2014 Lobster Forecast--Update 4

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I'm on vacation this week, so this post will be very brief. Here's the latest update of our lobster forecast:

Forecast2014_04.23.jpg

The 20m temperatures at Buoy E have stuck pretty close to the average over the last few days, and our forecasted start-date is pretty much where it was last week: a day or so later than the long-term mean date.  I will update again this weekend and once more next week.

2014 Lobster Forecast--Update 3

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School vacation starts tomorrow in Maine, and I'll be taking some much needed vacation time.  I will try to update the forecast at least once while I'm gone, but I wanted to make sure to get a fresh forecast up before I leave:

Forecast2014_04.17.jpg
The forecast again has shifted to the left, and we're now essentially predicting a normal season.  The best analog is 2008.  

I'm intrigued by how the season is progressing in the water.  My sense is that the ocean is warming up faster than on shore, especially below the surface.  I think this might be a result of the series of clear, bright days we've had recently.  The most important component to heating in the ocean is the penetration of light into the water.  On a clear day, especially if the winds are low, there are a lot of photons going into the ocean.  The temperature of the air above the water is a lesser factor, and can really just pull heat from the surface of the ocean.  The forecast for the next few days is for sunny and calm conditions.  My bet is that by the middle of next week, our forecast will be for an slightly early start.

2014 Lobster Forecast--Update 2

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The warming at Buoy E has continued and the temperatures there are now pretty much at the long-term average.  This means that our forecast is for a season that is only delayed two days (now projected for July 1):

Forecast2014_04.12.jpg
As before, the start dates from previous years are plotted at the top, with blue indicating cold years and red indicating warm years.  The diamonds represent a forecast.  The center of the diamond is the forecasted value and the width is the 95% confidence interval.  Each diamond represents a forecast made using data centered on the date on the left.  

Note that the width of the diamond is smaller than before.  This is due to both higher skill for this week compared to previous and to the fact that our forecast is close to the longer-term average.

I don't have a good sense for weather the warming will continue or whether we will remain close to the long term average.  NOAA's Climate Prediction Center is forecasting below average air temperatures over the next few weeks, so perhaps we'll hold steady with a slightly delayed season.

2014 Lobster Forecast--Update 1

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Seascape has a long tradition of trying to develop ecosystem forecasting.  It started with copepods and whales, and last year, we made our first stab at forecasting lobsters, specifically, the date when the Maine lobster landings begin their rapid summer increase.  Our  forecasts were motivated by the extremely warm year in 2012 and the havoc that it caused in the Maine lobster fishery.  

Here is our first attempt at a forecast for the 2014 fishing season:

Forecast2014_04.07.jpg

Just a reminder that this is the forecast for the start of the "high catch period" when landings really begin to increase.  They are based on the temperature at 20m at NERACOOS Buoy E operated by the University of Maine Physical Oceanography Group.  Full details are at the end of the post.

There's a lot on this figure (we're still experimenting with the best way to present these forecasts).  The blue diamonds are the forecasts, with the width of the diamond representing the 95% confidence interval.  Each diamond is the forecast generated on a specific date.  The forecast at the top is the most current, the one on the bottom was made using data in early February.  Our current forecast is for the landings to start picking up around the Fourth of July, about 5 days later than usual (usual is indicated by the black line).

The sticks and the text at the top indicate the start date from the past.  Our current forecast is for the timing of the 2014 season to look a lot like 2003, which was a pretty cold year (indicated by its blue color).  Years that were warmer than normal are indicated in red, years that are near the average temperatures are in black.  Gray indicates that buoy temperatures were not available in those years.

You'll notice that we were forecasting an even later start of the season (about 8 days delayed) back in the end of March.  This coincided with the coldest temperature anomalies. The warming over the last few weeks has been greater than normal, and water temperatures are almost to the 2002-2011 average for this time of year.  This has caused the forecasts to move back towards the center.  I would not be surprised if this trend continues and that our forecast at the end of April is close to the middle.  

We will try to update these forecasts over the next few weeks.  We also have a proposal pending at NASA that would allow us to improve and expand these forecasts in terms of what we forecast (timing and volume of landings by zone, hard/soft-shell mix) and how early we issue them.

Methods
We downloaded temperature data from the 20m sensor on NERACOOS buoy E.  The best place to look at the current conditions at E is through the NERACOOS Climatology Tool, but if you want the data, UMaine provides netCDF files.  We created a time series of 8-day average temperatures.  The dates on the left side of the figure are the middle of the 8d period used to generate the forecasts.

For each 8d period, we used historical temperature and landings data to build a simple linear model relating temperature on that date to the date when landings begin to increase.  We generated the lobster landings "start date" using monthly landings for Maine. For each year, we divide the monthly landings by the total landings for the year, and then use linear interpolation to find the point where normalized landings increase to 0.08.  These are the dates indicated by the sticks at the top.

Another warming-Maine map

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Feeling the chill of the approaching Northeaster? This map will warm your core. It highlights the areas in our neighborhood that are among the fastest warming in the global ocean over the past ten years. You can see that parts of the Gulf of Maine are among the fastest 0.01% of the ocean in terms of rate of warming. 

