Plant Competition Experiment

General Ecology

Dr. Gresens

Jordan Sedlock

December 5, 2014

Partners: Shelby Montgomery & Kayla Haile

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Introduction:

One of the key processes in plant communities and populations is competition (Berger

2008). Competition is the process that arises, when organisms, whether from the same species

(intra) or of different species from each other (inter) share common, essential resources and as a

result, experience pressure when it comes to growth, survival, and reproduction. Resources are

defined as something necessary for survival, in the case of plants that is generally things such as

water, light, nutrients, and space. In this manipulative experiment, nutrients, specifically

potassium, and space were manipulated, based on a full factorial design, in order to determine if

there were interactions occurring to suggest intraspecific exploitation competition or intraspecific

resource competition. It is hypothesized that low density and therefore maximum amount of

space will yield little evidence of intraspecific competition and conversely, that high density and

therefore minimal amount of space will yield substantial evidence of intraspecific competition. It

is also hypothesized that little to no added nutrients will hinder growth but fail to indicate

intraspecific competition in lower density experimental units and conversely, higher amounts of

added nutrients will more strongly influence growth but also more strongly indicate intraspecific

competition in high density experimental units.

Methods:

To perform this experiment, dwarf marigolds were selected to be the plant of choice for

manipulation. A full factorial design was used when planning this experiment. The following

table (Table 1) provides a general schematic of the physical set-up of this experiment.

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Table 1. General, physical set-up of full factorial experiment including factors, factor levels, species, and replicates

FA

CT

OR

B:

Nu

trien

ts (K)

• = 1 pot

FACTOR A: Density

3 Marigold Seeds 5 Marigold Seeds 10 Marigold seeds

No Added Potassium

•• ••

•• ••

•• ••

Low Potassium Added (1 mL)

•• ••

•• ••

•• ••

High Potassium Added (4 mL)

•• ••

•• ••

•• ••

There were three factor levels: low, medium, and high as well as two different factors that were

being manipulated, which included seed density per experimental unit as well as amount of a

particular nutrient per experimental unit. This experiment’s nutrient was potassium, chosen

because potassium is known to increase crop yield as well as aid in many physical processes

essential for plant life in its presence and in its absence is known to stunt plant growth (SMART

2013). Experimental units consisted of one flowerpot filled with potting soil. There were a total

of 36 replicate, experimental units. Each experimental unit contained a different density of seeds,

ranging from 3 – 10 seeds with 5 seeds being the intermediate between the highest density (10

seeds) and the lowest density (3 seeds). Twelve experimental units contained 3 seeds, a second

set of twelve experimental units contained 5 seeds, and the final set of twelve experimental units

contained 10 seeds.

Pots were assigned random numbers using a random number table, and then labeled.

Once labeled, pots were arranged in ascending order based on random number assignment to

ensure randomization of experimental units and reduce any bias or confounding that may have

occurred due to grouping all of the same replicates per each manipulated set of factors together.

Pots were watered three times per week and the amount of water ranged from 10 – 50 mL

depending upon soil conditions as well as physical plant conditions and taking into consideration

the temperature in the greenhouse where plants remained for the entire experiment.

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Once the experiment began, different levels of nutrients were then manipulated to

determine if there were interactions between the density of dwarf marigolds and the amount of

nutrients they received. To maintain stoichiometry and prevent other nutrients from becoming

limiting, other than potassium, other essential nutrients were added to all experimental units. A

solution of disodium phosphate (0.0136 g/L) was created and 2 mL of this was added to each

experimental unit, once per week. A solution of sodium nitrate (0.085 g/L) was created and 2 mL

of this was also added to each experimental unit, once per week. A final solution of potassium

chloride was created (0.0748 g/L) and used as the second factor to be manipulated in this

experiment. Twelve replicates of varying densities received 0 mL of KCl solution, once per

week, which was representative of the control group. Twelve replicates of varying densities

received 1 mL of KCl solution, once per week, which was representative of the medium factor

level and the final twelve replicates received 4 mL of KCl solution, once per week, which was

representative of the high factor level. Total duration of the experiment was eight weeks. Week

one of the experiment was designated to allow initial germination and growth of plants.

Beginning week two, addition and therefore, manipulation, of nutrients including Na2HPO4,

NaNO3, and the KCl solutions, in manner and amounts previously mentioned, began and

continued to the end of the experiment.

Following the eight-week experiment, plants were harvested. All above ground biomass

was cut at the dirt level, placed in an envelope and weighed on a top- loading balance. Total

number of surviving plants was summed as well as flowers produced by each plant and buds

produced by each plant. Response variables that were examined include per capita biomass of

each pot, and the proportion of flowers per total number of final plants.

