Adaptation of New Zealand dairy farms to climate change: An integrated, farm-level analysis

The dairy sector is a cornerstone of the New Zealand economy and as such, it is important to understand the ways in which it is likely to be affected by climate change, whether it will need to adapt, and if so, how this can best be achieved. The overall goal of this research was to analyse potential strategies for New Zealand dairy farms to adapt to projected climate change. For this purpose, an integrated biophysical and socio-economic research framework was developed. Drawing on recognised frameworks for the analysis of climate change adaptation, together with systems analysis methodologies, the framework sets out an integrated process for analysing potential adaptation strategies at farm level. Six case study farms were selected for the analysis, representing major dairying regions in New Zealand and covering a range of climatic zones and management approaches. The farmers selected were experienced and respected operators, in order to draw on their knowledge of farming systems resilience. Qualitative social research provided insights into the way the farmers saw their farming systems and how climate change issues were placed in the context of other challenges facing the farmers. It also provided a farmer perspective on some of the driving forces that influence the current trajectories of New Zealand dairy systems, in particular their concerns around the effects of environmental regulation and changes in farm structure, which may affect the future adaptive capacity of their farming systems. The next step in the analysis was to model the farms in the DairyNZ Whole Farm Model (WFM) under dynamically downscaled climate change scenarios provided by the National Institute of Water and Atmospheric Research (NIWA). This showed significant potential for some adaptations to mitigate the projected impacts of climate change. For example, making and feeding out more silage, and changing the pasture species modelled, showed benefits for nearly all farming systems. However, there were limitations in the capacity of the model to accurately represent the on-farm challenges of implementing such adaptations. Feedback from the farmers highlighted the limitations, as well as the potential value of such modelling work, emphasising the importance of assessing such research in context. A second round of modelling work was carried out based on the suggestions of individual farmers for their own farms. The suggestions made by farmers were predominantly incremental, rather than transformational adaptations, reflecting the farmer’s positive assessment of the current level of resilience in their farming systems, but also reflecting their operational and personal constraints. Modelling under present conditions and future climate showed that many of the adaptations did mitigate the impacts of climate change. However, there was still a largely negative impact compared to the same adaptations carried out under the baseline (current) climate. This implies that ongoing work, innovation and technological adjustments will be required to optimise these farming systems under future climate conditions. For both incremental and transformational adaptations, there are two key factors in finding resilient pathways when challenged with the uncertainty surrounding climate change and other pressures. The first is the maintenance of flexibility and the avoidance of path dependence, to ensure ongoing adaptive capacity. Secondly, it needs to be recognised that resilience occurs at different scales. In some cases, adaptation measures that increase resilience at farm level, such as importing feed, may reduce resilience at a broader scale, which may in turn come under pressure from climate change. The combined methodological approach meant that it was possible to reach beyond the limitations of each and form a more holistic picture of potential adaptation strategies. Some strategies lent themselves easily to testing in a model, while others were well beyond its scope. Conversely, the modelling work enabled a more objective and quantified assessment of farmer perceptions about the resilience of their systems. Every adaptation decision involves a set of trade-offs. In conclusion, some of the trade-offs identified as part of this study are summarised for the range of adaptation strategies as originally identified from the literature. Conscious articulation of these trade-offs, in terms of the factors important for ongoing system resilience, is the first step in better informed choices that may lead to more sustainable development of future farming systems