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Density dependence and stochastic variation in overabundant, unmanaged white-tailed deer herds of eastern national parks.

机译:东部国家公园过多,未经管理的白尾鹿群的密度依赖性和随机变化。

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摘要

In many parts of the eastern U.S., white-tailed deer populations have existed for decades at densities high enough to cause public concern due to decreased forest regeneration, more frequent deer-vehicle collisions, and increased spread of human and animal diseases. The National Park Service (NPS) has initiated management actions at several sites focused on decreasing deer density without a broader understanding of population dynamics that contribute to population size and fluctuation over time. Using 7-year to 13-year sets of deer monitoring data from 16 NPS sites, I estimated parameters of the theta-logistic model (TLM), a widely-used population model which integrates the two key factors of population dynamics: density dependence and environmental stochasticity. I found that: (1) the density dependent parameter of the TLM (theta) can be estimated from time-series if the ratio of process variance to sampling variance is more than 1.6 and if parameter bias is simulated and corrected; (2) deer populations existing at a lower equilibrium density fluctuated more over time and conversely larger populations fluctuated less; and (3) overall population variation is positively related to environmental stochasticity.
机译:在美国东部的许多地区,白尾鹿种群的存在已有数十年之久,其密度之高足以引起公众关注,这是由于森林再生减少,鹿与车辆的碰撞更为频繁以及人类和动物疾病的扩散增加所致。国家公园管理局(NPS)已在几个地点启动了管理行动,着重于降低鹿的密度,而没有更广泛地了解会导致种群数量和时间波动的种群动态。我使用来自16个NPS站点的7年到13年的鹿监测数据集,估算了theta-logistic模型(TLM)的参数,该模型广泛使用,它结合了种群动态的两个关键因素:密度依赖性和种群密度。环境随机性。我发现:(1)如果过程方差与采样方差之比大于1.6,并且模拟和校正了参数偏差,则可以从时间序列估算TLM的密度相关参数(θ)。 (2)处于较低平衡密度的鹿种群随着时间的推移波动更大,相反,较大种群的波动较小; (3)总体人口变化与环境随机性呈正相关。

著录项

  • 作者

    Wilkinson, Sarah A.;

  • 作者单位

    State University of New York College of Environmental Science and Forestry.;

  • 授予单位 State University of New York College of Environmental Science and Forestry.;
  • 学科 Wildlife management.;Wildlife conservation.
  • 学位 M.S.
  • 年度 2013
  • 页码 68 p.
  • 总页数 68
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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