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Calidad del agua en los arroyos de la regin de Monteverde, Costa Rica
Water quality in the Quebrada Mquina: heavy metal, fecal coliform, chloride and sulfide Levels
The purpose of this study is to determine if concentrations of heavy metals, sulfide, chloride and fecal coliforms vary based on relative location to commercial and domestic waste sources along the Quebrada Mquina in Monteverde. Assessments were performed at stream and road run-off sites near Hotel Belmar, CPI Language School, the Monteverde gas station, and below a main road. In addition, three pristine forest stream sites were assessed as controls for a basis of comparison. Chromium-hexavalent, chloride, copper, iron and sulfide levels were tested at each of the seven sites. No significant difference was observed for any heavy metals tested, or for chloride or sulfide. However, higher levels of copper and iron were observed at the gas station and road run-off sites. These sites were exposed to the highest levels of commercial waste, which may account for the trends observed. One water sample was analyzed for the presence of arsenic, mercury and lead from the off-road site and upper-most forest site. Concentrations were identical at both sites for all three metals and were well below toxicity levels. Coliform levels were tested at the pristine forest site and near a lower site exposed to domestic activity. There was a significant difference in the levels of coliforms between the two sites (p < 0.0001). The low levels observed at the pristine forest site were most likely due to animal feces and plant run-off, while the extremely high levels observed at the lower CPI site were likely indicative of improper disposal of domestic sewage.
La regin de Monteverde, Costa Rica esta creciendo rpidamente y la calidad de agua esta siendo indudablemente afectada. Se hicieron muestras en las Quebradas Rodrguez, Mquina y Cambronero a tres elevaciones para evaluar la calidad de agua de los ros segn los parmetros usados para calcular el ndice de la calidad del agua. Tambin se tomaron dos parmetros adicionales, la profundidad y la velocidad.
Text in English.
Water quality--Costa Rica--Puntarenas--Monteverde Zone
Heavy metals--Costa Rica
Metal wastes--Costa Rica
Urban runoff--Costa Rica--Puntarenas--Monteverde Zone
Calidad de agua--Costa Rica--Puntarenas--Zona de Monteverde
Metales pesados--Costa Rica
Residuos de metales--Costa Rica
Escorrenta Urbana --Costa Rica--Puntarenas--Zona de Monteverde
Tropical Ecology 2006
Ecologa Tropical 2006
McElfresh, Jessica; Sawatzke, Laura
t Monteverde Institute : Tropical Ecology
1 Water Quality in the Quebrada Mquina: Heavy Metal, Fecal Coliform, Chloride and Sulfide Levels Rachel Johnson Jessica McElfresh Laura Sawatzke Department of Art and Geography, University of Minn esota School of Journalism and Communications, University of Oregon Department of Integrative Physiology, University of Iowa ABSTRACT The purpose of this study is to determine if concen trations of heavy metals, sulfide, chloride and fec al coliforms vary based on relative location to commer cial and domestic waste sources along the Quebrada Mquina in Monteverde. Assessments were performed at stream and road run-off sites near Hotel Belmar, CPI Language School, the Monteverde gas station, an d below a main road. In addition, three pristine f orest stream sites were assessed as controls for a basis of comparison. Chromium-hexavalent, chloride, coppe r, iron and sulfide levels were tested at each of the seven sites. No significant difference was observed for any heavy metals tested, or for chloride or sulfide. H owever, higher levels of copper and iron were obser ved at the gas station and road run-off sites. These site s were exposed to the highest levels of commercial waste, which may account for the trends observed. One wate r sample was analyzed for the presence of arsenic, mercury and lead from the off-road site and upper-m ost forest site. Concentrations were identical at both sites for all three metals and were well below toxi city levels. Coliform levels were tested at the pr istine forest site and near a lower site exposed to domest ic activity. There was a significant difference in the levels of coliforms between the two sites (p < 0.00 01). The low levels observed at the pristine fores t site were most likely due to animal feces and plant runoff, while the extremely high levels observed at th e lower CPI site were likely indicative of improper d isposal of domestic