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G. Zhou

Publications and source records attributed to G. Zhou.

13 recordsLinked to original sources

Quantifying the hydrological responses to climate change in an intact forested small watershed in southern China

Responses of hydrological processes to climate change are key components in the Intergovernmental Panel for Climate Change (IPCC) assessment. Understanding these responses is critical for developing appropriate mitigation and adaptation strategies for sustainable water resources management and protection of public safety. However, these responses are not well understood and little long-term evidence exists. Herein, we show how climate change, specifically increased air temperature and storm intensity, can affect soil moisture dynamics and hydrological variables based on both long-term observation and model simulations using the Soil and Water Assessment Tool (SWAT) in an intact forested watershed (the Dinghushan Biosphere Reserve) in Southern China. Our results show that, although total annual precipitation changed little from 1950 to 2009, soil moisture decreased significantly. A significant decline was also found in the monthly 7-day low flow from 2000 to 2009. However, the maximum daily streamflow in the wet season and unconfined groundwater tables have significantly increased during the same 10-year period. The significant decreasing trends on soil moisture and low flow variables suggest that the study watershed is moving towards drought-like condition. Our analysis indicates that the intensification of rainfall storms and the increasing number of annual no-rain days were responsible for the increasing chance of both droughts and floods. We conclude that climate change has indeed induced more extreme hydrological events (e.g. droughts and floods) in this watershed and perhaps other areas of Southern China. This study also demonstrated usefulness of our research methodology and its possible applications on quantifying the impacts of climate change on hydrology in any other watersheds where long-term data are available and human disturbance is negligible.

Guangdong Province

Evaluating the effects of future climate change and elevated CO 2 on the water use efficiency in terrestrial ecosystems of China

Water use efficiency (WUE) is an important variable used in climate change and hydrological studies in relation to how it links ecosystem carbon cycles and hydrological cycles together. However, obtaining reliable WUE results based on site-level flux data remains a great challenge when scaling up to larger regional zones. Biophysical, process-based ecosystem models are powerful tools to study WUE at large spatial and temporal scales. The Integrated BIosphere Simulator (IBIS) was used to evaluate the effects of climate change and elevated CO 2 concentrations on ecosystem-level WUE (defined as the ratio of gross primary production (GPP) to evapotranspiration (ET)) in relation to terrestrial ecosystems in China for 2009–2099. Climate scenario data (IPCC SRES A2 and SRES B1) generated from the Third Generation Coupled Global Climate Model (CGCM3) was used in the simulations. Seven simulations were implemented according to the assemblage of different elevated CO 2 concentrations scenarios and different climate change scenarios. Analysis suggests that (1) further elevated CO 2 concentrations will significantly enhance the WUE over China by the end of the twenty-first century, especially in forest areas; (2) effects of climate change on WUE will vary for different geographical regions in China with negative effects occurring primarily in southern regions and positive effects occurring primarily in high latitude and altitude regions (Tibetan Plateau); (3) WUE will maintain the current levels for 2009–2099 under the constant climate scenario (i.e. using mean climate condition of 1951–2006 and CO 2 concentrations of the 2008 level); and (4) WUE will decrease with the increase of water resource restriction (expressed as evaporation ratio) among different ecosystems.

Ecological Modelling

Modeling the spatial-temporal dynamics of net primary production in Yangtze River Basin using IBIS model

The climate change has significantly affected the carbon cycling in Yangtze River Basin. To better understand the alternation pattern for the relationship between carbon cycling and climate change, the net primary production (NPP) were simulated in the study area from 1956 to 2006 by using the Integrated Biosphere Simulator (IBIS). The results showed that the average annual NPP per square meter was about 0.518 kg C in Yangtze River Basin. The high NPP levels were mainly distributed in the southeast area of Sichuan, and the highest value reached 1.05 kg C/m 2 . The NPP increased based on the simulated temporal trends. The spatiotemporal variability of the NPP in the vegetation types was obvious, and it was depended on the climate and soil condition. We found the drought climate was one of critical factor that impacts the alterations of the NPP in the area by the simulation.

