A simulation framework for the design of grassland-based beef-cattle farms

doi:10.1016/j.envsoft.2010.10.002

Environmental Modelling & Software

Volume 26, Issue 4, April 2011, Pages 371-385

https://doi.org/10.1016/j.envsoft.2010.10.002 Get rights and content

Abstract

Grassland-based beef-cattle farms are dynamic systems that are difficult to manage, particularly because of their sensitivity to uncontrollable environmental factors such as weather. The design of farms and management strategies capable of coping with a wide range of conditions is thus a challenging issue. The SEDIVER discrete-event simulation framework presented in this article has been developed to support the construction of dynamic simulation models of grassland-based beef-cattle farms for evaluation and empirical design purposes. The originality of the models built with SEDIVER lies in the explicit representation of: (i) management strategies as the planning and coordination of activities in time and space through which the farmer controls the biophysical processes occurring within the system and (ii) the diversity in plant, animals, grassland and farmland, and the management opportunities and difficulties that this might induce. An application example illustrates the kind of simulation-based investigations enabled by SEDIVER. A grassland-based beef-cattle farm in France is examined for two contrasted management strategies: the first one corresponding to the actual practice and the second one paying increased attention to and exploiting plant and grassland diversity. The simulation results showed that the second one could roughly double fodder yields and thus ensure farm self-sufficiency for fodder. Thanks to the capacity of a SEDIVER-based model to take practical production considerations into account, it is possible to increase the realism of farm simulations and the credibility and relevance of the farming systems which can thus be designed.

Introduction

In less-favourable areas, beef-cattle production involves the management of a wide diversity of semi-natural grasslands. Herbage production is highly variable in space and time (Pleasants et al., 1995) due to between-field differences in vegetation types, soil conditions and topography and also to weather variability within and between years. Similarly, beef-cattle feeding requirements change over time and between beef-cattle classes (INRA, 2007). Farmers need to be able to take decisions for planned management that in turn is able to take situation-dependent factors into account in order to achieve the most efficient use of production resources (grasslands, labour, etc.) over space and time to meet their objectives through a sustainable production system. The design of grassland-based beef-cattle farms capable of coping efficiently with a wide range of conditions (including climate variability and climate change and changing socio-economic conditions, etc.) is thus a challenging issue. This includes changes in the production resources of farms or in farmers’ management.

In such systems, we believe that there is great potential for farmers to improve their efficiency through better use of plant (within-field), grassland (between-field), animal and farmland diversity. Diversity adds potential flexibility that can be used in organizational and operational decision-making to cope with variations in uncontrollable factors, such as climate (e.g. White et al., 2004, Andrieu et al., 2007, Martin et al., 2009). For instance, grassland diversity means that particular fields may be suitable for various forms of use, matching the feeding requirements of different beef-cattle classes (e.g. cows vs. heifers) characterized by specific and fluctuating animal intake rates (White et al., 2004). In addition to this organizational flexibility, within-field plant diversity makes it possible to take advantage of operational flexibility in grassland management (Martin et al., 2009), i.e. the extent to which the use of a given grassland may be brought forward or held in reserve at various times of the year.

Simulation (McCown, 2002) is an obvious tool for the study of grassland-based production systems as their complexity makes analytical evaluation or optimization more difficult. However, its potential usefulness as a tool for the empirical design of agricultural systems with extension services and farmers depends on the conceptual richness of its modelling functions. To ensure that the systems designed and evaluated by simulation are credible and relevant to stakeholders’ needs, day-to-day farm operations need to be integrated in the model (Keating and McCown, 2001) in order to deal with the practical questions farmers have to answer such as “what should I do, where, when and how?” The model might then focus on the variability of biophysical processes over time and in space, the generated opportunities and constraints on grassland use and the way the farmer copes with them when planning and coordinating farming activities. Besides, developing credible farm-scale simulation models is a costly task that requires considerable agronomic knowledge and modelling skills. To make the simulation approach more accessible and to increase the reusability of previous modelling efforts, the simulation methodology needs to support the modelling process by providing generic knowledge patterns and functions which are suitable for dynamic simulation.

These considerations prompted the development of SEDIVER (Simulation-based Experimentation on livestock systems with plant, grassland, animal and farmland DIVERsity), a discrete-event simulation framework for supporting the construction of farm-scale dynamic models capable of reproducing the interactions on grassland-based beef-cattle farms between the biophysical and management processes in response to external factors such as weather. The purpose of this article is to present both this framework and an example of its application that illustrates the kinds of investigation enabled. In Section 2, the modelling approach and the ontology of agricultural production systems on which it relies are briefly described. Section 3 describes the domain-specific concepts underlying SEDIVER. An example is provided in Section 4 to illustrate how the modelling capabilities of SEDIVER are applied in a case study to compare the performance of a novel management strategy with the one already being used. Section 5 discusses the results obtained and situates SEDIVER with respect to related simulation models. Section 6 summarizes the main points and suggests possible future developments.

