1) Some species like mountain lions and feral pigs showed the strongest negative associations with recreation and shifted their activities away from areas with more recreation. 2) Coyotes were found to shift their diel activity patterns in areas with higher recreation levels. 3) Spatial analyses found no negative associations between recreation and some species like coyotes, bobcats, and opossums, while deer and other species did show negative associations.

1. Effects of non-motorized recreation
on medium and large mammals in
the San Francisco Bay Ecoregion
Michelle L. Reilly

2. Research Topics
1. Impacts of non-
motorized
recreation on
habitat use of
mammals
2. Shifts in diel
activity patterns in
relation to
recreation

3. Research Goals
• Determine how
habitat use is
affected by
recreation in
natural areas.
• Provide guidance
managers
• locate trails and
manage non-
motorized recreation
• do not degrade the
habitat value of
natural areas

4. Background
• Reed and Merenlender
(UC-Berkeley)
• 2008
• Coyote and bobcat
densities, 5x lower in areas
with rec. as opposed to
those without
• 2010
• Species richness 1.7x
greater in areas that
excluded rec.
• Abundance of carnivores
decreased as human
visitor use increased

5. Methods
• Include woodlands
and forested
protected areas
• Attempt to include
areas with varying
levels of recreation
use
• Type of rec
• Include mid-size to
large mammals
Study Design
• Randomly generate site
locations
• Use Reconyx HC600 trail
cameras

6. Study Area
• Over 1.5 million acres are
protected
Counties:
-Marin
-Sonoma
-Napa
-Contra Costa
-Alameda
-Santa Clara
-Santa Cruz
-San Mateo
Santa Cruz
Marin
Sonoma Napa
Contra
Costa
Alameda
Santa Clara
Santa
Cruz
San
Mateo

7. Design
• Plot cameras were
located 180 from one
another
• Offset 33 left
• Sites had a minimum
of 850 m between
them
Site
Plot

8. Analysis
• Use occupancy modeling to
model ‘habitat use’
• Utilized a multi-species
model implemented under
a Bayesian framework in
JAGS
• Hierarchical view allows for
separation of ecological
component and
observation component

9. Results
• 284 surveys conducted
from 2012-2014
• 8 counties and 87
protected areas
• 20,574 camera trap days
• 96% of cameras
functioned for full 15
day sampling period
• 18 species detected
• Recreation (max)
• 456 hikers/day
• 263 bikers/day
• 55 recreationists
with dogs/day
• 28 equestrians/day

10. Site Locations
Species Detected

11. β estimates from multi-species model

12. Summary
• Mt lions and feral pigs had the
strongest association with
recreation (both negative)
• Feral pigs are most impacted
by recreation (2 strongest
associations)
• Lion most impacted native
species
• For native species:
• Hikers = 2 negative
• Bikers = 2 negative
• Dogs = 3 positive; 1 negative
• Equest = 1 positive
• No negative association between
coyote & bobcats (contrary to
Reed & Merenlender)

13. Diel Activity
Patterns
• Determine if presence
of recreation
correlates to shifts in
diel activity patterns
of wildlife
• Describe temporal
patterns of recreation
and wildlife in
protected areas

14. Methods
• Use data from camera
traps
• Parse events to remove
multiple triggers at one
camera ( >60 minutes)
• Recreation diel activity
pattern versus diel
activity pattern of each
species

15. Analysis
• Want to ‘measure’ how
similar activity patterns are
in areas with and without
recreation
• ‘Coefficient of overlap’
measures amount of
agreement of 2 probability
distributions
• Difference in probability for
the 2 distributions is at most
Δ – 1
• Δ =
1 Iff the densities are identical
0 Iff the densities = 0 for all
values of the distribution

16. Weekend vs weekday recreation patterns
A – mountain bikers, B – equestrians, C – hikers, D – recreationsists with dogs

