STEM with Science and Technical Writing is taught by Dr. Kevin Crowthers. In this class we are guided in completing our STEM project. We also complete various activities to prepare for presenting our project and providing its necessary documentation.

Simulating Pollinators to Find How Habitat Loss Affects Biodiversity

Bees are keystone species and about ⅓ of our agriculture relies on them as pollinators (Rong & Sadhukhan, 2021). Habitat fragmentation is thus a major problem that is negatively affecting native bee species. It can cause problems with sourcing nectar and finding suitable areas to live in, that may result in decline or extinction of species. To be able to help mitigate this problem, solutions like adding in patches of flowers interspersed between major areas of habitat need to be tested.

Abstract

Nearly one third of all agriculture relies on pollination from bees. Native pollinators are very important to both native ecosystems as a keystone species and to farms because they provide pollination without needing to be constantly taken care of like the domesticated honeybees that commercial farms oftentimes use to pollinate their crops. Habitat fragmentation is causing decreased numbers of these native pollinators by removing their sources of food and places to make nests. To mitigate their falling populations due to habitat fragmentation, different flower types and positions that most effectively mitigate these problems are needed. This experiment evaluates the effectiveness of possible solutions when trying to increase the survival of native bees using software to simulate their behavior. To test these animal’s approximate behavior an agent-based model with varying bee agents that interact with a population of flowers was created. Then, various levels of habitat fragmentation were created to test the effects of habitat fragmentation on bees with different flower preferences and different patterns of solutions were tested. The results show that adding in smaller areas of habitat spread throughout an area of habitat loss could be an efficient way to reduce the impacts on native pollinators. While these results do not come from actual animals, they do give a good approximation of the best strategies to help these different bees. This research could be applied to different empty green spaces around towns and farms to help promote native pollinators in that area and help reverse the decline of native bees. Keywords: Agent-based modeling, habitat fragmentation, native pollinators, agriculture, bees

Research Question

Hypothesis

Is there a way to limit the effects of habitat loss on bee populations using flower placement?

Using a Netlogo simulation, I hypothesize that if native bee-specific flowers are concentrated in smaller patches spread throughout an ecological niche, the effects of habitat fragmentation will be mitigated.

Background

Pollinators are made up of different types of animals, but the most significant pollinators are the various bees (Rong & Sadhukhan, 2021). The most known type of bee is the western honeybee (Apis mellifera) which is domesticated to make our honey, but there are many other types of bees that are extremely important in the pollination of plants.

Native bees are important as they are well adapted to the plants of the area and can provide pollination without the need of being kept by beekeepers (Kremen et al., 2002; Native Pollinator Decline and Conservation, n.d.). In many cases, they are also better than honeybees at pollinating the type of flower that they specialize in, (Sapir et al., 2017).

All types of bees have been in decline due to various problems; however, important native species of bees do not receive the same conservation as honeybees (Native Pollinator Decline and Conservation, n.d.). These problems that are negatively affecting bees include pesticides, diseases and parasites, climate change, and fragmentation and loss of habitat (Rong & Sadhukhan, 2021).

Habitat Fragmentation

Habitat fragmentation, the breaking up of habitat into smaller, separated pieces, can have various negative effects on pollinators like bees because of reduced living space and places to find flowers. Reducing possible flower food sources can impact their ability to survive, as they must spend more time and energy getting to flowers and they have less nectar to sustain themselves in the end. This makes it harder for native bees live off sources of food that are farther away from their habitat (Huais et al., 2020). Habitat fragmentation can also have other more subtle impacts. One of these is that habitat fragmentation can cause the flowering periods of plants to shift times, changing when the pollinators are able to visit the flowers. This leads to the phenological patterns between pollinators and plants to become misaligned, leading to a greater risk for local pollinators to die out (Xiao et al., 2016).

Different types of bees have in different types of flowers and number of different flowers species that they will collect nectar from. Some bees are more generalist, meaning that they pollinate many different types of flowers, while others are more specialist, meaning that they pollinate only a couple types of flowers. This difference leads to differing consequences of habitat loss on them (Figure 1). Generalist bees in general do better in the face of habitat fragmentation when compared to specialist bees due to having a wider range of food sources. This causes decreased biodiversity as specialist bees will die out due to not being able to find new sources of food.

