More Livestock, More Pollution?
New Zealand Faces a Hard Trade-Off
New Zealand, also called Aotearoa in Māori, is the second largest economy in Oceania, after Australia. Despite its small size, New Zealand is one of the world's top exporters of fruits such as kiwifruit and apples.
However, New Zealand’s most important products are derived from sheep and cattle, like beef, dairy products, and lamb meat. According to the OECD database, in 2020, around 43% of New Zealand's exports were sheep and cattle derivatives. The top traded commodity was concentrated milk, valued at 5.92 billion dollars.
China is the largest export destination of New Zealand: the recent economic boom of China has brought prosperity to New Zealand's primary industries, especially its dairy industry. The demand for dairy products in China has increased since China joined the WTO in 2001. Increasing incomes in China are also another factor driving increases in dairy demand.
However, the economic boom in the dairy production has generated increased concerns about environmental damage from livestock. Agriculture accounts for half of New Zealand greenhouse gas emissions, most of which is methane from livestock. Cattle digestion accounts for 32.5% of emissions, and sheep digestion contributes approximately 11.8% of the total emissions. Dairy cattle produce more methane than sheep and beef cattle.
In a previous Ag Data News article, Aaron wrote about a proposal to bring agriculture into the greenhouse gas Emissions Trade Scheme in 2025. Cattle and sheep farmers will face increasing costs under this proposal, although the proposed costs are low in the beginning.
Another source of pollution, especially in the recent two decades, is animal waste, which causes nitrate leaching into groundwater. Many rural areas in the South Island rely on either rain or stream water for daily uses. Contamination of the water source poses threats to the locals, especially during the dry season when rainwater is not constantly available.
Due to international demand for dairy products, the number of dairy cattle in New Zealand has doubled since 1971. From 1990 to 2019, Canterbury dairy cattle increased tenfold from 113,000 to 1.2 million (Stats NZ, 2021). Some smaller regions are catching up, such as Otago and Southland. Southland may be too cold to plant kiwifruit and apples, but it is suitable for growing grass. Between 1990 and 2019, Southland dairy cattle increased sixteen-fold (1,584 percent) from 38,000 to 636,000 (Stats NZ, 2021). Waikato is the top dairy region with the largest number of dairy cattle on its grassland.
The number of sheep decreased dramatically over the same period due to the removal of generous government support programs and the high profits available in dairy farming.
Since dairy cattle produce more pollutants than beef cattle and sheep, the change in livestock composition did not improve water quality. The number of dairy cattle per hectare has remained relatively constant since 2005, so the increase in the number of dairy cattle is the main driver of pollution.
Waikato and Canterbury are the regions most affected by nitrate pollution from dairy cows. These are the primary dairy production regions in New Zealand. Notably, there is a sharp increase in nitrate leaching in Canterbury, where dairy cattle have increased tenfold since 1990.
Note that the nitrate leaching data follow livestock numbers closely because leaching is estimated using a model that takes into account livestock numbers, climate, soil type, and irrigation.
New Zealand’s current government is determined to fight climate change and water pollution problems. The Essential Freshwater package, introduced in 2020, is targeted at water pollution, and entry into the Emission Trade Scheme is targeted of greenhouse gas emissions reduction.
Decision-makers in the Beehive face a tough trade-off between a better environment and economic prosperity. Although the current government favor stronger environmental regulation, a general election in 2023 may see the pendulum swing back the other way.
We made the last three graphs in this article using this R code.
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