sites sampled by year a - colorado state...

174

Table 2.1. Temporal and spatial replication of small mammal abundance and microhabitatsamples in the Sacramento Mountains, New Mexico (1991–1996). Asterisks indicate sitessampled also during fall of 1993 and winter and spring of 1994.

Sites Sampled By Year a Habitat 1991 1992 1993 1994 1995 1996

Mid-seral BLUF (0) DELW (27) DELW (60)* DELW (34) DELW (0) DELW (0)Mesic Forest GRES (0) HAYC (1) HAYC (120)* HAYC (0) HAYC (0)

ZINK (0) ZINK (90) ZINK (30) ZINK (0)WAYL (5) WAYL (51) WAYL (65)WIWH (27) WIWH (80) WIWH (14)LWIL (38) LWIL (83)

Replicates: 2 6 6 5 3 1

Late Seral GDSL (121) GDSL (0) GDSL (0)Mesic Forest SUNS (121) SUNS (0)Replicates: 0 0 0 2 2 1

Montane DELW (22) DELW (29)* DELW (54) DELW (0) DELW (0)Meadow HAYC (30) HAYC (35)* HAYC (40) HAYC (0)

WILL (30) WILL (0) WILL (74) WILL (0)LWIL (27) LWIL (0) LWIL (78)WAYL (19) WAYL (32) WAYL (54)WIWH (28) WIWH (0) WIWH (76)

Replicates: 0 6 6 6 3 1

Xeric Forest FIRE1 (0) JAMS (19) JAMS (94)* JAMS (18) JAMS (0) JAMS (0)SIXT (0) CARR (30) CARR (19) CARR (71) CARR (0)

DRYB (31) DRYB (40) DRYB (48) BRYB (0)FIRE2 (22) FIRE2 (99)* FIRE2 (0)TRAL (3) TRAL (118) TRAL (0)WALK (8) WALK (102) WALK (11) WALK (0)

Replicates: 2 6 6 6 4 1 a Number of trap stations where environmental variables were sampled is shown in parentheses. Site names anduniversal transverse mercator coordinates (zone 13) for center of trapping grid: BLUF–Bluff Springs (4303E, 36321N);CARR–Carr Gap (4547E, 36438N); DELW–Delworth (MF:4309E, 36330N; MM:4305E, 36324N); DRYB–Dry Burnt(4473E, 36458N); FIRE1–Fire 1(4552E, 36450N); FIRE2–Fire 2 (4547E, 36446N); GDSL–Goodsell (4322E, 36411N);GRES–Greasy Canyon (4418E 36328N); HAYC–Hay Canyon (MF:4396E, 36295N; MM:4393E, 36298N);JAMS–James Canyon (4447E, 36474N); LWIL–Lower Wills Canyon (MF:4338E, 36311N; MM:4331E, 36311N);SIXT–Sixteen Springs (4541E, 36491N); SUNS–Sunspot (4239E, 36288N); TRAL–Trail Canyon (4444E, 36215N);WALK–Walker (4521E, 36474N); WAYL–Wayland (MF:4375E, 36237N; MM:4375E, 36239N); WILL–Upper WillsCanyon(4304E, 36293N); WIWH–Willie White Canyon (MF:4322E, 36324N; MM:4313E, 36323N); ZINK–Zink Trick(4372E, 36513N).

175

Table 2.2. Attributes sampled at live-trapping stations to characterize habitat types and quantify microhabitat associations of five rodent species occurring in the SacramentoMountains, New Mexico.

SamplingVariable Method a Description

SLOPE PT average between 2 slope (%) measurements using a clinometer ELEV PT elevation to nearest 10 ft (converted to m) taken with an altimeter

HERBCAV PI % herbaceous cover averaged over 10 point-intercepts SHRBCAV PI % shrub cover averaged over 10 point-intercepts TREECAV PI % tree cover averaged over 10 point-intercepts ROCKCAV PI % rock cover averaged over 10 point-intercepts BARECAV PI % bare ground averaged over 10 point-intercepts LITDPAV PI litter depth (cm) averaged over 10 point-intercepts GFHTAV PI maximum grass/forb height (cm) averaged over 10 point-intercepts

SLOG1D and SLOG1V FP density (no./ha) and volume (m3) of stage-1 logs (mid-diam. 10–30 cm) SLOG2D and SLOG2V FP density (no./ha) and volume (m3) of stage-2 logs (mid-diam. 10–30 cm) SLOG3D and SLOG3V FP density (no./ha) and volume (m3) of stage-3 logs (mid-diam. 10–30 cm) SLOG4D and SLOG4V FP density (no./ha) and volume (m3) of stage-4 logs (mid-diam. 10–30 cm) LLOG1D and LLOG1V FP density (no./ha) and volume (m3) of stage-1 logs (mid-diam. >30 cm) LLOG2D and LLOG2V FP density (no./ha) and volume (m3) of stage-2 logs (mid-diam. >30 cm) LLOG3D and LLOG3V FP density (no./ha) and volume (m3) of stage-3 logs (mid-diam. >30 cm) LLOG4D and LLOG4V FP density (no./ha) and volume (m3) of stage-4 logs (mid-diam. >30 cm) LOG5TL FP total length (m) of stage-5 logs SHRBD FP density (no. /ha) of shrubs (species specific) >0.5 m tall CSAPLD FP density (no. /ha) of conifer saplings. DSAPLD FP density (no. /ha) of deciduous saplings. STUMPD FP density (no. /ha) of tree stumps. LC20BA VR basal area (m2 /ha) of live conifer trees using 20 BAF (species specific) LH20BA VR basal area (m2 /ha) of live deciduous trees using 20 BAF (species specific) DC20BA VR basal area (m2 /ha) of dead conifer trees using 20 BAF (species specific) DH20BA VR basal area (m2 /ha) of dead deciduous trees using 20 BAF (species specific) LC20ST VR no. of stems of live conifer trees using 20 BAF (species; size specific) LH20ST VR no. of stems of live deciduous trees using 20 BAF (species; size specific) DC20ST VR no. of stems of dead conifer trees using 20 BAF (species; size specific) DH20ST VR no. of stems of dead deciduous trees using 20 BAF (species; size specific) a PT = point; PI = point-intercept; FP = fixed plot (78.5 m2); VR = variable-radius plot.

Table 2.3. Linear m

odels established a priori (original) and after initial analysis (exploratory) for predicting abundance (g/ha) of deer m

ice (DM

) in the Sacramento M

ountains, New

Mexico during sum

mers of 1992–1994. R

egressor acronyms are defined in the text.

Model Set /

Acronym

Model Structure (sum

mer biom

ass of deer mice =)

Implied Effects

Original /

DM

Global

$0 + $

1CM

CO

NIF + $

2CPR

EVR

AIN

+ $3CG

FHT + $

4CFW

TEMP +

Food supply, fall-winter tem

peratures, availability of $

5CM

ATFEM

+ $6CC

OV

ER !

$7CIN

FCO

MP

mature fem

ales, cover from predation and the

thermal environm

ent, and interspecific interferencecom

petition influence summ

er biomass of deer m

ice..D

MC

1$

0 + $1CM

CO

NIF + $

2CPR

EVR

AIN

+ $3CG

FHT + $

4CFW

TEMP !

$5CIN

FCO

MP

Food supply and fal-winter tem

peratures, andinterference com

petition.D

MC

2$

0 + $1CM

CO

NIF + $

2CPR

EVR

AIN

+ $3CG

FHT + $

4CFW

TEMP !

$5CD

END

EPFood supply, fall-w

inter temperatures, and delayed

density dependence.D

MC

3$

0 + $1CM

CO

NIF + $

2CPR

EVR

AIN

+ $3CG

FHT + $

4CFW

TEMP + $

5CM

ATFEM

Food supply, fall-winter energy dem

and, andavailability of m

ature females.

DM

C4

$0 + $

1CM

CO

NIF + $

2CPR

EVR

AIN

+ $3CG

FHT + $

4CC

OV

ER + $

5CA

LTPREY

Food supply, cover, and release from predation.

DM

C5

$0 + $

1CM

CO

NIF + $

2CPR

EVR

AIN

+ $3CG

FHT !

$4CD

END

EP + $5CA

LTPREY

Food supply, delayed density dependence, andrelease from

predation.D

MC

6$

0 + $1CM

CO

NIF + $

2CPR

EVR

AIN

+ $3CM

ATFEM

+ $4CC

OV

ERFood supply, availability of m

ature females, and

cover.D

MC

7$

0 + $1CM

CO

NIF + $

2CG

FHT + $

3CC

OV

ERM

icrohabitat model.

