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Träfflista för sökning "WFRF:(Luo Yiqi) srt2:(2015-2019)"

Sökning: WFRF:(Luo Yiqi) > (2015-2019)

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1.
  • Ahlström, Anders, et al. (författare)
  • Importance of vegetation dynamics for future terrestrial carbon cycling
  • 2015
  • Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 10:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Terrestrial ecosystems currently sequester about one third of anthropogenic CO 2 emissions each year, an important ecosystem service that dampens climate change. The future fate of this net uptake of CO 2 by land based ecosystems is highly uncertain. Most ecosystem models used to predict the future terrestrial carbon cycle share a common architecture, whereby carbon that enters the system as net primary production (NPP) is distributed to plant compartments, transferred to litter and soil through vegetation turnover and then re-emitted to the atmosphere in conjunction with soil decomposition. However, while all models represent the processes of NPP and soil decomposition, they vary greatly in their representations of vegetation turnover and the associated processes governing mortality, disturbance and biome shifts. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality, and the associated turnover. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the Coupled Model Intercomparison Project Phase 5 ensemble under RCP8.5 radiative forcing. By exchanging carbon cycle processes between these 13 simulations we quantified the relative roles of three main driving processes of the carbon cycle; (I) NPP, (II) vegetation dynamics and turnover and (III) soil decomposition, in terms of their contribution to future carbon (C) uptake uncertainties among the ensemble of climate change scenarios. We found that NPP, vegetation turnover (including structural shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33%, respectively, of uncertainties in modelled global C-uptake. Uncertainty due to vegetation turnover was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by biome shifts, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.
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2.
  • Huang, Kun, et al. (författare)
  • Enhanced peak growth of global vegetation and its key mechanisms
  • 2018
  • Ingår i: Nature Ecology and Evolution. - : Springer Science and Business Media LLC. - 2397-334X. ; 2:12, s. 1897-1905
  • Tidskriftsartikel (refereegranskat)abstract
    • The annual peak growth of vegetation is critical in characterizing the capacity of terrestrial ecosystem productivity and shaping the seasonality of atmospheric CO2 concentrations. The recent greening of global lands suggests an increasing trend of terrestrial vegetation growth, but whether or not the peak growth has been globally enhanced still remains unclear. Here, we use two global datasets of gross primary productivity (GPP) and a satellite-derived Normalized Difference Vegetation Index (NDVI) to characterize recent changes in annual peak vegetation growth (that is, GPPmax and NDVImax). We demonstrate that the peak in the growth of global vegetation has been linearly increasing during the past three decades. About 65% of the NDVImax variation is evenly explained by expanding croplands (21%), rising CO2 (22%) and intensifying nitrogen deposition (22%). The contribution of expanding croplands to the peak growth trend is substantiated by measurements from eddy-flux towers, sun-induced chlorophyll fluorescence and a global database of plant traits, all of which demonstrate that croplands have a higher photosynthetic capacity than other vegetation types. The large contribution of CO2 is also supported by a meta-analysis of 466 manipulative experiments and 15 terrestrial biosphere models. Furthermore, we show that the contribution of GPPmax to the change in annual GPP is less in the tropics than in other regions. These multiple lines of evidence reveal an increasing trend in the peak growth of global vegetation. The findings highlight the important roles of agricultural intensification and atmospheric changes in reshaping the seasonality of global vegetation growth.
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3.
