Current (2019) % of Area
Future (2050) % of Area
Using extremely approximate modeling, this tool looks at where different kinds of crops are grown today in California (2019) and under what climate conditions (temperature, precipitation). Then, using the HADGEM2 climate model via Cal-Adapt, it uses machine learning to very approximately guess where the same kinds of crops may be grown (areas with similar climate conditions). With this information, it divides up the agriculture-use land between crop types in simulations for 2019 and 2050.
Specifically, this shows the distribution of each crop type's amenable area in 2019 and what the percent distribution of that crop type's amenable area may look like in 2050.
| % of crop type's amenable area | 0% | 2% | 4% | 6% | 8% |
This doesn't display yields: all of the circles before and after add up to 100% of a crop type's allocated amenable area in a simulation. This is because this simulation doesn't assume 2kg of leafy greens are "worth" twice as much as 1kg of berries. Also, in reality, there are other factors at play in choosing where to grow. So, these are places where it (likely) may be grown from a climate perspective not where it actually is in 2019 or actually will be grown in 2050.
Note that this is a toy model with just two variables. It is likely is wrong in many ways and has a number of limitations. For example, it assumes locations of agriculture-use land will be the same in the future as they are today. Furthermore, it does not assume changes in farming practices such as a change to controlled agriculture and it doesn't consider infrastructure. In short, it just considers where crop types may shift to achieve more similar growing conditions (temperature, precipitation) to the past with recognition that "new" land cannot be created (all the crop types are "competing" for the same area).