Imran Rafi Ahmed Abdullah Punekar
Bio 3255 – Fall 2004
Interspecific competition lab report
Competitiveness and effects of differing densities of rye-grass (Lolium multiflorum) on
combined leaf length of soybean (Glycine max) plants does not differ between potting soil
and 33% sand environments.
ABSTRACT
Plant growth can be measured by several different variables, and is controlled by many
more. Interspecific competition can inhibit plant growth by exploiting shared resources or
having a direct influence on the growth of the target plants. Experiments were conducted
with differing planted seed densities of rye-grass (Lolium multiflorum) which competed
against soybean plants (Glycine max) in a potting-soil environment as well as a sandy, 33%
potting soil environment. It was hypothesized that rye-grass, being a more widely common
plant, would be a stronger competitor against soybean plants in the sandy environment
which t was expected that soybean would have a harder time adapting to. The results
indicated that there was no significant difference in the competitiveness of rye-grass against
soybean between the two environments. This suggests that the difference in environments
was not severe enough to elicit a difference in competition.
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INTRODUCTION
Plant performance in terms of growth is limited by many factors. These may include the
availability of resources such as nutrients, water, space, and sunlight which may be controlled by the
presence of intra- or inter-specific competitors. Intraspecific competition is typically critical only in
high-density populations and works to limit population size by reducing resources overall.
Interspecific competition, on the other hand, can be more complicated in that different species of
plants may have greater affinities for, and demands on, specific classes of resources. Therefore, the
effects of interspecific competition are more difficult to predict because they may rely on the
restriction of shared resources or direct interference between specimens of different species
(Ricklefs 2001:365-76).
In this experiment, the competitiveness and effects of differing densities of perennial ryegrass (Lolium multiflorum) on the combined leaf length of target soybean (Glycine max) plants were
tested and measured. The aim of this study was to determine what effect, if any, the higher
competitor density would have on the growth of the target specimens. Specifically, the effect, in
relation to soil quality, on target combined leaf length—a parameter measured by calculating the
sum of the lengths of each leaf on the plant—was examined, along with the dependent variables of
target plant height, mass, and number of leaves.
Higher densities of rye-grass were expected to result in inversely proportional performance
of the target soybean plants. In order to analyze the effect of soil composition, trials were repeated
in both potting soil and a 67% potting soil – 33% sand environments. It was predicted that soybean
growth would be inhibited, in terms of combined leaf length, to a greater degree by high densities of
rye-grass in the sandy environment than in the potting soil environment. Such a relationship, if true,
may be explained by the fact that rye-grass, common across most of the United States as well as
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Europe and adapted to climates as varied as those of Texas, Maine, and Alaska, is able to adapt well
and flourish in different environments successfully, whereas soybean plants, whose region of origin
is much smaller and which are much more dry-intolerant, presumably do not have the same level of
adaptability (Hannaway et al. 1999).
METHODS
This study was conducted in close collaboration with K. Shemanski, of Villanova University,
PA (Shemanski 2004). In order to test the above hypotheses, an experiment was conducted in
which target four soybean plants per pot were subjugated to interspecific competition from rye-grass
in five different competitor densities, ranging from 0 seeds to 80 seeds. A total of 30 pots were
used—split into two trays, one with potting soil, and the other with a 33% sand mixture. Within
each tray, three pots were dedicated to each competitor seed density, thus providing multiple trials
for the same test. The potting soil material was obtained from the potting soil supply at the
Villanova University Biology Department greenhouse, whereas the sandy mixture was custom made
by thoroughly mixing approximately 33% by volume coarse grained sand and 67% of the same
potting soil. The pots were arranged in both trays in the following manner, with the order of the
pots within each row having been determined by the use of a random number table, where A1, B1,
and C1 are identical trials:
COLUMN A
COLUMN B
COLUMN C
(A3) 7 soybean seeds, 40 rye-grass seeds
(B3) 7 soybean seeds, 40 rye-grass seeds
(C4) 7 soybean seeds, 60 rye-grass seeds
(A4) 7 soybean seeds, 60 rye-grass seeds
(B2) 7 soybean seeds, 20 rye-grass seeds
(C1) 7 soybean seeds, 0 rye-grass seeds
(A2) 7 soybean seeds, 20 rye-grass seeds
(B1) 7 soybean seeds, 0 rye-grass seeds
(C5) 7 soybean seeds, 80 rye-grass seeds
(A5) 7 soybean seeds, 80 rye-grass seeds
(B4) 7 soybean seeds, 60 rye-grass seeds
(C4) 7 soybean seeds, 60 rye-grass seeds
(A1) 7 soybean seeds, 0 rye-grass seeds
(B5) 7 soybean seeds, 80 rye-grass seeds
(C2) 7 soybean seeds, 20 rye-grass seeds
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Table 1 – Layout of 15 pots within each tray. A1, B1, C1 are identical trials, and so on. Order of
pots within each column determined by use of random number table.