sewage. RESUMEN El propsito de este estudio es determinar si las c oncentraciones de metales pesados, sulfito, cloruro y coliformes fecales varan con base en la ubicaci n con respecto a fuentes de residuos industriales y domsticos a lo largo de la quebrada Mquina en Mon teverde. Se llev a cabo evaluaciones en lugares e n la quebrada y en lugares de descarga en el camino c erca del hotel Belmar, la escuela de idiomas CPI, l a estacin de gasolina de Monteverde, y abajo del ca mino principal. Adems, tres lugares pristinos en la quebrada fueron evaluados como controles para tener una base de comparacin. Los niveles de cromiohexavalente, cloruro, cobre, hierro y sulfuro fuero n examinados en cada uno de los siete lugares. No se observ diferencia significativa para ninguno de lo s metales pesados examinados, ni para cloruro o sul fito. No obstante, se observ niveles ms altos de cobre y de hierro en los lugares de la estacin de gasoli na y de la descarga en el camino. Estos lugares estuvieron expuestos a los niveles ms altos de desechos industriales, los cuales pueden explicar las tenden cies observadas. Una muestra de agua fue analizada para la presencia de arsnico, mercurio y plomo del luga r fuera del camino y del lugar ms alto en el bosqu e. Las concentraciones fueron idnticas en ambos lugar es para los tres metales y estuvieron debajo de los niveles de toxicidad. Los niveles de coliformes fu eron examinados en el lugar del bosque pristino y c erca de un lugar ms bajo expuesto a actividad domstic a. Hubo una diferencia significativa en los niveles de coliformes entre los dos lugares (p < 0.0001). Los bajos niveles observados en el lugar del bosque pr istino fueron lo ms probable debido a heces animals y al goteo de las plantas, mientras que los niveles
2 extremadamente altos observados en el lugar del CPI ms abajo fueron probablemente indicativos de una disposicin inadecuada de desechos domsticos. INTRODUCTION Industrial, commercial and domestic activities intr oduce significant amounts of harmful waste into the environment. If not properly treated this waste drains into streams and other water systems, polluting water sources for bo th human communities and the habitats of aquatic flora and fauna (USGS 2006). P ollutants can then be carried via streams and rivers to the ocean and other major bod ies of water where fish and other aquatic life forms ingest them and bioaccumulation can ensue. Humans are then put at risk by consuming these organisms. Despite the risks to ecosystems and human health, people continue to engage in anthropogenic activities that are largely responsib le for high concentrations of pollutants found in water systems. For example, toxic levels o f heavy metals can be indicative of improper industrial waste disposal (LaMotte 2004). Water quality assessments aimed at targeting this type of problematic behavior often i nclude analyses of heavy metals. A heavy metal is defined as any metallic chemical ele ment with a high density and that is toxic at low concentrations. Heavy metals cannot b e destroyed and are dangerous to all living organisms because they tend to bioaccumulate (Lenntech 1998-2000). Examples of heavy metals commonly tested include mercury, le ad, cadmium, copper, iron and chromium-hexavalent (Mitchell 1995). Table 1 provid es information about the source(s) and impacts of commonly tested heavy metals. Improper disposal of anthropogenic waste can also b e identified by elevated water concentrations of various nonmetallic elements and coliform bacteria. Coliforms include fecal coliform, such as Escherichia coli and other strains of bacteria. While usually harmless if consumed, high concentrations of fecal coliform are strongly indicative of the presence of pathogenic bacteria, viruses, and paras ites from domestic sewage or animal waste contamination (EPA 2006). Table 2 describes t he source(s) and impacts of nonmetallic and microbial pollutants commonly used in water quality assessments. Table 1: Sources and Impacts of Heavy Metals
