News aggregator

How Much Has Global Warming Worsened California's Drought? We Now Have a Number - The Conversation

Featured News - Thu, 08/20/2015 - 12:00
In an essay for The Conversation, Lamont-Doherty's Park Williams describes his new study on the California drought.

Climate Change is Deepening California's Drought Crisis by as Much as a Quarter - International Business Times

Featured News - Thu, 08/20/2015 - 12:00
Lamont-Doherty's Park Williams discusses the first study to quantify just how much global warming is exacerbating California's drought.

The Climate Change "Bully" in California's Drought - Climate Central

Featured News - Thu, 08/20/2015 - 12:00
Lamont-Doherty's Park Williams discusses his study on the California drought. "From a method standpoint, it’s a big advancement," he says. "It’s the first time I know of that data has been parsed apart this way for any drought on the planet."

Climate Change Is Intensifying the California Drought - The Hill

Featured News - Thu, 08/20/2015 - 12:00
Lamont-Doherty's Park Williams explains how global warming has worsened the California drought, now entering its fourth year.

Scientists Strengthen Link Between Climate Change and Drought - High Country News

Featured News - Thu, 08/20/2015 - 12:00
In a new study led by Park Williams, researchers found that unusually hot temperatures attributable to anthropogenic climate change intensified the California drought.

Scientists Say Global Warming Has Made California Drought Worse - Washington Post

Featured News - Thu, 08/20/2015 - 12:00
Lamont's Park Williams explains that while natural weather patterns that push away atmospheric moisture that carries rain are normal for California, warming adds to the resulting dryness and heat. A small amount of moisture stored in plants and the soil evaporates into the drier atmosphere.

Park Williams on How Global Warming has Worsened the California Drought - Democracy Now

Featured News - Thu, 08/20/2015 - 12:00
Lamont-Doherty's Park Williams talks with Democracy Now about a new study gauging the role of a warming climate in worsening the California drought.

California Can Blame Climate Change for Fifth of Its Drought - Bloomberg

Featured News - Thu, 08/20/2015 - 09:00
California can blame about a fifth of the state’s record drought on climate change, says a new study led by Lamont's Park Williams.

Scientists Figure Out Just How Much of California's Drought Can Be Blamed on Climate Change -

Featured News - Thu, 08/20/2015 - 09:00
Climate change has made the California drought measurably worse - likely between 15 and 20 percent, says Lamont's Park Williams.

California Drought: Climate Change Plays a Role, Study says. But How Big? - Los Angeles Times

Featured News - Thu, 08/20/2015 - 09:00
A group of researchers led by Lamont's Park Williams have estimated the extent to which climate change has worsened the California drought: as much as 27 percent.

Global Warming Worsened the California Drought, Study Confirms - Xinhua

Featured News - Thu, 08/20/2015 - 07:00
Human-caused global warming has measurably worsened California's crippling drought, according to a new study led by Lamont's Park Williams.

How Climate Change Robs California of Scant Water Supplies - Christian Science Monitor

Featured News - Thu, 08/20/2015 - 07:00
A new study led by Lamont's Park Williams is the first to put numbers to the idea that increasing heat drives moisture from the ground, intensifying drought conditions in places like California.

Global Warming Has Worsened California's Drought - USA Today

Featured News - Thu, 08/20/2015 - 07:00
Man-made global warming has made California's historic drought 15% to 20% worse than it would have been and will likely make future droughts even worse, a new study led by Lamont's Park Williams says.

Diamonds Form from Ancient, Underground Seawater, Study Suggests - CBC

Featured News - Wed, 08/19/2015 - 12:00
Microscopic, ugly diamonds from the Northwest Territories are illuminating how diamonds are made. A new study involving Lamont's Yakovv Weiss explains.

How Diamond Formation Depends on the Ocean - Hakai Magazine

Featured News - Wed, 08/19/2015 - 12:00
Lamont geochemist Yaakov Weiss shows in a new study how diamonds from Canada’s Northwest Territories owe their existence in part to ancient salt water.

Tracing the Arctic

TRACES of Change in the Arctic - Wed, 08/19/2015 - 00:07
Leaving Dutch Harbor

The U.S. Coast Guard cutter Healy leaving Dutch Harbor, Alaska, and heading to the high Arctic for the GEOTRACES research cruise. It doesn’t take long to move from a landscape of steep carved cliffs to one of endless waves on an Arctic passage. Photo: T. Kenna

Dutch Harbor Alaska is located on that long spit of land that forms the Aleutian Islands of Western Alaska. Research vessels launch from this location and head northeast into the Bering Sea on their way to the Bering Strait, the gateway to the Arctic.

map of Dutch Harbor

Dutch Harbor, Alaska (from

Our research cruise is part of the international Arctic GEOTRACES program, which this summer has three separate ships in the Arctic Ocean. The Canadian vessel headed north in early July, and the German vessel will follow a week behind the Healy. Each will be following a different transect in the Arctic Ocean to collect samples. The U.S. vessel has 51 scientists on board, each with a specific sampling program. We will focus our time in the western Arctic, entering at the Chukchi Sea. (Follow the expedition here.)

