that they prepared for us.

While we were there, we were served lunch, a huge banquet. Three finds of fish, chicken, rice, vegetables, two desserts. The three of us sat a table outside in the yard, while the family plied us with the delicious home-cooked Bangladeshi food. The more important the guests, the more food and were were suitably overwhelmed. And since it was after 3 pm, we were famished and did our best make a dent in it. Since the GPS is no longer usable, we left them the battery and solar panel that was powering it, doubling their electricity supply. Before we installed the

The M.B. Bawali, our home for the next five nights and four days. Everything is great except for the cold water showers.

The M.B. Bawali, our home for the next five nights and four days. Everything is great except for the cold water showers.

equipment in 2011, they did not have electricity at all. After some heartfelt farewells, we headed to Khulna to meet up with Chris, Dan and Matt Winters, my TA from the class I taught in 2015. Fluent in Bangla, he has been working with Chris on field observations for his Master’s thesis at Columbia. He and some of his assistants will join us for a few days. The three of them had a dinner meeting, so my group headed to the M.B. Bawali, our home for the next 4 days. Smaller than the M.B. Kokilmoni, it is a perfect size for our group.

Humayun inspecting our equipment on the roof of a school on Polder 32. The tower is a meteorological station and our GPS antenna is on the back wall.

Humayun inspecting our equipment on the roof of a school on Polder 32. The tower is a meteorological station and our GPS antenna is on the back wall.

The next morning, we headed for Polder 32, the embanked island we have been studying. Humayun and I will visit the GPS station we set up there in 2012. It has a cellular modem so data can be downloaded remotely every day, but stopped working in November. It seemed that the receiver was not recording satellites, so we brought along replacement antennas, cables and lightning protectors. Another GPS station had a similar problem and there the cable had to be replaced. When we arrived at the school, we found the receiver was tracking satellites. We didn’t

Humayun stripping the end off the coaxial cable that we used as a grounding wire.

Humayun stripping the end off the coaxial cable that we used as a grounding wire.

have to track down a break in the system. But why wasn’t it recording data. The best we could ascertain was the modem had hung up; rebooting it fixed the problem. It was working, but I don’t understand what happened enough to be sure it won’t happen again. Hopefully, now that it is working, the engineers at UNAVCO can log in an work on it. When we doublechecked everything, we found that the grounding wire was missing. This is unsafe. If there is a lightning strike, the lightning protector blows the connection

A stopped to pay our respects to the small shrine in the schoolyard to Saraswati, the Hindu goddess of knowledge and education.

A stopped to pay our respects to the small shrine in the schoolyard to Saraswati, the Hindu goddess of knowledge and education.

to the equipment inside and shunts the electricity down the grounding wire. We cannot put a school full of children at risk. The only wires we had were the coaxial antenna cables. We stripped the ends off a partial cable and wired it between the cut ends on the roof and near the ground. We made a visit to the Hindu goddess of education and headed back to the ship having done all the repairs we could, and satisfied that the school was safe.

Heading back to the Bawali on the country boat after a successful day on the Polder (embanked island).

Heading back to the Bawali on the country boat after a successful day on the Polder (embanked island).

Back to Bangladesh to date earthquakes and more

Geohazards in Bangladesh - Fri, 01/27/2017 - 01:06

 

 

 

 

 

 

GroupWPolice

Our group, Dan, Liz, Chris and myself, posing with our police escort at the Amtali Resort

TreesFog

Trees peaking out from the fog in the early morning on the Rashidpur anticline. The anticlines are covered by forests and tea gardens (plantations)

It has been over a year since I was in Bangladesh after coming here twice a year for the previous five years. This will be a packed trip doing many different things, collecting samples, fixing equipment, visiting rivers and hopefully meeting with the public and government officials about the earthquake hazard. My paper last year showed that there is the potential for an earthquake of at least Mw8.2 here, an area with ~140,000,000 people. However, with no knowledge of when the last megaquake was or how often that comes, we don’t know when it might occur, in years or centuries. The article received widespread coverage in the press and caused a panic in the region. Now I feel an obligation to help steer things towards better preparation and building construction.
Our first task is related to a past earthquake. The last time we were here, Céline and I collected samples from an abandoned river that shifted ~20 km to the west. We think the shift was caused by an earthquake, but we don’t know if it

View of the banks of the Kushiara River in NE Bangladesh where we are looking to sample

View of the banks of the Kushiara River in NE Bangladesh where we are looking to sample

was a moderate M7 or a large M8.5. Either one could be pretty destructive to people living on the soft delta sediments. We now have dates for the samples. The 3 ages we got for the last sediments deposited before the shift, or avulsion, were 3800, 3800 and 3600 years ago. The method we used was OSL, optically stimulated luminescence, dating. It measures electrons trapped in quartz crystals. The electrons are so weakly trapped, that sunlight can set them free. Thus we date how long it has been since the sediment has seen the sun. The one

