[Vegetation damage, post-disaster change degree and driving factors in the cold temperate wind disaster area of Changbai Mountain, China.] / é•¿ç™½å±±å¯’æ¸©å¸¦é£Žç¾åŒºæ¤è¢«å—æŸä¸Žç¾åŽå˜åŒ–ç¨‹åº¦åŠå ¶å½±å“å› ç´ .

The typhoon outbreaks of 1986 caused many gaps in the cold temperate coniferous forest and Betula errmanii forest on the western and southern slopes in the Changbai Mountain. In 2017, a research area at the 1600-1800 m altitude in Changbai Mountain was established to explore the damage and changes of forest vegetation disturbed by the typhoon in cold temperate zone and to reveal the regulation of damage on vegetation and post-disaster change as well as the driving factors. The remote sensing data were used to classify research area based on the degree of vegetation damage and post-disaster change. A total of 40 plots were set up for vegetation survey. According to the damage degree of forest structure, three levels of severity of damage to vegetation in the cold temperate zone of Changbai Mountain were classified including gently, moderately, and severely damaged, in which moderately damaged area was largest, followed by gently damaged area and severely damaged area. Tree damage significantly differed among three level areas, with 20%, 50% and 85% reduction of the abundance of dominant trees in gently, moderately and severely damaged areas, respectively. The wind resistance ability of B. errmanii was higher than that of Picea jezoensis. The wind resistance ability of B. errmanii with larger diameter grade was higher than that of those with smaller diameter grade. The severity of damage to vegetation was strongly correlated with slope, with lower severity on the steeper slop area. From 1987 to 2017, the vegetation of wind disaster area significantly changed. The study area could be classified into three levels based on the degree of changing: fast, medium, and slow, with largest area in medium changed, followed by slowly and fast changed. The degree of vegetation changes was strongly correlated with altitude, with slower change at higher altitude area. The recovery rate of trees was slow, with P. jezoensis recovering slightly quicker than B. errmanii. The vegetation change mainly occurred in shrub and herb layers. Shrub layer recovered better than the herb layer in the fast changed area, while herb layer recovered better than the shrub layer in the medium changed area. In the slowly changed area, herb layer was generally low and dense with varying shrub layer.

[Effects of climate change, fire and silvicultural management on ecological resilience of typical cold-temperate forests in China.] / æ°”å€™å˜åŒ–ã€æž—ç«å’Œè¥æž—æŽªæ–½å¯¹å¯’æ¸©å¸¦å ¸åž‹æ£®æž—ç”Ÿæ€å¼¹æ€§çš„å½±å“.

Ecological resilience is characterized by the recovery capacity of forest ecosystem from a status affected by external disturbance to a stable status, which is one of the important targets for sustainable development of forests. Ecological resilience is sensitive to external factors, such as climate change, forest fire, and silvicutural management at large scales. Understanding the effects of those factors on ecological resilience is important for forest ecosystem management. In this study, we calculated ecological resilience with indicators including forest structure, composition and function. We used a landscape model LANDIS PRO to evaluate the effects of climate change, climate-induced fire, and silvicultural management on ecological resilience in boreal forests. We also evaluated whether the current thinning treatment could be implemented under the scenarios of climate change. The results showed that the initialized stand density and basal area from the year 2000 could represent the real forest landscape in year 2000, with no significant difference between the simulated landscape and the forest inventory data in the year 2010 at landscape scale. The results of simulated fire disturbance were consistent with the results from the field inventories in burned areas. The fire module parameters set adequately represented the current fire regimes in model simulation. The ecological resilience could increase by 15.7%-40.8% at landscape scale when fire intensity increased by 30%, whereas the ecological resilience decreased by 4.4%-24.6% when fire intensity increased by 200%. At the short and medium term, the effects of increased fire on forest ecological resilience were greater than that of climate change. Compared to the current base scenario, forest ecological resilience under B1 climate with fire intensity increased by 30% scenario and A2 climate with fire intensity increased by 200% scenario fluctuated in the ranges of -15.9%-38.9% and -60.4%-34.8% in the whole simulation period at landscape scale. Compared to no harvesting scenario, the current thinning strategy would decrease the ecological resilience at landscape scale under both B1 and A2 scenarios in all simulated periods. Under the scenario of B1 climate with 30% increases of fire intensity, no silvicultural management would be needed in the whole simulation period at landscape scale, whereas medium and high intensity of silvicultural management were suggested under the scenario of A2 climate with 200% increase of fire intensity.

