Deer+Agents

=** white-tailed deer ** (// Odocoileus virginianus //)=

=Overview=

White tailed deer represent a useful potential model organism because they represent a relatively stable and successful population of organisms with good quantitative data. Unfortunately, data collection is typically biased towards unstable populations which are threatened or endangered.

Management typically aims to promote large populations that are well below carrying-capacity; in the absence of sufficient predators, allowing the population to approach maximum densities would result in an endogenously applied limit to growth, in the form of starvation and disease. This would result in a decline across all individuals; instead, management strives to maintain healthy individuals by lowering densities, typically aiming for targets around 60-65% of the biological carrying capacity (//K//) (data). //K// represents the stable equilibrium between the deer-vegetation system. Currently populations in the Northern Forest region (which includes Vilas county) are around 70% of //K// (Anonymous 2001 ).

The increased food source as a result of the agricultural matrix in southern wisconsin increases carrying capacity; however, this also increases the connectivity of individuals, and in turn increases the opportunity for communicable diseases (like CWD) to take hold.

Snow depths (>45cm, Hosley 1956) restrict deer movement and also reduce amount of available forage.

A large amount of information regarding deer management in Wisconsin is provided in a publication produced by the Wisconsin DNR

=Internal State=


 * Internal Motivators
 * food
 * foraging behavior
 * detailed metabolic model (down to the individual chews) available (Moen et al 1997)
 * reliance on variable acorn masting (McShea and Schwede 1993)
 * shelter
 * particularly winter yarding - greater social tolerance (higher densities)
 * mating
 * mate searching
 * reproductive
 * 'birthing zone' - 20-25 exclusive acres (Marchington and Hirth 1984)

=Energy Budget=


 * metabolism drops in winter, rises in growing season
 * detailed metabolic models available from Moen 1978

=Motion Capacity=


 * Daily movement estimates (from Webb et al 2010) - central Oklahoma
 * Male movement
 * during rut: 7,363m ± 364
 * post-rut: 6,156m ± 260
 * Female movement
 * pre-birth: 2,682m ± 121
 * pregnant: 2,902 m ± 107
 * post-birth; 3,357m ± 91

=Behavior=


 * congregate in open areas (Lagory 1986)
 * membership of congregating group is completely open (Lagory 1986 + within)
 * widely dispersed resource (browse allows spreading the risk of predation (Lagory 1986 + within)
 * spread out in areas of cover (Lagory 1986)

=Habitat Utilization=

The DNR classifies **deer range** as "...all permanent cover—forest, woodlot, brush-covered land or marsh—at least ten acres or more in size. Because deer often use farm ﬁelds adjacent to permanent cover, 330 feet into these ﬁelds is also included in calculations of the amount of deer range in a deer management unit." (WDNR 1998) = = Habitat utilization can be broken down into three primary requirements (//al a// Felix et al 2004):
 * 1) Fall and winter food potential (FWFP) = (2 x browse_index + mast_index) / 3 x site_quality_index
 * 2) browse_index = (browse_quality_index + browse_availability_index) / 2
 * 3) browse_quality_index = 0-1 ranking based on palatability and nutrition of species (//Thuja occidentalis// = 1, //Abies balsema// = 0.25, fill in the rest)
 * 4) brose_availability_index = index describing accessibility of browse;
 * 5) deciduous forest: ages 0 - 10 = 1, decrease beyond 10 years
 * 6) coniferous forest: young- to mid-successional stands = 1, decrease beyond mid-successional
 * 7) mast_index
 * 8) site_quality_index
 * 9) Thermal Cover Potential = forest_composition_index x forest_structure_index x site_productivity_index
 * 10) forest_composition_index = forest_type_index x coniferous_species_index
 * 11) forest_type_index
 * 12) coniferous forest = 1
 * 13) mixed forest = 0.5
 * 14) deciduous forest = 0
 * 15) coniferous_species_index
 * 16) Northern Hemlock, White Cedar = 1 (mesic conifers)
 * 17) spruce and fir = 0.8 (woody wetlands)
 * 18) pine = 0.4 (upland/xeric conifers)
 * 19) forest_structure_index = {2 x ((BA_index + canopy_cover_index + DBH_index) / 3) + age_structure_index} / 3
 * 20) BA_index
 * 21) 0-10 years (0-7sq. m/ha) = 0
 * 22) 10-30 years (7-23 sq. m/ha) = 0.5
 * 23) 30+ years (23+ sq. m/ha) = 1
 * 24) canopy_cover_index
 * 25) < 50 years (40-70% canopy cover) = 0.5
 * 26) > 50 years (70-100% canopy cover) = 1.0
 * 27) DBH_index
 * 28) mean dbh > 9cm = 1.0 (pole or sawtimber)
 * 29) mean dbh 5 - 9cm = 0.5 (saplings)
 * 30) mean dbh < 5 = 0 (smaller than saplings)
 * 31) age_structure_index
 * 32) even-aged = 1.0 (30 - 150 years old)
 * 33) uneven-aged = 0.0 (>150 years old)
 * 34) site_productivity_index
 * 35) Spring and Summer habitat potential (SSHP) = vegetation_type_preference_index x successional_stage_index x site_quality_index
 * 36) vegetation_type_preference_index
 * 37) successional_stage_index
 * 38) site_quality_index

