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Table 1 Parameters estimations (Est) for the hurdle models for the three groups of fungi. αi are the parameters of the part of the hurdle model that predicts the probability of occurrence of mushroom production, βi are the parameters of the part of the hurdle model that predicts yield conditional on the probability of mushroom occurrence, vi are variance of year random effect in each part of the hurdle model, Cat1 is a dummy variable set to one for CAT1 group of plots and zero for the rest of the groups, Cat2 is a dummy variable set to one for CAT2 group of plots and zero for the rest of the groups, Cat3 is a dummy variable set to one for CAT3 group of plots and zero for the rest of the groups, CyL1 is a dummy variable set to one for CyL1 group of plots and zero for the rest of the groups, CyL2 is a dummy variable set to one for CyL2 group of plots and zero for the rest of the groups, G is stand basal area (m2·ha− 1), Pag is the accumulated precipitation of August, Pset is the accumulated precipitation of September, Poct is the accumulated precipitation of October, Pnov is the accumulated precipitation of November, Tnov is the mean temperature of November, the term “ln” refers to the natural logarithm. LowB and UpB are the lower and upper bounds of the bootstrapped 95% confidence intervals

From: Yield models for predicting aboveground ectomycorrhizal fungal productivity in Pinus sylvestris and Pinus pinaster stands of northern Spain

All ectomycorrhizal model

Edible model

Marketed model

  

Est

p

LowB

UpB

  

Est

p

LowB

UpB

  

Est

p

LowB

UpB

Cat1

α0

−10.42

0.01

−30,58

−10,08

Cat1

α0

−5,84

0,00

−10,26

−4,28

Cat1

α0

−2,22

0,00

−3,01

−1,68

Cat2

α1

−5.95

0

−14,00

−4,29

Cat2

α1

−3,91

0,00

−11,25

−2,99

Cat2

α1

−1,94

0,00

−2,79

−1,33

Cat3

α2

−6.85

0

−21,37

−5,47

Cat3

α2

−2,47

0,00

−3,40

−2,01

Cat3

α2

−0,86

0,01

−1,27

− 0,54

CyL1

α3

−4.96

0

−9,25

−4,20

CyL1

α3

−2,94

0,00

−3,91

− 2,60

CyL1

α3

−0,92

0,00

−1,26

−0,68

CyL2

α4

−5.88

0

−11,68

−4,46

CyL2

α4

−2,90

0,00

−3,88

−2,55

CyL2

α4

−0,54

0,04

− 0,86

− 0,28

ln (Tnov)

α9

0.99

0.04

0,34

2,44

year

var(v1)

3,09

0,05

2,30

6,51

year

var(v1)

1,37

0,01

1,15

2,40

year

var(v1)

3.09

0.09

2,68

16,96

            

Cat1

β0

2.60

0

0,82

3,95

Cat1

β0

3,10

0,00

1,21

4,46

Cat1

β0

3,01

0,00

1,55

4,35

Cat2

β1

2.63

0

0,81

4,01

Cat2

β1

3,10

0,00

1,13

4,53

Cat2

β1

3,75

0,00

2,22

5,09

Cat3

β2

2.26

0.01

0,45

3,65

Cat3

β2

2,95

0,00

1,14

4,32

Cat3

β2

2,91

0,00

1,41

4,26

CyL1

β3

3.23

0

1,46

4,57

CyL1

β3

3,64

0,00

1,89

5,02

CyL1

β3

3,95

0,00

2,55

5,19

CyL2

β4

2.91

0

1,23

4,13

CyL2

β4

2,70

0,00

1,02

3,99

CyL2

β4

2,62

0,00

1,23

3,87

ln(G/10)

β6

0.97

0.02

0,08

1,57

ln(G/10)

β6

1,15

0,01

0,42

1,69

ln(G/10)

β6

1,42

0,04

0,14

2,61

\( \sqrt{G/10} \)

β7

−1.21

0.01

−1,88

−0,22

\( \sqrt{G/10} \)

β7

−1,23

0,01

−1,85

−0,40

\( \sqrt{G/10} \)

β7

−1,66

0,04

−2,96

−0,22

ln (Pag)

β9

0.18

0

0,07

0,31

ln (Pag)

β9

0,14

0,04

0,02

0,29

ln (Pset)

β8

0,45

0,00

0,26

0,64

ln (Pset)

β10

0.22

0

0,04

0,41

ln (Pset)

β10

0,24

0,01

0,06

0,40

year

var(v2)

0,36

0,02

0,26

0,65

ln (Poct)

β11

0.43

0

0,29

0,61

ln (Poct)

β11

0,23

0,01

0,08

0,42

      

ln (Pnov)

β12

−0.25

0

−0,43

−0,07

ln (Pnov)

β12

−0,27

0,00

−0,45

− 0,08

      

ln (Tnov)

β13

0.36

0

0,19

0,53

ln (Tnov)

β13

0,30

0,01

0,14

0,45

      

year

var(v2)

0.60

0.01

0,49

0,94

year

var(v2)

0,60

0,01

0,48

0,98