Dafeng Hui

Acclimatization of soil respiration to warming in a tall grass prairie.

The latest report by the Intergovernmental Panel on Climate Change (IPCC) predicts a 1.4–5.8 °C average increase in the global surface temperature over the period 1990 to 2100 (ref. 1). These estimates of future warming are greater than earlier projections, which is partly due to incorporation of a positive feedback. This feedback results from further release of greenhouse gases from terrestrial ecosystems in response to climatic warming. The feedback mechanism is usually based on the assumption that observed sensitivity of soil respiration to temperature under current climate conditions would hold in a warmer climate. However, this assumption has not been carefully examined. We have therefore conducted an experiment in a tall grass prairie ecosystem in the US Great Plains to study the response of soil respiration (the sum of root and heterotrophic respiration) to artificial warming of about 2 °C. Our observations indicate that the temperature sensitivity of soil respiration decreases—or acclimatizes—under warming and that the acclimatization is greater at high temperatures. This acclimatization of soil respiration to warming may therefore weaken the positive feedback between the terrestrial carbon cycle and climate.

ELEVATED CO2 STIMULATES NET ACCUMULATIONS OF CARBON AND NITROGEN IN LAND ECOSYSTEMS: A META‐ANALYSIS

The capability of terrestrial ecosystems to sequester carbon (C) plays a critical role in regulating future climatic change yet depends on nitrogen (N) availability. To predict long-term ecosystem C storage, it is essential to examine whether soil N becomes progressively limiting as C and N are sequestered in long-lived plant biomass and soil organic matter. A critical parameter to indicate the long-term progressive N limitation (PNL) is net change in ecosystem N content in association with C accumulation in plant and soil pools under elevated CO2. We compiled data from 104 published papers that study C and N dynamics at ambient and elevated CO2. The compiled database contains C contents, N contents, and C:N ratio in various plant and soil pools, and root:shoot ratio. Averaged C and N pool sizes in plant and soil all significantly increase at elevated CO2 in comparison to those at ambient CO2, ranging from a 5% increase in shoot N content to a 32% increase in root C content. The C and N contents in litter pools are consistently higher in elevated than ambient CO2 among all the surveyed studies whereas C and N contents in the other pools increase in some studies and decrease in other studies. The high variability in CO2-induced changes in C and N pool sizes results from diverse responses of various C and N processes to elevated CO2. Averaged C:N ratios are higher by 3% in litter and soil pools and 11% in root and shoot pools at elevated relative to ambient CO2. Elevated CO2 slightly increases root:shoot ratio. The net N accumulation in plant and soil pools at least helps prevent complete down-regulation of, and likely supports, long-term CO2 stimulation of C sequestration. The concomitant C and N accumulations in response to rising atmospheric CO2 may reflect intrinsic nature of ecosystem development as revealed before by studies of succession over hundreds to millions of years.

FIRE EFFECTS ON NITROGEN POOLS AND DYNAMICS IN TERRESTRIAL ECOSYSTEMS: A META-ANALYSIS

A comprehensive and quantitative evaluation of the effects of fire on eco- system nitrogen (N) is urgently needed for directing future fire research and management. This study used a meta-analysis method to synthesize up to 185 data sets from 87 studies published from 1955 to 1999. Six N response variables related to fire were examined: fuel N amount (FNA) and concentration (FNC), soil N amount (SNA) and concentration (SNC), and soil ammonium (NH4 1 ) and nitrate (NO3 2 ) pools. When all comparisons (fire treatment vs. control) were considered together, fire significantly reduced FNA (58%), increased soil NH4 1 (94%) and NO3 2 (152%), and had no significant influences on FNC, SNA, and SNC. The responses of N to fire varied with different independent variables, which were vegetation type, fire type, fuel type, fuel consumption amount, fuel consumption percentage, time after fire, and soil sampling depth. The response of FNA to fire was significantly influenced by vegetation type, fuel type, and fuel consumption amount and percentage. The reduction in FNA was linearly correlated with fuel consumption percentage (r 2 5 0.978). The response of FNC to fire was only affected by fuel type. None of the seven independent variables had any effect on SNA. The responses of SNC, NH4 1 , and NO3 2 depend on soil sampling depth. The responses of both NH4 1 and NO3 2 to fire were significantly affected by fire type and time after fire but had different temporal patterns. The soil NH4 1 pool increased ap- proximately twofold immediately after fire, then gradually declined to the prefire level after one year. The fire-induced increase in the soil NO 3 2 pool was small (24%) immediately after fire, reached a maximum of approximately threefold of the prefire level within 0.5- 1 year after fire, and then declined. This study has identified the general patterns of the responses of ecosystem N that occur for several years after fire. A key research need relevant to fire management is to understand how the short-term responses of N to fire influence the function and structure of terrestrial ecosystems in the long term.

