Geomorphic and Water-Quality Factors Affecting Algae and River Food Webs


Algae in streams are affected by light availability, nutrient supply, physical habitat conditions, and grazing by herbivorous macroinvertebrates and fish, among other factors reviewed in Stevenson and others (1996). Streamflow, channel gradient, sediment supply, and other factors dictated by the river’s geomorphic framework affect the amount and quality of shallow riffle habitat suitable for periphyton to develop in the Molalla River, which in turn may influence the abundance and make up of grazer and fish populations at higher trophic levels. 


Through its influence on stream channels and aquatic life in streams, flooding and associated changes in the streambed can have profound effects on the river and its ecology. Peak-flow events, particularly ones that result in mobilization of stream bed material, can alter benthic communities and riverine food webs by suppressing or releasing algal populations through physical removal mechanisms (scour by sediments) and by affecting interactions among organisms occupying multiple trophic levels including primary producers, invertebrate and fish grazers, and top level predators (Powers and others, 2008). These influences can ultimately affect algal biomass levels, which are important because some of the water-quality impacts, such as high pH or low levels of dissolved oxygen, are worse when algal biomass is high. And, as an important food resource, algal abundance can govern the success of organisms positioned higher on the food chain that in the Molalla River culminates in fish.


Floods can have direct effects on channel location and form, and channel avulsions in the Molalla River have created new channels through the flood plain, resulting in dry abandoned channels in some reaches, which have unknown impacts on fish-spawning areas. Also, the channel migration and widening that has occurred in some areas produces a less shaded river, which can allow more sunlight to penetrate, promote higher water temperatures and bacterial growth, and lower dissolved oxygen concentrations in the river. Additional sunlight also favors the development of periphyton, including nuisance types of filamentous green algae such as Cladophora. Although determining the cause and effect relations among the various potential factors that affect algae was beyond the scope of this study, the multivariate analyses described below did identify some combinations of geomorphic and water-quality variables that could explain a significant amount of variability in the algal assemblages. 


Multivariate Analyses of Diatom Assemblages


To supplement the algal autecological indicator species analyses, non-parametric multivariate statistical techniques were performed on the diatom species composition data (cell density and algal biovolume) using PRIMER-E, version 6 (Clarke and Gorley, 2006). Such analyses help simplify the inherent complexity of the algal species data and resulted in a better understanding of patterns in the diatom assemblages among the sites or samples. These multivariate techniques allowed for testing of water quality and geomorphic variables to identify factors that may influence the diatom assemblage structure. 


After removing the three non-diatom taxa from the dataset, diatom-only data were square-root transformed and Bray-Curtis similarity matrices were generated to produce a non-metric multidimensional scaling (MDS) ordination plot (fig. 32). The ordination algorithm works to position samples (points on the plot) having greater similarity closer to each other, and samples that are more dissimilar are plotted farther apart through an iterative process until the most parsimonious result is achieved. Using this method, complex multivariate data can be simplified into plots containing just two dimensionless axes. 


Initially, analyses were carried out for density and biovolume separately, which produced inconsistent ordinations for the four possible combinations of cell density/biovolume for the July and August data-collection periods. In one case, the sites were arranged in a downstream pattern indicative of subtle change from one site to the next, whereas other ordinations either grouped sites inconsistently or not at all. These issues result from the fact that the algal data matrix is highly skewed by a few taxa that occur in either high density (small fast growing benthic diatoms Achnanthes minutissima and Achnanthes linearis; appendix B) or those with very large cell biovolumes of 5,000–6,000 µm³ (stalked diatoms Gomphoneis herculeana, Cymbella cistula, and Cymbella tumida; appendix C) that emphasizes their abundance in analyses based on biovolume. Differences in the various ordinations (not shown) reflect that analyses based on density emphasize small taxa whereas biovolume data highlight the larger taxa. The final analysis was based on a hybrid of density and biovolume, developed by averaging the relative cell density and relative algal biovolume into one expression for the analysis. This allows for simultaneous influence by the most abundant diatoms based on size and numbers. In addition, because the most abundant taxa were found at all five sites, there was a high degree of similarity among samples from the five main-stem sites in the Molalla River, ranging from 47 to 76 percent during each sampling. Considering that percent similarities of 60–70 percent are on par with what might be expected in replicate samples, these high percent similarities reveal, along with the low species richness, that algal assemblages did not vary considerably at the sites sampled. 


The resulting algal species ordination shows a trajectory in samples from Glen Avon Bridge downstream to the Highway 211 site and on to the Highway 213 site, then the trajectory changes direction whereby the Goods Bridge site plots closer to Glen Avon Bridge, whereas the Knights Bridge site is positioned out of the loop in the far corner (fig. 32). When considered in light of the results from the algal autecological analyses, the pattern in the ordination indicates that assemblages at the Goods Bridge site are more similar to those at the Glen Avon site. Higher proportions of oligotrophic, pollution-sensitive diatoms that require high levels of dissolved oxygen and lower abundances of eutrophic and high-pH-indicator diatoms were found at the Goods Bridge site (fig. 31). Actual measurements of water quality at Goods Bridge in 2010 show dissolved oxygen concentrations near saturation for much of the day, with daily minima of 85–90 percent saturation, relatively low conductance (65– 70 µS/cm), low concentrations of SRP (approximately 0.01 mg/L), and moderate concentrations of nitrate (0.07– 0.08 mg/L), but as mentioned previously, nutrient and dissolved oxygen levels measured in August and September actually indicated a small decline in quality from Highway 213 to Goods Bridge.


