The Effect of Land Use on Stream Water Quality in San Luis and CaÃ±itas Anna Stuart Burnett Department of Environmental Studies, Washington and Lee University ABSTRACT Human altered landscapes often have significant impacts on water quality in their respective watersheds. However, in order to create policy and educate people about better land use practices, it is necessary to have a thorough understanding of the effects of land use on stream water quality. This study looks at the health of stream water in three streams flowing through different land uses forest, cattle pasture, and coffee in San Luis and CaÃ±itas in the Monteverde area. Water quality was determined using biotic and abiotic indicators. The abiotic indicators include d dissolved oxygen, temperature, nitrogen, phosphorus, pH, and turbidity. Macroinvertebrates were sampled for t he biotic indicators , which include d the number of taxa (families) per site , and the Biological Monitoring Working Party Index (BMWP). The site s were compared in terms of similarity using a Morisita index of similarity. The Morisita index showed that similarity between site s was more likely a result of the stream the sample was tak en from than the land use it was taken in. Overall, the site s all had regular to high water quality according to the BMWP scores , indicating good land use practices. There were no significant correlations between the biotic and abiotic indi cators of water quality. C ombined with the good water quality of the streams, this study indicate s that there was too little pollution in the streams to have a significant impact on the macroinvertebrate communities. This study can provide comparisons to future studies on streams with more pollution as well as aid in determining the tipping points for abiotic factors that result in macroinvertebrate declines. RESUMEN Los paisajes alterados por humanos generalmente tienen impacto sobre la calidad de sus respectivos recursos hidricos. Sin embargo con el fin de crear politicas y educar a las personas sobre mejores prÃ¡cticas agrÃcolas, es necesario tener un entendimiento d e los efectos del uso de la tierra en la calidad del agua. En este estudio se determinÃ³ la calidad de tres quebradas, que fluyen a traves de diferentes usos de tierra bosque potrero y plantaciÃ³n de cafÃ© en San Luis CaÃ±itas en el area de Monteverde. La ca lidad de agua fue determinada usando factores bioticos y abiÃ³ticos. Los indicadores abiÃ³ticos incluyen oxigeno disuelto, temperatura, nitrÃ³geno, fosforo, pH, y turbidez. Los macroinvertebrados fueron muestreados por factores biÃ³ticos, que incluyeron nÃºmer o de taxa por sitio y el (BMWP Costa Rica). Los sitios fueron comparados en terminos de similitud usando el Ãndice de Morisita de similaridad. Los indices de Morisita mostraron que la similitud entre sitios es resultado de la quebrada en que fue tomada, ma s que en el uso de la tierra circundante. En general, todos los sitios tuveron BMWPs de regulares a altos indicando un buen uso de la tierra, No hubieron correlaciones significativas entre los indicadores bioticos y abioticos de la calidad de agua. Combina do con la buena calidad del agua de las quebradas, este estudio indica que habia poca contaminaciÃ³n en las quebradas para tener un impacto significativo en la comunidad de macroinvertebrados. Este estudio puede proveer comparaciones para estudios futuros e n quebradas con mas contaminantes, tambien puede ayudar a determinar los factores abiÃ³ticos que determinan el declive de macroinvertebrados. INTRODUCTION Humans have been altering the landscape and likewise negatively impacting aquatic ecosystems for thousands of years. Agricultural land use such as grazing, deforestation, and crop cultivation all have direct influences on watershed characteristics, changin g the chemical, physical, and
biological features of running waters (Allan 1995) . Some of the major impacts of agriculture include decreased streamside vegetation as well as increased sedim ent, chemical, and nutrient run off. A study by Omernik ( 1977 ) showe d a clear relationship between nitrogen and phosphorous nutrient levels in streams and land use, with streams on agricultural land having higher concentrations than streams draining from forested land (Allan 1995) . Therefore , important chemical factors to test water quality include turbidity, pH, nutrient levels, and oxygen levels. D issolved oxygen (DO) is one of the most important abiotic factors influencing water quality and therefore the diversity and abundance of aquatic invertebrates (Thorp & Covich 19 91) . While these data can be useful to determine the instantaneous quality of the water, testing biotic indicators can provide a much more thorough test of water quality because they are affected by intermittent pollution that may not be present at the tim e of sampling (Goodnight 1973) . The most commonly recommended organisms for biological monitoring are benthic macroinvertebrates (Resh et al. 1996) . Cattle pasture and coffee cultivation are the two primary agricultural practices in the Monteverde region. Cattle pastures impact aquatic ecosystems through erosion, accounting for 84% of Costa Rica's erosion (Griffith et al. 2000) . Improperly handled manure is also a serious source of pollution from cattle pastures (Griffith et al. 2000) . While the environmental