The Cognitive and Decision-making Process of M. Sabuleti Foraging During Food Shortages

4118 words (16 pages) Essay

8th Feb 2020 Biology Reference this

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ABSTRACT OF RESEARCH PLAN:

Myrmica sabuleti is a species of eusocial ant which exhibits a reproductive division of labor and age-dependent task specialization. The mushroom bodies are a part of the insect brain responsible for olfactory integration and experience-based learning. This portion of the brain varies in size depending on the task specialization of the individual ant. 10 colonies of ants will be given different combinations of nutrient-rich and -poor food to force specific decision-making during foraging. The morphology of the brains of the ants in each colony will be compared to see if there is a link between decision-making and the mushroom bodies.

A.  Specific Aims: 

 This study aims to explore the relationship between decision-making and ant brain morphology during times of environmental stress.

Our hypothesis is that decision-making while foraging will affect the mushroom bodies. Mushroom bodies are a section of the insect brain associated with olfactory integration and experience-based learning (Gronenberg, et al, 1996).

This study will utilize 10 colonies of Myrmica sabuleti to test the hypothesis. A portion of the colonies will be given nutrient-poor food or limited quantities of nutrient-rich food without any other choices. Another portion of the colonies (decision-making colonies) will be given the choice between varying quantities of nutrient-rich food and nutrient-poor food. A small sample of ants from each colony will be taken weekly and dissected to measure the size of their mushroom bodies. We will compare the average size of the mushroom bodies and the change in the size of the mushroom bodies over time between each colony. We will also track the number of ants visiting each food source every day to track their foraging behavior.

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Our prediction is that colonies forced to make foraging decisions will have larger mushroom bodies than non-decision-making colonies. By observing these differences, we can begin to make conclusions regarding how environmental stressors affect the neurology of social insects and how brain morphology mediates adaptive behavioral changes.

B.  Significance

Eusocial insects are species of insects characterized by a highly organized social structure of interrelated individuals whose fitness depend on the fitness of the collective nest and reproductive capabilities of the queen (Nowak, et al., 2010). For such a large number of individual organisms to function as a single superorganism requires levels of nuanced communication that makes their neurology inherently interesting (Perry, et al. 2013). Recent studies done on eusocial insects, most notably on honeybees, have shown that their social behaviors, communication methods, and cognitive abilities are far more advanced than previously anticipated (Menzel, 2012). By understanding these complex networks of communication and adaptive behavior, we can better understand how insect foraging functions within an ecosystem.

Myrmica sabuleti is a widely studied species of eusocial ant native to Europe. They exhibit age-dependent task determination (Gronenberg, et al, 1996). Communication between individuals relies primarily on olfactory chemical signaling (Cammaerts, M., et al, 2014). Foraging ants rely mainly on olfactory cues to locate food sources (Detrain, C., et al, 1999).

The decision-making capabilities of ants, and how this directly involves their neurology, have been studied but are still relatively unexplored (Detrain, C., et al, 1999) or have not established causal links (Robinson, et al., 2009). Past studies done on ant neurology have lead us to focus on the mushroom bodies of foraging ants (Gronenberg, et al, 1996). Mushroom bodies, or corpora pedunculata, are the parts of the insect brain responsible for olfactory learning and memory (Perry, et al, 2013). The morphology of mushroom bodies are also highly variable depending on the role an individual plays within the colony. Young, nonforaging ants and queen ants tend to have smaller mushroom bodies than foraging ants (Gronenberg, et al, 1996). Because ant foraging is based heavily in integrating olfactory information, it is essential for foraging ants to be able to distinguish between scents in order to make decisions that maintain the wellbeing of the whole colony.

While some of the traits described inherent to most eusocial insects and ant species, Myrmica sabuleti poses specifically relevant questions because it is a host for parasitic butterflies (Witek, et al., 2014). Maculinea butterflies, such as Phengaris alcon and Phengaris arion leave larvae inside of a M. sabuleti nest to either prey on ant larvae or eat food provided by nurse ants (Witek, et al., 2014). Maculinea butterflies are threatened species and the stability of a specific population can be accurately predicted by analyzing the related population of Mymica ants (Thomas, et al., 2009). However, hosting parasitic butterflies causes a significant strain on a colony’s resources and the wellbeing of its brood (Thomas, et al., 1992; Witek, et al., 2016). While the food shortages simulated in this experiment will not perfectly represent the affect of a parasitic butterfly in a colony, the results may provide insights into how a colony can adapt its behavior when under environmental stress, which will benefit conservation efforts.

