Phenology and Life History Characteristics of Mountain Pine Beetle ...

Phenology and Life History Characteristics of Mountain Pine Beetle and Jeffrey Pine Beetle Barbara J. Bentz

Rocky Mountain Research Station USDA Forest Service, Logan UT www.usu.edu/beetle

Collaborators Jim Vandygriff Camille Jensen Tom Coleman Patricia Maloney Sheri Smith Amanda Garcia Greta Langenheim Jim Powell

RMRS, Logan, UT UC Davis, Davis, CA Forest Health Protection, Riverside, CA UC Davis, Davis, CA Forest Health Protection, Susanville, CA Forest Health Protection, Flagstaff, AZ RMRS, Logan, UT Utah State University

Forested Area Affected by Bark Beetles 2000 – 2012 46.1 million acres

Photo Ken Gibson

http://foresthealth.fs.usda.gov/portal

June Mountain Ski Resort 2011 - Whitebark and Limber pine mortality

Photo Beverly Bulaon

Acres affected in California

3000000

MPB All bark beetles

2500000

Spooner Junction, Lake Tahoe 1995 - Jeffrey pine mortality

2000000

1500000

1000000

500000

0

2000

2002

2004

2006 Year

2008

2010

2012

Photo Sheri Smith

July 2002

July 2003

July 2004

July 2005

July 2007

July 2008

DRY

DRY

DRY

WARM

COOL WARM

1925 - Mountain pine beetle-killed lodgepole pine in Yosemite National Park, CA.

Pinyon pine mortality SW US (FHP ADS)

Tree-ring evidence of mountain pine beetle-killed whitebark pine in ID and MT.

Mountain pine beetle-caused tree mortality in northern Colorado (Chapman et al. 2012)

Temperature Trends in California

Cordero et al. 2010

Outline I. Voltinism and biology of mountain pine beetle (MPB) and Jeffrey pine beetle (JPB). II. Results from recent study describing thermal habitat and lifecycle timing of JPB and MPB in California and across western US (for MPB). III.Relate current and historical MPB population success using a model that describes temperature effects on phenology. IV. Climate Change Implications for MPB in California.

Thresholds and positive feedback processes at multiple scales contribute to the eruptive, outbreak nature of ‘aggressive’ bark beetle populations. Raffa et al. 2008, Bioscience

Voltinism Voltinism: number of generations per year Generation: number of days for a brood of individuals to develop and emerge from a tree.

Univoltine: Semivoltine: Bivoltine:

1 generation per year 1 generation in 2 years 2 complete generations within 1 year

MPB lifecycle timing has historically been reported as:

P. ponderosae Helena NF, MT

1) univoltine at low elevations

2) a mix of univoltine and semivoltine at high elevations (Reid 1962, Amman 1973)

P. albicaulis Yellowstone NP, WY

Voltinism Mountain pine beetle: “In portions of California, two and a partial third generation may develop…” (Furniss and Carolin 1977).

Jeffrey pine beetle: “One or two generations can be completed per year depending on location and temperature. One generation may be more common in northern California, whereas a second generation may occur in the same year in warmer areas like southern California…” (Smith et al. 2009).

Why is temperaturedependent voltinism and developmental timing important to MPB & JPB success?

• Mate finding • Attack of host trees at time when defenses are lowest • Overwhelm host tree defenses en mass • Appropriate timing to avoid cold susceptible lifestages (pupae, eggs) during winter • Univoltine life-cycle contributes to population eruptions.

MPB gene flow occurs in a horseshoe shape around the Great Basin with significant reproductive isolation between populations on either side.

There is substantial genetic variation in MPB development time across a latitudinal cline in western US. Common Garden Rearing Experiments 1.0

22 C

Cumulative Emergence

0.8

0.6

ID

0.4

OR CA3 UT

0.2

CA CA1 AZ

0.0 0

25

50

75

100

125

150

175

200

225

250

Days from Infestation

ID2 OR

ID SD

CA3 UT UT2 CA2 CA1

AZ

AZ2 Bracewell et al. 2013;

Bentz et al. 2001, 2011

From Mock et al. 2007; Bracewell et al. 2011

Outline I. Voltinism and biology of mountain pine beetle (MPB) and Jeffrey pine beetle (JPB). II. Results from recent study describing thermal habitat and lifecycle timing of JPB and MPB in California and across western US (for MPB). III.Relate current and historical MPB population success using a model that describes temperature effects on phenology. IV. Climate Change Implications for MPB in California.