Oak forest carbon and water simulations: model intercomparisons and evaluations against independent data

Models represent our primary method for integration of small-scale, process- level phenomena into a comprehensive description of forest-stand or ecosystem function. They also represent a key method for testing hypotheses about the response of forest ecosystems to multiple changing environmental conditions. This paper describes the eval- uation of 13 stand-level models varying in their spatial, mechanistic, and temporal com- plexity for their ability to capture intra- and interannual components of the water and carbon cycle for an upland, oak-dominated forest of eastern Tennessee. Comparisons between model simulations and observations were conducted for hourly, daily, and annual time steps. Data for the comparisons were obtained from a wide range of methods including: eddy covariance, sapflow, chamber-based soil respiration, biometric estimates of stand-level net primary production and growth, and soil water content by time or frequency domain reflectometry. Response surfaces of carbon and water flux as a function of environmental drivers, and a variety of goodness-of-fit statistics (bias, absolute bias, and model efficiency) were used to judge model performance. A single model did not consistently perform the best at all time steps or for all variables considered. Intermodel comparisons showed good agreement for water cycle fluxes, but considerable disagreement among models for predicted carbon fluxes. The mean of all model outputs, however, was nearly always the best fit to the observations. Not surprisingly, models missing key forest components or processes, such as roots or modeled soil water content, were unable to provide accurate predictions of ecosystem responses to short-term drought phenomenon. Nevertheless, an inability to correctly capture short-term physiolog- ical processes under drought was not necessarily an indicator of poor annual water and carbon budget simulations. This is possible because droughts in the subject ecosystem were of short duration and therefore had a small cumulative impact. Models using hourly time steps and detailed mechanistic processes, and having a realistic spatial representation of the forest ecosystem provided the best predictions of observed data. Predictive ability of all models deteriorated under drought conditions, suggesting that further work is needed to evaluate and improve ecosystem model performance under unusual conditions, such as drought, that are a common focus of environmental change discussions.

Response of soil CO2 efflux to water manipulation in a tallgrass prairie ecosystem

Although CO2 efflux plays a critical role in carbon exchange between the biosphere and atmosphere, our understanding of its regulation by soil moisture is rather limited. This study was designed to examine the relationship between soil CO2 efflux and soil moisture in a natural ecosystem by taking advantage of the historically long drought period from 29 July to 21 September 2000 in the southern Central Great Plain, USA. At the end of August when soil moisture content at the top 50 mm was reduced to less than 50 g kg−1 gravimetrically, we applied 8 levels of water treatments (simulated to rainfall of 0, 10, 25, 50, 100, 150, 200, and 300 mm) with three replicates to 24 plots in a Tallgrass Prairie ecosystem in Central Oklahoma, USA. In order to quantify root-free soil CO2 efflux, we applied the same 8 levels of water treatments to 24 500-mm soil columns using soil from field adjacent to the experimental plots. We characterized dynamic patterns of soil moisture and soil CO2 efflux over the experimental period of 21 days. Both soil moisture content and CO2 efflux showed dramatic increases immediately after the water addition, followed by a gradual decline. The time courses in response to water treatments are well described by Y=Y0+ate−bt, where Y is either soil moisture or CO2 efflux, t is time, Y0, a, and b are coefficients. Among the 8 water treatments, the maximal soil CO2 efflux rate occurred at the 50 mm water level in the field and 100 mm in the root-free soil 1 day after the treatment. The maximal soil CO2 efflux gradually shifted to higher water levels as the experiment continued. We found the relationship between soil CO2 efflux and soil moisture using the data from the 21-day experiment was highly scattered, suggesting complex mechanisms determining soil CO2 efflux by soil moisture.