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Results:

Following the harvesting of all experimental units, data analysis was then performed on

the per capita biomass of marigolds. Analysis of variance using the ANOVA technique was

conducted to determine whether or not the two factors that were manipulated had significant

effects on the per capita biomass of marigolds. Table 2 contains the output from the ANOVA

analysis for this response variable.

Table 2. ANOVA of Per capita biomass of marigolds

Source of Variation SS df MS F P-value

Density 22.82866314 2 11.41433157 18.72819942 7.9126E-06

KCl added (mL) 0.238713718 2 0.119356859 0.195836177 0.82330436

Interaction 5.049209952 4 1.262302488 2.071137725 0.112492507

Within 16.45577055 27 0.609472983

Total 44.57235736 35

Due to a large value of F for the density factor (Table 2) p < 0.05 (p = 7.913E-6) (Table 2), and

therefore indicates that density had a highly significant effect on the per capita biomass of

marigolds. Due to a small value of F for the nutrient level factor, (Table 2) p > 0.05 (p = 0.8233)

(Table 2), and therefore indicates that nutrient level did not have a significant effect on the per

capita biomass of marigolds. Following the statistical analysis, graphical analysis (Figure 1) was

performed in order to depict the data from Table 2.

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Figure 1. Interaction plot of per capita biomass of marigolds

Figure 1 depicts interactions of factors as a function of the response variable. Figure 1

indicates that density had the strongest effect on per capita biomass in experimental units with 3

seeds. The amount of nutrients added to experimental units with 3 seeds produced a negative

effect on the per capita biomass. Experimental units with 5 seeds yielded lower per capita

biomass than experimental units with 3 seeds and experimental units with 10 seeds yielded the

lowest per capita biomass. Overall, amount of nutrients added, more strongly influenced

experimental units with 5 seeds in them and produced per capita biomass that is nearly

comparable to that produced in experimental units with 3 seeds. Amount of nutrients added

produced an overall positive effect on experimental units with 5 seeds in them. Amount of

nutrients added produced little positive affect on experimental units with 10 seeds in them. Error

bars in Figure 1 indicate high variation amongst replicates and could therefore contribute to the

higher p value (Table 2) for amount of nutrients added to plants.

Analysis of variance using the ANOVA technique was then conducted to determine

whether or not the two factors that were manipulated had significant effects on the proportion o f

0

1

2

3

4

5

6

None (0 mL) Low (1 mL) High (4 mL)

Per

cap

ita

Bio

mas

s (g

)

Potassium addition level

Mean (+ S. E.) of per capita biomass of marigolds

3 seeds

5 seeds

10 seeds

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flowers per marigold plant. Table 3 contains the output from the ANOVA analysis for this

response variable.

Table 3. ANOVA of proportion of flowers per plant

Source of Variation SS df MS F P-value

Density 0.480873331 2 0.240436666 2.241704469 0.125691869

KCl added (mL) 0.190476505 2 0.095238253 0.887951162 0.42317498

Interaction 0.435833963 4 0.108958491 1.015871415 0.416754327

Within 2.895916951 27 0.107256183

Total 4.00310075 35

Due to a small value of F for the density factor (Table 3) p > 0.05 (p = 0.125) (Table 3), and

therefore indicates that density had no significant effect on the proportion of flowers per plant.

Due to a small value of F for the nutrient level factor, (Table 3) p > 0.05 (p = 0.423) (Table 3),

and therefore indicates that nutrient level had no significant effect on the proportion of flowers

per plant. Following the statistical analysis, graphical analysis (Figure 2) was performed in order

to depict the data from Table 3.

Figure 2. Interaction plot of proportion of flowers per final number of plants

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

None (0 mL) Low (1 mL) High (4 mL)Pro

po

rtio

n F

low

ers:

Fin

al P

lan

ts

Potassium addition level

Mean (+ S. E.) of flowers to plants

3 seeds

5 seeds

10 seeds

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Figure 2 depicts interactions of factors as a function of the response variable. When

considering experimental units with 3 seeds, it appears, overall, that these units yielded the most

flowers per plant. When considering experimental units with 5 seeds, it appears, overall, that

these units yielded the least flowers per plant. When considering experimental units with 10

seeds, it appears, overall, that these units yielded the second most flowers per plant compared to

units with 3 seeds. Considering amount of nutrients added to the experimental units, units with 3

seeds appear to have been negatively affected overall, units with 5 seeds appear to have been

positively affected overall, and units with 10 seeds appear to have been negatively affected

overall. Error bars in Figure 2 indicate very high variation within replicate groups. Due to

substantial overlap of error bars in the density levels, it is not possible to discern with certainty

that there was any interaction of factors on the response variable measured in this analysis.

