Alemseged, Yohannes

Hacker, Ronald B.

Murray, W. K.

Thompson, T. J.

Timmers, P. K.

English

University of Kentucky

University of Kentucky UKnowledge International Grassland Congress Proceedings 21st International Grassland Congress / 8th International Rangeland Congress Precision Pastoralism‐Advanced Systems for Management and Integration of Livestock and Forage Resources in the Semi‐Arid Rangelands in South Eastern Australia Ronald B. Hacker Department of Primary Industry, Australia T. J. Thompson AfterhoursAg, Australia W. K. Murray Department of Primary Industry, Australia Yohannes Alemseged Department of Primary Industry, Australia P. K. Timmers Department of Natural Resources & Water, Australia Follow this and additional works at: https://uknowledge.uky.edu/igc  Part of the Plant Sciences Commons, and the Soil Science Commons This document is available at https://uknowledge.uky.edu/igc/21/3-1/3 The 21st International Grassland Congress / 8th International Rangeland Congress took place in Hohhot, China from June 29 through July 5, 2008. Proceedings edited by Organizing Committee of 2008 IGC/IRC Conference Published by Guangdong People's Publishing House This Event is brought to you for free and open access by the Plant and Soil Sciences at UKnowledge. It has been accepted for inclusion in International Grassland Congress Proceedings by an authorized administrator of UKnowledge. For more information, please contact UKnowledge@lsv.uky.edu. 瞯 ]428　 瞯 　 Multifunctional Grasslands in a Changing World 　 Volume Ⅰ 　Grasslands/Rangelands Resources and Ecology ——— Soil‐Plant‐Animal InterrelationshipsPrecision pastoralism‐advanced systems for management and integration of livestock and forageresources in the semi‐arid rangelands in south eastern AustraliaR . B . H acker1 , 2 , T .J . Thompson3 , W .K Murray 1 . Y . A lemseged1 and P .K T immers 41 NSW Department o f Primary Industries , PMB 19 , T rangie , NSW A ustralia 28232 Corresponding author E‐mail ron .hacker＠ dp i .nsw .gov .au3 A f terhours A g , Bourke , NSW , 28404 Queensland Department o f Natural Resources & W ater , 80 Meiers Rd Indooroop illy , Q�ld 4068Key points : Precision pastoralism involves the application of new technology to manage animals according to individualrequirements and to assist the management of rangeland resources by matching forage supply with forage demand .Individual animal management is achieved through the capacity to identify and weigh individual animals as they enter a wateringenclosure , telemeter the data to a remote computer , and remotely activate drafting gates based on analysis of a quality assureddata set . Alternatively , any other individual attribute ( e .g . reproductive status) may be used as basis for remote drafting .Improved management of forage resources is achieved through a capacity to provide probabilistic estimates of future sustainablestocking rates , and ground cover under the current stocking rate , by forward projection of pasture grow th from currentconditions . Projections are derived from a pasture grow th model parameterised for individual vegetation types within a specificproperty , and applied at the paddock level . Decisions to increase or decrease stocking rate can then be considered in an objectiverisk management context .Key words : stocking , risk , ground cover , liveweightIntroduction Extensive pastoral production systems in Australia have traditionally managed animals , at best , according tooverall flock or herd requirements . Attempts to match forage demand with forage availability have of ten been restricted tostocking rate adjustments only at times of major animal husbandry events ( e .g . shearing ) although more frequent tacticaladjustments have become more common in recent years . Attempts to objectively forecast livestock productivity in relation toforage and animal factors have been virtually non‐existent in the pastoral context .However , technologies are now available to facilitate the management of individual animals , or animal groups , according totheir specific requirements , and to address more effectively the central issue of matching forage supply and demand to achieveboth optimum animal production and sustainable resource use . Objective forecasting of expected animal production is feasiblethough less well developed . Collectively , these technologies constitute �precision pastoralism�. Its application will providelivestock producers with opportunities to improve profitability and enhance sustainability not previously feasible in extensivemanagement systems .Components of precision pastoralismIndividual animal management Precision management of livestock requires a capacity to uniquely identify individual animals ,monitor their performance and apply husbandry measures accordingly . Some aspects of this approach have been available forsome time e .g . pregnancy diagnosis , with individual females assigned to groups managed according to their pregnancy status .However , such applications require physical separation of groups . The capacity is now available to electronically record theweight of individually identified animals , telemeter this information to a remote office and activate automatic drafting gates onthe basis of specified criteria . This allows the timely application of husbandry practices to individual animals without the needfor on‐going physical separation . Husbandry practices can also be changed as required on the basis of monitored performance .Physically , this system involves :瞯 Access facilities at watering points (�spear gates�and a race) that force animals to enter the watering enclosure in singlefile , while passing over a weighing