Zoning eco-environmental vulnerability for environmental management and protection

Eco-environmental vulnerability assessment is crucial for environmental and resource management. However, evaluation of eco-environmental vulnerability over large areas is a difficult and complex process because it is affected by many variables including hydro-meteorology, topography, land resources, and human activities. The Thua Thien – Hue Province and its largest river system, the Perfume River, are vital to the social-economic development of the north central coastal region of Vietnam, but there is no zoning system for environmental protection in this region. An assessment framework is proposed to evaluate the vulnerable eco-environment in association with 16 variables with 6 of them constructed from Landsat 8 satellite image products. The remaining variables were extracted from digital maps. Each variable was evaluated and spatially mapped with the aid of an analytical hierarchy process (AHP) and geographical information system (GIS). An eco-environmental vulnerability map is assorted into six vulnerability levels consisting of potential, slight, light, medium, heavy, and very heavy vulnerabilities, representing 14%, 27%, 17%, 26%, 13%, 3% of the study area, respectively. It is found that heavy and very heavy vulnerable areas appear mainly in the low and medium lands where social-economic activities have been developing rapidly. Tiny percentages of medium and heavy vulnerable levels occur in high land areas probably caused by agricultural practices in highlands, slash and burn cultivation and removal of natural forests with new plantation forests. Based on our results, three ecological zones requiring different development and protection solutions are proposed to restore local eco-environment toward sustainable development. The proposed integrated method of remote sensing (RS), GIS, and AHP to evaluate the eco-environmental vulnerability is useful for environmental protection and proper planning for land use and construction in the future.     

Modelling biomass of mountainous grasslands by including a species composition map

High mountain grasslands offer multiple goods and services to society but are severely threatened by improper land use practices such as abandonment or rapid intensification. In order to reduce abandonment and strengthen the common extensive agricultural practice a sustainable land use management of high mountain grasslands is needed. A spatially detailed yield assessment helps to identify possible meadows or, on the contrary, areas with a low carrying capacity in a region, making it easier to manage these sites. Such assessments are rarely available for remote and inaccessible areas. Remotely sensed vegetation indices are able to provide valuable information on grassland properties. These indices tend, however, to saturate for high biomass. This affects their applicability to assessments of high-yield grasslands.The main aim of this study was to model a spatially explicit grassland yield map and to test whether saturation issues can be tackled by consideration of plant species composition in the modelling process. The high mountain grassland of the subalpine belt (1800 – 2500 m a.s.l.) in the Kazbegi region, Greater Caucasus, Georgia, was chosen as test site for its strong species composition and yield gradients.We first modelled the species composition of the grassland described as metrically scaled gradients in the form of ordination axes by random forest regression. We then derived vegetation indices from Rapid Eye imagery, and topographic variables from a digital elevation model, which we used together with the multispectral bands as predictive variables. For comparison, we performed two yield models, one excluding the species composition maps and one including the species composition map as predictors. Moreover, we performed a third individual model, with species composition as predictors and a split dataset, to produce the final yield map.Three main grassland types were found in the vegetation analysis: Hordeum violaceum-meadows, Gentianella caucasea-grassland and Astragalus captiosus-grassland. The three random forest regression models for the ordination axes explained 64%, 33% and 46% of the variance in species composition. Independent validation of modelled ordination scores against a validation data set resulted in an R² of 0.64, 0.32 and 0.46 for the first, second and third axes, respectively. The model based on species composition resulted in a R² = 0.55, whereas the benchmark model showed weaker relationships between yield and the multispectral reflectance, vegetation indices, and topographical parameters (R² = 0.42). The final random forest yield model used to derive the yield map resulted in 62% variance explained and an R² = 0.64 between predicted and observed biomass. The results further indicate that high yields are generally difficult to predict with both models.The benefit of including a species composition map as a predictor variable for grassland yield lies in the preservation of ecologically meaningful features, especially the occurrence of high yielding vegetation type of Hordeum violaceum meadows is depicted accurately in the map. Even though we used a gradient based design, sharp boundaries or immediate changes in productivity were visible, especially in small structures such as arable fields or roads (Fig. 6b), making it a valuable tool for sustainable land use management. The saturation effect however, was mitigated by using species composition as predictor variables but is still present at high yields.     

