How Oil & Gas Drilling Impacts the Endangered Greater Sage Grouse and Lesser Prairie-Chicken
By Ted Auch
The New York Times' Diane Cardwell and Clifford Krauss recently published a piece on the interaction between the Greater Sage Grouse (GSG, Centrocercus urophasianus) and fracking in Big Sky country. We thought it might be helpful to dig a little deeper into the issue given the sensitivity of this species' as well as the Lesser Prairie-Chicken (Tympanuchus pallidicinctus) to habitat disturbance and the inevitable conflict between “energy independence" and the Endangered Species Act—the purpose of which “is to protect and recover imperiled species and the ecosystems upon which they depend."
Gunnison Sage Grouse
We looked at the GSG's range relative to hydrocarbon wells in Colorado and Wyoming keeping in mind the bird's range encompasses 11 states and “more than 165 million resource-rich acres." This analysis encompasses much of the bird's range accounting for 52 percent (134,149 square miles) of the aforementioned acreage (Figures 1 and 2) and 37 and 373 GSG habitat parcels in Wyoming and Colorado, respectively.
The largest shaded areas on the map are the bird's “Current Distribution" (67,879 square miles) in Wyoming and “Historic Habitat" in Colorado (24,505 square miles). GSG's range in Colorado is far more spread out than in Wyoming with discrete north- and southwest concentrations. Important Birding Areas (IBAs) as defined by the Audubon Society often overlap with oil and gas extraction sites as well as endangered species habitat. Thanks to the Audubon Society's Connie Sanchez and Tom Auer we were able to determine how many hydrocarbon production wells exist within these states' IBA parcels. Wyoming is home to 39 IBAs, while Colorado contains 53 of these designated parcels. The average Wyoming IBA is 257 square miles, however, while Colorado's average 59 mi2. In total these two states are home to 13,154 mi2worth of IBAs. These figures account for 3.7 percent of U.S. IBAs and 2.2 percent of IBA acreage.
1. Wyoming: 51 unconventional hydrocarbon wells in IBAs, 2,238 in primary GSG habitat, and for some perspective 1,983 of the latter are in what EIA has designated primary shale plays. At the present time 97 percent of Wyoming's production wells lie within some segment of the GSG's habitat.
2. Colorado: 163 unconventional hydrocarbon wells in IBAs
- Southwest: 7,838 wells in primary GSG habitat
- Northwest: 16,609 wells in primary GSG habitat
- EIA Shale Plays: 24,178 wells
- 53 percent of Colorado's production wells lie within some segment of the state's GSG habitat.
In Colorado, the GSG's historical habitat has already been overrun by hydrocarbon wells with 20,809 across the bird's north- and southwest range. The bird's production/brooding area in the northwest contains 1,142 wells while its winter range contains 662 wells.
Figure 2. Wyoming hydrocarbon production laterals and Greater Sage Grouse Habitat.
Table 2. Colorado hydrocarbon production wells in various sectors of the Greater Sage Grouse's range.
Another way to look at the interaction between hydrocarbon production and GSG in the Great Plains and Pacific Northwest is to investigate the density of wells in the bird's historic range. That is precisely what we did for the 16 states where GSG once roamed. The bird's historic range is 2.21 times the size of its current range, while the acreage we analyzed is slightly more than the often-reported “165 million resource-rich acres" (Cardwell and Krauss, 2014). On average each of the 16 states was home to 35,580 square miles of GSG habitat and are now home to a mere 28 percent of that figure.
While GSG habitat in these states has decreased, hydrocarbon production has skyrocketed. There are currently 153,358 hydrocarbon wells across the 16 states and an average of 12,780 wells per state—excluding the four states devoid of wells in GSG habitat. These wells and associated infrastructure occupy approximately 39,649 square miles which is a disturbing 7 percent of the species' historic range and nearly 15 percent of its current range. From an historic GSG range perspective, Kansas has the highest density of wells with 3.5 per square mile of habitat. Unsurprisingly North Dakota, has the highest density of wells in the bird's current range, with 6.1 wells per square mile of habitat. Colorado was second in both departments with 1.1 and 2.9 wells per square mile of historic and current GSG habitat, respectively.
The Lesser Prairie-Chicken (LPC)—along with GSG—is hardly what anyone would call charismatic mega-fauna but it's habitat is coming under pressure in the name of drill baby drill “energy independence" across many of the same Great Plains states. The Prairie-Chicken's range once spread across 97,977 square miles in five states with 43 percent of that acreage in Kansas alone. The bird's range has declined by 68 percent and as much as 78-79 percent in Colorado and New Mexico. In terms of US hydrocarbon production the Prairie-Chicken's historic range is home to 58,152 wells, while its current extent contains 22,049 wells.
