Seasonal Dynamics of Water Quality in the Plum Creek Tributary of the Black
River in NE Ohio as a Function of Land Use Practices
Mercedes Allen, Ryan King, Garrison Loope, Cheryl Wolfe-Cragin
Fall 2007, ENVS316
ABSTRACT
In 1985, the Black River was on a list of the most polluted and degraded problem areas in
the Great Lakes Watershed due to poor water quality. Plum Creek, a tributary of the
West Branch of the Black River, is considered an area of transition from the
urban/suburban portions of Lorain County to the highly agricultural areas found
upstream. It is important to understand the effects of seasonal nutrient loading due to
land-use in a stream during the course of an entire year in order to effectively manage the
watershed and maximize stream water quality. We expected elevated nutrient levels in
the spring due to high rainfall and subsequent runoff from spring fertilization in upstream
agricultural fields and during the fall due to application of manure and fall plowing. We
sampled Plum Creek at four sites, a point downstream from the town of Oberlin, one
point in the town, and two points upstream. The points upstream were, directly
downstream from a golf course and the other, above the course, representing the flow
from land that is primarily agricultural. Water samples were collected weekly from the
sites during spring, summer, and fall of 2007. They were analyzed for NO3 and PO4
concentrations, along with BOD, and turbidity. Depth was determined using a gauge
height measure [?], and precipitation data was collected from a local rain gauge. There
was no nutrient peak found corresponding to spring fertilization, but the concentrations of
NO3 and PO4 show distinct seasonal variation with varying degrees of correlation with
precipitation. [A sentence with management and/or future study conclusions would be
useful]
[Nice abstract, much improved!]
INTRODUCTION
Land use activities within a watershed have important influence on stream water quality
and can affect both spatial patterns and temporal patterns (Dodds and Oaks 2006). High
levels of nutrients are often introduced into agricultural streams from surrounding lands
through the runoff of nutrients and erosion by precipitation within the watershed.
Excessive levels of nutrients can lead to the eutrophication of stream waters and the lakes
into which they drain, depleting the water of oxygen and thereby impairing biological
processes (Dodds and Oaks 2006). Plum Creek is considered an area of transition from
the highly agricultural areas of Lorain County to the Urban/Suburban regions. Plum
Creek enters the West Branch of the Black River which then flows north through highly
residential and industrial areas to Lake Erie at the city of Lorain. It [Plum Creek or
Black River? If Plum Creek, this comment seems in contrast to statement about it being
“transitional”] is an agricultural watershed with conventionally planted corn, soybeans,
and winter wheat dominating the crops. A few beef and dairy cattle operations are
located in the very southern and western portions of the watershed. The City of Oberlin
with a golf course, forested park, and storm water inputs make land use patterns in this
agricultural watershed a little different from those described in the literature for Black
River [? Cite reference – specifically what literature?]. Since most regulations governing
land use in this region are made at the local level, an understanding of the impacts of
nonpoint pollution is crucial in order to identify and implement best management
practices (BMPs) in the agricultural community and effective zoning practices by local
officials [very useful statement as justification for your research]. Previous studies on
Plum Creek have focused on the fall, however it is important to understand the effects of
seasonal nutrient loading in a stream during the course of an entire year in order to
effectively manage the watershed and maximize stream water quality. [Good
development of gap in knowledge. As part of creating this gap, it would be useful for
you to describe (citing literature) typical patterns of seasonal water quality in agricultural
watersheds, and then indicate what these patterns might or might not apply to this
particular watershed (i.e. why it is important to directly measure).]
In 1985 the Water Quality Board of the International Joint Commission placed the Black
River on a list of 43 of the most polluted and degraded Areas of Concern (AOC) in the
Great Lakes Watershed and prescribed a Remedial Action Plan process (RAP) due to loss
of habitat, persistent toxins in sediments, and other impairments found in the mainstem
(Hartig and Zarull, 1992). The RAP efforts have been successful at cleaning up point
sources of pollution in the watershed, but to date have been rather ineffective in attempts
to curtail agricultural and construction nonpoint impacts on the watershed (Conlin,
October 2007). Additionally, the Total Maximum Daily Load (TMDL) document for the
Black River as required by the Clean Water Act is currently being drafted by the Ohio
Environmental Protection Agency (OEPA) and will serve to prioritize nonpoint source
remediations and preventative actions in the watershed (Conlin, September 2007).
