PH AND CONDUCTIVITY OF ROADSIDE SOILS IN RELATION TO MAGNESIUM CHLORIDE APPLICATION BRIANA SANTA ANA TELLURIDE HIGH SCHOOL BRIDAL VEIL LIVNG CLASSROOM TELLURIDE INSTITUTE COLORADO MESA UNIVERSITY ENVS 196 2013 Introduction Magnesium chloride (MgCl) is a salt used as an anti-­‐dust agent and road stabilizer on non-­‐paved roads during the spring/summer, and as a de-­‐icing product on paved roads and highways during the winter in Colorado, including San Miguel County. MgCl based products are known to travel from treated roads into soils through rain and snow storms. Chloride (Cl-­‐) and magnesium (Mg+2) are both essential nutrients that are important for normal plant growth and health. However, too much of either nutrient may harm the development of the surrounding vegetation. High concentrations of MgCl ions in the soil may be toxic or change water relationships such that the plant cannot easily accumulate water and other nutrients. Trees alongside these roads can then take up soil magnesium and chloride through their roots and accumulate them in their leaves. Once inside the tree, chloride moves through the water conducting system and accumulates at the margins of leaves or needles, where dieback occurs first. Since the leaves are weakened or killed, death can then follow for the tree. Often trees that are infected with high concentrations of magnesium chloride, have foliar damage in a spiral pattern through the crown of the tree, starting at the tip of the conifer trees following all the way down (1.). These effects can be observed while driving along many of the roads within the San Miguel Watershed. The paved state highways that run through San Miguel County are sprayed every winter during ice events with this MgCl. The county roads are treated every summer for dust suppression. (Horner, 2013) Colorado State University has conducted extensive research on the effects of magnesium chloride on trees and vegetation in Colorado. However, no research has been found on the effects of magnesium chloride in San Miguel County. In this research project, the effects of magnesium chloride on a dirt county road are analyzed by comparing conductivity levels, pH levels, and conducting a plant health comparison near treated and non-­‐treated sections of the road. Conductivity is a measure of the degree which a specific material conducts electricity, and is a common way to analyze soil for salts (2.). Soil pH indicates the acidity or alkalinity of a soil based on a scale of 1 to 14. The neutral on this scale is a 7, and the numbers above are alkaline, while those below are acidic. It is predicted that if a road is treated with MgCl, then; it should have a higher conductivity, contain a lower pH level, the vegetation should appear more yellow, frail or dead, and lastly the conductivity should be higher at 10 feet than at 20 feet. Conversely, if a road is not treated with MgCl the conductivity would be much lower than a road treated, the pH levels would be about neutral (7.01), and the vegetation should appear thriving with lots of new growth. Methods Two areas were chosen from Fall Creek Road, one area in the treated portion of the road and another in the non-­‐treated portions. Three 20-­‐foot transects were chosen on the treated and non-­‐
treated portions of the road. Transects ran downslope of, and perpendicular to the road, situated between the road and nearby Fall Creek channel. The untreated section of Fall Creek road is located upstream from the treated portion. The treated segment lays closer to the entrance to Fall Creek Road off of Highway 145. Before choosing the exact transects, they were all chosen to be on a fairly flat plain and have distance from the river running parallel. The section was large enough to have all three transects for that portion. Transects were spaced 50 meters apart from each other, following the roadside. Once transects were marked, 1 meter was measured off the road to create a starting point, marked with a flag. From the starting point, 10 and 20 feet were measured and flagged to create the soil sample sites. Soil samples were collected at both distances on each transect, 2 feet west of the measuring tape, at the depths of approximately 8 and 12 inches. Samples were put in their own separate Ziplock baggies marked with transect, distance, and depth. A first set of field samples was analyzed for conductivity and pH, but thought to be erroneously gathered and analyzed, due to curious results, so a second day of fieldwork and sampling was added, using more precision, more samples, and better equipment.