impact of pesticide use in Monteverde cattle pastures is unknown, it is believed that properly used fertilizers can improve vegetation quality and reduce erosion. For coffee farms in Monteverde, the primary inputs are herbicides such as Round up Â® . However, most of the coffee farms in Monteverde are producing successfully with apparently very few negative impacts on the environment, mostly as a result of the sound practices of the local Cooperative (Griffith et al. 2000) . Using both chemical and biological indicators, I will study the impact of different land uses on water quality in San Luis and CaÃ±itas , specifically looking at land under cultivation for coffee, land in cattle pasture, and land that is forested. One unknown that may affect my hy pothesis is that natural longitudinal changes in water quality occur, but are undocumented for the streams I surveyed (Harding et al. 1999) . I hypothesize that the water quality of the stream in the forest land use area will be better than for either of th e streams in agricultural land use s and further, that the stream in land under c ultivation for coffee will have higher water quality than the one in a cattle pasture. This research is important for providing empirical evidence of the impacts of various lan d uses, allowing policy makers to make informed recommendations. MATERIALS AND METHODS Study Site My study sites were located in the towns of Sa n Luis and CaÃ±itas near Monteverde, Costa Rica. I identified three streams of similar size, two that flowed th rough forest before transitioning into a human changed landscape, coffee and cattle pasture, and one that remained entirely in forest. I divided each stream into two sites: upstream (U) and downstream (D). I took three samples per site, for a total of 18 s amples. The forest steam in San Luis was named Alondra and the part I sampled w as on Mar he other two were in CaÃ±itas, one in and one near coffee farm. A ll my samples were taken between 8am and 3 pm .
Abiotic Water Quality Measurements I measured water quality using the following abiotic factors: temperature, turbidity, pH, dissolved oxygen (DO), and nutrient levels of phosphorous (P) and n itrogen (N). I visually tested the water for turbidity, and I tested pH using LaMotte color tablets. I took water samples from the field and used the LaMotte water quality kit and colorimeter to measure P and N . I used a n Oakton membrane electrod e to measure DO and temperature at the sample site. Biotic Water Quality Measurements I collect ed macroinvertebrates as my biological indicator of water quality because they have different, known tolerances for pollution and poor water quality , and sensitive species will be absent from im paired streams (Lehmkuhl 1979) . To collect m acroinvertebrates , I used a 12 inch benthic macroinvertebrate collection sieve and a pair of tweezers. I placed the sieve in the water and scraped the rocks, sand, or debris in front of it to dislodge the macroinvertebrates , which were then caught in the sieve. I used the tweezers to remove the macroinvertebrates from the sieve and placed them in a vial of 95% ethanol. In a study in Costa Rica in 2008, Mauer and Springer found that sampling for 60 minutes or more, rather than the recommended 8 10 minutes, resulted in a bett er representation of the taxonomic diversity and likewise water quality (Maue r et al. 2008) . Rather than sampling for a set amount of time as recommended, I sampled each site until I had at least 100 individuals or until I had been sampling for 75 minutes , with an average of 52 minutes per sample site (Mitchell et al. 1995) . I identified the macroinvertebrates to family in the lab under a stereoscope . I determined water quality using taxa (family) richness and the BMWP (Biological Monitoring Working Party Score System) (Resh et al. 1996) . The BMWP is a system created specifically for macroinvertebrates in Costa Rica. It ranks the macroinvertebrates on a scale of 0 9 with 9 being the most intolerant families and therefore the best indicators of high water quality. BMWP determines water quality based on the sum of the scores of the macroinvertebrates using a scale of 0 120, where 120 is excellent quality water (Springer et al. 2007) . I used regression analyses to compare the biotic and abiotic indicators of water quality. This show ed whether they were significantly correlated and allow ed me to identify the level of water quali ty of each site . I also used the Morisita Index of Similarity to determine how similar each site was in terms of family richness and abundance. RESULTS I identified a total of 1 , 634 macroinvertebrates from 36 families . Trichoptera was the most abundant order with 716 individuals identified, with the family Hydropsychidae comprising 694 of these. I found at least two families with a BMWP score of 9 at every site (families Hydrobiosidae, Perlidae , Heptigeniidae, and Polythoridae ) ( Table 1 in appendix ) . The total BMWP scores for the six s it es ranged from 70 109 , ( T able 2 ). T he highest water quality according to BMWP occurred in the Forest D and Pasture D site s and I found the lowest water quality in the Coffee D site . I also calculated the number of families (S) for each site ( Table 2 ) . Figure 1 shows that S and BMWP were pos itively correlated ( R 2 = .89, P = .005, n = 6 ) .
