Ecological Archives E096-253-A1

Nicholas A. Pardikes, Arthur M. Shapiro, Lee A. Dyer, Matthew L. Forister. 2015. Global weather and local butterflies: variable responses to a large-scale climate pattern along an elevational gradient. Ecology 96:2891–2901. http://dx.doi.org/10.1890/15-0661.1

Appendix A. Supplementary information, including detailed monitoring site information, species used in this analysis, presence data over the 23-year monitoring period, correlation matrix, additional ANOVA tables, and results from additional path analyses.

Table A1. A table revealing the sources for local weather values and the months in which data was missing.

Site

Elevation (m)

Weather Station

Missing Data filled in with PPCA

Suisun Marsh

0–1

Fairfield, 042934

(38.2667, -122.06667)

N/A

North Sacramento

8

Sac. FAA Airport, 047630 (38.5069, -121.5)

N/A

West Sacramento

9

Sac. 5 ESE, 047633 (38.55556, -121.95)

N/A

Rancho Cordova

18

PRISM

(39.6241, -121.2777)

N/A

Gates Canyon

190–600

Vacaville, 049200 (38.416667, -121.95)

1988 (April, May, June), 1989 (Nov.), 1990 (March, Dec.), 1994 (Oct.), 1998 (Aug.)

Washington

850–1,200

Nevada City, 6316 (39.26, -121.02)

N/A

Sierra Valley

1,500

Sierraville Ranger Station, 048218 (39.58333, -120.36667)

N/A

Lang Crossing

1,500–1,700

PRISM (39.315, -120.662)

N/A

Donner Pass

2,000–2,200

Sierra Snow Lab, 049998 (39.326, -120.367)

N/A

Castle Peak

2,400–2,775

PRISM (39.3395, -120.3474)

N/A

Notes: Sites are ordered from low to high elevation. Latitude and longitude are provided in parentheses for each weather station. Missing values were filled in using a Probabilistic Principle Coordinates Analysis (PPCA) in the “pcaMethods” package in R (Stacklies et al. 2012). N/A values represent sites that did not have any missing values.

 

Table A2. A list of the 28 butterfly species and their family used in this analysis.

Species

Family

Adelpha bredowii californica

Nymphalidae

Atalopedes campestris

Hesperiidae

Celastrina ladon echo

Lycaenidae

Colias eurytheme

Pieridae

Danaus plexippus

Nymphalidae

Erynnis persius

Hesperiidae

Euchloe ausonides

Pieridae

Hylephila phyleus

Hesperiidae

Junonia coenia

Nymphalidae

Limenitis lorquini

Nymphalidae

Lycaena helloides

Lycaenidae

Nymphalis antiopa

Nymphalidae

Nymphalis californica

Nymphalidae

Nymphalis milberti

Nymphalidae

Ochlodes sylvanoides

Hesperiidae

Papilio rutulus

Papilionidae

Papilio zelicaon

Papilionidae

Phyciodes mylitta

Nymphalidae

Pieris rapae

Pieridae

Plebejus acmon

Lycaenidae

Pontia protodice

Pieridae

Pyrgus communis

Hesperiidae

Satyrium sylvinus

Lycaenidae

Strymon melinus

Lycaenidae

Vanessa annabella

Nymphalidae

Vanessa atalanta

Nymphalidae

Vanessa cardui

Nymphalidae

Vanessa virginiensis

Nymphalidae

 

Table A3. Number of years that each species was seen over the 23-year monitoring period.

