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Abigail Lindner Worcester Polytechnic Institute |
Ecology is a branch of biological science that has existed as a formal field for only about a hundred years, though its history dates much farther back. Practitioners, called ecologists, study the relationships between living organisms and their physical environments to understand the connections between plants, animals, and the surrounding world and illuminate the benefits of ecosystems and humans’ influence on them (The Ecological Society, n.d.). Research may be focused on something as small as a single lake teeming with microbes or as large as Earth’s species-rich, largely unexplored oceans.
The importance of ecology has been gradually realized in the public and in academia as findings in other branches of biology and other scientific fields spotlight the impact of human activity on modern ecosystems, both natural and man-made, and on the interactions between the living things in them. For instance, the rapid growth of the human population in the last century and the demand for more oil and gas resources have altered the migratory patterns of many large mammals, including bison and elk, in North America, and these changes affect breeding patterns, grassland productivity, and the seasonal dietary habits of some animals (Wilcove, 2010). Experimenting and modeling by researchers in ecological studies can provide insight into what our decisions have affected and how we can respond to the changes in our ecosystems.
Applied mathematics and operations research tools and techniques play an important role in modern ecological studies. In fact, many ecologists come from non-ecology backgrounds, having studied mathematics, statistics, or physics beforehand (Bolker, 2005). These quantitative fields have theories and techniques that provide sufficient supplements and sometimes even substitutes to the empirical and large-scale field experiments that are difficult to replicate or attempt due to the high complexity of environmental conditions (Petrovskii, 2018). Moreover, while the traditional empirical formulae of ecology that use computer simulation techniques are highly adept at fitting curves to data and predicting specific cases, they fail to reveal the underlying ecology. Dynamical systems, often used in operations research logistics problems, can account for these ecological mechanisms (“Mathematical ecology," n.d.).
Historical Background
One of the oldest products of the fusion of applied mathematics and ecology is the Lotka-Voltera models (McCann, 2021). The Lotka-Volterra model, independently designed by American bio-physicist Alfred Lotka and Italian mathematician Vito Volterra in the mid-1920s, is the simplest predator-prey model, using a pair of first-order, nonlinear differential equations to describe the dynamics between two species, one predator and one prey.
The “heroic age” of theoretical ecology, before which point ecology was a severely theory-poor biological field, came with the work of Princeton biologist Robert MacArthur, Harvard biologist E.O. Wilson, and their colleagues (Bolker, 2005). MacArthur, in 1965, was “among the first to explore how interactions and competition among species support coexistence and ecosystems,” and in 1967 he published the seminal Theory of Island Biogeography with Wilson (Kelly, 2020). This theory supposed that the rates of migration and extinction in two islands that received species from a common mainland were governed by the distance of each island from the mainland and the size of each island.
Experiments in the latter half of the 20th century, such as one by E.O. Wilson and American biologist Daniel Simberloff involving tiny mangrove islands off the southern coast of Florida, provided ample evidence in support of the theory of island biogeography (Wills, 2013). When physicists began pouring into the field in the 1970s, the use of dynamical systems theory in ecology dramatically increased, enabling the extension of the two-species models of the first half of the 20th century to many more species (McCann, 2021). As a result of these advancements, in the last two or so decades biology has relied heavily on mathematical and computer-based models.
Ecological Research in the 21st Century
Modern ecological research is addressing and exploring a wide variety of problems, including the impact of climate change on marine ecosystems, nitrogen availability in soil affected by agricultural and industrial pollution, the success or failure of conservation efforts to protect underrepresented biomes and endangered species, and the adaptation of wild species to shrinking habitats.
A big topic in ecology is biodiversity, with increased attention and funding being funneled toward research of this topic and increased coordination of biodiversity assessment initiatives (Rillig et al., 2015). Biodiversity refers to the diversity of life on Earth or the “measure of the distribution and abundance of species” (Kelly, 2020). Mathematical models, gene sequencing, climate models, and satellites have expanded our understanding in the last fifty years, though a grand theory unifying all of biodiversity research, which is essential for continuous dialogue between the theoretical and empirical sides of ecology, has yet to be established (Rillig et al., 2015).
On the issue of theoretical ecology and empirical ecology dialoguing and coordinating, a research aim in the 21st century is a greater harmonization of theory and data. Ecology runs into the two extremes of having, in one area, theory without data and having, in another area, data without theory (Kelly, 2020). That is, theories are developed without empirical studies, or data is gathered without explicit reference to theory (Rillig et al., 2015).
Dr. Ben Bolker, a mathematical, statistical, and computational biologist at McMaster University and author of Ecological Models and Data in R (2008), refers to the more mature scientific field of physics as a good example of the type of relationship he hopes to see in ecology: “empirical and theoretical physicists may distrust each other, but they manage to communicate. Empiricists perform a new experiment, and all the theoreticians go out and try to explain it; theoreticians develop a new theory, and all the empiricists go out and try to test it" (Bolker, 2005).
Possibilities for Operations Research Practitioners
There are numerous examples of operations research practitioners participating in and contributing to ecological research or of operations research tools being used in the same. From modeling invasive species that destabilize ecosystems to identifying optimization methods that take into account efficient resource use and environmental concern to developing ways to minimize the negative impact of human activity on natural ecosystems, operations researchers are applying their quantitative and data-focused skills to address ecological concerns (Mishra, 2020; Büyüktahtakın and Haight, 2018; Dekker et al., 2012).
The skill set of an operations researcher could be easily adapted to the modeling and data demands of modern ecological research. As operations research is primarily concerned with the effectiveness and efficiency of decisions, OR professionals could engage in research on whether and how a given proposal to, say, encourage the repopulation of an endangered species could be executed to maximum benefit with minimal resource expense. Moreover, OR professionals would likely be comfortable poking through the rich store of increasingly publicly available biodiversity data, collecting their own, and making sense of all of it for the benefit of the theoretical ecologists (Rillig et al., 2015).
Opportunities exist on both sides - theoretical and empirical - of ecological research for OR practitioners to make a difference.
References:
- Bolker, B., 2005. Other people’s data. BioScience 55, 550–551.
- Büyüktahtakın, I.E., Haight, R.G., 2018. A review of operations research models in invasive species management: state of the art, challenges, and future directions. Annals of Operations Research 271, 357–403.
- Dekker, R., Bloemhof, J., Mallidis, I., 2012. Operations research for green logistics–an overview of aspects, issues, contributions and challenges. European journal of operational research 219, 671–679.
- Kelly, M., 2020. From muddy boots to mathematics: Advancing the science of ecosystems and biodiversity. Princeton Environmental Institute .
- McCann, K.S., 2021. Mathematical ecology. Oxford Bibliographies URL: https://www.oxfordbibliographies.com/view/document/obo-9780199830060/obo-9780199830060-0004.xml.
- Mishra, M.K., 2020. Application of operational research in sustainable environmental management and climate change .
- Petrovskii, S., 2018. Progress in mathematical ecology.
- Rillig, M.C., Kiessling, W., Borsch, T., Gessler, A., Greenwood, A.D., Hofer, H., Joshi, J., Schröder, B., Thonicke, K., Tock-ner, K., et al., 2015. Biodiversity research: data without theory—theory without data.
- Wilcove, D.S., 2010. No way home: the decline of the world’s great animal migrations. Island Press.
- Wills, C., 2013. Green Equilibrium: The vital balance of humans and nature. Oxford University Press.