Gap-filling missing data in eddy covariance measurements using multiple imputation (MI) for annual estimations

Abstract Missing data is a ubiquitous problem in evaluating long-term experimental measurements, such as those associated with the FluxNet project, due to the equipment failures, system maintenance, power-failure, and lightning strikes among other things. To estimate annual values of net ecosystem carbon exchange (NEE), latent heat flux (LE) and sensible heat flux ( H ), such gaps in the measured data must be filled or imputed. So far, no standardized method has been accepted and the imputation methods used are largely dependent on the researchers’ choice. Here, we used multiple imputation (MI) to gap-fill the missing data for annual estimations of NEE, LE and H at three flux sites associated with the FluxNet effort. MI is a Monte Carlo technique in which the missing values are replaced by several simulated values. Each data set imputed is a complete one where the observed values are the same as those in the original data set; only the missing values are different. Thus, the normal statistical analysis (e.g. annual total calculation) can be applied to each data set separately. The results of each analysis can be recombined into one summary. We applied the MI method to eddy covariance measurements collected from Walker Branch Watershed (WBW) site (a deciduous forest), Duke site (a coniferous forest) and Niwot site (a subalpine forest). Results showed that annual estimations of NEE, LE and H by MI were comparable to other imputation methods but MI was much easier to apply because of readily available software and standard algorithms. Besides the normal statistical analyses, MI also provided confidence intervals for each estimated parameter. This confidence interval is most useful when assessing energy, water, and carbon balance closures at a given tower site. Significant differences in annual NEE, LE and H were found among years at the three AmeriFlux sites. NEE at the Niwot Ridge site was lower and LE and H were higher than at the other two sites. With the available software and realistic gap-filling capability, MI has the potential to become a standardized method to gap-fill eddy covariance flux data for annual estimations and to improve the analysis of uncertainties associated with annual estimations of NEE, LE and H from regional and global flux networks.

GROSS PRIMARY PRODUCTIVITY IN DUKE FOREST: MODELING SYNTHESIS OF CO2 EXPERIMENT AND EDDY–FLUX DATA

This study was designed to estimate gross primary productivity (GPP) in the Duke Forest at both ambient and elevated CO2 (ambient + 200 fLL/L) concentrations using a physiologically based canopy model. The model stratified the canopy of loblolly pine (Pinus taeda L.) forest into six layers and estimated photosynthesis in each layer according to the Farquhar sub model coupled with the Ball-Berry stomatal conductance sub model. The model was parameterized with a suite of physiological measurements, in- cluding leaf area index (LAI), leaf nitrogen (N) concentration, photosynthesis-N relation- ships, and stomatal conductance. The model was validated against measured leaf photo- synthesis and canopy carbon (C) fluxes estimated from eddy-covariance measurements (ECM). Application of this model to simulate canopy C fixation from 28 August 1996, the onset of CO2 fumigation, to 31 December 1998 suggested that elevation of atmospheric (CO2J to ambient + 200 fLL/L resulted in increase of canopy C fixation by 35% in 1996, 39% in 1997, and 43% in 1998. The modeled GPP and its response to elevated (CO2J were sensitive to parameter values of quantum yield of electron transport, leaf area index, and the vertical distribution of LAI within the canopy. Thus, further investigation on those parameters will help improve the precision of estimated ecosystem-scale C fluxes. Fur- thermore, comparison between the modeled and ECM-estimated canopy C fluxes suggested that soil moisture, in addition to air vapor pressure, controlled canopy photosynthesis during the drought period.

