Browsing by Author "Piao, Shilong"

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1982–2010 Trends of Light Use Efficiency and Inherent Water Use Efficiency in African vegetation: Sensitivity to Climate and Atmospheric CO2 Concentrations
(MDPI, 2014) Traore, Abdoul Khadre; Ciais, Philippe; Vuichard, Nicolas; McBean, Natasha; Dardel, Cecile; Poulter, Benjamin; Piao, Shilong; Fisher, Joshua; Viovy, Nicolas; Jung, Martin; Myneni, Ranga B.
Light and water use by vegetation at the ecosystem level, are key components for understanding the carbon and water cycles particularly in regions with high climate variability and dry climates such as Africa. The objective of this study is to examine recent trends over the last 30 years in Light Use Efficiency (LUE) and inherent Water Use Efficiency (iWUE*) for the major biomes of Africa, including their sensitivities to climate and CO2. LUE and iWUE* trends are analyzed using a combination of NOAA-AVHRR NDVI3g and fAPAR3g, and a data-driven model of monthly evapotranspiration and Gross Primary Productivity (based on flux tower measurements and remote sensing fAPAR, yet with no flux tower data in Africa) and the ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) process-based land surface model driven by variable CO2 and two different gridded climate fields. The iWUE* data product increases by 10%–20% per decade during the 1982–2010 period over the northern savannas (due to positive trend of vegetation productivity) and the central African forest (due to positive trend of vapor pressure deficit). In contrast to the iWUE*, the LUE trends are not statistically significant. The process-based model simulations only show a positive linear trend in iWUE* and LUE over the central African forest. Additionally, factorial model simulations were conducted to attribute trends in iWUE and LUE to climate change and rising CO2 concentrations. We found that the increase of atmospheric CO2 by 52.8 ppm during the period of study explains 30%–50% of the increase in iWUE* and >90% of the LUE trend over the central African forest. The modeled iWUE* trend exhibits a high sensitivity to the climate forcing and environmental conditions, whereas the LUE trend has a smaller sensitivity to the selected climate forcing.
Change in terrestrial ecosystem water-use efficiency over the last three decades
(2015-03) Huang, Mengtian; Piao, Shilong; Sun, Yan; Ciais, Philippe; Cheng, Lei; Mao, Jiafu; Poulter, Benjamin
Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem-scale water-use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data-driven models derived from satellite observations and process-oriented carbon cycle models. Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.0001 g C mâˆ’2 mmâˆ’1 yrâˆ’1 under the single effect of rising CO2 (â€˜CO2â€™), climate change (â€˜CLIMâ€™) and nitrogen deposition (â€˜NDEPâ€™), respectively. Global patterns of EWUE trends under different scenarios suggest that (i) EWUE-CO2 shows global increases, (ii) EWUE-CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE-NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data-driven MTE model, however, shows a slight decline of EWUE during the same period (âˆ’0.0005 g C mâˆ’2 mmâˆ’1 yrâˆ’1), which differs from process-model (0.0064 g C mâˆ’2 mmâˆ’1 yrâˆ’1) simulations with all drivers taken into account. We attribute this discrepancy to the fact that the nonmodeled physiological effects of elevated CO2 reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data-driven model and the process-oriented models across different ecosystems. Change in water-use efficiency defined from transpiration-based WUEt (GPP/TR) and inherent water-use efficiency (IWUEt, GPPÃ—VPD/TR) in response to rising CO2, climate change, and nitrogen deposition are also discussed. Our analyses will facilitate mechanistic understanding of the carbonâ€“water interactions over terrestrial ecosystems under global change.
Detection and Attribution of Vegetation Greening Trend in China over the Last 30 Years
(2015-04) Piao, Shilong; Yin, Guodong; Tan, Jianguang; Cheng, Lei; Huang, Mengtian; Li, Yue; Liu, Ronggao; Mao, Jiafu; Myneni, Ranga B.; Peng, Shushi; Poulter, Benjamin
The reliable detection and attribution of changes in vegetation growth is a prerequisite for the development of strategies for the sustainable management of ecosystems. This is an extraordinary challenge. To our knowledge, this study is the first to comprehensively detect and attribute a greening trend in China over the last three decades. We use three different satellite-derived Leaf Area Index (LAI) datasets for detection as well as five different process-based ecosystem models for attribution. Rising atmospheric CO2 concentration and nitrogen deposition are identified as the most likely causes of the greening trend in China, explaining 85% and 41% of the average growing-season LAI trend (LAIGS) estimated by satellite datasets (average trend of 0.0070 yr−1, ranging from 0.0035 yr−1 to 0.0127 yr−1), respectively. The contribution of nitrogen deposition is more clearly seen in southern China than in the north of the country. Models disagree about the contribution of climate change alone to the trend in LAIGS at the country scale (one model shows a significant increasing trend, whereas two others show significant decreasing trends). However, the models generally agree on the negative impacts of climate change in north China and Inner Mongolia and the positive impact in the Qinghai–Xizang plateau. Provincial forest area change tends to be significantly correlated with the trend of LAIGS (P < 0.05), and marginally significantly (P = 0.07) correlated with the residual of LAIGS trend, calculated as the trend observed by satellite minus that estimated by models through considering the effects of climate change, rising CO2 concentration and nitrogen deposition, across different provinces. This result highlights the important role of China's afforestation program in explaining the spatial patterns of trend in vegetation growth.
