Linking spatial and temporal patterns in resource availability,

individual performance, & population dynamics.

Primary thesis objectives

• Determine how much individual detail is needed in models of population dynamics.

• Relate explicitly spatial and temporal variation in resource abundance to individual “success”.

For today….

• Population level dynamics of red squirrels in Kluane valley

• Temporal/spatial variation in resource abundance and territory sizes

Red Squirrel (Tamiasciuris hudsonicus)

Population dynamics

1. Population dynamics:

– Holistic approach assumes:• Habitat is homogeneous

• All individuals are identical

– Reductionist approach assumes:• individual level of detail is important

Go with Holistic View - for now

Midden locations

60 m

60 m

SU

KL

Female densities

Population models

• 4 competing models• Density independent: Nt+1 = Nt•ea

• Density dependent: Nt+1 = Nt•ea+bNt

• Delayed density dependent: Nt+1 = Nt•ea+bNt+cNt-1

• Response Surface model: Nt+1 = Nt•ea+bNt+cNt-1+dNt2+eNt-12+fNtNt-1

• AICc used to compare model fit to data

Population models: AICc results

KL SUModel AICc dAICc AICc dAICc

DI 13.51 0.00 18.52 3.57DD 13.55 0.04 14.95 0.00

DDD 16.66 3.14 17.42 2.47RSM 26.80 13.29 30.35 15.40

Population models: Density dependence??

SU

What about food??

KL

Population summary

• Food and density effects appear to differ between these ‘populations’

• KL - Density independent/Density dependent • SU - Density dependent

• Habitat quality too???

Why are they different?• Different birth rates, survival patterns?

– λ-contribution analysis (λ=er)

• which life-history characteristic best-tracks changes in population growth-rate?

» begin to tease apart what life-history is related to changes in the population growth rate (ie. fecundity, survival)

» also, investigate spatial variation in this “key-factor” within each population, and relate to territory ‘quality’

CONESAND TERRITORY SIZE

Annual cone production

• White spruce - a masting species

• Cone index - count top 3m of tree

• Cone calibration - count all cones!!

3m

White spruce cone production index vs. actual

0

1

2

3

4

5

6

7

8

0 1 2 3 4 5 6 7 8

ln(count)

ln(a

ctu

al)

Actual cone range: 1 - 2774

y=1.185*xr2=0.996

* ** * *

Sp

ruce

Co

nes

1988 1990 1992 1994 1996 1998 20000

50

100

150

200

250

300

350

* ** * *

Methods:

- individual squirrels visually observed- territorial behaviours & locations noted- 100 % MCP

60 m

1994 and 2001

Territory size

Temporal patterns

* ** * *

Temporal patterns

* ** * *

Linking food availability to reproductive output

Year1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Num

ber o

f birt

hs

0

1

2

3

4

5

Number of offspring per female per year.

ANOVA P > 0.05 NS

* ** * *

SE_WEAN

Year1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Num

ber w

eane

d

0

1

2

3

Number of squirrels weaned per female per year.

ANOVA P < 0.001

* ** * *

Year1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Num

ber s

urviv

ing

one

year

0

1

2

Number of squirrels born surviving to one year.

ANOVA P < 0.001

* ** * *

• Territory size decreases after a mast year, otherwisesize appears mostly constant

• No significant effect of resource fluctuations on litter size, BUT significant effect on juvenile survival to weaning, 1-yr

Territory Size - temporal summary

Recall: assumption of spatial homogeneity

IS IT?

Spatial vegetation patterns

• Vegetation transects every 60m - 3 transects 1200, 2400, 3600

- each transect 4m x 25m

• Kriged surfaces based on transects (10m2 cell size)- ws density- ws density >5cm dbh, alive- bark beetle killed trees- aspen- willow

