Geology topics

S. Liu

Publications and source records attributed to S. Liu.

31 records · Page 2Linked to original sources

USGS2008

Uncertainty and sensitivity issues in process-based models of carbon and nitrogen cycles in terrestrial ecosystems

Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for northern forest ecosystems. These models are widely used to evaluate the long-term decisions in forest management dealing with effects like particulate pollution, productivity and climate change. Regarding climate change, one of the key questions that have sensitive political implications is whether northern forests will sequester atmospheric C or not. Whilst many process-based models have been tested for accuracy by evaluating or validating against observed data, few have dealt with the complexity of the incorporated procedures to estimate uncertainties associated with model predictions or the sensitivity of these predictions to input factors in a systematic, inter-model comparison fashion. In general, models differ in their underlying attempts to match natural complexities with assumed or imposed model structure and process formulations to estimate model parameters, to gather data and to address issues on scope, scale and natural variations. Uncertainties may originate from model structure, estimation of model parameters, data input, representation of natural variation and scaling exercises. Model structure relates to the mathematical representation of the processes modelled and the type of state variables that a model contains. The modelling of partitioning among above- and below-ground C and N pools and the interdependence among these pools remain a major source of uncertainty in model structure and error propagation. For example, most soil C models use at least three state variables to represent the different types of soil organic matter (SOM). This approach results in creating three artificial SOM pools, assuming that each one contains C compounds with the same turnover rate. In reality, SOM consists of many different types of C compounds with widely different turnover rates. Uncertainty in data and parameter estimates are closely linked. Data uncertainties are associated with high variations in estimating forest biomass, productivity and soil organic matter and their estimates may be incomplete for model initialisation, calibration, validation and sensitivity analysis of generalised predictor models. The scale at which a model is being used also affects the level of uncertainty, as the errors in the prediction of the C and N dynamics differ from site to landscape levels and across climatic regions. If the spatial or temporal scale of a model application is changed, additional uncertainty arises from neglecting natural variability in system variables in time and space. Uncertainty issues are also intimately related to model validation and sensitivity analysis. The estimation of uncertainties is needed to inform decision processes in order to detect the possible corridor of development. Uncertainty in this context is an essential measure of quality for stakeholder and decision makers.

Book chapter↗

USGS2007

Optimization of an ecosystem model through the assimilation of eddy flux observations using a smoothed ensemble Kalman filter

The parameters of ecosystem models are conventionally optimized through nonsequential inversion methods, which treat observations as a whole and lack the flexibility to investigate possible temporal evolution of the model parameters. This research developed a smoothed ensemble Kalman filter (SEnKF) to assess to what extent the parameters and state variables of an ecosystem model can be simultaneously optimized through the assimilation of eddy flux observations. The performance of the SEnKF was demonstrated in one case study: the assimilation of measurements of carbon exchange between a mixed forest and the atmosphere at Niwot Ridge Forest (Colorado, USA) from 2000 to 2004 into a carbon flux partition model. Our analyses demonstrated that some model parameters, such as light use efficiency and respiration coefficients, were highly constrained by eddy flux data at daily to seasonal time scales. Light use efficiency was strongly seasonal. Model predictions based on parameters modified by the SEnKF were much improved, compared to predictions made without progressive data assimilation. The SEnKF reduced the variance of state variables that is caused by uncertainties of parameters and driving variables. The analysis of net ecosystem exchange of carbon between the forest and the atmosphere was improved.

Conference Paper↗

USGS2006

Litterfall production along successional and altitudinal gradients of subtropical monsoon evergreen broadleaved forests in Guangdong, China

