Habitats drive population biology

栖息地驱动种群生物学

• 批准号: RGPIN-2015-04154
• 负责人: Boyce, Mark
• 金额: $ 1.89万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=589626
• 关键词: Habitats; drive; population; biology

Early in my career I focused on demographic models in stochastic and seasonal environments, but it became clear that such theoretical constructs were insufficient for conservation applications. Links with habitats are essential for useful applications of population models, and in my lab we have developed many quantitative tools for building connections between habitats and populations. Animals are more abundant in habitats that are selected most strongly and, for the species that we have studied, fitness is highest in these habitats. Models of habitat selection can be used to distribute animals on the landscape and when the population is at carrying capacity, resource selection functions (RSF) can be used to estimate abundance. If the population is not at equilibrium, abundance might be influenced by factors not directly related to habitats thereby potentially (but not necessarily) compromising the use of habitat selection models for predicting population size. Distribution among habitats often is density dependent, but seldom follows an ideal free distribution. Many other complications can occur such as seasonal use of habitats, but such seasonality can be accommodated in model structure. Field studies to apply the principles of habitat-based population models will focus on my continuing studies of elk, grizzly bears, and wolverines. Our long-term elk studies are grounded in one of the largest radiotelemetry studies ever conducted on this species with substantially over 1 million GPS relocations accumulated during the past 8 years on seasonal ranges in SW Alberta. We have developed methods for step-selection functions (SSF) that allow us to analyze patterns of movement in context of habitats. Collaborators from Europe have shared comparable data on red deer revealing similar patterns of habitat selection and demography. Our proposed grizzly bear and black bear studies likewise extend habitat selection based on radiotelemetry data and more recently population inferences based on DNA from hair samples collected at rub trees. We are proposing to develop methods for Spatially Explicit Capture Recapture (SECR) population estimation and monitoring for bears. The structure of bear populations in SW Alberta suggests a source-sink balance with sinks often driven by conflicts with agriculture. Finally, we are excited about our ability to study wolverines in boreal and montane regions of Alberta using radiotelemetry and noninvasive sampling. Modern technology has allowed us to assemble new findings about habitat selection and demography of wolverines in the boreal forests of NW Alberta. This archetypical wilderness species coexists with humans in an industrial landscape at densities much higher than previously documented. Again, tools of SECR, RSF, and SSFs allow us to marry habitat ecology with population ecology in novel ways with applications for conservation biology and management.

在我的职业生涯的早期，我专注于随机和季节性环境中的人口模型，但是很明显，这种理论结构不足以保护应用程序。与栖息地的联系对于人口模型的有用应用至关重要，在我的实验室中，我们开发了许多定量工具来建立栖息地与人口之间的联系。动物在最强选择的栖息地中更丰富，对于我们研究的物种，在这些栖息地中，健身最高。栖息地选择模型可用于在景观上分配动物，当人口具有携带能力时，资源选择功能（RSF）可用于估计丰度。如果人口不均衡，那么丰度可能会受到与栖息地不直接相关的因素的影响，从而有可能（但不一定）损害使用栖息地选择模型来预测人口规模的情况。栖息地之间的分布通常取决于密度，但是很少遵循理想的自由分布。可能发生许多其他并发症，例如季节性使用栖息地，但是这种季节性可以在模型结构中适应。应用基于栖息地的人群模型原理的现场研究将重点关注我对麋鹿，灰熊和金刚狼的持续研究。我们的长期麋鹿研究基于有史以来对该物种进行的最大的Radiotelemetry研究之一，在过去的8年中，在SW Alberta的季节性范围内积累了超过100万GPS的重新定位。我们已经开发了用于逐步选择功能（SSF）的方法，使我们能够在栖息地中分析运动模式。来自欧洲的合作者共享了有关红鹿的可比数据，揭示了类似的栖息地选择和人口统计学模式。我们提出的灰熊和黑熊研究同样，基于放射性骨化数据的数据和最近的种群推断，基于从摩擦树木收集的头发样本中的DNA推断栖息地的选择。我们提议开发用于空间明确捕获重新捕获（SECR）人群估计和监测熊的方法。 SW艾伯塔省的熊种群的结构表明，源头平衡与水槽通常受到农业冲突的驱动。最后，我们对使用Radiotelemetry和非侵入性采样的北极和山地区域研究金刚狼的能力感到兴奋。现代技术使我们能够在西北艾伯塔省的北部北部森林中组装有关金刚狼的栖息地选择和人口统计的新发现。这种原型的荒野物种与人类在工业景观中并存，密度比以前记录的要高得多。同样，SECR，RSF和SSF的工具使我们能够以新颖的方式将栖息地生态与人口生态学结合，并应用于保护生物学和管理。