[Effects of climate change, fire and harvest on carbon storage of boreal forests in the Great Xing'an Mountains, China.] / æ°”å€™å˜åŒ–ã€æž—ç«å’Œé‡‡ä¼å¯¹å¤§å ´å®‰å²­æ£®æž—ç¢³å‚¨é‡çš„å½±å“.

Climate change will increase the frequency of fire disturbances, which may further exa-cerbate carbon loss from boreal forests in the Great Xing'an Mountains, China. In this study, we coupled forest ecosystem and forest landscape models to simulate the dynamics of boreal forest carbon storage in the next 100 years. We quantified the effects of climate change, fire and harvest on carbon storage of boreal forests. The results showed that climate change would increase carbon storage of boreal forests in the Great Xing'an Mountains, even if fire and harvest could partially offset such changes. Aboveground and soil organic carbon storage would increase by 9%-22% and 6%-9% in the next 100 years. In the short-term (0-20 years), the effects of climate change on carbon storage was stronger than fire. The effects of climate change on boreal forest carbon storage were less than fire and harvest in medium (30-50 years) and long-term (60-100 years). The variability of climate change and fire disturbance in the Great Xing'an Mountains caused high uncertainty of the future boreal forest carbon storage. The uncertainties of aboveground and soil organic carbon of boreal forests in the Great Xing'an Mountains were 12.4%-16.2% and 6.6%-10.4% in the next 100 years. The effects of seed dispersal, fire and harvest should be taken account for accurate estimation of carbon storage in Chinese boreal forests.

[Drivers of human-caused fire occurrence and its variation trend under climate change in the Great Xing'an Mountains, Northeast China]. / å¤§å ´å®‰å²­äººä¸ºç«å‘ç”Ÿå½±å“å› ç´ åŠæ°”å€™å˜åŒ–ä¸‹çš„è¶‹åŠ¿.

The Great Xing'an Mountains are an important boreal forest region in China with high frequency of fire occurrences. With climate change, this region may have a substantial change in fire frequency. Building the relationship between spatial pattern of human-caused fire occurrence and its influencing factors, and predicting the spatial patterns of human-caused fires under climate change scenarios are important for fire management and carbon balance in boreal forests. We employed a spatial point pattern model to explore the relationship between the spatial pattern of human-caused fire occurrence and its influencing factors based on a database of historical fire records (1967-2006) in the Great Xing'an Mountains. The fire occurrence time was used as dependent variable. Nine abiotic (annual temperature and precipitation, elevation, aspect, and slope), biotic (vegetation type), and human factors (distance to the nearest road, road density, and distance to the nearest settlement) were selected as explanatory variables. We substituted the climate scenario data (RCP 2.6 and RCP 8.5) for the current climate data to predict the future spatial patterns of human-caused fire occurrence in 2050. Our results showed that the point pattern progress (PPP) model was an effective tool to predict the future relationship between fire occurrence and its spatial covariates. The climatic variables might significantly affect human-caused fire occurrence, while vegetation type, elevation and human variables were important predictors of human-caused fire occurrence. The human-caused fire occurrence probability was expected to increase in the south of the area, and the north and the area along the main roads would also become areas with high human-caused fire occurrence. The human-caused fire occurrence would increase by 72.2% under the RCP 2.6 scenario and by 166.7% under the RCP 8.5 scenario in 2050. Under climate change scenarios, the spatial patterns of human-caused fires were mainly influenced by the climate and human factors.

[Spatiotemporal variation of vegetation phenology in the Daxing'an Mountains stratified by eco-geographical regions.] / åŸºäºŽç”Ÿæ€åœ°ç†åˆ†åŒºçš„å¤§å ´å®‰å²­æ¤è¢«ç‰©å€™æ—¶ç©ºå˜åŒ–.

