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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
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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
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Vegetation Responses Are Often Poorly Predicted by Ungulate Density
Rooney and Waller (2003) FEAM
Suzuki et al. (2008)
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Integrating ungulate density and landscape heterogeneity
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Integrating ungulate density and landscape heterogeneity
Landscape Heterogeneity
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Why Is This Important?
Landscape Heterogeneity
Forest Managers often have little
direct control on deer densities beyond Hunting Pressure & Mitigating Browsing
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Why Is This Important?
Landscape Heterogeneity
Forest Managers may proactively manage
habitat at larger scales to mitigate impact
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Integrating ungulate density and landscape heterogeneity: Study Area
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Integrating ungulate density and landscape heterogeneity: Study Area
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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
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Integrating ungulate density and landscape heterogeneity: Deer Gradient (2013 – Present)
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Integrating ungulate density and landscape heterogeneity: Landscape Gradient (Ongoing)
Landscape Heterogeneity
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Integrating ungulate density and landscape heterogeneity: Landscape Gradient (Ongoing)
Landscape Heterogeneity
LiDAR‐Based Model Landsat‐Based Model
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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**
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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
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Integrating ungulate density and landscape heterogeneity: Deer Impact Measures
Test direct and indirect effects
% %
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Meta‐Model• Embodies causal
relationships.
Percent ESF
# De
erForage Abundance
Structured Analyses: SEM
DeerAbundance
Landscape Heterogeneity(e.g., % Early Successional Forest)
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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)
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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)
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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.
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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
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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
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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
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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)
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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