 

C.  Experimental Design and Methodology: 

10 colonies of M. sabuleti will be used for this experiment. Each colony will have approximately 200 workers and 1 – 2 queens. They will be kept indoors in separate nest boxes in an appropriate substrate, with a regular 12 hour light/dark cycle and appropriate temperature.

Before any data collection takes place, we will rear single cohort colonies without brood. Previous studies have shown that young, non-foraging ants still experience olfactory-based learning within the nest due to tasks such as brood care and nest maintenance (Gronenberg, et al, 1996). By rearing the ants without brood, their mushroom bodies should stay relatively undeveloped until they specialize in foraging, and therefore should display a more clear trend over time.

Because ants are invertebrates, they are not protected under any animal testing legislation.

Preliminary data collection:

A period of one month will be reserved to collect preliminary data necessary for the controls during the next step in this experiment. The nests will be fed an excess of mealworms (protein source) combined with a sucrose solution. These food sources will be added at the beginning of the day and removed at the end. The weight of each food source will be taken to calculate the amount eaten in one day. The average amount of food eaten every day will be used as a guide to determine the “sufficient” amount of food.

As will be explained below, during the experimental data collection period, a citrus scent will be added to nutrient-poor food in order to mediate olfactory learning in the decision-making colonies. During the preliminary data collection period, we will run T-maze tests on a random sample of ants to make sure that the ants are neither attracted to or adverse to the scent. These ants will not be returned to the source colonies. If we find that the citrus scent biases the decision-making of these ants, we will test back-up aromatic chemicals such as vanilla or carvone oil (this is the last resort because it is the most difficult to obtain).

Each nest box will also be set up with a Broodminder tool. This tool is typically used for monitoring bee hives but can be adjusted for our purposes. It is placed underneath a nest box and provides real-time updates on the nest’s weight and temperature. The weight of a nest box is directly correlated to the number of individuals within the box. This information will be used to monitor the wellbeing of each colony throughout the experiment.

This period of data collection will also be used to fine tune the camera/video setup and procedures necessary for the next step. We will use the video data to determine the 3 hours of the day in which the nests are most actively foraging.

Foraging behavior treatments:

 Once preliminary data has been collected, the nests will be treated with different food sources so we can observe the changes in foraging behavior. Complete food contains the mealworm and sucrose-solution in the proportions observed during preliminary data collection. Protein-poor food contains half the necessary proportion of mealworms. Sucrose-poor food contains half the necessary proportion of sucrose solution. Additionally, both protein- and sucrose-poor food will include a citrus scent (nontoxic) in order to mediate olfactory-based learning.

Sufficient quantity means the food is present in the necessary quantity (by weight) observed in the preliminary data collection. Limited quantity is 2/3 the quantity of food determined necessary.

 

 

Table 1 – Treatments for each nest

Nest

Treatment

1

Nutrient-rich food in sufficient quantities.

2

Nutrient-rich food in limited quantities.

3

Protein-poor food in sufficient quantities.

4

Protein-poor food in limited quantities.

5

Sucrose-poor food in sufficient quantities.

6

Sucrose-poor food in limited quantities.

7

Choice between nutrient-rich food and protein-poor food in sufficient quantities.

8

Choice between nutrient-rich food and protein-poor food in limited quantities.

9

Choice between nutrient-rich food and sucrose-poor food in sufficient quantities.

10

Choice between nutrient-rich food and sucrose-poor food in limited quantities.

Nest 1 serves as the negative control because it will be given the same amounts of food given during the preliminary data collection and is not expected exhibit any changes in behavior.

Nests 2 – 6 will either be given a nutrient-poor diet, or a shortage of food. These serve as non-decision-making experimental groups. Food-shortage colonies are expected to increase their amount of foraging behavior in search of more food, even once the limited food source is depleted. Nutrient-poor colonies are expected to increase the amount of visits to the food sources because they will need a higher quantity of food to meet their nutritional needs. The observed behavioral changes in these groups will allow us to control for the effects of food shortages and malnutrition in the decision-making colonies.