Global patterns and climate drivers of water-use efficiency in terrestrial ecosystems deduced from satellite-based datasets and carbon cycle models
(2016-03) Sun, Yan; Piao, Shilong; Huang, Mengtian; Ciais, Philippe; Zeng, Zhenzhong; Cheng, Lei; Li, Xiran; Zhang, Xinping; Mao, Jiafu; Peng, Shushi; Poulter, Benjamin; Shi, Xiaoying; Wang, Xuhui; Wang, Ying-Ping; Zeng, Hui
Aim: To investigate how ecosystem water-use efficiency (WUE) varies spatially under different climate conditions, and how spatial variations in WUE differ from those of transpiration-based water-use efficiency (WUEt) and transpiration-based inherent water-use efficiency (IWUEt). Location: Global terrestrial ecosystems. Methods: We investigated spatial patterns of WUE using two datasets of gross primary productivity (GPP) and evapotranspiration (ET) and four biosphere model estimates of GPP and ET. Spatial relationships between WUE and climate variables were further explored through regression analyses. Results: Global WUE estimated by two satellite-based datasets is 1.9 ± 0.1 and 1.8 ± 0.6 g C m−2 mm−1 lower than the simulations from four process-based models (2.0 ± 0.3 g C m−2 mm−1) but comparable within the uncertainty of both approaches. In both satellite-based datasets and process models, precipitation is more strongly associated with spatial gradients of WUE for temperate and tropical regions, but temperature dominates north of 50° N. WUE also increases with increasing solar radiation at high latitudes. The values of WUE from datasets and process-based models are systematically higher in wet regions (with higher GPP) than in dry regions. WUEt shows a lower precipitation sensitivity than WUE, which is contrary to leaf- and plant-level observations. IWUEt, the product of WUEt and water vapour deficit, is found to be rather conservative with spatially increasing precipitation, in agreement with leaf- and plant-level measurements. Main conclusions: WUE, WUEt and IWUEt produce different spatial relationships with climate variables. In dry ecosystems, water losses from evaporation from bare soil, uncorrelated with productivity, tend to make WUE lower than in wetter regions. Yet canopy conductance is intrinsically efficient in those ecosystems and maintains a higher IWUEt. This suggests that the responses of each component flux of evapotranspiration should be analysed separately when investigating regional gradients in WUE, its temporal variability and its trends.
Interannual variability of ecosystem carbon exchange: From observation to prediction
(2017-09) Niu, Shuli; Zheng, Fu; Yiqi, Luo; Stoy, Paul C.; Keenan, Trevor F.; Poulter, Benjamin; Zhang, Leiming; Piao, Shilong; Zhou, Xuhui; Zheng, Han; Han, Jiayin; Wang, Qiufeng; Yu, Guirui
Aim Terrestrial ecosystems have sequestered, on average, the equivalent of 30% of anthropogenic carbon (C) emissions during the past decades, but annual sequestration varies from year to year. For effective C management, it is imperative to develop a predictive understanding of the interannual variability (IAV) of terrestrial net ecosystem C exchange (NEE). Location Global terrestrial ecosystems. Methods We conducted a comprehensive review to examine the IAV of NEE at global, regional and ecosystem scales. Then we outlined a conceptual framework for understanding how anomalies in climate factors impact ecological processes of C cycling and thus influence the IAV of NEE through biogeochemical regulation. Results The phenomenon of IAV in land NEE has been ubiquitously observed at global, regional and ecosystem scales. Global IAV is often attributable to either tropical or semi‐arid regions, or to some combination thereof, which is still under debate. Previous studies focus on identifying climate factors as driving forces of IAV, whereas biological mechanisms underlying the IAV of ecosystem NEE are less clear. We found that climate anomalies affect the IAV of NEE primarily through their differential impacts on ecosystem C uptake and respiration. Moreover, recent studies suggest that the carbon uptake period makes less contribution than the carbon uptake amplitude to IAV in NEE. Although land models incorporate most processes underlying IAV, their efficacy to predict the IAV in NEE remains low. Main conclusions To improve our ability to predict future IAV of the terrestrial C cycle, we have to understand biological mechanisms through which anomalies in climate factors cause the IAV of NEE. Future research needs to pay more attention not only to the differential effects of climate anomalies on photosynthesis and respiration but also to the relative importance of the C uptake period and amplitude in causing the IAV of NEE. Ultimately, we need multiple independent approaches, such as benchmark analysis, data assimilation and time‐series statistics, to integrate data, modelling frameworks and theory to improve our ability to predict future IAV in the terrestrial C cycle.