Yangtze River

Forecasting carbon budget under climate change and CO 2 fertilization for subtropical region in China using integrated biosphere simulator (IBIS) model

The regional carbon budget of the climatic transition zone may be very sensitive to climate change and increasing atmospheric CO 2 concentrations. This study simulated the carbon cycles under these changes using process-based ecosystem models. The Integrated Biosphere Simulator (IBIS), a Dynamic Global Vegetation Model (DGVM), was used to evaluate the impacts of climate change and CO 2 fertilization on net primary production (NPP), net ecosystem production (NEP), and the vegetation structure of terrestrial ecosystems in Zhejiang province (area 101,800 km 2, mainly covered by subtropical evergreen forest and warm-temperate evergreen broadleaf forest) which is located in the subtropical climate area of China. Two general circulation models (HADCM3 and CGCM3) representing four IPCC climate change scenarios (HC3AA, HC3GG, CGCM-sresa2, and CGCM-sresb1) were used as climate inputs for IBIS. Results show that simulated historical biomass and NPP are consistent with field and other modelled data, which makes the analysis of future carbon budget reliable. The results indicate that NPP over the entire Zhejiang province was about 55 Mt C yr -1 during the last half of the 21 st century. An NPP increase of about 24 Mt C by the end of the 21 st century was estimated with the combined effects of increasing CO 2 and climate change. A slight NPP increase of about 5 Mt C was estimated under the climate change alone scenario. Forests in Zhejiang are currently acting as a carbon sink with an average NEP of about 2.5 Mt C yr -1. NEP will increase to about 5 Mt C yr -1 by the end of the 21 st century with the increasing atmospheric CO 2 concentration and climate change. However, climate change alone will reduce the forest carbon sequestration of Zhejiang's forests. Future climate warming will substantially change the vegetation cover types; warm-temperate evergreen broadleaf forest will be gradually substituted by subtropical evergreen forest. An increasing CO 2 concentration will have little contribution to vegetation changes. Simulated NPP shows geographic patterns consistent with temperature to a certain extent, and precipitation is not the limiting factor for forest NPP in the subtropical climate conditions. There is no close relationship between the spatial pattern of NEP and climate condition.

Polish Journal of Ecology

Forecasting carbon budget under climate change and CO2 fertilization for subtropical region in China using integrated biosphere simulator (IBIS) model

The regional carbon budget of the climatic transition zone may be very sensitive to climate change and increasing atmospheric CO2 concentrations. This study simulated the carbon cycles under these changes using process-based ecosystem models. The Integrated Biosphere Simulator (IBIS), a Dynamic Global Vegetation Model (DGVM), was used to evaluate the impacts of climate change and CO2 fertilization on net primary production (NPP), net ecosystem production (NEP), and the vegetation structure of terrestrial ecosystems in Zhejiang province (area 101,800 km2, mainly covered by subtropical evergreen forest and warm-temperate evergreen broadleaf forest) which is located in the subtropical climate area of China. Two general circulation models (HADCM3 and CGCM3) representing four IPCC climate change scenarios (HC3AA, HC3GG, CGCM-sresa2, and CGCM-sresb1) were used as climate inputs for IBIS. Results show that simulated historical biomass and NPP are consistent with field and other modelled data, which makes the analysis of future carbon budget reliable. The results indicate that NPP over the entire Zhejiang province was about 55 Mt C yr-1 during the last half of the 21st century. An NPP increase of about 24 Mt C by the end of the 21st century was estimated with the combined effects of increasing CO2 and climate change. A slight NPP increase of about 5 Mt C was estimated under the climate change alone scenario. Forests in Zhejiang are currently acting as a carbon sink with an average NEP of about 2.5 Mt C yr-1. NEP will increase to about 5 Mt C yr-1 by the end of the 21st century with the increasing atmospheric CO2 concentration and climate change. However, climate change alone will reduce the forest carbon sequestration of Zhejiang's forests. Future climate warming will substantially change the vegetation cover types; warm-temperate evergreen broadleaf forest will be gradually substituted by subtropical evergreen forest. An increasing CO2 concentration will have little contribution to vegetation changes. Simulated NPP shows geographic patterns consistent with temperature to a certain extent, and precipitation is not the limiting factor for forest NPP in the subtropical climate conditions. There is no close relationship between the spatial pattern of NEP and climate condition.