DM

C8

$0 + $

1CM

CO

NIF + $

2CPR

EVR

AIN

+ $3CFW

TEMP

Food supply and fall-winter tem

peratures.

Table 2.3. (C

ontinued).

Model Set /

Acronym


mer biom

ass of deer mice =)

Implied Effects

Exploratory /

DM

E1$

0 + $1CPR

EVR

AIN

+ $2CG

FHT + $

3CFW

TEMP

Reduced m

odel of food supply and fall-winter

temperatures.

DM

E2$

0 + $1CG

FHT + $

2CFW

TEMP + $

3CM

ATFEM

Reduced m

odel of food supply, fall-winter

temperatures and availability of m

ature females.

DM

E3$

0 + $1CPR

EVR

AIN

+ $2CFW

TEMP + $

3CM

ATFEM

Reduced m

odel of food supply, fall-winter

temperatures and availability of m

ature females.

DM

E4$

0 + $1CPR

EVR

AIN

+ $2CFW

TEMP

Reduced m

odel of food supply and fall-winter

temperatures.

DM

E5$

0 + $1CFW

TEMP

Fall-winter tem

peratures.D

ME6

$0 + $

1CR

SPRA

IN + $

2CFW

TEMP

Food and water supply (indirect) and fall-w

intertem

peratures.D

ME7

$0 + $

1CM

ATFEM

Availability of m

ature females.

Table 2.4. Linear m

odels established a priori (original) and after initial analysis (exploratory) for predicting abundance (g/ha) ofbrush m

ice (BM


ountains, New

Mexico during sum

mers of 1992–1994. R

egressor acronyms are defined in the

text.

Model Set /

Acronym


mer biom

ass of brush mice =)

Implied Effects

Original /

BM

Global

$0 + $

1CPJTR

EE + $2CPR

EVR

AIN

+ $3CSH

RU

BS + $

4CFW

TEMP +

Food supply, fall-winter tem

peratures, availability of $

5CM

ATFEM

+ $6CR

OC

KS !

$7CIN

FCO

MP

mature fem

ales, cover from predation and therm

alenvironm

ent, and interspecific interferencecom

petition for den sites influence summ

er biomass

of brush mice.

BM

C1

$0 + $

1CPJTR

EE + $2CPR

EVR

AIN

+ $3CSH

RU

BS + $

4CR

OC

KS +

Fooda and presence of suitable den sites as m

odified $

5CLSC

OV!

$6CIN

FCO

MP

by interference competition.

BM

C2

$0 + $

1CO

AK

S + $2CPR

EVR

AIN

+ $3CG

FHT + $

4CR

OC

KS +

Foodb and presence of suitable den sites as m

odified $

5CLSC

OV

! $

6CIN

FCO

MP

by competition.

BM

C3

$0 + $

1CPJTR

EE + $2CPR

EVR

AIN

+ $3CSH

RU

BS + $

4CR

SPRA

IN + $

5CFW

TEMP

Fooda supply, w

ater, and fall-winter tem

peratures.B

MC

4$

0 + $1CO

AK

S + $2CPR

EVR

AIN

+ $3CG

FHT + $

4CFW

TEMP

Foodb supply and fall-w

inter temperatures..

BM

C5

$0 + $

1CPJTR

EE + $2CPR

EVR

AIN

+ $3CSH

RU

BS + $

4CR

SPRA

IN +

Fooda, w

ater, cover and den sites. $

5CR

OC

KS + $

6CLSC

OV

BM

C6

$0 + $

1CO

AK

S + $2CPR

EVR

AIN

+ $3CG

FHT + $

4CR

OC

KS + $

5CLSC

OV

Foodb supply, cover, and den sites.

BM

C7

$0 + $

1CPJTR

EE + $2CPR

EVR

AIN

+ $3CSH

RU

BS + $

4CR

SPRA

IN +

Fooda supply, w

ater, cover, and release from $

5CR

OC

KS + $

6CA

LTPREY

predation.

BM

C8

$0 + $

1CO

AK

S + $2CPR

EVR

AIN

+ $3CG

FHT + $

4CR

OC

KS +

Foodb supply, cover, den sites and release from

$5CLSC

OV

+ $6CA

LTPREY

predation.

BM

C9

$0 + $

1CO

AK

S + $2CPR

EVR

AIN

+ $3CG

FHT + $

4CR

OC

KS + $

5CA

LTPREY

Foodb supply, cover, and release from

predation.B

MC

10$

0 + $1CPJTR

EE + $2CPR

EVR

AIN

+ $3CR

SPRA

IN + $

4CM

ATFEM

+Food from

conifers, water, availability of m

ature $

5CR

OC

KS + $

6CLSC

OV

fem

ales, cover and dens.

Table 2.4. (C

ontinued).

Model Set /

Acronym


mer biom

ass of brush mice =)

Implied Effects

Original /

BM

C11

$0 + $

1CO

AK

S + $2CPR

EVR

AIN

+ $3CG

FHT + $

4CM

ATFEM

+Food

b, water, availability of m

ature females, cover,

$5CR

OC

KS + $

6CLSC

OV

and dens. B

MC

12$

0 + $1CPJTR

EE + $2CSH

RU

BS + $

3CR

OC

KS + $

4CLSC

OV

Microhabitat.

BM

C13

$0 + $

1CSH

RU

BS + $

2CM

ATFEM

+ $3CR

OC

KS

Food from shrubs, availability of fem

ales, and cover.

Exploratory /B

ME1

$0 + $

1CPR

EVR

AIN

+ $2CSH

RU

BS + $

3CM

ATFEM

+ $4CR

OC

KS

Food (shrub mast), availability of m

ature females,

and cover.B

ME2

$0 + $

1CPR

EVR

AIN

+ $2CO

AK

S + $3CM

ATFEM

+ $4CR

OC

KS

Food (acorns), availability of mature fem

ales, andcover.

BM

E3$

0 + $1CM

ATFEM

+ $2CR

OC

KS + $

3CIN

FCO

MP

Availability of m

ature females, cover, and

interference competition for rock dens.

BM

E4$

0 + $1CSH

RU

BS + $

2CM

ATFEM

+ $3CR

OC

KS

Food (shrub mast), availability of m

ature females,

and cover.B

ME5

$0 + $

1CO

AK

S + $2CR

OC

KS

Food (acorns) and cover; reduced microhabitat

model.

BM

E6$

0 + $1CM

ATFEM

+ $2CR

OC

KS

Availability of m

ature females and cover.

BM

E7$

0 + $1CM

ATFEM

Availability of m

ature females.

BM

E8$

0 + $1CR

OC

KS

Rock cover.

a Food from

conifer seeds, juniper berries, shrub mast, including acorns from

low-grow

ing oaks.b Food as acorns from

low-grow

ing and tree oaks, and from grass or forb seeds and foliage.

Table 2.5. Linear m

odels established a priori (original) and after initial analysis (exploratory) for predicting abundance (g/ha) ofM

exican voles (MV


ountains, New

Mexico during sum

mers of 1992–1994. R

egressor acronyms are defined in

the text.

Model Set /

Acronym


mer biom

ass of Mexican voles =)

Implied Effects

Original /

MV

Global

$0 + $

1CFW

TEMP + $

2CG

FHT + $

3CR

SPRA

IN + $

4CM

ATFEM

+ $5CIN

FCO

MP +

Fall-winter tem

peratures, summ

er cover, food, and $

6CA

LTPREY

! $

7CD

ENSD

EP w

ater supply, availability of sexually mature fem

ales,interspecific interference com

petition for meadow

sites, release from predation, and delayed density-

dependence influences summ

er abundance ofM

exican voles.M

VC

1$

0 + $1CFW

TEMP + $

2CG

FHT + $

3CR

SPRA

IN + $

4CM

ATFEM

+ $5CA

LTPREY

!Fall-w

inter temperatures, cover, food, and w

ater $

6CD

ENSD

EP supply, availability of m

ature females, release from

predation and delayed density-dependence.M

VC

2$

0 + $1CG

FHT + $

2CR

SPRA

IN + $

3CM

ATFEM

! $

4CD

ENSD

EPSum

mer cover, food, and w

ater supply, availabilityof m

ature females, and delayed density-dependence.

MV

C3

$0 + $

1CFW

TEMP + $

2CG

FHT + $

3CR

SPRA

IN + $

4CA

LTPREY

Fall-winter tem

peratures, summ

er cover, food andw

ater supply, and release from predation.

MV

C4

$0 + $

1CFW

TEMP + $

2CG

FHT + $

3CR

SPRA

INFall-w

inter temperature effects on energy dem

and,sum

mer cover, food and w

ater supply.M

VC

5$

0 + $1CG

FHT + $

2CR

SPRA

IN + $

3CM

ATFEM

+ $4CIN

FCO

MP

Summ

er cover, food, and water supply, availability

of mature fem

ales, effects of interferencecom

petition.M

VC

6$

0 + $1CG

FHT + $

2CR

SPRA

IN + $

3CM

ATFEM

Summ

er cover, food, water supply, and availability

of mature fem

ales.

