气候变化领域集成服务门户(CCPortal): First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems

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DOI	10.1016/j.jag.2019.01.018
	First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems
	Abdi A.M.; Boke-Olén N.; Jin H.; Eklundh L.; Tagesson T.; Lehsten V.; Ardö J.
发表日期	2019
ISSN	15698432
起始页码	249
结束页码	260
卷号	78
英文摘要	The importance of semi-arid ecosystems in the global carbon cycle as sinks for CO 2 emissions has recently been highlighted. Africa is a carbon sink and nearly half its area comprises arid and semi-arid ecosystems. However, there are uncertainties regarding CO 2 fluxes for semi-arid ecosystems in Africa, particularly savannas and dry tropical woodlands. In order to improve on existing remote-sensing based methods for estimating carbon uptake across semi-arid Africa we applied and tested the recently developed plant phenology index (PPI). We developed a PPI-based model estimating gross primary productivity (GPP) that accounts for canopy water stress, and compared it against three other Earth observation-based GPP models: the temperature and greenness (T-G) model, the greenness and radiation (GöR) model and a light use efficiency model (MOD17). The models were evaluated against in situ data from four semi-arid sites in Africa with varying tree canopy cover (3–65%). Evaluation results from the four GPP models showed reasonable agreement with in situ GPP measured from eddy covariance flux towers (EC GPP) based on coefficient of variation (R 2 ), root-mean-square error (RMSE), and Bayesian information criterion (BIC). The GöR model produced R 2 = 0.73, RMSE = 1.45 g C m −2 d −1 , and BIC = 678; the T-G model produced R 2 = 0.68, RMSE = 1.57 g C m −2 d −1 , and BIC = 707; the MOD17 model produced R 2 = 0.49, RMSE = 1.98 g C m −2 d −1 , and BIC = 800. The PPI-based GPP model was able to capture the magnitude of EC GPP better than the other tested models (R 2 = 0.77, RMSE = 1.32 g C m −2 d −1 , and BIC = 631). These results show that a PPI-based GPP model is a promising tool for the estimation of GPP in the semi-arid ecosystems of Africa. © 2019 Elsevier B.V.
英文关键词	Drylands; Eddy covariance; FLUXNET; GPP; Gross primary productivity; Land surface temperature; LST; MODIS; Plant phenology index; PPI; Semi-arid; Vapor pressure deficit; VPD
语种	英语
scopus关键词	carbon cycle; eddy covariance; MODIS; primary production; semiarid region; surface temperature; vapor pressure; vegetation index; Africa
来源期刊	International Journal of Applied Earth Observation and Geoinformation
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156472
作者单位	Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, Lund, SE-223 62, Sweden; Centre for Environmental and Climate Research, Lund University, Sölvegatan 37, Lund, SE-223 62, Sweden; Swiss Federal Institute for Forest, Snow and Landscape research (WSL), Zürcherstr. 11, Birmensdorf, CH-8903, Switzerland
推荐引用方式 GB/T 7714	Abdi A.M.,Boke-Olén N.,Jin H.,et al. First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems[J],2019,78.
APA	Abdi A.M..,Boke-Olén N..,Jin H..,Eklundh L..,Tagesson T..,...&Ardö J..(2019).First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems.International Journal of Applied Earth Observation and Geoinformation,78.
MLA	Abdi A.M.,et al."First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems".International Journal of Applied Earth Observation and Geoinformation 78(2019).