Ecological Archives E096-211-A3

Anna R. Peschel, Donald R. Zak, Lauren C. Cline, and Zachary Freedman. 2015. Elk, sagebrush, and saprotrophs: indirect top-down control on microbial community composition and function. Ecology 96:23832393. http://dx.doi.org/10.1890/15-0164.1

Appendix C. Fungal and bacterial orders, and, functional genes which significantly drive the difference in taxonomic composition and functional dissimilarity respectively, between treatments.

Table C1. Bacterial orders significantly driving difference in taxonomic composition between treatments. Pearson’s r correlation coefficient shows direction and degree of correlation of orders to PCo axis 1 or 2.

Order

Axis correlation

P value

Pearson’s r correlation coefficient

Actinomycetales

1(-)

<0.0001

-0.93

Pseudomonadales

1(-)

<0.0001

-0.93

Bacteroidales

1(-)

<0.0001

-0.93

Rhizobiales

1(-)

<0.0001

-0.92

Rhodobacterales

1(-)

<0.0001

-0.91

Xanthomonadales

1(-)

<0.0001

-0.89

Bacillales

1(-)

<0.0001

-0.88

Lactobacillales

1(-)

<0.0001

-0.87

Clostridiales

1(-)

<0.0001

-0.87

Burkholderiales

1(-)

<0.0001

-0.86

Enterobacteriales

1(-)

<0.0001

-0.85

Sphingomonadales

1(-)

<0.0001

-0.85

Chroococcales

1(-)

<0.0001

-0.84

Bdellovibrionales

1(-)

<0.0001

-0.84

Selenomonadales

1(-)

<0.0001

-0.83

Spirochaetales

1(-)

<0.0001

-0.83

Vibrionales

1(-)

<0.0001

-0.82

Deinococcales

1(-)

<0.0001

-0.80

Nitrospirales

1(-)

<0.0001

-0.79

Myxococcales

1(-)

<0.0001

-0.78

Erysipelotrichales

1(-)

<0.0001

-0.78

Bifidobacteriales

1(-)

<0.0001

-0.77

Fibrobacterales

1(-)

<0.0001

-0.77

Oscillatoriales

1(-)

<0.0001

-0.77

Cytophagales

1(-)

<0.0001

-0.77

Gloeobacterales

1(-)

<0.0001

-0.76

Caulobacterales

1(-)

<0.0001

-0.72

Desulfuromonadales

1(-)

<0.0001

-0.71

Flavobacteriales

1(-)

<0.0001

-0.69

Verrucomicrobiales

1(-)

<0.0001

-0.68

Thermotogales

1(-)

<0.0001

-0.65

Thermales

1(-)

<0.0001

-0.64

Sphingobacteriales

1(-)

<0.001

-0.60

Solibacterales

1(-)

<0.001

-0.60

Candidatus

1(-)

<0.001

-0.59

Caldilineales

1(-)

<0.001

-0.58

Nostocales

1(-)

<0.001

-0.57

Synergistales

1(-)

<0.001

-0.56

Rhodospirillales

1(-)

<0.001

-0.56

Chlorobiales

1(-)

<0.001

-0.55

Herpetosiphonales

1(-)

<0.001

-0.54

Methylococcales

1(-)

<0.001

-0.53

Neisseriales

1(-)

<0.01

-0.51

Phycisphaerales

1(-)

<0.01

-0.46

Oceanospirillales

1(-)

<0.01

-0.41

Thiotrichales

1(+)

<0.0001

0.70

Caldilineales

2(-)

<0.01

0.50

Chlamydiales

2(+)

<0.01

0.41

Ktedonobacterales

2(+)

<0.01

0.41

Rubrobacterales

2(+)

<0.01

0.43

Hydrogenophilales

2(+)

<0.01

0.51

Thermoanaerobacterales

2(+)

<0.001

0.52

Aeromonadales

2(+)

<0.001

0.58

Rhodocyclales

2(+)

<0.0001

0.64

Acidithiobacillales

2(+)

<0.0001

0.70

 

Table C2. Fungal orders significantly driving the difference in taxonomic composition between treatments. Pearson’s r correlation coefficient shows the direction and degree of correlation for bacterial orders to PCo axis 1 or 2.

