research article a comparison of three dry matter forage...

Research ArticleA Comparison of Three Dry Matter Forage Production MethodsUsed in South Africa

A J Joubert and W J Myburgh

Department of Nature Conservation Tshwane University of Technology Private Bag X680 Pretoria 0001 South Africa

Correspondence should be addressed to W J Myburgh myburghwjtutacza

Received 22 November 2013 Accepted 11 April 2014 Published 27 April 2014

Academic Editor Daniel I Rubenstein

Copyright copy 2014 A J Joubert and W J Myburgh This is an open access article distributed under the Creative CommonsAttribution License which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

A common method for determining forage production of rangelands is by clipping and weighing forage from quadrats withpredetermined areas This technique is however time consuming Other techniques which require less time and labour includeamongst others using the disk pasture meter or phytomass derived from the vegetation classification program PHYTOTAB inconjunction with the Plant Number Scale which is used to determine vegetation canopy cover The phytomass determined usingPHYTOTABPlant Number Scale and the disk pasturemeter was compared to the phytomass obtained from the actual clipping andweighing of forage Tests showed that there were indeed statistically significant differences between the mean phytomass values ofthe three techniques Considerable variation was shown in the results of the disk pasture meter readings compared to the other twotechniques The phytomass values obtained using the disk pasture meter were significantly higher than the phytomass determinedusing both the PHYTOTABPlant Number Scale and the clipping and weighing techniques Results further indicated a significantsimilarity in the phytomass determined using the PHYTOTABPlant Number Scale and the clipping and weighing technique Theresults of this pilot study need further investigation

1 Introduction

The ability to accurately measure aboveground phytomass ofthe grass layer is important in calculating forage availabilityfor grazing and animal stocking rates and it influences theeffectiveness of fire when used as a management tool toremove moribund material According to Harmoney et al[1] and Sharrow [2] clipped pasture samples are the mostaccurate and commonly used method for determining phy-tomass Clipping is laborious and destroys a portion ofthe sward sampled Much effort has been devoted to thedevelopment of rapidly measured nondestructive parame-ters from which phytomass may be predicted without thenecessity of clipping plots Both pasture height [3] and foragebulk [4 5] have been employed successfully as predictorsof pasture phytomass Forage bulk refers to the volume offorage compressed beneath a plate of known weight [3] Therelationship between forage bulk and pasture phytomass yieldgenerally has been strong with correlation coefficients greaterthan 090 often being reported [4ndash9] Because forage bulk is ameasure of ldquocompressed volumerdquo of forage it integrates both

sward height and density into a single three-dimensionalquantity This is believed to explain its value as a predictorof phytomass yield [4 6]

Less tedious methods that do not require clipping wouldallow managers to take phytomass readings more frequentlyThis can be particularly useful when for example theobjective is to determine the amount of forage consumed bylivestock and game species within certain seasons Accuracyof results can also be increased when more samples aretakenThe use of the disc pasture meter (DPM) to determineforage phytomass was developed by Bransby and Tainton [3]and integrates sward height and density into one measureoften called bulk height or bulk density [4] The mostpractical and efficient method for estimating grass fuel loadsis with the DPM and can be applied and used in numerousvegetation types [10] The technique involves relating thesettling height of an aluminum disc dropped onto the grasssward to the standing crop of grass holding up the discexpressed in kilograms per hectare This technique can beproblematic as estimations may be affected by rocks ratherthan grasses holding up the base plate [11] There is a simple

Hindawi Publishing CorporationInternational Journal of EcologyVolume 2014 Article ID 314939 6 pageshttpdxdoiorg1011552014314939

2 International Journal of Ecology

relationship between the settling height and the standingcrop of grass provided that the disc pasture meter has beensuccessfully calibrated Successful universal calibrations havebeen achieved for much of the grasslands and savannas inSouthern Africa [10] Research and field experience indicatethat the calibration developed in the Kruger National Park[12] can be used as a general calibration for estimating grassfuel loads for management purposes in these regions ofSouthern Africa [13]

