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Environmental variation is a crucial driver of ecological pattern, and spatial layers representing this variation are key to understanding and predicting important ecosystem distributions and processes. A national, standardised collection of different environmental gradients has the potential to support a variety of large-scale research questions, but to date these data sets have been limited and difficult to obtain. Here we describe the New Zealand Environmental Data Stack (NZEnvDS), a comprehensive set of 72 environmental layers quantifying spatial patterns of climate, soil, topography and terrain, as well as geographical distance at 100 m resolution, covering New Zealand's three main islands and surrounding inshore islands. NZEnvDS includes layers from the Land Environments of New Zealand (LENZ), additional layers generated for LENZ but never publicly released, and several additional layers generated more recently. We also include an analysis of correlation between variables. All final NZEnvDS layers, their original source layers, and the R-code used to generate them are available publicly for download at https://doi.org/10.7931/m6rm-vz40. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Human behaviour is commonly optimised in economic models of adaptation to climate change. These models assume that people work to maximise profit, subject to financial and technological limitations. In effect, these models simulate adaptive potential. In reality, adaptation falls short of this potential. This shortfall is conceptualised as the adaptation deficit, and it has been causing increasing concern. This study demonstrates the impacts of the ways by which people's real-world adaptive behaviours depart from those assumed under pure optimisation. These departures, known as adaptation constraints, are formalised as numerical preference functions based on an empirical case study in New Zealand, and they are used to constrain an agent-based model of climate change adaptation. We show that these empirically-specified adaptation constraints reduce profits relative to an optimised specification by roughly one third. This demonstrates that unconstrained economic models are likely to significantly underestimate the costs of adaptation to climate change, the benefits of reducing greenhouse gas emissions, and the residual loss and damage that climate change will cause. Unlabelled Image • People respond slowly and partially to biophysical and ecological change. • We modelled the economic impacts of adaptation constraints found among farmers. • Farming profits fell by roughly one third when adaptation constraints were added. • Models that optimise adaptation underestimate the impacts of climate change. • IAMs based on these models underestimate the costs of climate change. [ABSTRACT FROM AUTHOR]