grassland production under global change scenarios for new zealand pastoral agriculture
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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 national-scale estimates using a
model to evaluate the joint effects of climate change, CO2 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 CO2 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.
| Reference Key |
keller2014geoscientificgrassland
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|---|---|
| Authors | ;E. D. Keller;W. T. Baisden;L. Timar;B. Mullan;A. Clark |
| Journal | international journal of quantum chemistry |
| Year | 2014 |
| DOI |
10.5194/gmd-7-2359-2014
|
| URL | |
| Keywords |
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