Four grids, each 3,42 ha (4 morgen) in size, were live trapped from April 1967 through May 1969 in two soil and vegetation types (black turf~ Acacia nigrescens community, and brown reddish soil: Acacia tortilis community) at Pongola, northern Zululand, to determine the effect of dieldrin coverspraying, at a dosage of 87,4 g/hectare (2,64 oz/morgen), on rodents. Low population numbers before and especially at the time of spraying made clear-cut conclusions impossible to reach. Rodent populations (mainly Praomys (Mastomys) natalensis, Saccostomus campestris, and Lemniscomys griselda) were apparently not adversely effected, although L. griselda numbers showed a decline which was not in correspondence with that on the control area. This might be ascribed to dieldrin spraying. Relatively higher numbers of s. campestris and L. griselda were observed during periods of lower P.( M.) ~talensis numbers. Decreases in P.( Me) natalensis populations coincided with times of food scarcity. Praomys (Mastomys) natalensis are thus found in association with other rodents when abundant food is available, but seems to give way when competition due to food scarcity occurs. Reproductive data obtained from the study were too meagre to allow any conclusions concerning the effect of spraying thereon. The method involving the calculation of maximum distance between captures was used to express movement patterns of the species studied. Populat~on structure is express~d in terms of sex ratios, and frequency per mass class for each season. The size of animals was investigated by measuring total length, tail length, and head and body length. Behavioural features of the species captured were also noted. / Dissertation (MSc)--University of Pretoria, 1972. / gm2014 / Zoology and Entomology / Unrestricted

To determine the relationship between vegetation and environmental parameters in the middle and upper watershed of Nan-Tze-Shian stream, the first comprehensive multivariate statistical analysis of the woody vegetation data obtained from field survey, is presented. According to physiognomy and plant composition, 70 homogenous stands were sampled in the area. Each plot is composed of twenty 5 ¡Ñ 5 m2 quadrates. Five environmental factors including plot location, altitude, slope, aspect and microtopography were recorded. All woody plants in each plot species with dbh ≥ 1cm present in the quadrates were identified, and their dbh were measured. In addition, ground layer species were identified and evaluated by their coverage. The vascular plants inventory recorded a total of 118 families, 321 genera and 563 species. Among the 203 woody plants, the families are rich in species including Lauraceae, Fagaceae, Theaceae, Symploaceae and Moraceae. Detrended correspondence analysis (DCA) was applied to the ordination analysis, to clarify the spatial variation of the 70 plots and search for relationship of the variation with 5 environmental variables. Classification of the vegetation types was conducted by the cluster analysis (CA), two-way indicator species analysis (TWINSPAN) and tabular comparison method. The results obtained from the analysis are that the distribution of vegetation types and flora are obvious and sensitive to the elevation and whole light sky space (WLS) and the floristic classification distinguished 9 forest types: Neolitsea acuminatissima - Cyclobalanopsis morii, Vaccinium randaiense - Castanopsis cuspidata, Pasania kawakamii - Cyclobalanopsis stenophylloides, Beilschmiedia erythrophloia, Engelhardtia roxburghiana - Cyclobalanopsis longinux, Helicia formosana - Machilus konishii kusanoi, Castanopsis formosana, Machilus zuihoensis - Schefflera octophylla and Ficus irisana - Machilus kusanoi associations. The associations were re-arranged by tabular comparison method for developing a hierachy of forest vegetation system. This hierachical system consists of Three alliances, characterized by Cyclobalanopsis stenophylloides, Beilschmiedia erythrophloia and Machilus kusanoi, respectively. Finally, I ascribed the vertical vegetation spectrum along with altitude gradient. The altitudinal boundaries between upper Quercus, lower Quercus and Machilus-Castanopsis zones are ca. 1800 m and 1200 m, respectively. The results might help us to understand the habitat diversity and plant diversity in the area, and those are expected to apply to vegetation mapping and environment monitoring.