Chris on the boat taking a photo with the highway bridge over the Kushiara River in the background

Chris on the boat taking a photo with the highway bridge over the Kushiara River in the background

hitch is the possibility that when the sediment was transported down the river, not all the electrons were freed. This is known as incomplete bleaching and would result in too old an age. Our solution is to collect samples from the modern river to see if there is any residual age that would shift our estimate for the earthquake.
Four of us arrived together, Chris Small and Dan Sousa, who use remote sensing to study the changes in the delta: rivers, coastline, vegetation, Liz Chamberlain, a graduate student specializing in OSL and

A group of girls excited by the strange visitors to their village asked me to take their picture.

A group of girls excited by the strange visitors to their village asked me to take their picture.

myself. On arrival, we were met by Saddam Hossain and headed NE towards the Kushiara and Meghna Rivers. We stayed the first night in a “resort” in the folded hills of Sylhet where tea is grown. As a result of the attack on the Holey Artisan Bakery last year, the country is taking precautions. When we entered the Sylhet Division, we were met with a police escort. They stayed with us all through the nigh and their relief through the next day until we left the Division on our way to Dhaka. This is a new experience for me. It did have the

A set of colorful houses line the bank of the broad Meghna River. We continue south to find sampling sites.

A set of colorful houses line the bank of the broad Meghna River. We continue south to find sampling sites.

advantage of being able to drive without stopping for tolls and the police used their siren to help with passing cars. Still we only got to our room around midnight, a long drive after two long flights.
Our first stop was the Kushiara River, a bit upstream of the river avulsion, but above the lake that forms every summer during the monsoon. My concern is that the lake decants the sands so the sediments upstream and downstream of the lake are different. Thus we will sample both. We drove to the small town

Chris, Dan and Liz on the country boat scanning for good sampling sites.

Chris, Dan and Liz on the country boat scanning for good sampling sites.

of Sherpur and the police facilitated renting a small boat. Sailing along the river, we spotted a good spot where the bank was eroding and we could easily collect samples. This was as simple as cleaning a spot and then hammering an iron tube into the deposits. The main precaution is that the sample must not be exposed to light or it will lose all its electrons. We then decided to collect a sample from the river bottom from the boat. This proved more challenging and it took several tries to get the boat into the

I am hammering our iron pipe into the eroding cut bank to collect a sample without exposing the center of it to light so it can be use for OSL dating.

I am hammering our iron pipe into the eroding cut bank to collect a sample without exposing the center of it to light so it can be use for OSL dating.

correct depth of water and collect a sample with the sampler at the end of a several meter long augur. We found we had to work fast as the boat would drift in the strong current. By noon, we had our two samples and headed to the Meghna River on the way back towards Dhaka.
The much larger and more industrialized Meghna River was a bit more challenging. We need an area undisturbed by people. We rented a country boat at the ghat (dock) near the Bhairab Bazaar Bridge over the river and sailed off. After almost an hour on the river, we found it. The nose of a large island and an eroding cut bank nearby. The point of the island was protected by sand bars, so Liz and I got out and sampled the bottom with the augur. Not movement to worry about when the boat is aground. Then we headed to the cut back exposure and took our 4th and final sample. The set of samples is different then I envisioned, but with Liz’s guidance, they will fit the bill well. By the time we got back to the ghat it was dusk. Time for a slow and traffic filled drive to Dhaka. We got in just in time to rush off to our favorite restaurant for a celebratory dinner at our favorite restaurant before it closed. This trip is off to a great start.

Thanks, Station Obama: Scientists immortalize the former president in a way never seen before - Salon

Featured News - Sat, 01/21/2017 - 12:00
Quotes Lamont scientist Hugh Ducklow on Antarctic research location.

New paper published in ISME Journal

Chasing Microbes in Antarctica - Fri, 01/20/2017 - 19:36

I’m happy to report that a paper I wrote during my postdoc at the Lamont-Doherty Earth Observatory was published online today in the ISME Journal.  The paper, Bacterial community segmentation facilitates the prediction of ecosystem function along the coast of the western Antarctic Peninsula, uses a novel technique to “segment” the microbial community present in many different samples into a few groups (“modes”) that have specific functional, ecological, and genomic attributes.  The inspiration for this came when I stumbled across this blog entry on an approach used in marketing analytics.  Imagine that a retailer has a large pool of customers that it would like to pester with ads tailored to purchasing habits.  It’s too cumbersome to develop an individualized ad based on each customer’s habits, and it isn’t clear what combination of purchasing-habit parameters accurately describe meaningful customer groups.  Machine learning techniques, in this case emergent self-organizing maps (ESOMs), can be used to sort the customers in a way that optimizes their similarity and limits the risk of overtraining the model (including parameters that don’t improve the model).