Evaluation of litterfall production is important for understanding nutrient cycling, forest growth, successional pathways, and interactions with environmental variables in forest ecosystems. Litterfall was intensively studied during the period of 1982-2001 in two subtropical monsoon vegetation gradients in the Dinghushan Biosphere Reserve, Guangdong Province, China. The two gradients include: (1) a successional gradient composed of pine forest (PF), mixed pine and broadleaved forest (MF) and monsoon evergreen broadleaved forest (BF), and (2) an altitudinal gradient composed of Baiyunci ravine rain forest (BRF), Qingyunci ravine rain forest (QRF), BF and mountainous evergreen broadleaved forest (MMF). Mean annual litterfall production was 356, 861 and 849 g m-2 for PF, MF and BF of the successional gradient, and 1016, 1061, 849 and 489 g m-2 for BRF, QRF, BF and MMF of the altitudinal gradient, respectively. As expected, mean annual litterfall of the pioneer forest PF was the lowest, but rapidly increased over the observation period while those in other forests were relatively stable, confirming that forest litterfall production is closely related to successional stages and growth patterns. Leaf proportions of total litterfall in PF, MF, BF, BRF, QRF and MMF were 76.4%, 68.4%, 56.8%, 55.7%, 57.6% and 69.2%, respectively, which were consistent with the results from studies in other evergreen broadleaved forests. Our analysis on litterfall monthly distributions indicated that litterfall production was much higher during the period of April to September compared to other months for all studied forest types. Although there were significant impacts of some climate variables (maximum and effective temperatures) on litterfall production in some of the studied forests, the mechanisms of how climate factors (temperature and rainfall) interactively affect litterfall await further study. ?? 2006 Springer Science+Business Media B.V.

Plant Ecology↗

USGS2006

Soil-atmospheric exchange of CO2, CH4, and N2O in three subtropical forest ecosystems in southern China

The magnitude, temporal, and spatial patterns of soil-atmospheric greenhouse gas (hereafter referred to as GHG) exchanges in forests near the Tropic of Cancer are still highly uncertain. To contribute towards an improvement of actual estimates, soil-atmospheric CO2, CH4, and N2O fluxes were measured in three successional subtropical forests at the Dinghushan Nature Reserve (hereafter referred to as DNR) in southern China. Soils in DNR forests behaved as N2O sources and CH4 sinks. Annual mean CO2, N2O, and CH4 fluxes (mean ?? SD) were 7.7 ?? 4.6MgCO2-Cha-1 yr-1, 3.2 ?? 1.2 kg N2ONha-1 yr-1, and 3.4 ?? 0.9 kgCH4-Cha-1 yr-1, respectively. The climate was warm and wet from April through September 2003 (the hot-humid season) and became cool and dry from October 2003 through March 2004 (the cool-dry season). The seasonality of soil CO2 emission coincided with the seasonal climate pattern, with high CO2 emission rates in the hot-humid season and low rates in the cool-dry season. In contrast, seasonal patterns of CH4 and N2O fluxes were not clear, although higher CH4 uptake rates were often observed in the cool-dry season and higher N2O emission rates were often observed in the hot-humid season. GHG fluxes measured at these three sites showed a clear increasing trend with the progressive succession. If this trend is representative at the regional scale, CO2 and N2O emissions and CH4 uptake in southern China may increase in the future in light of the projected change in forest age structure. Removal of surface litter reduced soil CO2 effluxes by 17-44% in the three forests but had no significant effect on CH4 absorption and N2O emission rates. This suggests that microbial CH4 uptake and N2O production was mainly related to the mineral soil rather than in the surface litter layer. ?? 2006 Blackwell Publishing Ltd.

Global Change Biology↗

USGS2006

Belowground carbon balance and carbon accumulation rate in the successional series of monsoon evergreen broad-leaved forest

The balance, accumulation rate and temporal dynamics of belowground carbon in the successional series of monsoon evergreen broadleaved forest are obtained in this paper, based on long-term observations to the soil organic matter, input and standing biomass of litter and coarse woody debris, and dissolved organic carbon carried in the hydrological process of subtropical climax forest ecosystem—monsoon evergreen broad-leaved forest, and its two successional forests of natural restoration—coniferous and broad-leaved mixed forest and Pinus massoniana forest, as well as data of root biomass obtained once every five years and respiration measurement of soil, litter and coarse woody debris respiration for 1 year. The major results include: the belowground carbon pools of monsoon evergreen broad-leaved forest, coniferous and broad-leaved mixed forest, and Pinus massoniana forest are 23191 ± 2538 g · m −2 , 16889 ± 1936 g · m −2 and 12680 ± 1854 g · m −2 , respectively, in 2002. Mean annual carbon accumulation rates of the three forest types during the 24a from 1978 to 2002 are 383 ± 97 g · m −2 · a −1 , 193 ± 85 g · m −2 · a −1 and 213 ± 86 g · m −2 · a −1 , respectively. The belowground carbon pools in the three forest types keep increasing during the observation period, suggesting that belowground carbon pools are carbon sinks to the atmosphere. There are seasonal variations, namely, they are strong carbon sources from April to June, weak carbon sources from July to September; while they are strong carbon sinks from October to November, weak carbon sinks from December to March.