Table 2.5. (C

ontinued).

Model Set /

Acronym


mer biom

ass of Mexican voles =)

Implied Effects

Original /

MV

C7

$0 + $

1CG

FHT + $

2CM

ATFEM

+ $3CIN

FCO

MP

Summ

er cover and food supply, availability ofm

ature females, and effects of interference

competition.

MV

C8

$0 + $

1CFW

TEMP + $

2CG

FHT + $

3CA

LTPREY

Fall-winter tem

peratures, summ

er food and cover,and release from

predation.M

VC

9$

0 + $1CPSSR

AIN

+ $2CM

ATFEM

+ $3CIN

FCO

MP

Previous summ

er-spring rain as an indirect effect onfood and cover, availability of m

ature females, and

effects of interference competition.

MV

C10

$0 + $

1CG

FHT

Summ

er food and cover; microhabitat effects m

odel.

Exploratory /M

VE1

$0 + $

1CG

FHT + $

2CM

ATFEM

Summ

er food, cover, and availability of mature

females.

MV

E2$

0 + $1CFW

TEMP + $

2CG

FHT + $

3CM

ATFEM

+ $4CIN

FCO

MP

Fall-winter tem

peratures, food, cover, availability ofm

ature females, and interference com

petition.M

VE3

$0 + $

1CG

FHT + $

2CM

ATFEM

! $

3CD

ENSD

EPSum

mer food, cover, availability of m

ature females,

and delayed density dependence.M

VE4

$0 + $

1CG

FHT-Q

+ $2CM

ATFEM

-Q + $

3CD

ENSD

EP-QSum

mer food, cover, availability of fem

ales anddelayed density dependence (m

odeled as quadraticfunction).

MV

E5$

0 + $1CM

ATFEM

Availability of m

ature females.

Table 2.6. Linear m

odels established a priori (original) and after initial analysis (exploratory) for predicting abundance (g/ha) oflong-tailed voles (LV


ountains, New

Mexico during sum

mers of 1992–1994. R

egressor acronyms are defined in

the text.

Model Set /

Acronym


mer biom

ass of long-tailed voles =)Im

plied Effects

Original /

LVG

lobal$

0 + $1CFW

TEMP + $

2CSH

RU

BS + $

3CG

FHT + $

4CM

ATFEM

+ $5CLO

GS +

Fall-winter tem

peratures, food supply, cover, $

6CIN

FCO

MP + $

7CA

LTPREY

availability of sexually m

ature females, interspecific

interference competition and release from

predationinfluences sum

mer biom

ass of long-tailed voles.LV

C1

$0 + $

1CFW

TEMP + $

2CPSSR

AIN

+ $3CSH

RU

BS + $

4CG

FHT + $

5CIN

FCO

MP

Fall-winter tem

peratures, previous summ

er-springrainfall, food supply, cover, and interferencecom

petition.LV

C2

$0 + $

1CFW

TEMP + $

2CSH

RU

BS + $

3CG

FHT + $

4CM

ATFEM

+ $5CIN

FCO

MP

Fall-winter tem

peratures, food supply, cover,availability of m

ature females, and interference

competition.

LVC

3$

0 + $1CSH

RU

BS + $

2CG

FHT + $

3CM

ATFEM

! $

4CD

END

EPFood supply, cover, availability of m

ature females,

and delayed density-dependence. LV

C4

$0 + $

1CSH

RU

BS-Q

+ $2CG

FHT-Q

+ $3CM

ATFEM

-Q !

$4CD

END

EP-QFood supply, cover, availability of m

ature females,

and delayed density-dependence (quadratic function). LV

C5

$0 + $

1CSH

RU

BS + $

2CG

FHT + $

3CM

ATFEM

+ $4CLO

GS + $

5CA

LTPREY

Food supply, cover including logs, availability ofm

ature females, and release from

predation.LV

C6

$0 + $

1CFW

TEMP + $

2CG

FHT + $

3CM

ATFEM

+ $4CLO

GS

Fall-winter tem

peratures, forb-grass supply,availability of m

ature females, and log cover.

LVC

7$

0 + $1CPSSR

AIN

+ $2CSH

RU

BS + $

3CLO

GS

Previous summ

er-spring rainfall, food supply fromshrubs, and log cover.

Table 2.6. (C

ontinued).

Model Set /

Acronym


mer biom

ass of long-tailed voles =)Im

plied Effects

Original /

LVC

8$

0 + $1CSH

RU

BS + $

2CG

FHT + $

3CLO

GS + $

4CA

LTPREY

Food supply, cover, and release from predation.

LVC

9$

0 + $1CSH

RU

BS-Q

+ $2CG

FHT-Q

+ $3CLO

GS-Q

Food supply, and log cover; microhabitat effects

model (quadratic function).

LVC

10$

0 + $1CSH

RU

BS-Q

+ $2CR

SPRA

IN-Q

+ $3CLO

GS-Q

Food from shrubs, extra w

ater from recent spring

rain, and log cover (quadratic function).Exploratory /

LVE1

$0 + $

1CFW

TEMP + $

2CG

FHT + $

3CM

ATFEM

Fall-winter tem

peratures, food and cover from forbs

and grasses, and availability of mature fem

ales.LV

E2$

0 + $1CFW

TEMP + $

2CG

FHT + $

3CM

ATFEM

+ $4CIN

FCO

MP

Fall-winter tem

peratures, food, cover, availability ofm

ature females, and interference com

petition.LV

E3$

0 + $1CFW

TEMP + $

2CM

ATFEM

+ $3CIN

FCO

MP

Fall-winter tem

peratures, availability of mature

females, and interference com

petition.LV

E4$

0 + $1CG

FHT + $

2CM

ATFEM

+ $3CIN

FCO

MP

Food and cover from forbs and grasses, availability

of females, and interference com

petition.LV

E5$

0 + $1CM

ATFEM

+ $2CIN

FCO

MP

Availability of m

ature females and interference

competition.

LVE6

$0 + $

1CG

FHT + $

2CM

ATFEM

Food and cover from forbs and grasses, and

availability of mature fem

ales.LV

E7$

0 + $1CM

ATFEM

Availability of m

ature females.

Table 2.7. Linear m

odels established a priori (original) and after initial analysis (exploratory) for predicting abundance (g/ha) ofM

exican woodrats (M

W) in the Sacram

ento Mountains, N

ew M

exico during summ

ers of 1992–1994. Regressor acronym

s are definedin the text.

Model Set /

Acronym


mer biom

ass of Mexican w

oodrats =)Im

plied Effects

Original /

MW

Global

$0 + $

1CC

SAPL + $

2CSH

RU

BS !

$3CG

FHT + $

4CM

ATFEM

+Food supply, availability of sexually m

ature females,

$5CR

OC

KS + $

6CLG

LOG

! $

7CD

END

EP cover, and delayed density-dependence influencesum

mer biom

ass of Mexican w

oodrats..M

WC

1$

0 + $1CSH

RU

BS !

$2CG

FHT + $

3CM

ATFEM

+ $4CR

OC

KS !

$5CD

END

EPFood from

shrubs and forbs, availability of mature

females, cover, and delayed density-dependence.

MW

C2

$0 + $

1CM

TMG

OK

! $

2CG

FHT + $

3CM

ATFEM

+ $4CR

OC

KS !

$5CD

END

EPFood from

mountain m

ahogony, Gam

bel oak, andforbs, availability of m

ature females, cover, and

delayed density-dependence.M

WC

3$

0 + $1CC

SAPL + $

2CSH

RU

BS + $

3CM

ATFEM

+ $4CR

OC

KS + $

5CA

LTPREY

Food from conifer C

SAPLings and shrubs,


ales, cover, and releasefrom

predation. M

WC

4$

0 + $1CSH

RU

BS + $

2CM

ATFEM

+ $3CR

OC

KS + $

4CLG

LOG

+ $5CA

LTPREY

Food from shrubs, availability of m

ature females,

cover, and release from predation.

MW

C5

$0 + $

1CSH

RU

BS + $

2CM

ATFEM

+ $3CR

OC

KS + $

4CLG

LOG

Food from shrubs, availability of m

ature females, and

cover.M

WC

6$

0 + $1CC

SAPL + $

2CSH

RU

BS + $

3CR

SPRA

IN + $

4CR

OC

KS

Food from conifer C

SAPLings and shrubs, w

aterfrom

spring rains, and cover.M

WC

7$

0 + $1CC

SAPL + $

2CM

TMG

OK

+ $3CR

SPRA

IN + $

4CR

OC

KS

Food from conifer C

SAPLings and m

ountainm

ahogany and Gam

bel oak, water from

spring rains,and cover.