3 (1) EPA 2006, (2) Gillespie 1986, (3) LaMotte 2004, (4) Lenntech 1998-2000, (5) NPS 1997, (6) USGS 2006 Table 2: Sources and Impacts of Nonmetallic and Mi crobial Pollutants Contaminant Source(s) Impacts on Humans Impacts on the Environment Bacterial Coliform (including fecal coliform and E. coli ) Found in soils and plants and the intestines and feces of humans and other warm-blooded animals (1) Harmless, but indicator of other pathogens which can cause polio, cholera, typhoid fever, dysentery, and infectious hepatitis (2) High levels offset biodiversity of plants and animals Chloride (nonmetallic) Natural weathering, sewage pollution (2) N/A N/A Sulfide (nonmetallic) Industrial waste (used in batteries), detergents, fungicides, fertilizers, naturally found from volcanic activity (3) Neurological effects, decreased circulation, reproductive failure (2) N/A (1) Dyer 2003, (2) USGS 2006, (3) Lenntech 1998-200 0 Heavy Metal Source(s) Impacts on Humans Impacts on the Environment Arsenic Natural processes, industrial waste and activity, pesticides, smelting of lead, copper and zinc ore (6) Decreased blood hemoglobin, liver and kidney damage (6), bone marrow suppression (5) Fish: increases mucus production (suffocation), causes liver damage and morphology Birds: ataxia, immobility, tetanic seizures, jerkiness (5) Chromiumhexavalent (Cr+6) Improper disposal of industrial waste from nonferrous metallurgical processes, fossil fuel combustion, pigments, use in refractory materials (5) Damage to DNA and other tissues, kidney and liver damage, internal hemorrhaging, dermatitis, carcinogen (humans and animals) (6) Plants: interferes with uptake translocation and iron metabolism Aquatic organisms: decreased weight gain, impaired reproduction and increased hematocrit (5) Copper Industrial waste (3) Untreated chemical waste: used for electrical wiring and piping (2) Liver, kidney and gastrointestinal damage (6) Algae/fish/crustaceans: disrupts internal ion balance Toxic to fresh and saltwater plants and animals (5) Iron Natural erosion of rocks and sediment, industrial and domestic processes (6) High levels can cause conjunctivitis, choroiditis, and retinitis (4) N/A (can be found at high levels naturally) Lead Mining, plumbing, gasoline and coal industries (6) Affects red blood cell chemistry, causes delays in infant and child development, increased blood pressure in adults (6) All living organisms: bioaccumulates, adverse affects on survival, growth, learning, reproduction, development, behavior, metabolism (5) Mercury Industrial waste, pesticides, smelting, burning of fossil fuels, electrical equipment (batteries, lamps and switches) (6) Kidney damage and disorders of the nervous system, exposure almost entirely due to consumption of fish (6) Fish: most toxic heavy metal, bioaccumulates in tissues, nervous system disorders Aquatic organisms: denatures DNA (5)
4 Pollutants such as those listed in Tables 1 and 2 i mpact stream ecosystems negatively. While they exist as compounds dissolve d in water, they are also captured in the soil and sediment and are in turn taken up by p lants (Mitchell 1995). Since plants are a primary food source for herbivores and many omniv ores, the pollutants are able to permeate the entire ecosystem, and increase in conc entration, by traveling through trophic levels. In any ecosystem, but especially i n highly diverse tropical ecosystems such as those found in Costa Rica, the normal balan ce of flora and fauna abundance and diversity is disrupted by pollution. Diversity of a quatic macroinvertebrates is decreased while pollutant-tolerant species thrive (Essman 199 0). Studies conducted locally by Artavia (2000), Burns (2000), Miller (2000), and Sh ultz (1998) support the hypothesis that species diversity decreases with increasing po llution. Loss of species diversity with increasing exposure to water pollution affects not only flora and fauna in the ecosystem, but local hu man communities as well. Polluted water often develops an acrid, pungent odor and una ttractive appearance, losing much of its aesthetic value and calling into question the h ealth and safety standards of areas surrounding the contaminated site. This can threat en the economic well-being of an area and has major implications for tourism, the largest source of income in Costa Rica. Grey and black water near hotels and restaurants are una ttractive to tourists and blemish the names of establishments and locations. Successful t ourism hinges on positive perceptions, which guide where and how people spend their money. Many water quality studies have been conducted in d eveloped countries; however, there have been limited data collected for developing countries like Costa Rica (Malmquist 2002). Monteverde is a small community in Costa Rica with rapidly expanding farming and tourism sectors. Water quali ty assessment and pollution control have substantial implications for a place like Mont everde. Preliminary observations have shown that many businesses and private homes in the Monteverde area flush