Vegetation phenology is a good indicator of climate change, because of the close correlation between vegetation and climate. The Daxing'an Mountains, located in Chinese northernmost region, are more sensitive to climate change. Researching the spatio-temporal variation of vegetation phenology in this region is of great significance for assessing the influence of global change on terrestrial ecosystem. According to the eco-geographical zoning of China, the Daxing'an Mountains can be divided into for four eco-geographical regions. In this study, the spatial distribution and dynamics of vegetation phenology in the Daxing'an Mountains were analyzed using 8-km resolution GIMMS NDVI 3g dataset from 1982 to 2012. Results showed that the start of growing season in all partitions exhibited an advancing trend, and the end of growing season in all partitions had an extending trend. Vegetation phenology which was sensitive to the change of meteorological factors had a stronger correlation with temperature than with precipitation for all four eco-geographical regions. There was a significant negative correlation between the start of growing season in the northern region and spring temperature. Except for the south of the Daxing'an Mountains, the ending days of growing season in the other three eco-geographical regions had significant negative correlations with summer precipitation. The change of vegetation phenology in the whole study was obvious along with altitude and latitude.

[Progresses of alpine treeline formation mechanism.] / é«˜å±±æž—çº¿å½¢æˆæœºç†ç ”ç©¶è¿›å±•.

Alpine treelines represent one of the most distinct vegetation boundaries between canopy closed montane forest and treeless alpine vegetation. This transitional ecotone is highly sensitive to global and regional climate change and is considered as an ideal indicator of such changes. Treeline studies have evolved from morphological description to various hypotheses of treeline formation. Although individual hypothesis may provide reasonable explanation locally, a generalized hypothesis that is applicable on the global scale is still lacking. Temperature is considered the limited factor controlling the distribution of alpine treeline as low temperature restricts biochemical processes of tree growth. However, which particular biochemical processes are affected by low temperature remains unknown. This paper summarized the mechanisms of treeline formation with a focus on how low temperature affects photosynthesis characteristics, nutrient characteristics, non-structural carbohydrate (NSC) and antioxidant system. We also reviewed the key issues and future perspectives in treeline research.

[Influence of fire disturbance on aboveground deadwood debris carbon storage in Huzhong forest region of Great Xing'an Mountains, Northeast China].

Based on the field inventory data, the aboveground deadwood debris carbon storage under different fire severities was analyzed in Huzhong forest region of Great Xing' an Mountains. The results showed that the fire severity had a significant effect on aboveground deadwood debris carbon storage. The deadwood debris carbon storage was in the order of high-severity > low-severity > unburned in Larix gmelinii stands, and mixed conifer-broadleaf stands ( L. gmelinii and Betula platyphylla), and in the order of high severity > unburned > low-severity in B. platyphylla stands. Fire disturbance significantly changed the component percentage of the deadwood debris carbon storage. The component percentage of snags increased and litter decreased with the increasing fire severity. Logs and stumps did not change significantly with the increasing fire severity. The spatial variation of deadwood debris carbon storage in forests burned with low-severity fire was higher than that in unburned forests. The spatial variation of deadwood debris carbon storage with high-severity fires was lowest. This spatial variation needed to be accounted when calculating forest deadwood debris carbon storage.

[Effects of sampling plot number on tree species distribution prediction under climate change].

Based on the neutral landscapes under different degrees of landscape fragmentation, this paper studied the effects of sampling plot number on the prediction of tree species distribution at landscape scale under climate change. The tree species distribution was predicted by the coupled modeling approach which linked an ecosystem process model with a forest landscape model, and three contingent scenarios and one reference scenario of sampling plot numbers were assumed. The differences between the three scenarios and the reference scenario under different degrees of landscape fragmentation were tested. The results indicated that the effects of sampling plot number on the prediction of tree species distribution depended on the tree species life history attributes. For the generalist species, the prediction of their distribution at landscape scale needed more plots. Except for the extreme specialist, landscape fragmentation degree also affected the effects of sampling plot number on the prediction. With the increase of simulation period, the effects of sampling plot number on the prediction of tree species distribution at landscape scale could be changed. For generalist species, more plots are needed for the long-term simulation.

