Hydraulic Fracturing: What is it and what does it mean for the environment?

Original title: A Greater Need for Research into Environmental Effects of Hydraulic Fracturing in the U.S. By Bryan White, December, 2014

Hydraulic Fracturing Schematic.

Hydraulic Fracturing Schematic. CC 3.0 by Mikenorton. Wikimedia Commons.

Hydraulic fracturing, a shale gas mining process which allows untapped gas resources to be harvested from ancient rock, offers an economic boon for the United States. However, the pathways through which hydraulic fracturing can extoll negative effects on the environment have remained largely uninvestigated. One pathway, groundwater contamination has the potential to contaminate streams and other fresh water sources above ground. Groundwater contamination can occur when wastewater, the liquid byproduct of shale gas well formation, is recovered and either reused or sent to a water treatment facility. Another pathway is the direct contamination of underground freshwater aquifers from fracturing fluids due to the seepage of liquid through both existing and newly formed cracks in shale rock. A third pathway, increased seismic activity can be triggered during the well injection process leading to felt seismicity (earthquakes felt by humans). The differences in potential that these pathways have for causing environmental harm will be explored in this paper, and the current status of experimental evidence demonstrating (or failing to demonstrate) environmental harm will be reviewed.

Hydraulic fracturing, otherwise known as “fracturing” or “fracking”, became an industry standard practice during the 1980”s, although shale gas plays (geologic contiguous areas where shale gas can be harvested from) have been mined since the early 1900”s (Curtis 2002, Vidic 2013). Fracturing is the process in which many cracks, fractures, are created in Devonion (~300 million years old) shale rock via the injection of a high pressure liquid slurry. Shale rock is a type of sedimentary rock that consists of compacted layers of mud, silt, and other organic matter accumulated over millions of years. This densely compacted material facilitates the generation of both thermogenic (generated via intense heat and pressure) and biogenic (microbially generated) methane (CH4) gas creation (Curtis 2002, Cokar 2013). The high pressures induced on the shale rock by this injected slurry causes many fractures the size and type of which are determined by the pre-existing tectonic conditions (Hubbert and Willis 1972). When fractures are formed by the injection, normally unattainable natural gas begins to seep out of the rocks, a process called desorption, and can be collected under negative pressure at a surface well. During well completion, a percentage of the fracturing fluids used to create the fractures can be recovered and either reused or treated.

Due to the proprietary nature of fracturing fluids, the specific contents of fluids are largely unknown. According to the Oil and Gas (http://www.ogj.com), slurry injected into shale rock consists of 90.21% water, 8.9% Proppant, and 0.44% other (Saba 2013). Proppant is a technical term for a mixture of water and either ceramic particles or sand grains. These fine, sand-sized particles help to keep fractured shale rock open so that gas can be freely desorbed and extracted along a negative pressure gradient. Other proprietary chemicals used in hydraulic fracturing can include a pH Adjusting Agent (0.01%), a Breaker (0.009%), a Cross-linker (0.006%), an Iron Controller (0.004%), a Corrosion Inhibitor (0.001%), a Biocide (0.001%), a Friction Reducer (0.08%), a Surfactant (0.08%), potassium chloride (0.05%), a Gelling Agent (0.05%), and Acid (0.11%) (Saba 2013).

The unknown content of fracturing fluids makes tracing their pathway through the fracturing process difficult and makes the direct detection of groundwater and aquifers difficult, so field tests using methane have been devised. A recent study by Osborn et al. (2011) aimed to indirectly test for the contamination of fracturing fluids by tracing the origin of detectable methane. Shale gas plays (geologic areas deemed economically valuable) can contain two types methane: biogenic methane derived from microbes and thermogenic methane derived from intense geologic processes (Curtis 2002). The ratios of these two types of methane gas vary from shale gas play to play (Curtis 2002), and the isotopic signature of each type of methane differs depending on its origin (biogenic or thermogenic, Osborn et al. 2011). However, the analysis of Osborn et al. (2011) lacked enough data points in critical areas (water wells near inactive fracturing wells) to prove that methane contamination had occurred. Jackson et al. (2013) expanded on the Osborn et al. (2011) field test. The improved data coverage of Jackson et al. (2013) suggests methane contamination is occurring and that the source of methane contamination is indeed from fracturing wells. However, since the presence of methane may be from naturally occurring geological processes, the specificity of this field test remains uncertain without pre-fracturing data, which both studies lack. This highlights the absolute need for pre-emptive sampling before hydraulic fracturing occurs. Furthermore, due to play-specific differences in biogenic and thermogenic gas signatures (Curtis 2002) it remains uncertain how these data can be applied outside of Appalachian Basin plays they were tested in.