Science in China, Series D: Earth Sciences↗

USGS2006

Temporal evolution of carbon budgets of the Appalachian forests in the U.S. from 1972 to 2000

Estimating dynamic terrestrial ecosystem carbon (C) sources and sinks over large areas is difficult. The scaling of C sources and sinks from the field level to the regional level has been challenging due to the variations of climate, soil, vegetation, and disturbances. As part of an effort to estimate the spatial, temporal, and sectional dimensions of the United States C sources and sinks (the U.S. Carbon Trends Project), this study estimated the forest ecosystem C sequestration of the Appalachian region (186,000 km 2 ) for the period of 1972–2000 using the General Ensemble Biogeochemical Modeling System (GEMS) that has a strong capability of assimilating land use and land cover change (LUCC) data. On 82 sampling blocks in the Appalachian region, GEMS used sequential 60 m resolution land cover change maps to capture forest stand-replacing events and used forest inventory data to estimate non-stand-replacing changes. GEMS also used Monte Carlo approaches to deal with spatial scaling issues such as initialization of forest age and soil properties. Ensemble simulations were performed to incorporate the uncertainties of input data. Simulated results show that from 1972 to 2000 the net primary productivity (NPP), net ecosystem productivity (NEP), and net biome productivity (NBP) averaged 6.2 Mg C ha −1 y −1 (±1.1), 2.2 Mg C ha −1 y −1 (±0.6), and 1.8 Mg C ha −1 y −1 (±0.6), respectively. The inter-annual variability was driven mostly by climate. Detailed C budgets for the year 2000 were also calculated. Within a total 148,000 km 2 forested area, average forest ecosystem C density was estimated to be 186 Mg C ha −1 (±20), of which 98 Mg C ha −1 (±12) was in biomass and 88 Mg C ha −1 (±13) was in litter and soil. The total simulated C stock of the Appalachian forests was estimated to be 2751 Tg C (±296), including 1454 Tg C (±178) in living biomass and 1297 Tg C (±192) in litter and soil. The total net C sequestration (i.e. NBP) of the forest ecosystem in 2000 was estimated to be 19.5 Tg C y −1 (±6.8).

Forest Ecology and Management↗

USGS2006

Old-growth forests can accumulate carbon in soils

Old-growth forests have traditionally been considered negligible as carbon sinks because carbon uptake has been thought to be balanced by respiration. We show that the top 20-centimeter soil layer in preserved old-growth forests in southern China accumulated atmospheric carbon at an unexpectedly high average rate of 0.61 megagrams of carbon hectare-1 year-1 from 1979 to 2003. This study suggests that the carbon cycle processes in the belowground system of these forests are changing in response to the changing environment. The result directly challenges the prevailing belief in ecosystem ecology regarding carbon budget in old-growth forests and supports the establishment of a new, nonequilibrium conceptual framework to study soil carbon dynamics.

Science↗

USGS2005

Soil organic carbon dynamics as related to land use history in the northwestern Great Plains

Strategies for mitigating the global greenhouse effect must account for soil organic carbon (SOC) dynamics at both spatial and temporal scales, which is usually challenging owing to limitations in data and approach. This study was conducted to characterize the SOC dynamics associated with land use change history in the northwestern Great Plains ecoregion. A sampling framework (40 sample blocks of 10 × 10 km 2 randomly located in the ecoregion) and the General Ensemble Biogeochemical Modeling System (GEMS) were used to quantify the spatial and temporal variability in the SOC stock from 1972 to 2001. Results indicate that C source and sink areas coexisted within the ecoregion, and the SOC stock in the upper 20-cm depth increased by 3.93 Mg ha −1 over the 29 years. About 17.5% of the area was evaluated as a C source at 122 kg C ha −1 yr −1 . The spatial variability of SOC stock was attributed to the dynamics of both slow and passive fractions, while the temporal variation depended on the slow fraction only. The SOC change at the block scale was positively related to either grassland proportion or negatively related to cropland proportion. We concluded that the slow C pool determined whether soils behaved as sources or sinks of atmospheric CO 2 , but the strength depended on antecedent SOC contents, land cover type, and land use change history in the ecoregion.