17. Coefficient of Overlap Results
sample size
coefficient of
overlap Confidence interval
all rec
groups (any
amount) 69139
species high rec no rec high rec no rec high rec no rec
coyote 61 194 0.3116 0.50203220.3983349 0.5969582 0.2464625 0.3451229
bobcats 95 367 0.33172 0.39308330.2741478 0.3572055 0.3014132 0.4621459
lions 19 15 0.28543 0.14728420.1202419 0.3958241 0.01544352 0.2332166
fox 727 220 0.0871 0.09625660.05098710 0.08590957 0.03680304 0.1057213
raccoon 232 16 0.11765 0.07616810.05822096 0.1223036 -0.021110917 0.1453786
mule deer 1402 284 0.48087 0.55620560.4491426 0.4970883 0.4968515 0.5946134
skunk 92 220 0.08362 0.0574847 0.03069242 0.08159789 -0.006622896 0.05256344
opossum 100 35 0.05834 0.0547003-0.007330980 0.06259933 -2.969496e-02 0.07983907
Sylvilagus 41 21 0.34724 0.33818170.2394585 0.4126971 0.2084548 0.4574719
feral pig 4 17 0.00692 0.4776839 -0.0392529853 0.03240514 0.2810013 0.6871383

18. Result Summary
• Coyotes shifted activity
patterns in areas with
recreation
• Several species had low
sample sizes
• Not enough data to
make inferences
• Weekend and weekday
patterns of recreation
differs
• But not animal activity
patterns

19. Shift in activity related to recreation

20. Adapted to recreation

21. Activity pattern does not overlap with recreation

22. Summary –
Recreation
• diel activity of non-
motorized recreation
on weekdays differed
from weekends
• 48% more of weekends
• Weekend = 1 peak;
weekday = 2 peaks

23. Summary
• Coyotes shifted activity
patterns levels of rec
• Feral pig shifted activity
in areas with any
recreation but sample
size is very small
• Shift away from daylight
hours and toward
crepuscular or
nighttime hours

24. Overall
Summary
• Spatial analysis- no neg
association between
coyote and rec
• Feral pigs
• Temporal and spatial
• Lions, raccoons, skunk,
deer had neg. spatial
associations
• Sylvilagus – no
association
• Bobcats, opossums – no
negative associations

25. Discussion
• Response influenced by :
• Variation in experience
with humans
• History of exposure to
human
• Availability of alt. habitat
• Presence of other
predators
• Responses vary by
species
• recreation impacts—
either spatially or
temporally—a subset of
species found in
protected areas

26. Management
Implications
• Create buffers in protected
areas or maintain core areas
without trails
• Provide ‘refuge’ for species

27. QUESTIONS?

28. Caveats
• Several species
had low sample
sizes
• Not enough
data to make
inferences

29. Coyotes
(sample size: H =184 and 0=69 captures; p-value = 0.001).

30. Greyfox
(sample size: H=727 and 0=220 captures; (p-value= 0.033).

31. Muledeer
(sample size: H= 1401 and 0=284 captures, (p-value= 0.023).

32. Special Thanks
to:
My committee: Paul Beier,
Derek Sonderegger, Mathias Tobler,
Steve Rosenstock
My Funders: The Gordon and Betty
Moore Foundation
NAU Business Office (Kris Bellmore and
Beth Wixom)
GIS Analyst: Jeff Jenness
California Agencies: NPS, Cal State
Parks, Napa LT, Sonoma LT, Sonoma
Ecology Center, SF Public Utilities,
Conservation Fund,
ALL SF AGENCIES
My technicians: Tom Batter, Elden Holdorff, Sarah Espinosa,
Morgan Gray, Cody Griffin, Tucker Volk, Leanna Lucore, Jacob
Humm, Canyon Miller, Audrey Nickles, Nick Gengler, Kayla Lauger,
Greg Pfau, Ally Coconis, Vanessa Lane-Miller, Kate Galbreath,
Megan Sutton, Bri Halliwell, Caitlyn Cooper