Section snippets

Ontology-based modelling

In Section 2.1 we outline our approach to the study of grassland-based beef-cattle production systems. The backbone of the approach is a production system ontology introduced in Section 2.2.

Domain knowledge and dynamic functioning

A synthetic description of the conceptualization (Martin et al., in press) developed for the SEDIVER simulation framework is given in the next two sections that deal with the biophysical and management aspects respectively. In the sequel, class names start with a capital letter (e.g. GroupOfPlots), whereas names of class specialisations start with a lower case letter (e.g. groupOfPlots1). Section 3.3 outlines the dynamic functioning of the system through the processing of the event agenda.

Description of the experiment

On the French side of the Pyrenees, the climate is montane. Long, cold winters prevent animals from grazing for several months. During that period, about half of the grassland-based beef-cattle farms rely on roughly 20% of external hay supply to cover the fodder needs of their herd. Amazingly, on these farms, the herbage utilization rate, i.e. the ratio of herbage grazed and harvested to the herbage grown over the year, remains low at around 50%. The SEDIVER simulation framework was therefore

Discussion and related works

Effectiveness of the simulation approaches in supporting the design of farm systems, might be assessed according to three criteria (Cash et al., 2003): saliency (relevance to decision makers), credibility (scientific adequacy) and legitimacy (fair and unbiased production of information which respects stakeholders’ values and beliefs).

Farms, especially in less-favoured areas, are characterized by strongly heterogeneous resource use, resulting in considerable variability of production in time and

Conclusion

To sum up the models of grassland-based beef-cattle production systems built with the SEDIVER simulation framework incorporate an explicit representation of management strategies and decision processes, and exploit ready-to-use biophysical models while taking into account the diversity in plant, grassland, animal, and farmland. The models constructed with SEDIVER are definitely more representative of farmer management due to explicit representation of the organisation, coordination and

Acknowledgements

This study was partly funded by the French ANR ADD and VMC programmes in the framework of the TRANS (TRANSformations de l’élevage et dynamiques des espaces, ANR-05-PADD-003) and VALIDATE (Vulnerability Assessment of LIvestock and grasslanDs to climAte change and exTreme Events, ANR-07-VULN-011) projects. We would like to thank J.P. Theau and O. Therond who contributed to this research, and Alan Scaife for revising the English.

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A simulation framework for the design of grassland-based beef-cattle farms

Abstract

Introduction

Section snippets

Ontology-based modelling

Domain knowledge and dynamic functioning

Description of the experiment

Discussion and related works

Conclusion

Acknowledgements

Using leaf traits to rank native grasses according to their nutritive value

Rangeland Ecology & Management

Simulation of forage management strategies considering farm-level land diversity: example of dairy farms in the Auvergne

Computers and Electronics in Agriculture

Characterizing and predicting plant phenology in species-rich grasslands

Grass & Forage Science

Functional traits as indicators of fodder provision over a short time scale in species-rich grasslands

Annals of Botany

Caractérisation de la diversité fonctionnelle des prairies à flore complexe: vers la construction d’outils de gestion

Fourrages

Knowledge systems for sustainable development

Proceedings of the National Academy of Sciences of the United States of America

What are ontologies and why do we need them

IEEE Intelligent Systems

A method to analyse decision-making processes for land use management in livestock farming

International Journal of Agricultural Sustainability

Simulating management strategies: the rotational grazing example

Agricultural Systems

Vive la difference: plant functional diversity matters to ecosystem processes

Trends in Ecology & Evolution

A software component to simulate agro-management

Modelling above-ground herbage mass for a wide range of grassland community types

Ecological Modelling

Haymaking: risks and uncertainties in central Pyrenees grasslands

Agricultural Systems

Un modèle générique de digestibilité des graminées des prairies semées et permanentes pour raisonner les pratiques agricoles

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La hauteur du couvert prairial: un moyen d’estimation de la quantité d’herbe disponible

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Naisseur de broutards en montagne Pyrénées

A model predicting the seasonal dynamics of intake and production for suckler cows and their calves fed indoors or at pasture

Animal Feed Science and Technology

Simulating grassland utilization in beef suckler systems to investigate the trade-offs between production and floristic diversity

Agricultural Systems

Advances in farming systems analysis and intervention

Agricultural Systems