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，但很明显，这种理论结构不足以用于保护应用。与栖息地的联系对于人口模型的有用应用至关重要，在我的实验室里，我们已经开发了许多定量工具来建立栖息地和人口之间的联系。动物在选择最强烈的栖息地中更丰富，对于我们研究的物种来说，这些栖息地的适应性最高。栖息地选择模型可以用来分配动物的景观，当人口的承载能力，资源选择功能（RSF）可以用来估计丰度。如果人口是不平衡的，丰度可能会受到影响的因素不直接相关的栖息地，从而潜在的（但不一定）损害使用的栖息地选择模型预测人口规模。栖息地之间的分布往往是密度依赖，但很少遵循一个理想的自由分布。许多其他的并发症可能会发生，如季节性使用的栖息地，但这种季节性可以容纳在模型结构。应用基于栖息地的种群模型原理的实地研究将集中在我对麋鹿、灰熊和狼獾的持续研究上。我们的长期麋鹿研究是基于有史以来对该物种进行的最大的无线电遥测研究之一，在过去8年中，在西南部阿尔伯塔的季节性范围内积累了超过100万个GPS重新定位。我们已经开发了步骤选择功能（SSF）的方法，使我们能够分析的背景下的栖息地的运动模式。来自欧洲的合作者分享了关于红鹿的可比数据，揭示了相似的栖息地选择和人口统计模式。我们提出的灰熊和黑熊研究同样扩展了基于无线电遥测数据的栖息地选择，以及最近基于在橡胶树收集的毛发样本DNA的种群推断。我们建议开发空间显式捕获再捕获（SECR）人口估计和监测熊的方法。在西南阿尔伯塔熊种群的结构表明，与农业的冲突往往驱动汇源-汇平衡。最后，我们很高兴我们有能力研究狼獾在北方和山区的阿尔伯塔使用无线电遥测和非侵入性采样。现代技术使我们能够在西北部阿尔伯塔的北方森林中收集有关狼獾栖息地选择和人口统计的新发现。这种典型的野生物种与人类在工业景观中共存，密度比以前记录的要高得多。同样，SECR，RSF和SSFs的工具使我们能够以新颖的方式将栖息地生态学与种群生态学结合起来，并应用于保护生物学和管理。