The DPM relies on calibrations performed on pure orevenly distributed plant compositions to determine foragephytomass Commercially availablemeters comewith factorycalibrations however the accuracy and precision of theseequations have not been evaluated for SouthernAfrica range-land conditionsMany studies of double-sampling techniqueshave shown that these techniques require frequent calibrationand that universal equations for estimating pasture massmay be unreliable [14] Previous studies have indicated thatuniversal prediction equations were not useful because ofvariations in rangeland management and climate [14] Thelevel of error in measuring forage mass varies widely E BRayburn and S B Rayburn [15] and Unruh and Fick [16]however working in rangelands of Northeast USA obtainedcalibration errors with plate meters of about 10 of pastureyields They concluded that this level of error is acceptablefor farm use

The Plant Number Scale (PNS) was developed byWestfalland Panagos [17] as an improved method of cover esti-mation using variable-sized belt transects This techniqueis used to determine the canopy cover of all plant speciesrecorded using a quadrat or area-based survey techniqueThe quadrat size used in this study was 100m2 Individualsof each species recorded were counted using variable-sizedtransects The variability of the transect size (length andwidth) was dependent on the average canopy size and averagespacing between canopies of the same species The recordedvegetation data are loaded onto a computer and are classifiedinto plant communities using the PHYTOTAB computerprogram developed by Westfall [18] PHYTOTAB using thecanopy cover of each grass species recorded derives bothan estimated phytomass (kgha) for each individual grassspecies and an estimated grass biomass (kgha) for each plantcommunity This method has proved to provide accurateresults for estimations of canopy cover and phytomass if fieldsampling is accurate and precise [19]

Disadvantages of the PNS include reduced precisionbecause of the classes used for crown diameters as well assometimes insufficient variation being included within tran-sects especially short transects [20] A further disadvantageis the difficulty in determining mean crown to crown gap forplants with varied spacing Spacing can vary considerably forplants with a given cover and density in terms of individualsper hectare [20] Advantages of the PNS method includebeing originally developed in South African savannas withless observer bias than many other vegetation assessmenttechniques [21 22] The provision of species-specific phy-tomass density spacing and canopy cover estimates via theuse of PHYTOTAB [23 24] is an added advantage

The main objective of this pilot study was to test andcompare the grass phytomass derived using the PlantNumberScale with figures obtained using the disk pasture Theclipped and weighed phytomass served as a benchmark forcomparison with the phytomass figures obtained using theother two techniques

2 Study Area

The study area is situated in the Dinokeng Nature Reservewithin the boundaries of the Kwalata Game Ranch (KGR)located 20 km north of Pretoria in the Gauteng ProvinceSouth Africa between the southern latitudes 28∘ 201015840 and28∘ 211015840 and the eastern longitudes 25∘ 231015840 and 25∘ 241015840 Thealtitude of KGR ranges between 1140 and 1120m above sealevel The KGR consists of 2500 ha of natural vegetationin a low undulating landscape dominated by sandy plainswith vegetation varying from open savanna riverine tograssland [25]The tree canopy cover of the study area rangesfrom 11 to 20 and is dominated by woody species ofCombretum Acacia Ziziphus and Euclea found on flats andlower slopes primarily on eutrophic sands The herbaceouslayer is dominated by grasses with relatively low basal coveroccurring on sandy soils [26]

The study area is situated in the summer rainfall regionwith very dry winters Three seasonal distinctions can bemade within the area namely a cool dry season fromMay tomid-August a hot dry season from mid-August to Octoberand a hot wet season from November to April [25] KGR hasa mean annual rainfall of 500ndash700mm occurring mainly insummer and mean maximum and minimum temperaturesof 35∘C and minus31∘C for November and June respectively TheKGR consists of two major veld types [26] namely MixedBushveld (veld type 18) and Sourish Mixed Bushveld (veldtype 19) The same vegetation was more recently describedby Mucina and Rutherford [25] as Central Sandy Bushveld(SVcb12) and Loskop Mountain Bushveld (SVcb 13) Thesurvey sites of the study were however restricted to theCentral Sandy Bushveld

The geology of the KGR consists of the layered Bushveldigneous complex (Lebowa) dominated by mafic and ultra-mafic rocks intruding into the Transvaal Sequence [25] TheKGR falls within the southern parts of the Mixed Bushveldvegetation unit and has an underlining geology consisting ofgranite of the Lebowa Granite Suite and some granophyreof the Rashoop Granophyre Suite The most importantsedimentary rocks of the Waterberg Group are sandstoneconglomerate and siltstone of the Alma Formation and alsosandstone siltstone and shale of the Vaalwater Formation[25] The soils of the KGR are from either the Hutton orClovelly soil forms that are well drained and deep often withcatenary sequence from Hutton at the top to Clovelly onthe lower slopes Soils with minimal development also occurusually very shallow on hard or weathering rock Lime is veryrare or absent in the landscape [25]