Global Biogeochemical Cycles↗

USGS2004

Contemporary carbon dynamics in terrestrial ecosystems in the Southeastern Plains of the United States

Quantifying carbon dynamics over large areas is frequently hindered by the lack of consistent, high-quality, spatially explicit land use and land cover change databases and appropriate modeling techniques. In this paper, we present a generic approach to address some of these challenges. Land cover change information in the Southeastern Plains ecoregion was derived from Landsat data acquired in 1973, 1980, 1986, 1992, and 2000 within 11 randomly located 20-km × 20-km sample blocks. Carbon dynamics within each of the sample blocks was simulated using the General Ensemble Biogeochemical Modeling System (GEMS), capable of assimilating the variances and covariance of major input variables into simulations using an ensemble approach. Results indicate that urban and forest areas have been increasing, whereas agricultural land has been decreasing since 1973. Forest clear-cutting activity has intensified, more than doubling from 1973 to 2000. The Southeastern Plains has been acting as a carbon sink since 1973, with an average rate of 0.89 Mg C/ha/yr. Biomass, soil organic carbon (SOC), and harvested materials account for 56%, 34%, and 10% of the sink, respectively. However, the sink has declined continuously during the same period owing to forest aging in the northern part of the ecoregion and increased forest clear-cutting activities in the south. The relative contributions to the sink from SOC and harvested materials have increased, implying that these components deserve more study in the future. The methods developed here can be used to quantify the impacts of human management activities on the carbon cycle at landscape to global scales.

Environmental Management↗

USGS2003

Modeling carbon dynamics in vegetation and soil under the impact of soil erosion and deposition

Soil erosion and deposition may play important roles in balancing the global atmospheric carbon budget through their impacts on the net exchange of carbon between terrestrial ecosystem and the atmosphere. Few models and studies have been designed to assess these impacts. In this study, we developed a general ecosystem model, Erosion-Deposition-Carbon-Model (EDCM), to dynamically simulate the influences of rainfall-induced soil erosion and deposition on soil organic carbon (SOC) dynamics in soil profiles. EDCM was applied to several landscape positions in the Nelson Farm watershed in Mississippi, including ridge top (without erosion or deposition), eroding hillslopes, and depositional sites that had been converted from native forests to croplands in 1870. Erosion reduced the SOC storage at the eroding sites and deposition increased the SOC storage at the depositional areas compared with the site without erosion or deposition. Results indicated that soils were consistently carbon sources to the atmosphere at all landscape positions from 1870 to 1950, with lowest source strength at the eroding sites (13 to 24 gC m-2 yr-1), intermediate at the ridge top (34 gC m-2 yr-1), and highest at the depositional sites (42 to 49 gC m-2 yr-1). During this period, erosion reduced carbon emissions via dynamically replacing surface soil with subsurface soil that had lower SOC contents (quantity change) and higher passive SOC fractions (quality change). Soils at all landscape positions became carbon sinks from 1950 to 1997 due to changes in management practices (e.g., intensification of fertilization and crop genetic improvement). The sink strengths were highest at the eroding sites (42 to 44 gC m-2 yr-1 , intermediate at the ridge top (35 gC m-2 yr-1), and lowest at the depositional sites (26 to 29 gC m-2 yr-1). During this period, erosion enhanced carbon uptake at the eroding sites by continuously taking away a fraction of SOC that can be replenished with enhanced plant residue input. Overall, soil erosion and deposition reduced CO2 emissions from the soil into the atmosphere by exposing low carbon-bearing soil at eroding sites and by burying SOC at depositional sites. The results suggest that failing to account for the impact of soil erosion and deposition may potentially contribute to an overestimation of both the total historical carbon released from soils owing to land use change and the contemporary carbon sequestration rates at the eroding sites.