However, the nutrient, turbidity, and Biological Oxygen Demand (BOD) information in
the draft report was obtained from just one OEPA sampling site on the Plum Creek
located near its confluence with the West Branch (Conlin, September 2007). In order to
specify effective local BMPs and zoning practices, more specific information is needed
from additional sampling locations on Plum Creek that may help to distinguish land use
impacts. [This paragraph is not well integrated with prior paragraph]
Three previous studies have addressed nutrient dynamics of the Plum Creek. In 2000,
Fessenden et al. established that during low flow conditions, the headwaters and the
surrounding agricultural lands contribute high levels of sedimentation and nutrients
(specifically NH4+, PO43-, and NO32-) to the creek. In 2004, a study by Cummings et al.
examined the impact of urban runoff from the City of Oberlin on nutrient concentrations
before, during, and after a storm event. Their report concludes that nutrient
concentrations and turbidity tend to increase with increased flow rate. They also
observed that the City of Oberlin tends to increase nutrient concentration and turbidity
during low flow periods and decrease them during high flow periods (Cummings et al.
2004). In the third Plum Creek study in 2006, fluctuations in ion concentrations were
found by Feeser et al. with high concentrations associated with storm-drain inputs within
the City. They found that while there are numerous increases in nutrient concentrations
throughout the City, Oberlin has an overall diluting effect on both phosphate and nitrogen
ion concentrations (Feeser, et al. 2006). [Nice summary of previous work]
These previous studies of nutrient dynamics have been limited to the fall. While we, too,
sample Plum Creek during the fall, we also analyze data collected in the spring and
summer of 2007 by Feeser and Soong to determine if there are any seasonal variations in
nutrient concentrations. Our objective was to compare the water quality at four Plum
Creek sites in different seasons to determine seasonal variability in nutrient levels. Each
site is directly downstream from a different land use: Because streams are always flowing
and are influenced by the immediate surroundings, in situ processes, and upstream
dynamics, biological processing and nutrient inputs and outputs are difficult to quantify.
The water quality at a given sampling point in the river is a function of the water entering
the stream at the next sampling point upstream, plus whatever is added through pipe
outfalls and through runoff between sampling points and also of any biogeochemical
transformations that may have taken place in the stream between these points (Petersen,
2006). By studying nutrient concentrations in Plum Creek throughout a year we intend to
relate different types of seasonal land use and the resulting nutrient concentrations in the
creek. [Last sentence does not necessarily follow from preceding sentences –
biogeochemical processes in streams will be a function of temperature as well as land use
activities].
HYPOTHESIS
Our objective was to compare the water quality at four Plum Creek sites in different
seasons.. Each site is directly downstream from a different land use: #1 City of Oberlin,
#2 Forested Park, #3 Golf Course, #4 Agricultural Fields. (See figure 1.) Analogous
studies of NE Ohio agricultural ecosystems have found that nitrogen levels are low in the
summer, while nitrogen levels are high in winter due to high flow and loading combined
with low removal rates (Birgand, year?) [anything available on spring runoff or on P?].
We expected elevated nutrient levels in the spring due to runoff from spring planting in
upstream agricultural fields and during the fall due to application of manure and fall
plowing. Also, based on previous studies we expected the City of Oberlin to dilute
inorganic nutrients downstream (Feeser et al. 2006). Based on previous studies, we
expected that during high stream discharge in the spring there would be elevated nutrient
levels at site #4 due to the application of fertilizers associated with agricultural planting
and site #3 due to turf planting/maintenance at the golf course. (See Fig. 1) We also
expected elevated nutrient levels in the fall especially at site #4, associated with the
observed application of manure on fields, fall tillage, and the planting of winter wheat,
but did not expect the levels to be as high as in the spring. We expected turbidity to
follow a similar pattern due to the runoff carrying particulates from tilled agricultural
fields and the increased flow of water disturbing the stream sediments (Dodds and Oaks
2006). We also expected nutrient concentrations to progressively decrease downstream
during high flows in all seasons due to a dilution effect of Oberlin’s stormwater system.
