July 2011 Archives

Running on Empty

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Whether you are a Jackson Browne fan or not - there is one critter in the ocean that just may be 'running on empty'. And it is about time this swimming critter gets a proper introduction from the Ecosystem Modeling Lab.

If you ever had salmon on your dinner plate, it most likely was not wild Atlantic salmon. We have all heard the about the glories of eating omega-3 fatty acids and that salmon are loaded with that stuff.  You ecologists in the audience also recognize that salmon serve as an important nutrient link between marine, freshwater, and terrestrial ecosystems.

Despite decades of conservation efforts, Atlantic salmon populations are still declining. If we want to restore Atlantic salmon populations we need to better understand the marine-phase of their life cycle.

A lot of money and research has focused on the freshwater life-phase of Atlantic salmon in the form of habitat restoration and hatchery breeding and restocking programs. Despite these efforts we have not seen the response in population increase we would expect to see.

The salmon get counted as they leave the rivers and then get counted again as they return to the rivers. From these counts, we know that mortality in the ocean is high.

Salmon are easier to study in freshwater environments because they are shallow water and you can easily see the fish. Salmon are much more difficult to study in the ocean because they are more difficult to track. Tracking involves tagging devices that inherently have a low recovery rate or are typically cost prohibitive. This is one reason why we know relatively little about what factors influence salmon mortality as they migrate through the ocean.

The reality is that the persistence of the species of Atlantic salmon is heavily dependent on human intervention and management. Wild Atlantic salmon are on life support. Right now most of this management focuses on only one of two critical habitats this species utilizes during its life cycle. Enhanced research efforts on the ocean life-phase of Atlantic salmon will provide information that can be used to better manage this species.

So what is the Ecosystem Modeling Lab doing about it?

We are trying to uncover some of the mystery shrouding the high marine-phase mortality. We are attacking this mystery from a few different angles. Kathy Mills has been busying herself pulling together relevant data and information looking for trends in the timing of life-cycle events over the past several decades. Meanwhile, I busy myself building a computer model that will allow us to track swimming and growing particles (a.k.a. young salmon) across the Gulf of Maine (GoM). In the near future, questions that come out of Kathy's research can hopefully be examined using my model, which will be much more cost and time efficient than trying to track live fish in the vast ocean.

Assuming that a blog on ecosystem modeling attracts other ecosystem modelers, I will just briefly touch on a few characteristics of the model but will attempt to keep the lingo G rated for a general audience. We have considerable reason to believe that marine-phase mortality is highest just as they are entering the ocean. Therefore, we are focused on the outmigration of post-smolts (see life-cycle diagram attached) as they move through the GoM. The physical data informing the model comes from buoys in the GoM. Growth and the energetic costs of swimming across the GoM is calculated using the Wisconsin model (so named because it was developed by researchers at University of Wisconsin, which happens to also be my alma mater). We know the post-smolts make it to coast of Halifax a few months after leaving the rivers in Maine so we gave our particles a swimming speed and direction pointing towards Halifax. The particles are then released from a river site at a specified time corresponding to their outmigration, and left to swim towards Halifax while experiencing their oceanographic environment - which means that currents and temperature are able to impact their swimming pathways and growth. For more information regarding the model, please email me at cbyron@gmri.org.

So, Are Atlantic salmon running on empty? Do individuals have enough food to provide energy for their great migration? Are populations large enough to withstand predator attacks? Is the changing environment suitable and stable enough to allow persistence of this species? Stay tuned as we are still in quest for the answers to these questions.

salmon life history fw and marine.jpg

Provincetown Eco-cast

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Some time ago, I wrote an entry philosophizing on the idea of an eco-cast -- that is, an ecosystem forecast delivered like a daily weather forecast, complete with a debonniare newscaster.  This ... was my vision:


Sadly, our copepod / right whale forecasting project has all but wrapped up by now.  We did produce a few forecasts over the years (e.g. here, here, here, here...), both online and in print, but we never did the movie-star version.

A couple of days ago, on a ferry ride to work, I threw together a whimsical video of what such an eco-cast might look like.  The quality (including the newscaster) is not what you would find on cable TV -- you'll notice the amateur nature of it right away -- but it does start to make tangible the idea of an eco-cast.


-Nick Record, signing off


(Mathematicians) (Oceanographers) sin θ ?

Something about a "sine wave"?

I'm sure there's a punchline there somewhere.

At any rate, I recently returned from a great workshop where a subset of mathematicians and a subset of oceanographers intersected in the same pool.  It took place at the Mathematical Biosciences Institute at Ohio State.  The mix of people and perspectives was great, and the atmosphere was one of learning and brainstorming.  There is certainly a need for more integration of these two fields.

The talks spanned a range of topics, ranging from mathy to oceany.  Many of the presentations were live-streamed, and can be downloaded here.  My talk, "Toward a Grand Unified Theory of Copepods" is posted here:
Before you click, be warned: it's nearly an hour long.  Make certain you have some time--you might not be able to tear yourself away.

-Nick Record, signing off.

A Rookie's Perspective

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After being in the ecosystems modeling lab for over a month now I have (believe it or not) started to learn a few things.


As I'm new to the blog I guess I should introduce myself a bit.  My name is Dom and I graduated from Bowdoin College in 2009.  I am just starting a MS in Oceanography at the University of Maine and will be doing most of my study/work remotely from the EML.  In undergrad I majored in physics with a minor in math and somehow found myself at GMRI.  I am new to ecology and ecosystem studies. I have taken biology courses in the past, but never really studied anything about fisheries before now.  Here are some thoughts I had piling up since I've started...


Like Nick got into in a recent post, it has been interesting to see the degree of uncertainty so far.  I knew the ocean was relatively unexplored and is known as a "mysterious frontier" (at least to me), but some of the unknowns caught me by surprise.  Things like fish mortality rates and egg production rates are very difficult to find.  Migration patterns for species are modeled, but it seems to change from year to year, especially as the environment changes... so how useful are our models. People are tagging fish, weighing samples, measuring lengths among other data collection methods, but even with all this data we still have to extrapolate and fill in blanks.  Maybe this makes everything more exciting...


Going along with that idea is the significance of assumptions.  Some how we have to use what we have and try to make predictions.  "We don't know it?... Let's assume this for now and we'll go from there..."


The data and its use have been interesting to me so far. I should have seen this coming, but trying to make predictions with the data we have is a tough task.  When you think about predicting the dynamics of a populations of herring in the GOM, consider the circumstances: there is only data from the last 20 years, individuals could be 10, 12 or even 20 years old, they can swim in and out of this region at any point, stocks can take decades to shift and cycle... It just seems as though there are so many variables that it is impossible to know where to start. 


Data is collection is difficult and data collected is difficult to work with.  External conditions can create holes (i.e. a study can miss a measurement of copepod abundance during a given winter in the GOM).


From what I have seen so far it seems that everyone is trying their best with the resources and information we have available to us.  I guess this is all we can do.  It's easy to see how these obstacles can seem overwhelming.  I think the idea is to make sure we have short term, attainable goals and remind ourselves of the big picture from time to time.  It is undeniable that everything we are working on is important and relevant.  Keeping this in mind is key.


This is what I have picked up on so far.  It may seem a little dreary, but I think it also excites people... I'm excited... I think.


Always learning

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This page is an archive of entries from July 2011 listed from newest to oldest.

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