Heavy metals, such as mercury (Hg), have a long residence time in the atmosphere and can be transported long distances and deposited in the Arctic via wet and dry deposition. Still, there are few studies on the complex mercury cycle and how different plant groups absorb Hg. In this study, I investigated if and/or how Hg concentrations differ between different humus soils in tundra vegetation types in Alaska and Abisko. I also investigated the potential changes in Hg deposition with increasing elevation in Abisko (500, 750, and 1000 m a.s.l). Further, a comparison between the analyzing methods XRF (X-ray fluorescence) and HF digestion was evaluated to investigate if XRF is a suitable method for analyzing heavy metals in the humus layer of soils. To achieve this, humus soil samples from four different vegetation types in Alaska and two from Abisko were analyzed with a Hg analyzer (DMA-80 Direct Mercury Analyzer) and a handheld XRF. The results show that Hg concentration was highest in heath vegetation for Alaska and Abisko. Meanwhile, increasing elevation had no impact on Hg concentration in general, nor was there a difference within the two vegetation types. The comparison between HF digestion and XRF resulted in a positive linear relationship for P, Fe, and Al. The results highlight that Hg concentration differs between humus soil due to different vegetation types, although there is no clear explanation to the distribution of Hg in aboveground vegetation. Litterfall and precipitation may influence Hg concentrations with elevation, and the XRF samples need to be replicated multiple times to avoid errors, as my study shows.

Heavy metals, such as mercury (Hg), have a long residence time in the atmosphere and can be transported long distances and deposited in the Arctic via wet and dry deposition. Still, there are few studies on the complex mercury cycle and how different plant groups absorb Hg. In this study, I investigated if and/or how Hg concentrations differ between different humus soils in tundra vegetation types in Alaska and Abisko. I also investigated the potential changes in Hg deposition with increasing elevation in Abisko (500, 750, and 1000 m a.s.l). Further, a comparison between the analyzing methods XRF (X-ray fluorescence) and HF digestion was evaluated to investigate if XRF is a suitable method for analyzing heavy metals in the humus layer of soils. To achieve this, humus soil samples from four different vegetation types in Alaska and two from Abisko were analyzed with a Hg analyzer (DMA-80 Direct Mercury Analyzer) and a handheld XRF. The results show that Hg concentration was highest in heath vegetation for Alaska and Abisko. Meanwhile, increasing elevation had no impact on Hg concentration in general, nor was there a difference within the two vegetation types. The comparison between HF digestion and XRF resulted in a positive linear relationship for P, Fe, and Al. The results highlight that Hg concentration differs between humus soil due to different vegetation types, although there is no clear explanation to the distribution of Hg in aboveground vegetation. Litterfall and precipitation may influence Hg concentrations with elevation, and the XRF samples need to be replicated multiple times to avoid errors, as my study shows.

No description available.

Forests have the ability to sequester carbon from our atmosphere. Soil respiration (Rs) plays a role in a forest's ability to do so as it is a significant source of carbon dioxide back to the atmosphere. Therefore, understanding the process of Rs under varying conditions is gaining more attention. As of now we have a relatively good understanding of Rs under managed forest ecosystems such as pine plantations. This particular study examined Rs under different overstories and understories in a high elevation Southern Appalachian forest in order to get a better understanding of Rs under a natural hardwood system. The four vegetation types under consideration were an eastern hemlock (Tsuga canadensis L. Carriere) dominated overstory, a hardwood overstory with little to no understory, a mountain laurel (Kalmia latifolia L.) dominated understory, and a cinnamon fern (Osmundastrum cinnamomeum (L.) C.Presl) dominated understory. Differing temporal variations of Rs were observed under the vegetation types. We found monthly differences in rates among vegetation type however, an overall annual difference in Rs rates between vegetation types was not observed. This simply indicates the importance of observing Rs under different time scales to get a better understanding of its variation. We also calculated vegetation indices from remotely-sensed data to explore any relationships to Rs as well as if the indices themselves could improve out model. A vegetation index is a number that is calculated for every pixel in a remotely sensed image and represents plant vigor or abundance. Few significant relationships were found between the indices and Rs. Future work may want to better understand vegetation indices' spatial extent and accuracy in order to find whether they may be beneficial in Rs estimation. Understanding the influence of varying vegetation type and soil temperature and moisture on Rs will ultimately improve our ability to predict what drives changes in carbon fluxes. / Master of Science / Forests have the ability to sequester carbon from our atmosphere. Soil respiration (Rs) plays a role in a forest’s ability to do so as it is a significant source of carbon dioxide back to the atmosphere. Therefore, understanding the process of Rs under varying conditions is gaining more attention. As of now we have a relatively good understanding of Rs under managed forest ecosystems such as pine plantations. This particular study examined Rs under different overstories and understories in a high elevation Southern Appalachian forest in order to get a better understanding of Rs under a natural hardwood system. The four vegetation types under consideration were an eastern hemlock (Tsuga canadensis L. Carriere) dominated overstory, a hardwood overstory with little to no understory, a mountain laurel (Kalmia latifolia L.) dominated understory, and a cinnamon fern (Osmundastrum cinnamomeum (L.) C.Presl) dominated understory. Differing temporal variations of Rs were observed under the vegetation types. We found monthly differences in rates among vegetation type however, an overall annual difference in Rs rates between vegetation types was not observed. This simply indicates the importance of observing Rs under different time scales to get a better understanding of its variation. We also calculated vegetation indices from remotely-sensed data to explore any relationships to Rs as well as if the indices themselves could improve out model. A vegetation index is a number that is calculated for every pixel in a remotely sensed image and represents plant vigor or abundance. Few significant relationships were found between the indices and Rs. Future work may want to better understand vegetation indices’ spatial extent and accuracy in order to find whether they may be beneficial in Rs estimation. Understanding the influence of varying vegetation type and soil temperature and moisture on Rs will ultimately improve our ability to predict what drives changes in carbon fluxes.

