fire effects on chaparral-associated …...chaparral at 3,000- 3,500 ft elevation • from the heart...
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FIRE EFFECTS ON CHAPARRAL-ASSOCIATED MAMMALS
PROGRESS ON A MULTI-YEAR STUDY FOLLOWING THE CEDAR FIRE
Wayne Spencer - Conservation Biology InstituteJay Diffendorfer - Illinois Natural History SurveyScott Tremor - San Diego Natural History MuseumJan Beyers - USDA Forest Service, Pacific Southwest Research StationGenie Fleming - San Diego Natural History MuseumJulio Angel Soto-Centeno - San Diego Natural History MuseumJenny Duggan - San Diego State UniversityDana Morin - San Diego State UniversityDana Hogan - San Diego State UniversityPaul Schuette - San Diego State University
Funded by USDA/USDI Joint Fire Science Program
W. Spencer
S. Tremor S. Tremor
P. Levine
Short-term Fire Impacts on Mammals
Study Goals: Longer-term fire
effectsFollowing the largest wildfire event in recent
California history:• Track changes in
– Community composition – Species’ distribution– Species’ abundance
• For chaparral-associated mammals:– Rodents– Bats– Carnivores
• As functions of– Fire severity– Distance from unburned edge– Time since fire
Inform fuels management efforts in a hotspot of biological diversity.
D. Hogan
G. & B. Corsi
San Diego Zoo
Study Area Primary Study Area• Community patterns (rodents, bats, and carnivores)• Burned and unburned chaparral at 3,000- 3,500 ft elevation• From the heart of the Cedar Fire to outside its southern perimeter
Secondary Study Area• Rodent demography• Burned and unburned coastal sage scrub.• Pre- and post-burn capture-recapture data
Cedar Fire
Otay Fire
Methods - Rodents• Repeated-measures
sampling design based on occupancy methods of MacKenzie et al. (2002, 2003)
• 40 study plots: – 30 burned
• Ranging from burn edge to ~8 km into burn interior
• Covering range of burn severities
– 10 unburned• 30 Sherman live traps per
plot• Sampled spring and fall for
5 consecutive nights
D. Hogan
Methods – Bats• 36 passive
ultrasonic monitoring stations– 12 unburned– 12 burn edge– 12 burn interior
• Sampled each summer for 3 nights each
• 3 roving survey transects– Unburned– Burn edge– Burn interior
A. Soto-Centano
M. Tuttle
Methods - Carnivores• Game-Vu camera
stations & gypsum track stations– 11 Unburned– 11 Burn edge– 10 Burn interior
• Sampled 3 times per year (winter, spring, fall) for 8 consecutive nights each
P. Schuette
Methods – Vegetation and Other Environmental Variables
• Annual vegetation sampling:– 100 point intercepts per plot– 20 1-m2 quadrats per plot
• Plant cover and height by species and growth form
• Percent ground cover by litter, duff, cryptobiotic crust, etc.
• Burn severity index using shrub skeleton diameters (Keeley 1998)– 40 shrub skeletons/plot
• Distance to “fire refugia”• Soil characteristics
W. Spencer
J. Duggan
W. Spencer
Methods - Analyses• Today:
– Focus on rodent data, using two measures at each site:• Species presence (occupancy)• Species abundance (# unique captures)
– Use hierarchical linear modeling (HLM & HGLM) to explore trends.
• Regression-style, repeated measures techniques• Use burn severity and distance from unburned edge
as covariates
• Eventually: – More complete analyses on all taxa – Use occupancy modeling techniques that control for
differential detection rates– Increased use of multivariate techniques
Unburned Burned
Aver
age
abun
danc
e
0
2
4
6
8
10
12
14
16
18
20
22
Chaetodipus californicus & fallaxDipodomys simulansNeotoma lepidaP. californicus & boyliiPeromyscus eremicusPeromyscus maniculatus
• Community Composition Varies with Burn StatusResults - Rodents
W. Spencer
D. Hogan
K. DuBois
D. Hogan
D. Hogan
S. Tremor
D. Hogan
A. Mercieca
Dulzura Kangaroo Rats Consistently more common on burned areas.
13 19 24 30Time (Months Since Fire)
0.0
0.2
0.4
0.6
0.8
1.0
Pro
por ti
on p
lots
oc c
upie
d (o
bs)
BurnedUnburned
BURN0.0
0.2
0.4
0.6
0.8
1.0 Probability of P
resence (pred)
0.0
0.2
0.4
0.6
0.8
1.0 Probability of P
resence (pred)
Dulzura Kangaroo Rat Abundance trends differ with burn severity.
0
2
4
6
8
10
12
14
16
0
2
4
6
8
10
12
14
16
0
2
4
6
8
10
12
14
16
0
2
4
6
8
10
12
14
16
Time (months since fire)
13 18 24 30
Dip
odom
ys s
imul
ans
abun
danc
e
0
4
8
12
16Unburned Burned-light Burned-medium Burned-severe
W. Spencer
Pocket Mice (Chaetodipus fallax, C. californicus) Abundance trends vary with distance from unburned edge.
0
2
4
6
8
10
12
Cha
etod
ipus
abu
ndan
ce
0
2
4
6
8
10
12
0
2
4
6
8
10
12
0
2
4
6
8
10
12
T im e (m onths since fire )
13 18 24 30
Cha
etod
ipus
abu
ndan
ce
0
2
4
6
8
10
12U nburnedBurned-c lose Burned-m edium farBurned-far
D. Hogan
Pocket Mice (Chaetodipus fallax, C. californicus) Occupancy declined following heavy rains on
burned sites.