Regional Carbon Fluxes from Land Use and Land Cover Change in Asia, 1980-2009
(2016-07) Calle, Leonardo; Canadell, Josep; Patra, Prabir K.; Ciais, Philippe; Ichii, Kazuhito; Tian, Hui; Kondo, Masayuki; Piao, Shilong; Arneth, Almut; Harper, Anna B.
We present a synthesis of the land-atmosphere carbon flux from land use and land cover change (LULCC) in Asia using multiple data sources and paying particular attention to deforestation and forest regrowth fluxes. The data sources are quasi-independent and include the U.N. Food and Agriculture Organization-Forest Resource Assessment (FAO-FRA 2015; country-level inventory estimates), the Emission Database for Global Atmospheric Research (EDGARv4.3), the 'Houghton' bookkeeping model that incorporates FAO-FRA data, an ensemble of 8 state-of-the-art Dynamic Global Vegetation Models (DGVM), and 2 recently published independent studies using primarily remote sensing techniques. The estimates are aggregated spatially to Southeast, East, and South Asia and temporally for three decades, 1980–1989, 1990–1999 and 2000–2009. Since 1980, net carbon emissions from LULCC in Asia were responsible for 20%–40% of global LULCC emissions, with emissions from Southeast Asia alone accounting for 15%–25% of global LULCC emissions during the same period. In the 2000s and for all Asia, three estimates (FAO-FRA, DGVM, Houghton) were in agreement of a net source of carbon to the atmosphere, with mean estimates ranging between 0.24 to 0.41 Pg C yr−1, whereas EDGARv4.3 suggested a net carbon sink of −0.17 Pg C yr−1. Three of 4 estimates suggest that LULCC carbon emissions declined by at least 34% in the preceding decade (1990–2000). Spread in the estimates is due to the inclusion of different flux components and their treatments, showing the importance to include emissions from carbon rich peatlands and land management, such as shifting cultivation and wood harvesting, which appear to be consistently underreported.
Sunlight mediated seasonality in canopy structure & photosynthetic activity of Amazonian rainforests
(2015-06) Bi, Jian; Knyazikhin, Yuri; Choi, Sungho; Park, Taejin; Barichivich, Jonathon; Ciais, Philippe; Fu, Rong; Ganguly, Sangram; Hall, Forrest; Hilker, Thomas; Huete, Alfredo; Jones, Matthew; Kimball, John S.; Lyapustin, Alexei; Mottus, Matti; Nemani, Ramakrishna R.; Piao, Shilong; Poulter, Benjamin; Saleska, Scott R.; Saatchi, Sassan S.; Xu, Liang; Zhou, Liming; Myneni, Ranga B.
Resolving the debate surrounding the nature and controls of seasonal variation in the structure and metabolism of Amazonian rainforests is critical to understanding their response to climate change. In situ studies have observed higher photosynthetic and evapotranspiration rates, increased litterfall and leaf flushing during the Sunlight-rich dry season. Satellite data also indicated higher greenness level, a proven surrogate of photosynthetic carbon fixation, and leaf area during the dry season relative to the wet season. Some recent reports suggest that rainforests display no seasonal variations and the previous results were satellite measurement artefacts. Therefore, here we re-examine several years of data from three sensors on two satellites under a range of sun positions and satellite measurement geometries and document robust evidence for a seasonal cycle in structure and greenness of wet equatorial Amazonian rainforests. This seasonal cycle is concordant with independent observations of solar radiation. We attribute alternative conclusions to an incomplete study of the seasonal cycle, i.e. the dry season only, and to prognostications based on a biased radiative transfer model. Consequently, evidence of dry season greening in geometry corrected satellite data was ignored and the absence of evidence for seasonal variation in lidar data due to noisy and saturated signals was misinterpreted as evidence of the absence of changes during the dry season. Our results, grounded in the physics of radiative transfer, buttress previous reports of dry season increases in leaf flushing, litterfall, photosynthesis and evapotranspiration in well-hydrated Amazonian rainforests.