This Ant is an "Aphid Rancher." (SE Costa Rica)
Research conducted with: Carrie Bishop, Katie Kettler, J.P. Oehrtman, Joel Thrash
Contamination associated with wastewater effluent and micropollutants has been researched for many years as a source of water quality degradation; additionally these processes have been linked with the development of eutrophication. Eutrophication can be simply defined as the process of increasing primary production as a result of increased nutrient loading. Consequently, this result can lead to significant changes in marine community structure in a couple of different ways; either by “shifting” species composition among groups of primary producers (benthic algae, phytoplankton, or macrophytes), or by completely changing a dominance type. For example, a shift from a macrophyte-dominated system to an algae-dominated system, or algae-dominated to an angiosperm-dominated system (Portielje et. al., 1995).
Primarily, water quality problems associated with nutrient loading and the process of eutrophication can be strongly linked to point-source pollution or effluent pipes. Effluent wastewater may contain a wide range of organic compounds depending on its source; commonly ammonia, nitrogen, and phosphates from untreated or partially-treated sewage. Dissolved oxygen content may also be a factor when present with other compounds. Often times, aquatic systems are characterized by high nutrient and contaminant loading from both urban and agricultural input. These systems are usually highly productive, supporting a wide range of plant and animal species and maintaining complex food chains (Koelmans et. al., 2001).
San Salvador, Bahamas is one particular area where this potential for nutrient loading and eutrophication may be in existence. The Gerace Research Center, located on the north side of the island, utilizes an effluent pipe to directly release both wastewater and untreated sewage directly into Graham’s Harbor. Consequently, ammonia wastes, nitrogens, carbons, dissolved oxygen, as well as freshwater is being introduced to the saltwater, marine ecosystem of the harbor. As a result, these compounds and solutions will invariably have an affect on primay production, specifically the abundance and diversity of algal and grass species within a proximate area of the effluent source.
In a study performed by Llorens et. al. (1993), they state that the development of blooms of green algae, along with phytoflagellates and other microorganisms such as diatoms is an indication of “low organic loading.” However, they additionally mention that algal growth and primary productivity largely depend on solar radiation and temperature, and are affected additionally by organic loading and nutrient availability. Because of this, it may be difficult to ascertain how a combination of these factors will affect an aquatic community in relation to dominant types and species composition in an area such as Graham’s Harbor.
For our study of Graham’s Harbor, we hypothesize that the areas within closest proximity to the effluent pipe will show higher concentrations of algae and grass species when compared to areas up current. Additionally, we estimate that this area will show a lower species diversity and species individuals will be more productive in growth (taller).
The initial task was to determine the number of transects and samples to take around the effluent pipe. Five transects were measured at 10m increments with the central transect located at the pipe, while the four remaining transects were placed 10m and 20m both “up current” and “down current” of the pipe. Each transect was measured to a length of 20m off shore and divided up into five 4m increments along the length. Measurements of percent coverage were taken using a 0.5m2 quadrant, two measurements were recorded at each of the five increments of a transect (20m, 16m, 12m, 8m, 4m). Figure 1. displays the experiment grid.
Figure 1. Transect grid for the measurement of algal and grass species abundance and diversity in proximity to Gerace Research Center effluent pipe. Graham’s Harbor, San Salvador, Bahamas
In addition to percent coverage, the approximate height and number of species were also recorded. Percent coverage was divided into three categories: low (0-33%), medium (34-66%), and high (67-100%). Salinity testing was also completed using a refractometer at an equivalent distance to the pipe along each transect to determine any differences in fresh water presence, both up and down current.
The evaluation of the data collected was completed using the Analysis of Variance (ANOVA) test. This test would allow for any significant difference among the five transects to be detected; a p-value of .05 was used in order to achieve 95% confidence in our test, decreasing the chance of a type I error. For instance, a p-value of less than 0.05 indicates a significant difference. Post Hoc analysis (Scheffe’s) was also completed based on the finding of significant difference from the ANOVA, this test would pinpoint and identify which specific transects were significantly different from others.
The results from the ANOVA for number of species yields a p-value of .0014 (<.05), indicating there is significant difference in the number of species among the five transects, this can be stated with 95% confidence. Figure 2. displays the ANOVA statistical analysis as well as visual representation of the number of species at each transect. A general trend to note is the decreasing number of algal and grass species the closer in proximity to the effluent pipe.
Figure 2. ANOVA results and graphical analysis of the varying number of algal and grass species in proximity to the Gerace Research Center effluent pipe. San Salvador, Bahamas. P-value < .05 indicates significant difference.
Further examination from Scheffe’s Post Hoc analysis (Table 1.) indicates that the transect located 20m up current from the effluent had a significantly different number of species than the transect at the effluent pipe (p-value .0166). Additionally, the transect located 20m down current indicated a significant difference in species from the pipe transect (p-value .0166).
Table 1. Scheffe’s Post Hoc analysis of varying number of algal and grass species in proximity to the Gerace Research Center effluent pipe. San Salvador, Bahamas. Significant differences indicated = S.