=Population Level Data=


 * Overwintering densities for Vilas county: ~ 19-30 per square mile of suitable habitat (data)
 * Fall densities slightly lower - 18-28 per square mile of suitable habitat (data) - measurement area, or movement on a scale > management unit?
 * approximately 1.5 - 2.5 males harvested per square of suitable habitat mile in same region (data)
 * aim for approximately 20-25 deer per square mile of suitable habitat across DMU's in Vilas county (Anonymous 2001)
 * Approximating total population size in Vilas county:
 * Vilas county contains Deer Management Units (DMU's)
 * DMU estimated population sizes (data):
 * Demographics
 * Fawn Survival
 * 37/75 (49.333%) survival after ~1 year in Michigan
 * 42/75 (56%) excluding losses to hunting (Burroughs et al 2006)





= = = = =ODD Implementation=


 * Level 1 - simplest deer model
 * Implementation of ruby model: [[file:deer_ODD.txt]]

=Related Projects=


 * Individual-based modeling of white-tailed deer (Odocoileus virginianus) movements and epizootiology.

=References=

Anonymous (2001 ) Management Workbook for White-tailed Deer, 2nd edn. Bureaus of Wildlife Management and Integrated Science Services, Wisconsin Department of Natural Resources, Madison, WI, USA.

Burroughs, J.P. et al., 2006. Cause-Specific Mortality and Survival of White-Tailed Deer Fawns in Southwestern Lower Michigan. Journal of Wildlife Management, 70(3), p.743-751.

Lagory, K. E. (1986). Habitat, group size, and the behaviour of white-tailed deer. Behaviour 98, 168-179.

McShea, W. J., and Schwede, G. (1993). Variable acorn crops: responses of white-tailed deer and other mast consumers. Journal of Mammalogy 74, 999-1006.

Moen, A. (1978) Seasonal Changes in Heart Rates, Activity, Metabolism, and Forage Intake of White-Tailed Deer. The Journal of Wildlife Management, Vol. 42, No. 4 pp. 715-738.

Moen, R., Pastor, J., and Cohen, Y. (1997). A spatially explicit model of moose foraging and energetics. Ecology 78, 505-521.

Stephen L. Webb, Kenneth L. Gee, Bronson K. Strickland, Stephen Demarais, and Randy W. DeYoung, “Measuring Fine-Scale White-Tailed Deer Movements and Environmental Influences Using GPS Collars,” International Journal of Ecology, vol. 2010, Article ID 459610, 12 pages, 2010. doi:10.1155/2010/459610

Storm, D et al. (2007) “Space use and survival of white-tailed deer in an exurban landscape.” Journal of Wildlife Management 71(4) 1170-1176.  Wisconsin Department of Natural Resources (1998). Wisconsin's deer management program: the issues in decision-making. 2nd edition. WDNR, Madison, WI.