Spatial and Temporal Responses to an Emissions Trading Scheme Covering Agriculture and Forestry: Simulation Results from New Zealand

Kerr, Suzi; Anastasiadis, Simon; Olssen, Alex; Power, William; Tímár, Levente; Zhang, Wei

doi:10.3390/f3041133

Cited by 17 publications

(7 citation statements)

References 17 publications

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“…In order to partition the country into biomes approximating the five categories available in Biome-BGC and then mask and sum the NEP contributions from each biome, we produced a land-cover and land-use (LCLU) map. The LCLU map uses 10 categories based on a combination of the land-cover database (LCDB) for New Zealand (Shepherd and Newsome, 2009;Dymond et al, 2012) and the Land-Use in Rural New Zealand (LURNZ) model (Hendy et al, 2007;Timar, 2011;Kerr et al, 2012). The New Zealand LCDB is a thematic classification of land-cover and land-use categories, created using satellite imagery and covering all of mainland New Zealand.…”

Section: Terrestrialmentioning

confidence: 99%

Atmospheric CO<sub>2</sub> observations and models suggest strong carbon uptake by forests in New Zealand

et al. 2017

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Abstract. A regional atmospheric inversion method has been developed to determine the spatial and temporal distribution of CO 2 sinks and sources across New Zealand for 2011-2013. This approach infers net air-sea and air-land CO 2 fluxes from measurement records, using back-trajectory simulations from the Numerical Atmospheric dispersion Modelling Environment (NAME) Lagrangian dispersion model, driven by meteorology from the New Zealand Limited Area Model (NZLAM) weather prediction model. The inversion uses in situ measurements from two fixed sites, Baring Head on the southern tip of New Zealand's North Island (41.408 • S, 174.871 • E) and Lauder from the central South Island (45.038 • S, 169.684 • E), and ship board data from monthly cruises between Japan, New Zealand, and Australia. A range of scenarios is used to assess the sensitivity of the inversion method to underlying assumptions and to ensure robustness of the results. The results indicate a strong seasonal cycle in terrestrial land fluxes from the South Island of New Zealand, especially in western regions covered by indigenous forest, suggesting higher photosynthetic and respiratory activity than is evident in the current a priori land process model. On the annual scale, the terrestrial biosphere in New Zealand is estimated to be a net CO 2 sink, removing 98 (±37) Tg CO 2 yr −1 from the atmosphere on average during 2011-2013. This sink is much larger than the reported 27 Tg CO 2 yr −1 from the national inventory for the same time period. The difference can be partially reconciled when factors related to forest and agricultural management and exports, fossil fuel emission estimates, hydrologic fluxes, and soil carbon change are considered, but some differences are likely to remain. Baseline uncertainty, model transport uncertainty, and limited sensitivity to the northern half of the North Island are the main contributors to flux uncertainty.

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Section: Terrestrialmentioning

confidence: 99%

Atmospheric CO<sub>2</sub> observations and models suggest strong carbon uptake by forests in New Zealand

et al. 2017

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“…In our analysis, the total amount of forest land is exogenous, and we only consider the allocation of this land between production and permanent forests. Focussing on the decision to convert production forests into permanent forests at harvesting age is supported by the research by Kerr et al (2012), which found that the change in land use from other types of agriculture into forestry as incentivised by the carbon price is negligible. Additionally, if any land use change occurs between production and permanent forests at afforestation, it will not affect the creation of carbon permits for 23 years due to the crossover between stocktake and averaging accounting.…”

Section: The Forestry Model: Energy and Emissions In New Zealand (Enz)mentioning

confidence: 99%

“…They found that less productive forestry regions are the most efficient land areas to transition to permanent forests when the carbon price increases. Kerr et al (2012) estimated the expected land use change elasticities between different agricultural land uses. They found a relatively low level of land use change to forestry from agriculture under the NZ ETS.…”