3 Methods

Three survey sites of no specific dimensions were subjectivelyselected within the Central Sandy Bushveld portion of the

International Journal of Ecology 3

Samplesite

Samplesite

Samplesite

10m

10m10m

Survey sites 1 to 3

Figure 1 Placement of the sample sites at each of the three surveysites located within the Central Sandy Bushveld on Kwalata GameRanch

KGR in areas with limited or no woody cover At each surveysite three sample sites (quadrats) of 100m2 were placed outtenmeters from the survey site center using compass bearingsthus providing a total of nine sample sites surveyed (Figure 1)A photographic record was taken at each sample site forreference purposes and the coordinates of all nine samplesites were recorded using a global positioning system (GPS)

All three techniques were used for recording data at thenine sample sitesTheDPMwas calibrated for each individualsurvey site before any readings were recorded The DPMconsists of a long central aluminium rod an aluminiumsleeve which slides freely on the central rod and a discplate with a diameter of 362mm (0166m2) attached to itThe central rod is marked at 10mm intervals in an upwarddirection starting at the top end of the sleeve when the undersurface of the disc is flush with the lower end of the rod [4]The combined weight of both the aluminium sleeve and discplate is 15 kg which is dropped onto the grass underneaththe disc to obtain forage bulk readings The central rod ofthe DPM is placed perpendicular to the ground surfacewhile the sleeve with the attached disc is held over the grasssward and dropped from a standard height of 600mm abovethe ground After the settling height has been recorded thegrass underneath the disc is clipped as close to the groundsurface as possible Each individual clipping was collectedandmarkedThe grass clippings were sundried for a period ofthree weeks After the clippings had been dried and weighedtheywere used to calibrate theDPMby relating the discmetersettling height (cm) to the grass phytomass (g) of that specificreading [12] Four DPM readings were recorded within a 5mdistance from the centre of each survey site It was purposelydecided to record only four DPM readings to determinewhether accurate phytomass values can be obtained withlimited data Calibrations for each survey site were calculatedusing the mean of the four readings The calculated value foreach survey site was applied to the corresponding sample siteat that survey site

Three sample sites (quadrats) of 100m2 (10m times 10m)were recorded at each survey site (Figure 1) using the threedifferent techniques The herbaceous plant species wererecorded and canopy cover values determined using the PNSAt the same sample site a total of four DPM readings wererecorded The mean of these four recordings presented the

Disc pasture meter Clipping and weighing

Plant Number Scale

Techniques

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Phyt

omas

s (kg

ha)

Mean Mean plusmn SEMean plusmn SD

Figure 2 Mean mean plusmn SE and mean plusmn SD of phytomass for allthree techniques at survey site level

phytomass (kgha) of the sample site Lastly a one-square-meter frame was subjectively laid out within these quadratsand clipped One benchmark clipping was done in everyquadrat These clippings were also sundried for three weeksand weighed afterwards

The one-way analysis of variance (ANOVA) test which isa statistical technique used to compare the means of two ormore samples [27] was used in conjunction with the Tukeytest [28]The Tukey test also referred to as the Tukey-Kramermethod is a single-step multiple comparison procedure andstatistical test comparing all possible pairs ofmeans based ona studentized range distribution [28]

4 Results

The data of the sample sites were analyzed and a total of ninephytomass values (kgha) were calculated for each techniqueat the three survey sites (Table 1)

The one-way ANOVA analysis of variance statistical testwas used to investigate possible differences in results obtainedusing the different techniques The analysis indicated statis-tically significant differences between the mean phytomassvalues of the three samples where n = 9 in each case at 2and 24 df (F = 23767 P lt 005) (Table 2)

Once a significant difference was established (P =0000002) the Tukey test was used to determine which valuesdiffered significantly from one another The results indicateda significant difference in mean phytomass of the clippingand weighing and DPM techniques (P = 0000203) Therewas not however a significant difference between the meanphytomass of the clipping and weighing and PNS techniques(P = 0363271) (Table 3 and Figure 2)