Species

SM

NS

WS

RC

GC

WA

SV

LC

DP

CP

A. bredowii californica

14

1

2

14

20

17

9

18

18

8

Atalopedes campestris

19

21

20

20

19

14

8

3

1

1

Celastrina ladon echo

3

4

1

3

16

15

7

17

18

11

Colias eurytheme

21

18

20

19

19

19

16

15

14

6

Danaus plexippus

19

21

21

19

19

18

19

20

16

11

Erynnis persius

2

4

2

4

15

17

3

17

8

2

Euchloe ausonides

19

16

15

11

17

7

17

4

1

7

Hylephila phyleus

19

20

17

18

21

14

3

3

4

7

Junonia coenia

21

19

17

19

22

20

12

19

15

9

Limenitis lorquini

2

13

22

15

17

17

13

19

15

9

Lycaena helloides

20

19

21

10

15

6

16

14

8

3

Nymphalis antiopa

16

18

19

21

17

21

14

19

21

12

Nymphalis californica

13

11

9

18

18

19

17

19

20

13

Nymphalis milberti

2

8

1

3

1

2

5

2

15

13

Ochlodes sylvanoides

16

16

8

19

15

18

16

14

16

10

Papilio rutulus

18

17

18

17

19

19

16

16

19

10

Papilio zelicaon

19

18

19

19

18

18

11

10

18

11

Phyciodes mylitta

18

18

21

21

19

18

18

20

18

7

Pieris rapae

15

18

20

21

17

17

15

16

18

14

Plebejus acmon

19

21

21

19

19

16

16

18

16

11

Pontia protodice

13

14

17

18

11

9

20

11

18

8

Pyrgus communis

18

19

16

21

16

20

19

19

14

13

Satyrium sylvinus

1

17

15

6

18

14

9

14

15

3

Strymon melinus

19

17

19

17

19

17

14

10

13

6

Vanessa annabella

18

21

20

20

21

17

17

16

19

15

Vanessa atalanta

19

19

21

20

20

12

6

9

8

3

Vanessa cardui

21

20

21

22

20

16

20

15

18

16

Vanessa virginiensis

16

19

20

19

16

18

16

16

18

12

Notes: A.M.S. visited each site multiple times throughout the year; therefore years that the butterfly was absent from a particular site are meaningful absences.

 

Table A4. Pearson’s Correlation Coefficients for the variables used in theses analyses.

 

Visits

N

N(t-1)

MinT

MaxT

Precip

SSTA

Visits

1

0.0489

0.066

-0.11

-0.009

0.0143

0.001

N

-

1

0.812

0.020

0.026

0.0038

0.034

N(t-1)

-

-

1

0.0007

-0.015

0.045

-0.024

MinT

-

-

-

1

0.439

0.245

0.155

MaxT

-

-

-

-

1

-0.408

-0.216

Precip

-

-

-

-

-

1

0.129

SSTA

-

-

-

-

-

-

1

Notes: SSTA and local weather variables are z-standardized.

 

Table A5. Results from χ² Type III analyses of deviance for the GLMM, Table 1, Model 1.

Fixed-Effect

χ²

df

Pr(>χ²)

 

(Intercept)

668.5707

1

<0.0001

***

N (t-1)

8557.3922

1

<0.0001

***

SSTA

237.5695

1

<0.0001

***

MaxT

84.1841

1

<0.0001

***

Precip

6.6673

1

0.010

**

MinT

3.9659

1

0.05

*

Notes: The analysis of deviance was performed in the R package “car” (Fox et al. 2015). Variables are ordered from highest to lowest χ² values. The main effect of interest (SSTA) is shown in bold. *indicates significance at P < 0.05.

 

Table A6. Results from χ² Type III analyses of deviance for the GLMM, Table 1, Model 1 (Resident Data).

Fixed-Effect
χ²
df
Pr(>χ²)

(Intercept)

364.6199

1

<0.0001

***

N (t-1)

5181.5489

1

<0.0001

***

SSTA

91.2648

1

<0.0001

***

MaxT

71.7935

1

<0.0001

***

Precip

8.1446

1

0.004

**

MinT

0.5231

1

0.47

 

Notes: The analysis of deviance was performed in the R package “car” (Fox et al. 2015). This model corresponds to Model 1, Table 1, but only uses resident data. Variables are ordered from highest to lowest χ² values. The main effect of interest (SSTA) is shown in bold. *indicates significance at P < 0.05.

 

Table A7. Results from χ² Type III analyses of deviance for the GLMM, Table 1, Model 1 (Non-Resident Data)

Fixed-Effect

χ²

df

Pr(>χ²)

 

(Intercept)

49.6655

1

<0.0001

***

SSTA

191.7437

1

<0.0001

***

N (t-1)

126.6247

1

<0.0001

***

MaxT

7.891

1

0.005

**

Precip

5.3939

1

0.020

*

MinT

0.9715

1

0.324

 

Notes: The analysis of deviance was performed in the R package “car” (Fox et al. 2015). This model corresponds to Model 1, Table 1, but only uses non-resident data. Variables are ordered from highest to lowest χ² values. The main effect of interest (SSTA) is shown in bold. *indicates significance at P < 0.05.

 

Table A8. Results from χ² Type III analyses of deviance for the GLMM, Table 1, Model 1 (Valley Data)

Fixed-Effect

χ²

df

Pr(>χ²)

 

(Intercept)

204.7118

1

<0.0001

***

N (t-1)

2697.164

1

<0.0001

***

SSTA

172.0705

1

<0.0001

***

MaxT

61.315

1

<0.0001

***

Precip

9.8796

1

0.002

**

MinT

0.0999

1

0.752

 

Notes: The analysis of deviance was performed in the R package “car” (Fox et al. 2015). This model corresponds to Model 1, Table 1, but only uses data from the five valley sites. Variables are ordered from highest to lowest χ² values. The main effect of interest (SSTA) is shown in bold. *indicates significance at P < 0.05.

