Conservation Versus Jobs?
The problem
A couple weeks ago I read Patagonia's book Tools for Grassroots Activists and a line jumped off the page from the chapter written by Headwaters Economics. "During the last forty years, rural western counties with more than 30% of the county's land base in federal protected status created jobs four times faster than rural western counties without federal protected lands."
Intrigued and intent to add more spatial analysis to my toolbox, I set out to re-create the analysis. Could access to public land be part of the competitive advantage for rural communities across the West? If so, there's an interesting story of economic and conservation success happening in tandem.
Approach
That's exactly what I found; operation recreate-the-analysis was a success! Rural counties with the highest ratio of federally protected areas created jobs four times faster than counties with the lowest ratio of protected areas.
I riffed on the Headwaters approach a bit and segmented the counties into three groups according to the percent of their total area in federal protected status:
High: more than 20% of the county's land base in federal protected status
Medium: 10.01% - 20%
Low: Less than 10%
Compared to the Low group, the Medium group created jobs 3.3 times faster and the High group created jobs 1.5 times faster. Fascinating.
To expand on the backstory and methods a bit more, I first pulled together county-level economic and population data from 2001-2021 from the U.S. Census and Bureau of Economic Analysis, along with counties (Data.gov) and federally protected area (both land and water) across the West (USGS PAD-US 3.0 database): Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, and Wyoming. I also separated “rural” from “metro” counties according to the US Dept of Agriculture Economic Research Service’s Rural Continuum (RUC) Codes.
According to this classification, rural counties must include some combination of:
Open countryside
Rural towns (places with fewer than 2,500 people)
Urban areas with populations ranging from 2,500 to 49,999 that are not part of larger labor market areas (metropolitan areas).
I first brought all the data from the Census, BEA, and US Dept of Ag together in Python, removing extraneous variables to this analysis and filtering the data to just rural counties in the West.
I calculated the jobs-per-100k people for each rural county and year to normalize the comparison across counties of wildly different populations. Then I found the growth rate of jobs-per-100k people for each county and averaged this for each of the three groups of counties detailed above.
Then, I brought the data into ArcGIS and conducted a spatial analysis to determine the overlap ratio of federally protected areas in each county relative to the total county area.
To determine the height of each county and achieve the 3D effect, I elevated the county’s polygon according the 20-year average job growth rate for the group (High, Medium, or Low) it belonged to. In this height calculation I multiplied each of these group average job growth rates by a constant in order to convey the differences between groups at the extremely zoomed-out scale I wanted to use in this map.
Lastly, it would be interesting to look into what kinds of jobs are shaping this overall pattern (e.g. service jobs? White-collar jobs? Manufacturing jobs?), and to see the more nuanced story that could be uncovered by looking at the specifics driving this top-line insight.
This was a pretty fascinating project to stretch my skills in Python, ArcGIS, and cartography overall while exploring how protected lands & waters can be part of the competitive advantage for Western communities looking to expand economic opportunities and attract talent.
Skills
Data analysis in R Studio and ArcGIS Pro
Spatial analysis
Some light cartography in the design choices used for displaying the data
Results
None of note but it was a fun side project for a couple days!