Table 1 Mean phytomass values (kgha) calculated for each sample site at three survey sites using the different techniques

Sample siteDisc pasture meter (DPM) Clipping and weighing Plant Number Scale (PNS)

Survey site1 2 3 1 2 3 1 2 3

1 9 845 3 500 1 8522 7 324 3 250 2 1013 8 677 2 980 1 2584 7 774 2 060 3 9725 8 511 2 560 2 6276 5 361 1 600 3 4807 5 478 3 340 2 6058 6 621 6 980 3 2959 7 134 7 160 3 280Mean phytomass (kgha) 8 615 7 215 6 411 3 243 2 073 5 827 1 737 3 360 3 060

Table 2 Results of the one-way ANOVA statistical test indicating significant differences between the mean phytomass values of the threetechniques

Variable Marked effects are significant at 119875 lt 005000SS effect df effect MS effect SS error df error MS error 119865 119875

Phytomass (kgha) 110160135 2 55080068 55619236 24 2317468 2376735 0000002

Table 3 Statistical analysis of the differences in phytomass (M =mean phytomass) between the three techniques using the Tukey test

Techniques

Marked differences are significant at119875 lt 005000

1 2 3M = 74139 M = 27189 M = 37144

Disc pasture meter 1 0000130 0000203Plant Number Scale 2 0000130 0363271Clipping and weighing 3 0000203 0363271

5 Discussion

The survey sites were subjectively chosen to ensure samplingon evenly distributed plant compositions within the CentralSandy Bushveld [25] Vegetation data obtained using thePlant Number Scale [17] and analyzed using the PHYTOTABcomputer package [18 23] confirmed three distinct plantcommunities within this vegetation type The three surveysites sampled correlated with the three plant communitiesidentified Considerable variation was shown in the results ofthe DPM readings compared to the results of the other twotechniques used The phytomass values for all sample sitesusing the DPM were considerably higher than the valuescalculated using both the PNS and the clipped and weighingtechniques

Although the phytomass obtained using the DPM greatlyexceeded those of the other two techniques further investi-gation is needed before distinctive judgments can be maderegarding the accuracy of the method A study done byBransby and Tainton [3] on the application of the DPM in

grazing management clearly indicates that a specific calibra-tion process must be followed to obtain accurate results Thecalibration process explained involves the sampling of plusmn14individual readings opposed to the four readings done inthis study Bransby and Tainton [3] indicated that regressionrelationships can vary considerably between calibrations andthat these relationships may be influenced by rangeland typeand conditions (time in the season disc mass disc size etc)Grass structure and forage type are factors that should beconsidered when using the DPM Results from this studyshowed that the DPM provided the highest phytomass insurvey site 1 which is dominated by the highly fibrous grassesLoudetia simplex and Diheteropogon amplectens Comparedto the results of the other two techniques it is believed thatthe DPM tends to overestimate phytomass due to varyingsettling heights In the Kruger National Park Zambatis etal [11] noticed that the instrument frequently settles abovethe bulk of the grass leaf mass leading to the suspicionthat the settling height is inflated and nonrepresentativeDuring the application of the DPM the operator needs tocarefully consider the presence of rocks and even the stems ofherbaceous plants other than grasses since this will definitelyinfluence the settling height of the disc

The results of this study showed a significant similarityin the PNSrsquos projected phytomass and the actual clippedphytomass for all three survey sites Although the PNStechnique is somewhat labour intensive the results obtaineddo provide more accurate estimations of pasture phytomassthan the results of the DPM in relation to the benchmark(clipping and weighing) As the study progressed less timewas spent using the PNS technique suggesting that fieldworker experience plays a major role in the labour intensityof the method