 

Table A9. Results from χ² Type III analyses of deviance for the GLMM, Table 1, Model 1 (Mountain Data)

Fixed-Effect

χ²

df

Pr(>χ²)

 

(Intercept)

283.8398

1

<0.0001

***

N (t-1)

1956.8224

1

<0.0001

***

SSTA

42.3341

1

<0.0001

***

MaxT

10.7295

1

0.0011

**

MinT

9.5517

1

0.0020

**

Precip

1.4842

1

0.2231

 

Notes: The analysis of deviance was performed in the R package “car” (Fox et al. 2015). This model corresponds to Model 1 Table 1, but only uses data from the five mountain sites. Variables are ordered from highest to lowest χ² values. The main effect of interest (SSTA) is shown in bold. *indicates significance at P < 0.05.

 

Table A10. Results from χ² Type III analyses of deviance for the GLMM, Table 1, Model 2.

Fixed-Effect

χ²

df

Pr(>χ²)

 

(Intercept)

582.2475

1

<0.0001

***

N (t-1)

8539.4405

1

<0.0001

***

MaxT

81.617

1

<0.0001

***

Site

70.0246

9

<0.0001

***

SSTA × Site

33.7933

9

<0.0001

***

SSTA

10.9411

1

0.0009

***

Precip

6.9186

1

0.009

**

MinT

4.0445

1

0.0443

*

Notes: The analysis of deviance was performed in the R package “car” (Fox et al. 2015). Variables are ordered from highest to lowest χ² values. The interaction of interest (SSTA × Site) is shown in bold. *indicates significance at P < 0.05.

 

Table A11. Results from χ² Type III analyses of deviance for the GLMM, Table 1, Model 3.

Fixed-Effect

χ²

df

Pr(>χ²)

 

(Intercept)

2954.7533

1

<0.0001

***

N (t-1)

8723.557

1

<0.0001

***

Species

1245.2295

27

<0.0001

***

SSTA × Species

627.1538

27

<0.0001

***

MaxT

82.9208

1

<0.0001

***

Precip

6.9124

1

0.00856

**

MinT

4.2628

1

0.03896

*

SSTA

1.465

1

0.22613

 

Notes: The analysis of deviance was performed in the R package “car” (Fox et al. 2015). Variables are ordered from highest to lowest χ² values. The interaction of interest (SSTA × Species) is shown in bold. *indicates significance at P < 0.05.

 

Table A12. Results from Type III analyses of deviance for the GLMM Table 1, Model 4.

Fixed-Effect

LR χ²

df

Pr(>χ²)

 

Species × Site

5237.3

243

<0.0001

***

Site

909.9

9

<0.0001

***

Species

720.1

27

<0.0001

***

N (t-1)

436.6

1

<0.0001

***

SSTA × Species × Site

268.4

243

0.1259

 

SSTA × Species

74.3

27

2.71E-06

***

MaxT

55.3

1

1.03E-13

***

SSTA × Site

11.9

9

0.2186

 

SSTA

2.6

1

0.1067

 

MinT

0.5

1

0.4847

 

Precip

0.2

1

0.6765

 

Notes: The analysis of deviance was performed in the R package “car” (Fox et al. 2015). Variables are ordered from highest to lowest χ² values. The interaction of interest (SSTA × Species × Site) is shown in bold. *indicates significance at P < 0.05.

 

Table A13. Results from the path analysis in Fig. 4.

Path

Estimate

SE

t value

P value

Visits    →   #Pos. Sightings

0.38

0.01

34.70

< .0001 *

Year     →   Visits

0.18

0.01

14.91

< .0001 *

SSTA    →   MintT

0.15

0.01

12.36

< .0001 *

Precip  →   Visits

0.12

0.02

8.17

< .0001 *

MaxT   →   Visits

0.11

0.02

6.74

< .0001 *

SSTA    →   Precip

0.08

0.01

6.75

< .0001 *

SSTA     →   #Pos. Sightings

0.04

0.01

3.52

0.0004  *

Year     →   Precip

0.04

0.01

2.93

0.0034  *

MaxT    →   Pos. Sightings

0.04

0.02

2.12

0.0342  *

Year     →  MinT

0.03

0.01

2.37

0.0180  *

Precip   →   #Pos. Sightings

0.01

0.01

0.70

0.4824

MinT    →   #Pos. Sightings

0.01

0.02

0.60

0.5506

SSTA    →  #Pos. Sightings (indirect)

-0.02

0.00

-4.27

< .0001 *

Year    →    MaxT

-0.07

0.01

-5.81

< .0001  *

Year     →   #Pos. Sightings

-0.09

0.01

-7.75

< .0001  *

SSTA   →   MaxT

-0.19

0.01

-15.90

< .0001  *

MinT   →   Visits

-0.20

0.02

-12.99

< .0001  *

Notes: Displays model paths and their associated coefficients from Figure 4, including paths that were omitted from the figure for simplicity sake. Paths omitted from Figure 4 are shown in bold. Direct (SSTA #Pos. Sightings) and indirect (SSTA #Pos. Sightings (indirect)) effects of SSTA on the abundance of butterflies are shown in italics. Paths are ordered from most positive to most negative path coefficients. *indicates significance at P < 0.05.