Associations between the algal species composition data matrix and the environmental data matrix (geomorphic and water quality variables: tables 8, 9, and 14), and select habitat data from Cole (2004) were examined using the BEST procedure in PRIMER-E. The analysis identifies variables and combinations of variables that best describe the variation in algal assemblages among sites. For this analysis, binary environmental variables including the presence of local gravel bars and bedrock were assigned a value of “1” for presence or “0” for absence, and all environmental data were log transformed and standardized, or “normalized” in PRIMER-E, prior to utilization in the BEST analysis. Because the BEST analyses were performed on just a few samples (n=5 for the average of July and August samplings), these results represent only a cursory view of the potential interactions between algal assemblages and their environment. Other factors, such as benthic invertebrate grazing, light availability, or inputs of nutrient-rich groundwater, which can be important in shaping algal assemblages (Lyford and Gregory, 1995; Stevenson and others, 1996), were not evaluated during this study or included in this analysis. 


The multivariate analyses linking the periphyton species composition with a variety of environmental variables found that several environmental variables (table 15), in combinations of 4 to 5 variables each, produced significant models. Only the top 4- and 5-variable solutions are shown in table 15. 
The highest overall correlation (Rho=0.98, P=0.007, table 15) was attained with a 4-variable model that included the maximum pH in September, open canopy percent, the presence of local gravel bars, and bedrock. Because all algal samples were collected from riffles, some of the geomorphic influences on algae suggested by the BEST analyses could be governed through effects on the quality of riffle habitats, shading, or other factors, even through direct or indirect effects on benthic macroinvertebrates and grazing rates, although none of these mechanisms was evaluated during this study.


Among the water-quality variables, the afternoon (maximum) value of pH explained the greatest amount of variation in algal assemblages (table 15). Diatoms are especially sensitive to pH conditions, and pH is considered a fundamental factor in shaping the composition of diatom assemblages (Birks and others, 1990). Photosynthesis by algae also raises the pH through a shift in the inorganic carbon equilibrium (Wetzel, 1983) that results from algal uptake of carbon dioxide, so it is not surprising that the multivariate analysis would identify pH as being an important explanatory variable in shaping the diatom assemblages during summer. The high abundance of alkaliphilic diatoms in the river is also consistent with the alkaline pH values observed during summer, but it is unclear to what degree, if any, the alkaline pH affects the diatom assemblages, especially given the high similarity among samples. 


The percentage of open canopy, as determined by Cole (2004) was important in the 4- and 5-variable BEST models (table 15). Light can have a strong effect on algae (Lyford and Gregory, 1990), and daily cycles of oxygen production are predictably suppressed, for example, by cloudy weather, which reduces the sunlight required for photosynthesis. In the Molalla River, light availability is also partly controlled by channel width and sinuosity, which were highest in the alluvial GR3 reach.


An active stream channel, indicated by a high channel sinuosity (table 15; fig. 15), widened active channels (fig. 16), and high channel migration rates (fig. 17) can increase light availability for algae by reducing the amount of riparian vegetation or the effective shade through increases in the channel width as observed at the Goods Bridge site near the downstream end of GR3. Then again, a highly mobile channel can facilitate reworking of gravels and cobbles during high flow events that may scour algae from streambed substrates, reduce biomass, and ‘reset’ the system. Alternatively, reworking of gravels during bankfull flow events may also produce a positive effect on the algal biomass by reducing benthic invertebrate grazers. For example, studies over an 18-year period on the Eel River in northern California found that scouring high flows exceeding bankfull discharge had profound effects on vulnerable benthic macroinvertebrates that echoed through the river food web up to fish (Powers and others, 2008). In the absence of bankfull flows during winter, high survival of algal grazers resulted in higher abundance of macroinvertebrates in spring, especially Dicosmoecus caddisflies that graze on filaments of Cladophora (Wooton and others, 1996). In contrast, winters with flows exceeding bankfull discharge reduced the invertebrate grazers, which resulted in greater abundance of algae (Powers and others, 2008). Flows in the Molalla River during the winter preceding the 2010 summer sampling peaked at about 240 m³/s (8,500 ft³/s), or well below bankfull discharge value for the 2-year recurrence interval of 382 m³/s (13,500 ft³/s). This may explain the high abundances of Dicosmoecus observed in the Molalla River during 2010, and why algal biomass levels were not exceptionally high. Although similar interactions between high flow events, benthic invertebrate populations, and algal assemblages observed in the Eel River also may occur in the Molalla River, deciphering such effects in future studies is complicated by the year to year variability in streamflow conditions and the tendency for the channel to transport bedload material. 


