Do dryland ecosystems control variability and recent trends in the land CO2 sink?

GSTDTAP

项目编号	NE/R00062X/1
	Do dryland ecosystems control variability and recent trends in the land CO2 sink?
	Richard Edward Brazier
主持机构	University of Exeter
项目开始年	2018
	2018
项目结束日期	2021-06-30
资助机构	UK-NERC
项目类别	Research Grant
项目经费	650657(GBP)
国家	英国
语种	英语
英文摘要	Drylands store modest amounts of carbon in their soils and vegetation per unit area; however, as they cover 40% of the global land mass they store globally significant amounts of carbon overall. Rainfall is very variable between years, and these ecosystems respond rapidly to water availability. Therefore, carbon storage also varies greatly through time. Recent work has shown that dryland ecosystems may control variations in the global carbon cycle; however, there are significant uncertainties associated with understanding of carbon dynamics in dryland soils and vegetation, especially as climates change. Some researchers argue that drylands do not have the capacity to store or lose enough carbon to make any difference to the global amounts of carbon that are taken up by plants or soils, or lost to the atmosphere. Others argue that drylands may provide the 'missing-sink' in the global carbon cycle - helping to explain the stores of carbon needed to balance the global carbon budget, and that especially during wetter years, they have the capacity to store much more carbon than has previously been estimated. The current lack of consensus on the role of drylands in the global carbon cycle is hindering scientific ability to constrain the global carbon budget and understand future trends in the ability of the terrestrial carbon sink to mitigate climate change. This project will address this disagreement, providing robust analysis of existing data across a gradient of aridity and a range of plant types in a dryland region that contains the highest density of existing monitoring sites in the world. We will also undertake highly novel fieldwork, collecting new data which allow us to understand uncertainty in existing datasets that describe carbon storage and loss. We will then use new observations to evaluate which remotely sensed products, from existing satellite networks, are the most accurate at representing differences in carbon stocks in drylands. This element of the project is fundamental to understanding our planet, as it will enable more accurate global predictions of the carbon cycle and how this affects the global climate. Global modelling work argues that marginal, dryland ecosystems may control the global variability of carbon storage and loss and may also exert a profound control on the long-term trends of carbon storage and loss between the Earth and the atmosphere. This proposal will improve the empirical foundations of such model predictions. We contend that the predictions are likely to be true, but as yet have not been validated, nor understood well, in terms of the mechanisms that might underpin these controls. We will model the dynamics of vegetation in drylands, to test which vegetation models make the best predictions of growth and dieback, through wet and dry periods observed in the data that we collect in the first part of the project. Once we have established which vegetation models perform best, we will populate these models with appropriate parameters to predict how vegetation might respond to future climates, thus ensuring that the next step - to improve global model predictions of carbon loss and storage is made via a dialogue between empirical data collection and modelling. The project will deliver a fundamental improvement in our understanding of the carbon cycle in drylands, demonstrating empirically whether or not these landscapes have the capacity to control inter-annual variability and long-term trends in the land carbon sink. It will allow us to develop field techniques that can be exported to other landscapes, to constrain the uncertainty associated with measurements of ecosystem change. It will further allow us to understand and then recommend which globally available remote sensing products are best at characterising change in above-ground carbon stores in drylands. Finally it will permit us to make significant, data-based improvements to predictions of the global carbon cycle.
来源学科分类	Natural Environment Research
文献类型	项目
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/86992
专题	环境与发展全球科技态势
推荐引用方式 GB/T 7714	Richard Edward Brazier.Do dryland ecosystems control variability and recent trends in the land CO2 sink?.2018.