The influence of Acacia Mearnsii invasion on soil properties in the Kouga Mountains, Eastern Cape, South Africa
- Van der Waal, Benjamin Wentsel
- Authors: Van der Waal, Benjamin Wentsel
- Date: 2010
- Subjects: Acacia mearnsii -- South Africa , Wattles (Plants) -- South Africa , Soil erosion -- South Africa -- Eastern Cape , Conservation of natural resources -- South Africa , Biological invasions -- South Africa -- Eastern Cape , Alien plants -- South Africa -- Eastern Cape , Invasive plants -- South Africa -- Eastern Cape , Biogeography -- South Africa -- Eastern Cape , Soil management -- South Africa -- Eastern Cape , Soil moisture -- South Africa -- Eastern Cape , Soils -- Sodium content -- South Africa -- Eastern Cape
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4839 , http://hdl.handle.net/10962/d1005515 , Acacia mearnsii -- South Africa , Wattles (Plants) -- South Africa , Soil erosion -- South Africa -- Eastern Cape , Conservation of natural resources -- South Africa , Biological invasions -- South Africa -- Eastern Cape , Alien plants -- South Africa -- Eastern Cape , Invasive plants -- South Africa -- Eastern Cape , Biogeography -- South Africa -- Eastern Cape , Soil management -- South Africa -- Eastern Cape , Soil moisture -- South Africa -- Eastern Cape , Soils -- Sodium content -- South Africa -- Eastern Cape
- Description: The invasion of Acacia mearnsii in the Kouga catchment, Eastern Cape, South Africa, has various negative impacts on the ecosystem. These impacts include: reduced species richness, increased water use, increased nutrients and increased N cycling rates. The native shrubby fynbos vegetation has adapted to the acidic nutrient poor soils and Mediterranean climate of the Kouga Mountains. Fynbos, however, is currently being out competed by the much taller Acacia mearnsii trees, due to their competitive nature and ability to fix nitrogen, thereby enriching the soil. The invaded sections of the valley bottoms and lower hill slopes are characterised by an almost complete monoculture of Acacia mearnsii, with very few fynbos species still present. The Department of Water and Environmental Affairs sponsored Working for Water programme started clearing Acacia mearnsii in 1996 in the Kouga Mountains. Cleared sites have remained bare for long periods, indicating that soil properties are not favourable for indigenous propagule re-establishment. The aim of this research was to assess how A. mearnsii invasion and clearing affect fynbos recovery through its impact on soils. This was done by characterising vegetation and soil properties on fynbos, infested and cleared slopes. Vegetation cover for various growth forms was determined and a species list was compiled for each plot. The slope angle, surface hardness, litter cover, bare ground cover and soil depth were measured in the field, whereas water repellency, particle size and the chemical composition were measured in the laboratory. Furthermore, the plant establishment capacity of soils from fynbos, infested and cleared slopes was calculated. This was done by germinating fynbos seeds and growing fynbos plants in soils from the various slopes. The effect that invasion and clearing has on soil erosion was quantified using erosion plots on fynbos, infested and cleared slopes. The invasion and clearing of Acacia mearnsii led to an increase in soil nutrients, especially nitrogen, phosphorus, potassium, carbon and manganese. Furthermore, soils became more acidic, with increased water repellency and reduced surface hardness. The vegetation changed to a tree-dominated structure, replacing the native species. Native plant germination was relatively unaffected by invasion and clearing, with an increase in germination just after clearing. Plant growth of a native grass, Themeda triandra, and herb, Helichrysum umbraculigerum, has increased on soils from cleared slopes. This study showed that soil movement increased on slopes which are invaded and cleared of Acacia mearnsii, with erosion rates doubling on invaded slopes
- Full Text:
- Date Issued: 2010
- Authors: Van der Waal, Benjamin Wentsel
- Date: 2010
- Subjects: Acacia mearnsii -- South Africa , Wattles (Plants) -- South Africa , Soil erosion -- South Africa -- Eastern Cape , Conservation of natural resources -- South Africa , Biological invasions -- South Africa -- Eastern Cape , Alien plants -- South Africa -- Eastern Cape , Invasive plants -- South Africa -- Eastern Cape , Biogeography -- South Africa -- Eastern Cape , Soil management -- South Africa -- Eastern Cape , Soil moisture -- South Africa -- Eastern Cape , Soils -- Sodium content -- South Africa -- Eastern Cape
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4839 , http://hdl.handle.net/10962/d1005515 , Acacia mearnsii -- South Africa , Wattles (Plants) -- South Africa , Soil erosion -- South Africa -- Eastern Cape , Conservation of natural resources -- South Africa , Biological invasions -- South Africa -- Eastern Cape , Alien plants -- South Africa -- Eastern Cape , Invasive plants -- South Africa -- Eastern Cape , Biogeography -- South Africa -- Eastern Cape , Soil management -- South Africa -- Eastern Cape , Soil moisture -- South Africa -- Eastern Cape , Soils -- Sodium content -- South Africa -- Eastern Cape
- Description: The invasion of Acacia mearnsii in the Kouga catchment, Eastern Cape, South Africa, has various negative impacts on the ecosystem. These impacts include: reduced species richness, increased water use, increased nutrients and increased N cycling rates. The native shrubby fynbos vegetation has adapted to the acidic nutrient poor soils and Mediterranean climate of the Kouga Mountains. Fynbos, however, is currently being out competed by the much taller Acacia mearnsii trees, due to their competitive nature and ability to fix nitrogen, thereby enriching the soil. The invaded sections of the valley bottoms and lower hill slopes are characterised by an almost complete monoculture of Acacia mearnsii, with very few fynbos species still present. The Department of Water and Environmental Affairs sponsored Working for Water programme started clearing Acacia mearnsii in 1996 in the Kouga Mountains. Cleared sites have remained bare for long periods, indicating that soil properties are not favourable for indigenous propagule re-establishment. The aim of this research was to assess how