* Samples were taken home and dried in a 200 degree F oven for several hours in aluminum foil ‘boats’ until no moisture was present. Once soil samples were dried, each sample was crushed with a mortar and pestle set, eliminating dirt clumps, rocks, and any unwanted materials. Then the soil was sifted through a stainless steel handheld strainer basket, and 50 gram portions of each sample were weighed with a Fast Weigh MS-­‐500-­‐BLK Digital Pocket Scale, 500 by 0.1 G. Each 50 gram portion was placed in a quart sized Mason Jar and mixed with 250 mL of distilled water. First the solution was immediately shaken for 30 seconds and stirred for one minute. Before settling, a HANNA 991300 Conductivity/TDS multiparameter instrument was used to measure the pH and EC levels. 3 days later, samples were re-­‐tested with same procedure to observe any differences. Results were written down for each sample. Baseline data for EC and pH of MgCl was calculated with distilled water and a 15% Magnesium Chloride liquid solution provided by the San Miguel County Road and Bridge Department. Ratios of 1:100, 1:120, 1:140, and 1:160 were created for the baseline test. Vegetation species were observed using a Daubenmire Frame, which measures one tenth of a meter area. A Daubenmire Frame was laid on the ground due East, 2 feet from the measuring tape, at each of the 18 soil sample sites. Percent canopy cover of each species falling within the frame was recorded. A vegetation health scale was created to rate the overall health of the plants recorded as follows: 1= 0-­‐19% healthy and alive; 2=20-­‐39% healthy and alive, 3=40-­‐59% healthy and alive; 4= 60-­‐79% healthy and alive, 5= 80-­‐100% healthy and alive. Site Description: This research was conducted adjacent to different sections of Fall Creek Road, approximately 12 miles down valley from Telluride, CO, and near the small town of Sawpit. The road follows Fall Creek, which is a tributary of the San Miguel River, starting at Woods Lake approximately 10 miles up from the San Miguel River in the sub alpine zone. Fall Creek meets with the San Miguel River around 7000 ft. in elevation. Fall Creek Road is a dirt county road extending the length of its nearby channel. The study is located in a pinon/juniper woodland life-­‐zone, surrounded by red sandstone cliffs and side canyons. The road is in close proximity to the river, providing moist riparian habitat with willows, sedges, and Blue Spruce being common. Loads of summer time activity occurs around the area, requiring dust suppression of the roadbed. Fall Creek Road branches at a point about 4 miles upstream from the San Miguel River, and one branch leads to Woods Lake. Study sites untreated with MgCl were upstream of the treated study sites on Fall Creek Road. Most treated portions of the road lie below the fork to Woods Lake. RESULTS Baseline tests carried out in the lab prior to soil testing, revealed the following: The distilled water had a pH of 6.97 and a µs of 5. A 15% concentration of MgCl was used for the diluted concentrations of the baseline data. Less than 1% solutions were made for baseline data. Concentrations made were .83%, .71%, .625%, .5%, and .1%. See Table 1. Ratio of dilution 1 mL : 1000 mL 5 mL : 1000 mL 5 mL : 800 mL 5 mL : 700 mL 5 mL : 600 mL Percent solution 0.1% 0.5% 0.625% 0.71% 0.83% Electrical Conductivity 674 µS 2281 µS 2919 µS 3301 µS 3797 µS pH 8.44 9.05 9.05 9.04 8.95 Table 1: Baseline data showing MgCl dilution concentrations with distilled water The results found for pH and EC were unexpected and varied at each site. The first set of results produced values that were so unexpected, that a second day of field data collection was necessary, using more precise protocols including, multiple sample depths (“shallow” and “deep”, approximately at 6 and 12 inches below ground surface), more precise soil measurements, drying and grinding of samples. Samples were measured with dry weight rather than volume of wet soil. Even with a substantial amount of attention, results remained generally similar to the first sample set. Electrical conductivity had a trend when comparing treated and untreated sites. The untreated transects had a higher conductivity levels than the treated transects. In the first testing, the untreated sections barely had higher conductivity levels. The lowest number for treated transects was 55 µs, from a deep sample located 20 ft. off the road. The highest number for the treated transects in conductivity levels was 166 µs at a 10 ft. shallow sample. The lowest reading in conductivity for untreated transects was 93 µs at a 20 ft. shallow sample. The highest number found in the untreated sections was 