Table 2.7. (C

ontinued).

Model Set /

Acronym


mer biom

ass of Mexican w

oodrats =)Im

plied Effects

Original /

MW

C8

$0 + $

1CFW

TEMP + $

2CC

SAPL + $

3CSH

RU

BS !

$4CG

FHT + $

5CR

OC

KS

Fall-winter tem

perature, food supply, and cover.M

WC

9$

0 + $1CFW

TEMP + $

2CSH

RU

BS + $

3CR

SPRA

IN + $

4CR

OC

KS + $

5CLG

LOG

Fall-winter tem

perature, food from shrubs, w

aterfrom

spring rains, and cover.M

WC

10$

0 + $1CM

TMG

OK

+ $2CM

ATFEM

+ $3CR

OC

KS + $

4CLG

LOG

Food from m

ountain mahogany and G

ambel oak,


ales, and cover.M

WC

11$

0 + $1CC

SAPL + $

2CSH

RU

BS !

$3CG

FHT + $

4CR

OC

KS + $

5CLG

LOG

Food supply and cover; microhabitat effects m

odel.

Exploratory /M

WE1

$0 + $

1CM

ATFEM

+ $2CR

OC

KS + $

3CLG

LOG

Availability of m

ature females, rock cover, and large

log cover.M

WE2

$0 + $

1CM

ATFEM

+ $2CR

SPRA

IN + $

3CR

OC

KS + $

4CLG

LOG

Availability of m

ature females, m

oisture from recent

spring rains, rock cover and large log cover.M

WE3

$0 + $

1CM

ATFEM

+ $2CR

SPRA

IN + $

3CLG

LOG

Availability of m

ature females, m

oisture from recent

spring rains, and large log cover.M

WE4

$0 + $

1CM

ATFEM

+ $2CR

OC

KS

Availability of fem

ales, and rock cover.M

WE5

$0 + $

1CM

ATFEM

+ $2CLG

LOG

Availability of m

ature females and large log cover

MW

E6$

0 + $1CM

ATFEM

+ $2CR

SPRA

INA

vailability of mature fem

ales and moisture from

recent spring rains.M

WE7

$0 + $

1CM

ATFEM

Availability of m

ature females.

186

Table 2.8. Mean summer density ( /ha), mass (g), and biomass ( ; g/ha)

of five murid rodents occurring in three habitats (mesic forest, montane meadow, and xeric forest) of the Sacramento Mountains, New Mexico (1991–1996).

b c

Species (i) Habitat (k) a ( /ha) (g) (g/ha) (g/ha) (%) n1, n2, d

Deer mouse Mesic Forest-L 7.8 15.2 125.5 10.79 9 5, 5, 39Mesic Forest-M 10.6 17.4 175.7 8.78 5 23, 23, 45Montane Meadow 8.4 18.8 157.5 13.45 9 22, 21, 20Xeric Forest 4.9 17.4 84.6 6.18 7 25, 24, 25

Brush mouse Mesic Forest-L 0.1 20.0 1.0 — — 5, 0, 1

Mesic Forest-M 0.3 23.8 8.1 13.21 209 23, 3, 2Xeric Forest 5.8 23.6 138.6 7.22 5 25, 21, 29

Mexican vole Mesic Forest-L 0.4 27.5 10.3 15.33 149 5, 1, 2Mesic Forest-M 1.4 25.6 38.8 39.36 101 23, 4, 4Montane Meadow 59.8 28.4 1739.7 71.61 4 22, 20, 85Xeric Forest 1.5 23.3 38.0 9.65 25 25, 7, 7

Long-tailed Mesic Forest-L 3.3 31.2 104.1 14.32 14 5, 4, 15vole Mesic Forest-M 6.4 33.3 213.5 38.01 18 23, 15, 20

Montane Meadow 11.2 34.9 373.0 70.23 19 22, 17, 18Xeric Forest < 0.1 33.0 0.7 — — 25, 0, 1

Mexican Mesic Forest-L 0.7 122.4 81.2 28.36 35 5, 3, 5woodrat Mesic Forest-M 0.9 120.2 106.1 17.12 16 23, 16, 6

Montane Meadow 0.2 113.9 28.9 53.88 187 22, 2, 2Xeric Forest 1.1 119.6 132.7 14.09 11 25, 21, 7

a For Mesic Forest, L = late seral stage (dominant conifers > 200 yrs old); M = mid-seral stage (dominant conifers 60–100 yrs old).b The square root of the average enumeration error of within each habitat or habitat seral stage.

c CVe is the percent of variation in attributed to enumeration error, relative to the magnitude of .

d n1 is the number of replicates (sites and years) used to estimate mean density and mean biomass; n2 is the number of

replicates where enough captures permitted estimation of the sampling variance of biomass; is the mean number of

individuals captured and marked per replicate. Mean values of density and include zero values for sites or years

where a species was not captured except for brush mice which were never captured in montane meadows and wereexcluded.

Table 2.9. Tem

poral and spatial effects on summ

er biomass (g/ha) of five m

urid rodents occurring in three habitats (m

id-seral mesic forest, m

ontane meadow

, and xeric forest) of the Sacramento M

ountains, New

Mexico (1992–1995).

Long-tailed M

exican D

eer mouse

Brush m

ouse M

exican vole vole

woodrat

Effect ad.f. b

F P

F P

F P

F P

F P

Habitat

2, 7 1.00

0.414 7.29

0.019 4.40

0.058 2.48

0.15428.04

0.001

Year

3, 7 9.74

0.00721.57

0.007 7.91

0.012 5.14

0.034 4.01

0.059

Habitat x Y

ear6, 7

1.750.241

17.380.007

7.500.009

4.270.039

0.940.522

a The effects w

ere quantified as F-ratios between variances estim

ated with a m

ixed model of repeated m

easures of biomass over tim

e and assuming

unstructured covariances.b N

umerator and denom

inator degrees of freedom.

Table 2.10. M

ean biomass (g/ha) of five m

urid rodents occurring in mid-seral m

esic forests and xeric forests of the Sacram

ento Mountains, N

ew M

exico during July–August 1991 and 1992.

n1 b

n2

Species / habitat1991

19921991

19921991

19921991

1992 Z

c P

Deer m

ousem

id-seral mesic forest

783 85

47.1 10.6

2 6

169 23

14.44<0.001

xeric forest 89

110 33.4

8.3 2

6 24

33 0.61

0.541

Brush m

ousem


58 1

19.4 31.5

1 1

12 1

1.56 0.119

xeric forest 44

240 14.6

16.5 1

5 10

45 8.93

<0.001

Mexican vole

mid-seral m

esic forest 95

104 66.4

47.6 1

3 5

7 0.11

0.915xeric forest

74 121

30.2 13.6

1 4

8 19

1.41 0.158

Long-tailed volem


432 516

191.2103.4

2 4

16 49

0.39 0.700

Mexican w

oodratm


55 146

97.8 40.3

1 5

2 5

0.86 0.387

xeric forest 69

185 14.3

28.0 1

6 4

9 3.67

<0.001 a Square root of the enum

eration variance averaged across site replicates.b n

1 = number of sites w

here enough animals w

ere captured and marked to estim

ate enumeration error; n

2 = mean num

ber of marked anim

als used to estim

ate biomass at a given site.

c Z tests Ho : no difference in biom

ass between 1991 and 1992 w

ithin a habitat.

Table 2.11. B

iomass (g/ha) of five m

urid rodents occurring at a mid- and one late-seral m

esic forest site, one montane

meadow

site, and one xeric forest site in the Sacramento M

ountains, New

Mexico during July–A

ugust 1995 and 1996.

n a

Species / seral stage1995

19961995

19961995

1996 Z

1 b P

1 Z

2 c P

2

Deer m

ouselate-seral m

esic forest 52

182 13.8

27.5 22

524.24

<0.0011.72

0.086m


96 260

15.4 36.0

34 72

4.19<0.001

montane m

eadow 204

305 48.1

55.3 19

421.38

0.167xeric forest

53 183

9.9 37.0

22 49

3.41 0.001

Brush m

ousexeric forest

11 71

2.9 16.5

3 19

3.56<0.001

Mexican vole

montane m

eadow4184

2331338.1

353.1244

1073.79

<0.001

Long-tailed volelate-seral m

esic forest 36

390 17.2

51.6 5

526.53

<0.0012.19

0.028m


48 241

15.4 44.3

7 27

4.12<0.001

Mexican w

oodratlate-seral m

esic forest 80

239 58.2

47.5 4

112.13

0.0341.70

0.088m


84 113

57.0 57.0

3 5

0.35 0.725

xeric forest 87

212 33.9

47.2 5

112.15

0.032 a N

umber of m

arked animals used to estim

ate biomass.

b Z1 tests H

o : no difference in biomass betw

een 1995 and 1996 within a seral stage or habitat.

c Z2 tests H

o : no difference in biomass betw

een mesic forest seral stages in 1996.

