High-resolution estimates of land protection costs for "30 by 30" conservation planning: towards better global maps
Presented by:
Christoph Nolte
Department of Earth and Environment
Boston University
Friday, October 15, 2021
12:00 pm-1:15 pm
Taylor-Hibbard Seminar Room (Rm103)
Online - https://go.wisc.edu/esfdvx
The Biden administration aims to protect 30% of U.S. lands by 2030 ("30 by 30") to combat climate change and mass extinctions. Signatories to the Conservation of Biological Diversity will likely adopt the same goal at the next Conference of the Parties in Kunming in 2022. These ambitious targets raise an important question: which 30% should be protected? Systematic conservation planning methods can identify spatial protection portfolios that achieve fixed conservation targets at the lowest social cost, or that return the highest conservation benefits for a given budget. However, as academics and governments begin to apply these methods to "30 by 30" analyses, the lack of high-quality estimates of land protection cost is a major data constraint. In this talk, Nolte provides an overview of existing approaches and datasets to estimate protection cost at global and national scales and at the spatial resolutions needed for policy decisions. Validation against observed cost data from six thousand publicly funded conservation acquisitions in the U.S. and Colombia indicates that the use of low-quality cost proxies in published high-profile analyses produces misleading findings. Better cost estimates can be obtained by training simple machine learning algorithms on property sales observations with rich information on biogeophysical and social characteristics. However, leveraging the potential of these approaches to develop cost layers for large-scale conservation planning can introduce new biases, and requires access to large-scale real estate datasets (such as Zillow's ZTRAX in the U.S.) or major investments in collecting public sales data (Colombia).