TABLE 2: This table s hows the number of families (S) and the BMWP score for each s ite, as well as the average BMWP score for each of the three stream s tested in the Monteverde area ; t he colors for each site remain consistent for all charts and graphs . Forest D Forest U Pasture D Pasture U Coffee D Coffee U BMWP 107 75 109 75 70 90 S 20 14 23 16 15 19 BMWP Stream Aver Forest: 91 Pasture: 92 Coffee: 80 FIGURE 1 : Correlation of BMWP score and number of families per site (S) based on six sites from three streams in the Monteverde area ; (R2 = .89, P = .005, n = 6 ) Neither S nor BMWP were significantly correlated with any of the abiotic factors tested ( Table 3 ) . However, temperature and nitrogen levels were the most closely correlated to S and BMWP respectively ( Table 4 , Figure s 2 and 3 ). TABLE 3: Six a biotic factor s tested for each site in three streams in the Monteverde area Forest D Forest U Pasture D Pasture U Coffee D Coffee U DO (%) 95.67 97.23 95.30 93.27 92.20 95.70 Temp (Â°C) 14.53 13.53 15.93 15.60 15.35 14.93 N (ppm) 9.67 10.00 7.00 10.33 10.75 13.33 P (ppm) 0.26 0.10 0.21 0.19 0.57 0.46 pH 8.50 7.50 7.50 8.00 7.38 8.00 Turbidity Clear Clear Clear Clear Clear Clear 10 12 14 16 18 20 22 24 60 70 80 90 100 110 120 S BMPW
TABLE 4: R esults of the r egression a nalysis between four abiotic factors and the BMWP score and S for each site BMWP Variable Equation R2 F ratio DF P DO y=91. 07 + 0.04X 0.17 0.80 1, 4 0.42 Temp y=14.05 + 0.01X 0.04 0.18 1, 4 0.69 N y=14.9 7 0.05X 0.21 1.07 1, 4 0.36 P y=0.49 0.002X 0.04 0.1 8 1, 4 0.70 S Variable Equation R2 F ratio DF P DO y=92.97 + 0.11 X 0.04 0.17 1, 4 0.70 Temp y=12.78 + 0.12 X 0.24 1.27 1, 4 0.32 N y=14.75 0.26 X 0.19 0.92 1, 4 0.39 P y=.34 0.003 X 0.002 0.01 1, 4 0.92 FIGURE 2 : Regression of the number of families per site ( S) and temperature for each of the six sites FIGURE 3 : Regression of the BMWP sc ore and nitrogen levels for each of the six site s Using the Morisita index of similarity, I was able to determine which site s were the most and least similar in terms of taxa abundance and richness ( Table 5 and Figure 4 ). I found that Forest U and D were most closely related in terms of similarity (95%), as were Coffee U and D (93%). However, Pasture U and D were more similar to Forest U and D respectively (95%, 74%) than they were to each other (71%). Pasture D and Coffee D were the least similar (40%). y = 1.95x 11.38 RÂ² = 0.24 p = .32 10 12 14 16 18 20 22 24 13.0 14.0 15.0 16.0 17.0 S Temp Temp y = 3.87x + 127.08 RÂ² = 0.21 p = .36 60 70 80 90 100 110 120 6 8 10 12 14 BMWP N Nitrogen
TABLE 5: T able showing the results from the Morisita Index of Similarity in terms of percent similarity between each of the six site s based on the richness and abundance of macroinvertebrate families (below diagonal line) and number of shared families ( above diagonal line ) Forest D Forest U Pasture D Pasture U Coffee D Coffee U Forest D X 13 17 10 8 12 Forest U 0.948 X 13 9 8 11 Pasture D 0.735 0.672 X 12 10 13 Pasture U 0.91 0.945 0.718 X 9 10 Coffee D 0.451 0.415 0.402 0.552 X 11 Coffee U 0.724 0.699 0.598 0.809 0.925 X FIGURE 4 : Cluster chart of stream similarity in three streams in the Monteverde area according to the Morisita I ndex of S imilarity using macroinvertebrate richness and abundance . C represents the coffee stream, P represents the pasture stream, and F represents the forest stream, U stands for upstream site s and D stands for downstream site s .