Nests 7 – 10 will be referred to as the decision-making colonies, as they are the only colonies given two different food sources to choose from. In the case of colonies given two different food sources, 50% of the food by weight will be nutrient-rich and 50% will be nutrient-poor. Here, we expect to see a higher proportion of foraging ants to visit the nutrient-rich food over the nutrient-poor food. As mentioned earlier, the unique scent of the nutrient-poor food sources is expected to help foragers differentiate between the two food sources.

Every nest will be recorded from above for one hour a day. This hour will be determined randomly from the pool of three hour periods where the nests are most active, as determined during the preliminary data collection. During this 1 hour period, the following data will be recorded: the number of exits from the underground portion of the nest and the number of visits to each food source.

Because of the sheer number of ants and their small size, it would be unrealistic to tag ants in order to track individual behavior. Due to this, the number of exits, and number of forager visits to the food sources may include individual foragers who leave the nest multiple times or who visit a food source multiple times over the course of a single hour. This also means its possible for the number of visits to a food source to be higher than the number of exits from the nest.

During this period of data collection, we will continue to monitor the health of the colonies using Broodminder data. We will continue to collect data for 5 months or until the colonies show signs of hibernation.

Neurological assay:

 During both the preliminary and experimental periods, we remove a random sample of 5 workers from each nest once a week for dissection. This sample size may decrease if the population size of the nests decreases to a point where the colony’s wellbeing is at risk. We will cut open the head capsules and dissect the brains in isotonic saline. The brains will then be rinsed in a buffer solution, rinsed in water and dried in ethanol, then finally sectioned in 10 µm slices. The slices will be dyed with Methylene blue. These slices can then be observed under a microscope. These procedures have been used in previous studies to observe brain morphology in ants (Gronenberg, et al, 1996). Because head size is highly variable between individuals, we will measure the total brain volume, then calculate the percentage of brain volume taken by the mushroom bodies.

 We expect to see a correlation between decision-making and the morphology of the mushroom bodies. We will compare the morphology of the decision-making ants to the nutrient-poor ants and food-shortage ants to make sure that the food treatments alone were not responsible for any of the observed changes.

Statistics

 For each colony, we will have collected the following data: average % brain volume of the mushroom bodies, average visits to each food source, average exits from the nest. We can pool this data by week and plot each nest’s datapoints by time. In the control and non-decision-making colonies, we expect to see no difference in their foraging behaviors over time.

The decision-making colonies have two sets of data for food source visits, because each had two food sources. We will run paired T tests on these data to test for a difference between the number of visits to each food source. We expect to see a bias in food source visits towards the nutrient-rich food once the ants have established the relationship between the scent and nutritional value of each food source. A significant increase in visits to the nutrition-rich food source confirms that the ants are capable of making decisions while foraging and have been exhibiting this behavior over the course of the study.

We will run a second set of ANOVA tests on the weekly mushroom body data for each nest. A pairwise analysis will then be used to determine which weeks showed the significant increases in size (if the ANOVA test shows significant difference in the data sets). Decision-making colonies are expected to show a significant increase in the size of the mushroom bodies. The control and non-decision-making colonies are expected to not show a significant increase in their mushroom bodies. The lack of a significant trend in the non-decision-making experimental colonies will confirm that malnutrition or food shortages alone are not responsible for the changes in brain morphology of the ants. The lack of significant trend in the control colony will confirm that the change brain morphology is not an inherent physiological trait.

Table 2 – Proposed Budget

 

Item

Quantity

Unit cost

Retailer

Nest boxes

10

$23.79

Tar Heel Ants

Pumice (substrate, 10lb bag)

2

$17.00

Home Depot

BroodMinder-W weight scale

10

$179.00

BroodMinder

BroodMinder software

1

$25.00

BroodMinder

Frozen crickets (1lb bag)

3

$37.99

Fluker Farms

Food processor

1

$56.99

Amazon

Granulated sugar (1lb bag)

5

$4.99

Grocery store

Citric acid (food grade, 5oz)

3

$5.99

Grocery store

Carvone oil (5 oz)