A method for studying vegetation dynamics when there are no obvious individuals: Virtual-population analysis applied to the tundra shrub Betula nana L.

A method is presented to study dynamics of plants that cannot be separated into individuals such as many grassland, salt marsh and tundra species. A virtual population is created by using a permanent transect line through the vegetation and individuals are defined as the branch segments distal to the intercept with the transect line. Addition and loss of individuals together with growth or shrinkage form the basis for constructing a size-structured transition matrix. A discrete-event simulation demonstrates that: 1) a virtual population of individuals grows at the same rate as the parent population; and, 2) size-structured transition matrices for a virtual population and parent vegetation have similar dominant and subdominant eigenvalues so a virtual population can be used to describe the dynamics of a parent vegetation.Dwarf birch, Betula nana L., was studied in the northern foothills of the Brooks Range, Alaska, by using photography to record branch intercepts along permanent transect lines. The distal branch segments constitute a virtual population of the parent vegetation. Transects were photographed in 1985 and again in 1986 and changes of branch segments were used to construct two transition matrices for shrubs with and without elevated fertilizer treatment. Analysis of the virtual populations suggests that although Betula nana may show increased branch growth with increased fertilizer, in the long run this shrub may decline in the tundra in response to such treatment.     

Fractal properties of forest spatial structure

The definition of fractal dimension of natural objects, which enables to deal with scale dependence of fractal dimension is discussed. Abrupt changes of fractal dimension of spatial structure of terrestrial ecosystems are considered in the context of hierarchical paradigm. On this ground the procedure is proposed for segmentation of a territory, which takes into account the scale dependence of spatial variability of ecological parameters. Using remotely sensed data — normalized difference vegetation index (NDVI) and thermal radiation in the infrared band — fractal dimensions and critical scales are evaluated for different forest types with the help of software, developed for this purpose. The results obtained corroborate the potentialities of fractal approach in ecology. These methods and results can be used for discrimination of remotely sensed data; but further investigations, including detailed comparison of fractal characteristics of remotely sensed forest images with results of on-site field studies are necessary to validate them.     

Effects of fire on landscape heterogeneity in Yellowstone National Park,Wyoming

Abstract. A map of burn severity resulting from the 1988 fires that occurred in Yellowstone National Park (YNP) was derived from Landsat Thematic Mapper (TM) imagery and used to assess the isolation of burned areas, the heterogeneity that resulted from fires burning under moderate and severe burning conditions, and the relationship between heterogeneity and fire size. The majority of severely burned areas were within close proximity (50 to 200 m) to unburned or lightly burned areas, suggesting that few burned sites are very far from potential sources of propagules for plant reestablishment. Fires that occurred under moderate burning conditions early during the 1988 fire season resulted in a lower proportion of crown fire than fires that occurred under severe burning conditions later in the season. Increased dominance and contagion of burn severity classes and a decrease in the edge: area ratio for later fires indicated a slightly more aggregated burn pattern compared to early fires. The proportion of burned area in different burn severity classes varied as a function of daily fire size. When daily area burned was relatively low, the proportion of burned area in each burn severity class varied widely. When daily burned area exceeded 1250 ha, the burned area contained about 50 % crown fire, 30 % severe surface burn, and 20 % light surface burn. Understanding the effect of fire on landscape heterogeneity is important because the kinds, amounts, and spatial distribution of burned and unburned areas may influence the reestablishment of plant species on burned sites.     

Distribution and conservation status of coastal sage scrub in southwestern California

Abstract. A landscape-based characterization of vegetation has been developed for southwestern California using satellite imagery, air photos, existing vegetation maps, and field data. Distribution maps of nine dominant coastal scrub species and 13 species assemblages that were identified by divisive information analysis have been analyzed to quantify spatial patterns of species co-occurrence. Three general distribution patterns are identified that suggest the Diegan, Ventaran and Riversidian Associations identified by other workers. Vegetation data have also been related to land ownership and management to assess the conservation status of upland plant communities. A large proportion of the mapped distribution of species and vegetation types is on private land, and several taxa show less than 4 % of mapped distribution in nature reserves. The analysis highlights the need to extend current conservation planning efforts into the northern part of the region to encompass areas where Salvia leucophylla is a frequent community dominant.     

