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The Effects of Landscape Heterogeneity and Ungulate
Density on Understory Vegetation in Northwestern
PennsylvaniaAlejandro Royo1, Dave Kramer2, Susan Stout1, Nate Nibbelink2, and Karl Miller2
1U.S. Forest Service: Northern Research Station, 2University of Georgia, and
Hypothesized Relationships Between Ungulate Density and Understory Plants
Growth orR
eprodu
ction or
Survival
of Und
erstory Plan
ts
Ungulate Density
Linear
Non‐Linear
Non‐Linear with Threshold
Vegetation Responses Are Often Poorly Predicted by Ungulate Density
Rooney and Waller (2003) FEAM
Suzuki et al. (2008)
Integrating ungulate density and landscape heterogeneity
Integrating ungulate density and landscape heterogeneity
Landscape Heterogeneity
Why Is This Important?
Landscape Heterogeneity
Forest Managers often have little
direct control on deer densities beyond Hunting Pressure & Mitigating Browsing
Why Is This Important?
Landscape Heterogeneity
Forest Managers may proactively manage
habitat at larger scales to mitigate impact
Integrating ungulate density and landscape heterogeneity: Study Area
Integrating ungulate density and landscape heterogeneity: Study Area
Integrating ungulate density and landscape heterogeneity: Deer Gradient (2013 – Present)
Methods(1) We conduct yearly deer pellet
group counts within each block.
(2) Current mean deer densities < 1 – 14.9 deer/km2. Overall mean: 6.75 deer/km2.
Landscape Heterogeneity
Integrating ungulate density and landscape heterogeneity: Deer Gradient (2013 – Present)
Integrating ungulate density and landscape heterogeneity: Landscape Gradient (Ongoing)
Landscape Heterogeneity
Integrating ungulate density and landscape heterogeneity: Landscape Gradient (Ongoing)
Landscape Heterogeneity
LiDAR‐Based Model Landsat‐Based Model
Integrating ungulate density and landscape heterogeneity: Deer Impact (2013 – Present)
Methods & Early Results(1) 25 Experimental Sites(2) 0.4 ha exclosure and paired control.(3) Vegetation monitoring subplots
Variable Control FenceSdlg. Density (#/m2) 22.4 21.1
Richness (species/m2) 3.36 4
Sdlg. Height (cm) 16.4 20.2
Sprout Height (cm) 55.7 83.3**
Deer Impact on Stump Sprouts
Deer Density
5 10 15 20 25 30
Dee
r Im
pact
: Hei
ght
ln (X
C/X
F)
-1.8
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6P > F = 0.003;R2 = 0.47
Integrating ungulate density and landscape heterogeneity: Deer Impact Measures
Integrating ungulate density and landscape heterogeneity: Deer Impact Measures
Test direct and indirect effects
% %
Meta‐Model• Embodies causal
relationships.
Percent ESF
# De
erForage Abundance
Structured Analyses: SEM
DeerAbundance
Landscape Heterogeneity(e.g., % Early Successional Forest)
Meta‐Model• Embodies causal
relationships.
• Systems Approach‐ Variables can be responses & predictors
Structured Analyses: SEM
DeerAbundance
Deer Impact on Understory(e.g., Seedling Height
Landscape Heterogeneity(e.g., % Early Successional Forest)
Meta‐Model
Structured Analyses: SEM
• Embodies causal relationships.
• Systems Approach‐ Variables can be responses & predictors
‐ Indirect & Direct Effect
•Test entire hypotheses vs. individual processes
DeerAbundance
Deer Impact on Understory(e.g., Seedling Height)
% Fern Cover
Landscape Heterogeneity(e.g., % Early Successional Forest)
Added Collaborations: If you build it, they will come….
• Large‐scale replication with variation in important edaphic/light conditions.
• Spatially explicit pellet deposition/variable deer densities.
• Habitat characterization/Fragmentation.• Vegetation Surveys.
Added Collaborations: If you build it, they will come….
Deer – Habitat Usage: Spatially explicit fecal pellet deposition to assess over‐winter deer habitat use.
Joshua Paradise (Allegheny College) – Senior Thesis
Added Collaborations: If you build it, they will come….
Deer ‐ Forage: Browsing may limit forage (biomass) quantity, but may increase forage nutritional quality (e.g., Forage Conditioning Hypothesis/Compensatory Growth Hypothesis).
Tamara Johnstone‐Yellin & Christina Teter(Bridgewater College) – Honor’s Thesis NRS‐02 JRVA Grant
Added Collaborations: If you build it, they will come….
Chestnut Reintroductions: Effect of site quality and deer browsing on chestnut establishment and survival.
Leila Pinchot (USDA Forest Service)NRS‐02, NRS‐16 & Univ. of Tennessee
Added Collaborations: If you build it, they will come….
Lyme Disease Risk: Habitat fragmentation, vertebrate hosts, and disease risk: Dilution Effect Hypothesis
Thomas Simmons and Joe Duchamp (IUP)FPDC Seed Grant (2015)
Acknowledgements & Questions
• Voluntary participation of seven (7) public and private land‐management Agencies (Allegheny NF, Kane Hardwood, Forest Investment Associates, Bradford Water Authority, PA Bureau of Forestry, Hancock Timber Co., Landvest)
• Ed Vandever + 16 technicians, including 12 undergraduates.
• Funding sources:
USDA‐AFRI: Award #12‐IA‐11242302‐093Forest Service; Northern Research StationUniversity of Georgia: Warnell School