platform ; design of the system ensures that animals cannot be excluded from water ;瞯 RFID ( Radio Frequency Identification) tags applied to each animal ;瞯 A tag reader installed in the race in parallel with the weighing platform ;瞯 A scales indicator / computer that accepts input from both the tag reader and the weighing platform ;瞯 A connection or other wireless data transfer system that allows downloading of tag number‐weight pairs to a remote officecomputer ;瞯 Software that �cleans up�the data stream by eliminating spurious data points and calculates an average weight for eachanimal from the remaining set of �accepted�weights ( Richards et al . ２００６)瞯 An automatic drafting race that can be remotely programmed , via the indicator , to draf t animals according to tag numberonce performance data has been analysed and management requirements identified .This �walk‐over‐weighing�system is now operated by one of the authors ( TJT ) in an extensive grazing operation near Bourke ,　 Multifunctional Grasslands in a Changing World 　 Volume Ⅰ 　 瞯 ]429　 瞯Grasslands/Rangelands Resources and Ecology ——— Soil‐Plant‐Animal InterrelationshipsNSW , to manage an opportunistic livestock trading and fattening enterprise ( Figure １ ) . The system is portable and theintention is to use it , or its component parts , as required throughout the property . Remote weighing and drafting is usedprimarily to allocate specified animals to supplementary feed based on their monitored weight gain , and to identity those thathave reached a marketable weight . Other applications for the systems include :瞯 monitoring stock remotely to minimise need for physical checking , particularly when used in conjunction with water levelsensors at artificial watering points ;瞯 monitoring animal performance in relation to individual animal thresholds or targets such as joining weights or marketcontract specifications ;瞯 drafting of animals on the basis of other individualistic information ( e .g . reproductive status , age or classer assessment) ;瞯 drafting out animals without tags ( e .g . ferals) .Future applications could include :瞯 individual application of preventative veterinary treatments ;瞯 �mothering up�of ewes and lambs , if this is important in breeding programs , based on the observation that lambs tend tofollow ewes over the weighing platform and tag sequences can therefore be related to pedigree ( Richards and Atkins , ２００７) .Figure1 Remote weighing and automatic dra f ting f acility show ing thecurved race which encourages animals to pass slow ly over the weighingp lat f orm while entering a w atering enclosure , tag reader ( located inthe race) and draf ting gates .Precision pasture management Matching forage supply and demand through tactical adjustment of stock density is a fundamentalchallenge for all grazing systems . Spatial modelling of pasture grow th offers a new tool to address this issue in the context of�precision pastoralism�. Calibration of pasture grow th models for individual vegetation types within pastoral properties ,combined with mapping of theses units at paddock scale allows probabilistic forecasts of future pasture grow th on a paddockbasis to be generated from historical climate data . Several generic calibrations of the pasture grow th model GRASP ( Littleboyand McKeon １９９７) are available for western NSW ( Richards et al . ２００１) and can be relatively easily refined for more specificvegetation types by rapid assessment techniques to determine soil water holding capacity in the appropriate depth incrementsand tree basal area , a key driver of ground storey biomass production , for mapped vegetation types ( Alemseged et al . ２００６) .We have used this rapid calibration approach to develop a prototype version of the package PaddockGRASP for two extensiveproperties in western NSW . Once supplied with an updated file of daily climate date in the appropriate format from the SILOdata base ( http :/ / www .nrw .qld .gov .au/ silo / ppd/ index .html) , and initialised for current standing biomass levels based onfield observations , the model provides :瞯 pasture grow th estimates , for paddocks and vegetation types within paddocks , for the next ３‐１２ months at the ２０th ,５０th and８０th percentile levels ;Preliminary input screens allow specification of unique characteristics for vegetation types within individual paddocks such as the瞯 ]430　 瞯 　 Multifunctional Grasslands in a Changing World 　 Volume Ⅰ 　Grasslands/Rangelands Resources and Ecology ——— Soil‐Plant‐Animal Interrelationshipsallowable utilisation percentage , proportion of biomass produced that is palatable ( a surrogate for range condition ) andproportion accessible to grazing . Stocking history for each paddock is also entered . While alternative probability levels could bechosen , the output of ２０th , ５０th and ８０th values is considered to provide a reasonable representation of pasture grow th andground cover expectations for poor , reasonable and good seasonal conditions respectively .Given the general acceptance of ４０％ ground cover as the minimum desirable in the semi‐arid rangelands of western NSW ( e .g .Campbell and Hacker , ２０００ ; Western Catchment Management Authority , ２００５ ) these data allow the natural resourceimplications of the current stocking regime to be appreciated in a risk management framework and the same perspective to bebrought to tactical decisions regarding sale , purchase or agistment of stock .The rapid calibration approach outlined above is thought to capture most of the unique characteristics of particular vegetationtypes ( Hacker et al . ２００７ ) . However , further refinement may be justified but will require a period of least １２ months