WarmingPercentMaine.jpg

To put things in context, here are the warming and cooling regions throughout the global ocean. Red areas have warmed over the ten year period, blue areas have cooled.

OceanWarming.jpg
So if you're chilled to the bone this winter, go for a dip. Just make sure you swim for at least a decade so that you experience the climate signal.

Nick Record, signing off

A closer look at Gulf of Maine warming

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On a frigid February Friday, when I should otherwise be in Hawaii at the Ocean Sciences meeting, there is one substitution for staying warm: looking at Gulf of Maine temperature trends. This blog is a closer look at the Gulf of Maine warming that Andy described in an earlier post (and a still earlier post).

A closer look shows that the warming over the past 30 years (about .3 deg C per year) is not uniform across the gulf, or throughout the year. The plot shows the warming trend for each month across the gulf. The red regions in the upper left sub plot, for example, show areas where January temperatures have warmed over the past 30 years. The next sub-plot shows February and so on. Blue indicates a cooling trend. The twelve sub plots are for the twelve months.

GOM30yrwarming.jpg
The Bay of Fundy is consistently warming, and the autumn is generally warmer now than in the 1980s. But there is some nuance here. February, for example, has been getting cooler.

By contrast, here is the same plot looking at the past 10 years (same color scale):

GOM10yrwarming.jpg
This represents a gulf-wide 2-3 degree warming over the past 10 years. This histogram summarizes the data, similar to Andy's last post.

TchangeHist.jpg

Although these plots show warming trends, they don't produce warming themselves, and my fingers are starting to freeze up. This may be the last thing I type today.

Nick Record, signing off



A dynamical systems link between traits and ecosystems

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Over the past few decades, ocean ecosystem modelers like myself have gone from a Nutrient-Phytoplankton-Zooplankton picture of the ocean that looks like this:
NPZ.jpg


...to one that looks more like this:

NNPPZZ.jpg

The motivation, I would say, has been that the simple paradigm misses important processes, like species life history, or important properties, like diversity and its consequences. (Not to mention the myriad of Z that do not consume P.) The more complex picture, although impressive looking, comes with baggage. Among others, there is also the problem of parameterizing these models. Lots of boxes and arrows means lots of rates and properties to be measured--increasing roughly with the square of the number of species (or state variables).

One approach to simplifying this mess is to organize the ocean according to certain traits. Trait-based perspectives are not new, and I think they might be able to clean up the NNNNPPPPPZZZZZZZZZZ spider web we're tinkering around with these days. For example, we can approximate the distribution of a trait across species with a curve. With some analysis, we can then look at the effect of the shape of this curve on the structure of the community. In the example below, a Gaussian distribution of growth rates (gamma) produces realistic rank-abundance curves in a zooplankton population. Different curves produce different community-level patterns.

Traits.jpg

This is an idealized analytical model. The real world is messier. Still, as long as we are modeling species by using collections of ecologically important traits, we can use the distributions of those traits to inform the model. 

As a messier example, I'll draw from a more complex copepod model. We included a number of traits, such as activation energies, development times, and diapause strategies (many copepods go into dormancy during certain stages). These traits have been painstakingly tabulated across many species by people who I assume have lots of coffee and live in cold, cloudy places. By drawing from these distributions in a sort of stochastic way, and plugging the model into different parts of the ocean, we get very different communities emerging at different places.

TraitModel.jpg


The next image shows preliminary output from a North Atlantic model. These are the results for the diapause trait. Basically, in northern latitudes, species that diapause make up the majority of the population. Closer to the equator, they don't fare well. On the right you can see an image of what the population looks like in terms of the size of the animals, and a distribution of the diapause trait as a function of life stage. In the north, there are large diapausing species with long development times. In the south, the opposite.

DiapauseMap.jpg

If you know the North Atlantic well, you'll recognize that this map is not perfect, and we are still a ways from describing the whole ecosystem this way. Still, by shifting the perspective away from the individual species, and towards properties of the community, we are able to make some more sense out of the NNNNNNPPPPPPPZZZZZZZZZZZZ spider web.

Nick Record, signing off


Hubbell SP (2001) The unified neutral theory of biodiversity and biogeography (MPB-32) (Vol. 32). Princeton University Press.

Record NR, Pershing AJ, Maps F (2013) Emergent copepod communities in an adaptive trait-structured model. Ecol Model

Record NR, Pershing AJ, Maps F (2013) The paradox of "the paradox of the plankton". ICES J. Mar. Sci. 

  

The Gulf of Maine is Warming Fast!

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I'm at the NCSE "Climate Solutions Conference" in Washington, DC this week.  I was invited to talk about the lessons we can learn from the 2012 ocean heat wave in a session on "Managing Fisheries Under Climate Change."  For my talk, I was curious whether the warming we've seen in the Gulf of Maine is unique.  Short answers: it is very unique: since 2004, the Gulf of Maine has warmed faster than 99.85% of the global ocean.


