[env-trinity] CBB: Ocean research results on salmon cycles in NW

Sari Sommarstrom sari at sisqtel.net
Fri Jan 18 15:57:33 PST 2013

See 3 articles below


THE COLUMBIA BASIN BULLETIN: Weekly Fish and Wildlife News

www.cbbulletin.com      January 18, 2013               Issue No. 650


Opening The Black Box In A Salmon’s Life: Ocean Biological Indicators Offer
Improved Fish Return Forecasting


A team of scientists from NOAA and Oregon State University has found that a
wide range of biological and environmental indicators from the Pacific Ocean
are better predictors of adult salmon returns to the Columbia River than
local or regional physical indicators. 


The scientists combined data from 31 “indicators” – ranging from sea-surface
temperatures to the amount of prey available to salmon -- collected over 11
years to help predict adult spring chinook salmon returns to the Columbia
last year and then assessed the accuracy of that prediction. In predicting
adult returns they gave varying weights to the various environmental and
biological indicators, with some believed to provide more benefit than
others to fish during their ocean maturation.


Return estimates for 2011 and 2012 were, for the most part, on target.


The study, “Multivariate Models of Adult Pacific Salmon Returns,” was
published online Jan. 11 in PLoS ONE, an international, peer-reviewed,
open-access, online publication. PLOS ONE welcomes reports on primary
research from any scientific discipline. It is published by PLOS, a
nonprofit organization.


The article can be found at:



Lead author for the research paper is Brian J. Burke of the Northwest
Fisheries Science Center in Seattle. The center is an arm of NOAA’s National
Marine Fisheries Service. Co-authors are William T. Peterson, Brian R.
Beckman, Cheryl Morgan, Elizabeth A. Daly, and Marisa Litz. Peterson is
based at the NWFSC’s Newport, Ore., facility and Beckman is with the NWFSC
in Seattle. Morgan, Daly and Litz are with Oregon State University’s
Cooperative Institute for Marine Resources Studies in Newport.


The accuracy of such predictions could prove invaluable to state and federal
fisheries managers in setting harvest limits and allocations, and for
tracking recovery of endangered or threatened salmon runs.


Pacific salmon abundance has been highly variable over the last few decades
and most forecasting models have been inadequate, according to a NMFS press


The statistical modeling work used data collected for the NWFSC’s Ocean
Ecosystem Indicators of Salmon Marine Survival in the Northern California
Current, which has developed and refined a set of 18 indicators, and
collected data since 1998. 


The researchers that produced the new paper added in available data for 13
other indicators.


The long-running NWFSC research has annually assessed those 18 indicators,
and predicted returns for the following year for coho and two years out for
spring chinook. The status of each indicator is ranked – good conditions for
salmon, intermediate or poor. An average of the 18 scores was used for the
forecasts, with returns expected to be good, intermediate or poor.


The new modeling takes thing farther.


“Rather than just rank them, we could weight them differently,” Burke said.
Different variables seemed to affect the chinook differently. It is likely,
too, that different variables might affect different species, or even
populations within a species, differently.


“That is where we would like to go,” Burke said of adapting the method for
use in making other fish species forecasts.


“Our goal was to determine the best combination of indicators to explain the
abundance of spring Chinook salmon returning to the Columbia River each
year,” the article says. “The multivariate techniques we used resulted in
two important products: a pre-season forecast of adult salmon returns,
primarily for management of the fisheries, and a measure of indicator
importance, which can improve understanding of ocean ecology and guide
future marine research. Moreover, the pre-season estimates obtained through
these analyses can be used as a starting point for more detailed in-season
management adjustments.”


“If this is useful [to those making forecasts to advise fish management
decisions], that would be great,” Burke said. He stressed that time and more
research, will tell.


“I feel like we can do better,” he said.


Although some indicators were more important than others, the team said
certain trends were clear. For example, the best predictors of spring
chinook returns were indicators like the abundance of food or the presence
of prey in the ocean. 