On average the four states we investigated sans Texas contain 14,538 and 5,512 wells in this bird's historic and current range, respectively, with the largest values for both not surprisingly in the state that contains most of the bird's primary grassland habitat Kansas's southwest corner. Across these states the density of wells in Prairie-Chicken habitat is 0.603-0.682 hydrocarbon wells per square mile with as many as 1.06-1.25 wells per square mile of Prairie-Chicken habitat in New Mexico. These wells and related infrastructure have an approximate footprint of 22,378 square miles, which is 23 percent the LPC's historic range and 72 percent of its current range.
The five states that contain LPC habitat are also home to 2,978 square miles worth of IBAs across ten parcels averaging 596 square miles, with Kansas home to the most IBA acreage (1,793,845 acres) and New Mexico the most parcels (4 parcels). These values equate to 0.40 percent of US IBAs and 0.99 percent of IBA acreage.
What this analysis means for the GSG and LPC is hard to discern. It stands to reason, however, that their already sensitive mating behavior and plummeting/disconnected populations have not seen the last of energy independence's encroachment. In contrast to the well-noted battle in the Pacific Northwest between environmentalists, loggers, developers and cattle grazers over the much smaller range of the Spotted Owl—and the US Fish and Wildlife Service's “"God Committee"—the GSG's range includes much of the U.S.'s primary wind and mineral resource acreage. GSG's habitat requirements overlap with US shale resources in a significant way with 29 percent of its range in shale basins and 11 percent in currently active shale plays. For a more detailed legal perspective on this issue the reader is referred to our friends at the Center for Biological Diversity and their long-term commitment to protecting and increasing suitable GSG habitat.
Meanwhile the historic and current range of the LPC is like the Spotted Owl in that it is quite small amounting to 97,978 and 31,237 square miles, respectively, which is approximately 11-17 percent of the GSG's range. Similar to GSG we found that 31 percent of LPC's historic range lies within shale basins while only percentage of its habitat is within currently active shale gas plays.
Table 3. Historic and Current Range of Greater Sage Grouse along with the number of producing hydrocarbon wells in that range by state.
Table 4. Historic and Current Range of Lesser Prairie-Chicken along with the number of producing hydrocarbon wells in that range by state (Note: Texas well location data is not available at the present time).
Table 5. Square mileage and number of Important Birding Areas (IBAs) in the Lesser Prairie-Chicken's historic range.
You Might Also Like
A rare yellow penguin has been photographed for what is believed to be the first time.
- World-Renowned Photographer Documents Most Remote ... ›
- This Penguin Colony Has Fallen by 77% on Antarctic Islands ... ›
EcoWatch Daily Newsletter
By Stuart Braun
We spend 90% of our time in the buildings where we live and work, shop and conduct business, in the structures that keep us warm in winter and cool in summer.
But immense energy is required to source and manufacture building materials, to power construction sites, to maintain and renew the built environment. In 2019, building operations and construction activities together accounted for 38% of global energy-related CO2 emissions, the highest level ever recorded.
- Could IKEA's New Tiny House Help Fight the Climate Crisis ... ›
- Los Angeles City-Owned Buildings to Go 100% Carbon Free ... ›
- New Jersey Will Be First State to Require Building Permits to ... ›
By Eric Tate and Christopher Emrich
Disasters stemming from hazards like floods, wildfires, and disease often garner attention because of their extreme conditions and heavy societal impacts. Although the nature of the damage may vary, major disasters are alike in that socially vulnerable populations often experience the worst repercussions. For example, we saw this following Hurricanes Katrina and Harvey, each of which generated widespread physical damage and outsized impacts to low-income and minority survivors.