Figure 1. This chart shows a general model of the how well a generalist and a specialist bee would survive in response to habitat fragmentation, with fragmentation taking away several of the pollinators’ flowers that they can access. PS represents a specialist pollinator. PG represents a generalist pollinator. S represents a specialist plant and G represents a generalist plant. The line connecting elements represents that they have plant-pollinator relations. (Xiao et al., 2016)

Agent-based Modeling and Simulation

Agent-based models are simulations with different coded entities called agents that interact with each other. This allows for the behaviors to be coded for various organisms that then interact with each other. From these, biological systems can be approximated with enough accuracy that different variables can be tested and analyzed, and these results can tell us about biological systems otherwise impossible to test (Introduction to Simulation, n.d.). This type of simulation has already been in use to model bee hives, including BEEHAVE which attempts to accurately model the entire beehive system and its population dynamics (Becher et al., 2014). This makes it an optimal system for simulating population of bees with different levels of habitat fragmentation.

Equipment and Materials

The project was performed digitally. The work for the project was done on a MacBook Pro. This project was completed using the agent-based modeling software Netlogo. The original code used that was built off and adapted into this project was provided by Dr. Elizabeth Ryder and was from the WPI Beecology Project (Native Pollinator Decline and Conservation, n.d.). The original model was coded to model the effects of an invasive flower species on an ecosystem with four flower and two bee species. Modifications needed to be completed to adapt the previous model into what was needed for this project. These adaptations were an increase of scale of the simulation, add in an additional bee species, remove the invasive flower species, and add in a method for habitat fragmentation to be modeled.

Agent-based Model

Agent-based models have individual agents that interact with each other to simulate organisms in an ecosystem. The agents in this model were bees, hives, and flowers. Each of the three species had one starting hive with a set number of bees, these bees would then be released in seasons to collect nectar. The flowers which the bee agents would collect nectar from was determined by their preference for certain flowers. This allowed for some species to be generalist and visit any flower, while some were specialist and would avoid certain species of flower. This nectar collected would then go on to determine how many new bees could be produced as well as how many new hives could be produced. Every passing of time, or tick, any flower or hive agent on a white area would be removed to be able to model how habitat fragmentation limits the area which these bees and plants can be.

Collecting Data

To get the first part of the results, the models were ran three times each. Each of these times the model was ran with a different background that represented different levels of habitat fragmentation. The bees were modeled throughout ten seasons of collecting nectar.

To collect the main part of the data, 12 different situations of habitat fragmentation were created with varying configurations and varying percent coverage of habitat. The coverage of habitat was varied at 10%, 30%, 50%, and 80% of the area were covered with habitat. The different configurations were with the available equally spread into five different circular areas (Even), half in a circular section in the middle and the other area equally divided in 4 outer sections (Broken), and all in a circular section in the middle (Middle). The bee populations during the tenth season were collected. Each situation was run five times.

Figure 2. This figure shows the results gathered from running the model with land area pattern of habitat fragmentation shown to the right. To the left the graphs generated from the three tests are shown. The blue marker represents the singular generalist bee while the orange and yellow lines represent two different specialist bees with opposing flower preferences.

Figure 3. This figure shows the results gathered from running the model with land area pattern of habitat fragmentation shown to the right. To the left the graphs generated from the three tests are shown. The blue marker represents the singular generalist bee while the orange and yellow lines represent two different specialist bees with opposing flower preferences.

Figure 4. This figure shows the results gathered from running the model with land area pattern of habitat fragmentation shown to the right. To the left the graphs generated from the three tests are shown. The blue marker represents the singular generalist bee while the orange and yellow lines represent two different specialist bees with opposing flower preferences.

Averaged Population	Specialist Species 1	Generalist Species	Specialist Species 2	Average % Standard Deviation
10% Even	0	0	0	0%
10% Broken	6	17.8	0	149%
10% Middle	3	21.2	6.6	136%
30% Even	150	241	114.4	74%
30% Broken	127.6	227.8	99.4	115%
30% Middle	201.4	310	43.4	122%
50% Even	710.2	552	159.2	62%
50% Broken	679	424.4	143.6	107%
50% Middle	538	846	108.4	85%
80% Even	1481.4	1036.6	270	65%
80% Broken	797.8	1005.4	197.2	69%
80% Middle	1561.8	1073.8	376.8	61%

Figure 5. This figure shows the bee population in the tenth season of population growth and the standard deviation as a percentage of the average population. This is shown for 12 unique scenarios over five different runs each.

Analysis

While there is variance shown by the effects of different configurations with different amounts of habitat, there are correlations. One of these correlations is that when all the habitat is connected and together shown by the middle configuration, have a higher final population then other configurations. The configuration with evenly spread pockets of habitat had the least deviation from the average population for each of the species. This means that it allowed for more stability in all the populations of the bees, rather than just the highest total population.

Discussion

The goal of this project was to find what methods of planting flowers would potentially be the most effective for maintaining native bee populations. The data that was collected from the simulation of these native bees shows that the most land efficient way to mitigate the effects of habitat fragmentation are by using several patches of habitat outside remaining larger fragments of habitat.

