Biomedical subjects

Chonggang Xu

Publications and source records attributed to Chonggang Xu.

4 recordsLinked to original sources

PubMed2004

[Dynamics of forest landscape boundary at Changbai Mountain].

By using Geographic Information System (GIS) and Remote Sensing (RS) technology combined with field investigation and correlation analysis, this study was aimed to explore the dynamics of forest landscape boundary at Changbai Mountain, and to reveal the relationships among landscape fragmentation and changes of landscape boundary indices. The results showed that in the last 20 years or so, tundra decreased by 3694.8 hm2, spruce and fir forest reduced by 130482.03 hm2, and Korean pine-hardwood and mountain birch forest increased by 41610.4 hm2 and 669.78 hm2, respectively. The forest landscapes at Changbai Mountain tended to be more fragmented, and the shape of the landscape boundary became more complicated due to timber harvesting, forest cutting for cropping, and other human activities such as tourism. The changes of landscape shape index (LSI), contrast weighted edge density (CWED), total weighted edge length (TE-WGT) and weighted landscape shape index (LSI-WGT) could be used as good indicators for the degrees of forest landscape fragmentations, which was approved by correlation analysis among landscape fragmentation and changes of landscape boundary indices. The degree of human activities on landscape could be reflected by landscape shape index.

China↗

PubMed2004

[Sensitivity analysis in ecological modeling].

Sensitivity analysis is used to qualitatively or quantitatively apportion the variation of model output to different source of variation. It is a very useful tool in model parameterization and calibration, and has important ecological significance by identifying the governing factors for a certain ecological process simulated. There are two schools of sensitivity analysis, local sensitivity analysis and global sensitivity analysis. The former examines the local response of the output(s) by varying input parameters one at a time, holding other parameters to a central value; and the latter examines the global response (averaged over the variation of all the parameters) of model output(s) by exploring a finite (or even an infinite) region. Since it is very easy to conduct local sensitivity analysis, it is very popular in ecological models. However, local sensitivity analysis is not computationally effective, because it can only get the sensitivity of a single parameter at a time. It can not take into consideration the effect of interaction of different parameters. Additionally, the value of other parameters will affect the sensitivity of the parameter specified. In view of this, global sensitivity analysis is increasingly preferred to local sensitivity in recent years. However, for most of the ecological modeling study published in Chinese, only local sensitivity analysis is conducted. To provide a toolbox of alternative sensitivity analysis algorithms for ecological model development in future study, we reviewed the main methods of both local sensitivity analysis and global sensitivity analysis, including one at a time method, multivariate regression, Morris' method, Sobol's method, Fourier Amplitude Sensitivity Analysis, and Extended Fourier Amplitude Sensitivity Analysis. Based on the state-of-the-art research on sensitivity analysis, the sensitivity of the interaction between two or more than two model parameters, the sensitivity of common model parameters in a set of models, and the sensitivity analysis in spatially explicit landscape model simulation were identified as the key areas and difficulties of future study on sensitivity analysis in ecological modeling.

Ecology↗

PubMed2004

[Application of spatially explicit landscape model in soil loss study in Huzhong area].

Universal Soil Loss Equation (USLE) has been widely used to estimate the average annual soil loss. In most of the previous work on soil loss evaluation on forestland, cover management factor was calculated from the static forest landscape. The advent of spatially explicit forest landscape model in the last decade, which explicitly simulates the forest succession dynamics under natural and anthropogenic disturbances (fire, wind, harvest and so on) on heterogeneous landscape, makes it possible to take into consideration the change of forest cover, and to dynamically simulate the soil loss in different year (e.g. 10 years and 20 years after current year). In this study, we linked a spatially explicit landscape model (LANDIS) with USLE to simulate the soil loss dynamics under two scenarios: fire and no harvest, fire and harvest. We also simulated the soil loss with no fire and no harvest as a control. The results showed that soil loss varied periodically with simulation year, and the amplitude of change was the lowest under the control scenario and the highest under the fire and no harvest scenario. The effect of harvest on soil loss could not be easily identified on the map; however, the cumulative effect of harvest on soil loss was larger than that of fire. Decreasing the harvest area and the percent of bare soil increased by harvest could significantly reduce soil loss, but had no significant effects on the dynamic of soil loss. Although harvest increased the annual soil loss, it tended to decrease the variability of soil loss between different simulation years.

China↗

PubMed2003

[GIS and RS determination of abiotic range of forest landscape distribution in Changbai Mountain Natural Reserve].

Based on landscape classification of remote sensing data and spatial expression of environmental factors, the abiotic ranges of forest landscape distribution in Changbai Mountain Natural Reserve were determined by using GIS. The results showed that the optimum elevation range of tundra, mountain birch forest, evergreen coniferous forest, and broad-leaved Korean pine forest were 1780-2212 m, 1705-1956 m, 1042-1625 m, and 823-1184 m, respectively. The corresponding optimum annual average temperature ranges were -4.75(-)-2.40 degrees C, -3.42(-)-2.07 degrees C, -1.49-1.39 degrees C, and 0.71-2.37 degrees C, and the optimum ranges of annual precipitation were 1034-1110 mm, 1014-1060 mm, 883-1017 mm, and 824-925 mm, respectively. The forest landscapes in Changbai Mountain Natural Reserve were mainly distributed in flat and gentle areas. This distribution pattern was closely related to aspect. Tundra was almost evenly present in various aspects. In northern and northwestern direction, most forest landscapes were distributed, including mountain birch forest, evergreen coniferous forest, broad-leaved Korean pine forest, aspen and Betula forest. Most larch forest was in favor of northeastern direction with small amount facing eastern and northern way. Sparse forest briefly occupied west aspect with some orienting in southwest, northwest and south, while all wind-thrown areas were facing west, southwest and northwest aspects.

Conservation of Natural Resources↗