multi-scale effects of landscape heterogeneity and forest management on ungulate browsing: towards a...

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