Qianlai Zhuang

Methane fluxes between terrestrial ecosystems and the atmosphere at northern high latitudes during the past century : a retrospective analysis with a process-based biogeochemistry model

minus consumption) from these soils have increased by an average 0.08 Tg CH4 yr � 1 during the twentieth century. Our estimate of the annual net emission rate at the end of the century for the region is 51 Tg CH4 yr � 1 . Russia, Canada, and Alaska are the major CH4 regional sources to the atmosphere, responsible for 64%, 11%, and 7% of these net emissions, respectively. Our simulations indicate that large interannual variability in net CH4 emissions occurred over the last century. Our analyses of the responses of net CH4 emissions to the past climate change suggest that future global warming will increase net CH4 emissions from the Pan-Arctic region. The higher net CH4 emissions may increase atmospheric CH4 concentrations to provide a major positive feedback to the climate system. INDEX TERMS: 1610 Global Change: Atmosphere (0315, 0325); 1615 Global Change: Biogeochemical processes (4805); 1620 Global Change: Climate dynamics (3309); 1890 Hydrology: Wetlands; KEYWORDS: methane emissions, methane oxidation, permafrost

Modeling soil thermal and carbon dynamics of a fire chronosequence in interior Alaska

[1] In this study, the dynamics of soil thermal, hydrologic, and ecosystem processes were coupled to project how the carbon budgets of boreal forests will respond to changes in atmospheric CO2, climate, and fire disturbance. The ability of the model to simulate gross primary production and ecosystem respiration was verified for a mature black spruce ecosystem in Canada, the age-dependent pattern of the simulated vegetation carbon was verified with inventory data on aboveground growth of Alaskan black spruce forests, and the model was applied to a postfire chronosequence in interior Alaska. The comparison between the simulated soil temperature and field-based estimates during the growing season (May to September) of 1997 revealed that the model was able to accurately simulate monthly temperatures at 10 cm (R > 0.93) for control and burned stands of the fire chronosequence. Similarly, the simulated and field-based estimates of soil respiration for control and burned stands were correlated (R = 0.84 and 0.74 for control and burned stands, respectively). The simulated and observed decadal to centuryscale dynamics of soil temperature and carbon dynamics, which are represented by mean monthly values of these variables during the growing season, were correlated among stands (R = 0.93 and 0.71 for soil temperature at 20- and 10-cm depths, R = 0.95 and 0.91 for soil respiration and soil carbon, respectively). Sensitivity analyses indicate that along with differences in fire and climate history a number of other factors influence the response of carbon dynamics to fire disturbance. These factors include nitrogen fixation, the growth of moss, changes in the depth of the organic layer, soil drainage, and fire severity. INDEX TERMS: 1615 Global Change: Biogeochemical processes (4805); 0315 Atmospheric Composition and Structure: Biosphere/atmosphere interactions; 0330 Atmospheric Composition and Structure: Geochemical cycles; KEYWORDS: carbon, fire, nitrogen, hydrology, permafrost

Incorporation of a permafrost model into a large-scale ecosystem model: Evaluation of temporal and spatial scaling issues in simulating soil thermal dynamics

This study evaluated whether a model of permafrost dynamics with a 0.5-day resolution internal time step that is driven by monthly climate inputs is adequate for representing the soil thermal dynamics in a large-scale ecosystem model. An extant version of the Goodrich model was modified to develop a soil thermal model (STM) with the capability to operate with either 0.5-hour or 0.5-day internal time steps and to be driven with either daily or monthly input data. The choice of internal time step had little effect on the simulation of soil thermal dynamics of a black spruce site in Alaska. The use of monthly climate inputs to drive the model resulted in an error of less than 1°C in the upper organic soil layer and in an accurate simulation of seasonal active layer dynamics. Uncertainty analyses of the STM driven with monthly climate inputs identified that soil temperature estimates of the upper organic layer were most sensitive to variability in parameters that described snow thermal conductivity, moss thickness, and moss thermal conductivity. The STM was coupled to the Terrestrial Ecosystem Model (TEM), and the performance of the coupled model was verified for the simulation of soil temperatures in applications to a black spruce site in Canada and to white spruce, aspen, and tundra sites in Alaska. A 1°C error in the temperature of the upper organic soil layer had little influence on the carbon dynamics simulated for the black spruce site in Canada. Application of the model across the range of black spruce ecosystems in North America demonstrated that the STM-TEM has the capability to operate over temporal and spatial domains that consider substantial variation in surface climate given that spatial variability in key structural characteristics and physical properties of the soil thermal regime are described.