What is GEOTRACES studying? The program goal is to improve our understanding of ocean chemistry through sampling different trace elements in the ocean waters. Trace elements can be an asset or a liability in the marine system, providing either essential nutrients for biologic productivity, or toxic inputs to a rapidly warming system. This part of the larger program is focused on the Arctic Ocean, the smallest and shallowest of the world’s oceans and the most under siege from climate change. Results from this cruise will contribute to our understanding of the processes at work in the Arctic Ocean, providing both a baseline of contaminants for future comparisons as well as insights into what might be in store for our future.

The land surrounding the Arctic Ocean is like a set of cradling arms, holding the ocean and the sea ice in a circular grasp. Within that cradle is a unique mix of waters, including freshwater from melting glacial ice and large rivers, and a salty mix of relatively warm Atlantic water and cooler Pacific water. Our first sample station lasts over 24 hours and focuses on characterizing the chemistry of the water flowing into the Arctic from the Pacific Ocean. This is critical for locking down  the fluxes and totals of numerous elements in the Arctic.

Map of sea ice

Daily map from the ship showing sea ice cover. Yellow is the marginal ice, and the red is heavy ice. The location of the Healy is visible at the lower edge of the photo at the edge of the red dot.

In the past the “embrace” of the Arctic land has served as a barrier, holding in the sea ice, which is an important feature in the Arctic ecosystem. In 2007, however,  winds drove large blocks of sea ice down the Fram Stait and out of Arctic. In recent years the Arctic sea ice has suffered additional decline, focusing new attention on the resource potential of this ocean.

Unexpectedly this year, the sea ice is projected to be thick along the proposed cruise track, thick enough that it might cause the ship to adjust her sampling plan.


Walrus resting on Arctic sea ice. Photo: T. Kenna

The walrus in the above image are taking advantage of the Arctic sea ice. Walrus use the ice to haul out of the water, rest and float to new locations for foraging. Walrus food of preference is mollusks, and they need a lot of them to keep themselves satisfied, eating up to 5,000 a day, using the sea ice as a diving platform. As the ship moves further from shore, we will lose their company.

Margie Turrin is blogging for Tim Kenna, who is reporting from the field as part of the Arctic GEOTRACES, a National Science Foundation-funded project.

For more on the GEOTRACES program, visit the website here.

Introducing PAPRICA

Chasing Microbes in Antarctica - Tue, 08/18/2015 - 14:00

I’m very excited to report that our latest paper – Microbial communities can be described by metabolic structure: A general framework and application to a seasonally variable, depth-stratified microbial community from the coastal West Antarctic Peninsula was just published in the journal PLoS one.  The paper builds on two very distinct bodies of work; a growing literature on microbial community structure and function along the climatically sensitive West Antarctic Peninsula, and a family of new techniques to predict community metabolic function from 16S rRNA gene libraries, which we are calling metabolic inference.

The motivation for metabolic inference is in the large amount of time that it takes to manually curate a likely set of functions for even a small collection of 16S rRNA genes.  In today’s world, where most analyses of microbial community structure consist of many thousand of reads representing hundreds of taxa, it is simply impossible to dig through the literature on each strain to see what metabolic role each is likely to be playing.  Ideally a researcher would use metagenomics or metatranscriptomics to get at this information directly, but it is not advisable or desirable in most cases to sequence hundreds of metagenomes or metatranscriptomes (necessary for the kind of temporal or spatial resolution many of us want these days).  Metabolic inference provides a convenient alternative.

A quick Google Scholar survey of the number of studies since 2005 that have used high throughput 16S rRNA gene sequencing.

A quick Google Scholar survey of the number of studies since 2005 that have used high throughput 16S rRNA gene sequencing.  Over the last ten years we’ve collected an astonishing amount of sequence data from a diverse array of environments, however, much of this data has been from taxonomic marker genes like the 16S rRNA gene, leaving microbial community function largely unknown.  PAPRICA and other methods that try to infer microbial functional potential from 16S rRNA gene data can help bridge this gap.

The basic concept behind all metabolic inference techniques (e.g. PICRUSt, tax4fun, PAPRICA) is hidden state prediction (HSP) (you can find a nice paper on HSP here).  In 16S rRNA gene analysis metabolic potential is a hidden state.  The metabolic inference techniques propose different ways to predict this hidden state based on the information available.

Our small contribution to this effort was to develop a method (PAPRICA – PAthway PRediction by phylogenetIC plAcement) that uses phylogenetic placement to conduct the metabolic inference instead of an OTU (operational taxonomic unit) based approach.  Our approach provides a more intuitive connection between the 16S rRNA analysis and the HSP (or at least it does in my mind) and can increase the accuracy of the inference for taxa that have a lot of sequenced genomes.