Above-ground environmental contamination typically occurs following the injection of fracturing fluids when water is either recovered and reused on site or recovered and transported off-site where it undergoes water treatment for decontamination (Olmstead et al. 2013). Current recovery rates of fracturing fluids (flowback wastewater) have been estimated to be 10% with 90% of fluids remaining submerged (Rahm et al. 2013). Recovered waters can contain high levels of salts (Olmstead et al. 2013), as well as naturally occurring radionuclides (Olmstead et al. 2013). Along with drastically increased salt levels, total suspended solids can also be increased (Olmstead et al. 2013) to levels harmful to aquatic organisms. Two radionuclides found in hydraulic fracturing waste fluids are barium and radium which may bioaccumulate in stream sediments (Warner 2013). Radionuclides are atoms experiencing unstable nuclei and are prone to emit ionizing alpha, beta, and gamma radiation that bioaccumulates in the environment. Treatment of waste water successfully removes ~90% of radionuclides (Warner 2013). The bulk of the accumulation of contaminants output from above-ground wastewater treatment into streams occurs at or near where effluent is discharged into the environment. While it is clear that wastewater contaminants appear in effluent discharge and downstream of treatment plants, it is not clear whether salt, radionuclides, or TSS occur in toxic levels in those streams.

The occurrence of induced seismicity and earthquakes associated with hydraulic fracturing has been well documented (Hsieh and Bredehoeft 1981; Fehler et al. 1987), although occurrences of “felt seismicity”, earthquakes felt by humans, are actually quite rare. The first such account of felt seismicity occurred in 1960 when the U.S. military injected waste fluid into a borehole at the Rocky Mountain Arsenal, Colorado (Davies et al. 2013). Earthquakes generated by the injection of waste fluids caused earthquakes ranging up to 5.3M and caused significant structural damage in nearby towns and the use of the borehole was stopped in 1966 (Davies et al. 2013). More recent reports suggests that microseismic activity might trigger fault activation up to ~2k away from the site of hydraulic fracturing as fluid moves through permeable fracture fault systems (Holland 2013), which supported the conclusion of Rozhko (2010) regarding the mechanism of microseismic induction fluid diffusion. Davies et al. (2013) also concludes that hydraulic fracturing can activate faults and that the most likely method of fault activation is injection of fracturing fluids into pre-existing faults, although the actual magnitude of most earthquakes generated by hydraulic fracturing are less than 1 M on the Richter scale suggesting that the majority of seismic events are microearthquakes not felt on the surface. As the ranges of hydraulic fracturing expand, the risks associated with induced seismicity will also likely increase, potentially leading to a “point of no return” where natural faults have been permanently altered by fracturing activities.

In conclusion, hydraulic fracturing may present negative environmental impacts as a result of the bioaccumulation of salts and radionuclides, methane contamination of surface and subterranean aquifers, and an increase in geologic activity surrounding fracturing sites. A wide range of pollutants are hydraulically injected into wells, and injected water is rendered potentially toxic from naturally occurring elements (radionuclides). Most of the water injected into wells is recovered and either treated or reused in other wells reducing or eliminating effluent to sub-toxic levels, but little is known about current levels of potential environmental toxicity due to bioaccumulation. With new research and advances in fracturing technology potentially allowing completed wells to be modified into large subterranean bioreactors (Cokar 2013), the lifespan of wells may be increased drastically and any potentially negative environmental effects associated with well existence prolonged. The potentially harmful environmental effects associated with hydraulic fracturing warrants continued research into the how bioaccumulation of contaminants might occur, refining field tests for detecting well contamination, and understanding how increased seismic activity might permanently change the geologic landscape of an area.

