2016
DOI: 10.1007/s13593-016-0402-x
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Processes of adaptation in farm decision-making models. A review

Abstract: Agricultural production systems should evolve fast to cope with risks induced by climate change. Farmers should adapt their management strategies to stay competitive and satisfy the societal demand for sustainable food systems. It is therefore important to understand the decision-making processes used by farmers for adaptation. Processes of adaptation are in particular addressed by bio-economic and bio-decision models. Here, we review bio-economic and bio-decision models, in which strategic and tactical decisi… Show more

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Cited by 67 publications
(61 citation statements)
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References 87 publications
(106 reference statements)
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“…In this paper, the term 'farm workforce' relates to all these human resource categories reflecting broader changes in the social organisation of farming in developed countries (Lobley and Potter 2004;Santhanam-Martin and Nettle 2015). In a recent review of processes of adaptation within farm decision-making models, workforce resource decisions were absent from models relating to converting cash crops to silage for livestock feed in drought conditions (Robert et al 2016). In a study of peanut growers making transformational changes in Australia, Marshall et al (2014) discussed farmers' capacity to be employed outside the farm as an adaptation strategy, but did not consider the farm workforce decisions and implications associated with other adaptation strategies, such as changing farm location or the difficulties accessing a workforce in a more remote location (McKenzie 2011).…”
Section: Introductionmentioning
confidence: 99%
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“…In this paper, the term 'farm workforce' relates to all these human resource categories reflecting broader changes in the social organisation of farming in developed countries (Lobley and Potter 2004;Santhanam-Martin and Nettle 2015). In a recent review of processes of adaptation within farm decision-making models, workforce resource decisions were absent from models relating to converting cash crops to silage for livestock feed in drought conditions (Robert et al 2016). In a study of peanut growers making transformational changes in Australia, Marshall et al (2014) discussed farmers' capacity to be employed outside the farm as an adaptation strategy, but did not consider the farm workforce decisions and implications associated with other adaptation strategies, such as changing farm location or the difficulties accessing a workforce in a more remote location (McKenzie 2011).…”
Section: Introductionmentioning
confidence: 99%
“…This could be due to the general difficulty in measuring human resources and the nature of the workplace environment, such as job quality or work conditions (Harrison and Getz 2015), the difficulty in modelling workforce dynamics in farming systems (Robert et al 2016) or in incorporating the influence of external factors, such as labour market conditions, and the entry or exit of people in farming (Santhanam-Martin and Nettle 2014). However, on further analysis, it would appear that the farm workforce is examined only as a cost (e.g.…”
Section: Introductionmentioning
confidence: 99%
“…Decision rules can be conceptually grouped into two categories, depending on the time‐scale at which they operate: “strategic decisions” operate at a year or several year time‐scale, while “tactical decisions” operate at shorter time‐scales (season/week/day) (e.g. Cittadini, Lubbers, de Ridder, van Keulen, & Claassen, ; Le Gal, Dugue, Faure, & Novak, ; Ripoche et al., ; Robert et al., ). Strategic decisions correspond to farmer's objectives (e.g.…”
Section: A Trait‐based Framework For Agroecosystemsmentioning
confidence: 99%
“…Farmer's decision-making processes are complex and have been extensively studied for the last 30 years (Aubry & Michel-Dounias, 2006;Aubry et al, 1998;Cerf & Sébilllote, 1988;Darré, Mathieu & Lasseur, 2007;Duru, Papy, & Soler, 1988;Le Gal et al, 2010;Papy, 2001;Robert et al, 2016;Sébilllote & Soler, 1990). In the context of the framework proposed here, we grouped decision-making drivers into five groups, described below.…”
Section: The Biophysical Modulementioning
confidence: 99%
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