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Understanding Uncertainties in Paleoclimate and Paleoecology: Age Models, Proxy Processes, and Beyond | December 18, 2014 GUARDING AGAINST FALSE DISCOVERY IN LARGE-SCALE DENDRO CHRONOLOGY Sco St. George University of Minnesota

Guarding against false discovery in large-scale dendroclimatology

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Page 1: Guarding against false discovery in large-scale dendroclimatology

Understanding Uncertainties in Paleoclimate and Paleoecology: Age Models, Proxy Processes, and Beyond | December 18, 2014

GUARDING AGAINST FALSE DISCOVERY

IN LARGE-SCALE DENDRO

CHRONOLOGYSco! St. George

University of Minnesota

Page 2: Guarding against false discovery in large-scale dendroclimatology

3ASSERTIONS BASED ON

TREE-RING DATA

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COSMICRAYS

Page 4: Guarding against false discovery in large-scale dendroclimatology

“ ”Dengel et al., 2009

New Phytologist

… THERE WAS A CONSISTANT AND SIGNIFICANT RELATIONSHIP

BETWEEN GROWTH OF THE TREES

AND THE FLUX DENSITY OF GALACTIC COSMIC RADIATION.

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SOLARCYCLE

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“ ”

Duan and Zhang, 2014 Journal of Geophysical Research - Atmospheres

SPECTRAL ANALYSIS ALSO SHOW THAT SIGNIFICANT PERIODICITIES

OF ~11 YEAR, 54 YEAR, AND 204 YEAR PEAKS [IN TREE-RING DENSITY RECORDS]

RESPOND TO THE SCHWABE CYCLE,

THE FOURTH HARMONIC OF THE SUESS CYCLE, AND THE SUESS CYCLE,

RESPECTIVELY.

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ATLANTIC MULTIDECADAL

OSCILLATION

Page 8: Guarding against false discovery in large-scale dendroclimatology

“ ”Maxwell et al., 2013

Agricultural and Forest Meteorology

TUPELO HONEY YIELD-PER-HIVE [RECONSTRUCTED FROM TREE-RING WIDTHS]

HAS OSCILLATED BETWEEN MULTIDECADAL-LENGTH PERIODS OF LOW AND HIGH YIELDS

DURING THE PAST 211 YEARS AND IS ASSOCIATED WITH

THE ATLANTIC MULTIDECADAL OSCILLATION.

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LARGE-SCALE GEOPHYSICAL PHENOMENA

SMALL SETS OF TREE-RING WIDTH

DATA

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BOTTOM-UP APPROACH

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JUNE TEMPERATURE JULY TEMPERATURE

AUGUST TEMPERATURE SEPTEMBER TEMPERATURE

OCTOBER TEMPERATURE NOVEMBER TEMPERATURE DECEMBER TEMPERATURE

JANUARY TEMPERATURE FEBRUARY TEMPERATURE

MARCH TEMPERATURE APRIL TEMPERATURE

MAY TEMPERATURE JUNE TEMPERATURE JULY TEMPERATURE

AUGUST TEMPERATURE SEPTEMBER TEMPERATURE

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p > 0.05

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TYPE 1 ERROR

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PinusPicea

QuercusPseudotsuga

Larix

NothofagusAustrocedrisPhyllocladus

Agathis

Source: St. George, PAGES News, 2014

There are more than 3,200 publicly-available tree-ring records (and many more held by individual investigators).

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FALSE DISCOVERY

RATE

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“ ”Wilks, 2006

Journal of Applied Meteorology and Climatology

… THE EXPECTED PROPORTION OF REJECTED LOCAL NULL HYPOTHESIS

THAT ARE ACTUALLY TRUE.

