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Species diversity is changing globally and locally. For the longest time, biodiversity has played an unreplaceable role in maintaining the stability of the planet. Biodiversity helps to regulate the ecology as it reinforces the ecosystem productivity whereas each species, no matter how small it is, account for an important part of the whole. For instance, each species possesses their signature metabolism mechanism whose rate can affect the environment and on the contrary, can interchangeably depend on various outside factors. On another hand, metabolism rate could be changed by the characteristic of the species itself such as the type of animals, its genetic background, biological characteristics, etc. In other word, species metabolism is dependent on external and internal factors.

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A great example to further our knowledge of how these factors can greatly cause the differences in species organism metabolism, we conduct the experiment to investigate the influences of internal factors contribute in the change of metabolic rate of a species. An objective of this investigation is to discuss if the designated factors affect the metabolism rate and what is the correlation between two variables. The organism which is selected today is Manduca sexta, the common name is the caterpillar. Manduca sexta is a moth of the family Sphingidae present through much of the American continent. It had eight V-shaped white markings with no borders; hornworms have seven white diagonal lines with a black border. Additionally, hornworms have red horns (Harrison et al., 2013). The metabolism of caterpillar can be determined by the sum of energy releasing and energy consuming reactions. The primary measurement techniques we used is the quantification of gas consumption via the volume of oxygen consumed per unit time (ml O2 min-1).

In most species, fitness and size usually positive correlated (Schneider et al., 2016). Growing arthropods gain substantial mass both within and across intermolt periods (instars), so the respiratory system of developing insects must cope with tremendous increases in O2 consumption and CO2 production, as well as increases in tracheal lengths that may challenge diffusive capacity (Greenlee et al., 2005). Caterpillar with selected larger body size will have a larger surface area come into contact with the environment. This allows gas like oxygen or carbon dioxide diffusing more efficiently throughout the body. The volume of oxygen diffusing per unit of area increase could lead to an increase in a whole oxygen exchange causing the rise in metabolism rate. On the other hand, the larger caterpillar with larger mass requires more energy in order to provide for other living activities. This could also cause the rise in oxygen intake rate and the increase in metabolic rate. Based on our observation, our hypothesis is that there is a positive correlation between the size of the caterpillar with its metabolic rate. In clarification, the larger the caterpillar is, the higher the oxygen rate it will consume. If the hypothesis was true, the larger caterpillar will consume more oxygen then we should observe larger changes in the volume of O2 it consumes.


We obtained a set of 20 caterpillars for our experiments. At first approach, we weighted and recorded the weight of each caterpillar and marked them with numbers. We put each caterpillar in each designated test tubes and placed a piece of enough cotton balls inside the test tubes. This cotton ball served as a barrier between the caterpillar and soda lime as soda lime can be cautious and cause harm to our organism. Upon wrapping a soda lime with paper towel, we placed them on top the cotton ball inside the test tube. As caterpillar respire, they produced carbon dioxide gas and consumed oxygen. Soda lime absorb the carbon dioxide impurity in the test tube so it wouldn’t affect our oxygen measurement. Applying glycerol on the stopper before inserting the test tube, we secured the test tubes with stoppers. We processed by adding one drop of water on the tip of the pipette which was inserted in the stopper and recorded the initial volume.

Our experiment is ready to process, set the time for 2 minutes and observed the movement of the droplet of water in the pipette over time. After two minutes, we recorded the volume of O2 consumed on how much the water dropped down by calculating the difference between the initial and final volume. We can then calculate the metabolic rate by dividing the volume of oxygen per minute.


Regression Statistics
Multiple R 0.4809300302
R Square 0.2312936939
Adjusted R Square 0.1885877881
Standard Error 0.06852723377
Observations 20
df SS MS F Significance F
Regression 1 0.02543327315 0.02543327315 5.415965055 0.03182200406
Residual 18 0.08452767183 0.004695981768
Total 19 0.109960945
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 0.1095794172 0.03301811992 3.318766105 0.003819702072 0.04021092137 0.1789479131 0.04021092137 0.1789479131
Weight of Caterpillar (g) -0.01548860694 0.00665540413 -2.327222605 0.03182200406 -0.02947109216 -0.001506121716 -0.02947109216 -0.001506121716

Figure 1. The graph shows the metabolic rate measured by the volume of oxygen intake per minute (mL/min) relative to the weights of caterpillars – Malusca sexta. The data was graphed from the collection of 20 random in size of caterpillar being put in the test tube to measure the oxygen consuming for 2 minutes.


In today’s lab session, we measured the caterpillar’s metabolic rate comparing to its weight. Our hypothesis is that there is a positive correlation between the size of the caterpillar with its metabolic rate, the higher weight will have higher metabolic rate. Based on the graph that was obtained, the graph shows the trend line with positive slope with scattered dot data spanning around a linear line, we can observe the correlation between the weight of caterpillar and the metabolic rate which is measured through the volume of oxygen consuming per unit of time is that the larger the caterpillar is, the higher the metabolic rate that it has. There is a positive correlation between two variables. Moreover, based on our analysis table, our collective p- value is 0.03182 which is lower than the threshold 0.05 so we can conclude that the data support our hypothesis.

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Our experiment’s error in analysis can be derived from various factors. For instance, the precision and uncertainties in laboratory equipment, the quality of soda lime we used in absorbing carbon dioxide, the error in technique skill of whom who perform the experiment. Also, the quality of the caterpillar also is accounted for those errors in analysis.

The significance of our study is that we prove the relationship between internal factor, in this case the mass of the caterpillar, with its metabolic rate. We can use our experimental findings to apply in the real-life situation. In order to improve the quality and quantity of caterpillar, which can be helpful in the pollination of flower and agriculture industry products, we could provide the sufficient oxygen source aiding for the growth rate of caterpillar.



  • Harrison, JF., Cease, AJ., Vandenbrooks JM.,  Albert T., Davidowitz G. (2013) Caterpillars selected for large body size and short development time are more susceptible to oxygen-related stress. Ecol Evol;3(5):1305-16.
  • Schneider, F., Brose, U., Rall, B., Guill, C. (2016) Animal diversity and ecosystem functioning in dynamic food webs. Volume 7. 12718

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