Literature Cited

Cokar, M., Ford, B., Gieg, L. M., Kallos, M. S., & Gates, I. D. (2013). Reactive reservoir simulation of biogenic shallow shale gas systems enabled by experimentally determined methane generation rates. Energy & Fuels, 27(5), 2413-2421.
The authors performed laboratory experiments to determine the rates of natural gas produced by microbes under conditions similar to shale gas reservoirs. Methanogenesis was simulated in the laboratory by using core rock and water samples taken from shale gas reservoirs. Interiors of cores from different depths (ranging from 250 m to 350 m) were crushed and incubated to remove any surface-dwelling microbes, then inoculated with fresh water obtained from a shale reservoir. Kinetic rate equations for gas production were derived from the inoculated samples giving a rate equation for each depth. Microbes inoculated on different depths produced markedly different gas outputs but there was not a pattern associated with increased or decreased depth. Model parameters derived from rate experiments were input into a mathematical model to predict gas output for a 2500 day period (6.8 years) from a shale gas reservoir which closely matched output from an actual reservoir. The authors conclude that in active shale gas wells biogenic gas makes up roughly 12% of extracted gas. Biogenic gas output might be increased so long as electron donors (H2 or acetate) are present in sufficient quantities.

Curtis, J. B. (2002). Fractured shale-gas systems. AAPG Bulletin, 86 (11), 1921-1938.
This paper covers a brief history of shale gas mining followed up by a more detailed overview of 5 current shale-gas plays in the United States. The author also overviews current economic status of each shale-gas play, geological and geochemical composition, and the amount of gas that is economically feasible to recover. The concepts of biogenic vs. methanogenic gas are introduced and discussed.

Davies, R., Foulger, G., Bindley, A., & Styles, P. (2013). Induced seismicity and hydraulic fracturing for the recovery of hydrocarbons. Marine and Petroleum Geology, 45, 171-185.
This article focuses on the “felt seismicity”, earthquakes felt by humans, generated by hydraulic fracturing and injection mining. The authors began by a general introduction to how earthquakes can be caused by the injection of fluids, either fracturing fluids or other waste water, into boreholes. Induced earthquakes are typically caused by the progressive loading of stress from shifting tectonic plates, but any type of progressively changing stress can cause earthquakes. Typically faults are lubricated either by magma or water which allows the fault to overcome the friction on the fault plane. The injection of fracturing fluids increases stress on faults, can create new cracks and fractures in the rock surrounding faults, and makes it easier for fault slips to occur where there already exists pressure. The authors sought to understand the causes for the largest sized (highest magnitude) earthquakes. They conducted a meta-study consisting of 198 seismic examples from 66 published papers. They broke down the likely triggers of seismicity into specific subcategories and attributed each earthquake to a particular category. The authors found that hydraulic fracturing could trigger faults but the majority of published examples of induced seismicity were from conventional mining activities. Induced seismicity due to hydraulic fracturing also produces only very small earthquakes (~3 M) that are not likely to be felt by humans. However, this does not rule out the possibility that hydraulic fracturing could re-activate a larger fault and cause felt seismicity (~4 to 8 M).

Fehler, M., House, L., & Kaieda, H. (1987). Determining planes along which earthquakes occur: method and application to earthquakes accompanying hydraulic fracturing. Journal of Geophysical Research: Solid Earth (1978-2012), 92(B9), 9407-9414.
Provides a statistical method for finding the specific fault plane of an earthquake caused by hydraulic fracturing. They used this method to find the fault plane of microearthquakes and determined that those microearthquakes were caused by hydraulic fracturing.

Holland, A. A. (2013). Earthquakes Triggered by Hydraulic Fracturing in South-Central Oklahoma. Bulletin of the Seismological Society of America, 103(3), 1784-1792.
A case study report of 116 microearthquakes (0.6 to 2.9 M) that occurred near a well undergoing hydraulic fracturing in south-central Oklahoma. Authors found a very strong temporal correlation between fracturing events and seismic events. Interestingly the authors did not find a strong correlation between injection volume and earthquake magnitude. Authors also note that the majority of wells in Oklahoma have not been suggested to undergo any induced seismicity.

