Social networks in complex human and natural systems: the case of rotational grazing, weak ties, and eastern US dairy landscapes

Nelson, Kristen C.; Brummel, Rachel F.; Jordan, Nicholas R.; Manson, Steven M.

doi:10.1007/s10460-013-9462-6

Cited by 45 publications

(39 citation statements)

References 44 publications

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“…Specifically, decision making is considered a social process, influenced by community norms, whereby individuals enlist others, often those in their social network, to help them make specific management decisions (Pannell et al 2006). Social networks are important predictors of farmer transitions to sustainable agricultural and conservation-oriented practices (Coughenour 2003;Carolan 2006;Atwell et al 2009;Blesh and Wolf 2014;Nelson et al 2014). Additionally, norms also influence what constitutes a ''good farmer,'' which is a social construct laden with values and aesthetic preferences (e.g., ''a freshly tilled field is beautiful'') (Burton 2004).…”

Section: Conceptual Framework For Agricultural Adaptationmentioning

confidence: 99%

What would farmers do? Adaptation intentions under a Corn Belt climate change scenario

2016

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This paper examines farmer intentions to adapt to global climate change by analyzing responses to a climate change scenario presented in a survey given to largescale farmers (n = 4778) across the US Corn Belt in 2012. Adaptive strategies are evaluated in the context of decision making and farmers' intention to increase their use of three production practices promoted across the Corn Belt: no-till farming, cover crops, and tile drainage. This paper also provides a novel conceptual framework that bridges a typology of adaptation with concepts that help predict intentionality in behavior change models. This conceptual framework was developed to facilitate examination of adaptive decision making in the context of agriculture. This research effort examines key factors that influence farmers' intentions to increase their use of the practices evaluated given a climate change scenario. Twenty-two covariates are examined across three models developed for no-till farming, cover crops, and tile drainage. Findings highlight that farmers who believed they should adjust their practices to protect their farm from the negative impacts of increased weather variability were more likely to indicate that they would increase their use of each of the practices in response to climate change. Additionally, visiting with other farmers to observe their practices was positively associated with farmers' intentions to increase their use of the adaptive strategies examined. Farmers who were currently using no-till farming, cover crops, and tile drainage were also more likely to plan to increase their use of these practices in response to increased weather variability associated with climate change. However, farmers who reported high levels of confidence in their current practices were less likely to plan on changing their use of these practices in response to climatic changes.

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Section: Conceptual Framework For Agricultural Adaptationmentioning

confidence: 99%

What would farmers do? Adaptation intentions under a Corn Belt climate change scenario

2016

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“…Studies have found that the proximity to the people in one's network is not as important as the stature of those people [59,76]. Therefore we assume that two-way interactions such as endorsements are preferred by farmers and provide a higher level of information acceptance compared with one-way interactions such as imitation.…”

Section: Network Approachmentioning

confidence: 97%

“…Farmer's information networks are framed around their social [39,40,59] and geographical [74,75] interactions and play a role in decision-making processes [39,50,75]. Two theoretical frameworks inform how networks influence farmer decision making-endorsements and imitation.…”

Section: Network Approachmentioning

confidence: 99%

Simulation vs. Definition: Differing Approaches to Setting Probabilities for Agent Behaviour

Morgan

Brown

Daigneault

2015

Land

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While geographers and economists regularly work together on the development of land-use and land-cover change models, research on how differences in their modelling approaches affects the results is rare. Answering calls for more coordination between the two disciplines in order to build models that better represent the real world, we (two economists and a geographer) developed an economically grounded, spatially explicit, agent-based model to explore the effects of environmental policy on rural land use in New Zealand. This inter-disciplinary collaboration raised a number of differences in modelling approach. One key difference, and the focus of this paper, is the way in which processes that shape the behaviour of agents are integrated within the model. Using the model and a nationally representative survey, we compare the land-use effects of two disciplinary-aligned approaches to setting a farmer agent's likelihood of land-use conversion. While we anticipated that the approaches would significantly affect model outcomes, at a catchment scale they produced similar trends and results. However, further analysis at a sub-catchment scale suggests the approach to setting the likelihood of land-use conversion does matter. While the results outlined here will not fully resolve the disciplinary differences, they do outline the need to account for heterogeneity in the predicted agent behaviours for both disciplines. OPEN ACCESSLand 2015, 4 915

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“…In the study of complex networks, there are regular network, random network and general network, and there also derived small-world network model [6] and BA scale-free network model [7]. Complex network theory has been applied to business economics [8], energy economics [9,10], social sciences [11,12], cross-shareholding networks [13], and other fields. Since the 1990s, many economists and sociologists have focused on international trade and social networks.…”

Section: Introductionmentioning

confidence: 99%

Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network

2016

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Social networks in complex human and natural systems: the case of rotational grazing, weak ties, and eastern US dairy landscapes

Cited by 45 publications

References 44 publications

What would farmers do? Adaptation intentions under a Corn Belt climate change scenario

What would farmers do? Adaptation intentions under a Corn Belt climate change scenario

Simulation vs. Definition: Differing Approaches to Setting Probabilities for Agent Behaviour

Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network

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