MPB / JPB sample sites MPB Host tree species: Pinus albicaulis P. contorta P. lambertiana P. monticola P. flexilis P. monophylla

(MPB & JPB)

Elevation range: 1400 – 2920 m Latitude range: 34.3 – 48.1 ° N

(MPB & JPB)

Phloem temperatures

Temperatures were continually monitored Air temperatures

Attacks monitored

Adult emergence monitored

Timing, sex and size of all emerging adults was determined

4000

MPB / JPB sample sites

DH > 15C

3000

2002-03

ID44.2080 ID44.2250

2000

2005-06 ID44.2760 MT44.2760 WY43.2910

1000

0 11 22 pt 1 t 12 v 22 an2 b 12 h 25 ay 5 e 15 y 26 pt 5 t 16 y1 l J Ma June July M Jun rc Se Se Oc Oc Fe Ju No Ma

Date

Thermal heat accumulation at each site 4000

2010-11

CA40.1700 CA39.1780 CA36.2870 UT41.2190 WA48.1400 CA39.2590 WA48.1730 WA48.1900 CA39.2920

3000

2000

1000

Ju 1 ne 11 Ju ly 22 Se pt 1 O ct 12 N ov 22 Ja n2 Fe b 12 M ar ch 25 M ay Ju 5 ne 15 Ju ly 26 Se pt 5 O ct 16

0

M ay

DH > 15C

CA34.2100

Date

2009 150

2010

2011

Lassen

Emergence from 2009 attacks Emergence from 2010 attacks 2009 attacks 2010 attacks

100 50

200

2012

Prosser

150 100

Number mountain pine beetle attacks or emergence

50 200 150

Incline

100 50 200 150

Relay

100 50 200 150

Inyo

100 50 80 60 40

SanBern T2

Emergence from T2 09 attacks 2009 T2 attacks

SanBern T5, T7

Emergence from T5 09 attacks Emergence from 2010 attacks 2009 T5 attacks 2010 attacks

20 80 60 40 20 0

July 19 Oct 27 2009

Feb 4

May 15 Aug 23 2010

Dec 1

March 11 June 19 Sept 27 2011

Date

Jan 5

April 15 July 24 2012

MPB CA plots only

Pinus contorta, 1780 m Prosser creek CA39.1780 LE = 53.2

Univoltine

200

Parent adult attacks Brood emergence

100 50 0 250 200

2010

150 100 50 0

Oct 27

Feb 4

May 15

2009

Aug 23

Dec 1

March 11

2010

2010-11

2000

1000

Fe b 12 M ar ch 25 M ay Ju 5 ne 15 Ju ly 26 Se pt 5 O ct 16

22

N ov

n2

1

12 ct

O

pt

ly

Se

Ju

ne

1

11

22

0

Ju

DH > 15C

CA34.2100 CA40.1700 CA39.1780 CA36.2870 UT41.2190 WA48.1400 CA39.2590 WA48.1730 WA48.1900 CA39.2920

3000

Date

June 19 2011

4000

Ja

July 19

M ay

Number mountain pine beetle

2009 150

Sept 27

May 22

Pinus albicaulis, 2920 m Relay Peak CA39.2920 LE = 61.9

Univoltine - Semivoltine Mix

2009

Parent adult attacks Brood emergence

64%

150 100 50 0 200

2010

May 22 2010

150 100

14%

50 0

g Au

23

c De

1 rc Ma

h1

1 Ju

ne

19

2010

p Se

t2

7

Ja

n5

ri Ap

5 l 1

Ju

ly 2

4

2012

2011

1200

2009 2010

1000

4000 800

2010-11

600

3000 400 200

2000 0

1 12 22 ov 3 c 15 n 25 ch 8 il 18 y 30 ly 11 g 22 ct 2 O July Aug Sept N Ja Mar Apr Ju De Au Ma