In a 2D representation of an ESOM, the customers most like one another will be organized in geographically coherent regions of the map.  Hierarchical or k-means clustering can be superimposed on the map to clarify the boundaries between these regions, which in this case might represent customers that will respond similarly to a targeted ad.  But what’s really cool about this whole approach is that, unlike with NMDS or PCA or other multivariate techniques based on ordination, new customers can be efficiently classified into the existing groups.  There’s no need to rebuild the model unless a new type of customer comes along, and it is easy to identify when this occurs.

Back to microbial ecology.  Imagine that you have a lot of samples (in our case a five year time series), and that you’ve described community structure for these samples with 16S rRNA gene amplicon sequencing.  For each sample you have a table of OTUs, or in our case closest completed genomes and closest estimated genomes (CCGs and CEGs) determined with paprica.  You know that variations in community structure have a big impact on an ecosystem function (e.g. respiration, or nitrogen fixation), but how to test the correlation?  There are statistical methods in ecology that get at this, but they are often difficult to interpret.  What if community structure could be represented as a simple value suitable for regression models?

Enter microbial community segmentation.  Following the customer segmentation approach described above, the samples can be segmented into modes based on community structure with an Emergent Self Organizing Map and k-means clustering.  Here’s what this looks like in practice:

From Bowman et al. 2016.  Segmentation of samples based on bacterial community structure.  C-I show the relative abundance of CEGs and CCGs in each map unit.  This value was determined iteratively while the map was trained, and reflects the values for samples located in each unit (B).

This segmentation reduces the data for each sample from many dimensions (the number of CCG and CEG present in each samples) to 1.  This remaining dimension is a categorical variable with real ecological meaning that can be used in linear models.  For example, each mode has certain genomic characteristics:

From Bowman et al. 2016.  Genomic characteristics of modes (a and b), and metabolic pathways associated with taxa that account for most of the variations in composition between modes (d).

In panel a above we see that samples belonging to modes 5 and 7 (dominated by the CEG Rhodobacteraceae and CCG Dokdonia MED134, see Fig. 2 above) have the greatest average number of 16S rRNA gene copies.  Because this is a characteristic of fast growing, copiotrophic bacteria, we might also associate these modes with high levels of bacterial production.

Because the modes are categorical variables we can insert them right into linear models to predict ecosystem functions, such as bacterial production.  Combined with bacterial abundance and a measure of high vs. low nucleic acid bacteria, mode accounted for 76 % of the variance in bacterial production for our samples.  That’s a strong correlation for environmental data.  What this means in practice is; if you know the mode, and you have some flow cytometry data, you can make a pretty good estimate of carbon assimilation by the bacterial community.

For more on what you can do with modes (such as testing for community succession) check out the article!  I’ll post a tutorial on how to segment microbial community structure data into modes using R in a separate post.  It’s easier than you think…

Earth's Temperature Rises, Again - WNYC

Featured News - Thu, 01/19/2017 - 12:00
Jason Smerdon, a climate scientist with the Lamont-Doherty Earth Observatory at Columbia University, said the record temperature rise — for the third year in a row — is confirmation the earth is warming, and humans are causing it.

Earth Sets a Temperature Record for the Third Straight Year - New York Times

Featured News - Wed, 01/18/2017 - 12:00
Quotes Richard Seager, a climate scientist at Lamont-Doherty Earth Observatory.

Green Sahara's ancient rainfall regime revealed - Phys.org

Featured News - Wed, 01/18/2017 - 12:00
Cites Peter deMenocal of Lamont-Doherty Earth Observatory.

paprica v0.4.0

Chasing Microbes in Antarctica - Sun, 01/08/2017 - 15:04

I’m happy to announce the release of paprica v0.4.0.  This release adds a number of new features to our pipeline for evaluating microbial community and metabolic structure.  These include:

  • NCBI taxonomy information for each point of placement on the reference tree, including internal nodes.
  • Inclusion of the domain Eukarya.  This was a bit tricky and requires some further explanation.

The distribution of metabolic pathways, predicted during the creation of the paprica Eukarya database, across transcriptomes in the MMETSP.

Eukaryotic genomes are a totally different beast than their archaeal and bacterial counterparts.  First and foremost they are massive.  Because of these there aren’t very many completed eukaryotic genomes out there, particularly for singled celled eukaryotes.  While a single investigator can now sequence, assemble, and annotate a bacterial or archaeal genome in very little time, eukaryotic genomes still require major efforts by consortia and lots of $$.