Site #1 should show what is contributed by the City of Oberlin and we expect it to reflect
an increase in nutrients during low flow times (summer) and a decrease in nutrients
during the higher flow times based on Fesser et al. We expected the levels of nutrients in
all seasons to decrease slightly throughout the arboretum due to uptake through biological
processes in the stream and the data associated with the samples collected at site #2
should reflect that [would you expect biological processes to vary seasonally?]. We
predict that biological activity would have little effect on nutrient concentrations ,
especially during high flow periods, due to the constant flow and short residence time of
water within streams (Dodds and Oaks, 2006). [This last sentence appears to contradict
the sentence before. Do you think biological activity in the stream is important or not?
Will this vary with flow?]
MATERIALS AND METHODS
Data on PO4, NO3 [subscripts], turbidity, pH, BOD, and distance from bridge to water
surface were collected weekly from four sites on Plum Creek in the watershed of the
West Branch of the Black River by Feeser, Lauterbur, Soong in the fall 2006, by Soong
and Feeser in the spring of 2007 and Braziunas during the summer of 2007 (Braziunas,
2007). The sampling sites are located in the City of Oberlin at the bridge on Hamilton
Street (site #4), the border between the golf course and the arboretum (site #3), the bridge
on Professor Street (site #2), and the bridge on 511 (site #1). We continued sampling
from these sites at the same frequency using identical methods in order to facilitate data
comparison. In keeping with Ohio EPA protocol, we took samples starting at the farthest
downstream location (#1) and moved upstream to site #4 (Nichols, 2007). We took
samples from bridges using a sampling pole and bottle to reach the middle of the creek in
order to prevent contamination with debris from the bed. Samples taken at bridges were
upstream of the bridge. Distance from bridge to water surface was measured to determine
relative flow. We defined “high flow” as a distance greater than 130 inches from the
Professor Street bridge. Samples were taken weekly on Wednesday afternoons or as close
as possible. Turbidity, pH, and BOD (with two duplicates) measurements were taken on
the samples using protocols from Standard Methods for the Examination of Water and
Wastewater (Clesceri, 1989). BOD measurements were diluted based on the relative
turbidity of samples and appropriate calculations from Peterson 2007 were used to find
the oxygen demand. Two small samples from each site were filtered and frozen for later
analysis using the ion chromatograph to determine levels of PO4 and NO3. Neither were
diluted as we are dealing with a natural water body. Additionally, the ion data collected
over the past year was examined as well as the stream depth, turbidity, pH, and BOD for
those samples. Hourly stream height information was also obtained from a datalogger
placed in Plum Creek at site #2 [this is inconsistent with what you write in your abstract].
Detailed information regarding precipitation was obtained from the AJ Lewis Center
Data Monitoring Information System. We defined the seasons as follows: March-May =
spring, June-August = summer, September-November = fall, and December-February =
winter.
[Perhaps say something about why NH4 was not measured – found to be very low
relative to NO3 in prior studies and therefore not analyzed]
[Need to describe depth measures – use of tape measure and the particular automated
depth gauge used. Also you need to describe relationship between depth and flow –
mention that you don’t have a rating curve and so can’t directly related variables to flow]
Figure 1:
Flow
3
1
2
4
Figure 1. Map of sampling locations along plum creek. Site 1 = 511, Site 2 = Professor St., Site 3
= Ladies Grove, and Site 4 = Hamilton Street. Samples were taken from downstream to upstream.
Flow of stream is indicated on map.
RESULTS
Figure 2:
6
Nitrate Seasonal Change
Site 1
Site 2
Site 3
Site 4
5
Nitrate (mg/l)
4
3
2
1
0
28-Nov
21-Nov
13-Nov
7-Nov
31-Oct
24-Oct
22-Aug
16-Aug
10-Aug
Sample dates
4-Aug
28-Jul
14-Jul
7-Jul
30-Jun
23-Jun
12-May
5-May
27-Apr
20-Apr
14-Apr
5-Apr
23-Mar
17-Mar
10-Mar
3-Mar
-1
Figure 3: [figure legend? Units on y axis?]