Discussion:

Before beginning this experiment, it was hypothesized that low density and therefore

maximum amount of space would yield little evidence of intraspecific competition and

conversely, that high density and therefore minimal amount of space would yield substantial

evidence of intraspecific competition. This assumption was based off of a previous experiment

that found that as density of a plant population increases, above ground biomass decreases

(Wang 2005). It was also hypothesized that little to no added nutrients would hinder growth but

fail to indicate intraspecific competition in lower density experimental units and conversely,

higher amounts of added nutrients would more strongly influence growth but also more strongly

indicate intraspecific competition in high density experimental units. After completion of the

experiment, it has been concluded that units with the lowest density yielded the highest per

capita biomass (Figure 1) and the highest proportion of flowers to plants (Figure 2) and is

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therefore indicative of little intraspecific competition. It has also been concluded that units with

the highest density yielded the lowest per capita biomass (Figure 1) and is therefore indicative of

prevalent intraspecific competition. It cannot be stated with certainty that density strongly

affected the proportion of flowers to plants (Figure 2) with units of highest density because the

intermediate factor level (5 seeds) yielded a lower proportion of flowers to plants than the

highest density factor level (10 seeds), however, the data still suggest, overall, that with

increased density, intraspecific competition also increased. These results support the first part of

the aforementioned hypothesis. Upon further investigation of experimental results and examining

effects of added nutrients, it has been concluded that the second part of the aforementioned

hypothesis is not supported because there is high variation within replicates and very little

evidence of apparent trends in the data to state with certainty that amount of nutrients added had

any effect on intraspecific competition. When considering Figure 1, added nutrients decreased

per capita biomass in units with 3 seeds and 10 seeds, however, units with 5 seeds experienced,

overall, more growth as a result of an increase in nutrients and therefore experienced lower

intraspecific competition than units with 3 seeds and 10 seeds. When considering Figure 2,

increased amounts of nutrients greatly lowered the proportion of flowers to plants in units with 3

seeds and 10 seeds, however, units with 5 seeds experienced, overall, more production of flowers

per plant and therefore experienced lower intraspecific competition than units with 3 and 10

seeds.

To design an experiment that better aims at supporting the second part of the previously

stated hypothesis, many things could be done. To decrease amount of variance within replicate

groups, more replicates could be added, possibly increasing sample size from 36 to 56, for

example. Experimental units with 5 seeds appeared to be the outliers in the data sets and

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experienced more overall effects of manipulation of factors. When studying proportion of

flowers to plants, decreasing the amount of seeds from 3 to 2 in the low density units as well as

increasing the amount of seeds from 10 to 12, perhaps, and leaving 5 seeds in the intermediate-

level density units could allow for results that support the thought that highest density would

yield lowest proportion of flowers to plants, intermediate density would yield the second lowest

proportion of flowers to plants and lowest density would yield the highest proportion of flowers

to plants. Along with increasing replicates to decrease variation, adding more factor levels for

amount of nutrients added might yield better results with apparent trends that more strongly

indicate what type of effect amount of nutrients has on marigolds as well as suggest an

interaction between density and nutrient levels.

It is possible that there was so much variation among replicates due to variation in

amounts of water each plant received. Rather than watering plants every other day with different

amounts of water based on soil conditions and temperature of the environment, plants could be

kept in an environment with a more stable temperature and more access to sunlight as well as

being watered everyday with lesser amounts of water that would remain consistent within all

replicates throughout the duration of the experiment. Variation could also have been introduced

when administering nutrients once per week. Cross contamination of pipettes used for

administering nutrients could have occurred if another group borrowed pipettes for their

solutions. Lack of precision and accuracy when delivering nutrients to plants could be another

cause of variation within replicates. To correct for these causes of variation, more care can be

taken when delivering nutrients to plants to ensure better accuracy and precision. Also, pipettes

can be labeled and/or placed away so as not to allow use by other groups.

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Literature Cited

Berger, U. et. al. 2008. Competition among plants: concepts, individual-based modeling

approaches, and a proposal for a future research strategy. Perspectives in Plant Ecology, Evolution, and Systematics 9: 121-135.

SMART. December 3, 2014. http://www.smart- fertilizer.com/articles/potassium-in-plants.

Wang, L. et. al. 2005. Effects of intraspecific competition on growth and photosynthesis of Atriplex prostrate. Aquatic Botany 83: 187-192.