264 µs at a 20 foot shallow sample. See Chart 1 below. EC of First TesHng of Soil Samples 700 600 500 EC in Microsiemens 400 10'EC1 20'EC1 300 10'EC2 200 100 0 20'EC2 T1 T2 T3 U1 U2 U3 Sample Site Chart 1: Electrical conductivity of samples tested immediately after soil was put into solution with distilled water. T1, T2 and T3 represent the 3 treated transects; U1, U2 and U3 represent the 3 untreated transects. EC1 values represent shallow soil samples (approximately 6”), while EC 2 values represent deeper soil samples (approximately 12”). The second EC readings, taken 3 days after the first testing, showed the untreated transect conductivity levels were dramatically higher than transects treated with MgCl. For the second sample testing, the highest EC level found in a treated section was 485 µs at a 10 ft. shallow sample, while the lowest EC level was 55 µs at a 20 ft. “deep” sample. In the untreated transects, the second testing of the sample set, the lowest EC reading was 318 µs found at a 20 ft. “deep” sample and the highest EC reading in the untreated sections was 647 µs at both a 10 ft. and 20 ft. “deep” samples. It was also found that the shallow 10 ft. samples had a higher conductivity reading than the deeper samples. For overall 20 ft. samples, there was no trend as to which sample had a lower/higher EC level. Overall, the 10 foot samples had higher conductivity readings compared to the 20 foot samples. See Chart 2 below. EC of Second TesHng of Soil Samples 700 600 EC in Microsiemens 500 400 10'EC1 300 20'EC1 200 10'EC2 20'EC2 100 0 T1 T2 T3 U1 U2 U3 Sample Site Chart 2: Electrical conductivity of samples tested 3 days after soil was mixed with distilled water. T1, T2 and T3 represent the 3 treated transects; U1, U2 and U3 represent the 3 untreated transects. EC1 values represent shallow soil samples (approximately 6”), while EC 2 values represent deeper soil samples (approximately 12”). When pH was measured, the untreated transects had a lower pH than transects treated with the MgCl. The results were scattered on the first testing, for both 10 foot and 20 foot samples (See Chart 3). However, with the second testing, 3 days following the first, data showed a trend. The 10 foot samples had lower, less alkaline levels than the 20 foot samples. It is also seen that the pH levels in the untreated transects of the road appeared dramatically lower than the treated transects. But in general, the shallow samples at both 10 feet and 20 feet had a lower pH than the deeper samples at those soil sample sites. See Chart 4, below. ph of First TesHng of Soil Samples 9 8.8 8.6 8.4 ph value 8.2 10'ph1 8 20'ph1 10'ph2 7.8 20'ph2 7.6 7.4 7.2 T1 T2 T3 U1 Sample Sites U2 U3 Chart 3: Ph of samples tested immediately after soil was put into solution with distilled water. T1, T2 and T3 represent the 3 treated transects; U1, U2 and U3 represent the 3 untreated transects. ph1 values represent shallow soil samples (approximately 6”), while ph 2 values represent deeper soil samples (approximately 12”). ph of Second TesHng of Soil Samples 9 8.8 8.6 8.4 ph value 8.2 10'ph1 8 20'ph1 7.8 10'ph2 7.6 20'ph2 7.4 7.2 T1 T2 T3 U1 U2 U3 Sample Site Chart 4: Ph of samples tested 3 days after soil was put into solution with distilled water. T1, T2 and T3 represent the 3 treated transects; U1, U2 and U3 represent the 3 untreated transects. pH1 values represent shallow soil samples (approximately 6”), while ph 2 values represent deeper soil samples (approximately 12”). Vegetation was recorded in a Daubenmire frame near each soil sample site. Two common plants were found between the treated and non-­‐treated portions of the road; the Geranium species, Richardsonii geraniaceae, and the Aster species, Achillea lanulosa. The Geranium and Aster species were found in multiple sites in the treated portions of the road but only found once in a transect located in the untreated portion of the road. When analyzing of vegetation results, the untreated transects (see Table 2) show higher species diversity than the treated transects (see Table 3) of the road. When treated and untreated portions were evaluated, the treated portions scored an average of a 4.6 on the health scale while the untreated portions scored a 4.4. Table 2: Vegetation Chart for Untreated Transects Species Family Picea glauca Gallium-­‐sp? Swida serice Equisetum arvense Pyrola-­‐sp? Arvents Stellaum Viola-­‐sp? Achillea lanulosa Vicea americana Erigeron flagellaris Rudbeckia ampla Geranium richardsonii Pinaeae Rubiaceae Cornaceae Equisetaceae Pyrolaceae (Wintergreen) Equisetaceae Covallariaceae Violetaeae Asteraceae Fabaceae Asteraceae Asteraceae