fieldobservation of standing biomass , using rapid assessment techniques , for validation and finer parameterisation using the�GRASP Calibrator�( G . McKeon , pers . comm .) .While seasonal risk assessments for pasture grow th can be based simply on the historical record , analogue years could also beused for outlook periods when seasonal climate indicators such as the SOI Phase ( Stone , １９９６) are known to have useful skill .In western NSW this indicator has useful skill in estimating the probability of exceeding median pasture grow th for three‐monthperiods beginning June‐September inclusive ( Hacker et . al . , ２００６) .Forecasting of animal performance Estimation of animal performance based on pasture production estimates from the GRASPmodel have to date been successful only at the level of annual liveweight change ( Hall １９９６ ) . Calibration of the model toestimate live weight change over shorter period should be feasible given the capacity now available to obtain frequent liveweightsof individual animals . The objective is to produce probabilistic estimates of liveweight change to complement the correspondingestimates of forage grow th , sustainable stock densities and ground cover .Implementation and adoption The�walk‐over‐weighing�system is now operational based on off‐the‐shelf components for animalidentification , weighing and telemetry . Sof tware to clean up the data stream has been developed by NSW Department ofPrimary Industries and is currently in the process of commercialisation .Without considerable further development , or extensive support , it is unlikely that the PaddockGRASP software could be madeavailable to individual producers . The best means of achieving the widespread adoption of this technology will be bydevelopment of web‐based access for registered subscribers who would be able to contract the mapping of their properties tocommercial companies and who would either draw on an existing library of vegetation type parameter sets , or would againcontract the rapid parameterisation of their specific vegetation types to similar companies . Support for the extraction of climatefiles and maintenance of the software could then be cost‐effectively localised in organisation .Acknowledgements Development of �walk‐over‐weighing�has been supported by the Sheep Industry CRC and a NaturalResource Innovation Grant through the National Landcare program to TJT . Development of the PaddockGRASP was supportedby Land & Water Australia and Australian Wool Innovation Limited through the Managing Climate Variability and Land Waterand Wool Programs .ReferencesAlemseged , Y . , Hacker , R B . , Timmers , P .K . and Smith , W .J . , ２００６ . Estimation of paddock‐level pasture productionusing PaddockGRASP in western New South Wales . Poster presented to １４th Biennial Conference , Australian RangelandSociety , Renmark .Campbell , T . and Hacker , R . , ２０００ . The Glove Box Guide to Tactical Grazing Management for the Semi‐Arid Woodlands .ISBN ０ ７３４７ １１９５ ６ . NSW Agriculture . ６９pp .Hacker R . B . , Alemseged , Y . , Carberry , P .M . , Browne , R .H . and Smith , W .J . , ２００６ . Betting on Rain . Managingseasonal risk in western NSW . NSW Department of Primary Industries . ISBN ０ ７３４７ １７２７ X . ９３pp .Hacker , R . , Leys , J . , Alemseged , Y . , Heidenreich , S . and Timmers , P . , ２００７ . Climate science for better natural resourcemanagement in western New South Wales . Final Report , Land & Water Australia Project DAN １９ . NSW Department ofPrimary Industries .Hall , W .B . , １９９６ . Near‐real time financial assessment of the Queensland wool industry on a regional basis . Ph D thesis ,University of Queensland .Littleboy , M . and McKeon , G .M . , １９９７ . Subroutine GRASP : Grass production model , Documentation of the Marcoolaversion of Subroutine GRASP . In : Evaluating the risks o f p asture and land degradation in native pasture in Queensland .Final Report for Rural Industries Research and Development Corporation , Project DAQ１２４A . Queensland Department ofPrimary Industries : Brisbane .Richards , J .S . and Atkins , K .D . ,２００７ . Determining pedigree by association in Merino flocks . Proceedings of the Associationfor Advancement of Animal Breeding and Genetics １７ :４０３‐０６ .　 Multifunctional Grasslands in a Changing World 　 Volume Ⅰ 　 瞯 ]431　 瞯Grasslands/Rangelands Resources and Ecology ——— Soil‐Plant‐Animal InterrelationshipsRichards , J .S . , Atkins , K .D . , Thompson , T . and Murray , W .K . , ２００６ . Data from walk‐over weighing‐where are we at ?Australian Society of Animal Production ２６th Biennial Conference . Short Communication Number ３２ .Richards , R . , Watson , I . , Bean , J . , Maconochie , J . , Clipperton , S . , Beeston , G . , Green , D . and Hacker R . , ２００１ .Australian Grassland and Rangeland Assessment by Spatial Simulation ( A ussie GRA SS ) . Southern Pastures Sub‐project .QNR９ . Final Report for the Climate Variability in Agriculture Program . Department of Natural resources and Mines ,Queensland .Stone R . C . , Hammer G .L . , and Marcussen T . , １９９６ . Prediction of global rainfall probabilities using phases of the SouthernOscillation Index . Nature ３８４ :２５２‐５５ .Western Catchment Management Authority , ２００５ . Summary‐Draft Catchment Plan . September ２００５ .

Precision Pastoralism‐Advanced Systems for Management and Integration of Livestock and Forage Resources in the Semi‐Arid Rangelands in South Eastern Australia

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Precision Pastoralism‐Advanced Systems for Management and Integration of Livestock and Forage Resources in the Semi‐Arid Rangelands in South Eastern Australia

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