5-day precipitation prior to sampling
Precipitation (in)
5
4
3
2
1
0
PO4 concentration (mg/l)
0.7
Site
Site
Site
Site
0.6
0.5
1
2
3
4
Phosphate Seasonal Change
0.4
0.3
0.2
0.1
0.0
28-Nov
21-Nov
13-Nov
7-Nov
31-Oct
24-Oct
22-Aug
4-Aug
28-Jul
14-Jul
7-Jul
30-Jun
23-Jun
12-May
5-May
27-Apr
20-Apr
14-Apr
5-Apr
23-Mar
17-Mar
10-Mar
3-Mar
Sampling Date
Figure 4. Notice how peaks in precipitation do correlate with peaks in nutrients above,
but the large discrepancies make clear that precipitation and runoff are only one factor
controlling nutrient concentrations in Plum Creek. [It is not clear whether you intend for
this text to serve as a legend or not. A figure legend in a paper should guide the reader in
how to read the graph, but should not draw conclusions or inferences about the
significance of the graph]
Figures 2 and 4 show graphs of Plum Creek nitrate and phosphorous data including each
sample date and each sample site. Both nitrate and phosphate graphs show distinct
seasonal variation. Both nutrients are stable at low concentrations from March to early
August and show very little fluctuation with changing precipitation (figure 3). Nitrate is
28-Nov
Figure 4: [Figure legend? Units? ]
21-Nov
13-Nov
7-Nov
31-Oct
24-Oct
16-Aug
22-Aug
10-Aug
10-Aug
16-Aug
4-Aug
28-Jul
14-Jul
7-Jul
30-Jun
23-Jun
12-May
5-May
27-Apr
20-Apr
14-Apr
5-Apr
23-Mar
17-Mar
10-Mar
3-Mar
sampling dates
higher and much more variable from late August through November. Also in this period
nitrate concentration appears to be strongly influenced by relative precipitation [refer to
figure. Phosphate is also higher and more variable from late August through November,
but it isn’t correlated to precipitation like nitrate is. It must also be noted that because
phosphate levels were so low. [Are the data in the graphs that follow for all sites or only
for one of the sites? The reader does not know this unless you specify]
Average Nitrate (mg/l)
Figure 5: These are interesting graphs. Legend? Units? Text is too small to read. Did you try
a regression?]
Nitrate vs gauge depth
5
4
3
2
1
Spring
Summer
20Fall
0
0
5
10
15
Gauge water depth at Professor St.
Figure 6:
Average Phosphate (mg/l)
Phosphate vs gague depth
0.6
0.5
0.4
Spring
0.3
Summer
Fall
0.2
0.1
0.0
0
5
10
15
20
Gauge depth at Professor St.
Figures 5 and 6 show nutrient concentrations graphed against water depth measured by
the gauge at Professor St which can be thought of as a proxy for relative flow. There is a
positive relationship between nitrate and gauge depth but the relationship is weaker in the
phosphate graph. [Regression coefficients for these two would have allowed you to make
this point quantitatively rather than qualitatively.]
Figure 7:
depth v depth
Distance between bridge and
water surface at Professor
St (in)
130
140
150
160
Figure 8: [Units?]
BOD vs Turbidity
16
14
BOD (mg/ml)
12
10
Spring
Summer
Fall
8
6
4
2
0
0
20
40
60
80
100
120
140
Turbidity
Figure 7 plots two our two types of depth measurements against one another [which axis is which?
It would be instructive to see also a relationship between your 5 day precipitation and depth]. There
is a relationship, but we think that the gauge is more reliable because it always samples exactly the
same place. Figure 8 shows that there is a weak relationship between BOD and turbidity through all
seasons. This suggests that the debris that makes the water turbid has a lot of organic carbon
[results should describe but not interpret findings. Discussion section is where data are interpreted.
Again, a regression would allow you to quantitativey describe the relationship, (which looks pretty
Figure
strong9:to me)].