A. mearnsii invasion and clearing affect fynbos recovery through its impact on soils. This was done by characterising vegetation and soil properties on fynbos, infested and cleared slopes. Vegetation cover for various growth forms was determined and a species list was compiled for each plot. The slope angle, surface hardness, litter cover, bare ground cover and soil depth were measured in the field, whereas water repellency, particle size and the chemical composition were measured in the laboratory. Furthermore, the plant establishment capacity of soils from fynbos, infested and cleared slopes was calculated. This was done by germinating fynbos seeds and growing fynbos plants in soils from the various slopes. The effect that invasion and clearing has on soil erosion was quantified using erosion plots on fynbos, infested and cleared slopes. The invasion and clearing of Acacia mearnsii led to an increase in soil nutrients, especially nitrogen, phosphorus, potassium, carbon and manganese. Furthermore, soils became more acidic, with increased water repellency and reduced surface hardness. The vegetation changed to a tree-dominated structure, replacing the native species. Native plant germination was relatively unaffected by invasion and clearing, with an increase in germination just after clearing. Plant growth of a native grass, Themeda triandra, and herb, Helichrysum umbraculigerum, has increased on soils from cleared slopes. This study showed that soil movement increased on slopes which are invaded and cleared of Acacia mearnsii, with erosion rates doubling on invaded slopes
- Full Text:
- Date Issued: 2010
A predictive biogeography of selected alien plant invaders in South Africa
- Authors: Youthed, Jennifer Gay
- Date: 1997
- Subjects: Alien plants -- South Africa , Biogeography -- South Africa , Acacia -- South Africa , Acacia mearnsii -- South Africa , Opuntia ficus-indica -- South Africa , Solanum -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4846 , http://hdl.handle.net/10962/d1005522 , Alien plants -- South Africa , Biogeography -- South Africa , Acacia -- South Africa , Acacia mearnsii -- South Africa , Opuntia ficus-indica -- South Africa , Solanum -- South Africa
- Description: Five techniques were used to predict the potential biogeography of the four alien plant species, Acacia longifolia, Acacia mearnsii, Opuntia ficus-indica and Solanum sisymbrifolium. Prediction was based on five environmental factors, median annual rainfall, co-efficient of variation for rainfall, mean monthly maximum temperature for January, mean monthly minimum temperature for July and elevation. A geographical information system was used to manage the data and produce the predictive maps. The models were constructed with presence and absence data and then validated by means of an independent data set and chisquared tests. Of the five models used, three (the range, principal components analysis and discriminant function analysis) were linear while the other two (artificial neural networks and fuzzy logic) were non-linear. The two non-linear techniques were chosen as a plant's response to its environment is commonly assumed to be non-linear. However, these two techniques did not offer significant advantages over the linear methods. The principal components analysis was particularly useful in ascertaining the variables that were important in determining the distribution of each species. Artifacts on the predictive maps were also proved useful for this purpose. The techniques that produced the most statistically accurate validation results were the artificial neural networks (77% correct median prediction rate) and the discriminant function analysis (71% correct median prediction rate) while the techniques that performed the worst were the range and the fuzzy classification. The artificial neural network, discriminant function analysis and principal component analysis techniques all show great potential as predictive distribution models.
- Full Text:
- Date Issued: 1997
- Authors: Youthed, Jennifer Gay
- Date: 1997
- Subjects: Alien plants -- South Africa , Biogeography -- South Africa , Acacia -- South Africa , Acacia mearnsii -- South Africa , Opuntia ficus-indica -- South Africa , Solanum -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4846 , http://hdl.handle.net/10962/d1005522 , Alien plants -- South Africa , Biogeography -- South Africa , Acacia -- South Africa , Acacia mearnsii -- South Africa , Opuntia ficus-indica -- South Africa , Solanum -- South Africa
- Description: Five techniques were used to predict the potential biogeography of the four alien plant species, Acacia longifolia, Acacia mearnsii, Opuntia ficus-indica and Solanum sisymbrifolium. Prediction was based on five environmental factors, median annual rainfall, co-efficient of variation for rainfall, mean monthly maximum temperature for January, mean monthly minimum temperature for July and elevation. A geographical information system was used to manage the data and produce the predictive maps. The models were constructed with presence and absence data and then validated by means of an independent data set and chisquared tests. Of the five models used, three (the range, principal components analysis and discriminant function analysis) were linear while the other two (artificial neural networks and fuzzy logic) were non-linear. The two non-linear techniques were chosen as a plant's response to its environment is commonly assumed to be non-linear. However, these two techniques did not offer significant advantages over the linear methods. The principal components analysis was particularly useful in ascertaining the variables that were important in determining the distribution of each species. Artifacts on the predictive maps were also proved useful for this purpose. The techniques that produced the most statistically accurate validation results were the artificial neural networks (77% correct median prediction rate) and the discriminant function analysis (71% correct median prediction rate) while the techniques that performed the worst were the range and the fuzzy classification. The artificial neural network, discriminant function analysis and principal component analysis techniques all show great potential as predictive distribution models.
- Full Text:
- Date Issued: 1997
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