Global Biogeochemical Cycles↗

USGS2002

Historical and future land use effects on N 2 O and NO emissions using an ensemble modeling approach: Costa Rica's Caribbean lowlands as an example

[1] The humid tropical zone is a major source area for N 2 O and NO emissions to the atmosphere. Local emission rates vary widely with local conditions, particularly land use practices which swiftly change with expanding settlement and changing market conditions. The combination of wide variation in emission rates and rapidly changing land use make regional estimation and future prediction of biogenic trace gas emission particularly difficult. This study estimates contemporary, historical, and future N 2 O and NO emissions from 0.5 million ha of northeastern Costa Rica, a well-documented region in the wet tropics undergoing rapid agricultural development. Estimates were derived by linking spatially distributed environmental data with an ecosystem simulation model in an ensemble estimation approach that incorporates the variance and covariance of spatially distributed driving variables. Results include measures of variance for regional emissions. The formation and aging of pastures from forest provided most of the past temporal change in N 2 O and NO flux in this region; future changes will be controlled by the degree of nitrogen fertilizer application and extent of intensively managed croplands.

Global Biogeochemical Cycles↗

USGS1997

Analysis of environmental data with censored observations

The potential threats to humans and to terrestrial and aquatic ecosystems from environmental contamination could depend on the sum of the concentrations of different chemicals. However, direct summation of environmental data is not generally feasible because it is common for some chemical concentrations to be recorded as being below the analytical reporting limit. This creates special problems in the analysis of the data. A new model selection procedure, named forward censored regression, is introduced for selecting an appropriate model for environmental data with censored observations. The procedure is demonstrated using concentrations of atrazine (2-chloro-4-ethylamino-6-isopropylamino- s -triazine), deethylatrazine (DEA, 2-amino-4-chloro-6-isopropylamino- s -triazine), and deisopropylatrazine (DIA, 2-amino-4-chloro-6-ethylamino- s -triazine) in groundwater in the midwestern United States by using the data derived from a previous study conducted by the U.S. Geological Survey. More than 80% of the observations for each compound for this study were left censored at 0.05 μg/L. The values for censored observations of atrazine, DEA, and DIA are imputed with the selected models. The summation of atrazine residue (atrazine + DEA + DIA) can then be calculated using the combination of observed and imputed values to generate a pseudo-complete data set. The all-subsets regression procedure is applied to the pseudo-complete data to select the final model for atrazine residue. The methodology presented can be used to analyze similar cases of environmental contamination involving censored data.

Environmental Science & Technology↗

USGS1996

Atrazine concentrations in near-surface aquifers: A censored regression approach

In 1991, the U.S. Geological Survey (USGS) conducted a study to investigate the occurrence of atrazine (2-chloro-4-ethylamino-6- isopropylamino-s-triazine) and other agricultural chemicals in near-surface aquifers in the midcontinental USA. Because about 83% of the atrazine concentrations from the USGS study were censored, standard statistical estimation procedures could not be used. To determine factors that affect atrazine concentrations in groundwater while accommodating the high degree of data censoring. Tobit models were used (normal homoscedastic, normal heteroscedastic, lognormal homoscedastic, and lognormal heteroscedastic). Empirical results suggest that the lognormal heteroscedastic Tobit model is the model of choice for this type of study. This model determined the following factors to have the strongest effect on atrazine concentrations in groundwater: percent of pasture within 3.2 km, percent of forest within 3.2 km (2 mi), mean open interval of the well, primary water use of a well, aquifer class (unconsolidated or bedrock), aquifer type (unconfined or confined), existence of a stream within 30 m (100 ft), existence of a stream within 30 m to 0.4 km (0.25 mi), and existence of a stream within 0.4 to 3.2 km. Examining the elasticities of the continuous explanatory factors provides further insight into their effects on atrazine concentrations in groundwater. This study documents a viable statistical method that can be used to accommodate the complicating presence of censured data, a feature that commonly occurs in environmental data.

Journal of Environmental Quality↗