Hubbert, M. K., & Willis, D. G. (1972). Mechanics of hydraulic fracturing. Society of Petroleum
Engineers of AIME, 210, 153-168. Develops detailed physical model of induced seismicity due to hydraulic fracturing. The extent and type of fractures caused by fluid injection is largely dependent on the pre-existing tectonic stress of an area.

Jackson, R. B., Vengosh, A., Darrah, T. H., Warner, N. R., Down, A., Poreda, R. J., Osborn, O. G., Zhao K., & Karr, J. D. (2013). Increased stray gas abundance in a subset of drinking water wells near Marcellus shale gas extraction. Proceedings of the National Academy of Sciences, 110(28), 11250-11255.
This paper is a follow-up experiment from the Osborn 2011 paper. The authors collected water from shallow water wells used for drinking in Pennsylvania and traced the source of any methane found in those wells. The authors again use the method of assigning methane origin to shale gas wells (hydraulic fracturing) if it was geochemically produced thermogenic methane. Methane was assigned to non-fracking sources if it was found to be biogenic (originating from methanogenic microbes). The authors found dissolved methane in 82% of water wells sampled. They also found that the water samples with the most elevated methane levels had the most thermogenic origin, suggesting fracturing was the source of methane contamination. Ethane, propane, and helium isotopic analysis was also done and supported isotopic origins similar to those found in shale gas reservoirs for those isotopes as well, although sample sizes were much lower for the other isotopes. The authors concluded contamination was occurring in the Marcellus shale area and that the most likely sources of contamination are faulty steel casings and inadequate cement sealing.

Olmstead, S. M., Muehlenbachs, L. A., Shih, J. S., Chu, Z., & Krupnick, A. J. (2013). Shale gas development impacts on surface water quality in Pennsylvania. Proceedings of the National Academy of Sciences, 110(13), 4962-4967.
The authors conducted a statistical analysis using GIS software and the coordinates of sampled surface water locations in relation to fracking operations. To estimate surface water contamination previously collected data on Cl- and total suspended solids (TSS) were analyzed. Cl- is used during the fracking process and can harm aquatic ecosystems by increasing the amount of dissolved heavy metals or phosphates in water. TSS are also harmful to aquatic ecosystems and can clog and block out sunlight, increase temperatures, and reduce available dissolved oxygen. The authors found that the density of shale gas wells present upstream from a watershed did not statistically increase Cl- concentrations. However, increased density of water treatment facilities that receive fracking fluids did. This suggests that for Cl- levels increased Cl- in watersheds is a result of treated water rather than shale gas well contamination. For TSS, the effects of well pads (5-15 acre industrial sites surrounding a well head) were found to significantly increase downstream TSS levels. This suggests runoff from well heads are contributing to stream TSS, although the specific mechanism contributing to increased TSS is unclear.

Osborn, S. G., Vengosh, A., Warner, N. R., & Jackson, R. B. (2011). Methane contamination of drinking water accompanying gas-well drilling and hydraulic fracturing. Proceedings of the National Academy of Sciences, 108(20), 8172-8176.
Authors hypothesize that fracturing fluids injected into wells may leak into nearby freshwater aquifers and cause contamination. Contamination from fracturing fluids could increase the amounts of radioactive materials and toxic gases in fresh groundwater and pose a human health risk. The authors analyzed water samples from 68 wells for methane concentrations, dissolved salts, and dissolved isotopes. They sampled water from two treatments: active, a water source within 1 km of an active fracking well, and inactive, a water source greater than 1 km from a fracking well. The authors detected methane in 85% of drinking-water wells sampled and methane concentration increased nearer to gas wells. Furthermore, the authors found that the methane detected in drinking-water wells had a radioactive isotopic signature more closely related to deep, thermogenically derived methane rather than shallower, microbially generated biogenic methane. However, there are some issues with the representation of the data presented here. For example, Figure 3 shows many of the water samples taken nearest to active wells have higher methane concentrations, however, no samples were taken where a drinking-water well was nearest to a non-active gas well. In order to conclude shale gas wells are the source of increased methane, drinking sources near non-active wells (less than 1000 m) need to be sampled.