 

Table A14. Results from the path analyses in Fig. 4 for each individual species.

Species

Direct
SSTA Est.

P value
Direct SSTA

Total Indirect
SSTA Est.

P value
Indirect SSTA

V. cardui

0.41

< .0001 *

0.02

0.5248

P. protodice

0.27

< .0001 *

-0.04

0.1611

V. virginiensis

0.14

0.03      *

-0.03

0.2215

J. coenia

0.13

0.001    *

-0.05

0.056

A. campestris

0.12

0.003    *

-0.09

0.0014   *

V. atalanta

0.11

0.0122  *

-0.03

0.2995

C. eurytheme

0.10

0.0033  *

-0.07

0.0123   *

P. acmon

0.10

0.06

-0.04

0.1044

N. milberti

0.08

0.17

-0.04

0.1588

E. ausonides

0.07

0.25

-0.04

0.0719

P. rutulus

0.06

0.27

-0.05

0.0607

D. plexippus

0.06

0.32

-0.01

0.6748

V. annabella

0.05

0.35

0.01

0.5815

S. melinus

0.05

0.21

-0.05

0.0436   *

P. rapae

0.04

0.08

-0.05

0.0557

L. helloides

0.04

0.53

-0.05

0.0604

P. communis

0.04

0.40

-0.07

0.0093   *

S. sylvinus

0.03

0.65

-0.09

0.0024   *

H. phyleus

0.02

0.61

-0.06

0.0153   *

P. myllitta

0.01

0.90

-0.04

0.1417

L. lorquini

-0.01

0.89

-0.01

0.6342

P. zelicaon

-0.03

0.60

0.01

0.7054

E. persius

-0.03

0.67

0.04

0.0952

N. antiopa

-0.05

0.42

-0.04

0.1639

C. ladon echo

-0.06

0.39

0.05

0.0559

N. californica

-0.09

0.18

0.01

0.7184

A. bredowii

-0.10

0.17

0.08

0.008     *

O. sylvanoides

-0.13

0.06

0.04

0.1006

Notes: Species are ordered from highest to lowest direct SSTA estimate. The total indirect SSTA estimates coincide with the dashed line from FIG. 4. χ² values of model fit were all the same for each species (Pr (>χ²=0.7195)). *indicates significance at P < 0.05.

 

Table A15. Results from the path analyses in Fig. 4 when performed for each individual site.

Site

Pr (>χ²)

Direct
SSTA Est.

P value
Direct Est

Total Indirect
SSTA Est.

P value
Indirect Est.

CP

< .0001

0.096

0.017 *

0.0004

0.9767

DP

< .0001

0.032

0.4279

0.0203

0.0533 *

LC

0.0321

0.043

0.3065

-0.0238

0.1324

SV

0.1494

0.035

0.5475

-0.0022

0.9604

WA

0.3216

0.040

0.3745

-0.007

0.7637

GC

0.0049

0.090

0.0417 *

-0.005

0.8163

RC

< .0001

0.046

0.2951

0.0137

0.4679

WS

< .0001

0.021

0.6227

-0.002

0.8979

NS

0.0001

0.043

0.321

-0.006

0.7307

SM

0.1201

0.043

0.3597

-0.0126

0.6183

 

Notes: Sites are ordered from highest to lowest elevation. Higher p values represent greater support for the overall path model. *indicates significance at P < 0.05.

 

Literature Cited

Fox, J., S. Weisberg, D. Adler, D. Bates, G. Baud-Bovy, S. Ellison, D. Firth, M. Friendly, G. Gorjanc, S. Graves, R. Heiberger, R. Laboissiere, G. Monette, D. Murdoch, H. Nilsson, D. Ogle, B. Ripley, W. Venables, A. Zeileis, and R-Core. 2015. car: Companion to Applied Regression.

Stacklies, W., H. Redestig, M. Scholz, D. Walther, and J. Selbig. 2007. pcaMethods—a bioconductor package providing PCA methods for incomplete data. Bioinformatics 23:1164–1167.


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