DISCUSSION The BMWP for my six site s ranged from 70 109 , indicating regular to good water quality. Sites Forest U, Pasture U, Coffee D, and Coffee U fall in the 61 100 range and therefore have regular quality water with only moderate contaminants. Site s Forest D and Pasture D are in the 101 120 range and therefore have good quality water with no alterations or contaminants ( Springer et al. 2007). I also found at least two families with the lowest tolerance (a BMWP score of 9) in every stream, indicating good water quality (families Hydrobiosidae, Perlidae , Heptigeniidae, and Polythoridae ) . Perlidae was found at every site with a total of 173 individuals . Hydrobiosidae was found in every stream but Coffee, Polythoridae was found only in the Coffee stream, and Heptigeniidae was only found at the Forest D sit e . These families were much rarer, as I only found 1 7 individuals per site; however, the fact that they were present at all still indicates good water quality . The number of families (S) for each site was positively correlated to BMWP . This means that S i n the Monteverde area is also a good indicator of water quality since as water quality decreases, so does the number of families found . I expected to find better water quality in the upstream, forested reaches of each stream and lower water quality in the Coffee D site and the lowest water quality in Pasture D . However, I found that Pasture D and Forest D had the best water quality according to BMWP, and that only the Coffee stream decreased in quality from upstream to down. Also, contrar y to my hypothesis, Coffee D had lower water quality than Pasture D in BMWP score , DO levels, and the amount of nitrogen and phosphorous present . This implies that more agricultural inputs are running off into the Coffee stream than in the Pasture stream. N one of the abiotic indicators of water quality were significantly correlated with the BMWP for each site . According to the LaMotte colorimiter test instruction manual, water with less than 44 ppm nitrate are acceptable for drinking and water with an excess of .1 ppm phosphorus (using a range of 0 3 ppm) indicates pollution from waste water or drainage from agricultural areas (LaMotte 2007). While only Forest U is considered unpolluted by phosphorous standards , most site s were still relatively low , and all o f the site s were well under the acceptable nitrogen levels. In most unpolluted streams DO levels are above 80% (Hauer et al. 1996). Every site in my study had a DO level above 92%, again indicating good water quality ( Table 3 ). Although none of the abiotic indicators were significantly correlated, temperature and nitrogen levels were the most closely correlated to S and BMWP respectively. While temperature may have an influence on macroinvertebrates by affecting DO levels, it has not been demonstrated that the relationship between macroinvertebrates and temperature is more than coincendental (Thorp et al. 1991). For the streams I studied, it seems possible that chemical factors were not significantly correlated with the biotic factors because they were withi n acceptable ranges for the survival of However, the site s in the Coffee stream had the highest levels of both nitrogen and phosphorous , the lowest average DO level, and also had the lowest average BMWP score. This indicates that there is a certain point at which water quality decreases enough and chemical factors do become correlated with BMWP. I found that the upstream and downstream site s within a stream were most closely relat ed for two of the three streams. Forest U and D were nearest neighbors in terms of similarity (95%), as were Coffee U and D (93%). However, in the pasture stream, Pasture U and D were more similar to Forest U and D respectively (95%, 74%) than they were to each other (71%). I