Polish Journal of Ecology

Erosion and vegetation restoration impacts on ecosystem carbon dynamics in South China

To quantify the consequences of erosion and vegetation restoration on ecosystem C dynamics (a key element in understanding the terrestrial C cycle), field measurements were collected since 1959 at two experimental sites set up on highly disturbed barren land in South China. One site had received vegetation restoration (the restored site) while the other received no planting and remained barren (the barren site). The Erosion-Deposition Carbon Model (EDCM) was used to simulate the ecosystem C dynamics at both sites. The on-site observations in 2007 showed that soil organic C (SOC) storage in the top 80-cm soil layer at the barren site was 50.3 ± 3.5 Mg C ha −1 , half that of the restored site. The SOC and surface soil loss by erosion at the restored site from 1959 to 2007 was 3.7 Mg C ha −1 and 2.2 cm, respectively—one-third and one-eighth that of the barren site. The on-site C sequestration in SOC and vegetation at the restored site was 0.67 and 2.5 Mg C ha −1 yr −1 , respectively, from 1959 to 2007, driven largely by tree growth and high atmospheric N deposition in the study area. Simulated findings suggested that higher N deposition resulted in higher on-site SOC storage in the soil profile (with SOC in the top 20-cm layer increasing more significantly), and higher on-site ecosystem C sequestration as long as N saturation was not reached. Lacking human-induced vegetation recovery, the barren site remained as barren land from 1959 to 2007 and the on-site C decrease was 0.28 Mg C ha −1 yr −1 Our study clearly indicated that vegetation restoration and burial by soil erosion provide a large potential C sink in terrestrial ecosystems.

Soil Science Society of America Journal

Factors influencing leaf litter decomposition: An intersite decomposition experiment across China

The Long-Term Intersite Decomposition Experiment in China (hereafter referred to as LTIDE-China) was established in 2002 to study how substrate quality and macroclimate factors affect leaf litter decomposition. The LTIDE-China includes a wide variety of natural and managed ecosystems, consisting of 12 forest types (eight regional broadleaf forests, three needle-leaf plantations and one broadleaf plantation) at eight locations across China. Samples of mixed leaf litter from the south subtropical evergreen broadleaf forest in Dinghushan (referred to as the DHS sample) were translocated to all 12 forest types. The leaf litter from each of other 11 forest types was placed in its original forest to enable comparison of decomposition rates of DHS and local litters. The experiment lasted for 30 months, involving collection of litterbags from each site every 3 months. Our results show that annual decomposition rate-constants, as represented by regression fitted k-values, ranged from 0.169 to 1.454/year. Climatic factors control the decomposition rate, in which mean annual temperature and annual actual evapotranspiration are dominant and mean annual precipitation is subordinate. Initial C/N and N/P ratios were demonstrated to be important factors of regulating litter decomposition rate. Decomposition process may apparently be divided into two phases controlled by different factors. In our study, 0.75 years is believed to be the dividing line of the two phases. The fact that decomposition rates of DHS litters were slower than those of local litters may have been resulted from the acclimation of local decomposer communities to extraneous substrate. ?? 2008 Springer Science+Business Media B.V.

Plant and Soil

Resolving model parameter values from carbon and nitrogen stock measurements in a wide range of tropical mature forests using nonlinear inversion and regression trees

Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in seven life zones in Costa Rica. Net primary productivity from the Moderate-Resolution Imaging Spectroradiometer (MODIS), C and N stocks in aboveground live biomass, litter, coarse woody debris (CWD), and in soils were used to calibrate the model. To investigate the resolution of available observations on the number of adjustable parameters, inversion was performed using nine setups of adjustable parameters. Statistics including observation sensitivity, parameter correlation coefficient, parameter sensitivity, and parameter confidence limits were used to evaluate the information content of observations, resolution of model parameters, and overall model performance. Results indicated that soil organic carbon content, soil nitrogen content, and total aboveground biomass carbon had the highest information contents, while measurements of carbon in litter and nitrogen in CWD contributed little to the parameter estimation processes. The available information could resolve the values of 2-4 parameters. Adjusting just one parameter resulted in under-fitting and unacceptable model performance, while adjusting five parameters simultaneously led to over-fitting. Results further indicated that the MODIS NPP values were compressed as compared with the spatial variability of net primary production (NPP) values inferred from inverse modeling. Using inverse modeling to infer NPP and other sensitive model parameters from C and N stock observations provides an opportunity to utilize data collected by national to regional forest inventory systems to reduce the uncertainties in the carbon cycle and generate valuable databases to validate and improve MODIS NPP algorithms.

Ecological Modelling

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

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

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

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