“Local indicators of temperature or coastal upwelling did not contribute as
much as large-scale indicators of temperature variability, matching the
spatial scale over which salmon spend the majority of their ocean


“Using the combined information contained in 31 potential indicators of
salmon ocean survival, we were able to model spring Chinook salmon adult
returns quite well
 for spring Chinook salmon returning to the mouth of the
Columbia River through 2011,” the paper says. 


“In 2011, observed adult returns were just over 221 thousand fish, which is
almost exactly what the model predicted (the prediction was off by 6 fish).”


“In 2012, observed returns to Bonneville Dam were just over 186 thousand,
and a preliminary estimate of harvest downstream of Bonneville Dam was just
over 16 thousand fish (Enrique Patino, NOAA Fisheries, unpublished data),
suggesting that the final return of adult spring Chinook salmon to the mouth
of the Columbia River in 2012 was approximately 203 thousand fish. The
predictions for adult returns in 2012 from the current effort was 179
thousand, an error of 11.8 percent. 


“The accuracy of this model stems, in part, from the inclusion of indicators
representing many different aspects of the marine environment. Indeed,
models that used a smaller number of ocean indicators suggested that 300 to
600 thousand spring Chinook salmon would return in 2012.


“Counts at Ice Harbor Dam were underestimated in both 2011 (86 thousand
predicted versus 96 thousand observed) and 2012 (68 thousand predicted
versus 86 thousand observed), an average error of just over 15 percent.


“Counts at Priest Rapids Dam were overestimated in 2011 (17.8 thousand
predicted versus 15.2 thousand observed), but underestimated in 2012 (14.4
thousand predicted versus 19.5 thousand observed), an average error of just
over 21 percent. For both populations, these observed returns in 2012 were
similar to the average over the last decade.”


“In separate analyses, we modeled three response variables representing
different portions of the spring Chinook salmon run. The first was the
annual return of adult spring Chinook salmon, which represents the counts of
fish at Bonneville Dam (the first dam on the Columbia River that salmon must
pass during their return migration to spawn) through June 15th plus the
estimated number of fish harvested in the lower river,” the paper says. 


“Ideally, we would have modeled marine survival (smolt to adult return
rates), as we believe most of our marine indicators relate most directly to
survival, but the lack of good estimates of smolt abundance precluded this.
However, using adult returns as the response variable has direct management
implications, as pre-season harvest levels and dates are set based on
forecasts of this quantity.”


“The other two response variables approximate returns of specific adult
Chinook salmon ESUs. The first was adult salmon counts at Priest Rapids Dam,
which encompass the endangered Upper Columbia River spring-run Chinook
salmon ESU, and the second was adult counts at Ice Harbor Dam, which
encompass the threatened Snake River spring/summer-run Chinook salmon ESU.”
Evolutionarily Significant Units are groupings of related salmon populations
designated by NOAA Fisheries as species.


Results suggest that managing Pacific salmon effectively requires many types
of information and no single indicator can represent the complexities of a
salmon's life when it first enters the ocean. 


"The ocean has historically been viewed as a 'black box' in the life of a
salmon," said Burke, the "but this study opens that box just a little and
shines an important scientific light on its contents."


He said managers can take advantage of this information in forecasting the
size and timing of chinook returns to the Columbia River basin, a
particularly challenging task because harvest limits are typically set some
months before the season starts.


Research funding came from Bonneville Power Administration and through
National Oceanic and Atmospheric Administration Comparative Analysis of
Marine Ecosystem Organization and Global Ocean Ecosystems Dynamics grants.




* Ocean Condition Indicators Show Decent Juvenile Salmon Survival In 2012
Off NW Coast


The array of ocean condition “indicators” monitored by NOAA Fisheries’
Northwest Fisheries Science as a means of judging potential juvenile salmon
survival showed mixed signals in 2012, but seemed to contain more good than


“Our best guess is to expect average to above-average returns of coho in
2013 and Chinook in 2014, but similar to the statement we made last year,
the mixed signals add greater uncertainty to our predictions,” according to
the updated adult coho and spring chinook forecast produced through the
NWFSC’s “Ocean Ecosystem Indicators of Salmon Marine Survival in the
Northern California Current” research project. 