6 Conclusion

The results obtained from this pilot study which was con-ducted in natural grassland indicated the importance ofgrass structuregrowth form on disc settling height of theDPM The phytomass figures generated in grasslands otherthan planted pastures should be used with caution due tothe potentially inflated readings Another area of concernneeding more study is that of the universal calibrationmodelsequations used for Southern African grassland andsavanna systems As mentioned calibration models areinfluenced by a number of factors such as variations inrangelands management and climate of an area [3 14] thusmaking calibrations area and vegetation specific Phytomassestimations obtained using the PNS and the PHYTOTABcomputer program package compared favourably with thefigures of the actual clipping andweighing of grassThis couldbe a valuable spin-off from techniques that were primarilydeveloped for phytosociological studies The conclusions arehowever drawn from data recorded at a limited number ofsample sites and it is suggested that the number of sample sitesbe increased in further studies The number of calibrationsfor the DPM and the total number of clippings also need tobe increased at each sample site within the Central SandyBushveld The accuracy of the DPM results depends largelyon the structure of the dominant grass species at a sample sitewithin a specific vegetation type and it is suggested that thestudy be extended to other vegetation types

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] K R Harmoney K J Moore J R George E C Brummerand J R Russell ldquoDetermination of pasture biomass using fourindirect methodsrdquo Agronomy Journal vol 89 no 4 pp 665ndash672 1997

[2] S H Sharrow ldquoA simple disc meter for measurement of pastureheight and forage bulkrdquo Journal of Range Management vol 37pp 94ndash95 1984

[3] D I Bransby and N M Tainton ldquoThe disc pasture meterpossible applications in grazing managementrdquo Proceedings ofthe Grassland Society of SouthernAfrica vol 12 pp 115ndash118 1977

[4] D L Michalk and P K Herbert ldquoAssessment of four techniquesfor estimating yield on dryland pasturesrdquo Agronomy Journalvol 69 pp 864ndash868 1977

[5] T L Powell ldquoEvaluation ofweighted discmeter for pasture yieldestimation in intensively stocked dairy pasturerdquo New ZealandJournal of Experiential Agriculture vol 2 pp 237ndash241 1974

[6] C W Alexander J T Sullfvan and D E McCloud ldquoA methodfor estimating forage yieldsrdquo Agronomy Journal vol 54 pp468ndash469 1962

[7] M E Castle ldquoA simple disc instrument for estimating herbageyieldrdquo Journal of the British Grassland Society vol 31 pp 37ndash401976

[8] R A Santillan W R Ocumpaugh and G O Mott ldquoEstimatingforage yield with a disc meterrdquo Agronomy Journal vol 71 pp71ndash74 1979

[9] J P Shrivastava D A Miller and J A Jackobs ldquoEstimatingalfalfa yieldsrdquo Agronomy Journal vol 61 pp 649ndash651 1969

[10] W S W Trollope and L A Trollope ldquoFire behavior a key factorin the fire ecology of African grasslands and savannas in ForestFire Research and Wild Land Fire Safetyrdquo in Proceedings of IVInternational Congress on Forest Research Rotterdam MillpressD X Viegas Ed pp 1ndash6 2002

[11] N Zambatis P J K Zacharias C D Morris and J F DerryldquoRe-evaluation of the disc pasture meter calibration for theKruger National Park South Africardquo African Journal of Rangeand Forage Science vol 23 no 2 pp 85ndash97 2006

[12] W S W Trollope and A L F Potgieter ldquoEstimating grass fuelloads with a disc pasture meter in the Kruger National ParkrdquoJournal of the Grassland Society of Southern Africa vol 3 pp148ndash152 1986

[13] S I Higgins W J Bond and W S W Trollope ldquoFireresprouting and variability a recipe for grass-tree coexistencein savannardquo Journal of Ecology vol 88 no 2 pp 213ndash229 2000

[14] J Frame ldquoHerbage massrdquo in Sward Measurement HandbookA Davies et al Ed pp 59ndash63 The British Grassland SocietyOkehampton UK 1993

[15] E B Rayburn and S B Rayburn ldquoA standardized platemeter forestimating pasture mass in on-farm research trialsrdquo AgronomyJournal vol 90 no 2 pp 238ndash241 1998

[16] L J Unruh and G W Fick ldquoEquations for a commercial risingplate meter to predict yields of orchard grass and white cloverpasturesrdquo in Agronomy Abstracts p 149 ASA Madison WisUSA 1998

[17] R H Westfall and M D Panagos ldquoThe plant number scale- animproved method of cover estimation using variable-sized belttransectsrdquo Bothalia vol 18 no 2 pp 289ndash291 1988

[18] R H Westfall Objectivity in stratification sampling and clas-sification of vegetation [PhD thesis] Department of BotanyUniversity of Pretoria Pretoria South Africa 1992