Geraniaceae Apiaceae (Cowbane) Unidentified Grasses Table 3: Vegetation Chart for Treated Transects Species Thalictrum fendleri Geranium richardsonii Bromopsis inermis Virgurus campestris Achillea lanolosa Rosa wodsii Maianthemom stellaum Dandelion Unidentified Grass Moss Unknown Family Thalictraceae Geraniaceae Poaceae Asteracea Asteracea Roseaceae Conbulariacae DISCUSSION It is very useful to characterize an environment by its pH and EC. These measurements can be taken in water and soil. It is surprising; however, that there is no correlation between the two measurements, even though they both deal with ions. While pH only measures the concentration of the hydrogen ion, conductivity captures the measurement of all the ions. Conductivity is actually a measurement of how electricity can be conducted through a medium. Conductivity and pH are affected by; human impacts, climate, local life, bedrock, and geology. With that in mind, this study was formulated in order to see if there was a correlation between magnesium chloride and the health of the roadside vegetation. Trend found in conducting baseline data with 15% MgCl solution and distilled water showed that as EC rises with more MgCl in solution, the pH rises as well, becoming extremely basic. This would lead one to expect that the same results would be seen in soil samples treated with MgCl, when in fact, the only the pH behaved in this manner, while the EC values behaved exactly opposite of what would have been expected. Values for Electrical Conductivity were surprisingly opposite of what would be expected. Background research on salinity and EC measurement, as well as baseline tests done with liquid MgCl: and distilled water all point toward expecting a direct correlation between rising MgCl levels and EC. Actual soil testing results yielded lower EC values for MgCl treated portions of the road, and higher values for portions of road not treated with MgCl. PH, however, corresponded accordingly to what would be expected, if EC levels has yielded expected values. PH was shown to be higher, or, more basic, in soil samples treated with MgCl. Vegetation results may have been more accurate if a larger scale and more time had been given towards this research. Given direct and small portions of vegetation was seen to not be enough to make a reasonable comparison between the two sites, as to health, species diversity, and interaction between all the vegetation as a whole in each treated and untreated portions of Fall Creek Road. Results for this study make it difficult to come to a clear concise conclusion. It was found that a high concentration of ions will correspond to high conductivity. However, if ions react to form compounds of molecules, conductivity will then decrease. In conclusion, more mobile ions are equivalent to a higher conductivity, and viscosity in the ions lowers the EC (2). Since the untreated section had a higher EC than treated sections of the road, it is a possibility that there were binding reactions taking place with the Mg+, Cl-­‐ ions, and the water, which may have caused the conductivity to decrease in the treated portions of the road. Since there was no direct conclusion as to the confusing case of how pH levels were lower in the untreated portions and that section had a higher EC, this research can be used as a starting point for further research conducted later on. BIBLIOGRAPHY “Magnesium Chloride Toxicity in Trees” Fact Sheet no. 7.425, Jacob, W.R.; Goodrich, B.A.. Colorado State University Extension. 2013, Colorado State University, U.S. Department of Agriculture http://www.ext.colostate.edu/pubs/garden/07425.html (1) “Changes in Conductivity and pH, Teachers Guide” The WaterCAMPWS Center for Advanced Materials for Purification of Water with Systems, University of Illinois at Urbana-­‐Champaign, University of Illinois at Urbana http://www.watercampws.uiuc.edu/waterclear/labs/lessons/titration_teacher_guide.pdf (2) “Soil Test Explanation” Fact Sheet no. 0.502, Self, J.R., Colorado State University Extension. 2010, Colorado State University, U.S. Department of Agriculture “Water and Soil Characterization -­‐ pH and Electrical Conductivity”, Bruckner, M.Z., Science Education Resource Center, 2013, Carleton College, NSDL http://serc.carleton.edu/microbelife/research_methods/environ_sampling/pH_EC.html “Condition of Soils and Vegetation Along Roads Treated with Magnesium Chloride for Dust Suppression”, Goodrich B.A.; Koski R.D., Water Air Soil Pollute, 2008, Springer Science + Business Media B.V. http://treehealth.agsci.colostate.edu/publications/Goodrich%20pubs/mgclroadsideplotsbestversion.pdf