During college, I spent a summer working in Cape Cod, a headland known for its maritime personality, distinct architectural style, and the second homes of Massachusetts’s “East Egg.” On the weekends I would drive up the narrow cape, sink my toes in the dunes, and watch the sun disappear below the bay’s horizon. One weekend in Provincetown, at the tip of the Cape, I stumbled into a small art store owned by a woman who had lived in Cape Cod her entire life. I bought a little painting of a sunset, a representation of nature painted through her eyes.
In the 8.5” by 11” space, the painter shared her Cape Cod sunset. Her representation was abstract; she reduced the sunset’s quintessential red-orange gradient to broad, solitary strokes. The ocean’s ripples and foam were replaced with brisk blue fans, and the seabirds blended into the clouds, which blended into the sky. She used colors and shapes playfully, yet deliberately, to share her world. This painting has travelled with me to the many places I have since lived, and her abstract representation has shaped how I see and understand sunsets too.
Ecological models are also abstractions. In the same way an abstract painter distorts what is in front of her to reveal a truth, a model makes false, simplified statements to provide a useful insight about nature. A model represents an ecological process with mathematical expressions, relating what we can perceive to help us understand the unperceivable. By intentionally omitting many details, a model distills nature’s complexity to what its user believes are its most essential and useful elements.
The world can be divided into quantities that are observed and quantities that are unobserved, and we hope to learn about what we cannot observe through what we can observe. For example, the Lotka-Volterra model can reveal interactions between a predator, like killer whales, and their prey, Chinook salmon, in the Puget Sound. Through a pair of differential equations, this model uses what we can observe, the number of whales and salmon, to elucidate what we cannot observe, like the killer whales’ searching efficiency or the reproduction rate of the Chinook salmon. By collecting data through repeated observations of these species and linking these quantities through simplified mathematical expressions, we can explain their fluctuations and represent their interactions. These simplifications can be useful because they can bring us closer to understanding nature’s fundamental processes. Similarly, abstract art conveys concepts that are often not found in the physical world, but the artist’s representation, or misrepresentation, reveals a condensed truth.
Although abstractions can be useful, we cannot completely disregard the details they omit. We rarely observe perfectly the process we seek to understand. When a painter is looking at a sunset, there are certain wavelengths in sunlight that she cannot see. Maybe she is distracted by a cormorant with a fish in its mouth and misses a sailboat to the right, and she therefore incorrectly sees a reality she hopes to represent.
Scientists also do not observe nature perfectly. Marine scientists often estimate the number of salmon through a method called mark-recapture. In this technique, a portion of the fish in an area are captured, marked, and released back into the water. Later, another portion of fish is captured, and the proportion of marked to unmarked fish is used to then estimate the total number of fish in a water body. By definition, however, this estimation is a rough calculation of the true number of fish. Our attempts to express nature’s truths through abstraction inevitably result in error because of our inability to perfectly view the world.
These abstract representations are also limited by their medium. A painter is constrained by her toolset: the pigments that comprise her paints and the two-dimensionality of her canvas. Her ability to successfully communicate her abstract representation is also limited by untrained viewers, those who might rely on the omitted details to comprehend her distilled truth. Similarly, a set of Greek letters, and the arithmetic operators that link them, will never correctly represent nature’s intricacies.
For example, a simple mathematical expression representing interactions between salmon and killer whales ignores competition among salmon species and overlooks sound pollution that might affect a killer whale’s ability to eat. In addition to these intentionally omitted details, a model can fail to capture nature’s random, unpredictable processes. With lightning strikes, floods, and droughts, the natural world is a messy, noisy place. A goal in modeling natural processes, therefore, is to assess and quantify uncertainty that comes from imperfect observation and a limited medium.
There are ways, however, that these two types of abstractions critically diverge. Implicit in an artistic abstraction, but not in a mathematical abstraction, is that there are multiple truths. Abstract art is rooted in the discovery that truth is subjective, encouraging imagination and involvement. Conversely, objectivity is a fundamental ideal in science. An ecological model inherently claims that there is a singular truth in nature, an underlying, latent state that through repeated observations, we can asymptotically approach and increasingly understand. Western, colonial ideologies are grounded in the assumption of one dominant truth, and mainstream science often reinforces a singular way of knowing.
Environmental science can learn from abstract art’s embrace of multiple truths. For example, Indigenous ways of knowing, based in millenia of interactions with nature that often transcend settler modes of environmental observation, offer a different and historically suppressed interpretation of nature. While neither of the two knowledge systems is monolithic, Western science deconstructs nature’s patterns to then construct models and explain interactions among its parts, while Indigenous ways of knowing “weave patterns within nature and the relationships among love, land, and life.”
These ideologies, however, can be complementary; they do not have to be in opposition. Indigenous science challenges and improves Western science by offering alternative perspectives that ultimately lead to new hypotheses. Integrating multiple ways of knowing would not reduce science’s objectivity but would instead enhance objectivity through the inclusion of multiple truths and the elimination of bias favoring Western perspectives.
Many of us love art because we use it to make sense of the world around us. Both abstract art and mathematical models lie about nature to reveal a truth. By drawing on abstract art’s openness to subjectivity and different ways of knowing, we can come closer to uncovering nature’s processes.