Exploring the Exploitative Competition between Collards and Radishes at the Interspecific and Intraspecific Level

By: Shandrea Foster

Abstract

This study observed several types of competition including intraspecific, interspecific,

and exploitative competition. All of these types of competition are important because they are

the driving force behind variety in populations. The interactions that happen during competiton

are vital to the survival of different species on earth. This study mainly observed how density

and species affect the levels of competition that occur on two species of plants, which are

collard, Brassica oleraceae, and radishes, Raphinus sativa. The two hypotheses were: 1) Low

density plants would be more successful than the high density and 2) Radishes would be a

superior competitor over collards. Thusly, seeds of collards and radishes were planted in a

greenhouse and left to germinate for five weeks. After five weeks, the plants were observed,

measured, and cut into individual parts so that analyses could be performed to see if any

significance between the pots had occurred.

Using Anova single factor tests, two factor anova tests, and graphs, it was determined

that there was significance to the data and led to both hypotheses being accepted. The p-values

for the low density plants were below 0.05 except for in the collard data. The p-values were also

significant for the radishes and not the collards as well. These results are very important to the

ecological community because it examines the mechanism behind competition and the survival

traits that are used to make species a superior competitor. Furthermore, this experiment has

implications for the future and for similar experiments like it.

Introduction

One important aspect of life is the interactions that a species has with each other. While

some interactions do not affect the species, some interactions will. One important interaction that

is commonplace between species is called competition (Ricklefs 2010). Competition usually

arises when two or more species compete against each other, lowering the fitness of the species

involved, usually to obtain a limiting resource (Ricklefs 2010). Limiting resources can be

characterized as a nonrenewable or renewable substance that is either consumed by an organism,

or needed for survival (Ricklefs 2010). Some examples of limiting resources are sunlight, space,

water, and nutrients (Jekinson 2010). The two types of competition that were examined in this

study were interspecific and intraspecific competition. Intraspecific competition involves

competition between species that are the same, while interspecific competition is between two

different species (Ricklefs 2010).

From a biological perspective, competition is vital in nature because it provides increased

variety between populations and influences community interactions (Ricklefs 2010). The specific

mechanism or drive for this study is exploitative competition which means that a common

limiting resource indirectly affects the survival or fitness of the involved species. Another

definition includes: when an individual uses resources that limit a resource for the other

individual (Jekinson 2010). In any case it usually causes an increased ability to obtain resources

faster and more efficiently via growing faster or uptake of nutrient through its roots (Waller

1928). To explore the different types of competition and the mechanism involved, two species

of plants were observed which were radishes and collards. Radishes, Raphinus sativa, are

classified as a vegetable that has a purple-reddish tone to its roots and has green leaves with long

stems, which grow above ground (Wolford et al. 2013). Radishes are usually grown in the cool

months but several types can grow in different seasons as well. It is a fast maturing plant that is

easy to grow because it can sprout in almost any type of soil (Wolford et al. 2013). The best

conditions for radishes to grow in are where there is most soil that is well prepared (Wolford et

al. 2013).

One reason radishes are fast maturing is because of their taproot system. A taproot means

that one main root that usually grows vertically with the plant gathers the nutrients for the plant.

It makes radishes very efficient in getting nutrients because its taproot can gather more nutrients

than other plants with other types of root systems (Waller 1928). When radishes are planted they

are spaced about two to four inches apart from each other to allow optimal growth (Wolford et

al. 2013). Collards, Brassica oleraceae, on the other hand, are a very leafy green plant that is

known as “non-heading cabbage” because it does not form into a ball like cabbage does. Instead

it sprouts outward and has short stems that rise from the soil it is planted in. They are slow

maturing plants that are harvested about fifty to seventy months after being planted. When

allowed to mature, collards can grow to great amounts which are why they are planted about

eighteen inches apart from each other (Wolford et al. 2013). Collards have a fibrous root system

which means it has many roots that gather nutrients making it easy for the plant to reach deep

into the soil to get more nutrients (Waller 1928). In this experiment, we planted these two species

of plants to observe their competitiveness, which both plants have in their own right.