The seeds were planted on 21 Sep., 2004 and were allowed to grow in a greenhouse setting
(Villanova University Biology Dept. Greenhouse, Villanova, PA) for 8 weeks during which time they
were exposed to daytime lighting and regular watering. Aside from one visit on 6 Oct., during which
the target plants were “thinned-out” to 4-5 per pot, the plants were undisturbed. The local weather
during this time was variable, temperatures ranging from a high of 26 ˚C to a low of -5 ˚C with an
average of 11˚C. The precipitation during this time period for this region was minimal at only
1.99cm (Weather Underground 2004). On 16 Nov., 2004, destructive sampling commenced and the
plants were removed from the pots for measurement and disposal. The soil from the experiment
was duly collected for reuse. During sampling, first the rye-grass plants were cut off at soil level
using a blade, and subsequently collectively weighed then disposed of. Then, the soybean plants
were similarly cut off; each was weighed, its height determined, leaves counted, and combined leaf
length measured. The combined leaf length was an innovative measure carefully performed
according to the following protocol:
1
2
3
4
5
6
7
8
Figure 1 – Protocol showing method of measurement of combined leaf length, an innovative
measurement taken for target soybean plants. Under this protocol, the leaves of a particular plant
are removed, lined up end-to-end, and the total length measured using a standard centimeter-scale
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ruler. In the example above, the total leaf length for this soybean plant with three leaves is
approximately 8cm.
Data from these measurements were recorded and transcribed into JMP IN 4 (v. 4.0.2, SAS
Institute 2000). Further analysis and of the data was performed using various statistical tests using
JMP as well as Microsoft Excel (Microsoft Corp. 2003).
RESULTS
400
350
300
Combined
Leaf
Length
(mm)
250
200
150
100
50
0
-20
0
20
40
60
80
100
Competitive Rye-Grass Seed Density
Linear Fit Potting Soil Tray Data
Linear Fit 33% Sand, 67% Potting Soil Tray Data
Figure 2 – Effects of rye-grass seed density on target soybean combined leaf length in potting soil
and 33% sand mixture. Regression equations:
Leaf length in Potting soil= 241 - 5.10 (Rye-grass Seed Density); F1,13=23.4, P =0.0003, R2=0.643
Leaf length in Sandy soil= 213 - 5.55 (Rye-grass Seed Density); F1,13=10.7, P = 0.0061, R2=0.451
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0.025
0.02
0.015
Slope of Linear Fit
0.01
0.005
0
Potting soil Tray (100% Potting soil)
Sandy Tray (67% Potting Soil, 33% Sand)
Figure 3 – Comparison of slopes of linear fit of target mass vs competitor seed density plots in sandy and
Potting soil trays. Showing Standard Error bars for each.
Tray
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400
350
Soybean
Combined
Leaf Length
(mm)
300
250
200
150
100
50
0
0
.25
.5
.75
1
1.25
1.5
Soybean Mass (g)
Bivariate Normal Ellipse P=0.950 Potting Soil Tray Data
Bivariate Normal Ellipse P=0.950 33% Sand Tray Data
Figure 4 – Bivariate Fit analysis (P=0.950) of dependent variables: Soybean Mass and Soybean
Combined Leaf Length for Potting soil and 33% Sand Mixture Trays.
Combined leaf length vs. Mass correlation in Potting Soil= 91.5%.
Combined leaf length vs. Mass correlation in Sandy soil= 96.2%.
Analysis showed greater correlation between Soybean Leaf Length and Mass than between Leaf
Length and Height (76.7%, 72.7%).
Observations at time of sampling showed few plants which had not grown well. Most of the
poor plants were found in the pots with high rye-grass seed density (60-80 seeds) or were located at
the periphery of the pots, indicating that perhaps neighboring plants had overshadowed them and
thus restricted their growth. In every pot, at least 4 soybean plants were healthy enough to be
measured (Table 1), however in the few cases that there were more than 4 soybean plants, all were
measured.. Visual analysis confirmed the presence of intended plant densities of rye-grass in each
pot for both trays (Table 1).
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Results from both trays indicated a strong relationship between rye-grass density and target
performance as measured by combined leaf lengths (Fig. 1). The relationships between these two
variables were linear and appropriate linear fits were added (Fig. 1). The same was true of target
performance and rye-grass combined mass, however, the R2 values for these were much lower,
indicating a weaker relationship. Counting the actual number of rye-grass specimen alive was not
feasible, and so that variable was ignored.
The visual representation of the difference in the values of the slopes for each tray is seen in
Fig. 3, which also shows the standard error for each slope. An ANCOVA test of the two slopes
gave the following values: F = 0.0514, df = 29, P = 0.823.