[Establishment of standard forest fuel models for Fenglin Natural Reserve, Heilongjiang Province, China].

From the viewpoint of forest fire behavior, and based on the key parameters of fuels, three standard forest fuel models for the forests differed significantly in fuel characteristics and local environmental conditions in Fenglin Natural Reserve were established by using hierarchical cluster analysis. The three models were FL-I, FL-II, and FL-III for the broadleaved-Korean pine forest, spruce-fir forest, and poplar-birch forest, the representative forest types in the Reserve, respectively. According to the forest structure and composition, land cover type, and horizontal and vertical continuity, the three models FL-I , FL-II, and FL-III were similar to the models C-5, C-2, and D-1 in Canada CFBPS fuel classification system, respectively. The forest ground features and the horizontal and vertical characteristics of the three models established in this paper could help the investigators to identify the fuel types in fuel inventory.

[Effects of spatial heterogeneity on spatial extrapolation of sampling plot data].

By using model combination method, this paper simulated the changes of response variable (tree species distribution area at landscape level under climate change) under three scenarios of environmental spatial heterogeneous level, analyzed the differentiation of simulated results under different scenarios, and discussed the effects of environmental spatial heterogeneity on the larger spatial extrapolation of the tree species responses to climate change observed in sampling plots. For most tree species, spatial heterogeneity had little effects on the extrapolation from plot scale to class scale; for the tree species insensitive to climate warming and the azonal species, spatial heterogeneity also had little effects on the extrapolation from plot-scale to zonal scale. By contrast, for the tree species sensitive to climate warming, spatial heterogeneity had effects on the extrapolation from plot scale to zonal scale, and the effects could be varied under different scenarios.

[Responses of boreal forest landscape in northern Great Xing'an Mountains of Northeast China to climate change].

With the combination of forest landscape model (LANDIS) and forest gap model (LINKAGES), this paper simulated the effects of climate change on the boreal forest landscape in the Great Xing'an Mountains, and compared the direct effects of climate change and the effects of climate warming-induced fires on the forest landscape. The results showed that under the current climate conditions and fire disturbances, the forest landscape in the study area could maintain its dynamic balance, and Larix gmelinii was still the dominant tree species. Under the future climate and fire disturbances scenario, the distribution area of L. gmelinii and Pinus pumila would be decreased, while that of Betula platyphylla, Populus davidiana, Populus suaveolens, Chosenia arbutifolia, and Pinus sylvestris var. mongolica would be increased, and the forest fragmentation and forest diversity would have an increase. The changes of the forest landscape lagged behind climate change. Climate warming would increase the growth of most tree species except L. gmelinii, while the increased fires would increase the distribution area of P. davidiana, P. suaveolens, and C. arbutifolia and decrease the distribution area of L. gmelinii, P. sylvestris var. mongolica, and P. pumila. The effects of climate warming-induced fires on the forest landscape were almost equal to the direct effects of climate change, and aggravated the direct effects of climate change on forest composition, forest landscape fragmentation, and forest landscape diversity.

Development of customized fire behavior fuel models for boreal forests of northeastern China.

Knowledge of forest fuels and their potential fire behavior across a landscape is essential in fire management. Four customized fire behavior fuel models that differed significantly in fuels characteristics and environmental conditions were identified using hierarchical cluster analysis based on fuels data collected across a boreal forest landscape in northeastern China. Fuel model I represented the dense and heavily branched Pinus pumila shrubland which has significant fine live woody fuels. These forests occur mainly at higher mountain elevations. Fuel model II is applicable to forests dominated by Betula platyphylla and Populus davidiana occurring in native forests on hill slopes or at low mountain elevations. This fuel model was differentiated from other fuel models by higher herbaceous cover and lower fine live woody loading. The primary coniferous forests dominated by Larix gmelini and Pinus sylvestris L. var. mongolica were classified as fuel model III and fuel model IV. Those fuel models differed from one another in average cover and height of understory shrub and herbaceous layers as well as in aspect. The potential fire behavior for each fuel model was simulated with the BehavePlus5.0 fire behavior prediction system. The simulation results indicated that the Pinus pumila shrubland fuels had the most severe fire behavior for the 97th percentile weather condition, and had the least severe fire behavior under 90th percentile weather condition. Fuel model II presented the least severe fire potential across weather conditions. Fuel model IV resulted in greater fire severity than Fuel model III across the two weather scenarios that were examined.