Most analysis of large 16S rRNA datasets rely on an OTU based approach.  In a typical OTU analysis an investigator aligns 16S rRNA reads, constructs a distance matrix of the alignments, and clusters the reads at some predetermined distance.  By tradition the default distance has become a dissimilarity of 0.03.  This approach has some advantages.  By clustering reads into discrete units it is easy to quantify the presence or absence of different OTUs, and it allows microbial ecologists to avoid problems with defining prokaryotic species (which defy most of the criteria used to define species in more complex organisms).  To conduct a metabolic inference on an OTU based analyses it is possible to simply reconstruct the likely metabolism for a predefined set of OTUs based on the OTU assignments of published genomes.  This works great, but it limits the resolution of the inference to the selected OTU definition (i.e. 0.03).  For some taxa, such as Escherichia coli (and plenty of more interesting environmental bugs), there are many sequenced genomes that have very similar 16S rRNA gene sequences.  PAPRICA provides a way to improve the resolution of the metabolic inference for these taxa.

Our approach was to build a phylogenetic tree of the 16S rRNA genes from each completed genome.  For each internal node on the reference tree we determine a “consensus genome”, defined as all genomes shared by all members of the clade originating from the node, and predict the metabolic pathways present in the consensus and complete genomes using Pathway-Tools.  To conduct the actual analysis we use pplacer to place our query reads on the reference tree and assign the metabolic pathways for each point of placement to the query reads.  One advantage to this approach is that the resolution changes depending on genomes sequence coverage of the reference tree.  For families, genera, and even species for which lots of genomes have been sequenced resolution is high.  For regions of the tree where there are not many sequenced genomes resolution is poor, however, the method will give you the best of what’s available.


Figure from Bowman and Ducklow, 2015.  PAPRICA includes a confidence scoring metric that takes into account the relative plasticity of different genomes.  In this figure each vertical line is a genome (representing a numbered terminal node on our reference tree), with the height and color of the vertical line giving its relative plasticity (which we refer to as the parameter phi).  The genomes identified with Roman numerals are all known to be exceptionally modified, which is a nice validation of the phi parameter.  Many of these are obligate symbionts.  I) Nanoarcheum equitans II) the Mycobacteria III) a butyrate producing bacterium within the Clostridium IV) Candidatus Hodgkinia circadicola V) the Mycoplasma VI) Sulcia muelleri VII) Portiera aleyrodidanum VIII) Buchnera aphidicola, IX) the Oxalobacteraceae.

PAPRICA provides some additional helpful pieces of information.  We built in a confidence scoring metric that takes into account both predicted genomic plasticity and the size of the consensus genome relative to the mean size for the clade (deeper branching clades will have a bigger difference), and predicts the size of the genome and number of 16S rRNA gene copies associated with each 16S rRNA gene, both of which have a strong connection to the ecological role of a bacterium

For our initial application of PAPRICA we selected a previously published 16S rRNA gene sequence dataset from the West Antarctic Peninsula (our primary region of interest).  One thing that we were very interested in looking at was whether we could describe differences between microbial communities organized along ecological gradients (e.g. inshore vs. offshore, or surface vs. deep water) in terms of metabolic structure in place of the more traditional 16S rRNA gene (i.e. taxonomic) structure.  Using PAPRICA to convert the 16S rRNA gene sequences into collections of metabolic pathways we found that we could reconstruct the same inter-sample relationships identified by an analysis of taxonomic structure.  This means that a microbial ecologist can, if they choose, disregard the messy and sometimes uninformative taxonomic structure data and go directly to metabolic structure without losing information.  Applying common multivariate statistical approaches (PCA, MDS, etc.) to metabolic structure data yields information like which pathways are driving the variance between sites, and which are correlated with what environmental parameters.  This information is much more relevant to most research questions than the distribution of different microbial taxa.  It is worth noting that while inter-sample relationships are well preserved in metabolic structure, the absolute distance between samples is much less than for taxonomic structure.  This might have some implications for the functional resilience of microbial communities, which we get into a little bit in the paper.

PAPRICA was an outgrowth of a couple of other papers that I’m working on.  At some point the bioinformatic methods reached a point where separate publication was justified.  As a result, and reflecting the fact that I’m much more an ecologist than a computational biologist, PAPRICA is not nearly as streamlined as PICRUSt (which is even available through an online interface).  I’ve spent quite a bit of time, however, trying to make the scripts user friendly and transportable.  Anyone should be able to get them to work without too much difficulty.  If you decide to give PAPRICA a try and run into an hitches please let me know, either by posting an issue in Github or emailing me directly!  Suggestions for improvement are also welcome.

Glacial Earthquakes May Hold Clues to Future Sea Level Rise - Weather Channel

Featured News - Mon, 08/17/2015 - 12:00
Glacial earthquakes could help us measure how much ice is lost from glaciers around the world, Lamont-Doherty's Meredith Nettles says.


Sugar - Sun, 08/16/2015 - 22:33
... so my mother can see I'm wearing a hardhat (Hi Mom).  Galen getting done, Natalie with commentary, Yogi counting it down ...

Shot L3-01 video

Sugar - Sun, 08/16/2015 - 21:52

HUGE THANKS to all the volunteers who worked so hard to make this project such a great success. It  was a pleasure working with you and getting to know you all.  Also mega thanks to all the landowners who were kind enough, and trusting enough, to let us put a source on their property.  None of this could have happened without your generosity and spirit of curiosity.  Thanks so much.




Subscribe to Lamont-Doherty Earth Observatory aggregator