3

$5.89

Bulk Apothecary

Vanilla extract (1oz)

5

$3.49

Grocery store

Camcorder

10

$99.99

Best Buy

Tripod

10

$23.49

Amazon

Methylene blue dye (4 oz)

1

$4.89

Amazon

Miscellaneous carpentry 

$200.00

Home Depot

TOTAL

 

$3,775.59

Employee

Quantity

Salary

Head researcher

1

$80,000/year

Lab technicians

3

$50,000/year

TOTAL

 

$230,000/year

 

GRAND TOTAL

 

$233,775.59

Note: I will be able to access the equipment needed to slice and mount the ant brains in the mouse lab.

Initial M. sabuleti queens and colonies will be collected from the Philadelphia zoo and Central Park zoo, then additional workers will be reared for a period of three months before the study begins to ensure enough individuals for each colony.

 

D.  Literature cited: 
 

ABSTRACT OF RESEARCH PLAN:

Myrmica sabuleti is a species of eusocial ant which exhibits a reproductive division of labor and age-dependent task specialization. The mushroom bodies are a part of the insect brain responsible for olfactory integration and experience-based learning. This portion of the brain varies in size depending on the task specialization of the individual ant. 10 colonies of ants will be given different combinations of nutrient-rich and -poor food to force specific decision-making during foraging. The morphology of the brains of the ants in each colony will be compared to see if there is a link between decision-making and the mushroom bodies.

A.  Specific Aims: 

 This study aims to explore the relationship between decision-making and ant brain morphology during times of environmental stress.

Our hypothesis is that decision-making while foraging will affect the mushroom bodies. Mushroom bodies are a section of the insect brain associated with olfactory integration and experience-based learning (Gronenberg, et al, 1996).

This study will utilize 10 colonies of Myrmica sabuleti to test the hypothesis. A portion of the colonies will be given nutrient-poor food or limited quantities of nutrient-rich food without any other choices. Another portion of the colonies (decision-making colonies) will be given the choice between varying quantities of nutrient-rich food and nutrient-poor food. A small sample of ants from each colony will be taken weekly and dissected to measure the size of their mushroom bodies. We will compare the average size of the mushroom bodies and the change in the size of the mushroom bodies over time between each colony. We will also track the number of ants visiting each food source every day to track their foraging behavior.

Our prediction is that colonies forced to make foraging decisions will have larger mushroom bodies than non-decision-making colonies. By observing these differences, we can begin to make conclusions regarding how environmental stressors affect the neurology of social insects and how brain morphology mediates adaptive behavioral changes.

B.  Significance

Eusocial insects are species of insects characterized by a highly organized social structure of interrelated individuals whose fitness depend on the fitness of the collective nest and reproductive capabilities of the queen (Nowak, et al., 2010). For such a large number of individual organisms to function as a single superorganism requires levels of nuanced communication that makes their neurology inherently interesting (Perry, et al. 2013). Recent studies done on eusocial insects, most notably on honeybees, have shown that their social behaviors, communication methods, and cognitive abilities are far more advanced than previously anticipated (Menzel, 2012). By understanding these complex networks of communication and adaptive behavior, we can better understand how insect foraging functions within an ecosystem.

Myrmica sabuleti is a widely studied species of eusocial ant native to Europe. They exhibit age-dependent task determination (Gronenberg, et al, 1996). Communication between individuals relies primarily on olfactory chemical signaling (Cammaerts, M., et al, 2014). Foraging ants rely mainly on olfactory cues to locate food sources (Detrain, C., et al, 1999).

The decision-making capabilities of ants, and how this directly involves their neurology, have been studied but are still relatively unexplored (Detrain, C., et al, 1999) or have not established causal links (Robinson, et al., 2009). Past studies done on ant neurology have lead us to focus on the mushroom bodies of foraging ants (Gronenberg, et al, 1996). Mushroom bodies, or corpora pedunculata, are the parts of the insect brain responsible for olfactory learning and memory (Perry, et al, 2013). The morphology of mushroom bodies are also highly variable depending on the role an individual plays within the colony. Young, nonforaging ants and queen ants tend to have smaller mushroom bodies than foraging ants (Gronenberg, et al, 1996). Because ant foraging is based heavily in integrating olfactory information, it is essential for foraging ants to be able to distinguish between scents in order to make decisions that maintain the wellbeing of the whole colony.