[Simulation of timber-harvesting area in Xiao Xing' anling Mountains under climate change].

By using the spatially explicit forest landscape model (LANDIS 6.0 PRO), the percentages of timber-harvesting area in Xiao Xing' anling Mountains under current harvesting scenario and under 11 harvesting scenarios with alternating harvesting intensities (alternating time was 10, 20 and 30 years, respectively) in 2000-2400 under climate change were simulated. Alternating harvesting intensity could increase the harvesting area. Comparing with current harvesting scenario, the simulated scenarios could increase the harvesting area by 3%-5% at short term (10-30 years), 2.5%-7% at medium term (40-60 years), and 3.5%-8% at long term (70-100 years). On the whole, the current total harvesting area was still high. Alternating harvesting-intensity could increase the harvesting area within a definite term, but the effect would be unsustainable. To have a sustainable development of forestry in the study area, it is necessary to reduce the harvesting intensity and change the forest management policy.

[Effects of eco-protection policy on land use/cover in upper reaches of Minjiang River].

By using CLUE-S model, a scenario analysis was made on the land use/cover change in the upper reaches of Minjiang River from 2000 to 2020, based on the historic development trend and the regulations of policies "natural forest protection" and "grain for green". In 2000-2020, according to the historic development trend, the forestland area (landscape matrix) in the study region would have a continual decrease while the shrub land and grassland areas would be increased, and the landscape pattern would be more fragmental. The implementation of the policies "natural forest protection" and "grain for green" would effectively increase forestland area, being able to reverse the trend of landscape fragmentation and more optimize the landscape pattern.

[Long-term effects of Dendrolimus superans Bulter disturbance on forest landscape in Huzhong Forest Bureau of Great xing' an Mountains: a simulation study].

A spatially explicit landscape model LANDIS was applied to simulate the long-term effects of Dendrolimus superans Bulter disturbance on the forest landscape in Huzhong Forest Bureau of Great Xing' an Mountains. The statistical software pakage APACK was used to calculate the distribution area of D. superans and representative tree species, the aggregation index reflecting the spatial pattern, and the average area of forest patchs. The dynamics of forest landscape in the study region was simulated under two scenarios, i.e., with and without D. superans disturbance for 300 years (from 1990 to 2290). In the region, the distribution area of D. superans showed a trend of increased first and decreased then. Under D. superans disturbance scenario, the distribution area and the average patch size of Larix gmelinii in 0-150 years and the aggregation index of L. gmelinii in 0-190 years, the distribution area and the average patch size of Betula platyphylla and its aggregation index in 80-190 years, as well as the distribution area, average patch size, and aggregation index of Pinus sylvestris var. mongolica were lower or slightly lower than those under no disturbance scenario. D. superans disturbance led to the fragmentation of forest landscape to some extent.

[Extraction of buildings three-dimensional information from high-resolution satellite imagery based on Barista software].

The demand for accurate and up-to-date spatial information of urban buildings is becoming more and more important for urban planning, environmental protection, and other vocations. Today's commercial high-resolution satellite imagery offers the potential to extract the three-dimensional information of urban buildings. This paper extracted the three-dimensional information of urban buildings from QuickBird imagery, and validated the precision of the extraction based on Barista software. It was shown that the extraction of three-dimensional information of the buildings from high-resolution satellite imagery based on Barista software had the advantages of low professional level demand, powerful universality, simple operation, and high precision. One pixel level of point positioning and height determination accuracy could be achieved if the digital elevation model (DEM) and sensor orientation model had higher precision and the off-Nadir View Angle was relatively perfect.