Ocean conditions data has been collected and analyzed through the project
since 1998. The annual project reports, the latest posted on line this week,
“present a number of physical, biological, and ecosystem indicators to
specifically define the term ‘ocean conditions.’" The data is used to
forecast the survival of salmon 1–2 years in advance.


The report can be found at:



The report discusses how physical and biological ocean conditions may affect
the growth and survival of juvenile salmon in the northern California
Current off Oregon and Washington.


“The ocean is still a little goofy,” NWFSC oceanographer Bill Peterson said
of ocean conditions that both in 2011 and last year that were in various
stages of transition at about the time Columbia River juvenile salmon and
steelhead were emerging from freshwater and starting the saltwater portion
of their life.


“2012 was characterized by a steady move from La Niña conditions towards an
ENSO-neutral state. Combined with persistently negative PDO values
throughout the year, a high biomass of lipid-rich northern copepods
supporting the base of the food-chain, and an above average abundance of
winter-time ichthyoplankton (larval stages of fish-prey for salmon), 2012
had the potential to be a good year for supporting juvenile salmon entering
the ocean,” the report days. 


La Nina conditions, and negative Pacific Decadal Oscillation climatic
conditions, generally bode well for salmon and steelhead entering and
maturing in the northern Pacific.


“This positive bio-physical outlook was tempered a bit by a late start to
upwelling, warm sea-surface temperatures through much of the summer, and a
trend towards El Niño conditions, but overall the ocean conditions in 2012
appear to be greatly improved compared to the last several years,” the
report says.


Indicator data – whether it be for the number of young fish netted during
trawling expeditions, prey availability, water temperature or the upwelling
of nutrients – is individually ranked in three tiers. Lower numbers indicate
better ocean ecosystem conditions, or "green lights" for salmon growth and
survival, with ranks 1-4 green; 5-10 yellow, and 11-14 red. 


The 2012 scores were compared to the previous 13 years of the study, and
proved the fourth best for estimated juvenile salmon survival in the 14
years of research.


The researchers use the analysis of the suite of indicators to complement
existing indicators used to predict adult salmon runs, such as jack returns,
smolt–to–adult return rates (Scheurell and Williams 2005) and the Logerwell
production index.


“The strength of this approach is that biological indicators are directly
linked to the success of salmon during their first year at sea through
food–chain processes. These biological indicators, coupled with physical
oceanographic data, offer new insight into the mechanisms that lead to
success or failure for salmon runs,” the report introduction says.


“In addition to forecasting salmon returns, the indicators presented here
may be of use to those trying to understand how variations in ocean
conditions might affect recruitment of fish stocks, seabirds, and other
marine animals. We reiterate that trends in salmon survival track regime
shifts in the North Pacific Ocean, and that these shifts are transmitted up
the food chain in a more–or–less linear and bottom–up fashion as follows:
upwelling to nutrients to plankton to forage fish to salmon.


“The same regime shifts that affect Pacific salmon also affect the migration
of Pacific hake and the abundance of sea birds, both of which prey on
migrating juvenile salmon.” 




* Research: West Coast Salmon Runs Fluctuated Hugely Even Before Commercial
Fishing Started 


Salmon runs are notoriously variable: strong one year, and weak the next.
New research shows that the same may be true from one century to the next.

Scientists in the past 20 years have recognized that salmon stocks vary not
only year to year, but also on decades-long time cycles. One example is the
30-year to 80-year booms and busts in salmon runs in Alaska and on the West
Coast driven by the climate pattern known as the Pacific Decadal

Now work led by University of Washington researchers reveals those decadal
cycles may overlay even more important, centuries-long conditions, or
regimes, that influence fish productivity.


Cycles lasting up to 200 years were found while examining 500-year records
of salmon abundance in Southwest Alaska. Natural variations in the abundance
of spawning salmon are as large those due to human harvest.