expected the site s in pasture and coffee land use to be similar due to lower water quality, but I found that Pasture D and Coffee D were the least similar (40%). In conclusion, I found that none of the streams were severel y impacted by human alterations or contaminants according to abiotic factors and the BMWP index of stream health. N one of the abiotic factors I tested were significantly correlated to BMWP or S . This indicates that the abiotic factors are all within accept able ranges for the survival of macroinvertebrates and therefore are not limiting factor s that affect BMWP or S in the streams I studied . However, the fact that the Coffee stream had the lowest water quality in terms of both chemical and abiotic factors in dicates that there may be a tipping point at which chemical factors do become correlated with BMWP. According to the Morisita Index of S imilari ty for the streams surveyed , the most important factor in determining similarity between site s seems to be the stream itself, not the associated land use. This is a good sign for the agriculture of the Monteverde area , not taking urbanization into account , indicating that local farming practices do not seem to have a significant impact on health of the surrounding waterways. Future studies should include a follow up of the same streams I used to see if chemical factors change significantly from day to day , which may impact the biotic and abiotic correlations . It would also be helpful to include land uses with more known inputs and lower water quality to compare with the healthier streams I studied. ACKNOWLEDGEMENTS I would like to thank my advisor Pablo All e n for his enthusiasm and guidance throughout my project. I would like to thank Yimen Ar aya for his help with statistics and Guillermo Vargas for allowing me to use his stream . I also would like to thank my host family for their patience and support, especially Marvin Leiton for showing me around San Luis and allowing me to use his stream. I would like to thank Rafa Santamaria for his help in locating my study sites in CaÃ±itas and providing me with reliable transportation. Finally, I would like to thank my professors and family for encouraging me to study abroad in the first place. LITERATUR E CITED Allan, D . 1995. Stream Ecology: Structure and Function of Running Waters . Chapman & Hall, New York . Goodnight, C . 1973. The Use of Aquatic macroinvertebrates as Indicators of Stream Pollution. Transactions of the American Microscopical Society . 92:1. 1 13. Griffith, K ., D. Peck and J. Stuckey . 2000. Agriculture in Monteverde: Moving Toward Sustainability . In: Monteverde: Ecology and Conservation of a Tropical Cloud Forest, N. Nadkarni & N. Wheelwright. Oxford University Press, New York , pp. 394 407. Harding, J. ; R. Young, J. Hayes, K. Shearer, and J. Stark . 1999. Changes in Agricultural Intensity and River Health Along a River Continuum. Freshwater Biology , 42: 345 357. Hauer, F. R. and W. Hill. 1996. Temperature, Light, and Oxygen. In: Metho ds in Stream Ecology. F. R. H auer & G. Lamberti. Academic Press, Inc., San Diego, pp. 93 106. LaMotte. 2007. SMART2 Colorimiter Reagent Systems Tes t Instructions . Available in PDF on LaMotte website . Lehmkuhl, D. 1979. How to Know the Aquatic Insects. Pictured Key Nature Series, Dubuque .
Maue r , T . and M. Springer . 2008. Effect of methodology and sampling time on the taxa richness of aquatic macroinvertebrates and subsequent changes in the water quality index from three tropical rivers, Costa Rica. Revis ta de BiologÃa Tropical. 56:4 . 257 271. Mitchell, M . and W. Stapp . 1995. Field Manual for Water Quality Monitoring. Ann Arb or. GREEN Project . Resh, V ., M. Myers and M. Hannaford . 1996. Macroinvertebrates as Biotic Indicators of Environmental Quality. In: M ethods in Stream Ecology . F. Richard Hauer & G. Lamberti. Academic Press, I nc. , San Deigo , pp. 647 655. Springer, M . , et al. 2007. uso Del Indice BMWP' CR de la calidad de l agua. s.l. : University EARTH . Thorp, J. and A. Covich . 1991. An Overview of Freshwater Habitats. Ecology and Classificatino of North American Freshwater Invertebrates. Academic Press, Inc. , Boston p. 17 37.