13 19 24 30Time (Months Since Fire)
0.0
0.2
0.4
0.6
0.8
1.0
Prop
ort io
n p l
ots
occu
pied
(ob s
)
BurnedUnburned
BURN0.0
0.2
0.4
0.6
0.8
1.0 Probability of P
resence (pred)
0.0
0.2
0.4
0.6
0.8
1.0 Probability of P
resence (pred)
Record Rainfall D. Hogan
Effects of Fire and Rain on San Diego Pocket Mouse, Rancho Jamul Ecological Reserve
Chaetodipus fallax
Date
4-02 8-02 12-02 4-03 8-03 12-03 4-04 8-04 12-04 4-05 8-05 12-05
0
10
20
30
40
No.
Uni
que
Indi
vidu
als
Otay FireRecord winter rains
Brush Mice and California Mice Consistently more common on unburned sites, but evidence of recolonization on burned sites.
13 19 24 30Time (Months Since Fire)
0.0
0.2
0.4
0.6
0.8
1.0
Pro
porti
o n p
l ots
occ
u pie
d by
PE
CA
BO
BurnedUnburned
Burn Status
D. Hogan
Brush Mice and California Mice Weak evidence that fire severity effects abundance trends.
0
4
8
12
16
20
24
28
32
0
4
8
12
16
20
24
28
32
0
4
8
12
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24
28
32
0
4
8
12
16
20
24
28
32
0
4
8
12
16
20
24
28
32
Time (months since fire)
13 18 24 30
P. b
oylii
& c
alifo
nicu
s ab
unda
nce
0
4
8
12
16
20
24
28
32Unburned Burned-light Burned-medium Burned-severe
Deer Mice Somewhat more widespread on burned sites.
13 19 24 30Time (Months Since Fire)
0.0
0.2
0.4
0.6
0.8
1.0
Pro
porti
on p
lots
occ
upie
d (o
bs)
BurnedUnburned
BURN0.0
0.2
0.4
0.6
0.8
1.0 Probability of P
resence (pred)
0.0
0.2
0.4
0.6
0.8
1.0 Probability of P
resence (pred)
Deer Mice Weak evidence of abundance trends varying with fire severity.
0
2
4
6
8
10
12
14
0
2
4
6
8
10
12
14
0
2
4
6
8
10
12
14
0
2
4
6
8
10
12
14
Time (months since fire)
13 18 24 30
Per
omys
cus
man
icul
atus
abu
ndan
ce
0
2
4
6
8
10
12
14Unburned Burned-light Burned-medium Burned-severe
K. DuBois
Cactus Mice No difference in occupancy between burned and
unburned sites.
13 19 24 30Time (Months Since Fire)
0.0
0.2
0.4
0.6
0.8
1.0
Prop
ort io
n pl
ots
occ u
pied
by
PEER
BurnedUnburned
Burn Status
A. Mercieca
Cactus Mice No difference in abundance or trends between burned
and unburned sites.
Tim e (m onths since fire)
13 18 24 30
Per
omys
cus
erem
icus
abu
ndan
ce
0
2
4
6
8Unburned Burned
A. Mercieca
Desert Woodrats Low occupancy everywhere; but evidence of
recolonization following fire.
13 19 24 30Time (Months Since Fire)
0.0
0.2
0.4
0.6
0.8
1.0
Prop
ortio
n pl
ots
o ccu
pied
(ob s
)
BurnedUnburned
BURN0.0
0.2
0.4
0.6
0.8
1.0 Probability of P
resence (pred)L. Ingles
Bats – Calls Recorded by Burn Status
0
2
4
6
8
10
12
14
16
18
20
Unburned Burned Edge Burned Interior
Mea
n N
umbe
r of C
alls
Bat Distribution Relations to burn, unburn, and edge
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
COTO EPFU EUPE MYCA MYCI MYYU NYFE PIHE TABR
Prop
ortio
n of
Cal
ls
UnburnedBurned EdgeBurned Interior
Townsend’s big-eared
bat
Big brown
bat
Western mastiff
bat
California bat
Western small- footed
bat
Yuma bat
Pocketed free-tailed
bat
Western pipistrelle
Brazillian free-
tailed bat
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
COTO EPFU EUPE MYCA MYCI MYYU NYFE PIHE TABR
Prop
ortio
n of
Cal
ls
UnburnedBurned EdgeBurned Interior
Townsend’s big-eared
bat
Big brown
bat
Western mastiff
bat
California bat
Western small- footed
bat
Yuma bat
Pocketed free-tailed
bat
Western pipistrelle
Brazillian free-
tailed bat
Photos: M.D. Tuttle
1
323
32
Carnivore Detection Patterns
• Bobcats detected most often in unburned
• Coyotes detected least often in burn interior
• Gray fox detected most often in burn interior
Tentative Conclusions• More time (and multivariate
analyses) may reveal additional patterns
• Influences on post-fire recovery of chaparral mammal fauna:– Not so important?
• Fire size• Fire severity
– Perhaps more important?• Fire-return intervals (burn
frequency) and type conversion• Fire patchiness
• Avoid extrapolating chaparral results to other communities:• E.g., montane forests
L. Ingles
Source: Keeley (2001)