wastewater directly into the forest, roads and nearby streams. Among these are specifically CPI, a moderately sized language school, and the Monteverd e gas station. Both are situated to feed into the Quebrada Mquina (Figure 1). Human and industrial wastes have previously been te sted for and found in surface water in Monteverde, including fecal coliform in th e Quebrada Cambronero and the Ro Guacimal (Artavia 2000, Silvia 1998) However, the Quebrada Mquina has not been tested for fecal coliforms, nor have any streams in Monteverde been tested for heavy metals. The purpose of this study is to determine if concen trations of heavy metals, fecal coliforms, chloride and sulfide vary at designated point sources along the Quebrada Mquina. We hypothesize that metal, chemical and f ecal contaminants in streams arise from human behavior. These behaviors include mecha nical work, improper disposal of leaky batteries and improper disposal of domestic, commercial and industrial waste. We predict that heavy metal, fecal coliform, chloride and sulfide concentrations at stream sites along the Quebrada Mquina in Monteverde will vary based on relative location to commercial and domestic waste sources including the Hotel Belmar, CPI, the gas station and run-off from a main road. In this study we ask whether there is a significant difference in the average concentration of contamin ants found near these sites and others located upstream in the Cloud Forest on the Propert y of the Estacin Biolgica de Monteverde.
5 MATERIALS AND METHODS Study Sites The study site was the Quebrada Mquina, located in the Monteverde region of Costa Rica. The stream runs southwest from the Estacin B iolgica Monteverde (EBM) through the town of Cerro Plano. Four of the seven locations studied were chosen based on their proximity to sources of anthropogenic poll ution. The three other sites were located in pristine forest and isolated from human contaminants (Figure 1). Samples were collected on seven nonconsecutive days. Data collec tion took place between July 15th and July 26th. All sites were located in lower montane wet fores t and samples were collected during the rainy season. Water samples were collect ed at all seven sites on seven different days, a total of 49 samples. The three control sites were located on EBM proper ty with two upstream from the EBM and one downstream. These sites represented a p ristine environment without anthropogenic pollutants. The lower four sites were located on the Quebrada Mquina where it passed point sources of pollution. Site fo ur was adjacent to the Hotel Belmar, an environmentally friendly hotel recognized by the Co sta Rica government for sustainable ecotourism. Site five was below the CPI Language Sc hool, an observed source of sewage pollution. Site six was directly under the gas sta tion alongside the road in a drainage ditch with run-off water that would drain into the Mquina. The gas station was the only site that was not located on a tributary or section of the Quebrada Mquina, but the runoff did flow into the Mquina when it met with the off-road site. Water flow at this site was highly dependent on rain and human activities a t the gas station such as car washing. Site seven was 50 meters below the road and capture d the gasoline station run-off, suburban housing run-off and the run-off from the r oad that would eventually flow into the Mquina. Water Quality Analysis Each water sample was analyzed for the presence and abundance of chloride, chromiumhexavalent, copper, iron and sulfide. Copper levels were measured at five of the seven sites due to the limited availability of test reage nts. The chemical tests were conducted in the field immediately following collection using th e LaMotte Smart Water 2 Colorimeter and testing kit. Chloride was measured using a dire ct titration method instead of the colorimeter. The pH was measured one time, on the s eventh day of testing at each site. On the seventh day, water was collected from the of f-road site and the uppermost EBM site and sent to the Laboratrio LAMDA in San J os for analysis of concentrations of lead, mercury and arsenic. In addition to the te sts previously mentioned, water was also collected on seven days at the uppermost fores t site and the CPI site and given to the Laboratrio Microbilogico in Santa Elena for analysis of fecal coliform abund ance. These samples were collected in sterile containers to prevent contamination, and stored below 9 C to ensure that the bacteria did not reproduce bef ore being tested.