Section: Introductionmentioning

confidence: 99%

Logs or permits? Forestry land use decisions in an emissions trading scheme

White,

Winchester

2023

Aus J Agri & Res Econ

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Negative carbon emissions options are required to meet long‐term climate goals in many countries. One way to incentivise these options is by paying farmers for carbon sequestered by forests through an emissions trading scheme (ETS). New Zealand has a comprehensive ETS, which includes incentives for farmers to plant permanent exotic forests. This research uses an economy‐wide model, a forestry model and land use change functions to measure the expected proportion of farmers with trees at harvesting age that will change land use from production to permanent forests in New Zealand from 2014 to 2050. We also estimate the impacts on carbon sequestration, the carbon price, gross emissions, GDP and welfare. When there is forestry land use change, the results indicate that the responsiveness of land owners to the carbon price has a measured impact on carbon sequestration. For example, under the fastest land use change scenario, carbon sequestration reaches 29.93 Mt CO2e by 2050 compared to 23.41 Mt CO2e in the no land use change scenario (a 28% increase). Even under the slowest land use change scenario, carbon sequestration is 25.89 Mt CO2e by 2050 (an 11% increase compared with no land use change). This is because, if foresters decide not to switch to permanent forests in 1 year, carbon prices and ultimately incentives to convert to permanent forests will be higher in future years.

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“…The LURNZ model (Hendy et al, 2007Timar, 2011;Kerr et al, 2012) was developed to explain and simulate changes in four major rural land-use types in New Zealand: dairy, sheep and beef, plantation forestry and regenerating natural forest (henceforth termed scrubland). LURNZ models land use both dynamically, based on national time-series econometric estimates of land-use change, and spatially, based on crosssectional observations of biophysical and socio-economic land attributes.…”

Section: Lurnz Modelmentioning

confidence: 99%

Grassland production under global change scenarios for New Zealand pastoral agriculture

et al. 2014

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Abstract. We adapt and integrate the Biome-BGC and Land Use in Rural New Zealand models to simulate pastoral agriculture and to make land-use change, intensification of agricultural activity and climate change scenario projections of New Zealand's pasture production at time slices centred on 2020, 2050 and 2100, with comparison to a present-day baseline. Biome-BGC model parameters are optimised for pasture production in both dairy and sheep/beef farm systems, representing a new application of the Biome-BGC model. Results show up to a 10 % increase in New Zealand's national pasture production in 2020 under intensification and a 1-2 % increase by 2050 from economic factors driving land-use change. Climate change scenarios using statistically downscaled global climate models (GCMs) from the IPCC Fourth Assessment Report also show national increases of 1-2 % in 2050, with significant regional variations. Projected out to 2100, however, these scenarios are more sensitive to the type of pasture system and the severity of warming: dairy systems show an increase in production of 4 % under mild change but a decline of 1 % under a more extreme case, whereas sheep/beef production declines in both cases by 3 and 13 %, respectively. Our results suggest that high-fertility systems such as dairying could be more resilient under future change, with dairy production increasing or only slightly declining in all of our scenarios. These are the first nationalscale estimates using a model to evaluate the joint effects of climate change, CO 2 fertilisation and N-cycle feedbacks on New Zealand's unique pastoral production systems that dominate the nation's agriculture and economy. Model results emphasise that CO 2 fertilisation and N-cycle feedback effects are responsible for meaningful differences in agricultural systems. More broadly, we demonstrate that our model output enables analysis of decoupled land-use change scenarios: the Biome-BGC data products at a national or regional level can be re-sampled quickly and cost-effectively for specific land-use change scenarios and future projections.

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Spatial and Temporal Responses to an Emissions Trading Scheme Covering Agriculture and Forestry: Simulation Results from New Zealand

Cited by 17 publications

References 17 publications

Atmospheric CO<sub>2</sub> observations and models suggest strong carbon uptake by forests in New Zealand

Atmospheric CO<sub>2</sub> observations and models suggest strong carbon uptake by forests in New Zealand

Logs or permits? Forestry land use decisions in an emissions trading scheme

Grassland production under global change scenarios for New Zealand pastoral agriculture

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Spatial and Temporal Responses to an Emissions Trading Scheme Covering Agriculture and Forestry: Simulation Results from New Zealand

Cited by 17 publications

References 17 publications

Atmospheric CO&lt;sub&gt;2&lt;/sub&gt; observations and models suggest strong carbon uptake by forests in New Zealand

Atmospheric CO&lt;sub&gt;2&lt;/sub&gt; observations and models suggest strong carbon uptake by forests in New Zealand

Logs or permits? Forestry land use decisions in an emissions trading scheme

Grassland production under global change scenarios for New Zealand pastoral agriculture

Contact Info

Product

Resources

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Atmospheric CO<sub>2</sub> observations and models suggest strong carbon uptake by forests in New Zealand

Atmospheric CO<sub>2</sub> observations and models suggest strong carbon uptake by forests in New Zealand