Biomedical subjects

Hongshi He

Publications and source records attributed to Hongshi He.

6 recordsLinked to original sources

PubMed2006

[Long-term effects of different planting proportion on forest landscape in Great Hing' anling Mountains after the catastrophic fire in 1987].

With LANDIS model, this paper simulated the long-term dynamics of 100% larch (P1) 70% larch and 30% Mongolian Scotch pine (P2), 50% larch and 50% Mongolian Scotch pine (P3), 30% larch and 70% Mongolian Scotch pine (P4), and 100% Mongolian Scotch pine (P5) in the Tuqiang Forest Bureau at the northern slope of Great Hing' anling Mountains after the catastrophic fire in 1987, taking the forest under natural regeneration as the reference. The results showed that at the early, medium, and late stages of succession, different planting proportion all had significant effects on the abundance of larch, Mongolian Scotch pine, and white birch. The abundance of larch increased with time,while that of Mongolian Scotch pine was in a converse way. Larch and Mongolian Scotch pine had an increased abundance with their increasing planting proportion, but the abundance of white birch was higher under natural regeneration than under different proportions of planting. The abundance of white birch was positively affected by the planting proportions of larch and Mongolian Scotch pine. As for the total abundance of larch and Mongolian Scotch pine, it had no significant difference under P2, P3 and P4, but was higher than that under P1 and P5, indicating that individual-species planting should not be used in the forest landscape.

Betula↗

PubMed2006

[Effects of different sampling modes on the results of vegetation ordination analysis].

The relationships between plant and environment are an important topic in community ecology. To study these relationships, quadrate is often used to sample vegetation and environmental data, and ordination techniques are used to analyze the data. However, the size and shape of quadrate considerably affect the ordination results. To understand this effect remains a research item for various vegetation and environmental data settings. This paper studied the effects of different sampling quadrate (size and shape) on the results obtained from three common ordination techniques (CA, DCA and CCA). We did this by sampling the same transect in forest form map six times, using six different quadrates (0.5 km x 0.5 km, 0.5 km x 2 km, 2 km x 0.5 km, 1 km x 1 km, 1 km x 4 km, 2 km x 2 km). The results showed that large rectangle quadrate could capture greater percent variance of species data and more information about rare and unique species than small square quadrate. All sizes and shapes of quadrate used in this study had little effect on the dominant species. The captured soil information was sensitive both to the size and to the shape of quadrate, and the information of slope, longitude and latitude was sensitive to the change of quadrate size. Slope position, altitude, temperature and precipitation were sensitive to the change of quadrate shape. Large quadrate reduced the importance of altitude, temperature and precipitation while increased the importance of exposure, but these environmental factors appeared to be important in small quadrate sampling.

Conservation of Natural Resources↗

PubMed2004

[Spatially explicit landscape model-LANDIS I. Mechanism].

Spatially explicit landscape models are the models that spatially explicitly simulate the ecological processes at landscape scale on heterogeneous landscape. LANDIS is a spatially explicit landscape model of forest landscape disturbance, succession and management. By recording the absence/presence of species in terms of 10-yr age cohorts at site level, the semi-quantitative description of fire and windthrow disturbances, and the representation of age-cohorts by bit-wise array, it is possible for LANDIS to simulate the ecological processes at species, site and landscape level. We addressed in detail the approaches used in simulating seed dispersal, disturbances of fire and windthrow, and harvesting. The deficiencies of the model were also discussed to provide feedback for model development.

Biodiversity↗

PubMed2004

[Consistency between neutral landscape models and real landscape].

Neutral landscape models (NLM) can provide standards against real landscapes, and are used to describe landscape pattern and process in the past few decades. In this paper, the neutral landscape models RULE and SimMap were tested against a real landscape, and a set of landscape metrics were used to quantify the spatial characteristics of real and simulated patterns. Measurements of some metrics (total number of patches, total perimeter, average patch area, aggregation index, contagion and lacunarity) suggested that definite level of consistency between NLM-generated maps and real landscape did exist at landscape or class levels. But, there were also some metrics, such as corrected patch perimeter-area ratio, fractal double-logged and edge distribution evenness, which didn't show any agreement between the generated maps and real landscape. In all, each NLM had its own strength in representing real landscape, but none of them was perfect.

Conservation of Natural Resources↗

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↗