Turbidity vs Flow
140
120
Turbidity
100
80
Spring
Summer
Fall
60
40
20
0
0
5
10
Gauge Depth
15
20
Figure 10:
BOD vs Nitrate
Spring
Summer
Fall
16
BOD (mg/ml)
14
12
10
8
6
4
2
0
0
2
4
6
8
10
12
Nitrate (mg/l)
Figure 9 shows that there is a relationship between turbidity and relative flow mainly
during the spring and fall [Would be interesting to have seperate regressions for each
season]. Something else is causing turbidity during the summer low flow period.
Figure 10 shows that there is no relationship between nitrate and BOD. This suggests
that nitrate and labile carbon in the stream have different sources.
Figure 11: Nutrient Concentrations at sampling sites for High Flow
10-Mar
5-Apr
14-Apr
20-Apr
5-May
12-May
30-Jun
7-Jul
14-Jul
28-Jul
4-Aug
10-Aug
16-Aug
7-Nov
13-Nov
28-Nov
NO3 Site 1
PO4 Site 1
NO3 Site 2
PO4 Site 2
NO3
0.42
0.01
0.46
0.01
0.10
0.05
-0.03
0.01
0.75
0.06
0.87
0.06
0.29
0.05
0.29
0.05
0.29
0.05
0.35
0.05
0.42
0.09
0.45
0.10
0.56
0.0629
0.38235
0.07085
0.3958
0.0794
0.42495
0.06815
0.5252
0.08895
0.4889
0.1374
0.7166
0.0788
0.61235
0.0787
2.36725
0.3101
1.53465
0.45685 NA
1.0249
0.1365
0.8264
0.1535
0.8601
0.1411
0.83
0.1483
0.32245
0.2043
0.32345
0.1721
2.01675
0.44255
2.81285
0.5085
2.3485
0.0616
2.96185
0.0856
Site 3
PO4 Site 3
NO3 Site 4
PO4 Site 4
0.45
0.03
-0.03
0.00
0.12
0.01
0.86
0.05
0.95
0.06
0.29
0.05
0.29
0.05
0.30
0.05
0.31
0.06
0.21
0.06
0.42
0.08
0.31235
0.06075
0.2823
0
0.2873
0.0596
0.2833
0
0.37015
0.0926
0.35635
0
0.79355
0.10455
0.59135
0.0726
NA
0
0
0.94785
0.1509
0.8975
0.136
0.84185
0.1488
0.76085
0.1379
0.3226
0.2078
0.34475
0.1215
2.8403
0.53
4.627
0.6503
3.16745
0.08425
3.86225
0.0849
Figure 12: Nutrient Concentrations at sampling sites for Low Flow
3-Mar
17-Mar
23-Mar
27-Apr
23-Jun
22-Aug
24-Oct
31-Oct
21-Nov
NO3 Site 1
PO4 Site 1
NO3 Site 2
PO4 Site 2
NO3 Site 3
PO4 Site 3
NO3 Site 4
PO4 Site 4
0.15
0.05
0.37
0.09
0.05
0.09
0.20
1.58
0.59
0.02
0.46
0.02
0.71
0.00
0.42
0.02
0.32
0.01
0.37
0.01
0.37
0.01
0.44
-0.02
0.74
0.06
1.10
0.08
1.16
0.06
1.27
0.09
0.48795
0.05455
0.4105
0.05645
0.318
0
0.2919
0.0519
2.51295
0.17395
6.82795
0.21985
5.87065
0.2096
5.59835
0.2132
1.3806
0.21295
3.69445
0.27855
3.2979
0.266
3.7286
0.29695
3.08845
0.18295
0.5914
0.13885
0.5934
0.15505
0.6133
0.13925
0.86425
0.03975
0.9306
0.0472
0.95675
0.0533
0.9189
0.0414
Figures 11 and 12 show a tabular presentation of the nutrient concentrations of nitrogen
and phosphorous on each sampling date [these are redundant to graphs]. The data shows
no relationship between flow and nutrient concentration in Plum Creek.
