Effects of Habitat Enrichment on White-Tailed Deer Selective ...

2010 TCTWS Cottam Presentation
By
Ryan L. Darr
Coauthors: Dr. David G. Hewitt, Dr. Timothy E. Fulbright, Dr. Charles A. DeYoung,
Don Draeger, and Dr. Kelley M. Stewart.

Introduction: <strong>Habitat</strong> <strong>Enrichment</strong>
• <strong>Habitat</strong> <strong>Enrichment</strong> –The act <strong>of</strong> providing
wildlife with a high‐quality dietary
supplement that alters dependency on natural
forages 3,16
• Examples
– Supplemental Feed
– Food Plots
– Baits
– Agricultural Products

Selective Foraging
• Selective Foraging –
Choice made to
consume one food
over another 10
• Herbivores select
forages <strong>of</strong> high
nutritional quality and
low toxicity 4,7,19,21

<strong>Effects</strong> <strong>of</strong> <strong>Habitat</strong> <strong>Enrichment</strong> on
Selective Foraging
• <strong>Habitat</strong> enrichment with a high‐quality food
source may increase selective foraging on
high‐quality vegetation 9,16
– <strong>Habitat</strong> enrichment meets a large portion <strong>of</strong>
nutritional needs
– Remainder <strong>of</strong> needs can be met by selecting the
highest‐quality vegetation

Primary Effect
Increase in Selective Foraging
Secondary <strong>Effects</strong>
Vegetation Community
5,11,12,20,23
Tertiary <strong>Effects</strong>
Other Ecosystem Components
2,10,13,14,15,22

Objectives
• Assess the effects <strong>of</strong> habitat enrichment on
selective foraging
• Develop hypotheses concerning vegetation
community and ecosystem effects

Approach and Hypotheses
Two Approaches:
1. Diet Quality (Vegetation Only)
– <strong>Habitat</strong> enrichment would cause deer to select a
higher quality diet
2. Vegetation Quality
– Low, medium, and high‐quality vegetation based
on nutrition
– <strong>Habitat</strong> enrichment would cause deer to select
• More high‐quality vegetation
• Less low and medium quality vegetation

Study Area
• Faith and Comanche
Ranches near Carrizo
Springs, TX
• My study took place in:
– 2, 81‐ha enclosures on
each site (high fenced)
– All maintained at a low
density (0.12 deer/ha)
– One enclosure on each
site provided with
pelleted supplemental
feed*

Stable Isotopes: A Novel Approach
• Stable isotopes used to
estimate supplemental
feed use
• Stable Isotopes ‐ Different
forms <strong>of</strong> an element
varying by atomic mass
• Make up tissues <strong>of</strong> all
organisms
• Transferred from food to
a consumer

Methods: <strong>Habitat</strong> <strong>Enrichment</strong>
• Supplemental Feed
– Designed to differ from natural vegetation
isotope values
– Designed to exceed the quality <strong>of</strong> the vegetation
consumed by deer on the study sites 24

Forage Selection
• Bite Counts
– 8‐10, hand‐raised female
deer distributed among
enclosures
– Permanently maintained in
enclosures
– Data collected seasonally
from Spring 2007 to
Summer 2008
• 2 hours <strong>of</strong> constant foraging
data per deer
• Data collected on
vegetation species, plant
part, and bite size

Diet Quality
• Collected forage samples and representative
bite weights seasonally for each study site
– Quantity based on dry matter not arbitrary bite
size
• Nutritional Analyses
– Detergent fiber, crude protein, gross energy,
radial diffusion (tannin)
• Measures <strong>of</strong> Diet Quality
– Apparent Digestible Protein (DP)
– Apparent Metabolizable Energy (ME)

Stable Isotopes to Determine
Supplement Use
• Tissue Collection
– Tissues collected from supplemented (fed) and
unsupplemented (unfed) deer during spring and
summer.
• Average unfed values gave vegetation isotope value
• Fed values used to determine percent feed use
– Different turnover rates allowed reconstruction <strong>of</strong>
diet during all bite count seasons
• SISUS: Stable Isotope Sourcing Using Sampling
– Stable isotope mixing model based on Bayesian
statistics 8

• Response Variables
– Diet quality
Data Analysis
– Percent Low, Medium, and High‐quality vegetation
consumed
– Established for DP and ME during each season
• Explanatory Variables
– Treatment (Fed or Unfed)
– Percent feed for fed deer only
• Study site included as a block

Data Analysis
• Repeated Measures ANOVA using SAS 9.2
(PROC MIXED)
• Selected best covariance structure based on
Akaike’s information criterion (AIC C )
– Candidate Covariance Structures: CS, AR(1),
ARMA(1,1), TOEP

Results: Bite Counts and Feed Use
• Counted over 157,000 bites
• Feed use:
– Range: 0% to above 90%
– Average: 58.6% (95% CI = 49.3–67.8%)

Diet Quality
• Supplemental feed ME was similar to natural vegetation ME in Spring and Summer 2008
(F 1,44
≤ 1.33, P ≥ 0.2549)

Vegetation Quality Category

Discussion
• Many non‐significant effects
• Results did indicate a few trends
• Clearly habitat enrichment did not cause a direct
increase in selective foraging as hypothesized

Discussion
• Trends were not consistent across seasons or years
– <strong>Effects</strong> <strong>of</strong> habitat enrichment on selective foraging
likely governed by external factors
– e.g.) Rainfall, forage availability, nutrient requirements,
etc.

Discussion
Conclusion:
1. <strong>Habitat</strong> enrichment
influences white‐tailed
deer selective foraging
2. Current hypothesis is too
simple:
• <strong>Habitat</strong> enrichment does
not automatically increase
selective foraging
3. The exact effects likely
depend on multiple
external factors

Discussion
• <strong>Habitat</strong> enrichment could
still have vegetation
community and ecosystem
effects
• <strong>Effects</strong> may be more
complex/less direct than
hypothesized

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Acknowledgements: Financial Contributors
Faith Ranch and
The Stedman West
Foundation
Comanche Ranch and
T. Dan Friedkin
US EPA Greater Research
Opportunities (GRO)
Fellowship Program

Acknowledgements
• Committee Members: Dr. Hewitt, Dr. Fulbright, Dr.
DeYoung, Dr. Stewart
• Comanche‐Faith Project Members: Kent Williamson and
Luke Garver, Eric Grahmann, Matt Moore, Will Moseley,
Luke Garver, Kent Williamson, Nate Kelley, Robin
Donohue, Reagan Gage, and Lalo Gonzalez.
• Statistics Consulting: Dr. Litt
• Technical Assistance: Jimmy Rutledge, Dr. Alice Hempel,
Dr. Joe Bisch<strong>of</strong>f, Brian Jones, Dr. Merav Ben‐David, Dr.
Sajid Bashir, J.R. Hernandez, Dr. Ann Hagerman
• Technicians: Uma Munduru, Don Gillespie, Lavanya
Reddy, Paula Skrobarczyk, and Chuck Coots
• CKWRI Student Volunteers

Thank You!