Researchers gathered sediment cores from lakes in 16 major watersheds in
southwestern Alaska.

“We’ve been able to reconstruct what salmon runs looked like before the
start of commercial fishing. But rather than finding a flat baseline – some
sort of long-term average run size – we’ve found that salmon runs fluctuated
hugely, even before commercial fishing started. That these strong or weak
periods could persist for sometimes hundreds of years means we need to
reconsider what we think of as ‘normal’ for salmon stocks,” said Lauren
Rogers, who did this work while earning her doctorate in aquatic and fishery
sciences at the UW and is now a post-doctoral researcher with the University
of Oslo, Norway.

Rogers is the lead author of a paper

on the findings in the Jan. 14 online early edition of the Proceedings of
the National Academy of Sciences http://www.pnas.org/.

“Surprisingly, salmon populations in the same regions do not all show the
same changes through time. It is clear that the salmon returning to
different rivers march to the beat of a different – slow – drummer,” said
Daniel Schindler, UW professor of aquatic and fishery sciences and co-author
of the paper.

“The implications for management are profound,” Schindler said. “While it is
convenient to assume that ecosystems have a constant static capacity for
producing fish, or any natural resource, our data demonstrate clearly that
capacity is anything but stationary. Thus, management must be ready to
reduce harvesting when ecosystems become unexpectedly less productive and
allow increased harvesting when ecosystems shift to more productive regimes.

“Management should also allow, and probably even encourage, fishers to move
among rivers to exploit salmon populations that are particularly productive.
It is not realistic to assume that all rivers in a region will perform
equally well or poorly all the time,” he said.

The layers in this sediment core will be analyzed for the isotopic signature
of nitrogen that salmon accumulate in the ocean and leave behind in lake
sediments when they die: When there’s a lot of such nitrogen, it means
returning runs during that time period were abundant.

The researchers examined sediment cores collected from 20 sockeye nursery
lakes within 16 major watersheds in southwestern Alaska, including those of
Bristol Bay. The scientists homed in on the isotopic signature of nitrogen
that salmon accumulate in the ocean and leave behind in lake sediments when
they die: When there was a lot of such nitrogen in the sediments, it meant
returning runs during that time period were abundant; when there was little,
runs had declined.

Climate is not the only reason for long-term changes in salmon abundance.
Changes in food webs, diseases or other factors might be involved; however,
at present, there are no clear explanations for the factors that cause the
long-term variability observed in this study.

Most, but not all, of the lakes examined showed declines in the kind of
nitrogen the scientists were tracking beginning around 1900, once commercial
fisheries had developed. However, earlier fluctuations showed that natural
processes had at times reduced salmon densities as much as recent commercial
fisheries, the co-authors said.

“We expected to detect a signal of commercial fishing – fisheries remove a
lot of the salmon, and thus salmon nitrogen, that would have otherwise ended
up in the sediments. But we were surprised to find that previous returns of
salmon to rivers varied just as dramatically,” Rogers said.

As the paper said, “Interestingly these same fluctuations also highlight
that salmon stocks have the capacity to rebuild naturally following
prolonged periods with low densities, suggesting a strong resilience of
salmon to natural and anthropogenic depletion processes. Indeed, total
salmon production (catch plus escapements) has been relatively high in
recent years for most sockeye salmon stocks in southwestern Alaska, despite
a century of intense harvesting.”

Other co-authors are Peter Lisi and Gordon Holtgrieve with the UW, Peter
Leavitt and Lynda Bunting with University of Regina, Canada, Bruce Finney
with Idaho State University, Daniel Selbie with Fisheries and Oceans Canada,
Canada, Guangjie Chen with Yunnan Normal University, China, Irene
Gregory-Eaves with McGill University, Canada, and Mark Lisac and Patrick
Walsh with Togiak National Wildlife Refuge, Alaska.

Funding was provided by the Gordon and Betty Moore Foundation, the National
Science Foundation, the U.S. Fish and Wildlife Service and the Natural
Sciences and Engineering Research Council of Canada.


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