190

Table 2.12. Seral-stage and year effects on biomass (g/ha) of three rodents occurringin mid- (60–100 yr) and late (>200 yr) seral stages of mesic forest of the SacramentoMountains, New Mexico during July–August 1994 and 1995.

Deer Mouse Long-tailed vole Mexican woodratEffect a df b F P F P F P

Seral stage 1, 3 1.99 0.253 0.20 0.688 1.78 0.274

Year 1, 3 27.59 0.013 * 0.12 0.752 0.53 0.514

Stage x Year 1, 3 0.65 0.478 <0.01 0.952 0.84 0.428 a Effects were tested using a repeated measures, mixed model assuming unstructured covariances.b Numerator, denominator (mid seral = 3 sites; late seral = 2 sites).* Significant at the " = 0.05 level.

Table 2.13. C

oefficients of modeled effects on sum

mer abundance (g/ha) of deer m

ice in the Sacramento M

ountains, New

Mexico

(1992–1994) and weights of m

odel reliability. Sample size (n = 42) is based on 20 sites each sam

pled during 1, 2 or 3 summ

ers. M

odel order based on )A

ICc . R

egressor variables are described in the text and Table 2.3.

DM

aR

2 O

riginal Models

c A

ll Models

d PR

EV-

MA

T-M

odelK

b(%

))

AIC

cW

eight)

AIC

c W

eightIN

TERC

EPTM

CO

NIF

RA

ING

FHT

FWTEM

PFEM

CO

VER

E25

53.5–

–0

0.6701*!

127.768–

–2.226

!26.267

8.214–

E35

49.1–

–3.73

0.1037*!

55.668–

!1.779

–!

39.2197.272

–G

lobal9

61.50

0.4822*3.95

0.0931*22.258

!0.146

!2.509

!2.948

!35.900

8.110!

0.0012C

37

55.00.20

0.4355*4.15

0.0841*!

121.657!

0.500!

0.5491.584

!34.625

8.188–

E73

39.2–

–6.17

0.0306 50.617

––

––

9.479–

C6

647.8

3.590.0800*

7.540.0155

!195.406

!0.598

3.824–

–9.591

!0.0029

E53

29.3–

–12.51

0.0013!

218.138–

––

!52.350

––

E64

30.3–

–14.34

0.0005!

201.316–

––

!45.742

––

E44

30.1–

–14.46

0.0005!

90.604–

!2.568

–!

61.323–

–C

85

32.111.89

0.001315.84

0.0002!

181.098!

0.556!

1.171–

!62.167

––

E15

31.3–

–16.31

0.0002!

82.965–

!2.656

1.100 !

59.540–

–C

17

39.812.45

0.001016.39

0.0002!

46.978!

0.138!

3.145!

4.206!

63.095–

–C

27

33.716.50

0.000120.45

<0.0001!

209.643!

0.408!

0.6840.602

!60.822

––

C7

5 7.1

25.04<0.0001

28.98<0.0001

91.4010.506

–2.052

––

!0.0022

C5

716.3

26.31<0.0001

30.26<0.0001

!472.962

!0.374

8.3082.183

––

–C

47

14.527.19

<0.000131.14

<0.0001!

404.523!

0.3977.292

2.003–

–!

0.0004

Table 2.13. (C

ontinued).

DM

aR

2 O

riginal Models c

All M

odelsd

Model

K b

(%)

)A

ICc

Weight

)A

ICc

Weight

INFC

OM

PA

LTPREY

DEN

DEP

SPRR

AIN

E25

53.5–

–0

0.6701*–

––

–E3

549.1

––

3.730.1037*

––

––

Global

961.5

00.4822*

3.950.0931*

0.879–

––

C3

755.0

0.200.4355*

4.150.0841*

––

––

E73

39.2–

–6.17

0.0306–

––

–C

66

47.83.59

0.0800*7.54

0.0155–

––

–E5

329.3

––

12.510.0013

––

––

E64

30.3–

–14.34

0.0005–

––

2.244E4

430.1

––

14.460.0005

––

––

C8

532.1

11.890.0013

15.840.0002

––

––

E15

31.3–

–16.31

0.0002–

––

–C

17

39.812.45

0.001016.39

0.00020.955

––

–C

27

33.716.50

0.000120.45

<0.0001–

–!

0.848–

C7

5 7.1

25.04<0.0001

28.98<0.0001

––

––

C5

716.3

26.31<0.0001

30.26<0.0001

–!

0.009!

0.949–

C4

714.5

27.19<0.0001

31.14<0.0001

–!

0.009–

– a Linear regression m

odels of deer mouse abundance described in Table 2.3.

b Num

ber of model param

eters estimated from

data including intercept coefficient, effect coefficients, and a residual error term.

c Weighted according to m

inimum

AIC

c value of the nine a priori models.

d Weighted according to m

inimum

AIC

c value of the nine a priori and seven exploratory models.

193

Table 2.14. Precision and relative importance of ecological factors associated withsummer abundance (g/ha) of deer mice in the Sacramento Mountains, New Mexico(1992–1994). Two sets of regression coefficients ( ) are given; those averaged over apriori (original) models and the other averaged over original and exploratory (all) models. CVs of the average coefficients include variation associated with uncertainty ofmodel structure. Relative importance (RI) of each regressor variable is also shown forboth model sets and is based on the sums of Akaike weights for each model that includedthe regressor. Asterisks indicate effects included in the 95% confidence set of models. Regressor acronyms are defined in the text. Factors are ordered from highest to lowestaccording to RI in the original model set.

Original Models All Models Factor CV(%) RI CV(%) RI

MCONIF !0.337 164.1 1.000* !0.065 181.4 0.193*PREVRAIN !1.147 329.7 1.000* !0.408 274.1 0.297*MATFEM 8.243 23.3 0.998* 8.141 23.7 0.997*FWTEMP !32.535 47.5 0.920* !28.083 48.7 0.954*GFHT !0.736 366.9 0.919* 1.349 113.2 0.848*COVER !0.0008 189.2 0.562* !0.0002 203.8 0.109*INFCOMP 0.425 66.7 0.483* 0.082 100.0 0.093*DENDEP !0.0001 151.1 0.000 !0.00002 151.1 0.000ALTPREY .0.a 163.2 0.000 .0.a 163.2 0.000RSPRAIN – – – 0.001 165.4 0.001 a #0.000001

Table 2.15. C


mer abundance (g/ha) of brush m

ice in the Sacramento M

ountains, New

Mexico

(1992–1994) and weights of m


pled during 1, 2 or 3 summ

ers. M


ICc . R


BM

aR

2O

riginal Models

c A

ll Models

d IN

TER-

PREV

-FW

-R

SP-M

odelK

b(%

))

AIC

cW

eight)

AIC

c W

eightC

EPTPJTR

EER

AIN

TEMP

RA

INSH

RU

BS

GFH

T E4

593.5

––

00.3414*

10.159–

––

––

–E7

392.6

––

0.330.2902*

3.942–

––

––

–E6

492.8

––

1.810.1382*

!6.326

––

––

––

E26

93.5–

–2.66

0.0902*!

32.300–

0.572–

––

–E3

593.0

––

2.930.0789*

!9.804

––

––

––

C13

592.8

00.8547*

4.350.0389*

!6.161

––

––

0.0004–

E16

92.9–

–6.17

0.0156134.993

–!

1.842–

–0.0007

–C

118

93.5 4.19

0.1052*8.53

0.0048!

17.350–

0.425–

––

!0.202

C10

893.1

6.950.0265

11.290.0012

156.7360.043

!2.193

–0.430

––

Global

993.4

8.280.0136

12.630.0006

180.8190.038

!2.570

!1.406

–0.0012

–E5

463.4

––

69.95<0.0001

!48.780

––

––

––

E83

58.5–

–72.85

<0.0001!

99.384–

––

––

–C

28

67.971.45

<0.000175.80

<0.0001 100.102

–!

2.352–

––

1.087C

18

67.771.73

<0.000176.07

<0.0001440.910

!0.173

!7.075

––

0.0026–

C4

662.6

71.85<0.0001

76.20<0.0001

37.629–

!1.255

!4.879

––

0.144C

67

63.973.32

<0.000177.67

<0.0001 1.189

–!

