MMIA: Integrated Assessment of African Savannas with Spatial- Dynamic Vegetation and Land Use Modeling

MMIA：利用空间动态植被和土地利用建模对非洲稀树草原进行综合评估

• 批准号: 9711627
• 负责人: Michael Coughenour
• 金额: $ 45万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-09-01 至 2001-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9711627&HistoricalAwards=false
• 关键词: MMIA; Integrated; Assessment; African; Savannas

Coughenour 97-11627 Current projections of the effects of global climate change on terrestrial ecosystems are generated through simulations of climate-vegetation interactions at regional to global scales. However current models generally predict new equilibrium conditions and do not emulate process-driven transient conditions which could last for a long time, or even indefinitely if climate variability increases substantially. The models do not resolve vegetation responses to landscape structure, nor do they represent vegetation responses to herbivory by wild or domestic animals, or other human land uses. A major objective of this project is to evamate how much one can improve estimates or climate change effects on vegetation, ecosystems and people, by using process-oriented ecosystem-level simulauons. Current climate patterns will be used to drive three different types or models (quasi-equilibrium, SAVANNA-climate, SAVANNA-biotic), all parameterized to simulate extant vegetation conditions in the Serengeti Regional Ecosystem; a savanna system where soil, landscape features, human land use, fire and herbivore impacts all interact with climate to influence vegetation patterns and ecosystem state. Differences among models in predictions of responses to global change will be evaluated in terms of: (a) the accuracy of the models at predicting extant and as potential vegetation under current and doubled CO2 climate conditions; (b) the effects of considering herbivory, land-use compared to climate alone; (c) the effects of spatial scale on the predicted responses Supporting field and remote sensing studies will result in a better understanding of current vegetation in relationship to climate, soils, herbivory, and land use. The research will be relevant to natural resources policy in the East African region. The integrated modeling approach will have utility for government land management and planning, for famine early warning, for park and game reserve managers, and for pastoral peoples. The re search will contribute to the development of dynamic global vegetation models (DGVM's).

Coughenour 97-11627目前对全球气候变化对陆地生态系统的影响的预测是通过在区域到全球范围内对气候-植被相互作用的模拟产生的。然而，目前的模型通常预测新的平衡条件，并不模拟可能持续很长时间的过程驱动的瞬时条件，如果气候变异性大幅增加，甚至是无限期的。这些模型没有解决植被对景观结构的响应，也没有代表植被对野生或家养动物或其他人类土地利用草食的响应。该项目的一个主要目标是，通过使用面向过程的生态系统水平模拟，评估人们可以在多大程度上改进对植被、生态系统和人类的估计或气候变化影响。目前的气候模式将被用来驱动三种不同的类型或模式(准平衡、稀树草原-气候、稀树草原-生物)，所有这些类型或模式都被参数化以模拟塞伦盖蒂地区生态系统中现有的植被条件；稀树草原系统，其中土壤、景观特征、人类土地利用、火和食草动物的影响都与气候相互作用，影响植被模式和生态系统状态。对不同模型在预测对全球变化的反应方面的差异将从以下方面进行评估：(A)在当前和加倍的二氧化碳气候条件下，模型预测现有植被和潜在植被的准确性；(B)与单独考虑气候相比，考虑草食、土地利用的影响；(C)支持实地和遥感研究的空间尺度对预测反应的影响将导致更好地了解当前植被与气候、土壤、草食和土地利用的关系。这项研究将与东非地区的自然资源政策相关。综合建模方法将对政府土地管理和规划、饥荒预警、公园和野生动物保护区管理人员以及牧民具有实用价值。该研究将有助于动态全球植被模型(DGVM)的发展。