## 6 Discussion  
### Range of Model Approaches and Thematic Applications  
The approaches and model examples presented in Figure 2 and Table 1 show a range of freely and easily accessible tools, which require low to high levels of input data and application skills. That means modelling of agricultural systems does not necessarily require time-consuming data collection or model development for certain levels of application, but only a few models are available for regional or national modelling applications. For example, the FAO models can be used as-is for basic scenario modelling or for feeding another model. The benefits from combined approaches and the use of spatial models for better land planning are also obvious. For example, coupling a participatory approach to a quantitative deterministic or probabilistic approach to include stakeholder engagement for scenario design or to test stakeholder behaviours on an ABM enhances the model outputs. A range of models are available to address specific questions faced by the NZ government at a national or regional decision-level, related to agricultural systems technology, disruptions, and the environment (Figure 1), but none of the currently available models or approaches can answer all questions by themselves. A combination of several approaches and existing models can help address individual disparate issues (Table 2). \begin{table}
\begin{tabular}{l l l} \hline \hline \multicolumn{2}{c}{**Question Examples**} & \multicolumn{2}{c}{**Modelling Process Options**} \\ \hline \multirow{7}{*}{\(\bullet\)} & \multirow{7}{*}{How will anthropogenic} & \multirow{7}{*}{-} & Deterministic approach to understand physical processes (climate, crop, milk yields models, economic models); \\  & & & \multicolumn{1}{c}{} \\  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \hline \hline \end{tabular} \
\begin{tabular}{l l l} \hline \hline \multicolumn{2}{c}{**Question Examples**} \\ \hline \hline \multirow{7}{*}{\(\bullet\)} & \multirow{7}{*}{How will disruptive} & \multirow{7}{*}{-} & Deterministic approach to understand physical processes (climate, crop, milk yields models, economic models); \\  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \hline \hline \end{tabular}
\begin{tabular}{l l l} \hline \hline \multicolumn{2}{c}{**Question Examples**} \\ \hline \hline \multirow{7}{*}{\(\bullet\)} & \multirow{7}{*}{How will anthropogenic} & \multirow{7}{*}{-} & Probabilistic approach to define vulnerability (land-use model); \\  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \cline{1-1}  & & & \multicolumn{1}{c}{} \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Synthesis of example questions and modelling process options. Analysis of modelling approaches and model examples allows for identifying model strengths, weaknesses, data needs, and skill requirements to select the best combination for the NZ needs. A DST, based on an SD approach, can be the most suitable modelling system at a regional to national scale for modelling the agricultural systems to support policy development and anticipate main impacts. For example, the iSDG model developed by the Millennium Institute [40] aims to model the interconnections between a large number of objectives to help identify policy interventions (Table 1). This model focuses on the dynamic interactions within the objectives to reveal the best pathways towards achieving them all.