6 Statistical Analyses A Friedman Test was used on the heavy metals, chrom ium and sulfide, which were collected and analyzed from each site on the same d ay. A Kruskal-Wallis Test and a Sign Test were used to analyze the fecal coliform result s. RESULTS A total of 329 water samples were tested for the pr esence and abundance of contaminants at seven sites. A Friedman statistical analysis was used to evaluate the difference in water quality between sites. In particular, the statistic s were used to determine if the concentrations of contaminants was higher in sites with suspected sources of anthropogenic pollutants as compared to the forest control sites. Water quality analysis detected varying concentrations of heavy metals at the seven sites. Of the 49 chloride tests, one registered above four ppm (the lowest concentration that the direct titration method could detect and a ll the rest had values too low to detect chloride). Therefore, it was not necessary to test statistically the chloride levels at the different sites. There was no significant statistical difference in the concentrations of chromiumhexavalent, copper, iron or sulfide between sites ( c2 = 6.23, p = 0.39, df = 6; c2 = 3.314,p = 0.51, df = 4; c2 = 12.51, p = 0.052, df= 6; c2 = 4.44, p = 0.72, df = 6). Although none of the contaminants was statistically significant, some did have trends. Chromium-hexavalent did not have a trend to the data because of the high variability at every site (Figure 2). The average c oncentration of chromium-hexavalent at all sites (0.03 ppm) was below the standard toxicit y level (Table 3). Copper and iron showed similar trends. The highest levels of each w ere found near the gas station and offroad; the two sites with exposure to the commercial wastes of the gas station and the road (Figure 3 and 4). The mean level of copper was belo w toxicity levels, but the mean level of iron was well above toxicity levels (Table 3). A s with chromium-hexavalent, sulfide did not have a trend in the data because of the hig h level of variance for all seven sites (Figure 5). Of the contaminants tested through the Laboratrio LAMDA, mercury (<0.001 0.001 mg/L) and arsenic (<0.001 0.001 mg/L) were found at levels of zero with the precision of the tests taken into account and lead was 0.11 mg/L for both the upper forest site and the off-road site. The tests for the average E. coli levels, average fecal coliform levels and average total coliform levels were significantly different between the uppermost forest site and the CPI site (Kruskal-Wallis Test, n = 7, c2 = 26.10, df = 4, p < 0.0001, Figure 5; c2 = 23.59, df = 4, p < 0.0001, Figure 6; c2 = 29.91, df = 4, p < 0.0001, Figure 7). A Sign Tes t was used to determine if the null hypothesis, that there was no difference between the sites, could be rejected (Sign Test Table 5 a. b. & c; results showed a significant difference between the two sites and null hypothesi s was rejected).
