Statistically efficient integration of animal tracking data into ecological theory and evidence-based conservation

将动物追踪数据统计有效地整合到生态理论和循证保护中

• 批准号: RGPIN-2021-02758
• 负责人: Noonan, Michael
• 金额: $ 2.04万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=742203
• 关键词: Statistically; efficient; integration; animal; tracking

Animal movement is a key behavioural process that governs how individuals, populations, and species interact with each other and the environment, and is a core component of conservation science. Spurred by advances in tracking technologies, movement ecology has expanded from a niche topic to one of the fastest growing fields in ecology. Problematically, however, statistical techniques for analyzing these new and challenging datasets have lagged behind. This can limit the ability for tracking data to reliably inform species conservation. My long-term objective is to support the statistically efficient integration of animal tracking data into ecological theory and evidence-based conservation. Over the next 5 years, I will build toward this goal by tackling three key challenges. Challenge (i): Accurate estimation of latent variables estimated from animal paths. HQP in my lab will leverage established modelling and simulation methods to develop novel estimators of path-derived latent variables (e.g., habitat time budgets, road crossing rates, etc.). Software implementations of these estimators will be made freely available to the scientific community. Using pre-existing tracking datasets HQP will apply these tools to achieve accurate estimates for mitigating human-wildlife conflict. Challenge (ii): Encounter distribution estimation. Existing work on modelling inter-individual encounters has focused primarily on relating animal movement and encounter rates, while no research directly links individual movement with the spatial locations of encounter events in the environment. HQP will bridge this gap by introducing a new theoretical distribution, deriving this distribution, and implementing its estimator in open-access software. This estimator will then be integrated with the tools from challenge (i) to build an analytical framework for answering questions on animal-vehicle interactions. Challenge (iii): Macro-ecology and global conservation. I have assembled an extensive empirical animal tracking dataset, consisting of ~1300 individuals from 76 globally distributed species. By pairing these data with robust analytical tools, my trainees and I will evaluate four key questions aimed at understanding how animals are responding to anthropogenic impacts globally: a) the allometric scaling of movement speeds; b) an evaluation of the effects of anthropogenic disturbance on circadian rhythms; c) an evaluation of the evolution of periodic behaviour; and d) an evaluation of the evolutionary constraints on the phenotypic plasticity of animal movement. A diverse group of HQP, including at least 3 PhD, 3 MSc, and 4 UG will be trained as part of this project. The lab's research and training activities will help position Canada at the forefront of the rapidly growing field of movement ecology. Findings will have direct application for government agencies and NGOs charged with protecting and restoring Canada's culturally and ecologically important species.

动物运动是一个关键的行为过程，控制着个体、种群和物种如何相互作用，也是保护科学的核心组成部分。在跟踪技术进步的推动下，运动生态学已经从一个利基话题扩展到生态学中增长最快的领域之一。然而，问题是，用于分析这些新的和具有挑战性的数据集的统计技术已经落后。这可能会限制跟踪数据的能力，从而可靠地为物种保护提供信息。我的长期目标是支持动物跟踪数据的统计有效整合到生态理论和基于证据的保护。在接下来的五年里，我将通过解决三个关键挑战来实现这一目标。 挑战（i）：准确估计从动物路径估计的潜在变量。我实验室的HQP将利用已建立的建模和模拟方法来开发路径衍生潜变量的新估计（例如，栖息地时间预算、道路穿越率等）。这些估算器的软件实现将免费提供给科学界。HQP将使用现有的跟踪数据集，应用这些工具来实现准确的估计，以减轻人类与野生动物的冲突。挑战（ii）：遭遇分布估计。现有的工作建模个体间的遭遇主要集中在有关动物运动和遭遇率，而没有研究直接联系个人的运动与空间位置的遭遇事件在环境中。HQP将通过引入一个新的理论分布，推导该分布，并在开放获取软件中实现其估计量来弥合这一差距。然后将该估计器与挑战（i）中的工具集成，以构建用于回答动物-车辆相互作用问题的分析框架。挑战（三）：宏观生态和全球保护。我已经收集了一个广泛的经验动物跟踪数据集，包括来自全球分布的76个物种的约1300个个体。通过将这些数据与强大的分析工具相结合，我和我的学员将评估四个关键问题，以了解动物如何在全球范围内对人类活动的影响作出反应：a）运动速度的异速生长比例; B）人类活动对昼夜节律的影响的评估; c）周期性行为的进化评估;以及d）评估动物运动的表型可塑性的进化约束。作为本项目的一部分，将培训一组不同的HQP，包括至少3名博士，3名硕士和4名UG。该实验室的研究和培训活动将有助于加拿大在快速发展的运动生态学领域的最前沿。调查结果将直接应用于负责保护和恢复加拿大文化和生态重要物种的政府机构和非政府组织。