Why We Need Animal Agriculture Data
If we want to combat climate change and create a fair food system, many researchers say we need to drastically decrease the size of the animal agriculture industry. Even so, the industry continues to grow across the world. In this paper, researchers discuss what research approaches would help reduce our reliance on animal agriculture. Overall, they argue that we need both better data and more accurate models of the consequences of various dietary changes.
First, we need more research on the effects of dietary change on “planetary health,” which combines human health and the health of the planet. So far, planetary health work has mostly focused on how a global dietary shift would affect ecological and human health outcomes. However, researchers haven’t explored the ways that changes to a specific process (such as supply chain management) would affect economic, environmental, and human health outcomes.
Some changes might pose tradeoffs between important goals, while others might have benefits in multiple areas at once. Researchers also haven’t looked at the way the models might be different in different places (e.g., cities vs. rural areas) or times (e.g., right now vs. the year 2100). Policymakers need more specific models to help them decide how best to change their countries’ dietary habits.
Second, we need better data on the role that animal products play in our society and in nature. We don’t have data about a lot of things we care about. Even when we do, the data is often sparse. For example, we might have country-level data but not city-level data. For example, we have a lot of country-level data about the production and consumption of animal products, but it’s usually not broken down by region.
We also don’t know whether the data are measuring the things we care about. For example, we don’t have a good way of measuring soil health, and have to use measures like soil erosion which don’t capture important information. Sometimes people develop indicators that synthesize many different factors we care about: for example, a measurement of the greenhouse gas emissions of all animal agriculture. These indicators can be more confusing than helpful because the creators had to make many judgment calls that aren’t necessarily obvious to the reader.
We understand the effects of animal products on nature better than we understand their effects on humans. We’re missing basic data, such as what people want to eat, when and how they eat particular foods, and whether various jobs in animal agriculture are exploitative of their workers. Our measures of food security also don’t go back very far, so we don’t have a great sense of how it’s changed over time. We don’t know which economic factors affect how farmers decide how to use their land, and therefore we don’t know how the transition away from animal agriculture would change their land use decisions.
Third, the researchers note that we need more analysis of ways in which we could transform the food system. Developing a “baseline” scenario where nothing changes about our diets can help us measure change. The world isn’t static, so researchers’ models of the effects of dietary change should incorporate information from other models of future change, such as models of climate change and global development. These models should account for all the different kinds of animal agriculture, including different animals (cows, pigs, etc.) and different systems (pastoral, industrial, etc.). In that way, models can predict what would happen if specific changes were made, instead of just modeling an overall decrease in meat consumption.
Finally, the authors note that we need to know how to judge the consequences of possible future scenarios. We’ll need to plan for potential trade-offs, like the unemployment of the 1.3 billion people who work in animal agriculture globally. It’s possible that the loss of these jobs would make income inequality worse. Understanding the likely effects of a transition away from animal agriculture on jobs will also help us understand which scenarios are likely to get political support. We can also think about how our scenarios might affect human health. People in developing countries often rely on animal products to get key nutrients, especially protein, while people in developed countries eat more animal products than is optimal for their health.
This study makes it clear that when it comes to reducing our reliance on animal agriculture, advocates need more data on a variety of topics. Furthermore, when presenting our data, we should make sure that we’re exploring all avenues and being as transparent as possible. While removing animals from the food system is the goal, we must account for all the ways to do it — and all the consequences once we do.