Possible limitations of the experiment are that it is just a computer model, so it cannot truly know the exact behavior of pollinators to show the effects of habitat fragmentation. The purpose of the model is to approximate it the best it can. A way that may not be is the most realistic is that maintaining the virtual population of bees to study how well they do in the environment is not the most realistic. This is because to have the bee population reach carrying capacity by generating new hives when there is a set amount of nectar, which for real bees, would only generate if they ran out of space, they would make a new hive for the next season. A possible alternative model would be to test real living bees in an experiment to see how they behave in a closed system, albeit one that is a large scale, or to analyze data collected from different bee species and compare it to the levels of habitat fragmentation happening in that area.

While just the amount of cover still available has been tested before and its effects on both generalist and specialist pollinators has been studied before, never has agent-based modeling been used to study different configurations of habitat available effect on bee populations. This data can be used to create optimal solutions for planting flora to limit the effects of habitat fragmentation. This placement can be used around farms to promote agricultural yields and reduce the need to get honeybees brought in, and it can be used around to create a more ecofriendly environment. This will help to mitigate the effects on the populations of native bee species.

Future Research

More research is needed is this area to provide more justification for towns and farms to use some of these methods. Further making the model more realistic as well as using more and more different configurations to see what the absolute best way is to help native bees. This could be applied to individual situations by configuring what already exists in some places and testing different ways of adding new habitat.

References

Becher, M. A., Grimm, V., Thorbek, P., Horn, J., Kennedy, P. J., & Osborne, J. L. (2014). BEEHAVE: A systems model of honeybee colony dynamics and foraging to explore multifactorial causes of colony failure. Journal of Applied Ecology, 51(2), 470–482. https://doi.org/10.1111/1365-2664.12222

Borst, P. (2015). The Fall and Rise of the Honey Bee. American Bee Journal, 315-319.

Huais, P. Y., Grilli, G., Amarilla, L. D., Torres, C., Fernández, L., & Galetto, L. (2020). Forest fragments influence pollination and yield of soybean crops in Chaco landscapes. Basic and Applied Ecology, 48, 61–72. https://doi.org/10.1016/j.baae.2020.09.003

Introduction to Simulation. Chapter 1: Introduction to Simulation. (n.d.). https://intro.bio.umb.edu/SLNbook/introduction.html

Kline, O., & Joshi, N. K. (2020). Mitigating the effects of habitat loss on solitary bees in agricultural ecosystems. Agriculture, 10(4), 115. https://doi.org/10.3390/agriculture10040115

Kremen, C., Williams, N. M., & Thorp, R. W. (2002). Crop pollination from native bees at risk from agricultural intensification. Proceedings of the National Academy of Sciences, 99(26), 16812–16816. https://doi.org/10.1073/pnas.262413599

Native Pollinator Decline and Conservation. (n.d.). Beecology Project; WPI. https://beecology.wpi.edu/website/home

Pollination. (n.d.). Native Plants and Ecosystem Services. Retrieved November 23, 2023, from https://www.canr.msu.edu/nativeplants/pollination

Rivière, J., Alaux, C., Le Conte, Y., Layec, Y., Lozac’h, A., Rodin, V., & Singhoff, F. (2018). Toward a Complete Agent-Based Model of a Honeybee Colony. In J. Bajo, J. M. Corchado, E. M. Navarro Martínez, E. Osaba Icedo, P. Mathieu, P. Hoffa-Dąbrowska, E. del Val, S. Giroux, A. J. M. Castro, N. Sánchez-Pi, V. Julián, R. A. Silveira, A. Fernández, R. Unland, & R. Fuentes-Fernández (Eds.), Highlights of Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection (pp. 493–505). Springer International Publishing. https://doi.org/10.1007/978-3-319-94779-2_42

Rong, C., & Sadhukhan, S. (2021). Decline of Bees, a Major Pollinator – A Review. 2(2), 9. https://bkgc.in/ejournal/paper_list/35-43.pdf

Ryder, E., Corace, M., Heath, K., & McDonough, D. (n.d.). Blooms (Version 5) [NetLogo].

Sapir, G., Baras, Z., Azmon, G., Goldway, M., Shafir, S., Allouche, A., Stern, E., & Stern, R. A. (2017). Synergistic effects between bumblebees and honey bees in apple orchards increase cross pollination, seed number and fruit size. Scientia Horticulturae, 219, 107–117. https://doi.org/10.1016/j.scienta.2017.03.010

Xiao, Y., Li, X., Cao, Y., & Dong, M. (2016). The diverse effects of habitat fragmentation on plant–pollinator interactions. Plant Ecology, 217(7), 857–868. https://doi.org/10.1007/s11258-016-0608-7

STEM