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KEY GRASS SPECIES in VEGETATION UNIT Gm 11: Rand Highveld Grassland in MPUMALANGA PROVINCE, SOUTH AFRICA

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KEY GRASS SPECIES in VEGETATION UNIT Gm 11: Rand Highveld Grassland in MPUMALANGA PROVINCE, SOUTH AFRICA IDENTIFICATION OF KEY GRASS SPECIES IN VEGETATION UNIT Gm 11: Rand Highveld Grassland IN MPUMALANGA PROVINCE, SOUTH AFRICA Winston S.W. Trollope & Lynne A. Trollope 22 River Road, Kenton On Sea, 6191, South Africa Cell; 082 200 33373 Email: [email protected] INTRODUCTION Veld condition refers to the condition of the vegetation in relation to some functional characteristic/s (Trollope, et.al., 1990) and in the case of both livestock production and wildlife management based on grassland vegetation, comprises the potential of the grass sward to produce forage for grazers and its resistance to soil erosion as influenced by the basal and aerial cover of the grass sward. The following procedure was used for developing a key grass species technique for assessing veld condition in the vegetation type Gm 11: Rand Highveld Grassland (Mucina & Rutherford, 2006) in Mpumalanga Province – see Figure 1. Rand Highveld Grassland: Gm11 Figure 1: The Rand Highveld Grassland Gm11 vegetation type located in the highveld area east of Pretoria in Mpumalanga Province (Mucina & Rutherford, 2006). The identification of the key grass species is based on the procedure developed by Trollope (1990) viz.. Step 1: Identify and list all the grass species occurring in the study area noting their identification characteristics for use in the field. Step 2: Based on careful observations in the field and consultations with local land users, subjectively classify all the known grass species in the area into Decreaser and Increaser species according to their reaction to a grazing gradient i.e. from high to low grazing intensities, as follows: DECREASER SPECIES: Grass & herbaceous species that decrease when veld is under or over grazed; 2 INCREASER I SPECIES: Grass & herbaceous species that increase when veld is under grazed or selectively grazed; INCREASER II SPECIES: Grass & herbaceous species that increase when veld is over grazed. Step 3: Based on experience, observation and local knowledge subjectively allocate forage and fuel factors on a scale of 0 - 10 according to the potential of the different grass species to produce forage for both domestic and wild ungulate bulk grazers and to produce grass fuel to support a prescribed burn. This procedure is used because it conforms to the concept of veld condition being the condition of the vegetation in relation to some functional characteristic and in this case the potential to produce grass forage for domestic livestock and wild ungulates and grass fuel to support a prescribed burn.. Step 4: Using the information from Step 3, develop a technique for assessing the condition of the grass sward based on the classification of the grass species into Decreaser and Increaser species together with their respective forage and fuel factors. Step 5: Conduct grass surveys over the widest range of grassland, in as many different conditions possible, and with these data identify the key grass species that have the greatest effect on veld condition in terms of their potential to produce forage and grass fuel. The potential for producing forage and grass fuel is calculated for each grass survey by multiplying the respective forage and fuel factors with the percentage relative frequency for each of the herbaceous plant species recorded during the different grass surveys. The sum of these products is expressed as the forage and fuel scores for each sample site. The selection of the key grass species is done using a multiple regression analysis where the forage and fuel scores are the dependent variables and the percentage frequency for each recorded grass or herbaceous species are the independent variable. The precision of the resultant regression model is then tested in a goodness of fit graph illustrating the relationship between actual and predicted forage and fuel scores. The reason for selecting the key grass species in terms of their forage and fuel production potential is because the area in the aforementioned vegetation unit is used for both livestock production and in recent times for wildlife management and it is therefore essential that the key grass species be selected to reflect the grazing potential of the veld and its potential to support prescribed burns in the area. The data used for identifying the key grass species was collected by Mr Francois de Wet from ENVIROPULSE, Middelburg, Mpumalanga Province. RESULTS Ecological Categories and Forage Factors In accordance with Steps 1, 2 and 3 the following set of different grass species were recorded in the project area. These were classified into Decreaser and Increaser I and II species according to their perceived reaction to a grazing gradient from high to low grazing intensities based on personal experience, research and consultations with successful livestock farmers in South Africa over the last three decades. In addition Forage & Fuel Factors on a scale of 0 - 10 were allocated to the different grass species recorded in the project area using the expert system developed by Bosch & Gaugh (1991). A total of 88 different grass species were recorded reflecting the botanical composition of the grass sward over a wide range of veld conditions in the project area – see Table 1. 