An analysis of the carbon balance of the Arctic Basin from 1997 to 2006

This study used several model-based tools to analyse the dynamics of the Arctic Basin between 1997 and 2006 as a linked system of land-ocean-atmosphere C exchange. The analysis estimates that terrestrial areas of the Arctic Basin lost 62.9 Tg C yr-1 and that the Arctic Ocean gained 94.1 Tg C yr-1. Arctic lands and oceans were a net CO2 sink of 108.9 Tg C yr-1, which is within the range of uncertainty in estimates from atmospheric inversions. Although both lands and oceans of the Arctic were estimated to be CO2 sinks, the land sink diminished in strength because of increased fire disturbance compared to previous decades, while the ocean sink increased in strength because of increased biological pump activity associated with reduced sea ice cover. Terrestrial areas of the Arctic were a net source of 41.5 Tg CH4 yr-1 that increased by 0.6 Tg CH4 yr-1 during the decade of analysis, a magnitude that is comparable with an atmospheric inversion of CH4. Because the radiative forcing of the estimated CH4 emissions is much greater than the CO2 sink, the analysis suggests that the Arctic Basin is a substantial net source of green house gas forcing to the climate system.

Assessing the carbon balance of circumpolar Arctic tundra using remote sensing and process modeling

This paper reviews the current status of using remote sensing and process-based modeling approaches to assess the contemporary and future circumpolar carbon balance of Arctic tundra, including the exchange of both carbon dioxide and methane with the atmosphere. Analyses based on remote sensing approaches that use a 20-year data record of satellite data indicate that tundra is greening in the Arctic, suggesting an increase in photosynthetic activity and net primary production. Modeling studies generally simulate a small net carbon sink for the distribution of Arctic tundra, a result that is within the uncertainty range of field-based estimates of net carbon exchange. Applications of process-based approaches for scenarios of future climate change generally indicate net carbon sequestration in Arctic tundra as enhanced vegetation production exceeds simulated increases in decomposition. However, methane emissions are likely to increase dramatically, in response to rising soil temperatures, over the next century. Key uncertainties in the response of Arctic ecosystems to climate change include uncertainties in future fire regimes and uncertainties relating to changes in the soil environment. These include the response of soil decomposition and respiration to warming and deepening of the soil active layer, uncertainties in precipitation and potential soil drying, and distribution of wetlands. While there are numerous uncertainties in the projections of process-based models, they generally indicate that Arctic tundra will be a small sink for carbon over the next century and that methane emissions will increase considerably, which implies that exchange of greenhouse gases between the atmosphere and Arctic tundra ecosystems is likely to contribute to climate warming.

Reorganization of vegetation, hydrology and soil carbon after permafrost degradation across heterogeneous boreal landscapes

The diversity of ecosystems across boreal landscapes, successional changes after disturbance and complicated permafrost histories, present enormous challenges for assessing how vegetation, water and soil carbon may respond to climate change in boreal regions. To address this complexity, we used a chronosequence approach to assess changes in vegetation composition, water storage and soil organic carbon (SOC) stocks along successional gradients within four landscapes: (1) rocky uplands on ice-poor hillside colluvium, (2) silty uplands on extremely ice-rich loess, (3) gravelly‐sandy lowlands on ice-poor eolian sand and (4) peaty‐silty lowlands on thick ice-rich peat deposits over reworked lowland loess. In rocky uplands, after fire permafrost thawed rapidly due to low ice contents, soils became well drained and SOC stocks decreased slightly. In silty uplands, after fire permafrost persisted, soils remained saturated and SOC decreased slightly. In gravelly‐sandy lowlands where permafrost persisted in drier forest soils, loss of deeper permafrost around lakes has allowed recent widespread drainage of lakes that has exposed limnic material with high SOC to aerobic decomposition. In peaty‐silty lowlands, 2‐4 m of thaw settlement led to fragmented drainage patterns in isolated thermokarst bogs and flooding of soils, and surface soils accumulated new bog peat. We were not able to detect SOC changes in deeper soils, however, due to high variability. Complicated soil stratigraphy revealed that permafrost has repeatedly aggraded and degraded in all landscapes during the Holocene, although in silty uplands only the upper permafrost was affected. Overall, permafrost thaw has led to the reorganization of vegetation, water storage and flow paths, and patterns of SOC accumulation. However, changes have occurred over different timescales among landscapes: over decades in rocky uplands and gravelly‐sandy lowlands in response to fire and lake drainage, over decades to centuries in Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

Twentieth-Century Droughts and Their Impacts on Terrestrial Carbon Cycling in China

Abstract Midlatitude regions experienced frequent droughts during the twentieth century, but their impacts on terrestrial carbon balance are unclear. This paper presents a century-scale study of drought effects on the carbon balance of terrestrial ecosystems in China. The authors first characterized the severe extended droughts over the period 1901–2002 using the Palmer drought severity index and then examined how these droughts affected the terrestrial carbon dynamics using tree-ring width chronologies and a process-based biogeochemistry model, the Terrestrial Ecosystem Model (TEM). It is found that China suffered from a series of severe extended droughts during the twentieth century. The major drought periods included 1920–30, 1939–47, 1956–58, 1960–63, 1965–68, 1978–80, and 1999–2002. Most droughts generally reduced net primary productivity (NPP) and net ecosystem productivity (NEP) in large parts of drought-affected areas. Moreover, some of the droughts substantially reduced the countrywide annual NPP...

