Alexander Herzig

This study explores the potential benefits of transitioning from livestock farming to high-value alternative crops as a strategy for mitigating agricultural greenhouse gas (GHG) emissions in New Zealand. The government has set ambitious targets for reducing methane (CH₄) emissions. However, since animal product exports play a crucial role in New Zealand’s economy, any shift in land use will have significant impacts on both the regional and national economy. We developed a GIS framework that integrated (i) growing requirements, (ii) GHG emissions and (iii) profitability for crops. Analysis of export market opportunities identified twelve high-value “alternative crops”. Availability of suitable land for crop expansion was not a limiting factor. Working with the Ministry for Primary Industries, we explored how land use change scenarios contributed to Government 2050 biogenic CH₄ emission reduction targets. Doubling the area of alternative crops (a 195,000-ha increase) by reallocating land from livestock farming resulted in reducing biogenic CH₄ emissions by 1.2 to 5.4% (0.35 to 1.57 Mt CO₂-e) compared to 2017 baseline values, contributing to between 2.6 and 22.5% of the 2050 CH₄ reduction targets, simultaneously increasing profitability by $NZ1.25 to 1.32 billion annually. While this approach demonstrates potential benefits of land use change, a deeper understanding of the complexity of land use decision-making is required to enable successful transitions. Addressing barriers to change requires collaborative efforts from land users, researchers and policy makers.

Intensive production landscapes provide low levels of many ecosystem services and support limited biodiversity, so they require restoration to enhance their multifunctionality. International guidelines suggest that restoration should aim to establish natural woody vegetation cover across 30% of landscapes. Such restoration may be implemented in varied spatial configurations and complemented by additional land use changes from intensive to extensive semi-natural pastoral grasslands. To restore multifunctional landscapes, we need to understand the impacts of restoration spatial configuration and complementary grassland extensification, both in isolation and in combination. We used a virtual landscape simulation to systematically analyse the impacts of alternative restoration strategies on the provision of nine indicators of ecosystem services and biodiversity, and the overall multifunctionality of the landscapes. All restored landscapes achieved improvements in the performance of individual ecosystem services and multifunctionality compared to the baseline. The benefits of a given restored natural vegetation effort were increased by adding extensive grassland and modifying the spatial configuration of restoration. Randomly distributed patterns of restoration provided higher multifunctionality than restoration adjacent to existing natural areas or as large land blocks. The virtual landscape approach allowed systematic exploration of alternative restoration strategies, providing a mechanistic understanding that will inform restoration tailored to local priorities and conditions.

Food production plays a central role in the health of humanity and our environment. New Zealand produces a large amount of food, but it is unknown if it can produce enough of the right crops in the places to better the health of New Zealanders, profitably, while maintaining New Zealand's primary production exports and meeting ambitions to lower greenhouse gas (GHGs) emissions and nutrient losses to water. We tested two scenarios that aimed at delivering a healthy diet while maximising profit and minimising GHGs (climate‐focused scenario) or losses of nitrogen (N) and phosphorus (P) to water (freshwater‐focused scenario). Land use change was targeted to areas not currently meeting bottom lines for N or P loss but needed to spill over to other areas to meet dietary targets in both scenarios. The maximum cost of the required land use change was about 1% of the primary sector's export revenues, and orders of magnitude less than the estimated savings for the health system from an optimised diet. We conclude that shifting productive land uses can help meet environmental targets for GHGs, N and P while saving money and improving the health of its people.

An Interoperable Low-Code Modelling Framework for Integrated Spatial ModellingAlexander Herzig, Jan Zoerner, John Dymond, Hugh Smith, Chris PhillipsManaaki Whenua – Landcare Research New ZealandModelling complex environmental systems, such as earth surface processes, requires the representation and quantification of multiple individual but connected processes. In the Smarter Targeting Erosion Control (STEC) research programme, we are looking to improve understanding of where erosion occurs, how much and what type of sediment is produced and by which processes, how sediment moves through catchments, and how erosion and sediment transport can be targeted and mitigated cost-effectively. Different research groups involved in the programme will develop different model components representing different processes. To be able to assess the impact of sediment on water quality attributes in the river and for develop effective erosion control measures, the individual models need to be integrated to a composite model. In this paper we focus on the technical aspects and seamless integration of individual model components utilising the Basic Model Interface (BMI, Peckham et al. 2013) as interoperability standard and the extension of the LUMASS spatial modelling environment into a BMI-compliant model coupling framework. LUMASS provides a low-code visual development environment for building complex hierarchical system dynamics models that can be run in HPC environments and support sequential and parallel processing of large datasets. Each model developed in the framework can be exposed to other models and frameworks through the BMI-compliant LUMASS engine, without requiring any additional programming, thus greatly simplifying the development of interoperable model components. Here, we concentrate on the integration of BMI-compliant external model components and how they are coupled into the overall model structure. In the STEC programme, we use LUMASS for both the implementation of model components representing individual soil erosion processes, such as landslides, earthflows, and surficial erosion and for the integration (i.e. coupling) of other (external) BMI-compliant model components into a composite model. Using available (prototype) models we will demonstrate how LUMASS’ visual development environment can be used to build interoperable integrated component models with very little coding requirements. Peckham SD, Hutton EWH, Boyana N 2013. A Component-based approach to integrated modelling in the geosciences: The design of CSDMS. Computers & Geosciences 53: 3—12. http://dx.doi.org/10.1016/j.cageo.2012.04.002 LUMASS: https://bitbucket.org/landcareresearch/lumass 

SedNetNZ is used to model the effect of erosion control undertaken under the Sustainable Land Use Initiative (SLUI) and predict the effect of climate change on sediment load in the Manawatū–Whanganui region. Sediment load in 2004 is estimated at 13.4 Mt yr ⁻¹ ; by 2018, ≈5000 km ² of land had farm plans implemented and annual sediment load reduced by 6.2% of the 2004 load. If SLUI stops at the 2018 level of implementation, by 2038 it is predicted to achieve a 15.7% reduction in annual sediment load. If SLUI continues to implement farm plans, 7949 km ² of land will be treated by 2043 and annual sediment load could be reduced by a further 14.7%. Climate change is predicted to substantially increase sediment loads. By 2043 annual sediment load for the region is predicted to increase, compared to 2004, by between 8.3 and 23.7%. However, this can largely be offset by SLUI works. By 2090 an annual sediment load increase of between 53 and 224% due to climate change is predicted. The results suggest climate warming may dominate changes in sediment load in the future.

Irrigation schemes enable agricultural intensification or change to more profitable land uses, but may also lead to adverse environmental effects (e.g. nitrate leaching). Decision‐makers face the challenge of assessing potential intensification options and comparing their advantages and disadvantages. We used the Land‐Use Management Support System (LUMASS) to assess land‐use development scenarios for the potential irrigable areas Black Creek and White Rock in the Ruamahanga catchment. Our results show that intensification and expansion of dairy farming and arable cropping increased production levels, but also nitrate leaching and greenhouse gas emissions. A higher production increase was associated with a higher environmental footprint. However, increasing the number of land‐use conversion options reduced the environmental footprint while achieving the same agricultural production. Optimizing the match of land use and the landscape’s potential to provide ecosystem services increased the operating surplus while maintaining the environmental footprint. The presented modelling approach can provide decision‐makers with evidence‐based guidance for spatial planning and policy development on agricultural and environmental limits of land‐use development.