In addition to grazers, another factor governing algal biomass is the length of the algal growing season, which in 2010 was truncated by the cool and cloudy weather. Algal biomass levels presented here may, therefore, be lower than what might occur in years with more sunshine. This fact emphasizes the importance of long-term data and documentation of conditions over a range in conditions so that a better understanding of factors controlling algal-invertebrate-fish dynamics can be developed.


The two other geomorphic variables identified in the BEST analyses were the presence of local gravel bars and bedrock, which can influence algal assemblages through various mechanisms and that operate on different spatial and temporal scales. Cobble and gravel bars provide ideal habitat for algae to colonize and grow, while bedrock can direct groundwater to the surface through features such as contact springs that may deliver nutrients that fuel algal growth. 


Gravel bars in the alluvial section of the middle lower Molalla River can serve many potential ecosystem functions. The gravels are generally clean with little sediment, which provides high quality spawning habitat, and water flows into and out of gravel bars. Such hyporheic flows may produce cool water patches as they do in other rivers (Ebersole and Liss, 2003), and flow through the hyporheic zones or associated habitats can lower nutrients through various biogeochemical processes (Davis and others, 2011; Bencala, 2005; Mulholland and DeAngelis, 2000). Gravel bars also work to aerate surface water, and in the Molalla River, minimum dissolved oxygen levels were 84–87 percent of saturation in August and September 2010, which was sufficient to support a host of benthic organisms for riverine food webs. Benthic respiration in cobble and gravel habitats could contribute to offsetting increases in pH from algal photosynthesis or bring pH down, as was observed in this study in the reach from Glen Avon Bridge to Highway 211. The fact that afternoon pH values now occasionally approach and sometimes reach the State standard of 8.5 during summer places importance on sustaining ecosystem function of such gravel habitats by limiting introduction of fine sediments or “fining” of the coarse productive cobbles. At times, benthic respiration and production of CO₂ in the alluvial GR3 reach appear to more than offset the decrease in CO₂ associated with photosynthesis. In August and September 2000, for example, a 0.5 unit decline in afternoon pH was observed between Highway 213 and Goods Bridge (fig. 26C and D). This may have resulted from greater respiration by benthic communities and (or) input of lower pH ground water or exchanges of hyporheic flows, or from less periphyton that year. Powell (1995) measured distinct declines in stream pH downstream of alluvial reaches of the Little River (North Umpqua Basin, Oregon) and increases in pH in open bedrock channels where algae was abundant but gravels few. In 2010, however, the alluvial reach of the Molalla River contained appreciable periphyton, and as a result there were modest increases in pH of 0.2–0.3 units downstream at Goods Bridge (fig. 26A and B) indicating that photosynthesis utilization of inorganic carbon outpaced respiration. The vast expanses of gravel bars and shallow riffles in the reach upstream of Goods Bridge also result in lowering nutrient concentrations for further algal growth in downstream reaches. Reductions in concentrations of soluble reactive phosphorus and ammonium were observed at the Goods Bridge site in both 2000 and 2010 (fig. 28). Nitrate concentrations, however, were higher at Goods Bridge and increased further downstream at Knights Bridge. This could have resulted from a higher net balance between uptake by algae and inputs of nitrate from tributaries such as Milk and Gribble Creeks, agricultural irrigation return flows, groundwater seeps, urban runoff, or other sources.


The presence of bedrock in a stream channel could influence algal assemblages in a number of ways. As mentioned previously, bedrock may bring groundwater to the surface within the channel or through contact springs along the banks, which could affect water chemistry by enhancing nutrient and major ion concentrations. Inputs of cooler groundwater could also, for example, moderate minimum and maximum water temperatures, as was observed in the nearby Clackamas River (Burkholder, 2007). Conversely, the absence of bedrock and dominance by alluvium in much of the reach upstream of Goods Bridge (GR3) could produce a habitat that is conducive to streamflow gains and losses (hyporheic exchange) that could affect the physical and hydraulic habitat conditions and the downstream water chemistry. Hyporheic flow into and out of gravel bars was commonly observed in the Molalla River, especially in the reach downstream of Highway 213. The daily maximum water temperature at Goods Bridge, although higher than at the Highway 213 site, was not as high as the longitudinal trajectory might suggest (fig. 24). In 2001, a very warm, low flow-water year, water temperatures did not increase much in the reach between Highway 213 and Knights Bridge (fig. 25), which could be from hyporheic cooling or inputs of cooler groundwater near the downstream end of the alluvial reach. Although not measured in this study, it is possible that shallow or regional groundwater enters the river upstream of where bedrock again emerges to the surface near Canby. The longitudinal pattern in streamflow during June 2000 (fig. 24C) showed about a 7 percent loss in flow at Rkm 15.8 despite the input of Milk Creek. Then, a 20 percent gain in flow was observed downstream at Canby. Although part of this increase can be attributed to input of Gribble Creek, the measuring site was downstream of the Canby drinking water intake, so the increase is likely larger.


First posted February 29, 2012