DISCUSSION
In this section, we will discuss and analyze our findings, provide potential
mechanisms and causes, connect our data with other analogous studies within NE Ohio,
and suggest further research. But first it is especially important to address limitations and
modifications we encountered in our experiment design. [This is what you should do, but
no need to so explicitly state this]
First of all, we were unable to make any correlations between the flow rates [do
you mean depth or precipitation? Neither are actually flow, but can be thought of as
related to flow] of the stream with inorganic nutrient concentrations [but the
relationships look reasonable in the graphs and below graph 7 you write, “There is a
positive relationship between nitrate and gauge depth”. Your explanation needs to be
consistent]. We expected the stream at low flow to receive minimal input from the
watershed while, during a post-storm period (high flow), precipitation from the storm
event would likely carry nutrients into the stream from the area. However, it was clear
that this was not the case (Fig. 11 & 12). This frustrating yet important discovery
reallocated our attention to focus more on spatial and temporal patterns in inorganic
nutrients in Plum Creek as a function of land use practices rather than directly studying
the affects of low flow and high flow on nutrient loading. [OK, good, but is it possible
that the approach you took simply was not sufficient to capture a relationship that might
have actually been evident. For example, the sample regime that has been employed this
year has not been designed to actually capture nutrient data at peak flow periods. To
what extent might this influence your interpretation of the data?]
We also observed high variability in the months of August-November with
nutrient concentrations, which might have been due to inconsistencies with our sampling
procedures [be specific]. We measured the height of the water column from the bridge on
Site 2 and plotted our data against the automatic sensor readings during our sampling
dates. We found a strong relationship between the measurements (Fig. 7), suggesting that
the variability was not due to instrumental or human error. The large variability made it
extremely difficult to average the nitrogen and phosphorous concentrations monthly and
correlate nutrient patterns between the sites in a given month.
Despite these adjustments, we can boldly [?] offer several conclusions about our
results regarding the seasonal patterns of inorganic nutrients in Plum Creek through
different land covers. The results of our study indicate that there is seasonal variation in
nitrogen and phosphorous concentrations in Plum Creek. We also concluded that land use
practices do affect the water quality of the stream and account for the seasonal
fluctuations in inorganic nutrients as they move downstream. [Be specific, what do you
think is going on and what mechanisms might account for this?].
The changes in inorganic nutrient concentrations between seasons may be
associated with the application of manure and tilling of agricultural fields in the fall
season. The land use practices by the agricultural fields upstream affects the downstream
inorganic concentrations. In a study conducted by Cummings, et al (2004), it was found
that higher concentrations of nitrogen are being washed out of agricultural land upstream
of Oberlin than the urban/residential portion of Oberlin adds in its own run-off. We found
that nutrient runoff from agricultural fields upstream is in fact the highest [greatest source
of nitrogen] and it is diluted by urban/suburban runoff as it moves downstream (Fig. 2 &
4). [It is very reasonable to draw this inference from the data, but you can’t really state
that you know this since what you measured was nutrient concentration in the stream
water and not the actual movement of nutrients from the fields. There is a way of
finessing your wording so that you make clear to the reader what you know and what you
are inferring. For example, “The fact that nutrient concentrations were highest at xxx
leads us to conclude that …. is likely.]
Furthermore, our data suggest that there are patterns within seasons, as
demonstrated by of the large variability between August-November. This phenomenon
may be attributable to biological activity in the stream [earlier you indicated that you do
not feel this is important]. Although the nitrogen and phosphorous data did not correlate
with precipitation information (Fig. 3), higher turbidity levels would result in increased
erosion of mineral sediment into the stream, as caused by the precipitation during a storm
event. Fesser, et al (2006) concluded that high turbidity would lead to high BOD, as
organic material within the water column is the primary fuel source of most organisms
performing respiration. They also concluded that effects of in-stream biological activity
on nutrient concentrations vary with changes in flow conditions.
We found a weak relationship between BOD and turbidity through all seasons
(Fig. 8). This suggests that the debris that makes the water turbid has a lot of organic
carbon and that other microbial and chemical processes were consuming oxygen. Also,
the weak relationship between turbidity and flow during the summer indicates that
something else is causing turbidity during the summer low flow period [good]. It is
possible that seasonal storm patterns and the accompanying increase in day length may
affect the role of biological processing on nutrient concentrations during different
seasons. This was in agreement with our original prediction that biological activity would
have little effect on nutrient concentrations, especially during high flow periods, due to
the constant flow and short residence time of water within the stream.
