Response of Fish Population Changes to Climate Events

James Overland and Nick Bond

First Concept - Climate

• Decadal Climate Variability more “Event-like” than regular Oscillations

• Large and long deviations from averages

• Default Model is Stochastic Red Noise- AR1 to Long Memory; Little deterministic predictability

Extended annual mean SAT record for the northern North Atlantic region (TNA). (Wood, et al.

2010). NO 60-80 Year Oscillations in early portion of record.

1800 1825 1850 1875 1900 1925 1950 1975 2000

Year

Tem

p. A

nom

aly

(°C)

SW GreenlandIceland

Tornedalen

Arkhangel’sk

North AtlanticOcean

ETCW

-2.0

0.0

2.0

1800 1825 1850 1875 1900 1925 1950 1975 2000

Year

Tem

p. A

nom

aly

(°C)

SW GreenlandIceland

Tornedalen

Arkhangel’sk

SW GreenlandIceland

Tornedalen

Arkhangel’sk

North AtlanticOcean

ETCW

-2.0

0.0

2.0

Year

SAT

anom

aly

(°C)

Havsklimatgruppenwww.oceanclimate.

se

-10

-8

-6

-4

-2

0

2

Tem

pera

ture

(o C)

1500 1550 1600 1650 1700 1750 1800 1850 1900 1950 20000

60

120

180

240

300

360

420

Year

Max

imum

ice

exte

nt (x

103 k

m2 )

Sub-arktisk vinterklassifikation för de senaste 500 åren

Eriksson et al, in press

Perioder1522-36 Mild1562-76 Kall1577-91 Mild1597-1629 Kall1630-62 Mild1663-1706 Kall1707-50 Mild1750-1877 Kall - 1803-20 Kall1878-nu Mild - 1930-40 Mild - 1940-42 Kall - 1971-75 Mild - 1985-87 Kall - 1988-93 Mild

No Regular Climate “Cycles”

1900 1920 1940 1960 1980 2000 2020-3

0

3

Butterworth

EEMD C6+R

Smoothed Air Temperature St Paul Island, Bering Sea

Low-pass EEMD analysis with a low-pass Butterworth filter applied to the St. Paul air temperature time series. (From Overland et al., 2012)

Can Fit a square oscillator to Pacific Decadal Oscillation (PDO) timeseries to give “multiple stable states”

BUT: Other simple times series models without multiple stable states (Stochastic Red Noise AR1 and Long Memeory) also fit the PDO data equally wellCONCLUSION: Cannot determine underlying process model from data alone for records shorter than 200 years, CANNOT Deterministically Project, only use Statistical Scenarios

Overland et al. (2006)

George Sugihara:

“time series observations of key physical variables for the North Pacific Ocean…are best described as linear stochastic. In

contrast, we find that time series for biological variables having similar properties exhibit a low-dimensional nonlinear

signature*.”

*Chih-hao Hsieh, Sarah M. Glaser, Andrew J. Lucas & George Sugihara, Distinguishing random environmental fluctuations from ecological catastrophes for the North Pacific Ocean, Nature 435, 336-340 (2005)

(E) Embedding dimension/Degrees of freedom: how many independent ways a system can vary

Distinguishing random environmental fluctuations from ecological catastrophes for the North Pacific OceanChih-hao Hsieh, Sarah M. Glaser, Andrew J. Lucas & George SugiharaNature 435, 336-340(19 May 2005)

Second Concept: Ecosystems/Fish Populations

The responses to climate shifts by biological systems are direct, but diverse because intervening processes introduce amplifications, time lags, hysteresis, and non-linearities, leading a variety of climate to ecosystem transfer functions

But northern North Pacific Ecosystems have a limited number of main interactions for each major species

Aydin

Gaichas and Francis

Coyle et al.

Southern Bering Sea Ecosystem Changes

Warm temperatures previouslyfavored pollock over Arctic species. But recently, poor prey in very warm period, more predators gave a biomass loss of 50%Now recovery with cold temperatures- but nearly a biological regime shift

20012000

Photo by W.B. Miller ca. 1920, AlaskaLibrary of Congress

Cod in the Bering Sea

1870s- 1930s

Stochastic Climate Variability Low Dimension on all time scales Ecosystems

SUMMARY:Northern North Pacific Ecosystem Response to Climate Variability

TemperatureC

1) In the future we can expect large excursions in the climate system that last for multiple years, but there is as yet little predictability for when they will occur or how long they will last. -Low Frequency Red Noise Stochastic System with long AVERAGE return periods

2) Transitions mechanisms appear more like individual multi-year events rather than multi-decadal oscillations. Minimal decadal (PDO) memory processes.

3) Biology shows regime shifts in response to random climate forcing. Northern species develop to take advantage of this stochastic structure of extremes. A few dominant species, patchiness, multi-year life spans with highly variable year classes.

Conclusions