7 DISCUSSION We hypothesized that heavy metals, sulfide, chlorid e and coliform bacteria in streams arise from human behavior. We predicted that contam inant concentrations would vary at designated points on the Quebrada Mquina based on location relative to potential commercial and domestic waste sources. Our results showed no significant statistical difference in the levels of heavy metals, chloride or sulfide at different sites in the Quebrada Mquina. However, there was a significant statistical difference in the levels of coliform bacteria found at different sites in the Q uebrada Mquina. We found that in the three pristine forest sites th ere were consistent background levels for most contaminants. The low background le vels of copper (0.03 ppm), iron (0.708 ppm) and chromium-hexavalent (0.026 ppm) fou nd in the pristine forest sites may be explained by natural processes like the weatheri ng of rock, volcanic activity and rain containing dissolved inorganic matter, all of which may be contributors to stream composition at the upper sites (Allan 1995, Mitchel l 1995). Our results support our expectation that there are low to no levels of lead (0.11 0.01 mg/L), mercury ( < 0.001 mg/L) and arsenic ( < 0.001 mg/L) because they are rare in Costa Rica and are indicative of commercial contamination (Amn 2006, LaMotte 2004)). Also as expected, the upper sites had no chloride (an indicator of do mestic activity). The uppermost forest site and the CPI site were tes ted for the presence of total coliform, fecal coliform (a component of total coli form) and E. coli (a component of fecal coliform). Total coliform was found at both sites; however, levels were much higher at CPI (851.43 NMP/100mL) than the forest (29.86 NMP/1 00mL). Fecal coliforms have been found in the run-off of bromeliads and other l eaves in a tropical pristine forest (Rivera et al. 1987). This provides an explanation for the presence of coliform bacteria we found in the stream. Animal feces are another po ssible explanation for the presence of total coliform at the forest site (Calvo 2006). The statistically greater abundance of coliform bacteria at the CPI site is likely to be r elated to anthropogenic activities. High levels of fecal coliform are indicative of pathogen ic bacteria, viruses and parasites from domestic sewage or animal waste (EPA 2006). On aver age there was 405.71 NMP/100mL of fecal coliforms found at the CPI site, which was much higher then the standard for treated wastewater (< 100 NMP/100mL) ( Calvo 2006). In this study, we cannot exclusively isolate any point source of the contamination, it could be from CPI or any of the private residences further upstream alon g the Quebrada Mquina. At sites with observed exposure to domestic waste, such as the CPI site and the Hotel Belmar site, the concentration of the other c ontaminants were relatively low in comparison to the sites with exposure to commercial wastes such as the gas station and the off-road sites. Although no significant differe nce was found in the levels of heavy metals, sulfide or chloride between these sites and the others, there was a discernible trend of higher mean levels of iron and copper at t he gas station and off-road sites. The mean concentration levels of iron (3.27 ppm) and co pper (0.17 ppm) were higher at the gas station and the off-road sites, than the CPI an d Hotel Belmar sites. These trends may be accounted for by the different types of wastes a ssociated with the gas station and the road as compared to the other sites. The gas statio n and the road are exposed to higher levels of commercial wastes including the following : car traffic, gas run-off, battery disposal and metallurgical processes. Additionally, the soil around these sites may have