While some of the traits described inherent to most eusocial insects and ant species, Myrmica sabuleti poses specifically relevant questions because it is a host for parasitic butterflies (Witek, et al., 2014). Maculinea butterflies, such as Phengaris alcon and Phengaris arion leave larvae inside of a M. sabuleti nest to either prey on ant larvae or eat food provided by nurse ants (Witek, et al., 2014). Maculinea butterflies are threatened species and the stability of a specific population can be accurately predicted by analyzing the related population of Mymica ants (Thomas, et al., 2009). However, hosting parasitic butterflies causes a significant strain on a colony’s resources and the wellbeing of its brood (Thomas, et al., 1992; Witek, et al., 2016). While the food shortages simulated in this experiment will not perfectly represent the affect of a parasitic butterfly in a colony, the results may provide insights into how a colony can adapt its behavior when under environmental stress, which will benefit conservation efforts.

 

C.  Experimental Design and Methodology: 

10 colonies of M. sabuleti will be used for this experiment. Each colony will have approximately 200 workers and 1 – 2 queens. They will be kept indoors in separate nest boxes in an appropriate substrate, with a regular 12 hour light/dark cycle and appropriate temperature.

Before any data collection takes place, we will rear single cohort colonies without brood. Previous studies have shown that young, non-foraging ants still experience olfactory-based learning within the nest due to tasks such as brood care and nest maintenance (Gronenberg, et al, 1996). By rearing the ants without brood, their mushroom bodies should stay relatively undeveloped until they specialize in foraging, and therefore should display a more clear trend over time.

Because ants are invertebrates, they are not protected under any animal testing legislation.

Preliminary data collection:

A period of one month will be reserved to collect preliminary data necessary for the controls during the next step in this experiment. The nests will be fed an excess of mealworms (protein source) combined with a sucrose solution. These food sources will be added at the beginning of the day and removed at the end. The weight of each food source will be taken to calculate the amount eaten in one day. The average amount of food eaten every day will be used as a guide to determine the “sufficient” amount of food.

As will be explained below, during the experimental data collection period, a citrus scent will be added to nutrient-poor food in order to mediate olfactory learning in the decision-making colonies. During the preliminary data collection period, we will run T-maze tests on a random sample of ants to make sure that the ants are neither attracted to or adverse to the scent. These ants will not be returned to the source colonies. If we find that the citrus scent biases the decision-making of these ants, we will test back-up aromatic chemicals such as vanilla or carvone oil (this is the last resort because it is the most difficult to obtain).

Each nest box will also be set up with a Broodminder tool. This tool is typically used for monitoring bee hives but can be adjusted for our purposes. It is placed underneath a nest box and provides real-time updates on the nest’s weight and temperature. The weight of a nest box is directly correlated to the number of individuals within the box. This information will be used to monitor the wellbeing of each colony throughout the experiment.

This period of data collection will also be used to fine tune the camera/video setup and procedures necessary for the next step. We will use the video data to determine the 3 hours of the day in which the nests are most actively foraging.

Foraging behavior treatments:

 Once preliminary data has been collected, the nests will be treated with different food sources so we can observe the changes in foraging behavior. Complete food contains the mealworm and sucrose-solution in the proportions observed during preliminary data collection. Protein-poor food contains half the necessary proportion of mealworms. Sucrose-poor food contains half the necessary proportion of sucrose solution. Additionally, both protein- and sucrose-poor food will include a citrus scent (nontoxic) in order to mediate olfactory-based learning.

Sufficient quantity means the food is present in the necessary quantity (by weight) observed in the preliminary data collection. Limited quantity is 2/3 the quantity of food determined necessary.

 

 

Table 1 – Treatments for each nest

Nest

Treatment

1

Nutrient-rich food in sufficient quantities.

2

Nutrient-rich food in limited quantities.

3

Protein-poor food in sufficient quantities.

4

Protein-poor food in limited quantities.

5

Sucrose-poor food in sufficient quantities.

6

Sucrose-poor food in limited quantities.

7

Choice between nutrient-rich food and protein-poor food in sufficient quantities.

