25 research outputs found

    Achieving and maintaining sustainable white-tailed deer density with adaptive management

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    A leadership team developed an adaptive management program to reduce deer density and impact on a 29,642-ha forested demonstration area in northwest Pennsylvania incorporating goal setting, monitoring, and communicating with and motivating hunters. We linked reduction of deer density to environmentally sustainable levels with an appeal to the values of hunters (improving deer and habitat quality). The communication program educated and involved hunters as active participants in all phases of the management plan. We monitored deer density, deer impact, deer health, and hunter satisfaction to adjust numbers of permits for harvesting antlerless deer and to improve hunter access and use of all areas within the demonstration area. We reduced deer density and impacts to goal levels within 4 years and improved deer health. We maintained a base of satisfied hunters who continued to harvest enough deer to maintain goal levels of deer density and impact by the fifth year of the program, which continues to the present. Once we cut deer density in half with public hunting, maintaining deer density at the reduced (goal) rate was achieved with a relatively small pool of dedicated hunters who returned every year to harvest enough deer to off set recruitment

    \u3ci\u3eOpinion\u3c/i\u3e Bridging the disconnect between agencies and forest landowners to manage deer impact

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    White-tailed deer (Odocoileus virginianus) are managed at 2 levels: by federal, state, or local resource agencies on large, heterogeneous landscapes usually \u3e200 ha; and by individual property owners on smaller (generallyha) and more discrete forestlands. This dichotomy results in a management disconnect: regulations controlling deer hunting (seasons and bag limits) are developed by agencies for landscapes the size of deer management units (DMU) and often are not sufficiently area-specific to meet management needs of individual forest landowners. Resource agencies manage hunters and regulate deer abundance by controlling harvest within DMUs, and they use license and permit fees paid by hunters to finance the costs of agency deer management, including law enforcement. Some, such as the Pennsylvania Game Commission (PGC), derive income from timber harvest on landscapes they manage (gamelands) as an additional source of revenue and may use it for habitat enhancement that favors deer and other wildlife species. Most deer management occurs on forestlands where habitat (forage, cover, water, plant composition) is manipulated by landowners. Landowners absorb the costs of management that affect deer habitat, abundance, and impact on natural resources. Costs include herbicide application to control unwanted vegetation resulting from overabundant deer; development and maintenance of roads hunters use to gain access to deer hunting; activities associated with managing deer harvest (posting boundaries, repairing road damage); and measures, including fencing, to protect forest resources from damages caused by overabundant deer. Other costs, like thinning or timber harvest, which produce deer forage, are partially or wholly off set by the sale of resulting forest products. Unlike agencies, costs to forest landowners of managing deer and hunting access are rarely subsidized by hunters (a notable exception was the PGC program to provide deer fencing materials to protect tree regeneration on forest landowner properties), but rather are borne by forest landowners—unless landowners lease hunting rights to hunters for a fee. The disconnect and resultant emphasis on deer management at the DMU level by agencies rather than individual forestlands favors the priorities of hunters (bigger and more deer) that conflict with those of landowners whose resources and revenues may be negatively impacted by high deer density. The situation results from the history of deer management, which must be placed in perspective along with the importance and influence of stakeholders, who affect an organization’s objectives (Freeman 1984)

    Estimating Cost-Effectiveness of Controlling Animal Damage to Conifer Seedlings

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    A model for determining the benefit-cost ratio of controlling damage by vertebrate pests to conifer seedlings requires knowledge of the amount, distribution, and duration of animal damage, reduction in damage associated with control, costs of control, methodology and value of trees at harvest. Because control costs occurring in the present must be compared with savings recovered decades later in the future, the model incorporates procedures for discounting or adjusting future monetary benefits into present net worth valuations. The model allows forest managers to evaluate a wide range of damage costs and savings accruing from use of various control techniques. The model clearly demonstrates that application of controls before damage occurs is more cost-effective than withholding application until it is established that damage will occur

    ESTIMATING COST-EFFECTIVENESS OF CONTROLLING ANIMAL DAMAGE TO CONIFER SEEDLINGS

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    A model for determining the benefit-cost ratio of controlling damage by vertebrate pests to conifer seedlings requires knowledge of the amount, distribution, and duration of animal damage, reduction in damage associated with control, costs of control, methodology and value of trees at harvest. Because control costs occurring in the present must be compared with savings recovered decades later in the future, the model incorporates procedures for discounting or adjusting future monetary benefits into present net worth valuations,, The model allows forest managers to evaluate a wide range of damage costs and savings accruing from use of various control techniques. The model clearly demonstrates that application of controls before damage occurs is more cost-effective than withholding application until it is established that damage will occur

    Methodology for Estimating Deer Browsing Impact

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    Because there were no reliable indicators of deer browsing on tree seedling regeneration, we developed methodology that can be used to measure deer browsing impact. We compared 11 years (2002 to 2012) of annual estimates of deer density with coarse (percent-plots-no-regeneration, percent-plots-no-impact) and fine (3 levels of impact on 6 indicator seedling species) indicators within a 29,642-ha study area in northwestern Pennsylvania. Coarse and fine measures met established criteria for indicators of environmental stress (e.g., high deer density); they were predictive of stresses that can be: avoided by management; integrative with causes of stress; responsive to disturbances and changes over time; and of sufficiently low variability to be significantly responsive to changes in stressors. Time spent and equipment required to collect indicator data were minimal. Data were collected at the same time and on the same plots as deer density data, producing a significant savings of time and capital. Indicators tested had potential as proxies for deer impact on other forest resources
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