Impacts of urbanization on carbon balance in terrestrial ecosystems of the Southern United States

Using a process-based Dynamic Land Ecosystem Model, we assessed carbon dynamics of urbanized/developed lands in the Southern United States during 1945-2007. The results indicated that approximately 1.72 (1.69-1.77) Pg (1P = 10(15)) carbon was stored in urban/developed lands, comparable to the storage of shrubland or cropland in the region. Urbanization resulted in a release of 0.21 Pg carbon to the atmosphere during 1945-2007. Pre-urbanization vegetation type and time since land conversion were two primary factors determining the extent of urbanization impacts on carbon dynamics. After a rapid decline of carbon storage during land conversion, an urban ecosystem gradually accumulates carbon and may compensate for the initial carbon loss in 70-100 years. The carbon sequestration rate of urban ecosystem diminishes with time, nearly disappearing in two centuries after land conversion. This study implied that it is important to take urbanization effect into account for assessing regional carbon balance.

Joint control of terrestrial gross primary productivity by plant phenology and physiology

Significance Terrestrial gross primary productivity (GPP), the total photosynthetic CO2 fixation at ecosystem level, fuels all life on land. However, its spatiotemporal variability is poorly understood, because GPP is determined by many processes related to plant phenology and physiological activities. In this study, we find that plant phenological and physiological properties can be integrated in a robust index—the product of the length of CO2 uptake period and the seasonal maximal photosynthesis—to explain the GPP variability over space and time in response to climate extremes and during recovery after disturbance. Terrestrial gross primary productivity (GPP) varies greatly over time and space. A better understanding of this variability is necessary for more accurate predictions of the future climate–carbon cycle feedback. Recent studies have suggested that variability in GPP is driven by a broad range of biotic and abiotic factors operating mainly through changes in vegetation phenology and physiological processes. However, it is still unclear how plant phenology and physiology can be integrated to explain the spatiotemporal variability of terrestrial GPP. Based on analyses of eddy–covariance and satellite-derived data, we decomposed annual terrestrial GPP into the length of the CO2 uptake period (CUP) and the seasonal maximal capacity of CO2 uptake (GPPmax). The product of CUP and GPPmax explained >90% of the temporal GPP variability in most areas of North America during 2000–2010 and the spatial GPP variation among globally distributed eddy flux tower sites. It also explained GPP response to the European heatwave in 2003 (r2 = 0.90) and GPP recovery after a fire disturbance in South Dakota (r2 = 0.88). Additional analysis of the eddy–covariance flux data shows that the interbiome variation in annual GPP is better explained by that in GPPmax than CUP. These findings indicate that terrestrial GPP is jointly controlled by ecosystem-level plant phenology and photosynthetic capacity, and greater understanding of GPPmax and CUP responses to environmental and biological variations will, thus, improve predictions of GPP over time and space.

Soil microbial community and its interaction with soil carbon and nitrogen dynamics following afforestation in central China.

Afforestation may alter soil microbial community structure and function, and further affect soil carbon (C) and nitrogen (N) dynamics. Here we investigated soil microbial carbon and nitrogen (MBC and MBN) and microbial community [e.g. bacteria (B), fungi (F)] derived from phospholipid fatty acids (PLFAs) analysis in afforested (implementing woodland and shrubland plantations) and adjacent croplands in central China. Relationships of microbial properties with biotic factors [litter, fine root, soil organic carbon (SOC), total nitrogen (TN) and inorganic N], abiotic factors (soil temperature, moisture and pH), and major biological processes [basal microbial respiration, microbial metabolic quotient (qCO2), net N mineralization and nitrification] were developed. Afforested soils had higher mean MBC, MBN and MBN:TN ratios than the croplands due to an increase in litter input, but had lower MBC:SOC ratio resulting from low-quality (higher C:N ratio) litter. Afforested soils also had higher F:B ratio, which was probably attributed to higher C:N ratios in litter and soil, and shifts of soil inorganic N forms, water, pH and disturbance. Alterations in soil microbial biomass and community structure following afforestation were associated with declines in basal microbial respiration, qCO2, net N mineralization and nitrification, which likely maintained higher soil carbon and nitrogen storage and stability.