Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1111/gcb.14602 |
Anticipating global terrestrial ecosystem state change using FLUXNET | |
Yu, Rong1; Ruddell, Benjamin L.2; Kang, Minseok3; Kim, Joon3; Childers, Dan4 | |
2019-07-01 | |
发表期刊 | GLOBAL CHANGE BIOLOGY
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ISSN | 1354-1013 |
EISSN | 1365-2486 |
出版年 | 2019 |
卷号 | 25期号:7页码:2352-2367 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; South Korea |
英文摘要 | Ecosystems can be characterized as complex systems that traverse a variety of functional and structural states in response to changing bioclimatic forcings. A central challenge of global change biology is the robust empirical description of these states and state transitions. An ecosystem's functional state can be empirically described using Process Networks (PN) that use timeseries observations to determine the strength of process-level functional couplings between ecosystem components. A globally extensive source of in-situ observations of terrestrial ecosystem dynamics is the FLUXNET eddy-covariance network that provides standardized observations of micrometeorology and carbon, water, and energy flux dynamics. We employ the LaThuile FLUXNET synthesis dataset to delineate each month's functional state for 204 sites, yielding the LaThuile PN version 1.0 database that describes the strength of an ecosystem's functional couplings from air temperature and precipitation to carbon fluxes during each site-month. Then we calculate the elasticity of these couplings to seasonal scale forcings: air temperature, precipitation, solar radiation, and phenophase. Finally, we train artificial neural networks to extrapolate these elasticities from 204 sites to the globe, yielding maps of the estimated functional elasticity of every terrestrial ecosystem's functional states to changing seasonal bioclimatic forcings. These maps provide theoretically novel resource that can be used to anticipate ecological state transitions in response to climate change and to validate process-based models of ecological change. These elasticity maps show that each ecosystem can be expected to respond uniquely to changing forcings. Tropical forests, hot deserts, savannas, and high elevations are most elastic to climate change, and elasticity of ecosystems to seasonal air temperature is on average an order of magnitude higher than elasticity to other bioclimatic forcings. We also observed a reasonable amount of moderate relationships between functional elasticity and structural state change across different ecosystems. |
英文关键词 | eddy covariance FLUXNET functional elasticity information flow phenology precipitation process network radiation structural state temperature |
领域 | 气候变化 ; 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000477087100014 |
WOS关键词 | ARTIFICIAL NEURAL-NETWORK ; CLIMATE-CHANGE ; ECOLOGICAL RESILIENCE ; CARBON DYNAMICS ; FEEDBACKS ; SHIFT ; SCALE ; LAND ; VARIABILITY ; FLUXES |
WOS类目 | Biodiversity Conservation ; Ecology ; Environmental Sciences |
WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/184619 |
专题 | 气候变化 资源环境科学 |
作者单位 | 1.Univ Nebraska, Sch Nat Resources, Lincoln, NE USA; 2.No Arizona Univ, Sch Informat Comp & Cyber Syst, Flagstaff, AZ 86011 USA; 3.Natl Ctr AgroMeteorol, Seoul, South Korea; 4.Arizona State Univ, Sch Sustainabil, Tempe, AZ USA |
推荐引用方式 GB/T 7714 | Yu, Rong,Ruddell, Benjamin L.,Kang, Minseok,et al. Anticipating global terrestrial ecosystem state change using FLUXNET[J]. GLOBAL CHANGE BIOLOGY,2019,25(7):2352-2367. |
APA | Yu, Rong,Ruddell, Benjamin L.,Kang, Minseok,Kim, Joon,&Childers, Dan.(2019).Anticipating global terrestrial ecosystem state change using FLUXNET.GLOBAL CHANGE BIOLOGY,25(7),2352-2367. |
MLA | Yu, Rong,et al."Anticipating global terrestrial ecosystem state change using FLUXNET".GLOBAL CHANGE BIOLOGY 25.7(2019):2352-2367. |
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