1.027–

––

1.190C

97

63.873.41

<0.000177.76

<0.0001!

40.501–

!0.352

––

–0.878

C12

660.5

74.15<0.0001

78.49<0.0001

!91.703

!0.132

––

–0.0024

–C

78

64.875.30

<0.000179.64

<0.0001368.095

!0.126

!7.061

–4.570

0.0019–

C5

864.6

75.52<0.0001

79.87<0.0001

442.653!

0.137!

7.981–

4.6010.0004

–C

88

63.976.37

<0.000180.72

<0.00014.208

–!

1.100–

––

1.084C

37

57.879.82

<0.000184.16

<0.0001999.615

0.077!

11.74035.237

7.5920.0091

–

Table 2.15. (C

ontinued).

BM

aR

2O

riginal Models

c A

ll Models

d M

AT-

INF-

ALT-

Model

K b

(%)

)A

ICc

Weight

)A

ICc

Weight

OA

KS

FEMR

OC

KS

LSCO

VC

OM

PPR

EY E4

593.5

––

00.3414*

0.01116.058

!0.779

––

–E7

392.6

––

0.330.2902*

–17.547

––

––

E64

92.8–

–1.81

0.1382* –

16.6540.432

––

–E2

693.5

––

2.660.0902*

0.01216.076

!0.790

––

–E3

593.0

––

2.930.0789*

–16.313

0.408–

7.112–

C13

592.8

00.8547*

4.350.0389*

–16.646

0.388–

––

E16

92.9–

–6.17

0.0156–

16.4320.077

––

–C

118

93.5 4.19

0.1052*8.53

0.00480.012

16.119!

0.891!

0.0003–

–C

108

93.16.95

0.0265 11.29

0.0012–

16.635!

0.1520.0168

––

Global

993.4

8.280.0136

12.630.0006

–16.197

!0.361

–7.912

–E5

463.4

––

69.95<0.0001

0.027–

1.640–

––

E83

58.5–

–72.85

<0.0001–

–5.165

––

–C

28

67.971.45

<0.000175.80

<0.00010.022

–1.583

0.006028.436

–C

18

67.771.73

<0.000176.07

<0.0001–

–3.854

!0.0574

35.555–

C4

662.6

71.85<0.0001

76.20<0.0001

0.037–

––

––

C6

763.9

73.32<0.0001

77.67<0.0001

0.024–

2.1740.0246

––

C9

763.8

73.41<0.0001

77.76<0.0001

0.025–

2.096–

–0.0005

C12

660.5

74.15<0.0001

78.49<0.0001

––

5.482!

0.0712–

–C

78

64.875.30

<0.000179.64

<0.0001–

–4.800

––

0.0045C

58

64.675.52

<0.000179.87

<0.0001–

–4.751

0.0274–

–C

88

63.976.37

<0.000180.72

<0.00010.024

–2.197

0.0278–

0.0014C

37

57.879.82

<0.000184.16

<0.0001–

––

––

– a Linear regression m

odels of brush mouse abundance described in Table 2.4.

b Num

ber of model param


data, including intercept coefficient, effect coefficients, and a residual error term.


inimum

AIC

c value of the 14 a priori models.


inimum

AIC

c value of the 14 a priori and eight exploratory models.

196

Table 2.16. Precision and relative importance of ecological factors associated withsummer abundance (g/ha) of brush mice in the Sacramento Mountains, New Mexico(1992–1994). Two sets of regression coefficients ( ) are given; those averaged over apriori (original) models and the other averaged over original and exploratory (all) models. CVs of the average coefficients include variation associated with uncertainty ofmodel structure. Relative importance (RI) of each regressor variable is also shown forboth model sets and is based on the sums of Akaike weights for each model that includedthe regressor. Asterisks indicate effects included in the 95% confidence set of models. Regressor acronyms are defined in the text. Factors are ordered from highest to lowestaccording to RI in the original model set.


MATFEM 16.584 6.8 1.000* 16.624 7.3 1.000*ROCKS 0.229 354.6 1.000* !0.234 299.6 0.710*SHRUBS 0.0003 11,095.0 0.868* 0.00002 9,020.6 0.055PREVRAIN !0.048 595.4 0.145* 0.020 945.1 0.112*LSCOV 0.0004 6,168.9 0.132* 0.00002 6,169.1 0.006GFHT !0.021 458.8 0.105* !0.001 460.9 0.005OAKS 0.001 699.3 0.105* 0.005 681.8 0.436*PJTREE 0.002 581.9 0.040 0.00008 582.5 0.002RSPRAIN 0.011 283.0 0.026 0.0005 283.9 0.001INFCOMP 0.107 103.9 0.014 0.566 98.4 0.080*FWTEMP !0.019 239.8 0.014 !0.0009 240.3 0.001ALTPREY .0.a 6,420.0 0.000 .0.a 6,420.0 0.000 a #0.000001

Table 2.17. C


mer abundance (g/ha) of M

exican voles in the Sacramento M

ountains, New

M

exico (1992–1994) and weights of m


pled during 1, 2 or 3 sum

mers. M


ICc . R


MV

aR

2O

riginal Models

c A

ll Models

d IN

TER-

FW-

RSP-

MA

T-IN

F-M

odelK

b(%

))

AIC

cW

eight)

AIC

c W

eightC

EPTTEM

PG

FHT

RA

INFEM

CO

MP

Global

995.5

00.9202*

00.9051*

86.52468.514

76.759!

3.07346.708

35.466C

75

93.25.55

0.0573*5.52

0.0563* !

449.116–

70.484–

35.71431.787

C5

693.4

7.430.0224

7.390.0221

!563.997

–65.872

13.62837.300

30.017E2

693.3

––

8.01 0.0162

!246.431

33.08771.222

–35.375

32.443E3

591.2

––

16.450.0002

!423.390

–89.776

–54.277

–C

26

91.318.60

0.000118.57

0.0001 !

543.283–

83.83013.857

54.065–

C1

892.3

19.62<0.0001

19.51<0.0001

!323.223

61.39181.530

15.01560.016

–C

65

89.723.00

<0.0001 22.96

<0.0001!

748.100–

72.47034.854

42.698–

E14

88.7–

–24.23

<0.0001!

455.142–

86.554–

39.126–

C9

588.7

26.92<0.0001

26.88<0.0001

!376.176

––

–65.920

37.638C

103

83.737.42

<0.0001 37.38

<0.0001!

685.259–

149.040–

––

E45

84.3–

–14.83

<0.0001 !

34.137–

––

––

C4

584.0

41.63<0.0001

41.59<0.0001

!627.210

42.357144.435

22.567–

–C

85

83.742.42

<0.0001 42.38

<0.0001!

788.130!

15.134148.665

––

–E5

381.5

––

42.60<0.0001

!17.029

––

–79.436

–C

36

84.044.34

<0.0001 44.30

<0.0001!

632.79643.965

144.30322.744

––

Table 2.17. (C

ontinued).

MV

aR

2 O

riginal Models

c A

ll Models

d A

LT-PSS-

MA

T- M

odelK

b(%

))

AIC

cW

eight)

AIC

c W

eightPR

EYD

END

EPR

AIN

GFH

T_QFEM

_QD

END

_Q

Global

995.5

00.9202*

00.9051*

!0.121

!6.594

––

––

C7

593.2

5.550.0572*

5.550.0563*

––

––

––

C5

693.4

7.430.0224

7.430.0221

––

––

––

E26

93.3–

–8.05

0.0162–

––

––

– E3

591.2

––

16.480.0002

–!

7.635–

––

– C

26

91.318.60

0.000118.60

0.0001–

!6.812

––

––

C1

892.3

19.62<0.0001

19.62<0.0001

0.302!

8.965–

––

– C

65

89.723.00

<0.0001 23.00

<0.0001 –

––

––

– E1

488.7

––

24.27<0.0001

––

––

––

C9

588.7

26.92<0.0001

26.92<0.0001

––

4.848–

––

C10

383.7

37.42<0.0001

37.42<0.0001

––

––

––

E45

84.3–

–40.80

<0.0001–

––

6.8560.839

0.026C

45

84.041.63

<0.0001 41.63

<0.0001–

––

––

– C

85

83.742.42

<0.0001 42.42

<0.00010.017

––

––

– E5

381.5

––

42.64<0.0001

––

––

––

C3

684.0

44.34<0.0001

44.34<0.0001

0.025–

––

––

a Linear regression m

odels of Mexican vole abundance described in Table 2.5.

b Num

ber of model param


data including intercept coefficient, effect coefficients, and a residual error term.


inimum

AIC

c value of the 11 a priori models.


inimum

AIC

c value of the 11 a priori and five exploratory models.