Rozhko, A. Y. (2010). Role of seepage forces on seismicity triggering. Journal of Geophysical Research: Solid Earth (1978-2012), 115(B11).
The author develops a mathematical model based on poroelasticity to demonstrate microseismic events occur due to seepage (the diffusion of injection fluids) into boreholes. The author validated his model against published data from both hydraulic fracturing injection wells and a geothermal injection well. In the hydraulic fracturing well, microseismic events lasted about 5 hours following injection, 1 hour after injection stopped, and traveled about 600 m. Injection into the geothermal well lasted about 60 hours and an additional 20 hours after injection had stopped. Microseismic events also only occurred roughly 600 m from the borehole at the geothermal well site. The nonlinearity of microseismic events is due to the diffusion of fluid and elastic stress response of rock. This model suggests that well depletion, the removal of fluid pressure, would also cause microseismic events.

Saba, T. (2013). Evaluating claims of groundwater contamination from hydraulic fracturing. Oil & Gas Journal, 111(7).
This an article published in the Oil and Gas Journal, which is not a peer-reviewed journal. However, it does include detailed statistics from sources active in the gas and oil industry and so is relevant to this review. Unfortunately peer-reviewed articles containing detailed statistics of the ingredients used in fracking fluids are not currently available. It is important because these are the values and names of chemicals that the gas and oil industry feels comfortable publishing to the public. Although many of the chemicals listed in this article are proprietary names and the exact chemical compounds are unknown, it does give some insight into the chemicals used during the process of well injection.

Rahm, B. G., Bates, J. T., Bertoia, L. R., Galford, A. E., Yoxtheimer, D. A., & Riha, S. J. (2013). Wastewater management and Marcellus Shale gas development: Trends, drivers, and planning implications. Journal of Environmental Management, 120, 105-113.
The authors summarize the economic benefits of hydraulic fracturing and note that interest is increasing internationally and that until unconventional (hydraulic fracturing) gas mining was implemented in the United States, gas production was on the decline. The authors also state that while hydraulic fracturing has many economic benefits, it also has environmental negatives associated with fracking wastewater. The authors investigated how the wastewater management process has changed over time with regards to hydraulic fracturing fluids. Data for this study were obtained from Pennsylvania Department of Environmental Protection (PADEP). Overall, the volume of wastewater resulting from fracking in the Marcellus shale increased roughly 5 fold from 2008 to 2011 due to increased well drilling. However, much of the volume has shifted its destination from being treated and returned to groundwater systems to being reused by well operators for new wells. Disposal of wastewater by injecting it into wells and leaving it there (injection disposal) also increased. Well drilling tended to decrease as the prices of natural gas decreased from $4 per million cubic feet from 2010 to $2 in 2012. Wastewater was treated or reused in over 70 counties and the travel distance for wastewater disposal decreased by 30% most likely associated with increased treatment infrastructure.

Warner, N. R., Christie, C. A., Jackson, R. B., & Vengosh, A. (2013). Impacts of shale gas wastewater disposal on water quality in Western Pennsylvania. Environmental Science & Technology, 47(20), 11849-11857.
The authors analyzed effluent discharged from a brine treatment facility near the Marcellus shale in Pennsylvania and sought to understand the short and long-term environmental effects of unconventional (hydraulic fracturing) gas drilling. Effluent (water initially leaving the treatment facility) samples were collected and also surface water samples from both upstream and downstream from the treatment facility. Samples were collected over the course of 2 years (2010 to 2012). The authors found major salt elements were up to 6,700 times higher concentrations in effluent discharge compared to upstream river sites. The treatment plant was found to contribute 78% of downstream salt (chloride) flux, mean annual salt concentration multiplied by total annual effluent discharge volume. Barium and radium elements (both radionuclides) were reduced by 99% following water treatment. However, sludge produced during the treatment process would theoretically contain radium levels higher than safe disposal regulations allowed in the U.S. Furthermore, although radium discharge was significantly decreased, much of the radium that was discharged would accumulate in sediments near the discharge site and amplified by increased salt levels. These levels run the risk of causing bioaccumulation in benthic invertebrates, fish, and even plants.