Our results are not consistent with a few of our hypotheses. First, increases in
nutrient concentrations occurring within the arboretum contradict this trend of dilution
and are contrary to what we expected to find in this area. This is in agreement with Fesser
et al (2006) and this might be the result of inputs from the storm drainage system.
Secondly, we hypothesized elevated nutrient levels in the spring due to runoff from
spring planting and fertilizer use in upstream agricultural fields. However, our data
indicates no significant trend in nutrient peaks that correspond to spring planting and
fertilization (Fig. 2 & 4). It is possible that high flow in the stream limits the effects of
biological activity, so a lull in storm activities in the spring could account for less nutrient
loading into Plum Creek upstream and that in-stream processing of nitrogen occurs
during low flow, thereby decreasing the amount of nitrogen in Plum Creek during the
spring.
The results of our study indicate that there are general temporal trends in nutrient
concentrations in Plum Creek, and that the effects of land use practices upstream affects
nutrient concentrations downstream. What this study did not accomplish is finding a
strong correlation between nutrient concentrations in Plum Creek and flow conditions. A
study of Plum Creek should be conducted over the course of a full year to establish a
baseline understanding [further explore? Doesn’t this study in part accomplish what you
are suggesting?] of Plum Creek’s nutrient concentrations as a function of flow rate [Do
you mean flow rate here or surrogates for flow such as depth and precipitation?]. This
information would allow us to link our finding of seasonal patterns with meteorological
data, thereby analyzing upstream agricultural practices during different seasons and its
affect on downstream nutrient concentrations. Also, including the months of December,
January, and February at the four sample sites into the annual data would lead to a greater
confidence in the data for future research.
Plum Creek serves as a canvas [? Intended meaning not clear here. Example?
Model? Test case?] for determining potential anthropological courses of action to
address the issue of eutrophication in Lake Erie. Real management implications of our
results and conclusions include a strong attempt to make local management officials
responsible for making farmers aware of their land use practices and their affect
downstream [is awareness the key?]. Officials should also consider reducing [do you
mean requiring reductions?] the application of fertilizers and manure in the fall season.
This will result in lower levels of inorganic nutrients in Black River and ultimately in
Lake Erie [I like your idea of focusing attention on the season that you found greatest
nutrient concentration]. Furthermore, the Black River watershed is mostly agricultural, so
implementing best management practices in the agricultural community can develop into
a larger regional change in land use practices. Continuing this study for multiple years
would aid in interpreting the role of agriculture on nutrient loading into Lake Erie and
help management officials draft changes in BMPs. [This seems important as well. Your
data suggest that this was a dry spring and this may well explain the low nutrient
concentrations that you observed]
LITERATURE CITED
Braziunas, K. September 2007. Personal communication.
Birgand, F. Nitrogen Removal in Streams of Agricultural Catchments
Clesceri, S. Lenore. Standard Methods for the Examination of Water and Wastewater,
17th edition 1989.
Conlin, T. September 2007. TMDL Development for the Black River Watershed, Ohio,
Revised Agency Review Draft, (Version 3, 10-23-2007). Prepared for Ohio
Environmental Protection Agency by Tetra Tech, Inc.
Conlin, T. October 2007. Personal communication.
Cummings, J., T. Reed, K. Weinberger. 2004. The city of Oberlin’s effect on the Plum
Creek watershed during a storm event: variation in upstream and downstream
water quality during and after storm water run-off as a function of urban land
cover. Report for Oberlin College ENVS 316.
Dodds, W.K., and R. M. Oakes. 2006. Controls on nutrients across a prairie stream
watershed: land use and riparian cover effects. Environmental Management
37:634-646.
Feeser et al. [include complete list of authors] 2006. Nutrient Concentrations Along an
Agricultural/Urban Stream During Low Flow and Post-Storm Periods as a
Function of Varying Land-Use and Biological Processing.
Fessenden et al. [include complete author list] 2000. Plum Creek Water Quality. Report
for Oberlin College ENVS 316.
Hartig J. and Zarull M. 1992. Under RAPs Toward Grassroots Ecological Democracy in
the Great Lakes Basin. Pp.5-49.
