DOI: 10.1111/gcb.12766
论文题名: Predictability of the terrestrial carbon cycle
作者: Luo Y. ; Keenan T.F. ; Smith M.
刊名: Global Change Biology
ISSN: 13541013
出版年: 2015
卷: 21, 期: 5 起始页码: 1737
结束页码: 1751
语种: 英语
英文关键词: Climate change
; Data assimilation
; Data-model fusion
; Disturbance events and regimes
; Mathematical model of carbon cycle
; Model tractability and traceability
; Parameterization
; Soil carbon dynamics
; Vegetation
Scopus关键词: carbon cycle
; carbon sequestration
; climate change
; data assimilation
; numerical model
; parameterization
; soil carbon
; terrestrial ecosystem
; vegetation
; carbon cycle
; climate change
; ecosystem
; photosynthesis
; physiology
; theoretical model
; Carbon Cycle
; Climate Change
; Ecosystem
; Models, Theoretical
; Photosynthesis
英文摘要: Terrestrial ecosystems sequester roughly 30% of anthropogenic carbon emission. However this estimate has not been directly deduced from studies of terrestrial ecosystems themselves, but inferred from atmospheric and oceanic data. This raises a question: to what extent is the terrestrial carbon cycle intrinsically predictable? In this paper, we investigated fundamental properties of the terrestrial carbon cycle, examined its intrinsic predictability, and proposed a suite of future research directions to improve empirical understanding and model predictive ability. Specifically, we isolated endogenous internal processes of the terrestrial carbon cycle from exogenous forcing variables. The internal processes share five fundamental properties (i.e., compartmentalization, carbon input through photosynthesis, partitioning among pools, donor pool-dominant transfers, and the first-order decay) among all types of ecosystems on the Earth. The five properties together result in an emergent constraint on predictability of various carbon cycle components in response to five classes of exogenous forcing. Future observational and experimental research should be focused on those less predictive components while modeling research needs to improve model predictive ability for those highly predictive components. We argue that an understanding of predictability should provide guidance on future observational, experimental and modeling research. © 2014 John Wiley & Sons Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/61793
Appears in Collections: 影响、适应和脆弱性
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作者单位: Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, United States; Center for Earth System Science, Tsinghua University, Beijing, China; Department of Biological Sciences, Macquarie University, Sydney, Australia; Computational Science Laboratory, Microsoft Research, Cambridge, United Kingdom
Recommended Citation:
Luo Y.,Keenan T.F.,Smith M.. Predictability of the terrestrial carbon cycle[J]. Global Change Biology,2015-01-01,21(5)