Hsieh, P. A., & Bredehoeft, J. D. (1981). A reservoir analysis of the Denver earthquakes: A case of induced seismicity. Journal of Geophysical Research: Solid Earth (1978-2012), 86(B2), 903-920.
Analysis of data from 1960’s injection of wastewater fluids by U.S. Army Corps of Engineers at the Rocky Mountain Arsenal in Denver, Colorado. Author concludes that earthquakes were caused by the pressure build-up of fluid injection. Some earthquakes exceeded magnitudes of 3 or 4 on the Richter scale. Earthquakes continued after fluid injection stopped and caused structural damage in the Denver area.

Undergraduate Thesis: Effects of Artificial Moonlight on the Foraging Behavior of Mojave Desert Rodents

Effects of Artificial Moonlight on the Foraging Behavior of Mojave Desert Rodents

An Undergraduate Thesis Project
By Bryan White


Desert rodent communities are extremely diverse, which has prompted researchers to ask how so many species can coexist on similar, limited resources. Differences in foraging preferences associated with predator avoidance may contribute to coexistence. I determined how the foraging behavior of Mojave Desert rodents, especially pocket mice (Chaetodipus), were influenced by the increase in perceived predation risk associated with moonlight, which I simulated using artificial illumination. Millet (6.00 g) was mixed into trays filled with 2 L of pre-sifted sand. Seed trays were placed at stations located at different distances (2-82 m) from Coleman camping lanterns, and in either open or shrub microhabitats, so that rodents could choose to forage from resource patches with different levels of perceived risk. I also live-trapped rodents to identify likely foragers near the lanterns, and to determine the diversity and abundance of rodents in the area. Background illumination levels were recorded with using a Lux meter. I predicted that the amount of seeds removed would be highest at seed trays farthest from lanterns and under shrubs, and lowest at stations closest to lanterns and in open microhabitats. Surprisingly, I found no effect of distance, microhabitat, or illumination level on the amount of seeds removed by rodents.

Merriam's Kangaroo Rat

Merriam’s Kangaroo Rat. Photo CC 4.0 By Bcexp. Wikimedia Commons.


Desert rodents are intriguing animals because of their ability to survive in extremely harsh climates where resources are limited. Desert rodent communities are extremely diverse, which has prompted researchers to ask how so many species can coexist on the same resources, seeds (Brown 1988). In the Mojave Desert, for example, six different genera (Ammospermophilus, Chaetodipus, Dipodomys, Neotoma, Onychomys, Perognathus, Peromyscus), representing three rodent families (Heteromyidae, Muridae, Sciuridae) can all be captured in roughly the same area (Stevens et al. 2009). Most explanations suggest that animals reduce competition via resource partitioning, but differences in predator avoidance abilities may also contribute to coexistence (Kotler 1984).

It is widely accepted that desert rodents differ in their microhabitat preferences, and that these preferences reflect differences in the ability of rodents to detect and avoid predators, including owls, mammalian carnivores, and snakes. For example, quadrupedal rodents such as pocket mice (Chaetodipus, Perognathus), tend to forage in the cover of large shrubs, whereas bipedal rodents such as kangaroo rats (Dipodomys) are often found in open microhabitats between shrubs (Kotler 1984). Kangaroo rats are adapted to forage in open microhabitats in which there is little cover from visual predators (Thompson 1982; Kotler 1984). These adaptations include hopping locomotion, the ability to hear very low frequency sounds (1-3 kHz), and dorsally located eyes that should aid in spotting predators (Thompson 1982; Kotler 1984). Predation rates on rodents by owls are higher both in open microhabitats and (in a separate experiment) during periods of full moon, when levels of illumination might make movements more conspicuous (Kotler 1988). In contrast, pocket mice lack these morphological specializations, but presumably can move more efficiently beneath the denser shrub canopy (Thompson 1982). Interestingly, owls and rattlesnakes, the two most important rodent predators in the Mojave Desert, may have different effects on microhabitat use by rodents. Owls directly affect the perception of risk by desert rodents (Kotler 1988), which is higher in open microhabitats (Brown et al. 1988). The presence of rattlesnakes, which tend to hide near shrubs to wait for prey and to avoid being eaten themselves, decreased foraging of kangaroo rats in shrub microhabitats, although only during summer, when snakes are active (Bouskila 1995).