8

Choice between nutrient-rich food and protein-poor food in limited quantities.

9

Choice between nutrient-rich food and sucrose-poor food in sufficient quantities.

10

Choice between nutrient-rich food and sucrose-poor food in limited quantities.

Nest 1 serves as the negative control because it will be given the same amounts of food given during the preliminary data collection and is not expected exhibit any changes in behavior.

Nests 2 – 6 will either be given a nutrient-poor diet, or a shortage of food. These serve as non-decision-making experimental groups. Food-shortage colonies are expected to increase their amount of foraging behavior in search of more food, even once the limited food source is depleted. Nutrient-poor colonies are expected to increase the amount of visits to the food sources because they will need a higher quantity of food to meet their nutritional needs. The observed behavioral changes in these groups will allow us to control for the effects of food shortages and malnutrition in the decision-making colonies.

Nests 7 – 10 will be referred to as the decision-making colonies, as they are the only colonies given two different food sources to choose from. In the case of colonies given two different food sources, 50% of the food by weight will be nutrient-rich and 50% will be nutrient-poor. Here, we expect to see a higher proportion of foraging ants to visit the nutrient-rich food over the nutrient-poor food. As mentioned earlier, the unique scent of the nutrient-poor food sources is expected to help foragers differentiate between the two food sources.

Every nest will be recorded from above for one hour a day. This hour will be determined randomly from the pool of three hour periods where the nests are most active, as determined during the preliminary data collection. During this 1 hour period, the following data will be recorded: the number of exits from the underground portion of the nest and the number of visits to each food source.

Because of the sheer number of ants and their small size, it would be unrealistic to tag ants in order to track individual behavior. Due to this, the number of exits, and number of forager visits to the food sources may include individual foragers who leave the nest multiple times or who visit a food source multiple times over the course of a single hour. This also means its possible for the number of visits to a food source to be higher than the number of exits from the nest.

During this period of data collection, we will continue to monitor the health of the colonies using Broodminder data. We will continue to collect data for 5 months or until the colonies show signs of hibernation.

Neurological assay:

 During both the preliminary and experimental periods, we remove a random sample of 5 workers from each nest once a week for dissection. This sample size may decrease if the population size of the nests decreases to a point where the colony’s wellbeing is at risk. We will cut open the head capsules and dissect the brains in isotonic saline. The brains will then be rinsed in a buffer solution, rinsed in water and dried in ethanol, then finally sectioned in 10 µm slices. The slices will be dyed with Methylene blue. These slices can then be observed under a microscope. These procedures have been used in previous studies to observe brain morphology in ants (Gronenberg, et al, 1996). Because head size is highly variable between individuals, we will measure the total brain volume, then calculate the percentage of brain volume taken by the mushroom bodies.

 We expect to see a correlation between decision-making and the morphology of the mushroom bodies. We will compare the morphology of the decision-making ants to the nutrient-poor ants and food-shortage ants to make sure that the food treatments alone were not responsible for any of the observed changes.

Statistics

 For each colony, we will have collected the following data: average % brain volume of the mushroom bodies, average visits to each food source, average exits from the nest. We can pool this data by week and plot each nest’s datapoints by time. In the control and non-decision-making colonies, we expect to see no difference in their foraging behaviors over time.

The decision-making colonies have two sets of data for food source visits, because each had two food sources. We will run paired T tests on these data to test for a difference between the number of visits to each food source. We expect to see a bias in food source visits towards the nutrient-rich food once the ants have established the relationship between the scent and nutritional value of each food source. A significant increase in visits to the nutrition-rich food source confirms that the ants are capable of making decisions while foraging and have been exhibiting this behavior over the course of the study.

We will run a second set of ANOVA tests on the weekly mushroom body data for each nest. A pairwise analysis will then be used to determine which weeks showed the significant increases in size (if the ANOVA test shows significant difference in the data sets). Decision-making colonies are expected to show a significant increase in the size of the mushroom bodies. The control and non-decision-making colonies are expected to not show a significant increase in their mushroom bodies. The lack of a significant trend in the non-decision-making experimental colonies will confirm that malnutrition or food shortages alone are not responsible for the changes in brain morphology of the ants. The lack of significant trend in the control colony will confirm that the change brain morphology is not an inherent physiological trait.

