Tropical Biomes in Transition

转型中的热带生物群落

• 批准号: NE/D002303/1
• 负责人: Stephen Sitch
• 金额: $ 18.84万
• 依托单位: University of Sheffield
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2006
• 资助国家: 英国
• 起止时间: 2006 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FD002303%2F1
• 关键词: Tropical; Biomes; Transition

Rainforest and savanna constitute the dominant two biomes of the tropical zone. They account for over 70% of the world's plant species. With massive areas and with high rates of latent and sensible heat exchange, rain forest and savanna also exert large, yet different, effects on the global climate. We have a limited understanding of their contemporary and future responses to global change. Tropical rainforests are a major terrestrial carbon store and are currently estimated to account for around half of the global terrestrial carbon sink. Although rainfall is a key determinant affecting their relative distributions, other factors such as soil conditions, fire and disturbances such as grazing and human influence are also involved. Our knowledge of these factors and how they interact in influencing vegetation type is still poor - all global vegetation models currently misspecify the distributions of these biomes. Such knowledge is fundamental for understanding and predicting transitions in tropical vegetation at local, regional and global scales. A drying of the Amazon Basin in coming decades could lead to the irreplaceable replacement of tropical forest with savanna, this then feeding back on the climate system as a consequence of changes in surface energy and mass balances - thereby accelerating global warming and tropical drying. Significant transitions centered around the gain or loss of savanna vegetation are not restricted to South America Improved predictions of the factors causing a transition from forest to savanna are fundamental to understanding this, and will depend on a significantly improved understanding of the environmental and edaphic determinants of the distribution of tropical vegetation at a global scale. Our main objective is to thus obtain a new knowledge of the underlying physiological basis of these determinants, to better understand the basis of differences in surface energy and CO2 exchange differences between forest and savanna, and to integrate this information for a much more accurate representation of these processes in global vegetation models than is currently possible. This will be achieved by a 'model-data development program involving field campaigns with local collaborators to examine climate/soil/disturbance associations in key 'hot spot' rainforest/savanna transition zones. Comprehensive measurements will be made including key plant physiological processes (photosynthesis water relations), vegetation stand structure and composition, and soil physical and chemical properties. New high resolution climatologies will also be developed and novel methodologies advanced to allow determination of tropical vegetation structure and fire frequency from space. These will be validated and tested and along with the field based data and then used to develop a new quantitative understanding of tropical biome distributions at a global scale. Derived relationships will be compared against more primitive ones currently used to describe tropical vegetation/climate relationships and consequences for predictions of past and future vegetation change evaluated Information from field observations will be used in conjunction with data assimilated from outside the project to develop new models of tropical vegetation distribution and function. Models derived will be as mechanistic as possible with predicted distributions and structure/flux of vegetation tested using larger scale distributional and structural data from remote sensing data Finally we will incorporate our new and improved understanding of tropical vegetation distribution and processes with new global climate model (GCM) runs to provide new insights into impending tropical vegetation change, associated climatic feedbacks and the future global climate. We anticipate this will lead to a fundamental improvement in our ability to predict the global climate of the 21st century.

雨林和稀树草原构成了热带地区的主要两个生物群落。它们占世界植物物种的70％以上。由于巨大的区域以及较高的潜在热交换率，雨林和稀树草原也对全球气候产生了很大但不同的影响。我们对他们对全球变化的当代和未来反应有限。热带雨林是一家主要的地面碳店，目前估计占全球陆地碳水槽的一半。尽管降雨是影响其相对分布的关键决定因素，但也涉及其他因素，例如土壤条件，火灾和干扰和人类影响力等因素。我们对这些因素以及它们如何在影响植被类型中相互作用的知识仍然很差 - 目前所有的全球植被模型都误解了这些生物群落的分布。这种知识对于理解和预测当地，区域和全球量表的热带植被的过渡至关重要。在未来几十年中，亚马逊盆地的干燥可能会导致不可替代的热带森林用稀树草原替换，然后由于表面能量和质量平衡的变化而在气候系统上反馈，从而加速了全球变暖和热带干燥。围绕稀树草原植被的收益或丧失的重大过渡不仅限于南美的改善对导致从森林过渡到稀树草原的因素的预测，这对于理解这一点至关重要，并且将显着改善对环境和质量的确定性对全球热带植被分布的理解。我们的主要目标是因此，获得这些决定因素的基本生理基础的新知识，以更好地了解森林和稀树草原之间的表面能量和二氧化碳交换差异的差异的基础，并将这些信息整合在一起以比目前可能更准确地表示这些过程中这些过程的准确表示。这将由“模型数据开发计划”实现，该计划涉及与当地合作者进行现场活动，以检查关键“热点”雨林/稀树草原过渡区中的气候/土壤/干扰协会。将进行全面的测量，包括关键的植物生理过程（光合作用水关系），植被结构和组成以及土壤物理和化学特性。还将开发新的高分辨率气候，并采用新颖的方法，以确定热带植被结构和空间的火灾频率。这些将经过验证和测试，以及基于现场的数据，然后用于在全球范围内对热带生物群体分布进行新的定量理解。将与目前用于描述热带植被/气候关系的更原始的关系进行比较，以及对过去和未来的植被变化的预测，评估了来自现场观察的信息，将与项目外部同化的数据一起使用，以开发热带植被分布和功能的新模型。通过远程感应数据的较大规模分布和结构数据进行了预测的分布和植被测试的预测分布和结构/通量，得出的模型将尽可能地机械化，最终，我们将与新的全球气候模型（GCM）一起进行对热带植被分布和过程的新的了解，以将新的见解提供新的见解，以提供新的见解，以将热带蔬菜变化为即将发生的环境反馈，并与未来的全球变化相关。我们预计这将导致我们预测21世纪全球气候的能力的基本改善。