The experiment tested the competitiveness of the plants at two different levels: the first

comparing the success of growing in high and low densities, and the second comparing the

success of growth in same species pots and two different species pots. The importance of this

experiment was to observe the interspecific and intraspecific competition of the plants in order to

see the mechanism of exploitative competition (Jenkinson 2010). This type of study is important

because it identifies key elements of each plant that lead to its success or survival when faced

with competition. All of these aspects lead to the two hypotheses which are: 1) Low density

plants will be more successful than high density plants because there is more exploitation in low

density since there are more nutrients available (Aguiar et al. 2001) (MacIsaac et al. 1991). The

rationale behind this is since sunlight is a limiting resource, the leaves of the low density plants

will grow longer and bigger because they have more room to grow and to acquire sunlight with

the survival trait being rapid growth making them have more total biomass (Wolford et al. 2013).

2) Radishes will be more successful than collards because of an increase in exploitative

competition (Jenkinson 2010) (Wolford et al. 2013). The rationale being that water is a limiting

resource and the taproot system is able to gather the most water than the fibrous root system of

the collards, with survival trait being efficient absorption of nutrients because of rapid growth,

which was tested by total biomass (Waller 1928). The first hypothesis was measured using

normalized leaf data to acquire differences between low and high density leaves and the success

checked using the total biomass of the plants collected which were measured per plant. The

second hypothesis was measured using normalized stem data to observe the growth of the stems

and the success of the absorption of the roots using the total biomass of the plants, which were

measured per plant.

Methods and Materials

This experiment was conducted in the Greenhouse on the University of South Carolina

campus. The entire study was conducted in three separate steps, with the first being the set up at

the greenhouse. The greenhouse was very hot and humid and had green and clear windows on

the roof and walls which let in plenty of sunlight. The rest of the greenhouse was built with

cinderblocks which help to keep a constant insulation for the plants inside of it. There were

wooden tables for the plants to sit on and above them were big light bulbs that are used for

heating. Also, along each row of tables there were sprinklers which provide water for the plants

to grow.

The experiment commenced by spreading the seeds of the plant into their respective

seeds with the larger yellow seeds being collards and the small red seeds being radishes. The

counting out the seeds of each plant based on what density and species the pot needed. Then soil

was taken and put into the pot, filling it to about one inch from the top (Jenkinson 2010). The

seeds were then separated into eight seeds for low density and sixty- four seeds for high density

pots. In all pots, the seeds were evenly spaced between each other to allow equal growing

opportunity. In the intraspecific pots, seeds were alternated between radish and collard seeds in

both densities of pots (Jenkinson 2010). In total there were three levels of species at two separate

densities that included: collards only, radishes only, and collards and radishes, making a total of

six different treatments for the pots to receive. A total of twenty-four pots, four replicates of each

of the six treatment designs, were labeled appropriately with treatment, group name, and section

number .Once the seeds were planted, the pots were filled with one centimeter of soil over the

top of them and left to germinate for five weeks and watered every eight hours (Jenkinson 2010).

The second step was conducted again in the greenhouse and it involved collecting the

data from the experiment. Plants were removed from the pots with extreme care by squeezing the

pots to break up the soil and then holding the plants downward until they fell out of the pot. Then

the plants were removed trying not to break the roots away from the plants. With fingers, the soil

was pushed away from the plant roots and then washed off in a bucket of water. Once all of the

plants were freed from the pots they were taken and counted and if the pot was mixed they were

also separated into their different species (Jenkinson 2010).

Once separated, the cotyledons of the plants ,which are the sprouting leaves, were cut

away from the plant and discarded. Then the below ground biomass, roots of the plant, was cut

off and put in a weigh boat and measured. The leaves of the plants were cut off and counted and

were put into weigh boats and measured. Then the stems on each plant were measured five

separate times, divided by five to get an average of the stem length, and weighed. All of the

measurements were taken and recorded on the data sheet provided. Once everything was

weighed and measured, the plants were discarded in the compost pots, dirt was put into a bucket,

and water was thrown out (Jenkinson 2010). The final step of the experiment was conducted in

the laboratory where all of the data from each group was compiled and data analyses were run on

the data. The testing required single factor ANOVA tests on each species to compare the success

rate at each density, which tells whether there is a significant difference between the groups

(Microsoft 2012). Then a two factor ANOVA test was ran on the mixed pot data to see if there

was any significant difference between the densities and the interactions between species

(Microsoft 2012). Then the data analyses were repeated using the survival traits of the plant

species. The data was normalized using equations which included average number of leaves (# of

leaves / # of plants), average stem lengths (5 stem averages / 5), and average biomass (total stem

weight + total leaf weight + total root weight / # of plants) (Jenkinson 2010).

