Bioenergetic approaches for understanding and forecasting ecological and epidemiological impacts of climate change

用于理解和预测气候变化的生态和流行病学影响的生物能源方法

• 批准号: RGPIN-2016-06301
• 负责人: Molnar, Peter
• 金额: $ 2.4万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=631606
• 关键词: Bioenergetic; approaches; understanding; forecasting; ecological

Climate change, land use change, and other large-scale disturbances are altering ecosystems globally at an accelerating rate. Ecological forecast models that can outline the scope, timeline and manner of future impacts are needed to allow for proactive management strategies, for example, in the conservation of endangered species and the control of diseases. However, unlike the climate sciences, where mechanistic models are routinely used to predict climate changes, ecology does not yet offer a comprehensive framework for predicting ecosystem response to these changes. This proposal integrates physiological, ecological and epidemiological principles to develop, test, and apply mechanistic models for understanding and forecasting climate change impacts in two key areas of conservation and public/wildlife health.

气候变化、土地利用变化和其他大规模干扰正在加速改变全球生态系统。需要能够概述未来影响的范围、时间轴和方式的生态预测模型，以便能够在保护濒危物种和控制疾病等方面采取积极主动的管理战略。然而，与气候科学不同，机械模型通常用于预测气候变化，生态学尚未提供预测生态系统对这些变化的反应的综合框架。该提案整合了生理学、生态学和流行病学原理，以开发、测试和应用机械模型，用于理解和预测气候变化在保护和公共/野生动物健康两个关键领域的影响。