Nichols, M. 2007. “What? Chemicals in the Water? An Introduction to Chemical Water
Quality Monitoring”, Lecture, Department of Chemistry, John Carroll University.
Petersen, J. 2006. “Methods for Analyzing Aquatic Ecosystems”. Oberlin College.
Petersen, J. December 2006. Editing remarks in Feeser et al. 2006.
APPENDICES
Appendix A: Division of Labor
Allen, Mercedes S.:
Sampler Setup, Filtering, BOD reader, Abstract, Revisions to final poster
and report.
King, Ryan:
Sampler setup, pH and turbidity analysis, Nutrient Graphs, Revisions to
final poster and report, Discussion, Maintenance of sampling instruments
Loope, Garrison:
Sampler setup, Methods and Procedure supervisor, Nutrient-Ion
Concentration Analysis, Peak Corrector on IC, Data Organization, BOD
reader, Revisions to final poster and report
Wolfe-Craigin, Cheryl:
Sampler setup, Introduction, Hypothesis, BOD reader and setup, Public
Communications, Map, Revisions to final poster and report,
Transportation to sampling sites
1. Title
>Clearly indicates what you did and ideally what you found. Y
2. Abstract (250 word max)
>Summarizes what you did, how you did it, what you found, and why it is important. Y,
noticeably improved over proposal
3. Introduction/Background
>Sets context by describing the overall problem that research addresses and appropriately
situates this in larger ecological and societal context. Y, also a great improvement over
proposal
>Cites relevant primary and secondary literature to support arguments (minimum of four
citations). Y, but see comments
>Problem statement establishes gap in knowledge, need for research, and describes how
your research fills gap. Y
>Clearly states mechanistic hypotheses explaining what you expected to observe and
why. Y
4. Methods (revised from proposal)
>Describes what you did in sufficient detail that someone could repeat your experiment.
>Answers what, where, when, and how you made your measurements. See comments,
further explanation of methods and caveats regarding relationship between depth,
precipitation and flow is necessary.
>Includes diagrams, maps of sampling, tables, timelines as appropriate (only if
appropriate). OK
>References literature where appropriate (who’s procedure did you follow?).
5. Results:
>Includes text, tables, graphs & figures that describe but do not explain results. N, see
comments
>Explains calculations. OK
>Indicates statistical significance. See comments, would be useful to include regression
analysis
>Does not present same data in both tables and graphs. N
6. Analysis & Discussion:
>Interprets and critically analyzes your findings. See extensive comments
>Explores connections between your findings and those of other studies (agreement,
disagreement, relevance). Further explanation necessary
>Addresses the usefulness and limitations of the methods you used. Y
>Addresses limitations of findings and suggests further research that might extend or
more conclusively addresses your initial hypotheses and findings. Y
7. Literature cited:
>Uses format of the journals Ecology or American Naturalist. OK, see comments
>Does not use footnotes. Y
8. Figures and figure legends: (tables, graphs, conceptual models, etc. that appear in
introduction, results, and analysis & discussion sections)
>Text legend below each figure describes content in sufficient detail that reader can
understand what the figure represents without reference to text in manuscript . N, see
comments
>Symbol legend within the frame of each graphic indicates what different color bars,
lines or shapes represent. Y, but Fig 5 and 6 too small to easily see
>Figures are numbered sequentially in the order in which they appear in the paper. Y
>Every figure that appears in paper is directly referenced within the paper. Y
>Units are indicated either within the figures (often in the x and y axis labels) or in the
text legend. N!
9. Appendix 1: Division of labor:
>Describes role of each group member in developing and implementing the project. Y
10. General comments:
Mercedes, Ryan, Garrison and Cheryl:
It is clear that productive work went into revising the abstract and introduction sections.
The gap in knowledge is clear as is the general context for understanding the importance
of your study. See extensive notes in methods, results and discussion sections. Some of
what you write appears to be contradictory and in general these sections would benefit
from clearer and tighter organization. Layout of poster was nice, though map is a bit
noisy with details (hard to see creek).Your poster presentation was generally clear. With
a bit more rehearsal, you could have reduced redundancy and shortened length of
presentation. The conclusions you stated in your poster presentation were tighter than
what I see here in the report.