Invasive spread of neophyte Impatiens glandulifera in central Europe started approximatelly eighty years ago. First records of dense cover stands come from belt stands in riparian habitats. The scale of invaded habitats and degree of the dominance of I. glandulifera is more diversified nowadays. This thesis is objected on the dominance and fertility of I. glandulifera within different habitat types and scale of invaded habitats in different parts of invaded range within Europe (i. e. in Czech Republic and Switzerland). The results show that the height and cover (substitutes for biomass and dominance) of this neophyte (i) correlates with the character of invaded vegetation (ii) relates to the degree of hemeroby (a measure of human impact) negativelly, and (iii), of course, both the growth and dominance are positively affected by nutrient content. Fertility does not differ among the types of invaded habitats, but goes up with the height of I. glandulifera and decreases with its cover. Invaded habitats comprises ruderal and riparian vegetation, but also wet maedows, forest clearances, beach and slope forests or weed vegetation.

This research developed an ArcGIS Python model that extracts polygons from aerial imagery and assigns each polygon a vegetation type based on a modified set of landcover classes from the Southwest Regional Gap Analysis Project. The model showed an ability to generate polygons that accurately represent vegetation community boundaries across a large landscape. The model is for use by the Utah Division of Forestry, Fire, and State Lands to assist in the preparation of forest management plans. The model was judged useful because it was easy to use, it met a designated 50% threshold of useable polygons, and it met a designated 50% threshold of vegetation class assignment accuracy.

In boreal catchments, stream water chemistry is influenced and controlled by several landscape factors. The influence of spatially distributed variables is in turn dependent on the hydrological scale. Headwater streams have larger variability of water chemistry, and thus together represent a large biodiversity, and therefore need to be monitored in official environmental assessments. One objective of this study was, using Geographical Information Systems (GIS), to analyse co-variation between landscape variables and water chemistry and to determine which of the landscape variables have a major influence on the concentration of dissolved organic carbon (DOC) in headwater streams. Another objective was to find a simple method for predicting sources of DOC, using official map data and publically available GIS applications. Totally 85 headwater catchments (0.1-4 km2) in the county of Värmland, western south Sweden, were used in the study. Water chemistry was analysed for water sampled at low, medium and high flows, and landscape variables were extracted from official map data sources: topographic maps, a digital elevation model (DEM, 50 m grid), and vegetation data. Statistical analyses showed that topography (mean slope and mean topographic wetness index (TWI)) and wetland cover often correlated well with DOC in headwater catchments. Official map data could satisfactorily extract landscape variables (mean slope, mean TWI) that were useful in predicting stream water chemistry (DOC). A high-resolution elevation model, which was generated by interpolation of photogrammetric data, was used to calculate and evaluate two different wetness indices and their ability to predict the occurrence of wetlands in six catchments of different sizes and topography. The SAGA (System for Automated Geoscientific Analyses) wetness index (SWI) gave substantially better results than the TWI. The effects of resolution of DEMs on calculations of the SWI were investigated using 5, 10, 25 and 50 m grids. The results showed that SWI values increased with increasing cell size. The near linear increment of mean values for resolutions 10-50 m suggests a independence of terrain type and catchment size, which supported previous findings that indicated that mean slope and mean wetness index calculated from coarse elevation models may be used for prediction of DOC in headwater streams.