[19] J M Van StadenDie fitososiologie van die Steenbokpan omgew-ing in die noordwes-Transvaal [MS thesis] Department ofBotany University of Pretoria Pretoria South Africa 1992

[20] S M Abeare Dry season habitat and patch selection by Africanbuffalo herds test of a new home range estimator [MS thesis]Faculty of Natural and Agricultural Sciences University ofPretoria Pretoria South Africa 2004

[21] J Braun-Blanquet Pflanzensoziologie 1 Aufl Springer WienAustria 1928

[22] J Braun-Blanquet Pflanzensoziologie-Grundzuge der Vegeta-tionskunde 2 Aufl Springer Wien Austria 1951

[23] R H Westfall G K Theron and N Rooyen ldquoObjectiveclassification and analysis of vegetation datardquo Plant Ecology vol132 no 2 pp 137ndash154 1997

[24] R H Westfall and A Greeff ldquoA national grid of vegetationmonitoring sitesrdquo South African Journal of Science vol 94 no4 pp 150ndash151 1998

[25] L Mucina and M C Rutherford The vegetation of SouthAfrica Lesotho and Swaziland vol 19 of Strelitzia SouthAfricanNational Biodiversity Institute 2006

[26] J P H Acocks ldquoVeld types of South Africardquo Memoirs of theBotanical Survey of South Africa vol 57 pp 1ndash146 1998


[27] D S Moore G P McCabe and B Craig Introduction to thePractice of Statistics W H Freeman amp Co 4th edition 2003

[28] R Lowry One Way ANOVAmdashIndependent Samples VassarEducation 2008

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relationship between the settling height and the standingcrop of grass provided that the disc pasture meter has beensuccessfully calibrated Successful universal calibrations havebeen achieved for much of the grasslands and savannas inSouthern Africa [10] Research and field experience indicatethat the calibration developed in the Kruger National Park[12] can be used as a general calibration for estimating grassfuel loads for management purposes in these regions ofSouthern Africa [13]

The DPM relies on calibrations performed on pure orevenly distributed plant compositions to determine foragephytomass Commercially availablemeters comewith factorycalibrations however the accuracy and precision of theseequations have not been evaluated for SouthernAfrica range-land conditionsMany studies of double-sampling techniqueshave shown that these techniques require frequent calibrationand that universal equations for estimating pasture massmay be unreliable [14] Previous studies have indicated thatuniversal prediction equations were not useful because ofvariations in rangeland management and climate [14] Thelevel of error in measuring forage mass varies widely E BRayburn and S B Rayburn [15] and Unruh and Fick [16]however working in rangelands of Northeast USA obtainedcalibration errors with plate meters of about 10 of pastureyields They concluded that this level of error is acceptablefor farm use

The Plant Number Scale (PNS) was developed byWestfalland Panagos [17] as an improved method of cover esti-mation using variable-sized belt transects This techniqueis used to determine the canopy cover of all plant speciesrecorded using a quadrat or area-based survey techniqueThe quadrat size used in this study was 100m2 Individualsof each species recorded were counted using variable-sizedtransects The variability of the transect size (length andwidth) was dependent on the average canopy size and averagespacing between canopies of the same species The recordedvegetation data are loaded onto a computer and are classifiedinto plant communities using the PHYTOTAB computerprogram developed by Westfall [18] PHYTOTAB using thecanopy cover of each grass species recorded derives bothan estimated phytomass (kgha) for each individual grassspecies and an estimated grass biomass (kgha) for each plantcommunity This method has proved to provide accurateresults for estimations of canopy cover and phytomass if fieldsampling is accurate and precise [19]

Disadvantages of the PNS include reduced precisionbecause of the classes used for crown diameters as well assometimes insufficient variation being included within tran-sects especially short transects [20] A further disadvantageis the difficulty in determining mean crown to crown gap forplants with varied spacing Spacing can vary considerably forplants with a given cover and density in terms of individualsper hectare [20] Advantages of the PNS method includebeing originally developed in South African savannas withless observer bias than many other vegetation assessmenttechniques [21 22] The provision of species-specific phy-tomass density spacing and canopy cover estimates via theuse of PHYTOTAB [23 24] is an added advantage

