Rencang Bu

The adequacy of different landscape metrics for various landscape patterns

The behavior of several landscape pattern metrics were tested against various pattern scenarios generated by neutral landscape models, including number of classes, scale-map extent, scale-resolution, class proportion, aggregation level-RULE, and aggregation level-SimMap. The results demonstrate that most of the metrics are sensitive to certain pattern scenarios, yet are not sensitive to others; therefore, none of them is appropriate for all aspects of a landscape pattern. Despite these limitations, some of these metrics are recommended for future use, which include total number of patches, average patch size, total edge density, double-logged fractal, contagion, and aggregation index. Special attention should be paid to the relationships between metric values and ecological processes rather than the numbers themselves. es.

Long-term forest landscape responses to fire exclusion in the Great Xing'an Mountains, China

Understanding of long-term forest landscape dynamics under fire exclusion, which have not been studied in north-eastern China, is increasingly needed for designing sound forest management and protection plans. In the present study, we examine whether long-term fire exclusion leads to catastrophic fires and whether the fire regimes altered by fire exclusion have changed the course of natural succession of dominant tree species. We designed two simulation scenarios - fire exclusion and no fire exclusion - and used LANDIS to study the long-term (300 years) fire regime dynamic and the succession of dominant tree species in terms of species abundance, age structure and spatial pattern. Our simulated results show that fire exclusion can lead to catastrophic fires with return intervals ranging from 50 to 120 years, increase the proportion of coniferous forests and decrease the proportion of deciduous forests, simplify tree species composition, and alter forest age structures and landscape patterns. Based on these simulated results, we suggest that prescribed burning or coarse woody debris reduction, uneven age management, and a comprehensive wildlife habitat suitability analysis should be incorporated in forest management plans in this region.

Predicting fire occurrence patterns with logistic regression in Heilongjiang Province, China

Prediction of forest fire ignition may aid in forest fire vigilance and monitoring, and in prioritizing forest fuel treatments. In this paper, we chose easily obtained spatial variables pertaining to topography, vegetation types, meteorological conditions, climate, and human activity to predict forest fire ignition in Heilongjiang province, China, using logistic regression. Results showed fire ignition prediction through logistic regression had good accuracy. Climatic variables (e.g., average annual mean temperature and precipitation) and meteorological conditions (e.g., daily minimum temperature, daily minimum humidity, daily mean humidity, and mean wind speed) are the main determinants of natural forest fires. In the case of anthropogenic fires, vegetation types and human activity as indicated by distances to roads and settlements combined with suitable meteorological conditions (e.g., daily mean humidity) are the main driving factors. The fire ignition probability map can be easily used to prioritize areas for vigilance, to make decisions on allocating firefighting resources, and to select vulnerable spots for forest fuel treatments. It was found that forest fuel treatments should be focused on the Great Xing’an Mountains.

Simulating the impacts of ecological protection policies on urban land use sustainability in Shenyang-Fushun, China

Chinese cities are undergoing rapid urban sprawl, dramatic landscape change, industrialisation, and ecological damage, which threaten urban sustainable development. The aim of our research was to answer the following question: is it possible to achieve sustainable development through rational ecological protection policies that harmonise future urbanisation, re‐industrialisation, economic development, and sustainable urban land use in these cities? To answer the question, we conducted a simulation of policy impacts on future urban growth and landscape change. We applied a widely used regional assessment and predictive model, SLEUTH, to explore the potential impacts of different ecological protection policy scenarios in the Shenyang-Fushun metropolitan region of China. Future urban growth and landscape changes were projected out to 2050, assuming three different ecological protection policy scenarios: (1) accelerated urban development (AUD), (2) managed urban development (MUD), and (3) limited urban development (LUD). Landscape metrics were used to compare and analyse the impacts of the future scenarios on urban growth and landscape change. Analysis reveals that urban growth and landscape fragmentation increase in all scenarios, but future urban growth area and landscape pattern differ among the scenarios. The AUD scenario will cause excessive urban growth, major land loss, and serious landscape fragmentation. The LUD scenario shows good land resource protection and low landscape fragmentation, but the urban growth rate is unrealistically low, reducing the extent of likely re-industrialisation and economic development. The MUD scenario shows moderate urban growth and landscape fragmentation. It would be the most suitable scenario for the industrial metropolitan area under study if the urban sprawl can be controlled, and it would better harmonise re-industrialisation, ecological health, and land preservation and achieve sustainable development in the area.

