Biomedical subjects

Yuanman Hu

Publications and source records attributed to Yuanman Hu.

13 recordsLinked to original sources

PubMed2006

[Land use and land cover changes and driving forces in the upper reach of Minjiang River].

The upper reach of Minjiang River is the representative of mountainous area in Southwest China in the aspects of natural environment, ecosystem structure, economic development, and social culture. The characteristics of the dynamic changes of its land use and land cover stood for the common questions occurred in the land resources and usage of this area. Woodland and grassland are the main types of land use and land cover, and many changes in land use/cover types happened from 1974 to 2000. Among forestland, shrub land, economic forestland, grassland, cropland and resident land,changes mainly happened between woodland and grassland, and all occurred bilaterally. The area of forestland changed mostly and kept decreasing from 1974 to 2000, while that of other land types increased. The changes of land use and land cover happened between 1974 and 1986 were larger than those happened between 1986 and 2000. Population and economy were the main driving factors for the changes of land use and land cover in the upper reach of Minjiang River. Since the programs of Natural Forest Protection and Withdrawing Cropland to Woodland and Grassland carried into execution, the land use and land cover have changed rationally.

China↗

PubMed2005

[Landscape change in Kangbao County of Hebei {rovince].

Based on RS image TM5 of 1999 and SPOT5 of 2003, this paper studied the landscape change from 1999 to 2003 of Kangbao County, Hebei Province. Logistic regression was adopted to analyze the driving factors, and Kappa index was used to evaluate the accuracy of the landscape classification result, which was 86.72% for 1999, and 89.76% for 2003. The area of cropland in Kangbao County reduced largely, while that of vegetable field, forestland and artificial grassland increased sharply, among which, vegetable field and artificial grassland had the greatest increasing rate. The landscape fragmentation aggravated in the region. The landscape change was mainly caused by the policy of reducing cultivated land, with the main driving factor slope, and the direct driving factor water-heat condition and soil fertility determined by slope aspect.

China↗

PubMed2005

[Dynamics of soil erosion at upper reaches of Minjiang River based on GIS].

Based on TM and ETM imagines, and employing GIS technique and empirical Revised Universal Soil Loss Equation (RUSLE) model, this paper studied the dynamics of soil erosion at the upper reaches of Minjiang River during three typical periods, with the main affecting factors analyzed. The results showed that the soil erosion area was increased by 1.28%, 1.84 % and 1.70% in 1986, 1995 and 2000, respectively. The average erosion modulus was increased from 832.64 t x km(-2) x yr(-1) in 1986 to 1048.74 t x km(-2) yr(-2) in 1995 and reached 1362.11 t x km(-2) yr(-1) in 2000, and soil loss was mainly of slight and light erosion, companying with a small quantity of middling erosion. The area of soil erosion was small, and the degree was light. There was a significant correlation between slope and soil loss, which mainly happened in the regions with a slope larger than 25 degrees, and accounted for 93.65%, 93.81% and 92.71% of the total erosion in 1986, 1995 and 2000, respectively. As for the altitude, middling, semi-high and high mountains and dry valley were liable to soil erosion, which accounted for 98.21%, 97.63% and 99.27% of the total erosion in 1986, 1995 and 2000, respectively. Different vegetation had a significant effect on soil erosion, and shrub and newly restored forest were the main erosion area. Excessive depasture not only resulted in the degradation of pasture, but also led to slight soil erosion. Land use type and soil type also contributed to soil loss, among which, dry-cinnamon soil and calcic gray-cinnamon soil were the most dangerous ones needing more protection. Soil loss was also linearly increased with increasing population and households, which suggested that the increase of population and households was the driving factor for soil loss increase in this area.

China↗

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

[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

[Landscape pattern change at the upper reaches of Minjiang River and its driving force].

The upper reaches of Minjiang River is an ecological sensitive and vulnerable area in southwest of China. It is of great significance to the ecological pattern safety in China. In this study, we analyzed the landscape pattern change through the interpretation of TM imageries in 1986, 1995 and 2000. The results showed that the matrix landscape in this area was grass landscape. Forest landscape patches were embedded in the grass landscape. The forest landscape area increased from 1986 to 1995 and decreased from 1995 to 2000. However, the number of patches of forest landscape was increasing during all the time. This suggested that the intensity of anthropogenic disturbances including harvesting, forest landscape reclaiming and excessive grazing were persistently increasing from 1986 to 2000. The ecological driving forces of the landscape change in this area were the intensified anthropogenic disturbances as a result of the population boom including the predacious harvesting of forest and excessive grazing. The natural disturbances such as the global climatic change also partly influenced the landscape change in this area.

China↗

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

[A review on road ecology].

Roads are a widespread and increasing feature of most landscapes, and have great ecological effects, e.g., increased mortality of animals and plants and habitat loss from road construction, alteration of the physical and chemical environment, and changes in roadsides vegetation. The great impact on animal population includes road-kills, limiting population, road avoidance causing home arrange shift, modification of movement pattern and barrier effect subdividing habitat and populations. Roads alter landscape spatial pattern and interrupt horizontal ecological flows strongly. These impacts can be assayed by indices of road density, road-effect zone and road location. Furthermore, important applications of road ecology to planning, conservation and management are essential and potential. Road ecology presents us a surprising frontier of ecology.

Animals↗

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↗

PubMed2003

[Spatial diversity index analysis on wildlife habitat pattern change in the Liaohe Delta].

Based on the study of land cover change in the Liaohe Delta with GIS and RS, the wildlife habitat pattern was described quantitatively, and the pattern change between 1988 and 1998 was analyzed with spatial diversity index. The results showed that the wildlife habitat pattern had an obvious change during the ten years caused by natural and human disturbance. The area of suitable habitat(Sd > or = 0.35) was becoming smaller and more fragmented, with a deteriorated quality. It was proved that spatial diversity index could reflect the habitat suitability of wildlife, and describe the habitat spatial pattern explicitly. This study would provide a scientific basis for protecting wild animals and their habitats.

Animals↗

PubMed2003

[Scaling effects on landscape pattern indices].

The methods of spatial data aggregation based on majority and random rules were used in this study to reveal the scaling effects on landscape pattern in a classified TM imagery with 8 land cover types. For the majority rule-based aggregations, the proportion of most common cover types increased slowly, while that of less common cover types decreased rapidly with increasing grain. For random rule-based aggregation, each cover remained its original area on the aggregated maps. The largest patch sizes of shrub decreased, and those of the others increased in the majority rule-based aggregations with increasing scales. For random rule, the largest patch size of water (smallest cover type) decreased, but that of the others increased. The smallest patch size of each cover type was equal to the square of grain sizes. The average patch size of each cover type increased with increasing scales. However, the average patch size of dominant cover types increased rapidly in majority rule-based aggregations, while that of less common cover types increased rapidly in random rule-based aggregation. The patch count of each cover types decreased substantially with increasing grain. Random rule-based aggregation made landscape more fragmented and remained more patches. The diversity decreased in majority rule-based aggregation, and maintained its original value in random rule-based aggregation with increasing scales. Aggregation indices decreased with increasing map and measurement resolution, and the landscape became more aggregated in majority rule-based aggregation. However, under fixed measurement resolution (e.g., 30 m), aggregation indices increased and cover types were more clustered with increasing resolution. Moran's I decreased rapidly with increasing measurement and map resolution, and each cover type tended to be arranged randomly and independently in space. However, under fixed measurement resolution (e.g., 30 m), Moran's I increased and cover types were more clustered on aggregated maps than on original map with increasing map resolution.

Ecosystem↗