8 higher concentration levels of copper and iron. The se different wastes and soil makeup may account for the levels of copper and iron in th e water. Heavy metal concentration is also affected by pH and water hardness. As the pH decreases, the solubility of the metals increases, and as the hardness of the water increas es, the toxicity of metals decrease (Mitchell 1995). On the last day of testing, pH lev els were recorded (Table 4). We found a range at all sites close to seven so the pH proba bly did not affect the metals in the stream. Due to limited sampling of pH, statistical significance cannot be confirmed. Chromium-hexavalent and sulfide levels were highly variable and no statistically significant differences were found between any of t he sites. Chromium-hexavalent forms complexes with iron when present and therefore the presence of iron may have masked the presence of chromium-hexavalent (NPS 1997). It was surprising that no sulfides were found because they are strong indicators of domesti c and commercial waste (Lenntech 1998). There have been no previous studies on heavy metals in the streams of the Monteverde region, so there are no data to compare to our investigation. Future studies could examine levels of heavy metals in different s easons, or compare levels in different times of day, since metals fluctuate often (Amn 20 06). Additionally, future studies could test mercury, arsenic and lead throughout a m onth to be able to find out if our findings are accidental or accurate (Amn 2006). It would also be important to test the soil, sediment, and plants for levels of heavy meta ls; heavy metals are stored in the river sediment or in plants along streams (Mitchell 1995) A final suggestion would be to test hardness and pH at every site, and before every tes t. AKNOWLEDGEMENTS We would like to extend our thanks to Karen Masters for helping us design our project and offering mor al support throughout the process. A huge thanks to C armen Rojas, our personal research assistant and translator who always had a smile on her face and a cab ride. Thanks to our wonderful TAÂ’s, Tom and Camryn, for their editing and supply scavenging ski lls. Thank you to microbiologist Alfonso Calvo for analyzing our coliform samples and Laboratrio LAMD A. Thank you to the owners of Hotel Belmar and Luna Azul for full access to the sites near their b usinesses. A very special thanks to Stinky, our fo ur-legged field assistant. LITERATURE CITED Allan, J.D. 1995. Stream Ecology: Structure and Fun ction of Running Waters. Chapman & Hall. London. pp 23-30. Amn, R. 2006. Personal communication. LAMDA. San J ose, August 2006. Artavia, V.G. 2000. Water Quality Assessment of the Quebrada Cambronero Using Biological Indicators. UCEAP Tropical Biology Program-Spring. Burns, C.J. 2000. Water Quality Assessment of the R io Guacimal. UCEAP Tropical Biology ProgramSpring. Calvo, A. 2006. Laboratorio microbilogico, Cerro P lano, Monteverde. August 2006. DHHS: Department of Health and Human Services. CDC Center for Disease Control and Prevention. . Accessed August 5, 2006.
9 Dyer, D.B. 2003. A Field Guide to Bacteria. Cornell University Press. Ithaca and London. pp 135-136. EPA. 2006. . Accessed July 30, 2006. Essman, J. and S. Zarpas. 1990. Canaries of the Str eam. The Conservationist. NYSDEC: 8-10. Gillespe, R., D. Humphreys, C. Baird and E. Robinso n. 1986. Chemistry. Allyn & Bacon Inc. Boston. pp 751. Lamotte Smart 2 Colorimeter OperatorÂ’s Manual. 2004 Safe Water Lab model SCL-04 code 1991. Lenntech. 1998-2000. . Accessed. July 5, 2006. Malmqvist, B. and S. Rundle. 2002. Threats to the R unning Water Ecosystems of the World. Environmental Conservation 29: 134-153. Miller, P.M. 2000. The Effects of Human-caused Dist urbances on Water Quality and the Capability of River Ecosystems to Recover from Disturbances: Usin g Benthic Macroinvertebrates as Indicators of Water Quality. CIEE Tropical Ecology and Conserv ation-Fall. Mitchell, K.M., and W.B. Stapp. 1995. Field Manual for Water Quality Monitoring. Thompson-Shore Printers. Dexter, MI. pp 86-69. NPS. 1997. Environmental Contaminants Encylopedia. . Accessed July 30, 2006. Rivera, S., T. Hazen and G. Toranzos. 1988. Isolati on of Fecal Coliforms from Pristine Sites in a Trop ical Rainforest. Applied and Environmental Microbiology 54: 513-517. Schultz, M.A. 1998. The Effects of Pollution on Wa ter Quality and Species Richness on Diversity. CI EE Tropical Ecology and Conservation Biology Program-S ummer. Silvia, H. and L. Hansen. 1998. Biotic Indicators o f Water Quality in the Rio Guacimal from the Headwaters to the Estuary. UCEAP Tropical Biology P rogram-Fall. ToxFAQs: CABS/Chemical Agent Briefing Sheet. ATSDR/ Divison of Toxicology and Environmental Medicine (DTEM). 2006. . Accessed Augu st 2, 2006. USGS. 2006. . Accessed Ju ly 30,2006.