One way to get around this scale problem is to focus on eukaryotic transcriptomes instead of genomes.  Because much of the eukaryotic genome is noncoding this greatly reduces sequencing volume.  Since there is no such thing as a contiguous transcriptome, this approach also implies that no assembly (beyond open reading frames) will be attempted.  The Moore Foundation-funded Marine Microbial Eukaryotic Transcriptome Sequencing Project (MMETSP) was an initial effort to use this approach to address the problem of unknown eukaryotic genetic diversity.  The MMETSP sequenced transcriptomes from several hundred different strains.  The taxonomic breadth of the strains sequenced is pretty good, even if (predictably) the taxonomic resolution is not.  Thus, as for archaea, the phylogenetic tree and metabolic inferences should be treated with caution.  For eukaryotes there are the additional caveats that 1) not all genes coded in a genome will be represented in the transcriptome 2) the database contains only strains from the marine environment and 3) eukaryotic 18S trees are kind of messy.  Considerable effort went into making a decent tree, but you’ve been warned.

Because the underlying data is in a different format, not all genome parameters are calculated for the eukaryotes.  18S gene copy number is not determined (and thus community and metabolic structure are not normalized), the phi parameter, GC content, etc. are also not calculated.  However, eukaryotic community structure is evaluated and metabolic structure inferred in the same way as for the domains bacteria and archaea:

./paprica-run.sh test.eukarya eukarya

As always you can install paprica v0.4.0 by following the instructions here, or you can use the virtual box or Amazon Web Service machine instance.

Lamont-Doherty Professor to Head Science Organization - The Journal News

Featured News - Fri, 01/06/2017 - 13:00
Video interview with Robin Bell who was recently elected president of the American Geophysical Union.

More Frequent Glacial Quakes on Greenland Signal Ice Retreat - Eos

Featured News - Thu, 01/05/2017 - 12:00
Lamont graduate student Kira Olsen and Meredith Nettles report that glacial earthquakes in Greenland, a measure of ice loss from the leading edges of glaciers, increased in frequency by a factor of four over the period 1992-2013.

Conditions That Form More Hurricanes Also Protect U.S., Study Finds - New York Times

Featured News - Wed, 01/04/2017 - 12:00
Suzana Camargo comments on a report that during times of frequent Atlantic hurricanes, climate conditions tend to weaken storms that approach the U.S. east coast, whereas during times of less frequent tropical storms, major hurricanes approaching the U.S. are likely to intensify before making landfall.

2016 to Break Heat Records - The Mercury News

Featured News - Sun, 01/01/2017 - 09:26
Scientists are expected to announce that 2016 was the hottest year on Earth since record-keeping began in 1880 ​— news that will test national, state and economic leadership on climate change. “The climate system gives not a hoot about politicians in Washington denying the reality of human-driven climate change — but it does respond to decisions on energy, fuels and the environment those politicians make,” Lamont's Richard Seager said.

With Enough Evidence, Even Skepticism Will Thaw - Washington Post

Featured News - Fri, 12/30/2016 - 12:00
Greenland's Petermann Ice Shelf has lost huge ice islands since 2010. The question is no longer whether it is changing — it’s how fast it could give up still more ice to the seas. Chris Mooney talks with scientists, including Lamont's Marco Tedesco, about what they're seeing.

The R/V Langseth Is Helping Uncover Clues to Chile's Offshore Earthquakes - El Mercurio (in Spanish)

Featured News - Mon, 12/26/2016 - 09:36
The Lamont-operated R/V Marcus G. Langseth is in Chile with teams of scientists studying the region's offshore seismicity. El Mercurio wrote about the work as a magnitude 7.7 earthquake struck off the Chilean coast. The article is in Spanish.

Nukes or Quakes? Scientists Decipher Tiny Tremors in North Korea - Christian Science Monitor

Featured News - Tue, 12/20/2016 - 18:11
Researchers including Lamont's Paul Richards say a 2010 event previously thought to be a small nuclear test in North Korea was actually just a small earthquake – a finding that could have implications for monitoring the regime's nuclear tests.

North Korea Nuclear Tests: 2010 ‘Explosion’ Was Just An Earthquake, Study Finds - International Business Times

Featured News - Tue, 12/20/2016 - 09:19
A new report by seismologists from Columbia University's Lamont-Doherty Earth Observatory concluded that the tremors were much more like that of an earthquake than an explosion.

How Bias Undermines Women's Access to Scientific Careers - Science Friday

Featured News - Fri, 12/16/2016 - 12:00
What will it take to bring true equity to research labs? Science Friday talks with Lamont's Kuheli Dutt and others (segment begins at 17:40).

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