Yuanman Hu

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.

A simulation study of landscape scale forest succession in northeastern China

Abstract Changbai Natural Reserve in northeastern China provides an excellent opportunity to explore how temperate and boreal forest ecosystems in northeastern China will evolve and recover over large spatial and temporal scales. Such studies are increasingly needed to design scientifically sound forest management and restoration plans in this region. Long-term (300 years) successional trajectories of the dominant tree species are simulated on the heterogeneous, undisturbed area (within the reserve) using a spatially explicit landscape model. We also examine the spatial and temporal constrains of landscape recovery on the human disturbed areas (surrounding the reserve). Simulation results suggest that an equilibrium in landscape structure and composition is approached on the large landtypes dominated by shade tolerant species, but not on landtypes altered by humans. Such equilibrium can be observed in spruce-fir, mountain birch, and larch forests and not in aspen-birch forests. Our results suggest that direct and indirect human impact may produce long-term alterations to forest landscape patch structure that persist for decades to centuries. For example, even with complete natural succession over 300 years, Korean pine only recovers on 1/3 of the areas in the landtypes it can dominate. We estimate a full recovery would take another 200–300 years without human disturbance. Our results also indicate that landscape-scale recovery is often limited by the available seed sources and this is particularly true for Korean pines in this region. Comparison of simulation results for the entire study area with land types (two scales) reveals the greatest variations at the land type scale. This discrepancy indicates that the ‘space-for-time’ substitutions can be flawed as species composition and age class at a given site and time may represent only the specific successional history of that site. This is particularly true for human disturbed forest landscapes where higher variations are observed.

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.

Methane (CH4) Emission from a Natural Wetland of Northern China

Abstract This article focuses on the seasonal and spatial changes of CH4 emission from the natural reed marsh of Liaohe Delta, China. Field experiments showed that this natural wetland acts as a CH4 sink in spring (−30 ∼ −1000 μ g/m2.h), a strong source in summer (400–3000 μ g/m2.h) and a weak source in autumn (< 400 μg/m2.h). Reed plants play an important role in transportation and emission of methane produced in soil. According to our field measurement data, CH4 emission is positively related to temperature, and negatively related to Eh value and water depth. The activity of methanogenic bacteria is higher in the rhizosphere and surface layer, and thus contributes more in CH4 emission than other layers.

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.

Combining CLUE-S and SWAT models to forecast land use change and non-point source pollution impact at a watershed scale in Liaoning Province, China

Non-point source (NPS) pollution has become a major source of water pollution. A combination of models would provide the necessary direction and approaches designed to control NPS pollution through land use planning. In this study, NPS pollution load was simulated in urban planning, historic trends and ecological protection land use scenarios based on the Conversion of Land Use and its Effect at Small regional extent (CLUE-S) and Soil and Water Assessment Tool (SWAT) models applied to Hunhe-Taizi River Watershed, Liaoning Province, China. Total nitrogen (TN) and total phosphorus (TP) were chosen as NPS pollution indices. The results of models validation showed that CLUE-S and SWAT models were suitable in the study area. NPS pollution mainly came from dry farmland, paddy, rural and urban areas. The spatial distribution of TN and TP exhibited the same trend in 57 sub-catchments. The TN and TP had the highest NPS pollution load in the western and central plains, which concentrated the urban area and farm land. The NPS pollution load would increase in the urban planning and historic trends scenarios, and would be even higher in the urban planning scenario. However, the NPS pollution load decreased in the ecological protection scenario. The differences observed in the three scenarios indicated that land use had a degree of impact on NPS pollution, which showed that scientific and ecologically sound construction could effectively reduce the NPS pollution load in a watershed. This study provides a scientific method for conducting NPS pollution research at the watershed scale, a scientific basis for non-point source pollution control, and a reference for related policy making.

Simulate urban growth based on RS, GIS, and SLEUTH model in Shenyang-Fushun metropolitan area northeastern China

Shenyang and Fushun are two most nearest mega cities in China. Integration of the two cities as one sub-administrative economic region is a state and province policy to promote economy development of Liaoning province. How the urban patterns of the mega cities will grow is interested to city planners, decision-makers, land managers, ecologists, geographers, and resource managers because its special policy and spatiotemporal dynamic complexity. This study explore the combined application of remote sensing, geographical information system and SLEUTH urban growth model to analyze and model urban growth pattern in Shenyang-Fushun metropolitan area northeastern China. The sequential RS images can give quantitative descriptors of the geometry of urban form to be computed and compared over time. The investigation is based on a 16-year time series data set compiled from interpreted historical TM satellite imagery. The SLEUTH model was calibrated using the mutil-temporal data set for the 6391.12km2 area where has experienced rapid urbanization in recent years. The model allowed a spatial forecast of urban growth, and future growth was projected out to 2050 assuming four different policy scenarios: (1) current trends (CT), (2) accelerated urban development (AUD), (3) protected urban development (PUD), and (4) limitative urban growth (LUD). The predicted urban growth shows similar compact pattern under each scenario except the current trends scenario that shows diffused urban growth pattern and most diffused growth appears at south of region. Edge growth and road gravity growth are the main growth types in the future. The accelerated urban development scenario shows the most urban growth area. The limitative urban growth scenario shows the least urban growth area. The protected urban development scenario shows moderate urban growth area and good protection to other land resources. The urban land of two mega cities will connect firstly to a whole on the south bank of Hun River about in 2040 in the accelerated urban development and the current trends scenarios, and will not connect on the other two scenarios until 2050. The combined method using remote sensing, geographical information system and SLEUTH urban growth model is powerful for representation, modeling and prediction of the spatiotemporal urban growth, and useful for understanding the alternative future planning scenarios, but location accuracy and scenarios design must be further considered for local application.