1000 Date

CA34.2100 CA40.1700 CA39.1780 CA36.2870 UT41.2190 WA48.1400 CA39.2590 WA48.1730 WA48.1900 CA39.2920

12 M ar ch 25 M ay Ju 5 ne 15 Ju ly 26 Se pt 5 O ct 16

n2

Fe b

22

N ov

Ja

1

12 ct

O

pt

22

0

ly

15

Se

y Ma

Ju

b4

1

Fe

11

2009

7

ne

t2

Oc

M ay

9

Ju

ly 1

DH > 15C

Ju

DH > 15C

Number mountain pine beetle

200

Date

June 17 2011

v1

No

Pinus monophylla, 2100 m San Bernardino CA34.2100 LE = 50.6

< Univoltine, Univoltine

80 60

2009 T2

Parent adult attacks Brood emergence

20 0 80

2009 T5 60 40 20 0 25 20

2010

15 10 5 0

Feb 4

Oct 27

July 19

Aug 23

May 15

March 11

Dec 1

4000

2010-11

2000

1000

0

Ju 1 ne 11 Ju ly 22 Se pt 1 O ct 12 N ov 22 Ja n2 Fe b 12 M ar ch 25 M ay Ju 5 ne 15 Ju ly 26 Se pt 5 O ct 16

DH > 15C

CA34.2100 CA40.1700 CA39.1780 CA36.2870 UT41.2190 WA48.1400 CA39.2590 WA48.1730 WA48.1900 CA39.2920

3000

Date

June 19 2011

2010

2009

M ay

Number mountain pine beetle

40

Sept 27

CA39.2920 LE = 61.9

How do thermal regimes differ geographically (by latitude and elevation) and among specific voltinism pathways?

Univoltine - Semivoltine Mix

Number mountain pine beetle

200

2009

Parent adult attacks Brood emergence

150 100 50 0 200

2010 150 100 50 0

Ju

ly 1

9

t Oc

27

Fe

b4

y Ma

15

g Au

23

c1

De

rc Ma

h1

1 Ju

ne

19

p Se

t2

7

Ja

n5

ri Ap

5 l 1

Ju

ly 2

4

v No

1

Generation time: Number of days between median attack date and median emergence date. Degree Days (DD) and Degree Hours (DH):

Temperature C

40 30 20

Summed across generation time (between median attack and emergence dates).

10 0 -10 -20 -30 July 19

Oct 27

Feb 4

May 15

Date

Aug 23

Based on hourly air temperature at each site using thresholds of 5.6°, 12° and 15°C.

Latitude and elevation were NOT significant in describing generation time. Latitude and elevation WERE significant in describing DD summed across generation time.

Effect DD > 5.6°C Latitude Elevation

Estimate

F

P

-43.9216 -0.25713

5.46 4.56

0.0394 0.0561

Elevation corrected latitude (LE) = -28.8575/-0.22302 = 129.4

DD > 12.0°C Latitude -37.2711 Elevation -0.27619

10.46 17.69

0.0079 0.0015

An increase in 129.4 m elevation has an equal effect on DD>15°C required for MPB generation as an increase in 1°N

DD > 15.0°C Latitude -28.8575 Elevation -0.22302

23.66 20.74

0.0005 0.0008

Derived Effective Latitude LE for each site Bradshaw and Lounibos 1977

R2 0.4766

Mean (± SD) 1102.9 (242.2)

0.7190

421.8 (180.2)

0.7409

240.5 (139.9)

Generation time (days)

700 600 500 400

Average generation time = 374 d

300 200 100 0

50

52

54

56

58

60

62

LE

Warmest

Coolest

WA48.1730-10 WA48.1400-10 UT41.2190-11 UT41.2190-10 CA40.1700-09 CA40.1700-10 CA39.2920-09 CA39.2920-10 CA39.2590-09 CA39.2590-10 CA39.1780-10 CA39.1780-09 CA34.2100-09 T2 CA34.2100-10 T5

Generation time (days)

700 600 500 400

Average generation time = 374 d

300

WA48.1730-10 WA48.1400-10 UT41.2190-11 UT41.2190-10 CA40.1700-09 CA40.1700-10 CA39.2920-09 CA39.2920-10 CA39.2590-09 CA39.2590-10 CA39.1780-10 CA39.1780-09 CA34.2100-09 T2 CA34.2100-10 T5

200 100

DD > 15C for generation time

0 Accumulated thermal energy at warm univoltine site was 600 > 4 times that at the coolest, mostly semivoltine site

500

R2 = 0.7409 400

MPB populations at coolest sites required fewer thermal units to complete a generation than populations at warmest sites.