Net emissions of CH4 and CO2 in Alaska: implications for the region's greenhouse gas budget.

We used a biogeochemistry model, the Terrestrial Ecosystem Model (TEM), to study the net methane (CH4) fluxes between Alaskan ecosystems and the atmosphere. We estimated that the current net emissions of CH4 (emissions minus consumption) from Alaskan soils are approximately 3 Tg CH4/yr. Wet tundra ecosystems are responsible for 75% of the regions net emissions, while dry tundra and upland boreal forests are responsible for 50% and 45% of total consumption over the region, respectively. In response to climate change over the 21st century, our simulations indicated that CH4 emissions from wet soils would be enhanced more than consumption by dry soils of tundra and boreal forests. As a consequence, we projected that net CH4 emissions will almost double by the end of the century in response to high-latitude warming and associated climate changes. When we placed these CH4 emissions in the context of the projected carbon budget (carbon dioxide [CO2] and CH4) for Alaska at the end of the 21st century, we estimated that Alaska will be a net source of greenhouse gases to the atmosphere of 69 Tg CO2 equivalents/yr, that is, a balance between net methane emissions of 131 Tg CO2 equivalents/yr and carbon sequestration of 17 Tg C/yr (62 Tg CO2 equivalents/yr).

Impacts of land use change due to biofuel crops on carbon balance, bioenergy production, and agricultural yield, in the conterminous United States

Growing concerns about energy and the environment have led to worldwide use of bioenergy. Switching from food crops to biofuel crops is an option to meet the fast‐growing need for biofuel feedstocks. This land use change consequently affects the ecosystem carbon balance. In this study, we used a biogeochemistry model, the Terrestrial Ecosystem Model, to evaluate the impacts of this change on the carbon balance, bioenergy production, and agricultural yield, assuming that several land use change scenarios from corn, soybean, and wheat to biofuel crops of switchgrass and Miscanthus will occur. We found that biofuel crops have much higher net primary production (NPP) than soybean and wheat crops. When food crops from current agricultural lands were changed to different biofuel crops, the national total NPP increased in all cases by a range of 0.14–0.88 Pg C yr−1, except while switching from corn to switchgrass when a decrease of 14% was observed. Miscanthus is more productive than switchgrass, producing about 2.5 times the NPP of switchgrass. The net carbon loss ranges from 1.0 to 6.3 Tg C yr−1 if food crops are changed to switchgrass, and from 0.4 to 6.7 Tg C yr−1 if changed to Miscanthus. The largest loss was observed when soybean crops were replaced with biofuel crops. Soil organic carbon increased significantly when land use changed, reaching 100 Mg C ha−1 in biofuel crop ecosystems. When switching from food crops to Miscanthus, the per unit area croplands produced a larger amount of ethanol than that of original food crops. In comparison, the land use change from wheat to Miscanthus produced more biomass and sequestrated more carbon. Our study suggests that Miscanthus could better serve as an energy crop than food crops or switchgrass, considering both economic and environmental benefits.

A global sensitivity analysis and Bayesian inference framework for improving the parameter estimation and prediction of a process-based Terrestrial Ecosystem Model

[1] A global sensitivity analysis and Bayesian inference framework was developed for improving the parameterization and predictability of a monthly time step process-based biogeochemistry model. Using a Latin Hypercube sampler and an existing Terrestrial Ecosystem Model (TEM), a set of 500,000 Monte Carlo ensemble simulations was conducted for a black spruce forest ecosystem. A global sensitivity analysis was then conducted to identify the key model parameters and examine the interaction structures among TEM parameters. Bayesian inference analysis was also performed using these ensemble simulations and eddy flux data of carbon, latent heat flux, and MODIS gross primary production (GPP) to reduce the uncertainty of parameter estimation and prediction of TEM. We found that (1) the simulated carbon fluxes are mostly affected by parameters of the maximum rate of photosynthesis (CMAX), the half-saturation constant for CO2 uptake by plants (kc), the half-saturation constant for Photosynthetically Active Radiation used by plants (ki), and the change in autotrophic respiration due to 10C temperature increase (RHQ10); (2) the effect of parameters on seasonal carbon dynamics varies from one parameter to another during a year; (3) to well constrain the uncertainties of TEM predictions and parameters using the Bayesian inference technique, at least two different fluxes of NEP, GPP, and ecosystem respiration (RESP) are required; and (4) different assumptions of the error structures of the flux data used in the Bayesian inference analysis result in different uncertainty bounds of the posterior parameters and model predictions. We further found that, using the Bayesian framework and eddy flux and satellite data, the uncertainty of simulated carbon fluxes has been remarkably reduced. The developed global sensitivity analysis and Bayesian framework could further be used to analyze and improve the predictability and parameterization of relatively coarse time step biogeochemistry models when the eddy flux and satellite data are available for other terrestrial ecosystems.