3 Table 1: The different grass species recorded in the vegetation units in Gm 11: Rand Highveld Grassland and classified into Decreaser and Increaser I and II species together with their respective Forage & Fuel Factors reflecting their forage and fuel production potential for bulk grazers (cattle, buffalo) and for prescribed burning on a scale of 0 – 10. GRASS SPECIES ECOLOGICAL CATEGORY FORAGE FACTOR FUEL FACTOR Andropogon appendiculatus D 8 8 Andropogon chinensis D 4 4 Andropogon schirensis D 4 5 Bewsia biflora D 1 3 Brachiaria brizantha D 5 6 Brachiaria nigropedata D 7 8 Brachiaria serrata D 3 3 Digitaria brazzae D 4 5 Digitaria eriantha D 6 6 Digitaria tricholaenoides D 4 5 Diheteropogon amplectens D 3 3 Eustachys paspaloides D 5 6 Lophacme digitata D 2 3 Monocymbium ceresiiforme D 2 3 Panicum maximum D 8 8 Setaria lindenbergiana D 5 8 Setaria nigrirostris D 7 8 Setaria sphacelata D 6 7 Themeda triandra D 8 8 Alloteropsis semialata I 2 7 Andropogon eucomus I 1 2 Aristida meridionalis I 1 5 Aristida transvaalensis I 1 4 Arundinella nepalensis I 4 6 Ctenium concinnum I 1 5 Cymbopogon caesius I 2 6 Cymbopogon validus I 2 10 Digitaria setifolia I 1 2 Elionurus muticus I 2 7 Enneapogon pretoriensis I 2 6 Eragrostis curvula I 4 9 Eragrostis gummiflua I 2 6 Hyparrhenia anamesa I 4 10 Hyparrhenia dregeana I 3 10 Hyparrhenia filipendula I 4 10 Hyparrhenia hirta I 4 10 Leersia hexandra I 4 6 Loudetia flavida I 3 6 Loudetia simplex I 2 6 4 Melinis nerviglumis I 1 3 Panicum natalense I 4 6 Paspalum notatum I 3 5 Pennisetum sphacelatum I 1 8 Rendlia altera I 1 3 Schizachyrium sanguineum I 1 8 Schizachyrium ursulus I 1 8 Sporobolus centrifugus I 1 3 Sporobolus pectinatus I 1 2 Trachypogon spicatus I 1 6 Triraphis andropogonoides I 2 6 Tristachya biseriata I 1 7 Tristachya leucothrix I 6 7 Tristachya rehmannii I 1 10 Urelytrum agropyroides I 1 9 Aristida adscensionis II 1 2 Aristida congesta subsp. barbicollis II 1 2 Aristida congesta subsp. congesta II 1 2 Aristida diffusa II 1 2 Aristida vestita II 1 4 Chloris gayana II 5 8 Cynodon dactylon II 3 3 Digitaria longiflora II 2 2 Digitaria monodactyla II 1 3 Enneapogon cenchroides II 1 4 Eragrostis capensis II 2 3 Eragrostis chloromelas II 3 4 Eragrostis inamoena II 1 4 Eragrostis lehmanniana II 3 4 Eragrostis nindensis II 2 3 Eragrostis plana II 2 4 Eragrostis pseudosclerantha II 1 4 Eragrostis racemosa II 1 2 Eragrostis rigidior II 2 5 Eragrostis sclerantha II 2 3 Eragrostis viscosa II 2 3 Heteropogon contortus II 5 6 Melinis repens II 1 2 Microchloa caffra II 1 1 Paspalum scrobiculatum II 1 3 Paspalum urvillei II 2 8 Perotis patens II 1 1 Pogonarthria squarrosa II 1 3 Sporobolus africanus II 3 4 Sporobolus festivus II 1 2 Sporobolus ioclados II 1 2 5 Sporobolus stapfianus II 1 2 Tricholaena monachne II 2 3 Trichoneura grandiglumis II 1 2 Bare Ground II 0 0 Identification of Key Grass Species In accordance with Step 5 multiple regression analyses were conducted to identify the Key Grass Species where the Forage & Fuel Scores were the dependent variables and the percentage frequency recorded for the different grass species in the different sample sites were the independent variables. Two multiple regression analyses were conducted using data from the Gm 11: Rand Highveld Grassland vegetation unit to identify the key grass species that had the greatest statistically significant effect on the grass forage and fuel potentials in this vegetation unit. Firstly a multiple regression analysis was conducted involving all the abundantly occurring grass species in the different sample sites as a means of identifying those species that had a statistically significant effect on the Forage and Fuel Scores. Arising from these results the multiple regression analysis was repeated using the aforementioned significant grass species resulting in the identification of the Key Grass Species for the aforementioned vegetation unit. The following Key Grass Species were identified for the vegetation unit Gm 11: Rand Highveld Grassland for predicting the forage potential of the grass sward and their respective statistical parameters and regression coefficients are presented in Table 4. Table 4: The Key Grass Species identified in the vegetation unit Gm 11: Rand Highveld Grassland in Mpumalanga Province for predicting the FORAGE potential of the grass sward together with their
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