Many recent studies (such as ones I have published recently) identify where it would be optimal to locate conservation and/or agriculture. These studies produce “land-use decision maps” that use high-resolution remote sensing data to identify specific grid-cells where it would be optimal to change current land use (see the image below for an example). These studies only describe what the best arrangement of land uses would be but do not discuss how they could be implemented under current policy contexts. In my job market paper, I define a spatially-explicit auction mechanism and payments for ecosystem service policy that implements a global land-use decision map.

Where should we prioritize conservation spending?

The image below shows the priority we should assign to different grid-cells if we want to minimize carbon-storage loss while still producing enough food to meet agricultural demand in 2050. This priority is based on calculating the net marginal benefit of conservation per agricultural profit forgone (NMB), which was used in a spatially-explicit optimization. In short, this map shows where it is best to protect land while not undermining food security goals.

How much should money should we offer?

Just knowing where we should protect is not enough. To implement a decision map via payments for ecosystem services, we need to know exactly how much we should offer landowners to conserve their land. The image below shows a key result from the forthcoming paper, indicating how much should be allocated per hectare to each 10 by 10 km grid-cell. The values shown represent the best set of payments to offer if one optimally allocated a $100 billion conservation investment. Optimized payments can also be found for smaller budgets or specific regions.

Will landowners actually participate?

The decision to participate in a payments for ecosystem service program depends on if the value received is higher than the next best alternative (which is usually agriculture). But, the opportunity cost of agriculture is usually private information. How can we create a payments program that optimizes payments if we don’t have this information? In the paper, I present a sealed-bid auction that elicits truthful revelation of opportunity cost from land-owners, allowing payments to be set at just the right amount. This allows for dramatic cost-reductions in conservation investment.

Application to current decisions

These results are ready for implementation and can be used to guide current decision making processes. To assist in the use of these results, I have created a software application (produced as a desktop application and a phone app) that allows decision makers to input a specific budget and area of interest and generate a set of spatially-explicit, optimized payments. The code is currently open-source and available for download on bitbucket at https://bitbucket.org/jandrewjohnson/ffn/overview. Final release of the software will coincide with the publication of the paper.