Mapping Social Vulnerability<p>Figure 1a is a typical map of social vulnerability across the United States at the census tract level based on the Social Vulnerability Index (SoVI) algorithm of <a href="https://onlinelibrary.wiley.com/doi/abs/10.1111/1540-6237.8402002" target="_blank"><em>Cutter et al.</em></a> . Spatial representation of the index depicts high social vulnerability regionally in the Southwest, upper Great Plains, eastern Oklahoma, southern Texas, and southern Appalachia, among other places. With such a map, users can focus attention on select places and identify population characteristics associated with elevated vulnerabilities.</p>
Fig. 1. (a) Social vulnerability across the United States at the census tract scale is mapped here following the Social Vulnerability Index (SoVI). Red and pink hues indicate high social vulnerability. (b) This bivariate map depicts social vulnerability (blue hues) and annualized per capita hazard losses (pink hues) for U.S. counties from 2010 to 2019.<p>Many current indexes in the United States and abroad are direct or conceptual offshoots of SoVI, which has been widely replicated [e.g., <a href="https://link.springer.com/article/10.1007/s13753-016-0090-9" target="_blank"><em>de Loyola Hummell et al.</em></a>, 2016]. The U.S. Centers for Disease Control and Prevention (CDC) <a href="https://www.atsdr.cdc.gov/placeandhealth/svi/index.html" target="_blank">has also developed</a> a commonly used social vulnerability index intended to help local officials identify communities that may need support before, during, and after disasters.</p><p>The first modeling and mapping efforts, starting around the mid-2000s, largely focused on describing spatial distributions of social vulnerability at varying geographic scales. Over time, research in this area came to emphasize spatial comparisons between social vulnerability and physical hazards [<a href="https://doi.org/10.1007/s11069-009-9376-1" target="_blank"><em>Wood et al.</em></a>, 2010], modeling population dynamics following disasters [<a href="https://link.springer.com/article/10.1007%2Fs11111-008-0072-y" target="_blank" rel="noopener noreferrer"><em>Myers et al.</em></a>, 2008], and quantifying the robustness of social vulnerability measures [<a href="https://doi.org/10.1007/s11069-012-0152-2" target="_blank" rel="noopener noreferrer"><em>Tate</em></a>, 2012].</p><p>More recent work is beginning to dissolve barriers between social vulnerability and environmental justice scholarship [<a href="https://doi.org/10.2105/AJPH.2018.304846" target="_blank" rel="noopener noreferrer"><em>Chakraborty et al.</em></a>, 2019], which has traditionally focused on root causes of exposure to pollution hazards. Another prominent new research direction involves deeper interrogation of social vulnerability drivers in specific hazard contexts and disaster phases (e.g., before, during, after). Such work has revealed that interactions among drivers are important, but existing case studies are ill suited to guiding development of new indicators [<a href="https://doi.org/10.1016/j.ijdrr.2015.09.013" target="_blank" rel="noopener noreferrer"><em>Rufat et al.</em></a>, 2015].</p><p>Advances in geostatistical analyses have enabled researchers to characterize interactions more accurately among social vulnerability and hazard outcomes. Figure 1b depicts social vulnerability and annualized per capita hazard losses for U.S. counties from 2010 to 2019, facilitating visualization of the spatial coincidence of pre‑event susceptibilities and hazard impacts. Places ranked high in both dimensions may be priority locations for management interventions. Further, such analysis provides invaluable comparisons between places as well as information summarizing state and regional conditions.</p><p>In Figure 2, we take the analysis of interactions a step further, dividing counties into two categories: those experiencing annual per capita losses above or below the national average from 2010 to 2019. The differences among individual race, ethnicity, and poverty variables between the two county groups are small. But expressing race together with poverty (poverty attenuated by race) produces quite different results: Counties with high hazard losses have higher percentages of both impoverished Black populations and impoverished white populations than counties with low hazard losses. These county differences are most pronounced for impoverished Black populations.</p>
Fig. 2. Differences in population percentages between counties experiencing annual per capita losses above or below the national average from 2010 to 2019 for individual and compound social vulnerability indicators (race and poverty).<p>Our current work focuses on social vulnerability to floods using geostatistical modeling and mapping. The research directions are twofold. The first is to develop hazard-specific indicators of social vulnerability to aid in mitigation planning [<a href="https://doi.org/10.1007/s11069-020-04470-2" target="_blank" rel="noopener noreferrer"><em>Tate et al.</em></a>, 2021]. Because natural hazards differ in their innate characteristics (e.g., rate of onset, spatial extent), causal processes (e.g., urbanization, meteorology), and programmatic responses by government, manifestations of social vulnerability vary across hazards.</p><p>The second is to assess the degree to which socially vulnerable populations benefit from the leading disaster recovery programs [<a href="https://doi.org/10.1080/17477891.2019.1675578" target="_blank" rel="noopener noreferrer"><em>Emrich et al.</em></a>, 2020], such as the Federal Emergency Management Agency's (FEMA) <a href="https://www.fema.gov/individual-disaster-assistance" target="_blank" rel="noopener noreferrer">Individual Assistance</a> program and the U.S. Department of Housing and Urban Development's Community Development Block Grant (CDBG) <a href="https://www.hudexchange.info/programs/cdbg-dr/" target="_blank" rel="noopener noreferrer">Disaster Recovery</a> program. Both research directions posit social vulnerability indicators as potential measures of social equity.</p>
