A response to Doole and Marsh () article: methodological limitations in the evaluation of policies to reduce nitrate leaching from New Zealand agriculture

Daigneault, Adam; Greenhalgh, Suzie; Samarasinghe, Oshadhi

doi:10.1111/1467-8489.12051

Cited by 7 publications

(4 citation statements)

References 10 publications

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“…Daigneault et al (2014) explain that NZFARM calibrates within 1-3% of the reported baseline without PMP, given the accuracy of the underlying farm level data. This would appear to support the case for not using PMP, as its omission would have little impact on model calibration, while also allowing the modellers to separate themselves from a wealth of research that has invalidated the application of this technique.…”

mentioning

confidence: 83%

Use of positive mathematical programming invalidates the application of the NZFARM model

Doole

Marsh

2014

Aus J Agri & Res Econ

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confidence: 83%

Use of positive mathematical programming invalidates the application of the NZFARM model

Doole

Marsh

2014

Aus J Agri & Res Econ

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“…Python 2.7 is used to facilitate a loose coupling [ 38 ] between ARLUNZ and a modified version of the New Zealand Forest and Agriculture Regional Model (NZFARM) that provides economic information within ARLUNZ. NZFARM is a comparative-static, non-linear, partial equilibrium mathematical programming model of New Zealand land use operating at the catchment scale [ 32 ]. The modified version used within ARLUNZ has been refined to produce an economically optimised result for each farm rather than an optimised landscape for an entire catchment.…”

Section: Methodsmentioning

confidence: 99%

“…The modified version used within ARLUNZ has been refined to produce an economically optimised result for each farm rather than an optimised landscape for an entire catchment. For more information about NZFARM, Daigneault et al [ 32 ] details its design, parameterisation and validation while Daigneault et al [ 39 – 42 ] discusses the input data used within model.…”

Section: Methodsmentioning

confidence: 99%

Estimating Impacts of Climate Change Policy on Land Use: An Agent-Based Modelling Approach

Morgan

Daigneault

2015

PLoS ONE

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Agriculture is important to New Zealand’s economy. Like other primary producers, New Zealand strives to increase agricultural output while maintaining environmental integrity. Utilising modelling to explore the economic, environmental and land use impacts of policy is critical to understand the likely effects on the sector. Key deficiencies within existing land use and land cover change models are the lack of heterogeneity in farmers and their behaviour, the role that social networks play in information transfer, and the abstraction of the global and regional economic aspects within local-scale approaches. To resolve these issues we developed the Agent-based Rural Land Use New Zealand model. The model utilises a partial equilibrium economic model and an agent-based decision-making framework to explore how the cumulative effects of individual farmer’s decisions affect farm conversion and the resulting land use at a catchment scale. The model is intended to assist in the development of policy to shape agricultural land use intensification in New Zealand. We illustrate the model, by modelling the impact of a greenhouse gas price on farm-level land use, net revenue, and environmental indicators such as nutrient losses and soil erosion for key enterprises in the Hurunui and Waiau catchments of North Canterbury in New Zealand. Key results from the model show that farm net revenue is estimated to increase over time regardless of the greenhouse gas price. Net greenhouse gas emissions are estimated to decline over time, even under a no GHG price baseline, due to an expansion of forestry on low productivity land. Higher GHG prices provide a greater net reduction of emissions. While social and geographic network effects have minimal impact on net revenue and environmental outputs for the catchment, they do have an effect on the spatial arrangement of land use and in particular the clustering of enterprises.

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“…Python 2.7 is used to facilitate a loose coupling [64] between ARLUNZ and a modified version of the New Zealand Forest and Agriculture Regional Model (NZFARM) that provides economic information. NZFARM is a non-linear, partial equilibrium mathematical programming model of New Zealand land use operating at the sub-catchment scale [65]. The version used within ARLUNZ has been refined to produce an economically optimised result for each farm rather than an optimised landscape for a sub-catchment [66][67][68][69].…”

Section: Methodsmentioning

confidence: 99%

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

Morgan

Brown

Daigneault

2015

Land

Self Cite

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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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A response to Doole and Marsh () article: methodological limitations in the evaluation of policies to reduce nitrate leaching from New Zealand agriculture

Cited by 7 publications

References 10 publications

Use of positive mathematical programming invalidates the application of the NZFARM model

Use of positive mathematical programming invalidates the application of the NZFARM model

Estimating Impacts of Climate Change Policy on Land Use: An Agent-Based Modelling Approach

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

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