Table 2 – Proposed Budget

 

Item

Quantity

Unit cost

Retailer

Nest boxes

10

$23.79

Tar Heel Ants

Pumice (substrate, 10lb bag)

2

$17.00

Home Depot

BroodMinder-W weight scale

10

$179.00

BroodMinder

BroodMinder software

1

$25.00

BroodMinder

Frozen crickets (1lb bag)

3

$37.99

Fluker Farms

Food processor

1

$56.99

Amazon

Granulated sugar (1lb bag)

5

$4.99

Grocery store

Citric acid (food grade, 5oz)

3

$5.99

Grocery store

Carvone oil (5 oz)

3

$5.89

Bulk Apothecary

Vanilla extract (1oz)

5

$3.49

Grocery store

Camcorder

10

$99.99

Best Buy

Tripod

10

$23.49

Amazon

Methylene blue dye (4 oz)

1

$4.89

Amazon

Miscellaneous carpentry 

$200.00

Home Depot

TOTAL

 

$3,775.59

Employee

Quantity

Salary

Head researcher

1

$80,000/year

Lab technicians

3

$50,000/year

TOTAL

 

$230,000/year

 

GRAND TOTAL

 

$233,775.59

Note: I will be able to access the equipment needed to slice and mount the ant brains in the mouse lab.

Initial M. sabuleti queens and colonies will be collected from the Philadelphia zoo and Central Park zoo, then additional workers will be reared for a period of three months before the study begins to ensure enough individuals for each colony.

 

D.  Literature cited: 
 

  • Cammaerts, M., & Gosset, G. (2014). Ontogenesis of visual and olfactory kin recognition, in the ant Myrmica sabuleti (Hymenoptera: Formicidae). Annales De La Société Entomologique De France (N.S.),50(3-4), 358-366.
  • Cammaerts, M., & Cammaerts, R. (2015). The acquisition of cognitive abilities by ants: A study on three Myrmica species (Hymenoptera, Formicidae). Advanced Studies in Biology,7, 335-348.
  • Detrain, C., Deneubourg, J., & Pasteels, J. M. (1999). Decision-making in foraging by social insects. Information Processing in Social Insects,331-354.
  • Gronenberg, W., & Hölldobler, B. (1999). Morphologic representation of visual and antennal information in the ant brain. The Journal of Comparative Neurology,412(2), 229-240.
  • Gronenberg, W., Heeren, S., & Hölldobler, B. (1996). Age-dependent and task-related morphological changes in the brain and the mushroom bodies of the ant, Camponotus floridanusJournal of Experimental Biology
  • Perry, C. J., Barron, A. B., & Cheng, K. (2013). Invertebrate learning and cognition: Relating phenomena to neural substrate. Wiley Interdisciplinary Reviews: Cognitive Science,4(5), 561-582.
  • Menzel, R. (2012). The honeybee as a model for understanding the basis of cognition. Nature Reviews Neuroscience,13(11)
  • Robinson, E. J., Richardson, T. O., Sendova-Franks, A. B., Feinerman, O., & Franks, N. R. (2009). Radio tagging reveals the roles of corpulence, experience and social information in ant decision making. Behavioral Ecology and Sociobiology,63(5), 779-779.
  • Thomas, J. A., & Wardlaw, J. C. (1992). The capacity of a Myrmica ant nest to support a predacious species of Maculinea butterfly. Oecologia,91(1), 101-109.
  • Witek, M., Barbero, F., & Markó, B. (2014). Myrmica ants host highly diverse parasitic communities: From social parasites to microbes. Insectes Sociaux,61(4), 307-323.
  • Witek, M., Ślipiński, P., Peral, G. T., & Csata, E. (2016). Consequences of the arms race between Maculinea teleius social parasite and Myrmica host ants for myrmecophilous butterfly conservation. Journal of Insect Conservation,20(5), 887-893.
  • Thomas, J. A., Simcox, D.J., & Clarke, R.T. (2009) Successful conservation of a threatened Maculinea butterfly. Science, 325(5936), 80-83
  • Nowak, M. A., Tarnita, C. E., & Wilson, E.O. (2010) The evolution of eusociality. Nature. 466, 1057-1062.

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