Evolution of the GRAZPLAN decision support tools and adoption by the grazing industry in temperate Australia

Donnelly, J. R.; Freer, M.; Salmon, L; Moore, Andrew D.; Simpson, Richard J.; Dove, H.; Bolger, T. P.

doi:10.1016/s0308-521x(02)00024-0

Cited by 77 publications

(38 citation statements)

References 12 publications

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“…Modelling of soil moisture was carried out using the model AusFarm (CSIRO 2007), previously known as Farmwi$e (Moore 2001), which is a component of the GrazPlan suite of decision support tools (Donnelly et al , 2002. AusFarm is a complex, multi-component, biophysical model that utilises the climate, soil moisture, pasture, and livestock sub-models from other GrazPlan decision support tools (Moore 2001).…”

Section: Climate Modellingmentioning

confidence: 99%

Comparing the climate experienced during the Cicerone farmlet experiment against the climatic record

et al. 2013

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Abstract. Farming systems research conducted under dryland conditions is subject to the vagaries of the climate during the experimental period. Whether such an experiment experiences a representative series of climatic years must be examined in relation to the longer term climatic record. The Cicerone Project's farmlet experiment was conducted on the Northern Tablelands of New South Wales, Australia, to investigate the profitability and sustainability of three different management systems: one managed under typical, moderate-input conditions (farmlet B); a second which employed a higher level of pasture inputs and soil fertility (farmlet A); and a third which focussed on the use of moderate inputs and intensive rotational grazing (farmlet C).The climate experienced during the 6.5-year experimental period was compared with the 118-year climatic record, using a biophysical simulation model of grazed systems. The model utilised the long-term daily climate data as inputs and provided outputs that allowed comparison of parameters known to affect grazed pastures. Modelled soil-available water, the number of soil moisture stress days (SMSDs) limiting pasture growth, and growth indices over the experimental period (2000-06) were compared with data over the climatic record from 1890 to 2007. SMSDs were defined as when the modelled available soil moisture to a depth of 300 mm was <17% of water-holding capacity. In addition, minimum temperatures and, in particular, the frequency of frosts, were compared with medium-term (1981-2011) temperature records.Wavelet transforms of rainfall and modelled available soil water data were used to separate profile features of these parameters from the noise components of the data. Over the experimental period, both rainfall and available soil water were more commonly significantly below than above the 95% confidence intervals of both parameters. In addition, there was an increased frequency of severe frosting during the dry winters experienced over the 6.5-year period. These dry and cold conditions were likely to have limited the responses to the pasture and grazing management treatments imposed on the three farmlets. In particular, lower than average levels of available soil water were likely to have constrained pasture production, threatened pasture persistence, and reduced the response of the pasture to available soil nutrients and, as a consequence, livestock production and economic outcomes.Ideally, dryland field experimentation should be conducted over a representative range of climatic conditions, including soil moisture conditions both drier and wetter than average. The drier than average conditions, combined with a higher than normal frequency of severe frosts, mean that the results from the Cicerone Project's farmlet experiment need to be viewed in the context of the climate experienced over this 6.5-year period.

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Section: Climate Modellingmentioning

confidence: 99%

Comparing the climate experienced during the Cicerone farmlet experiment against the climatic record

et al. 2013

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“…through commercial software distributors (Donnelly et al, 2002) or on the Internet (Welch et al, 2002). All three qualify for Churchman and Schainblatt's 'separate-function' relationship between the scientist/modeller and the farm manager.…”

Section: Minimal Relationship Between Scientist and Farmer-reliance Omentioning

confidence: 99%

Changing systems for supporting farmers' decisions: problems, paradigms, and prospects