With the statistical analysis of percent bottom coverage among the transects, ANOVA indicates there is significant difference. At the 95% confidence level, p-value = .0001. Figure 3. visually shows the differences among the five transects; the generally trend being that the lowest percent coverage was found at the pipe transect and increased downstream with the 20m downstream transect having the highest.
Figure 3. ANOVA results and graphical analysis of the % bottom coverage of algal and grass species in proximity to the Gerace Research Center effluent pipe. San Salvador, Bahamas. P-value < .05 indicates significant difference.
Scheffe’s Post Hoc further supports the data that is visually shown. As a result, the down 20m transect had a significantly different percent coverage than down 10m, up 20m, up 10m, and the pipe transect at p-values of .0004, .0001, .0001, and .0001 respectively (Table 2.).
Table 2. Scheffe’s Post Hoc analysis of the % bottom coverage of algal and grass species in proximity to the Gerace Research Center effluent pipe. San Salvador, Bahamas. Significant differences indicated = S.
Results from the ANOVA for vegetation height were similar to the results for percent coverage in that there was a significant difference shown among the five transects with a p-value of .0006. Similarly, in the examination of Figure 4. there is a visual indication that vegetation height at the pipe transect is lowest, while down current 20m produced higher approximate vegetation height for both grasses and algae.
Figure 4. ANOVA results and graphical analysis of the vegetation height of algal and grass species in proximity to the Gerace Research Center effluent pipe. San Salvador, Bahamas. P-value < .05 indicates significant difference.
Completion of Post Hoc analysis supported the visual results of Figure 4. indicating that both the up 20m transect and down 20m transect are both significantly different from the pipe transect at p-values of .0412 and .0008 respectively (Table 3.).
Table 3. Scheffe’s post hoc analysis of the % bottom coverage of algal and grass species in proximity to the Gerace Research Center effluent pipe. San Salvador, Bahamas. Significant differences indicated = S.
Based on experimentation results, the only hypothesis that was supported was the decrease in species diversity with closer proximity to the effluent pipe. The results, conversely, did not support the prediction that percent coverage would increase in areas closer to the pipe, however showed the trend that percent coverage increased further down current with down 20m having “high” coverage. Similarly, results for approximate vegetation height revealed the trend that height increased down current from the pipe rather than with proximity to the effluent as the previous prediction stated.
One possible conclusion for the tendency of species diversity to be lower at the pipe is that nutrient loading from the wastewater produced an environment that favored more hardy or competitive species such as Turtle grass (Thalassia testudinum) and the genus of green algae Penicillus. A probable reason for the trend of lower percent coverage and height at the effluent pipe could be due to the amount of freshwater entering Graham’s Harbor, this in combination with certain nutrient loads may have been outside tolerable ranges of benthic algae and grass species. The process of dilution may be accountable for the reason height and percent cover were much higher down current, providing a much more tolerable or even “ideal” environment for growth.
Another possible factor that may have been investigated further would be the connection of decreased salinity in combination with nutrient loading. Salinity tests reveal that the water in close proximity to the pipe had a slightly lower salinity level (3.6) versus the level of salinity up current and outside of the sampling grid (4.2). A consequence of this difference would be a decrease in the presence of algae and grasses that may have a very narrow salinity tolerance range.
As mentioned previously in a study by Llorens et. al. (1993), algal growth and primary productivity depend on a wide variety and combination of factors especially solar radiation, temperature, organic loading, and nutrient availability; because of this, it is difficult to ultimately determine which combination of factors are producing trends of grass and algal growth from the Gerace Research Center effluent in Graham’s Harbor. Possible avenues of future research would include not only increasing the size of the test area, but take readings from other areas of the harbor at a further distance from the research center. More accurate water testing could be achieved, such as pH, nutrient content, and chemical content with proper equipment, this would enable the identification of more specific compounds that may be harmful or favorable to the growth of primary producers. Additionally, measures of biomass within the area and creation of species diversity index would allow for more accurate data on species distribution and percent coverage, rather than approximating coverage from a quadrant.
Llorens, M.; Saez, J.; Soler, A. Primary productivity in a deep sewage stabilization lagoon. Water Research v. 27 (Dec. '93) p. 1779-85.
Welch, E.B.; Hickey, Christopher W.; Quinn, J.M. Periphyton biomass related to point-source nutrient enrichment in seven New Zealand streams. Water Research v. 26 (May '92) p. 669-75.
Koelmans, A.A.; Van der Heijde, A.; Knijff, L.M.; Aalderink, R.H. Integrated Modelling of Eutrophication and Organic Contaminant Fate & Effects in Aquatic Ecosystems. A Review. Water Research v. 35 (Oct. ’01) p. 3517-3536
Portielje, R.; Kersting, K.; Lijklema(M), L. Primary production estimation from continuous oxygen measurements in relation to external nutrient input. Water Research v. 30 (March ’96) p. 625-643.
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