Microscale spatial variability of redox potential in surface soil

Redox potential (Eh) is one of the most important chemical properties that control a variety of chemical or biochemical processes in soil ecosystem. Conventional Eh measurements that assume soil Eh as a random, independent variable provide a means for representing the unsampled neighborhood. However, the assumption is inappropriate if spatial dependence of the soil Eh occurs among the samples. This study was conducted to examine microscale spatial dependence and variability of Eh in surface soil using both classic and spatial variance analyses. Four undisturbed soil cores, 13 cm in depth and 10 cm in diameter, were taken from the Ap horizon of Mexico silt loam (fine montmorillonitic, mesic Udollic Ochraqualfs). Soil Eh was measured in situ at 1-cm horizontal and vertical intervals by the platinum microelectrode system and the spatial-dependent structure determined by semivariogram function. The Eh variability in the vertical intervals was higher than that in the horizontal intervals, indicating a higher degree of the vertical heterogeneity. All cores showed the spatial dependence of soil Eh with either spherical or exponential function, but only one core exhibited the range of spatial dependence. Spatially dependent variances accounted for a large portion of the sample total variance, which might be attributed to the Eh trends over soil depth. This study demonstrated that spatial dependence of soil Eh does exist in microscale, and the extent or degree of the spatial variability varies with sampling location and scale, which may affect the extent of a means for representing unsampled neighborhood. Characterization of microscale spatial variability would be a useful tool in revealing or investigating the microscale heterogeneous interactions among soil constituents, plants, and environment.

Predicting Impacts of Climate Change on the Aboveground Carbon Sequestration Rate of a Temperate Forest in Northeastern China

The aboveground carbon sequestration rate (ACSR) reflects the influence of climate change on forest dynamics. To reveal the long-term effects of climate change on forest succession and carbon sequestration, a forest landscape succession and disturbance model (LANDIS Pro7.0) was used to simulate the ACSR of a temperate forest at the community and species levels in northeastern China based on both current and predicted climatic data. On the community level, the ACSR of mixed Korean pine hardwood forests and mixed larch hardwood forests, fluctuated during the entire simulation, while a large decline of ACSR emerged in interim of simulation in spruce-fir forest and aspen-white birch forests, respectively. On the species level, the ACSR of all conifers declined greatly around 2070s except for Korean pine. The ACSR of dominant hardwoods in the Lesser Khingan Mountains area, such as Manchurian ash, Amur cork, black elm, and ribbed birch fluctuated with broad ranges, respectively. Pioneer species experienced a sharp decline around 2080s, and they would finally disappear in the simulation. The differences of the ACSR among various climates were mainly identified in mixed Korean pine hardwood forests, in all conifers, and in a few hardwoods in the last quarter of simulation. These results indicate that climate warming can influence the ACSR in the Lesser Khingan Mountains area, and the largest impact commonly emerged in the A2 scenario. The ACSR of coniferous species experienced higher impact by climate change than that of deciduous species.

Are plot data effective for landscape prediction? A simulation study of tree species response to climate warming under varying environmental heterogeneity

IntroductionExtrapolating plot data to broader spatial scales depends largely on environmental heterogeneity.ObjectivesWe studied this subject in the Changbai Mountains Natural Reserve in northeastern China by examining three scenarios of environmental heterogeneity. Scenarios 1, 2 and 3 represented local, class and zonal scale, and corresponded to the highest, intermediate and lowest level of environmental heterogeneity, respectively. Plot-level observation was represented by species establishment probability derived from an ecosystem process model that used plot observational data (e.g., weather, soil, vegetation, etc.) as input. Response variables at broader spatial scales, which were derived from a landscape model, included species total area and spatial pattern (measured by mean patch size) in the short, medium and long term. We examined whether these response variables differ statistically among the three scenarios.ResultsOur results indicate that for species whose total area changes occur mainly within the same elevation zone in which the experimental plots reside, individual plots can capture the changes for the entire elevation zone. By contrast, for species that span many elevation zones under warming climate, plot-level observations are not reliable in predicting broader spatial scale change. Our results also suggest that species spatial patterns do not always coincide with those found for total area.