  • Komatsu, Kimberly J., et al. (författare)
  • Global change effects on plant communities are magnified by time and the number of global change factors imposed
  • 2019
  • Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 116:36, s. 17867-17873
  • Tidskriftsartikel (refereegranskat)abstract
    • Accurate prediction of community responses to global change drivers (GCDs) is critical given the effects of biodiversity on ecosystem services. There is consensus that human activities are driving species extinctions at the global scale, but debate remains over whether GCDs are systematically altering local communities worldwide. Across 105 experiments that included over 400 experimental manipulations, we found evidence for a lagged response of herbaceous plant communities to GCDs caused by shifts in the identities and relative abundances of species, often without a corresponding difference in species richness. These results provide evidence that community responses are pervasive across a wide variety of GCDs on long-term temporal scales and that these responses increase in strength when multiple GCDs are simultaneously imposed.Global change drivers (GCDs) are expected to alter community structure and consequently, the services that ecosystems provide. Yet, few experimental investigations have examined effects of GCDs on plant community structure across multiple ecosystem types, and those that do exist present conflicting patterns. In an unprecedented global synthesis of over 100 experiments that manipulated factors linked to GCDs, we show that herbaceous plant community responses depend on experimental manipulation length and number of factors manipulated. We found that plant communities are fairly resistant to experimentally manipulated GCDs in the short term (<10 y). In contrast, long-term (≥10 y) experiments show increasing community divergence of treatments from control conditions. Surprisingly, these community responses occurred with similar frequency across the GCD types manipulated in our database. However, community responses were more common when 3 or more GCDs were simultaneously manipulated, suggesting the emergence of additive or synergistic effects of multiple drivers, particularly over long time periods. In half of the cases, GCD manipulations caused a difference in community composition without a corresponding species richness difference, indicating that species reordering or replacement is an important mechanism of community responses to GCDs and should be given greater consideration when examining consequences of GCDs for the biodiversity–ecosystem function relationship. Human activities are currently driving unparalleled global changes worldwide. Our analyses provide the most comprehensive evidence to date that these human activities may have widespread impacts on plant community composition globally, which will increase in frequency over time and be greater in areas where communities face multiple GCDs simultaneously.
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4.
  • Li, Zhao, et al. (författare)
  • Non-uniform seasonal warming regulates vegetation greening and atmospheric CO2 amplification over northern lands
  • 2018
  • Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 13:12
  • Tidskriftsartikel (refereegranskat)abstract
    • The enhanced vegetation growth by climate warming plays a pivotal role in amplifying the seasonal cycle of atmospheric CO2 at northern lands (>50° N) since 1960s. However, the correlation between vegetation growth, temperature and seasonal amplitude of atmospheric CO2 concentration have become elusive with the slowed increasing trend of vegetation growth and weakened temperature control on CO2 uptake since late 1990s. Here, based on in situ atmospheric CO2 concentration records from the Barrow observatory site, we found a slowdown in the increasing trend of the atmospheric CO2 amplitude from 1990s to mid-2000s. This phenomenon was associated with the paused decrease in the minimum CO2 concentration ([CO2]min), which was significantly correlated with the slowdown of vegetation greening and growing-season length extension. We then showed that both the vegetation greenness and growing-season length were positively correlated with spring but not autumn temperature over the northern lands. Furthermore, such asymmetric dependences of vegetation growth upon spring and autumn temperature cannot be captured by the state-of-art terrestrial biosphere models. These findings indicate that the responses of vegetation growth to spring and autumn warming are asymmetric, and highlight the need of improving autumn phenology in the models for predicting seasonal cycle of atmospheric CO2 concentration.
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5.
  • Luo, Yiqi, et al. (författare)
  • Toward more realistic projections of soil carbon dynamics by Earth system models
  • 2016
  • Ingår i: Global Biogeochemical Cycles. - 0886-6236. ; 30:1, s. 40-56
  • Tidskriftsartikel (refereegranskat)abstract
    • Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.
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6.
  • Luo, Yiqi, et al. (författare)
  • Transient dynamics of terrestrial carbon storage : Mathematical foundation and its applications
  • 2017
  • Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 14:1, s. 145-161
  • Tidskriftsartikel (refereegranskat)abstract
    • Terrestrial ecosystems have absorbed roughly 30 % of anthropogenic CO2 emissions over the past decades, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling and experimental and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under global change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, which is the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3-D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. In addition, the physical emulators make data assimilation computationally feasible so that both C flux-and pool-related datasets can be used to better constrain model predictions of land C sequestration. Overall, this new mathematical framework offers new approaches to understanding, evaluating, diagnosing, and improving land C cycle models.