Results

The first anova showed that the p-value was 0.019115 when comparing the high and low

density radish plants to each other (Table 1). Table two compares the intraspecific densities of

collards to each other and calculated the p-value to be 0.190661. The graph shows that the

general trend between the intraspecific densities of radishes and collards to be that, at low

density radishes had a higher number of leaves than collards and at high density, both species

had about the same number of leaves between them ( Figure 1). Anova test were also done on the

success of the low and high density plants when comparing the survival trait of rapid growth.

Table three had success data of the intraspecific total biomass of the radishes with a p-value of

5.66E-06and table 4 showed the total biomass of the collards with a p-value of 0.145581. The

general trend of the graph showed that high density plants had higher total biomass than the low

density pots (figure 2).

Table 1: Single Data Anova Results for Intraspecific Radishes at High and Low Densities – Table 1 shows the variation between the high and low density groups of the radish plants. The plants were tested to see the significance between high and low density plants when examining the number of leaves they grew.

ANOVASource of Variation SS df MS F P-value F crit

Between Groups 5.295599 1 5.295599 6.134814 0.019115 4.170877Within Groups 25.89613 30 0.863204

Total 31.19173 31Table 2: Single Data Anova Results for Intraspecific Collards at High and Low Densities- Table 2 shows the variation between high and low density groups of the collards. The plants were tested to see the significance between the high and low density plants when examining the number of leaves them grew.

ANOVASource of Variation SS df MS F P-value F crit

Between Groups 4.882812 1 4.882812 1.792657 0.190661 4.170877Within Groups 81.71354 30 2.723785

Total 86.59635 31

Figure 1: Average Number of Leaves of Radishes and Collards at Low and High Density – Figure 1 shows the average densities of both species of plants at an intraspecific level. The low density plants had a higher difference between them than the high density plants did.

Table 3: Single Data Anova Results for Success of Survival Trait in Radishes- Table 3 shows the significance of the survival trait which was rapid growth by analyzing the total biomass of the radishes at low and high densities. ANOVA

Source of Variation SS df MS F P-value F critBetween Groups 1107.702 1 1107.702 30.26333 5.66E-06 4.170877Within Groups 1098.063 30 36.6021

Total 2205.765 31

Table 4: Single Data Anova Results for Success of Survival Trait in Collards- Table 4 examines the significance of the survival trait of rapid growth on the total biomass of the collards at low and high densities.

ANOVA

Source of Variation SS df MS F P-value F crit

Between Groups 0.731647 1 0.731647 2.232482 0.145581 4.170877

Within Groups 9.831836 30 0.327728

Total 10.56348 31

Low High0

0.51

1.52

2.53

3.54

Average Number of Leaves of Radishes and Collards at Low and High Density

Radish Collard

Density

Num

ber o

f Lea

ves/

Plan

t

Figure 2: Average Success of Radishes and Collard Using Total Biomass- Figure 2 shows the average biomass of the intraspecific pots at high and low densities. The low density plants had the greater difference between the two species than at the high density level.

The interspecific data was performed with two-factor anova tests and they compared the

radishes and collards that were in the same pots with each other. The first anova tested the stems

lengths of the collards and radishes against each other and the p-value was determined to be

1.23E-13 between the species (Table 5). The general trend of the graph showed that radishes at

both high and low densities had much higher stem lengths than the collards did (Figure 3). The

next anova was performed on the success of how well radishes and collards could absorb

nutrients, therefore the total biomass was examined and the p-value was determined to be 5.28E-

16 between the species (Table 6). The general trend of the graph examining this was radishes

showed a tremendous difference in total biomass between the radishes and collards, with

radishes having more biomass (Figure 4).

Table 5: Anova Two- Factor Test to Determine Significance of Interspecific Collards and Radishes- Table 5 shows the significance of the stem lengths of the plants to see if there was any difference between the species to see if one species was superior over the other.