Ecosystem responses to changes in plant functional type composition: An example from the Patagonian steppe

Abstract. Grass cover along a grazing intensity gradient in Patagonia decreases, whereas bare soil and shrub cover increases. Our objective was to study the effect of a change in the dominant plant functional type on soil water balance, primary production, herbivore biomass, roughness, and albedo. Using a soil water balance model, we found increases in evaporation and deep drainage, and a decrease in total transpiration along the grazing intensity gradient. Above-ground primary production, estimated from transpiration, decreased along the grazing intensity gradient because shrubs did not fully compensate for the decrease in grass production. Using a statistical model, we calculated herbivore biomass from estimates of above-ground primary production. Estimated herbivore biomass was lowest in the shrub-dominated extreme of the grazing gradient. Roughness increased from the grass-dominated to the shrub-dominated community. Albedo had a maximum at an intermediate position along the gradient. Our results suggest that changes in plant functional type composition, independent of changes in biomass, affect ecosystem functioning and the exchange of energy and material with the atmosphere. Grasses and shrubs proved to be appropriate plant functional types to link structure and function of ecosystems.     

A vegetation map of tropical continental Asia at scale 1:5 million

Abstract. A vegetation map at scale 1:5 million is presented. * * Attached on the inside of this issue's back cover.
It covers Bangladesh, Burma (Myanmar), India, Cambodia, Laos, Thailand, Vietnam and Sri Lanka and fills a conspicuous gap in the cartography of tropical vegetation, following the publication of vegetation maps of South America, Africa and Malaysia. For conformity, it is presented as one sheet at a scale of 1:5 million. It uses the basic map of the American Geographical Society (1942; bipolar oblique conformal projection) which forms the base for FAO's Soil map of the world. Basic information was obtained from many published maps, unpublished observations and satellite data. The limits of the main vegetation types have been updated with a complete set of Landsat MSS images (369 scenes) with a mosaic of Landsat TM data for 1991 and with recent forest maps from Asia. Nine main vegetation units, which are groups of forest formations, have been identified and mapped, including woodlands, thickets and wooded savannas. Agricultural land has been shown in a uniform pale green colour in order to clearly express the extent of human impacts on woody vegetation. In spite of the necessary oversimplification of the ground data, this map is probably the most explicit expression of the remaining forest stands and of the regression of natural vegetation in the region. It can be considered as a benchmark for future monitoring of tropical vegetation.     

泥炭藓群落的光谱特征及遥感识别研究

以中位泥炭藓（Sphagnum magellanicum Brid.）为研究对象,分别从实测冠层光谱和遥感传感器模拟光谱层面分析其群落的光谱特征。研究结果显示,中位泥炭藓与北方针叶林光谱差异明显,最佳光谱识别区间为740~1140 nm和1230~1412 nm。在可见光波段上,中位泥炭藓与云杉（Picea engelmannii Parry ex Engelmann）和黑松（Pinus contorta Douglas ex Loudon）的绿峰位置有所差异。水竹（Phyllostachys heteroclada Oliver）和中位泥炭藓的光谱识别特征波段集中在可见光-近红外波段,分别为400~550、560~696、1025~1143 nm。中位泥炭藓与北方针叶林以及水竹的特征光谱区间存在细微差异,且与水竹在可见光波段有较好的可分性,因此不同纬度带上中位泥炭藓群落的特征谱宽有所差异。红外波段是中位泥炭藓识别的最佳光谱区间。在多光谱遥感水平上,中位泥炭藓识别效果较好,传感器的识别能力依次为：MSI > ALI > OLI > ASTER。在2个中位泥炭藓群落的光谱特征分析中,导数、对数、包络线去除法的光谱降维能力有所差异,其中包络线去除法效果最好。