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7.
  • McGuire, A. David, et al. (författare)
  • Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009
  • 2016
  • Ingår i: Global Biogeochemical Cycles. - 0886-6236 .- 1944-9224. ; 30:7, s. 1015-1037
  • Tidskriftsartikel (refereegranskat)abstract
    • A significant portion of the large amount of carbon (C) currently stored in soils of the permafrost region in the Northern Hemisphere has the potential to be emitted as the greenhouse gases CO2 and CH4 under a warmer climate. In this study we evaluated the variability in the sensitivity of permafrost and C in recent decades among land surface model simulations over the permafrost region between 1960 and 2009. The 15 model simulations all predict a loss of near-surface permafrost (within 3m) area over the region, but there are large differences in the magnitude of the simulated rates of loss among the models (0.2 to 58.8x10(3)km(2)yr(-1)). Sensitivity simulations indicated that changes in air temperature largely explained changes in permafrost area, although interactions among changes in other environmental variables also played a role. All of the models indicate that both vegetation and soil C storage together have increased by 156 to 954TgCyr(-1) between 1960 and 2009 over the permafrost region even though model analyses indicate that warming alone would decrease soil C storage. Increases in gross primary production (GPP) largely explain the simulated increases in vegetation and soil C. The sensitivity of GPP to increases in atmospheric CO2 was the dominant cause of increases in GPP across the models, but comparison of simulated GPP trends across the 1982-2009 period with that of a global GPP data set indicates that all of the models overestimate the trend in GPP. Disturbance also appears to be an important factor affecting C storage, as models that consider disturbance had lower increases in C storage than models that did not consider disturbance. To improve the modeling of C in the permafrost region, there is the need for the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost C feedback and for the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.
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8.
  • van Gestel, Natasja, et al. (författare)
  • Predicting soil carbon loss with warming
  • 2018
  • Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 554:E4-5
  • Tidskriftsartikel (refereegranskat)
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9.
  • Wu, Zhendong, et al. (författare)
  • Approaching the potential of model-data comparisons of global land carbon storage
  • 2019
  • Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9
  • Tidskriftsartikel (refereegranskat)abstract
    • Carbon storage dynamics in vegetation and soil are determined by the balance of carbon influx and turnover. Estimates of these opposing fluxes differ markedly among different empirical datasets and models leading to uncertainty and divergent trends. To trace the origin of such discrepancies through time and across major biomes and climatic regions, we used a model-data fusion framework. The framework emulates carbon cycling and its component processes in a global dynamic ecosystem model, LPJ-GUESS, and preserves the model-simulated pools and fluxes in space and time. Thus, it allows us to replace simulated carbon influx and turnover with estimates derived from empirical data, bringing together the strength of the model in representing processes, with the richness of observational data informing the estimations. The resulting vegetation and soil carbon storage and global land carbon fluxes were compared to independent empirical datasets. Results show model-data agreement comparable to, or even better than, the agreement between independent empirical datasets. This suggests that only marginal improvement in land carbon cycle simulations can be gained from comparisons of models with current-generation datasets on vegetation and soil carbon. Consequently, we recommend that model skill should be assessed relative to reference data uncertainty in future model evaluation studies.
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10.
  • Xia, Jianyang, et al. (författare)
  • Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region
  • 2017
  • Ingår i: Journal of Geophysical Research - Biogeosciences. - 2169-8953. ; 122:2, s. 430-446
  • Tidskriftsartikel (refereegranskat)abstract
    • Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246±6gCm-2yr-1), most models produced higher NPP (309±12gCm-2yr-1) over the permafrost region during 2000-2009. By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982-2009, there was a twofold discrepancy among models (380 to 800gCm-2yr-1), which mainly resulted from differences in simulated maximum monthly GPP (GPPmax). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vcmax_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPPmax as well as their sensitivity to climate change.
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