Anova: Two-Factor With Replication

low high0

5

10

15

20

25

30

Average Succes of Radishes and Col-lards Using Total Biomass

Radish

Collard

Density

Aver

age

Biom

ass/

Plan

t

ANOVASource of Variation SS df MS F P-value F crit

Species 396.1344 1 396.1344 91.01092 1.23E-13 4.001191Columns 9.77E-06 1 9.77E-06 2.24E-06 0.99881 4.001191

Interaction 2.732822 1 2.732822 0.627859 0.431263 4.001191

Within 261.1562 60 4.352603

Total 660.0234 63

Figure 3: Average Stem Length Growth

of Radishes and Collards - Figure 3 shows that stem lengths of

the radishes were a lot longer than

the collards which shows they most likely were able to absorb the most sunlight, blocking it from the collards that grew poorly.

Table 6: Anova Two-Factor Test that determines the Significance of the Success of the Interspecific Collards and Radishes- Table 6 examines the significance of the success of the survival trait which was nutrient absorption by measuring the total biomass of the plants.

Radish Mix Collard Mix01234567

Average Stem Length Growth of Radishes and Collards

Low High

Species

Stem

Leng

ths

Anova: Two-Factor With ReplicationANOVA

Source of Variation SS df MS F P-value F crit

Species 2691.383 1 2691.383 120.8214 5.28E-16 4.001191Columns 291.1928 1 291.1928 13.07221 0.000615 4.001191Interaction 251.3717 1 251.3717 11.28456 0.001363 4.001191Within 1336.543 60 22.27572

Total 4570.49 63

Figure 4: Average Success of Radish and Collard Mixes Using Total Biomass - Figure 4 shows the success of the absorption of the nutrients by weighing the total biomass of the radish and collards at the interspecific level. The radishes had a significantly higher biomass overall than the collards.

DiscussionThe interactions that take place in the natural world are necessary from a biological

standpoint. When interactions between species lower the fitness or causes an effect on a species

is known as completion. Competition is a necessary part of the natural world because it promotes

variation within communities (Ricklefs 2010). When competition arises between species, it

Radish Mix Collard Mix02468

101214161820

Average Success of Radish and Collards Mixes Using Total Biomass

Low High

Species

Aver

age

Biom

ass/

Plan

t

usually because a limiting resource which is a nonrenewable source that is vital to the survival of

a species. Some examples of a limiting resource include sunlight, water, and nutrients (Ricklefs

2010). Specifically this experiment examined interspecific competition, which is a species

competing against itself, and interspecific competition, which is when a species competes against

a different species. Both types of competition occur frequently in nature and have a necessary

part in the interactions between organisms (Jenkinson 2010).

The mechanism behind interspecific and intraspecific competition in called exploitation

competition, which is when a common limiting resource indirectly effects the survival of another

species (Ricklefs 2010). The two plants that were observed to show this mechanism were radish

and collards. Radishes and collards both grow in cool weathered months and have their own

survival traits. Radishes are fast growing and have a taproot which allows for efficient absorption

of nutrients. Collards are slower growing but have fibrous roots that allow it to go deep into the

soil to gather nutrients that some other plants cannot get to (Wolford et al. 2013). Based on the

traits, limiting resources, and densities, two hypotheses were formed. The first being that low

density plants will be more successful in growing because then have more nutrients to absorb

and will have more exploitative competition driving the plants to grow faster (Aguiar et al. 2001)

(MacIsaac et al. 1991). The second hypothesis was that radishes will be the more superior plant

because of its survival characteristics when faced with a competitor (Jenkinson 2010) (Wolford

et al. 2013).

The expected results of the intraspecific competition experiment was that low density

plants would fair far better than the high density plants because they would have more room to

grown and the high density plants would have less growth overall because of all of the plants

trying to get all of the resource that it could absorb (Jenkinson 2010) (Ricklefs 2010). While low

density plants could have grown slower because of fewer plants to compete with, it was

suspected that they would become even more competitive because there was more nutrient for

them to absorb (MacIsaac et al. 1991). The expected results of the radish and collard mixes were

that radishes would be the superior plant because it is known to mature a lot faster than collards

and to have great absorption ability (Waller 1928) (Wolford et al. 2013). They also initially grow

faster than the collards which made it clear that radishes would get most of the sunlight and

block the collards from getting as much sun on its leaves (Wolford et al. 2013).