199

Table 2.18 Precision and relative importance of ecological factors associated withsummer abundance (g/ha) of Mexican voles in the Sacramento Mountains, New Mexico(1992–1994). Two sets of regression coefficients ( ) are given; those averaged over apriori (original) models and the other averaged over original and exploratory (all) models. CVs of the average coefficients include variation associated with uncertainty ofmodel structure. Relative importance (RI) of each regressor variable is also shown forboth model sets and is based on the sums of Akaike weights for each model that includedthe regressor. Asterisks indicate effects included in the 95% confidence set of models. Regressor acronyms are defined in the text. Factors are ordered from highest to lowestaccording to RI in the original model set.


GFHT 76.156 17.7 1.000* 76.080 17.8 1.000*MATFEM 45.869 18.3 1.000* 45.701 18.5 1.000*INFCOMP 35.128 20.5 1.000* 35.076 20.5 1.000*RSPRAIN !2.520 636.9 0.943* !2.478 636.9 0.927*DENDEP !6.069 34.1 0.920* !5.970 34.4 0.905*FWTEMP 63.048 104.3 0.920* 62.548 105.5 0.921*ALTPREY !0.111 118.3 0.920* !0.110 118.4 0.905*PSSRAIN 0.000006 279.4 0.000 0.000006 279.4 0.000GFHT_Q – – – .0.a 100.8 0.000MATFEM_Q – – – .0.a 103.6 0.000DEND_Q – – – .0.a 127.3 0.000 a #0.000001

Table 2.19. C


mer abundance (g/ha) of long-tailed voles in the Sacram

ento Mountains, N

ew

Mexico (1992–1994) and w

eights of model reliability. Sam

ple size (n = 42) is based on 20 sites each sampled during 1, 2 or

3 summ

ers. Model order based on )

AIC

c . Regressor variables are described in the text and Table 2.6.

LVa

R 2

Original M

odelsc

All M

odelsd

INTER

-FW

-M

AT-

INF-

ALT-

Model

K b

(%)

)A

ICc

Weight

)A

ICc

Weight

CEPT

TEMP

SHR

UB

SG

FHT

FEMLO

GS

CO

MP

PREY

E45

79.7–

–0

0.6172*114.612

––

!26.193

35.014–

8.908–

E26

80.3–

–1.52

0.2883* !

98.388!

34.764 –

!26.723

34.093–

8.911–

C2

780.3

00.7190*

4.410.0680*

!93.142

!34.394

!0.0006

!26.842

34.043–

8.914–

Global

982.3

1.880.2810*

6.29 0.0266

!209.982

!58.583

0.0059!

24.39738.155

!0.402

8.593!

0.030E6

461.7

––

24.14<0.0001

!82.765

––

16.45737.878

––

–E1

562.3

––

26.10<0.0001

!293.856

!34.442

–15.939

36.966–

––

C6

664.2

22.22<0.0001

26.64<0.0001

!406.730

!63.980

–12.470

39.301!

0.396–

–C

36

63.123.49

<0.0001 27.91

<0.0001!

105.570–

0.000716.130

32.941–

4.377–

E54

57.1–

– 28.97

<0.0001 !

22.333–

––

35.072–

––

C5

764.2

25.12<0.0001

29.53<0.0001

!37.181

–0.0033

19.39442.188

!0.342

4.305–

E35

58.8–

–29.83

<0.0001 !

194.292!

27.701–

–34.339

––

–E7

348.8

––

33.91<0.0001

!50.938

––

–42.997

–9.096

–C

17

58.331.51

<0.0001 35.92

<0.0001!

858.922!

51.253!

0.0055!

27.171–

––

–C

46

44.840.40

<0.0001 44.81

<0.0001!

65.932–

0.01022.602

33.389–

–!

0.048C

75

34.744.77

<0.000149.18

<0.0001 56.854

–!

0.0121–

–!

0.288–

–C

86

28.951.06

<0.0001 55.47

<0.0001!

633.475–

!0.0177

21.646–

0.347–

!0.003

C10

522.2

52.10<0.0001

56.51<0.0001

!1.541

–!

0.0100–

––

––

C9

517.9

54.38<0.0001

58.79<0.0001

!633.475

–!

0.041419.732

–0.241

––

Table 2.19. (C

ontinued).

LVa

R 2

Original M

odelsc

All M

odelsd

PSS-D

EN-

MA

T-R

SP-M

odelK

b(%

))

AIC

cW

eight)

AIC

c W

eightR

AIN

DEP

GFH

T_QSH

RB

_QFEM

_QLO

GS_Q

RSPR

_QD

END

_QR

AIN

E45

79.7–

–0

0.6172*–

––

––

––

––

E26

80.3–

–1.52

0.2883*–

––

––

––

––

C2

780.3

00.7187*

4.410.0680*

––

––

––

––

–G

lobal9

82.31.88

0.2813*6.29

0.0266–

––

––

––

––

E64

61.7–

–24.14

<0.0001–

––

––

––

––

E15

62.3–

–26.10

<0.0001–

––

––

––

––

C6

664.2

22.22<0.0001

26.64<0.0001

––

––

––

––

–C

36

63.123.49

<0.0001 27.91

<0.0001–

4.502–

––

––

––

E54

57.1–

–28.97

<0.0001–

––

––

––

– 24.878

C5

764.2

25.12<0.0001

29.53<0.0001

––

––

––

––

–E3

558.8

––

29.83<0.0001

9.128–

––

––

––

–E7

348.8

––

33.91<0.0001

––

––

––

––

–C

17

58.331.51

<0.0001 35.92

<0.00017.659

––

––

––

––

C4

644.8

40.40<0.0001

44.81<0.0001

––

––

––

– 0.268

–C

75

34.744.77

<0.000149.18

<0.000113.507

–1.189

!0.000

1.208–

––

–C

86

28.951.06

<0.0001 55.47

<0.0001–

––

!0.000

––

––

–C

105

22.252.10

<0.0001 56.51

<0.0001–

––

––

0.0009 10.696

––

C9

517.9

54.38<0.0001

58.79<0.0001

––

1.156 !

0.000–

0.0011–

––

a Linear regression m

odels of long-tailed vole abundance described in Table 2.6.b N

umber of m

odel parameters estim

ated from data including intercept coefficient, effect coefficients, and a residual error term

.c W

eighted according to minim

um A

ICc value of the 11 a priori m

odels.d W


um A

ICc value of the 11 a priori and seven exploratory m

odels.

202

Table 2.20 Precision and relative importance of ecological factors associated withsummer abundance (g/ha) of long-tailed voles in the Sacramento Mountains, NewMexico (1992–1994). Two sets of regression coefficients ( ) are given; those averagedover a priori (original) models and the other averaged over original and exploratory (all) models. CVs of the average coefficients include variation associated with uncertainty ofmodel structure. Relative importance (RI) of each regressor variable is also shown forboth model sets and is based on the sums of Akaike weights for each model that includedthe regressor. Asterisks indicate effects included in the 95% confidence set of models. Regressor acronyms are defined in the text. Factors are ordered from highest to lowestaccording to RI in the original model set.


MATFEM 35.200 14.9 1.000* 34.767 13.6 1.000*INFCOMP 8.823 17.6 1.000* 8.901 17.2 1.000*GFHT !26.152 32.6 1.000* !26.343 30.8 1.000*FWTEMP !41.208 91.3 1.000* !13.918 112.7 0.383*SHRUBS 0.0012 748.0 1.000* 0.0001 750.6 0.095*LOGS !0.113 93.4 0.281* !0.011 114.1 0.027 ALTPREY !0.0086 119.9 0.281* !0.0008 136.7 0.027MATFEM_Q .0.a 103.5 0.000 .0.a 103.5 0.000GFHT_Q .0.a 104.3 0.000 .0.a 104.3 0.000RSPR_Q .0.a 104.9 0.000 .0.a 104.9 0.000PSSRAIN .0.a 110.9 0.000 0.000002 106.5 0.000DEND_Q .0.a 112.5 0.000 .0.a 112.5 0.000DENDEP 0.00003 131.2 0.000 0.000002 131.2 0.000LOGS_Q .0.a 184.7 0.000 .0.a 184.7 0.000SHRB_Q .0.a 307.4 0.000 .0.a 307.4 0.000RSPRAIN – – – 0.000008 106.4 0.000 a #0.000001

Table 2.21. C


mer abundance (g/ha) of M

exican woodrats in the Sacram

ento Mountains,

New

Mexico (1992–1994) and w

eights of model reliability. Sam

ple size (n = 42) is based on 20 sites each sampled during 1, 2

or 3 summ

ers. Model order based on )

AIC

c . Regressor variables are described in the text and Table 2.7.