Mojave desert rattlesnake

Mojave Green Rattlesnake. Predator of Kangaroo rats. Public Domain By Lvthn13. Wikimedia Commons.

The response of rodents to predation risk has traditionally been measured in 2 ways: analysis of microhabitat characteristics at locations where rodents are captured, and foraging experiments to estimate differences in seed removal rates associated with different microhabitats. Optimal foraging theory states that animals will forage in an area until the costs of continued foraging, including perceived predation risk, outweigh the benefits (Morris 1997). The giving-up density (GUD), the density of seeds remaining in an artificial seed patch after a foraging bout, reflects this quitting harvest rate, and thus provides an index of an animal’s perceived risk and foraging costs associated with particular microhabitats (Brown et al. 1988). Both methods have been used to study how moonlight intensity affects rodent activity. Kotler (1984) found that increased illumination, simulated by camping lanterns, decreased captures in open microhabitats for some species and shifted habitat use for others in the Great Basin. Others have reported that bright moonlight reduces overall rodent activity aboveground (Brown et al. 1988).

I modified Kotler’s (1984) approach to investigate the possible effects of artificial illumination on foraging behavior of rodents in shrub and open microhabitats in the Mojave Desert. Rather than studying shifts in captures in different microhabitats, I measured seed removal rates in artificial seed trays placed at different distances from an artificial light source, a gas-powered Coleman lantern. I also quantified variation in light levels at varying distances from the lantern and in the open and beneath shrubs to understand better how actual light levels differ between these microhabitats. I predicted that seed removal rates would be lower (and GUDs higher) in trays close to the lanterns, where illumination was greatest, than at trays where there was only natural light. I also expected that rodents would remove relatively more seeds from trays beneath shrubs than in open microhabitats, especially near the lanterns, where the difference in illumination would be greatest.


My study site was conducted approximately 5 km NW of the Desert Studies Center, Zzyzx, California, during the months of June and July 2010. The site was a broadly sloping bajada at the base of an alluvial fan. Vegetation consisted mostly of creosote bush (Larrea tridentata), burrobush (Ambrosia dumosa) and desert holly (Atriplex hymenelytra), with scattered forbs and grasses. The substrate was a mixture of medium-size to small rocks and gravel, with some sandy washes. Shrub microhabitats were considered to be any shrub that appeared large enough to provide adequate canopy cover over a seed tray. Open microhabitats were locations that were at least 1 m from shrubs.

Creosote bush, Mojave Desert

Creosote bush, Mojave Desert. Public Domain By Klokeid. Wikimedia Commons.

To determine which rodent species were present at my site and foraging in seed trays, I set large Sherman live traps on the night prior to foraging trials. Traps were baited with commercial bird seed that had been microwaved for 5 min to prevent germination. During June, 30 traps were placed at same locations as the seed trays. During July, trapping was done in a 7 x 7 grid (49 traps separated by 10 m) in the area where seed trays were placed.

Artificial seed trays were houseplant saucers (6 cm deep and 32.5 cm in diameter) buried so that edges were flush with the ground. When set, each tray contained 6.00 g of millet mixed in 2 L of pre-sifted, fine sand. In June, I placed trays 2, 12 and 22 m points along 2 parallel lines extending out from a central Coleman (Dual Fuel) camping lantern. This was repeated 3 times at 50-m intervals, for a total of 30 trays. In July, I placed 32 trays from (2 m to 72 m at 10 m increments) in four different directions extending out from two centrally-placed lanterns. Two lanterns were used in the second design in an attempt to increase illumination levels. At a given location, seed trays were randomly assigned to be either in a shrub or open microhabitat. One additional tray was covered with hardware cloth to prevent foraging and was used as a control to quantify changes in weight of seeds due to moisture overnight (Stapp and Lindquist 2007).

Trays were set out at dusk. I allowed rodents to forage in seed trays for approximately 4 h. The remaining seeds and sand were collected from trays and taken back to the Desert Studies Center lab, where the sand was sifted to remove seeds. The seed was cleared of debris and weighed using a precision scale to estimate the amount of seeds removed. Seed trays were considered to have been foraged if the amount of seed removed differed by 2% of control trays from that night.