Order

Axis correlation

P-value

Pearson's r correlation coefficient

Agaricales

1(-)

<0.0001

-0.90

Eurotiales

1(-)

<0.0001

-0.88

Sordariales

1(-)

<0.0001

-0.86

Onygenales

1(-)

<0.0001

-0.81

Glomerellales

1(-)

<0.0001

-0.81

Saccharomycetales

1(-)

<0.0001

-0.79

Hypocreales

1(-)

<0.0001

-0.76

Dothideales

1(-)

<0.0001

-0.74

Magnaporthales

1(-)

<0.0001

-0.74

Pleosporales

1(-)

<0.001

-0.68

Auriculariales

1(-)

<0.001

-0.67

Microascales

1(-)

<0.001

-0.66

Mucorales

1(-)

<0.01

-0.62

Helotiales

1(-)

<0.01

-0.54

Schizosaccharomycetales

2(+)

<0.05

0.45

Xylariales

2(+)

<0.01

0.57

Capnodiales

2(+)

<0.0001

0.77

 

Table C3. Bacterial gene variants, that encode for lignocellulolytic enzymes, which are responsible for functional dissimilarity between treatments. Pearson’s r correlation coefficient shows the degree and direction of correlation of a gene variant to PCo axis 1 or 2.

Enzymes encoded

by gene variants

Gene family

PCo axis

P value

Pearson’s r correlation coefficient

alpha-amylase

starch

1(-)

<0.001

-0.97

cellobiase

cellulose

1(-)

<0.001

-0.96

alpha-L-arabinofuranosidase

hemicellulose

1(-)

<0.001

-0.95

xylose isomerase

hemicellulose

1(-)

<0.001

-0.93

D-alanine—(R) lactate ligase

vanillin/lignin

1(-)

<0.001

-0.93

phenol oxidase

lignin

1(-)

<0.001

-0.92

pullulanase

starch

1(-)

<0.001

-0.92

endoglucanase

cellulose

1(-)

<0.001

-0.91

isoamylase

starch

1(-)

<0.001

-0.89

cutinase

cutin

1(-)

<0.001

-0.85

glucoamylase

starch

1(-)

<0.001

-0.80

neopullulanase

starch

1(-)

0.022

-0.46

exoglucanase

cellulose

2(-)

0.004

-0.56

glyoxal oxidase

lignin

2(-)

0.005

-0.55

 

Table C4. Fungal gene variants that encode for lignocellulolytic enzymes, which are responsible for functional dissimilarity between treatments. Pearson’s r correlation coefficient shows the degree and direction of correlation of a gene variant to PCo axis 1 or 2.

Enzymes encoded by gene variants

Gene family

PCo axis

P value

Pearson’s r correlation coefficient

phenol oxidase

lignin

1(-)

<0.0001

-0.94

xylanase

hemicellulose

1(-)

<0.0001

-0.93

exoglucanase

cellulose

1(-)

<0.0001

-0.92

Alpha-L-arabinofuranosidase

hemicellulose

1(-)

<0.0001

-0.90

endoglucanase

cellulose

1(-)

<0.0001

-0.90

glucoamylase

starch

1(-)

<0.001

-0.89

glyoxal oxidase

lignin

1(-)

<0.0001

-0.89

cellobiase

cellulose

1(-)

<0.0001

-0.88

alpha-amylase

starch

1(-)

<0.001

-0.87

acetylxylan esterase

cellulose

1(-)

<0.0001

-0.87

manganese peroxidase

lignin

1(-)

<0.000001

-0.82

mannanase

hemicellulose

1(-)

<0.001

-0.71

ligninase

lignin

1(-)

<0.0001

-0.69

cutinase

cutin

1(-)

<0.001

-0.63

vanillin dehydrogenase

vanillin/lignin

1(-)

<0.01

-0.59

 

Literature cited

Riccardi, C. L., S. J. Prichard, D. V. Sandberg, and R. D. Ottmar. 2007. Quantifying physical characteristics of wildland fuels using the Fuel Characteristic Classification System. Canadian Journal of Forest Research 37:2413–2420.

Reiner, A. L., R. J. Tausch, and R. F. Walker. 2010. Estimation procedures for understory biomass and fuel loads in sagebrush steppe invaded by woodlands. Western North American Naturalist 70:312–322.


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