To get to this number, I grabbed the global sea surface temperature (SST) data set from NOAA's   optimally interpolated product.  I removed the mean annual cycle (1982-2011) to produce daily anomalies.  I then selected 2,000 point at random (shown over the mean SST from June):
SSTtrendpoints.jpg
At each point, I computed the linear trend over the last 10 years (January 2004-September 2013).  At this relatively short time scale, I would expect to see a lot of variability--a lot of places warming, but also a lot of places cooling, and this is what I found. The mean trend is 0.006°C/yr and there are slightly more points that are warming (1024 points) than cooling (976).  

The distribution of trends is pretty much normal (in the statistical sense):
GlobalSSTdistr.jpg
but the Gulf of Maine is decidedly abnormal.  The Gulf is warming at 0.23°C/yr (see my previous post), and from my 2000 randomly selected points, I found only four (FOUR!) that were warming faster (red stars on the map).    Turns out one of them was from the Gulf of Maine (go figure), and that the other points were from the Kuroshio extension region northeast of Japan.  This makes some sense oceanographically and is probably driven by a northward shift in the Kuroshio (the Pacific's Gulf Stream). 

According to this analysis, the warming in the Gulf is remarkable, and frankly, a little scary.  However, it is important to remember that this is just a statistical analysis.  At some point, the trend will slow, but we don't know when and by how much.  There is clearly more work to be done to understand the mechanisms that are driving the current trend.   And, there is also an opportunity to use the Gulf of Maine to understand how an ecosystem responds to rapid climate change.

Are chaetognaths gelatinous? You be the judge

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(Apologies in advance for the perhaps obscure and esoteric content of this entry.)

The "Jelly Ocean Hypothesis" suggests that due to human-driven changes in the environment, we are headed toward an ocean dominated by jellyfish. Before determining whether this scientifically intriguing dystopian nightmare comes to pass, we need to agree on what classifies as a "gelatinous zooplankton"

Some people assert that chaetognaths fit into this category; others do not. Since we are debating this in the lab now, here is some information for context. What we need is a measure of how gelatinous something is. Ideally we would like to have a measure of carbon-to-volume ratio for each taxon--basically a measure of organic density--but for now, dry weight as a percentage of wet weight (DW as %WW) will have to do. --Basically the amount of the organism that is not water.

Ctenophore01.jpg Calanus_CV.jpg 170px-MEB_back.png
ctenophore    copepod            chaetognath
gelatinous    not gelatinous       ??


Here are the numbers:

Euphausiid DW as %WW: range 20-24% (depending on stage) +/- ~3
(Iguchi & Ikeda 1998 table 1)

Copepod DW as %WW: average ~19% +/- 10
(computed from Mauchline 1998 fig 50)

Chaetognath DW as % WW: 8
(Sameoto 1972 reported in Feigenbaum 1982)

Thaliacea DW as %WW: average 5.5% +/- 2.47
Ctenophora DW as %WW: average 3.53% +/- 0.92
Cnidaria DW as % WW: average 4.07% +/- 1.23
(Lucas et al. 2011)

And in graphical format:

chaetognath1.jpg
<--------- more gelatinous                                       less gelatinous --------->


I think this crude and cursory analysis settles the debate. Now we can get back to talking about copepods.

Nick Record, signing off

References

Lucas CH, Pitt KA, Purcell JE, Lebrato M, Condon RH (2011) What's in a jellyfish? Proximate and elemental composition and biometric relationships for use in biogeochemical studies. Ecology 92:1704.

Feigenbaum D (1982) Feeding by the chaetognath, Sagitta elegans, at low temperatures in Vineyard Sound, Massachusetts. Limnol. Oceanogr. 27(4): 699-706.

Iguchi N, Ikeda T (1998) Elemental composition (C, H, N) of the euphausiid Euphausia pacifica in Toyama Bay, southern Japan Sea. Plankton Biol. Ecol. 45(1): 79-84.

Mauchline (1998) The biology of calanoid copepods

Sameoto DD (1972) Yearly respiration rate and estimated energy budget for Sagittu elegans. J. Fish. Res. Bd. Can. 29: 987-996.

Gulf of Maine Temperature Trends

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Happy 2014 to you, dear Seascape reader(s)! To kick off another year of oceanographic musings, here is the updated temperature trend for the Gulf of Maine:

GOMssttimeseries.jpg

This is essentially the same figure we used to show the 2012 event, but extended through early September (the last available AVHRR OI field).  As you can see, 2013 was cooler than 2012, but was still a very warm year. The recent warming trend has continued (it's actually a little stronger), and 2012 still stands out as unusual.  Of course, this doesn't include the impact of a few very cold days recently (I'm talking about you, polar vortex), nor does it include the very mild weather we're experiencing now.  Temperatures in the ocean change much more slowly than those on land, and water temperatures are a better indicator of climate trends than the weather on a given day.  I hope to update the SST animations in a couple of weeks.

 

Recent Comments

  • Nick Record: Follow up: a series of measurements by Kotori (1976) put read more
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  • Andy Pershing: I thought it looked like you'd put on a read more
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