APPENDIX TABLE 1: Total number and distribution of macroinvertebrates identified in each of the six sites studied in streams in Monteverde Order/ Family Forest D Forest U Pasture D Pasture U Coffee D Coffee U Totals Annelida 6 17 7 5 4 3 42 Annelida 1 1 6 5 4 2 19 Hirudinea 5 16 1 1 23 Blattodea 7 1 8 Blaberiidie 7 1 8 Coleoptera 11 4 19 27 176 119 356 Curculionidae 1 1 Elmidae 5 1 1 4 3 14 Gyrinidae 1 1 2 Haliplidae 1 1 Hydrophilidae 2 2 Limnichidae 1 1 Psepheridae 1 1 Ptilodactylidae 6 3 16 25 169 114 333 Staphylinidae 1 1 Diptera 11 11 53 2 3 80 Chironomidae 8 8 Dolichopodidae 1 1 Simulidae 3 10 53 1 67 Tipulidae 1 1 2 4 Ephemeroptera 37 22 36 11 5 14 125 Baetidae 14 3 1 1 3 22 Heptageniidae 1 1 Leptohyphidae 20 19 31 11 4 7 92 Leptophlebiidae 2 4 4 10 Hemiptera 6 10 10 2 5 33 Belostoma 2 1 1 4 Gerridae 1 1 2 Naucoridae 3 7 7 4 21 Veliidae 3 2 1 6 Megaloptera 3 1 3 7 Corydalidae 3 1 3 7 Odonata 14 6 35 15 4 3 77 Aeshnidae 3 3 8 1 15 Calopterygidae 11 3 24 15 3 1 57 Coenagrionidae 3 3
Polythoridae 1 1 2 Plecoptera 50 38 10 2 43 30 173 Perlidae 50 38 10 2 43 30 173 Shrimp 3 4 4 6 17 Decapoda 3 4 4 6 17 Trichoptera 146 203 73 115 69 110 716 Hydrobiosidae 7 7 2 1 17 Hydropsychidae 136 196 69 114 69 110 694 Leptoceridae 1 1 Philopotamidae 1 1 Polycentropodidae 2 1 3 Total 284 302 249 198 308 293 1634
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Burnett, Anna, Stuart
El efecto del uso de la tierra en la calidad del agua del ro en San Luis y Caitas
The effect of land use on stream water quality in San Luis and Caitas
Human altered landscapes often have significant impacts on water quality in their respective watersheds. However, in order to create policy and educate people about better land use practices, it is necessary to have a thorough understanding of the effects of land use on stream water quality. This study looks at the health of stream water in three streams flowing through different land uses forest, cattle pasture, and coffee in San Luis and Caitas in the Monteverde area. Water quality was determined using biotic and abiotic indicators. The abiotic indicators included dissolved oxygen, temperature, nitrogen, phosphorus, pH, and turbidity. Macroinvertebrates were sampled for the
biotic indicators, which included the number of taxa (families) per site, and the Biological Monitoring Working Party Index (BMWP). The sites were compared in terms of similarity using a Morisita index of similarity. The Morisita index showed that similarity between sites was more likely a result of the stream the sample was taken
from than the land use it was taken in. Overall, the sites all had regular to high water quality according to the BMWP scores, indicating good land use practices. There were no significant correlations between the biotic and abiotic indicators of water quality. Combined with the good water quality of the streams, this study indicates that
there was too little pollution in the streams to have a significant impact on the macroinvertebrate communities. This study can provide comparisons to future studies on streams with more pollution as well as aid in determining the tipping points for abiotic factors that result in macroinvertebrate declines.
Los paisajes alterados por los humanos generalmente tienen un impacto sobre la calidad de sus respectivos recursos hdricos. Sin embargo con el fin de crear polticas y educar a las personas sobre las mejores prcticas agrcolas, es necesario tener un entendimiento de los efectos del uso de la tierra en la calidad del agua. En este estudio se determin la calidad de tres quebradas, que fluyen a travs de diferentes usos de tierra- bosque potrero y plantacin de caf- en San Luis y Caitas en el rea de Monteverde. La calidad del agua fue determinado usando factores biticos y abiticos. Los indicadores abiticos incluyen oxgeno disuelto, temperatura, nitrgeno, fosforo, pH, y turbidez. Los macroinvertebrados fueron muestreados por factores biticos, que incluyeron nmero de taxa por sitio y el ndice (BMWP Costa Rica). Los sitios fueron comparados en trminos de similitud usando el ndice de Morisita de similaridad. Los ndices de Morisita mostraron que la similitud entre los sitios es el resultado de la quebrada en la que la muestra fue tomada, ms que en el uso de la tierra circundante. En general, todos los sitios tuvieron Indices de BMWPs de regulares a altos indicando un buen uso de la tierra. No hubo correlaciones significativas entre los indicadores biticos y abiticos de la calidad del agua. Combinado con la buena calidad del agua de las quebradas, este estudio indica que haba poca contaminacin en las quebradas para tener un impacto significativo en la comunidad de macroinvertebrados. Este estudio puede proveer comparaciones para estudios futuros en quebradas con ms contaminantes, tambin puede ayudar a determinar los factores abiticos que determinan el declive de los macroinvertebrados.
Text in English.
Environmental impact analysis
Costa Rica--Puntarenas--Monteverde Zone
Anlisis de impacto ambiental
Calidad de agua
Costa Rica--Puntarenas--Zona de Monteverde
Tropical Ecology Fall 2009
Ecologa Tropical Otoo 2009
t Monteverde Institute : Tropical Ecology