300

200

100

0

50

52

54

56

58

60

62

LE

Warmest

Coolest

Two evolved traits serve as a barrier to decreased MPB generation time despite ample thermal input. 1) Sensitivity to cold in the egg and pupal lifestages. 2) Development thresholds that serve to synchronize cohorts and minimize cold sensitive lifestages in winter.

Development Rate

Instar 4 pre-pupae

Pupae

Temperature

From Régnière et al. 2012

Jan

March May June July

Aug

Sept

Nov

Jan

March May June July

Aug

Sept Nov

Jan

Univoltine

March May June July

Jan

CA34.2100 LE = 50.6

Aug

Sept

Nov

March May June July

Jan

Aug

Sept Nov

Jan

June 1

< Univoltine, Univoltine

80

Development Rate

60

2009 T2

Parent adult attacks

20

20

15°C

0 80

2009 T5

Temperature C

Number mountain pine beetle

30

InstarBrood 4 emergence pre-pupae

40

60 40

Pupae

20

0 25 20

10

0

-10

2010

15 10

-20

5 0

July 19

Oct 27 2009

Jan

Temperature Feb 4

May 15

Aug 23

Dec 1

March 11

2010

March May June July

June 19

Ja

2011

Aug

Sept

9

0

Sept 27

n3

b2

Fe

r Ma

30

r Ap

29

y Ma

5 5 6 29 e 28 ly 28 g 27 26 t 2 ov 2 ec 2 pt n Oc Ju N Au D Se Ju

Date

Nov

Jan

March May June July

Aug

Sept Nov

Jan

Lab: Common garden experiments at 22°C

Field: Median generation time

800 700

140

Median Generation Time

Median Development Time

160

120

100

80

600 500 400 300 200 100

60

32

34

36

38

40

42

Latitude

44

46

48

50

0

32

34

36

38

40

42

44

46

48

50

Latitude

In northern populations there is selection pressure for traits that result in shorter development time, and selection pressure for longer development time in southern populations. Results from the field study suggest these potentially opposing selection pressures serve to maintain univoltinism across the latitudinal gradient.

Lassen NF

2009

2010 200

Jeffrey Pine Beetle

140

Jeffrey Pine Beetle

120 100

Number JPB

Number JPB

150

80 60 40

2009 Attacks

2009 Attacks 100

2010 Emergence 50

2010 Emergence

20 0

0 200

140

Mountain Pine Beetle

Mountain Pine Beetle

120 100

Number MPB

Number MPB

150

80 60

Attacks

40

100

Attacks 50

Emergence

Emergence

20

0

0

July 19

Oct 27

Feb 4 Date

May 15

Aug 23

July 19

Oct 27

Feb 4 Date

May 15

Aug 23

MPB Non-lodgepole pine host MPB Lodgepole pine host JPB 3.0

Females bigger than males.

Female 2.8

Adult size (mm)

2.6

JPB significantly bigger than MPB.

2.4 2.2

MPB adult size was not correlated with site temperature.

2.0 1.8 1.6

MPB adults from sites with only lodgepole pine were smallest.

1.4 3.0

Male 2.8

Adult size (mm)

2.6 2.4

Sex Ratio (Male:Female)

2.2 2.0

MPB range - 1:1.07 to 1:2.13

1.8 1.6

JPB range - 1:1.00 to 1:1.33

1.4 00 00 80 70 90 20 00 30 00 90 .21 0.17 9.17 6.28 1.21 8.14 9.25 8.17 9.29 8.19 34 4 3 3 3 3 4 4 4 4 T A A A A A A A A A U C C C C C C W W W .8 .6 .1 .2 .6 .4 .9 .1 .4 .8 58 50 53 53 58 59 61 59 61 62

LE and Site Name

Warmest

Coolest

Peak emergence of semivoltine beetles was at a lower temperature and earlier in the year (not shown) than univoltine beetles

Frequency of emergence events

Univoltine Semivoltine 600

400

200

0 0

5

10

15

20

Maximum temperature C

25

30

Summary 1. Thermal regimes of MPB habitats vary significantly across the western US and California. 2. MPB (and potentially JPB) can produce a summer generation in southern CA, but bivoltinism does not appear possible due to evolved adaptations. 3. There appears to be strong selection for univoltinism. 4. MPB and JPB have similar lifecycle timing. 5. Although lodgepole pine is the most widely available host tree species, it may not produce MPB offspring with the greatest fitness advantage, relative to other host tree species.