At the beginning of each foraging trial, I measured light intensity using an Extech 401036 light meter. Illumination was measured by placing the light meter on the seed tray so that the light receptor faced straight up. This measured the ambient light in the area, as opposed to the relative intensity that a rodent may perceive being emitted from a light source (either the moon and stars or lantern). I assumed that rodents look to their immediate surroundings, rather than some distant light source, to decide the relative risk of the potential foraging patches. Trials were conducted under similar background moon conditions (waxing gibbous).

All statistical analyses were conducted in Microsoft Excel (2007) Data Analysis Toolpack and Minitab 15 (Minitab Inc. 2007).


Based on a total trapping effort of 64-trap-nights over the 2 trapping sessions, pocket mice Chaetodipus (17 individuals of 2 species, C. penicellatus, C. formosus, that were not distinguished) were the most abundant rodents, followed by Merriam’s kangaroo rat (D. merriami, 6 individuals) and the desert woodrat (Neotoma lepida, 1 individual). I therefore assumed that most trays were visited by pocket mice.

A total of 62 seed trays were set out during the 2 trials. During the June trials, 3 of 30 trays (1 shrub, 2 open, 1 spilled) were considered to have not been foraged, whereas in July, more than 2/3 (22/32) of the trays were not foraged (10 shrub, 12 open, 1 spilled). Only results from seed trays that were considered foraged were included in the analysis. Combining across all distances and trials, there was no significant difference in the amount of seeds removed in shrub and open microhabitats during June or July (Fig.1; P > 0.05). Combining both trials, the amount of seed removed was not related to distance from the lanterns in either open (Fig. 2; R2 = 0.007, P = 0.745, DF = 15) or shrub (Fig. 2; R2 = 0.15, P = 0.0936, DF = 18) microhabitats.

Illumination levels were highest in seeds trays near the lanterns, but declined considerably by 12 m from the lanterns (Fig. 3). Shrub and open trays were exposed to similar light levels.

Surprisingly, illumination did not influence seed removal rate in the way that I predicted. At all levels of illumination and in both shrub and open microhabitats, rodents consumed most of the seeds in the trays (Fig. 4). In fact, the amount of seeds removed was lowest and most variable at the lowest light intensities.


I found no evidence to support my hypothesis that rodents would spend more time foraging in darker, shrub microhabitats, where risk of predation would presumably be lower. This was particularly surprising because pocket mice were the most common rodents I captured at my study sites and probably were responsible for most of the foraging in seed trays. Pocket mice are quadrupedal and generally prefer the cover of shrubs (Kotler 1988), and therefore would be expected to be sensitive to predation risk. My results differ from those of Kotler (1984), who found, based on live-trapping, that rodents, including quadrupedal species, increased their use of shrub microhabitats in the presence of artificial illumination. However, Kotler (1984) also found that seed enrichments increased the use of the open microhabitat by kangaroo rats. This suggests that, in my study, while pocket mice may have focused their foraging efforts on removing seeds from under shrubs, kangaroo rats may have been opportunistically foraging in brighter areas, and due to its larger body size and bipedal locomotion, consistently removed large amounts of seeds from those trays.

The fact that rodents ate nearly all the seeds in seed trays at all distances from the lanterns and irrespective of illumination levels suggests that the bright light associated with the lanterns did not deter them from foraging. In fact, rodents removed the smallest amounts of seed in trays at the darkest light levels, including some beneath shrubs (Fig. 4). This suggests that factors other than illumination and microhabitat influenced foraging behavior at these low light levels. It also suggests that rodents can find a large amount of dispersed seed (6 g) in a relatively short time. It is possible that multiple rodents visited a given tray, but I was not able to determine the number of rodents using each tray.

If I were to repeat this study, I would increase the number of replicate seed trays and use the same experimental design throughout. I also would keep a record of whether there are tracks in trays as an index of foraging. Another way to improve my experimental design would be to video record seed trays to know how many animals and of which species visited a seed tray during a foraging bout.

Literature Cited

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Kotler, B. P. (1984). Risk of predation and the structure of desert rodent communities. Ecology, 65(3), 689-701.

Kotler, B. P. (1988). Environmental heterogeneity and the coexistence of desert rodents. Annual Review of Ecology and Systematics, 19, 281-307.

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