MW

aR

2O

riginal Models

c A

ll Models

d IN

TER-

MA

T-M

odelK

b(%

))

AIC

cW

eight)

AIC

c W

eightC

EPTC

SAPL

SHR

UB

SG

FHT

FEMR

OC

KS

E73

67.3–

–0

0.3873*20.271

––

–61.295

–E6

468.2

––

1.300.2021*

!5.460

––

–61.288

–E4

467.5

––

2.130.1333*

28.118–

––

63.051!

0.329E5

467.4

––

2.340.1204*

22.717–

––

61.606–

E35

68.2–

–3.81

0.0576*!

3.080–

––

61.540–

E15

67.8–

– 4.34

0.0442*36.734

––

–64.508

!0.486

E26

68.5–

– 6.18

0.0176*10.510

––

–63.850

!0.386

C5

668.1

00.3597*

6.710.0135

34.203–

!0.0018

–64.324

!0.238

C10

667.8

0.320.3065*

7.030.0115

34.315–

––

64.430!

0.448C

17

68.22.76

0.0905*9.47

0.003414.800

–!

0.00180.737

62.669!

0.009C

47

68.12.89

0.0846*9.61

0.003234.379

–!

0.0018–

64.317!

0.240C

37

68.03.07

0.0776*9.78

0.002922.858

0.006!

0.0020–

63.092!

0.125C

27

67.93.09

0.0766*9.81

0.002911.642

––

0.93262.617

!0.144

Global

968.4

8.810.0044

15.530.0002

18.862 0.016

!0.0016

0.79962.621

!0.337

C7

618.3

39.49<0.0001

46.20<0.0001

!38.784

0.092–

––

0.519C

66

18.239.52

<0.000146.24

<0.0001 !

31.2910.096

!0.0007

––

0.456C

117

20.241.38

<0.0001 48.10

<0.0001!

56.400 0.094

!0.0014

3.463–

1.480C

87

17.742.68

<0.0001 49.40

<0.0001!

49.598 0.113

!0.0007

2.731–

0.721C

98

23.342.80

<0.0001 49.51

<0.0001226.828

0.084!

0.0003–

–!

0.267

Table 2.21. (C

ontinued).

MW

aR

2 O

riginal Models

c A

ll Models

d D

EN-

ALT-

MTM

-FW

-R

SP-M

odelK

b(%

))

AIC

cW

eight)

AIC

c W

eightLG

LOG

DEP

PREY

GO

KTEM

PR

AIN

E73

67.3–

–0

0.3873*–

––

––

–E6

468.2

––

1.300.2021*

––

––

–2.301

E44

67.5–

–2.13

0.1333*–

––

––

–E5

467.4

––

2.340.1204*

!0.121

––

––

–E3

568.2

––

3.81 0.0576*

!0.098

––

––

2.265E1

567.8

––

4.340.0442*

!0.241

––

––

–E2

668.5

––

6.180.0176*

!0.195

––

––

2.049C

56

68.10

0.3597*6.71

0.0135 !

0.189–

––

––

C10

667.8

0.320.3065*

7.030.0115

!0.252

––

0.0037–

–C

17

68.22.76

0.0905*9.47

0.0034 –

3.854–

––

–C

47

68.12.89

0.0846*9.61

0.0032 !

0.190–

!0.0001

––

–C

37

68.03.07

0.0776*9.78

0.0029–

–0.0016

––

–C

27

67.93.09

0.0766*9.81

0.0029–

3.129–

0.0017–

–G

lobal9

68.4 8.81

0.004415.53

0.0002!

0.1723.621

––

––

C7

618.3

39.49<0.0001

46.20<0.0001

––

–0.0072

–4.812

C6

618.2

39.52<0.0001

46.24<0.0001

––

––

–4.603

C11

720.2

41.38<0.0001

48.10<0.0001

0.796–

––

––

C8

717.7

42.68<0.0001

49.40<0.0001

––

––

!4.377

–C

98

23.342.80

<0.0001 49.51

<0.00010.877

––

–48.250

9.519 a Linear regression m

odels of Mexican w

oodrat abundance described in Table 2.7.b N

umber of m

odel parameters estim

ated from data including intercept coefficient, effect coefficients, and a residual error term

.c W


um A

ICc value of the 12 a priori m

odels.d W


um A

ICc value of the 12 a priori and seven exploratory m

odels.

205

Table 2.22 Precision and relative importance of ecological factors associated withsummer abundance (g/ha) of Mexican woodrats in the Sacramento Mountains, NewMexico (1992–1994). Two sets of regression coefficients ( ) are given; those averagedover a priori (original) models and the other averaged over original and exploratory (all) models. CVs of the average coefficients include variation associated with uncertainty ofmodel structure. Relative importance (RI) of each regressor variable is also shown forboth model sets and is based on the sums of Akaike weights for each model that includedthe regressor. Asterisks indicate effects included in the 95% confidence set of models. Regressor acronyms are defined in the text. Factors are ordered from highest to lowestaccording to RI in the original model set.


MATFEM 63.972 12.7 1.000* 61.867 11.4 1.000*ROCKS !0.264 297.0 1.000* !0.082 201.1 0.233*LGLOG !0.162 200.5 0.755* !0.040 269.9 0.268*SHRUBS !0.00110 180.8 0.617* !0.0000 4 201.9 0.023MTMGOK 0.00125 604.3 0.383* 0.00005 609.2 0.014GFHT 0.142 192.2 0.172* 0.005 199.8 0.006DENDEP 0.604 356.9 0.172* 0.023 361.1 0.006ALTPREY 0.000119 1,135.2 0.162* 0.000004 1,136.4 0.006CSAPL 0.00056 571.3 0.082* 0.00002 572.6 0.003 FWTEMP .0.a 199.7 0.000 .0.a 199.7 0.000RSPRAIN .0.a 126.6 0.000 0.632 121.5 0.277* a #0.000001

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Table 2.23. Regressor variables ranked as most important effects on summer abundance (g/ha) of five rodent species in the Sacramento Mountains, New Mexico,during 1992–1994. Two sets of effects are shown, those determined from a priori(original) models and those from original and exploratory (all) models.

Original Models All Models Species Effecta RIb CV%c Signd Effecta RIb CV%c Signd

Deer mouse MCONIF 1.000 164.1 !, ? MATFEM 0.997 23.7 +, +*PREVRAIN 1.000 329.7 !, +* FWTEMP 0.954 48.7 !, !MATFEM 0.998 23.3 +, +* GFHT 0.848 113.2 +, +*

Brush mouse MATFEM 1.000 6.8 +, +* MATFEM 1.000 7.3 +, +*ROCKS 1.000 354.6 +, +* ROCKS 0.710 299.6 !, +*SHRUBS 0.868 11,095.0 +, +* OAKS 0.436 681.8 +, +*

Mexican vole GFHT 1.000 17.7 +, +* GFHT 1.000 17.8 +, +*MATFEM 1.000 18.3 +, +* MATFEM 1.000 18.5 +, +*INFCOMP 1.000 20.5 +, +* INFCOMP 1.000 20.5 +, +*

Long-tailed MATFEM 1.000 14.9 +, +* MATFEM 1.000 13.6 +, +*vole INFCOMP 1.000 17.6 +, +* INFCOMP 1.000 17.2 +, +*

GFHT 1.000 32.6 !, +* GFHT 1.000 30.8 !, +*FWTEMP 1.000 91.3 !, vSHRUBS 1.000 748.0 +, !

Mexican MATFEM 1.000 12.7 +, +* MATFEM 1.000 11.4 +, +*woodrat ROCKS 1.000 297.0 !, v

LGLOG 0.755 200.5 !, ?SHRUBS 0.617 180.8 !, ?

a MCONIF—density ( /ha) of mature conifers; PREVRAIN—total rainfall (cm) during two previous growing

seasons (March–August); MATFEM—number of reproductively active females in the summer population;FWTEMP—mean minimum temperature (°C) during late fall and winter; GFHT—mean maximum height (cm) ofgrasses or forbs; ROCKS—mean percentage of rock cover (arcsine-square root transformed); SHRUBS—density of allshrubs; OAKS—density of shrub and tree-sized oaks; INFCOMP—density of species likely to interfere with use ofspace during the same summer; LGLOG— density of logs >30 cm in diameter at mid-point.b Relative importance based on Akaike weights of models for a given species.c Coefficient of variation of model-averaged estimates of effect coefficients.d Sign of model-averaged coefficient followed by sign of relationship in bivariate plots of indicated variable withsummer abundance of listed species; v indicates a quadratic relationship and ? indicates an unclear relationship; *denotes agreement of bivariate relationships with envirogram predictions.

sites sampled by year a - colorado state...

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