Behind-the-Scenes: How We Decide What Land to Buy

In POST’s history, the way we make decisions about what land to purchase has changed quite a bit. Today, we face the ever-growing pressures of development, skyrocketing land costs and the need to prioritize acquisition opportunities across our working area. This is a tall order! Fortunately, there has been an explosion in the amount of environmental data available to us—and we have assembled an awesome team to harness this new power.

Two years ago, Annie Taylor (our former GIS Analyst), Dr. Peter Cowan (our Director of Conservation Science) and I set out on a mission to fine-tune our prioritization process to maximize POST’s impact in our region. Our work resulted in a tool we call our Conservation Prioritization Framework (CPF), and we depend on the CPF daily when making important decisions about land acquisition and stewardship. So, how was the CPF developed and how is it currently used?

Step 1: Data Collection

The first step in this process was to collect the most relevant environmental data. And lots of it. We gathered information about wildlife movement, public access and more.

For example, our region is prone to drought—so, how do we ensure that our lands are prepared for a drier climate in the future? For this, we use something called Climate Water Deficit (CWD) from the U.S. Geological Survey, which measures annual water loss (see below). In this map, the areas in red have higher annual water loss, and areas in blue have lower annual water loss. In general, CWD is a good way to determine how well an area will rebound from drought. At POST, we use it to look at everything from the estimated irrigation needs of crops to the sustainability of redwood forests that rely on the wet climate of the Santa Cruz Mountains to thrive.

Step 2: Stack the Data

The next step toward developing our CPF was to stack these datasets on top of one another. As data nerds, we think this part is really cool. We get to look across our entire landscape and prioritize critical areas where abundant water, wildlife corridors and scenic vistas overlap (to name a few). In total, our CPF uses 35 different datasets gathered from many sources.

Case Study: Gazos Creek Redwoods

To give you a sense of how the final CPF works, let’s focus in on our recent protection of 320 acres of redwood forest in San Mateo County (see right). Our data showed abundant native habitat there, and because it’s surrounded on three sides by a state park, it’s a likely home for all types of wildlife. We also found a .5 mile tributary of Gazos Creek flows through this property, a pristine stream corridor flowing within the Butano watershed.

In addition, our data revealed a healthy, relatively old redwood forest—these remaining giant trees create great habitat for the native flora and fauna that we love, and are also most likely to survive the stressors of a changing climate. With the help of our handy CPF, these data were brought to our attention and helped determine our strategy for protection.

The Big Picture:

We use the CPF differently for each of our programs, or areas of focus. For example, our Public Access program prioritization uses detailed trail data while our Wildlife Linkages program prioritization analyzes corridors for animal movement. Our CPF has proven to be an extremely versatile and powerful tool. It allows us to use the latest conservation science to narrow our focus on projects that will have the biggest impact on our region. Ultimately, our CPF helps us stay true to our mission.

I hope this article helps illustrate how our CPF is integral to POST’s decision-making process. It was written in collaboration with Annie Taylor, our former GIS Analyst who was a key player in developing our CPF. She recently joined the Department of Environmental Science, Policy, and Management at the University of California Berkeley to pursue a PhD and continue her passion for data. We miss her!