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| Collaborative Research: Integrating Plant Hydraulics with Climate and Hydrology to Understand and Predict Responses to Climate Change | |
| 项目编号 | 1450679 |
| David Mackay | |
| 项目主持机构 | SUNY at Buffalo |
| 开始日期 | 2015-05-15 |
| 结束日期 | 2018-04-30 |
| 英文摘要 | Droughts threaten the health of the nation's forest resources by reducing tree growth and increasing mortality from multiple causes including fires and insect attack. This project will determine when and where forests are most at risk from drought-induced mortality in the western USA under current and future climate scenarios. Plant drought responses will be predicted from a theory of water supply and demand that is based on the physics of water flow. When plants are photosynthesizing they are also losing water by evaporation through the stomatal pores that take up CO2 in their leaves. The lost water is replenished by a passive wicking process that pulls water from the soil into roots and up dead, water-filled xylem tubes. Drought-induced failure of this water transport limits the possible rate of water supply, which by theory is associated with reduced water demand caused by closure of stomatal pores. Consequently, prolonged droughts reduce growth and transport capacity, creating persistent metabolic stresses that increase mortality by the "chronic stress hypothesis". A computer model will combine the supply-demand theory with climatic and landscape causes of drought stress, including precipitation, groundwater hydrology, and atmospheric humidity. The model and chronic stress hypothesis will be tested in greenhouse, plantation, and natural stands, focusing on trees of the intermountain west. Predictions for the region's forests will be made from climate projections. Forecasts will inform decisions on land management. Educational versions of the model will illustrate the combined roles of climate and groundwater hydrology on plant health. The project is a regionally focused trial of an approach that can be applied nationally and globally. The goal is to identify and characterize the key hydraulic traits of plants necessary for accurate predictions of how their gas exchange, vascular performance, productivity, and risk of mortality will respond to climate change. The context is forests of the mountain west (USA), where droughts have already caused significant woody plant mortality. The backbone of the project is a model of the soil-plant-atmosphere continuum that applies mathematical approaches for soil water flow to plant xylem. Key research questions include whether the model can be accurately driven by climate and hydrology, the importance of vascular recovery via xylem refilling, and whether there is a chronic stress threshold of vascular dysfunction and consequent reduction in CO2 uptake and productivity that is reproducibly associated with mortality risk. The utility of the chronic stress hypothesis is that hydraulics can be predicted from the climate-coupled model, whereas the exact proximal cause of death is likely variable and less predictable. The integrated model and chronic stress idea will be tested rigorously in greenhouse, research garden, and natural settings, including tests of its ability to "hindcast" the current hydraulic status of montane woody plants in the region from known climate inputs. The model will predict the severity of droughts required to threaten western forests, and forecast the immediate impacts of future climate scenarios for the region. Forecasts will inform forest management decisions. Educational model versions will promote understanding of the plant-climate linkage. Research versions will be available via website, because the basic approach is relevant for analyzing drought impacts on forests of any region. |
| 学科分类 | 06 - 生物科学;0611 - 生理学与整合生物学 |
| 资助机构 | US-NSF |
| 项目经费 | 196128 |
| 项目类型 | Standard Grant |
| 国家 | US |
| 语种 | 英语 |
| 文献类型 | 项目 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/69989 |
| 推荐引用方式 GB/T 7714 | David Mackay.Collaborative Research: Integrating Plant Hydraulics with Climate and Hydrology to Understand and Predict Responses to Climate Change.2015. |
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