The results of the experiment for the first hypothesis showed the p-value between the

radishes at low and high density to be 0.019115, which shows that there was a significant

difference between the numbers of leaves found on the radish species (Table 1). However, for

the high and low density collards the p-value was 0.190661 showed there was no significant

difference between the numbers of leaves found at the different densities (Table 2). Moreover,

the results for the success tested for the low density radishes showed a significant difference in

the total biomass of the plants with a p-value of 5.66E-06 (Table 3). This significance showed

that the survival trait of rapid growth was successful in helping the leaves absorb water from the

soil. There was no significance in the survival trait of the collards since the p-value was

0.145581, which means that neither low nor high density plants had difference in the amount of

biomass collected (Table 4).

The results for the interspecific data concluded that the stem lengths had a significant

difference when juxtaposed between the collard and radishes because the p-value was 1.23E-13

between the species, meaning that the stems of one of the species were significantly longer than

the other species stems (Table 5). There was also significance to the success test because the p-

value was 5.28E-16 which means that the survival trait of nutrient absorption was correct

because there was significance in the biomass of the plants (Table 6). The graphs of the data

made it clear that hypothesis one was accepted. Taking the graphs into account, low density

plants grew longer leaves and retained water better than the high density plants when looking at

the biomass (Figure 1) (Figure 2). From a biological standpoint this makes a lot of sense because

the survival trait of rapid growth made the less dense plants want to gather as many nutrients as it

could because of limiting resources (Wolford et al. 2013). This shows exploitation competition

between the less dense pots, which is a surprising result that it is much stronger in the low

density plants than the high density plants since the high density plants have fewer resources to

go around (Ricklefs 2010). The total biomass also showed the success of the survival trait, since

there was evidence of rapid growth, it would be logical that the biomass would weigh more

because they were more mature (Bonser et al. 1995).

Hypothesis two was also accepted because of the graphs of the data. The graphs showed

that radishes were superior in growing longer, which helped them to be more competitive by

blocking the sun from the collards which are lower to the soil level (Bonser et al 1995) (Figure

3). The stems of the radishes were significantly longer because of exploitation competition since

sunlight is a limiting resource (MacIsaac et al. 1991). The success of this was checked by the

total biomass graph which in short, shows that the taproot of the radishes was able to absorb

more nutrients than the fibrous roots of the collards so the radishes grew longer because they had

more nutrients making them into a superior predator over the collards (Figure 4) ( Waller 1928).

Radishes have a more efficient growing system than collards because they specialize in growing

rapidly and exemplify exploitative competition because the collards definitely had a decrease in

its fitness level and it was very hard for the collards to grow at all during this experiment

(Ricklefs 2010).

The main importance of this study was to examine the effects of competition because it is

a vital part of understanding many biological processes. This study also shows the survival traits

that arise within species to help the plant become a better competitor, as with the radishes

(Wolford et al. 2013). By looking at the mechanisms of how competition works helps to get a

better understanding of why it happens in nature. It teaches the ways in which organisms have

evolved in order to survive such a competitive world (Ricklefs 2010). Moreover, there are future

research ideas that could delve into the issue of competition even further. The first is seeing if

certain parts of an area can possibly predict how competitive the competition will be (Aguiar et

al. 2001). Another could be to test the environment health of the soil to the root systems of the

plants planted in those areas (Waller 1928).Lastly, is to see if biomass and competition increase

by a significant level with other organisms, such as plant with the same rapid growth as radishes

(Bonser et al. 1995).

Acknowledgements

Firstly I want to acknowledge all of my group members whom included: Blair, Gabrielle,

Courtney, and Carly. Blair worked very fast and efficiently to label all of the pots correctly.

Gabrielle worked as team leader and wrote down the data collected. Courtney worked hard at

planting the plants during the first initial step and also acted as team leader and delegated tasks to

everyone when we were gathering data. Carly also worked as team leader and kept everything on

track and helped with the clean up after all data was collected. Everyone worked very well

together and it helped us to finish quickly and correctly. I also want to acknowledge USC for

providing the greenhouse in which the experiment was carried out in and for providing the

resources as well. I also want to acknowledge Leslie Muggelberg for her patience and help in

compiling the data correctly for the Anova and graphs for this experiment.

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