60 m

Legend

<VALUE>

0.16 - 1.1

1.2 - 1.9

2 - 2.7

2.8 - 3.6

3.7 - 6.3

# kl_su_midden_gps

Value

0 - 0.0005

0.00051 - 0.025

0.026 - 0.083

0.084 - 0.15

0.16 - 0.23

0.24 - 0.38

<VALUE>

0 - 0.002

0.002 - 0.022

0.023 - 0.063

0.064 - 0.11

0.12 - 0.16

0.17 - 0.25

Total white spruce density

60 m

Legend

<VALUE>

0.16 - 1.1

1.2 - 1.9

2 - 2.7

2.8 - 3.6

3.7 - 6.3

# kl_su_midden_gps

Value

0 - 0.0005

0.00051 - 0.025

0.026 - 0.083

0.084 - 0.15

0.16 - 0.23

0.24 - 0.38

<VALUE>

0 - 0.002

0.002 - 0.022

0.023 - 0.063

0.064 - 0.11

0.12 - 0.16

0.17 - 0.25

Midden placement (total ws den)

60 mWhite spruce (>5cm dbh, alive) density

Legend

<VALUE>

0.098 - 0.49

0.5 - 0.84

0.85 - 1.2

1.3 - 2

2.1 - 3.7

60 mBark beetle killed spruce density

Legend

Value

0 - 0.0005

0.00051 - 0.025

0.026 - 0.083

0.084 - 0.15

0.16 - 0.23

0.24 - 0.38

60 mAspen density

Legend

<VALUE>

0 - 0.045

0.046 - 0.26

0.27 - 0.63

0.64 - 1.1

1.2 - 1.8

60 mWillow density

Legend

Value

0.23 - 0.59

0.6 - 0.79

0.8 - 0.96

0.97 - 1.2

1.3 - 1.6

Spatial patterns in territory size

60 mWhite spruce (>5cm dbh, alive) density and August 2002 territories

Legend

<VALUE>

0.098 - 0.49

0.5 - 0.84

0.85 - 1.2

1.3 - 2

2.1 - 3.7

60 m

Legend

<VALUE>

0.098 - 0.49

0.5 - 0.84

0.85 - 1.2

1.3 - 2

2.1 - 3.7

White spruce (>5cm dbh, alive) density, June and August territories

60 m

Legend

<VALUE>

0.098 - 0.49

0.5 - 0.84

0.85 - 1.2

1.3 - 2

2.1 - 3.7

123

110

170

84

166

579

293

399

139120

28695

5828 41

101

333

57

579

258

429

700

310

652

735

175

400

248

1034

143

122

70

119

40

90

Number of white spruce (>5cm dbh) and August territories

Spatial patterns in cone production

IS IT SPATIALLY HOMOGENEOUS???

• Additional cone count trees established in 2002

• Modelling cone production- independent variables: dbh, density of surrounding trees, dbh of surrounding trees, location (r2 = 0.38)plus.. slope, aspect, height, basal light class (r2 = 0.60)

Cone Production 2002

6760900

6761100

6761300

6761500

6761700

6761900

659800 660000 660200 660400 660600 660800 661000 661200

UTM X

UT

M Y

= 500

6760900

6761100

6761300

6761500

6761700

6761900

659800 660000 660200 660400 660600 660800 661000 661200

UTM X

UT

M Y

= 500

Cone Production 2003

p<0.05

Change in June territory size 2002-03

Goal - to map variation in habitat quality

6760900

6761100

6761300

6761500

6761700

6761900

659800 660000 660200 660400 660600 660800 661000 661200

UTM X

UT

M Y

= 500

=

c

cc

c

c

c

+

Continuing Objectives

• Continue to develop cone production models

• Link spatial and temporal cone availabity and territory size to territory quality & “success”

• Investigate individual contributions to overall population dynamics

Long-Term Food Add Thoughts

• What happens to territory size when under constant high food conditions?

• Will females maintain high reproductive output under high food?

• What’s the key factor for recruitment?

• (What is the effect of lack of cues for increased cone production?)

Summer 2002 – field methods1. Territory mapping

June AugustAdult Female 27 19 Male 9 8

Juvenile Female - 5 Male - 3Total 36 35

Population growth rate

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

KL SU

terr

ito

ry s

ize

(h

a)

June

August

NSpaired t-test

June and August 2002 territory sizes.(paired data only)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

1994 1995 1996 1997 1998 1999 2000 2001

Year

Terr

itory

siz

e (h

a)

* *

Changes in an individual’s territory size