Social Vulnerability as a Measure of Equity<p>Given their focus on social marginalization and economic barriers, social vulnerability indicators are attracting growing scientific interest as measures of inequity resulting from disasters. Indeed, social vulnerability and inequity are related concepts. Social vulnerability research explores the differential susceptibilities and capacities of disaster-affected populations, whereas social equity analyses tend to focus on population disparities in the allocation of resources for hazard mitigation and disaster recovery. Interventions with an equity focus emphasize full and equal resource access for all people with unmet disaster needs.</p><p>Yet newer studies of inequity in disaster programs have documented troubling disparities in income, race, and home ownership among those who <a href="https://eos.org/articles/equity-concerns-raised-in-federal-flood-property-buyouts" target="_blank">participate in flood buyout programs</a>, are <a href="https://www.eenews.net/stories/1063477407" target="_blank" rel="noopener noreferrer">eligible for postdisaster loans</a>, receive short-term recovery assistance [<a href="https://doi.org/10.1016/j.ijdrr.2020.102010" target="_blank" rel="noopener noreferrer"><em>Drakes et al.</em></a>, 2021], and have <a href="https://www.texastribune.org/2020/08/25/texas-natural-disasters--mental-health/" target="_blank" rel="noopener noreferrer">access to mental health services</a>. For example, a recent analysis of federal flood buyouts found racial privilege to be infused at multiple program stages and geographic scales, resulting in resources that disproportionately benefit whiter and more urban counties and neighborhoods [<a href="https://doi.org/10.1177/2378023120905439" target="_blank" rel="noopener noreferrer"><em>Elliott et al.</em></a>, 2020].</p><p>Investments in disaster risk reduction are largely prioritized on the basis of hazard modeling, historical impacts, and economic risk. Social equity, meanwhile, has been far less integrated into the considerations of public agencies for hazard and disaster management. But this situation may be beginning to shift. Following the adage of "what gets measured gets managed," social equity metrics are increasingly being inserted into disaster management.</p><p>At the national level, FEMA has <a href="https://www.fema.gov/news-release/20200220/fema-releases-affordability-framework-national-flood-insurance-program" target="_blank">developed options</a> to increase the affordability of flood insurance [Federal Emergency Management Agency, 2018]. At the subnational scale, Puerto Rico has integrated social vulnerability into its CDBG Mitigation Action Plan, expanding its considerations of risk beyond only economic factors. At the local level, Harris County, Texas, has begun using social vulnerability indicators alongside traditional measures of flood risk to introduce equity into the prioritization of flood mitigation projects [<a href="https://www.hcfcd.org/Portals/62/Resilience/Bond-Program/Prioritization-Framework/final_prioritization-framework-report_20190827.pdf?ver=2019-09-19-092535-743" target="_blank" rel="noopener noreferrer"><em>Harris County Flood Control District</em></a>, 2019].</p><p>Unfortunately, many existing measures of disaster equity fall short. They may be unidimensional, using single indicators such as income in places where underlying vulnerability processes suggest that a multidimensional measure like racialized poverty (Figure 2) would be more valid. And criteria presumed to be objective and neutral for determining resource allocation, such as economic loss and cost-benefit ratios, prioritize asset value over social equity. For example, following the <a href="http://www.cedar-rapids.org/discover_cedar_rapids/flood_of_2008/2008_flood_facts.php" target="_blank" rel="noopener noreferrer">2008 flooding</a> in Cedar Rapids, Iowa, cost-benefit criteria supported new flood protections for the city's central business district on the east side of the Cedar River but not for vulnerable populations and workforce housing on the west side.</p><p>Furthermore, many equity measures are aspatial or ahistorical, even though the roots of marginalization may lie in systemic and spatially explicit processes that originated long ago like redlining and urban renewal. More research is thus needed to understand which measures are most suitable for which social equity analyses.</p>
Challenges for Disaster Equity Analysis<p>Across studies that quantify, map, and analyze social vulnerability to natural hazards, modelers have faced recurrent measurement challenges, many of which also apply in measuring disaster equity (Table 1). The first is clearly establishing the purpose of an equity analysis by defining characteristics such as the end user and intended use, the type of hazard, and the disaster stage (i.e., mitigation, response, or recovery). Analyses using generalized indicators like the CDC Social Vulnerability Index may be appropriate for identifying broad areas of concern, whereas more detailed analyses are ideal for high-stakes decisions about budget allocations and project prioritization.</p>
By Jessica Corbett
Sen. Bernie Sanders on Tuesday was the lone progressive to vote against Tom Vilsack reprising his role as secretary of agriculture, citing concerns that progressive advocacy groups have been raising since even before President Joe Biden officially nominated the former Obama administration appointee.