McCown

2002

Agricultural Systems

326

182

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All correct reasoning is a grand system of tautologies, but only God can make direct use of that fact. The rest of us must painstakingly and fallibly tease out the consequences of our assumptions. (Herbert Simon in 'The Sciences of the Artificial', p.15)Decision support systems (DSS), like other information systems (IS) before them, were designed to serve functions deemed by 'management scientists' to be potentially useful to managers. But the unwelcome fact is that the use of agricultural DSSs by managers of farms has been low. This paper probes possible reasons for this through interpretation of agricultural DSS case histories and several strands of relevant social theory. From nine cases of DSS development effort and 14 products interpreted comparatively, a number of generalisations are made that serve as reference points in the following search for explanation in theory.First, the nature of management practice of family farms is explored and differences between the internal structure governing personal action and the scientific approach to practice are contrasted. Next, the interaction between the nature of the particular action/practice and the nature of the DSS is explored. A DSS designed to provide integrated, optimal recommendations for management typifies the DSS as a proxy for a manager's decision process. Examples of elaborate expert systems that simply were not used dramatically illustrate the resistance of family farmers to have their decision processes by-passed. On the other hand, the DSS designed to serve as a tool in a modified decision process is shown to have experienced higher use, by deriving and exploiting 'deep,' abstract information about the system, by introducing a powerful 'logic,' or a combination of both. A number of the referenced case stories demonstrate the resurgence of the decision support mode whereby the simulator is in the hands of an expert intermediary as an alternative to easy-to-use software in the hands of a farmer. This is the mode of operational research/ management science, which preceded the DSS.In comparison with hierarchical organizations, available options for overcoming the persistent 'problem of implementation' of the DSS in family farms are inherently weak. This focuses attention on the importance of the relationship between the DSS developer and the potential user. Drawing on a classic typology of possible configurations of 'understanding' between the scientist and the manager, four approaches to intervention are discussed. Three entail a degree of engagement that qualifies them as 'participative.' But one of these constitutes a departure from the DSS and broader IS traditions that places it in another paradigm. In this 'mutual understanding' relationship, intervention intent shifts from educating and persuading to recognition of and respect for other ways of viewing the world. This opens up the opportunities for co-creating information systems that utilise the comparative advantages of both practical and scientific knowledge. Intervention emphasis shi...

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“…For example, GRAZPLAN [9] has been chosen by teachers of the University of New England for a 4-year curriculum. Students become very familiar with this software and could easily use it, as long as this software can solve the problems they will encounter during their professional careers.…”

Section: General Discussion and Conclusionmentioning

confidence: 99%

Modelling as a tool for the teaching of livestock dynamics

Moulin

Blanc

Ezanno³

et al. 2004

Anim. Res.

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-Modelling is a way of integrating and formalising the knowledge about how a system works. Thus, it is a relevant approach for teaching agricultural systems analysis to undergraduate students. In most cases, research models or decision support tools cannot be easily used for teaching purposes because conceptual models are too complex to be handled by students during a short training course or do not fit pedagogic goals. However, from our own modelling research, we developed two techniques to support our teaching program in herd dynamics. The first one was based on a deterministic approach and used simple flow diagrams. Students had to fill in a paper chart that depicts the breeding scheme of a flock for several years. Thus, they test if a combination of decision rules (e.g., breeding, replacement, culling) allows to reach a given production objective. Then, students had to suggest technical means or management decisions that could improve flock productivity. The second technique relied on a stochastic matrix model that was used to illustrate the sensitivity of herd productivity in a tropical environment. The model was computerised using spreadsheets. On the basis of the simulation results, students had to comment on the behaviour of the system and to appraise the model, with respect to the choice of assumptions and formalisation. Because our teaching approach is progressive and interactive, we are confident that students will become well-informed users of more elaborated models such as decision support tools.teaching / livestock management / flock / herd / sensitivity analysis / modelling / stochastic / spreadsheet / flow diagram Résumé -L'utilisation de modèles pour l'enseignement sur le fonctionnement des troupeaux. La modélisation permet de résumer un ensemble de connaissances sur le fonctionnement d'un système. C'est ainsi un outil pertinent pour la formation des futurs ingénieurs à la complexité des systèmes agricoles. Les modèles de recherche ou les outils d'aide à la décision ne peuvent pas toujours être facilement utilisés pour la formation parce qu'ils ne correspondent pas toujours à nos objectifs pédagogiques ou parce qu'ils sont trop complexes pour être manipulés par les étudiants dans des séances d'enseignement de courte durée. En utilisant nos travaux de recherche sur la dynamique des troupeaux ovins ou bovins, nous avons développé deux techniques pour l'enseignement. La première est fondée sur l'utilisation de diagrammes de flux d'animaux. Les étudiants doivent remplir des graphes qui décrivent, de façon déterministe, l'organisation de la reproduction d'un troupeau ovin sur plusieurs années. Ils vérifient ainsi si une combinaison de règles de décision concernant la mise à la lutte, le renouvellement et la réforme permet de satisfaire un objectif de production donné. Les étudiants doivent alors réfléchir aux moyens techniques et organisationnels pour améliorer la productivité du troupeau. La seconde technique est fondée sur l'utilisation d'une feuille de calcul. Les étudiants doivent évalue...

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Evolution of the GRAZPLAN decision support tools and adoption by the grazing industry in temperate Australia

Cited by 77 publications

References 12 publications

Comparing the climate experienced during the Cicerone farmlet experiment against the climatic record

Comparing the climate experienced during the Cicerone farmlet experiment against the climatic record

Changing systems for supporting farmers' decisions: problems, paradigms, and prospects

Modelling as a tool for the teaching of livestock dynamics

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