Outline I. Voltinism and biology of mountain pine beetle (MPB) and Jeffrey pine beetle (JPB). II. Results from recent study describing thermal habitat and lifecycle timing of JPB and MPB in California and across western US (for MPB). III.Relate current and historical MPB population success using a model that describes temperature effects on phenology. IV. Climate Change Implications for MPB in California.

MPB Phenology

Phloem Sandwich

MPB Phenology Model

Egg

Development rates are summed (integrated) over short time steps.

Instar 1

Physiological age , a, proportion of the stage completed from 0 at the onset to 1 at completion -

Instar 2

t

t

0

0

at   r (Tt , A)dt   r (Tt , A)t

Instar 3

Instar 4

Pupae

Teneral Adult

Oviposition

From Regniere et al. 2012; Bentz et al. 1991

Number MPB

2010

Oct 27

40

Feb 4

May 15

Observed emergence and phenology modelpredicted emergence

Aug 23

Date

30 20 10 0

1.0

-10 -20 -30 July 19

Oct 27

Feb 4

May 15

Date

Phloem temperatures

Aug 23

Cumulative Emergence

Temperature C

Observed Emergence

Observed Attacks

July 19

Prosser Creek Tahoe National Forest, 1757 m Lodgepole pine Univoltine lifecycle

2011

0.8

Predicted North aspect Predicted South aspect Observed North aspect Observed South aspect

0.6

median emergence 0.4

0.2

0.0 June 24

July 14

Aug 3

Aug 23

Date in 2011

Sept 12

Oct 2

2010 Observed Emergence

Relay Peak Tahoe Basin Mgmt Unit, 2920 m Whitebark pine Univoltine - Semivoltine lifecycle

2011 Observed Emergence

Number MPB

2009 Observed Attacks

Oct 27

Feb 4

May 15

Aug 23

Dec 1 March 11 June 19 Sept 27

40 30 20 10 0 -10 -20 -30 -40

0.8

Predicted emergence Observed emergence

Univoltine

0.6

0.4

0.2

0.0 June 4 June 24 July 14 Aug 3 Aug 23 Sept 12 Oct 2 Oct 22 Date in 2010

July 19

Oct 27

Feb 4

May 15

Aug 23

Date

1.0

Dec 1 March 11 June 19 Sept 27 Cumulative Emergence

Temperature C

July 19

Cumulative Emergence

1.0

0.8

Predicted emergence Observed emergence

Semivoltine

0.6

0.4

0.2

0.0

June 19

July 9

July 29

Aug 18

Date in 2011

Sept 7

Sept 27

Oct 17

80

San Bernardino NF, 2100 m Pinyon pine < Univoltine & Univoltine lifecycle 2009 Emergence T2

40

20

2009 Attacks T2

July 19

2010 Emergence T2 Aug 7

Oct 27

40

Dec 16

Feb 4 March 26 May 15

1.0

July 4

Date

20 10 0

0.8 Predicted emergence Observed emergence 0.6

0.4

0.2

-10 -20

0.0

July 19

Aug 7

Oct 27

Dec 16

Feb 4

March 26

May 15

July 4

July 19

Aug 7

Oct 27 Dec 16

Date

Feb 4 March 26 May 15

Date 1.0

Cumulative Emergence

Temperature C

30

Cumulative Proportion Emergence

Number MPB

60

0.8

0.6

0.4

ID CA1 CA2 SD

0.2

0.0 40

60

80

100

120

140

160

Days from Infestation

180

200

220

July 4

MPB Phenology, Host Resistance & Epidemiology Calculating ‘R’ population growth E(t) Emerging > A June 1 to Sept 1

I(t) Infesting

A

E(t) < A A E(t)

Relay Peak (2920m)

Prosser Creek (1757m)

2.0 2.0

1.2

1.0

1.8 1.8

1.0 0.8

0.6

R

1.2 1.2 1.0 1.0 0.8 0.8

0.4

0.6 0.6 0.4 0.4

0.8

R

1.4 1.4

Proportion Univoltine

1.6 1.6

0.6

0.4

0.2

0.2

0.2 0.2 0.0 0.0

0.0

0.0

1980

1985

1990

1995

2000

2005

1980

2010

1985

1990

1995

2000

2005

2010

Attack Year

Attack Year 2.0

1.2

At cool site, R greater when it is warm.