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SYNOPTIC APPROACH

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PiceaPinus

PseudotsugaQuercusLarix

A

C

# re

cord

s

% re

cord

sB

18ºN

36ºN

54ºN

72ºN90ºN

120ºW 60ºW 0º 60ºE 120ºE 180ºW180ºW

1000 20001200 1400 1600 1800

2000

1000

0 0%

12%

6%

1000 20001200 1400 1600 1800Year Year

Source: St. George et al., Geophysical Research Le!ers, 2013

This map illustrates the reasonably-large subset of the North American tree-ring width network

analyzed by this study.

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STRONG WIDESPREAD

DIRECT

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-0.8 -0.6 -0.4 -0.2 +0.2 +0.4 +0.6 +0.8

correlation coefficient (ring-width vs. climate)

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(a) Winter precipitation

(b) Summer precipitation

(c) Summer temperature

-0.8 +0.8-0.6 -0.4 -0.2 +0.2 +0.4 +0.6

WINTER PRECIPITATION

Source: St. George, Quaternary Science Reviews, 2014

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Fri!s, H.C. Growth-rings of trees: their correlation with climate. Science 154, 973-975 (1966).

Page 26: Guarding against false discovery in large-scale dendroclimatology

EL NIÑOSOUTHERN OSCILLATION

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(a) El Niño-Southern Oscillation

(b) Pacific Decadal Oscillation

(c) Atlantic Multidecadal Oscillation

-0.8 +0.8-0.6 -0.4 -0.2 +0.2 +0.4 +0.6

ENSO

Source: St. George, Quaternary Science Reviews, 2014

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WEAK(ER) UNCOMMON

INDIRECT

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ATLANTIC MULTIDECADAL

OSCILLATION

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(a) El Niño-Southern Oscillation

(b) Pacific Decadal Oscillation

(c) Atlantic Multidecadal Oscillation

-0.8 +0.8-0.6 -0.4 -0.2 +0.2 +0.4 +0.6

Source: St. George, Quaternary Science Reviews, 2014

ATLANTIC MULTIDECADAL OSCILLATION

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PACIFIC/ NORTH AMERICAN

PATTERN

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(d) Pacific/North-American Pattern

(e) North Atlantic Oscillation

-0.8 +0.8-0.6 -0.4 -0.2 +0.2 +0.4 +0.6

PACIFIC/NORTH AMERICAN PATTERN

Source: St. George, Quaternary Science Reviews, 2014

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ENSO PNA475/2270 records

139/2270 records

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p > 0.05

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TYPE 1 ERROR

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3POTENTIALLY-USEFUL APPROACHES TO ADDRESS

THIS CHALLENGE

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1STATISTICAL SIMULATIONS

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Dr. Dave Meko University of Arizona

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EXACT SIMULATION

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0

+200

1900 1920 1940 1960 1980 2000

precipitation anomaly (mm)

-200

decadal target

decadal ‘noise’

Source: St. George and Ault, Journal of Geophysical Research - Atmospheres, 2011

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2FORWARD MODELLING

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Dr. Eugene Vaganov Siberian Federal University

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Source: Vaganov et al., In Dendroclimatology, 2010

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180oW 120oW 60oW 0o 60oE 120oE 180oW

15oN

30oN

45oN

60oN

75oN

90oN

180oW 120oW 60oW 0o 60oE 120oE 180oW

15oN

30oN

45oN

60oN

75oN

90oN 1.00.80.60.40.20.0

Synthetic tree-ring records generated by a forward model (and modern climate data) exhibit largely the same spatial pa!erns in climate response as real trees.

Can we predict how local trees should respond to weak or remote climate influences?

SOIL MOISTURE : TEMPERATURE

Source: Xiaolu (Grace) Li, Cornell University

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3SELECTIONCRITERIA

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PinusPicea

QuercusPseudotsuga

Larix

NothofagusAustrocedrisPhyllocladus

Agathis

Source: St. George, PAGES News, 2014

Because the global ring-width network is now so large, it is crucial to ensure our understanding of tree-environment relations is not influenced

by decisions to include or exclude particular records.

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