I have a Dracaena marginata plant in my study that has grown to within three inches of our ten foot ceilings. Its highest branches have hovered at that height for a couple of years, and while it keeps growing, the plant appears to know where the ceiling is and contorts itself to avoid it.
We’ve all seen plants that grow towards a light source, from trees that seem determined to rise above the foliage around them, to the spindly succulents of college dorm rooms. Other plants, like poppies and morning glories “sleep” at night by furling their petals closed. And recently, experiments on plants have shown that they can adapt in the moment to new environmental conditions. Which leads scientists to wonder, What’s driving these responses in the moment that they occur?
Plant Cognition is an emergent field adjacent to the cognitive sciences and behavioral ecology, which investigates how the environment affects and produces behaviors. Evolutionary ecologist Monica Gagliano (most recently of the University of Sydney) prefers the name Plant Cognitive Ecology, which points to the interplay between the environment and plant intelligence. But using the word “intelligence” to describe plants is controversial. Although a finely tuned definition of intelligence may well describe the adaptations that plants undertake, the word “intelligence” is so closely associated with the presence of a brain that it can be a hard pill to swallow when it comes to describing plant abilities.
Thus, and as Gagliano notes, the field of plant cognition is undergoing a difficult birthing process, largely because it relies on expertise from both behaviorists and physiologists. The former sees an organism that evolved in its environment holistically, and the latter deduces cognitive possibilities from the sum of the organism’s parts. So, while a behaviorist analyzes actions as coordinated responses to their surroundings, a physiologist may conclude that an organism without a central nervous system simply isn’t capable of intelligently coordinating such a response.
Gagliano’s research is behavioral and includes a study that elicited a Pavlovian response from a plant. Instead of using food plus a sound cue to make a dog drool even in the absence of food, Gagliano used light plus the breeze from a fan to make pea plants turn in expectation of light, even when only the fan was blowing. Pea plants turn toward the light naturally, so Gagliano tested whether they could, like Pavlov’s dogs, be trained to physically respond to something they merely associated with light. Over the course of just three days, the plants learned to associate the fan with the light they craved.
The parallels to Pavlov’s experiment are compelling, but other scientists have objected that comparing the plants’ responses to those of dogs is mixing apples and oranges. Lincoln Taiz (professor emeritus of molecular, cell, and developmental biology at UC Santa Cruz) argues that Gagliano’s language is metaphorical: according to Taiz, plants “habituate” or “become desensitized” rather than “learn.” But Gagliano insists that using the language of learning is necessary for plant and animal cognition to be comparable, and that comparing the two sheds light on each and is thus important for scientists’ understanding. Interestingly, her perspective is reflected in one Darwin held in the nineteenth century when he compared the apex or “radicle” of the plant root to the animal brain.
Experiments to determine whether learning occurs in other non-animal organisms may shed further light on the plant question. Slime molds in particular demonstrate uncanny abilities given that they are single celled organisms (which used to be classified as fungi, but which are now considered more akin to amoeba, though in a class unto themselves). They can migrate over land to reach food sources, suggesting that they can smell or otherwise sense the presence of food, even without a nervous system. And that’s the least of their accomplishments. Slime molds can also form memories—and pass them on when they fuse with other slime molds—and even solve problems. In one experiment, a slime mold called Physarum polycephalum was presented with a version of the Traveling Salesman problem, which requires finding the most efficient route among a number of cities, with each visited once. Not only did it solve the problem, but it did so as efficiently as if an algorithm had directed it.
Other single-celled organisms called Stentor roeselii—a tube shaped ciliate—learned a variety of methods to avoid a noxious dye and, more debatably, learned to escape from a glass vial. So, it would appear that some sort of learning is taking place at the cellular level, which has interesting implications for the question of plant cognition, since plants are comprised of a variety of cell types.
Slime mold, Stentor, and plant behavior show how difficult it is to describe the boundaries of intelligence, especially in the absence of a central nervous system.
We can think of the nervous system as something of an expectation machine involving a sensory apparatus, an evaluator or memory, and an actor or operator that interprets difference and problem solves. What scientists across primitive organisms appear to be learning is that something akin to a nervous system need not be centralized. In other words, maybe our own limited understanding of the human brain should not, given those limitations, foreclose the admission of other life as intelligent.
By Aimee Fountain
References: https://www.nature.com/news/how-brainless-slime-molds-redefine-intelligence-1.11811 https://www.theguardian.com/science/2019/jul/03/group-of-biologists-tries-to-bury-the-idea-that-plants-are-conscious https://royalsocietypublishing.org/doi/10.1098/rsos.180396#d3e2496 https://pubmed.ncbi.nlm.nih.gov/28875517/ https://www.forbes.com/sites/andreamorris/2018/05/09/a-mind-without-a-brain-the-science-of-plant-intelligence-takes-root/?sh=738ba2be76dc https://www.newyorker.com/magazine/2013/12/23/the-intelligent-plant https://www.wnycstudios.org/podcasts/radiolab/articles/smarty-plants https://www.pnas.org/content/106/10/4048 https://www.sciencealert.com/an-amoeba-has-solved-an-exponentially-complex-problem-in-linear-time https://www.sciencedirect.com/science/article/pii/S0960982219313740 https://www.quantamagazine.org/slime-molds-remember-but-do-they-learn-20180709/