A bivariate fit test was conducted on Soybean Leaf Length vs. Height, however, the level of
correlation obtained was rather low, especially when compared to the correlation percentages of
Soybean Leaf Length vs. Soybean Plant Mass (Fig. 4). The high correlation values obtained
indicated a very strong relationship between Soybean leaf length and plant mass (Fig. 4).
DISCUSSION
There was a strong effect of interspecific competition by the rye-grass on the combined leaf
length of the target soybean plants in this experiment. This effect was clearly density dependent and
increased according to rye-grass seed density (Fig. 2). The data was approximated by linear fits
reasonably well (and gave significant P values), although the R2 values were nonetheless rather small
(Fig. 2). This simply indicated that the linear fits and any conclusions formed from, although maybe
significant, did not overwhelmingly represent the entire sample of study. Visual analysis of the
slopes of the two lines reveals that they are almost equal (Fig. 2). This suggests that, in fact, the null
hypothesis that there was no overarching effect of soil quality on the effect of interspecific
competition on soybean combined leaf length, was true. The two slopes are represented visually
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with SE bars in Fig 3, and the major overlap confirms the fact that the slopes are not significantly
different, and that there was no effect of soil composition on the competitiveness of rye-grass
against soybean plants. This was further corroborated by the results of the ANCOVA test, which
showed revealed a P-value of 0.823, much higher than the .05 or less needed to show that the two
slopes are significantly different. This result is surprising, as it was expected that there would be an
effect of soil composition, especially considering the wide origin and adaptability of the rye-grass but
not the soybean. Visual examination showed that, in general, the plants of the sandy tray did worse
than those in the potting-soil tray, however, the effect of competition by the rye-grass and the
resultant inhibition of soybean combined leaf length growth, seems to have been equivalent in both
trays. This disproves the hypothesis that rye-grass would be a better competitor against soybean in
the sandy soil. One reason that the hypothesis did not hold may be that the difference in soil
quality, while it may seem large, did not affect the nutrient content and draining ability of the
environment as much as might be necessary to elicit significant differences. The data also suggest,
by the fact that the slopes for both trays came out to be essentially the same, that, instead, the effect
on soil quality was so great that the decrease in the ability of rye-grass to compete was fully
compensated by a similar decrease in survivorship of the target plants. However, the conditions as
determined by visual inspection, while they do support this theory, were not severely different
enough to provide conclusive evidence.
Analysis of the data, and in particular, the bivariate fit presented in Fig. 4 showed that height
and combined leaf length were not highly correlated variables, with correlation percentages of 76.7%
and 72.7% for the potting soil tray and the sandy tray, respectively. However, as is shown in Fig. 4,
combined leaf length and plant mass was very highly correlated, with correlation percentages of
91.5% for the potting soil tray and the extremely high 96.5% for the sandy tray. This is expected,
because, whereas it is clear that leaf length and height are not intimately related variables, mass and
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leaf length must be simply because it is not possible to increase leaf length alone without also
increasing the mass of the plant. On the other hand, it is possible to increase leaf length without
affecting the plants height. It is interesting that there is a higher correlation in the sandy, and
presumably, nutrient-deficient soil than in the pure potting soil, however, this may be explained by
the fact that, when nutrients are scarce, plants would be more likely to limit, and control to a greater
degree, growth in both terms of leaf-length and mass. These results may not revolutionize the world
of ecology today, and they not even have a lasting impact on this course… but the methods
innovated here surely will. Combined leaf length, with its high correlation to biomass and accuracy
may soon become a new standard in ecological ventures world wide. In other aspects, the data is
not terribly remarkable, nor does it bespeak any special endowment of knowledge. However, it may
be useful in the innovation of experimental design and the exploration of new methods, variables
and outlooks which may prove fruitful to this or any scientific endeavor.
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LITERATURE CITED
Hannaway, D., S. Fransen, J. Cropper, M. Teel, M. Chaney, T. Griggs, R. Halse, J. Hart, P.
Cheeke, D. Hansen, R. Klinger, and W. Lane. Annual Ryegrass. PNW 501: April 1999.
http://wwwagcomm.ads.orst.edu/AgComWebFile/EdMat/PNW501.pdf
Microsoft Corporation. 2003. Microsoft Excel v11.6355.6360. Microsoft Office Professional
Edition 2003. USA.
Ricklefs, R. E. 2001. The economy of nature, Fifth edition. W. H. Freeman, New York, New York,
USA.
Sall, J., Lehman, A., and Creighton, L. 2001. JMP v5.1.0.2. Duxbury Press, Belmont, California,
USA.
Shemanski, K., 2004. Untitled. Unpublished laboratory project report, Biology 3255, Villanova
University, Fall 2004.
Weather Underground, 2004. History for Philadelphia Wings Airport, Pennsylvania.
http://wunderground.com/history/airport/KLOM/2004/9/21/CustomHistory.html?daye
nd=16&month=11&yearend=2004-12-02