The main objective of this pilot study was to test andcompare the grass phytomass derived using the PlantNumberScale with figures obtained using the disk pasture Theclipped and weighed phytomass served as a benchmark forcomparison with the phytomass figures obtained using theother two techniques

2 Study Area

The study area is situated in the Dinokeng Nature Reservewithin the boundaries of the Kwalata Game Ranch (KGR)located 20 km north of Pretoria in the Gauteng ProvinceSouth Africa between the southern latitudes 28∘ 201015840 and28∘ 211015840 and the eastern longitudes 25∘ 231015840 and 25∘ 241015840 Thealtitude of KGR ranges between 1140 and 1120m above sealevel The KGR consists of 2500 ha of natural vegetationin a low undulating landscape dominated by sandy plainswith vegetation varying from open savanna riverine tograssland [25]The tree canopy cover of the study area rangesfrom 11 to 20 and is dominated by woody species ofCombretum Acacia Ziziphus and Euclea found on flats andlower slopes primarily on eutrophic sands The herbaceouslayer is dominated by grasses with relatively low basal coveroccurring on sandy soils [26]

The study area is situated in the summer rainfall regionwith very dry winters Three seasonal distinctions can bemade within the area namely a cool dry season fromMay tomid-August a hot dry season from mid-August to Octoberand a hot wet season from November to April [25] KGR hasa mean annual rainfall of 500ndash700mm occurring mainly insummer and mean maximum and minimum temperaturesof 35∘C and minus31∘C for November and June respectively TheKGR consists of two major veld types [26] namely MixedBushveld (veld type 18) and Sourish Mixed Bushveld (veldtype 19) The same vegetation was more recently describedby Mucina and Rutherford [25] as Central Sandy Bushveld(SVcb12) and Loskop Mountain Bushveld (SVcb 13) Thesurvey sites of the study were however restricted to theCentral Sandy Bushveld

The geology of the KGR consists of the layered Bushveldigneous complex (Lebowa) dominated by mafic and ultra-mafic rocks intruding into the Transvaal Sequence [25] TheKGR falls within the southern parts of the Mixed Bushveldvegetation unit and has an underlining geology consisting ofgranite of the Lebowa Granite Suite and some granophyreof the Rashoop Granophyre Suite The most importantsedimentary rocks of the Waterberg Group are sandstoneconglomerate and siltstone of the Alma Formation and alsosandstone siltstone and shale of the Vaalwater Formation[25] The soils of the KGR are from either the Hutton orClovelly soil forms that are well drained and deep often withcatenary sequence from Hutton at the top to Clovelly onthe lower slopes Soils with minimal development also occurusually very shallow on hard or weathering rock Lime is veryrare or absent in the landscape [25]

3 Methods

Three survey sites of no specific dimensions were subjectivelyselected within the Central Sandy Bushveld portion of the


Samplesite

Samplesite

Samplesite

10m

10m10m

Survey sites 1 to 3






Plant Number Scale

Techniques

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Phyt

omas

s (kg

ha)





4 Results







Survey site1 2 3 1 2 3 1 2 3




Phytomass (kgha) 110160135 2 55080068 55619236 24 2317468 2376735 0000002


Techniques


1 2 3M = 74139 M = 27189 M = 37144


5 Discussion






6 Conclusion




References


































Journal of












Volume 2014

Advances in









Geophysics















Samplesite

Samplesite

Samplesite

10m

10m10m

Survey sites 1 to 3






Plant Number Scale

Techniques

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Phyt

omas

s (kg

ha)





4 Results







Survey site1 2 3 1 2 3 1 2 3




Phytomass (kgha) 110160135 2 55080068 55619236 24 2317468 2376735 0000002


Techniques


1 2 3M = 74139 M = 27189 M = 37144


5 Discussion






6 Conclusion




References


































Journal of












Volume 2014

Advances in









Geophysics

















Survey site1 2 3 1 2 3 1 2 3




Phytomass (kgha) 110160135 2 55080068 55619236 24 2317468 2376735 0000002


Techniques


1 2 3M = 74139 M = 27189 M = 37144


5 Discussion






6 Conclusion




References


































Journal of












Volume 2014

Advances in









Geophysics















6 Conclusion




References


































Journal of












Volume 2014

Advances in









Geophysics





















Journal of












Volume 2014

Advances in









Geophysics














research article a comparison of three dry matter forage...

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