[Spatiotemporal pattern of urban growth and its driving forces in urban agglomeration of central Liaoning Province, China].

Based on the five temporal Landsat TM remote sensing data of 1988, 1992, 1997, 2000, and 2004, and by using GIS spatial analysis and landscape pattern analysis, this paper analyzed the spatiotemporal pattern of urban growth and its driving forces in the urban agglomeration of central Liaoning Province (UACLP). From 1988 to 2004, the urban area in the UACLP had being increased from 812.55 km2 to 1345.86 km2, with an average growth rate of 32.96 km2 per year. The urban growth rate increased rapidly after 1997, and the urban growth intensity was up to the peak in 1997-2000. The urban growth was mainly concentrated in the central dense belt of the UACLP. From 1988 to 1997, the urban growth was relatively slow, its spatial pattern was compact, and edge growth and filling were the main urban growth types. From 1997 to 2004, the urban growth became faster with diffused spatial pattern and complex patch shape, and "frog leap" and diffusion were the main urban growth types. Non-agricultural population growth, economic growth, urban spatial mutual attraction, industrial development, and development zones construction policies were the main driving forces of urban growth in the UACLP.

[Dynamic changes of urban architecture landscape based on Barista: a case study in Tiexi District of Shenyang City].

In this paper, three-dimensional building information was extracted from high resolution satellite image based on Barista software. Combined with ArcGIS software, the dynamic changes of the building landscape in Tiexi District of Shenyang City during urban renewal process were analyzed from the conversion contribution rate, building density, average building height, and built-up area rate. It was found that during this urban renewal process, four dominant landscape types (vacant lot, residential building, industrial building, and road) were the main parts of the landscape changes. The areas of vacant lot, residential building, commercial building, and road increased, while that of industrial building decreased. The building density decreased, while the average building height increased. There was an obvious regional variation in building landscape. The building density in industrial district was higher than that in residential district, while the average building height was in adverse. The further from the city center, the lower the building density and building average height.

[Precision of spatial interpolation for forest duff layer depth based on secondary variable].

Based on geostatistical method, three algorithms of spatial interpolation with elevation as a secondary variable, i.e., simple kriging with varying local means (SKlm), kriging with an external drift (KED), and cokriging (COK), were used to calculate the precision of spatial interpolation for the forest duff layer depth, and cross validation was conducted. The results showed that among the three algorithms, KED gave the highest precision because of its taking into account both the spatial variation among variables and the factors affecting local spatial change, SKlm did not yield expected precision because of the weaker correlation between elevation and forest duff layer depth, while COK directly used the variable elevation to estimate forest duff layer depth but many unexpected results yielded for the boundary area due to insufficient samplings. Comparing with the method of inverse distance weighting (IDW), only KED had a higher precision of interpolation, while for SKlm and COK, their interpolation precision was lower, suggesting that when a secondary variable was used for geostatistical interpolation, the correlation between primary and secondary variables was of significance in increasing the precision of interpolation.

[Spatiotemporal expansion of urban and rural built-up areas in Shenyang City: an analysis based on remote sensing and GIS technology].

By using 1985, 1995, 1997, 2000 and 2004 satellite images and GIS technology, three indices including built-up area density, expansion intensity index, and fractal dimension were chosen to analyze the spatiotemporal characteristics, spatial differentiation, and morphological changes of urban and rural built-up areas in Shenyang City in 1985-2004, with the main driving factors discussed. In the study period, the high-density area of urban built-up area in the City increased year by year, and that of rural built-up area changed slightly before 1997 but increased gradually thereafter. The increased area, expansion speed, and expansion intensity of built-up area were evidently greater in urban than in rural area. An obvious spatial differentiation was observed in the expansion of built-up area between urban and rural areas, with the high-speed expansion mainly concentrated in urban area. The fractal dimension in urban area increased gradually, which meant that the integrated configuration of urban area became more and more complex, while that in rural area changed irregularly, because of the lack of reasonable planning and construction. Economic development, population growth, transportation, natural environment, policy-guiding, and urban planning were the main driving forces of the expansion of built-up areas in Shenyang City.