1.8 1.6 1.4

At warm site, R greater when it is cool.

1.0

0.8

R

R

1.2 1.0

0.6

0.8

0.4

0.6 0.4

0.2

0.2 0.0

0.0

40

60

80

100

120

DD > 15 C

140

160

180

250

300

350

400

DD > 15 C

450

500

550

Outline I. Voltinism and biology of mountain pine beetle (MPB) and Jeffrey pine beetle (JPB). II. Results from recent study describing thermal habitat and lifecycle timing of JPB and MPB in California and across western US (for MPB). III.Relate current and historical MPB population success using a model that describes temperature effects on phenology. IV. Climate Change Implications for MPB in California.

80

San Bernardino T2 model predictions Current temperature plus 2, 4, 8 °C

2009 Emergence T2

40

20

2009 Attacks T2

July 19

2010 Emergence T2 Aug 7

Oct 27

Dec 16

Feb 4 March 26 May 15

July 4

Date

1.0

0.8

Temperature

Cumulative emergence

Number MPB

60

Observed emergence Observed emergence Plus 2 degrees C Plus 4 degrees C Plus 8 degrees C

0.6

0.4

Adult emergence timing is later with increasing temperature

0.2

0.0 July 19

Aug 8

Aug 28

Sept 17

Oct 7

Oct 27

Nov 16

Date

In this warm environment, MPB is living at or very close to it’s optimal temperature. Small increases can have negative impacts on fitness. The thermal “safety margin” is small. Hotter is not always better.

Relay Peak model predictions Current temperature plus 4°C and temperature estimated for 2011-2040 normal period 1.0

Semivoltine

Cumulative emergence

0.8

0.6

0.4

0.2

0.0 July 19

Univoltine

Feb 4

Aug 23

March 11

Observed emergence 2040 temperatures Plus 4 degrees C

Sept 27

April 15

Date

At higher latitudes and elevations, populations are currently living at environmental temperatures cooler than their optimal temperatures, such that climate warming may enhance fitness.

Prosser Creek model predictions Current temperature plus 4°C and temperature estimated for 2011-2040 normal period 1.0

Cumulative Emergence

0.8

Observed emergence 2040 temperatures Plus 4 degrees C

0.6

0.4

0.2

0.0 July 19

Oct 27

Feb 4

May 15

Date

Aug 23

Dec 1

March 11

What about cold?

from 1960 to 2012

From Weed et al. In Review

Cold-induced caused MPB mortality may not play as big a role in California as in northern latitudes.

MPB in western US evolved in cool rather than warm environments.

Generation ti

Average generation time = 374 d

300

WA48.1730-10 WA48.1400-10 UT41.2190-11 UT41.2190-10 CA40.1700-09 CA40.1700-10 CA39.2920-09 CA39.2920-10 CA39.2590-09 CA39.2590-10 CA39.1780-10 CA39.1780-09 CA34.2100-09 T2 CA34.2100-10 T5

200 100 0 600

DD > 15C for generation time

Implications

400

500

R2 = 0.7409 400

300

200

100

0

50

52

54

56

58

60

LE

Evolved adaptations reduce MPB capacity to take full advantage of increased thermal heat at warmest sites, limiting potential for bivoltinism within current realized distribution. MPB populations with the greatest capacity to take full advantage of increasing temperatures are those in marginally cool habitats. MPB and JPB appear to have similar lifecycle timing. In California both can complete a partial generation the first year. More data is needed on southern populations of both species. The MPB phenology model can be used to evaluate the influence of increasing temperatures on population success, although new parameters are needed for southern populations.

62

Acknowledgements USDA FS, Forest Health Monitoring WC-EM-09-02

Matt Hansen, Leslie Brown, Andreana Cipollone, David Fournier, Stacy Hishinuma, Leverett Hubbard, Michael Jones, Joey Keeley, Brian Knox, Joshua Lambdin, Connie Mehmel