Changhui Peng

Increasing net primary production in China from 1982 to 1999

We used a simple process model and satellite data to explore trends in China’s terrestrial net primary production (NPP). We found that the country’s terrestrial NPP increased by 18.7% from 1982 to 1999. Evidence for this major increase also came from crop yields and forest inventory surveys, and much of it appeared to be the result of a lengthening of the growing season. Plant growth also increased during the middle of the growing season, but to a lesser extent. Historical NPP trends indicate a great deal of spatial heterogeneity, increasing significantly over an area covering 30.8% of China during the past 18 years, but decreasing in areas undergoing rapid urbanization.

GROWTH AND YIELD MODELS FOR UNEVEN-AGED STANDS: PAST, PRESENT AND FUTURE

Abstract Growth and yield modeling has a long history in forestry. Methods of measuring the growth of uneven-aged forest stands have evolved from those developed in France and Switzerland during the last century. Furthermore, uneven-aged growth and yield modeling has progressed rapidly since the first models were pioneered by Moser and Hall (1969) (Moser Jr., J.W., Hall, O.F., 1969. For. Sci. 15, 183–188). Over the years, a variety of models have been developed for predicting the growth and yield of uneven-aged stands using both individual and stand-level approaches. Modeling methodology not only has moved from an empirical approach to a more ecological process-based mechanistic approach, but also has incorporated a variety of techniques, such as, (1) systems of equations, (2) nonlinear stand table projections, (3) Markov chains, (4) matrix models, and (5) artificial neural network models. However, modeling the growth and yield of uneven-aged stands has received much less attention than that of even-aged stands. This paper reviews the current literature regarding growth and yield models for uneven-aged stands, discusses basic types of models and their merits, and reports recent progress in modeling the growth and dynamics of uneven-aged stands. Furthermore, future trends involving integration of new computer technologies (object-oriented programming and user-friendly interfaces), tree visualization techniques, and the spatially explicit application of Geographical Information Systems (GIS) into uneven-aged modeling strategies are discussed.

TRIPLEX: a generic hybrid model for predicting forest growth and carbon and nitrogen dynamics

To predict the potential effects of future global environmental changes (e.g. climate, land-use, fire disturbance, and forest harvesting) on the sustainability of forest ecosystems, forest resource managers will need forest simulation models. Basic approaches to modelling forest growth and dynamics include the use of empirical, mechanistic, and hybrid forest simulation models. In this paper, a hybrid, monthly time-step model of forest growth and carbon dynamics (TRIPLEX) is described and tested. The TRIPLEX model integrates the forest production model of 3-PG (For. Ecol. Manage. 95 (1997) 209), the forest growth and yield model of TREENYD3 (Ecol. Model. 90 (1996) 187), and the soil–carbon–nitrogen model of CENTURY4.0 (Global Biogeochem. Cycles 7 (1993) 785). The model is intended to be comprehensive without becoming complex, and minimizes the number of input parameters required, while capturing key processes and important interactions between the carbon and nitrogen cycles of forest ecosystems. It is designed as a hybrid of both empirical and mechanistic components that can be used for (1) making forest management decisions (e.g. growth and yield prediction), (2) quantifying forest carbon budgets, and (3) assessing the effects of climate change in both the short and long term. We tested TRIPLEX against age-dependent growth measurements from 12 permanent sample plots (PSP) in jack pine (Pinus banskiana Lamb.) stands in northern Ontario (Canada). Comparisons of simulated stand growth variables (e.g. tree diameter, height, and stem density) with those observed in PSPs indicated a good agreement over 30 years. Predictions of tree total volume and aboveground biomass were within the expected range for these plots. While the model is promising, future modifications are discussed.

Regional drought-induced reduction in the biomass carbon sink of Canada's boreal forests

The boreal forests, identified as a critical “tipping element” of the Earths climate system, play a critical role in the global carbon budget. Recent findings have suggested that terrestrial carbon sinks in northern high-latitude regions are weakening, but there has been little observational evidence to support the idea of a reduction of carbon sinks in northern terrestrial ecosystems. Here, we estimated changes in the biomass carbon sink of natural stands throughout Canadas boreal forests using data from long-term forest permanent sampling plots. We found that in recent decades, the rate of biomass change decreased significantly in western Canada (Alberta, Saskatchewan, and Manitoba), but there was no significant trend for eastern Canada (Ontario and Quebec). Our results revealed that recent climate change, and especially drought-induced water stress, is the dominant cause of the observed reduction in the biomass carbon sink, suggesting that western Canadas boreal forests may become net carbon sources if the climate change–induced droughts continue to intensify.