10 Table 3: Standard toxicity levels for each contamin ant compared with mean concentrations found in the Quebrada Mquina n = 7. (Note: Arsenic, Lead and Mercury n = 1) *Values are effectively zero (1) DHHS 2006, (2) LaMotte, 20 04, (3) ToxFAQs 2006 Table 4: pH Levels for all sites ( n = 1) Location on Quebrada Mquina pH Levels Forest Upper 7.4 Forest Middle 7.3 Forest Lower 7.2 Belmar 7.6 CPI 6.7 Gas station 7.6 Off-road 7.5 Contaminant in Water Standard Toxicity Levels Mean Level in Quebrada Mquina Arsenic (1) > 10 ppb < 0.01 mg/L* Chloride N.A. < 4 ppm Chromium (2) > 0.5 ppm 0.03 ppm Copper (2) > 1.0 ppm 0.09 ppm Iron (2) > 0.2 ppm 1.63 ppm Lead (1) > 15 g/L 0.11 mg/L Mercury (3) > 0.002 mg/L < 0.001 mg/L* Sulfide N.A. 0.05 ppm
11 Table 5 a., b. & c. Sign tests of coliforms in the Quebrada Mquina. There is a significant difference between levels of coliform in upper fore st site and the CPI site (Negative sign indicates significance of higher coliform levels at the CPI site compared to the uppermost forest site and allows rejection of null hypothesis ) a. E. coli b. Fecal coliform n nr r "! c. Total coliform n nr r #$ $ !# #$ n nr r $ $ #
12 # # # #$ # # # # %n& n %n& '(() %n& *+n ,)n-& & .n( nrn Figure 2. The mean chromium concentration (ppm; with standard error bars) in the Quebrada Mquina at five locations (n = seven days). There was no significant difference between the site locations a nd the abundance of chromium. (Friedman Test, c2 = 6.23, p = 0.39, df = 6) # # # # # nrn %n&n ,)n -&r .n( Figure 3 The mean copper concentration (ppm; with standard error bars) in the Quebrada Mquina at five locations (n = seven days). There was no significant difference between the site locations and the abundance of copper. (Friedman Test, c2 = 3.314, p = 0.51, df = 4). Figure 4 The mean iron concentration (ppm, with standard error bar) in the Quebrada Mquina at seven locations (n= seven days). There was not a significant difference between the site locations a nd the abundance of copper. (Friedman Test, c2 = 12.51, p = 0.052, df= 6) # # # # # %n& n %n& '(() %n& *+n ,)n-& & .n( nrn Figure 5 The mean sulfide concentration (ppm; with standard error bars) in the Quebrada Mquina at five locations (n = seven days). There was no significant difference between the site locations and the abundance of sulfide. (Friedman Test, c2 = 4.44, p = 0.72, df = 6). # # # # # %n& n %n& '(() %n& *+n ,)n-&&.n( nrn
13 n/n(0&+n r(n( 12nn& rn0n 3) r Figure 6. The average E. coli (in NMP/100ml, SE bars included) in the upper and CPI site in comparison t o the treated wastewater standard and the average pristin e stream water quality. There is a significant diffe rence between the concentrations at CPI and the upper sit e (Kruskal-Wallis Analysis, c2 = 26.10, p < 0.0001, df = 4) n/n( 0&+n r(n( 12nn& rn0n 3) r Figure 7. The average fecal coliform (in NMP/100ml, SE bars included) in the upper and CPI site in comparison to the treated wastewater standa rd and the average pristine stream water quality. The re is a significant difference between the concentrations at CPI and the upper site (Kruskal-Wallis Analysis, c2 = 23.59, p < 0.0001, df = 4) $ n/n(0&+n r(n( 12nn& rn0n 3) r Figure 8. The average total coliform (in NMP/100ml, SE bars included) in the upper and CPI site in comparison to the treated wastewater standard and t he average pristine stream water quality. There is a significant difference between the concentrations a t CPI and the upper site (Kruskal-Wallis Analysis, c2 = 29.91, p < 0.0001, df = 4)