Study on forecast scenarios for simulation of future urban growth in Shenyang City based on SLEUTH model

The SLEUTH urban growth model was used to simulate future urban growth patterns and to explore potential environmental impacts of urban development under different conditions of development in Shenyang City, China. The SLEUTH model was calibrated with historical data (1988–2004) extracted from a time series of TM satellite images, and the future growth was projected out to 2030 assuming three different policy scenarios: (1) current trends scenario (Scenario CT), (2) regional policy and urban planning scenario (Scenario PP), and (3) environmental protection scenario (Scenario EP). Scenario analysis showed that urban growth would accelerate under all policy scenarios with significant differences in development pattern and sustainability after 2016. Urban development under Scenario CT would lead to substantial loss of resource lands than that under the other two scenarios, and the urban landscape pattern would be increasingly complex and dispersed. In contrast, urban growth under scenario PP and EP would consume less natural resource land and show a relatively compact urban development pattern during the prediction period. This study suggested that it is crucial to take stringent urban planning and management measures to control future urban growth and to protect primary farmland and the support system of urban ecology in Shenyang City. The SLEUTH model is a useful planning tool to guide sustainable utilization of urban land resources to a certain extent.

Changes of forest fire regime and landscape pattern under different harvesting modes in a boreal forest of Northeast China

Forest management such as timber harvesting shapes fire regimes and landscape patterns, and these patterns often differ significantly from those under natural disturbances. Our objective was to examine the effects of timber harvesting modes on fire regimes and landscape patterns in a boreal forest of Northeast China. We used a spatially explicit landscape model, LANDIS, to simulate the changes of forest landscape in the Huzhong forest region of the Great Khingan Mountains under no-cutting, clear-cutting, gradual-cutting and selective-cutting modes. Results showed that: (1) the fine fuel loadings generally decreased while the coarse fuel loadings increased with the increase of timber harvesting intensity; (2) the potential burn area significantly varied among different cutting modes, but the potential fire frequency had no obvious difference. Moreover, timber harvesting generally increased the potential fire risk; (3) clear-cutting mode significantly decreased the mean patch size and the aggregation of larch forests and increased the mean patch size and the aggregation of white birch forests. Therefore, clear-cutting mode should be abandoned, and selective-cutting mode be recommended for the sustainable forest management in the Great Khingan Mountains.

Recovery of understory vegetation biomass and biodiversity in burned larch boreal forests in Northeastern China

ABSTRACT Recovery of biomass and biodiversity of forest understory vegetation after fire disturbance has been widely studied; however, how this relationship changes and what are the determinants at different post-fire stages in larch boreal forests are still unclear. We investigated a chronosequence of 81 understory plots in larch boreal forests that were disturbed by fires in 1987 (S5), 1992 (S4), 1996 (S3), 2002 (S2), or 2007 (S1). Analysis of variance was conducted to test the differences of biodiversity and biomass among various post-fire stages. Different regression models were used to fit the relationship between biomass and biodiversity, while factors influencing this relationship were identified by boosted regression tree analysis. Results showed that total understory biomass increased from 2.51 t ha−1 in S1 to 8.47 t ha−1 in S3 and declined to 5 t ha−1 in S5. Similar dynamics were also found between species richness and species diversity. Positive linear correlations linked biomass and biodiversity throughout most of the post-fire periods. Slope and stand density were the two most important factors influencing the secondary succession of understory vegetation after fire. Geographical factors and overstory competition determine the orientation of vegetation recovery, and the impacts of climate on vegetation are muted after fire disturbances.