Distribution and storage of soil organic carbon in China

organic carbon density in soils varies from 0.73 to 70.79 kg C/m 2 with the majority ranging between 4.00 and 11.00 kg C/m 2 . Carbon density decreases from east to west. A general southward increase is obvious for western China, while carbon density decreases from north to south in eastern China. Highest values are observed in forest soils in northeast China and in subalpine soils in the southeastern part of the Tibetan Plateau. The average density of � 8.01 kg C/m 2 in China is lower than the world’s mean organic carbon density in soil (� 10.60 kg C/m 2 ), mainly due to the extended arid and semi-arid regions. Total organic carbon storage in soils in China is estimated to be � 70.31 Pg C, representing � 4.7% of the world storage. Carbon storage in the surface organic horizons which is most sensitive to interactions with the atmosphere and environmental change is � 32.54 Pg C. INDEX TERMS: 0330 Atmospheric Composition and Structure: Geochemical cycles; 1615 Global Change: Biogeochemical processes (4805); 1815 Hydrology: Erosion and sedimentation; 1625 Global Change: Geomorphology and weathering (1824, 1886);

High carbon dioxide uptake by subtropical forest ecosystems in the East Asian monsoon region

Significance Understanding the location of carbon sources and sinks is essential for accurately predicting future changes in atmospheric carbon dioxide and climate. Mid- to high-latitude terrestrial ecosystems are well known to be the principal carbon sink regions, yet less attention has been paid to the mid- to low-latitude ecosystems. In this study, long-term eddy covariance observations demonstrate that there is a high carbon dioxide uptake (net ecosystem productivity) by the mid- to low-latitude East Asian monsoon subtropical forests that were shaped by the uplift of the Tibetan Plateau. Increasing nitrogen deposition, a young forest age structure, and sufficient water and heat availability combined to contribute to this large carbon dioxide uptake. Temperate- and high-latitude forests have been shown to contribute a carbon sink in the Northern Hemisphere, but fewer studies have addressed the carbon balance of the subtropical forests. In the present study, we integrated eddy covariance observations established in the 1990s and 2000s to show that East Asian monsoon subtropical forests between 20°N and 40°N represent an average net ecosystem productivity (NEP) of 362 ± 39 g C m−2 yr−1 (mean ± 1 SE). This average forest NEP value is higher than that of Asian tropical and temperate forests and is also higher than that of forests at the same latitudes in Europe–Africa and North America. East Asian monsoon subtropical forests have comparable NEP to that of subtropical forests of the southeastern United States and intensively managed Western European forests. The total NEP of East Asian monsoon subtropical forests was estimated to be 0.72 ± 0.08 Pg C yr−1, which accounts for 8% of the global forest NEP. This result indicates that the role of subtropical forests in the current global carbon cycle cannot be ignored and that the regional distributions of the Northern Hemispheres terrestrial carbon sinks are needed to be reevaluated. The young stand ages and high nitrogen deposition, coupled with sufficient and synchronous water and heat availability, may be the primary reasons for the high NEP of this region, and further studies are needed to quantify the contribution of each underlying factor.

Toward more realistic projections of soil carbon dynamics by Earth system models

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.

From Static Biogeographical Model to Dynamic Global Vegetation Model: A Global Perspective on Modelling Vegetation Dynamics*

Abstract Predicting the potential effects of future climatic change and human disturbances on natural vegetation distribution requires large-scale biogeographical models. There have been two basic approaches to modelling vegetation response to changing climates: static (time-independent) or dynamic (time-dependent) biogeographical models. This paper reviews and compares two major types of static biogeographical models, climate–vegetation classification and plant functional type models, and the first generation of Dynamic Global Vegetation Models (DGVMs). These models have been widely used to simulate the potential response of vegetation to past and future climate change. Advantage and disadvantage of each type of model are discussed. Global vegetation modelling for investigations of climate change effects has progressed from empirical modelling to process-based equilibrium modelling to the first generation of DGVMs. Some DGVMs are able to capture the responses of potential natural vegetation to climate change with a strong orientation towards population processes. Nevertheless, the uncertainty around the quantitative simulated results indicates that DGVMs are still in the early stages of development. Validating and capturing disturbance-related effects are major challenges facing the developers of the next generation of DGVMs. In future, DGVMs will become an important tool for assessing the effects of climate change on potential vegetation dynamics and terrestrial carbon storage and for managing terrestrial ecosystem sustainability.

Biomass offsets little or none of permafrost carbon release from soils, streams, and wildfire: an expert assessment

As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export. Models predict that some portion of this release w ...

Global satellite monitoring of climate-induced vegetation disturbances

Terrestrial disturbances are accelerating globally, but their full impact is not quantified because we lack an adequate monitoring system. Remote sensing offers a means to quantify the frequency and extent of disturbances globally. Here, we review the current application of remote sensing to this problem and offer a framework for more systematic analysis in the future. We recommend that any proposed monitoring system should not only detect disturbances, but also be able to: identify the proximate cause(s); integrate a range of spatial scales; and, ideally, incorporate process models to explain the observed patterns and predicted trends in the future. Significant remaining challenges are tied to the ecology of disturbances. To meet these challenges, more effort is required to incorporate ecological principles and understanding into the assessments of disturbance worldwide.