Why and How Plants are Intelligent

The concept of intelligence broadly refers to the capacity to solve problems and to adapt to the environment. The phenomenon of phototropism can throw light on an amazing chapter of contemporary research on the systemic responses of the natural realm

A A baby plant in an egg shell (Wix Pic)

By Primavera Fisogni

If intelligence is defined as the ability to solve problems, then plants are undoubtedly intelligent, albeit in a way different from that of humans. Even the most radical objection — that plants lack a central nervous system — cannot really be considered valid. Consider forms of collective intelligence, such as swarms or colonies, and broaden your perspective. These are sets of repeating modules, each of which has a command centre. In this article, I revisit some reflections published in a paper co-authored with Professor Lucia Urbani Ulivi (Urbani Ulivi & Fisogni, 2024) concerning the multiple ways to adapt to the environment. The focus is on phototropism and the intentional responses of plants.

A biological phenomenon

Phototropism (light + movement) is the way green plants respond to a light source and is an easily observable biological phenomenon. Imagine a seedling in a dimly lit room: its stems are oriented towards the brightest light; if we change the direction of the light beam, the plant turns in that direction. It seems to move deliberately to ensure that the flowers, leaves, trunk and roots have the optimal growth conditions.

Phototropism clearly reveals adaptive behaviour within the botanical realm and has become a relevant topic for a better understanding of the intelligent behaviour of green plants, raising several issues regarding plant cognition. The lack of a neuronal system is no longer considered a sufficient reason to exclude these living entities a priori from the highest levels of capability belonging to more evolved living beings.

Two related paradigms

There is a wide consensus among scholars that the photosynthetic and phototropic world of plants is related to specific organs that collect, organise, and re-modulate external light stimuli, giving rise to the ability to choose between different and conflicting options, similar to that of more evolved living beings. On the one hand, the focus is on cells as the centre of neuronal skills (Trewavas, 2009, 2014, 2016).

Conversely, the 'root brain' is considered to be the central infrastructure of plants (Baluska, Schlicht, Volkmann & Mancuso, 2008). Both search for minimal cognition in plants (Garzón & Keijzer, 2011).

According to the first theory, intelligent behaviour exhibited by single cells and systems, and the similarity between the interactome and connectome, indicate that neural systems are not necessary for intelligent capabilities (Trewavas, 2017: 1).

Intelligent leaf movement in low light, adaptive plasticity, and intelligent responses to light and light resources can be experimentally detected, as can adaptive variability in response to light in crowded conditions. These investigations echo Darwin's intuitions (1880) and the discourse of the plant biologist McClintock when she was awarded the Nobel Prize.

'A goal for the future would be to determine the extent of the cell's knowledge of itself and how it uses that knowledge thoughtfully when faced with change' (McClintock, 1984; quoted in Trewavas, 2016: 2).

The other scientific approach to plant intelligence, plant neurophysiology, is based on plant neurobiology. Many neuronal-like activities based on plant synapses appear not only to be theoretically justified but also to have been observed experimentally (Baluška, Mancuso, Volkmann, Hlaváček, Barlow, 2006; Baluška and Mancuso, 2007). A network of synapses, for example, transports auxin, the hormone responsible for growth related to phototropism. The roots' apices 'emerge as command centres' while 'acting as the posterior poles'. In conclusion, plants are capable of learning and making decisions about their future activities according to current environmental conditions; it is clear that they possess a complex system for storing and processing information' (Baluška, Mancuso, Volkmann, Hlaváček, Barlow, 2006: 19).

Beyond the different paradigms — cell- or root-brain-oriented — both perspectives recognise light-foraging behaviours as a proper way of learning by association (Gagliano et al., 2016). This is an intentional response of plants, in other words, a finely grained skill of intelligent beings. Intention is the kind of knowledge that enables one to achieve a goal. According to Anscombe (1957), intention is a type of knowledge belonging to the class of 'non-observational knowledge', or 'the class of movements known without observation' (Proposition 8). To give an example, when we say 'I open the windows', we perform a number of actions to carry out that task. What does this mean from a cognitive perspective? Simply, that intention is based on knowledge of how a goal is achieved (opening a window) (Torralba and Lano, 2008; 2010). However, it is one thing to say that plants are not passive systems and quite another to attribute their sophisticated behaviour to a specific agency or intention.

This is a challenging question.

Nevertheless, phototropism — the result of the effective interaction of multiple systems (the plant, its environment, light and metabolism) — resembles cognitive processes performed without clear consciousness, such as appetite. In classical philosophy, Thomas Aquinas theorised this idea in the doctrine of connaturalitas, referring to judgment per modum inclinationis, which differs from intellectual judgment (per modum cognitionis) (Biffi, 1964). Natural inclination is recognised as being present throughout nature (Baldner, 2020) and is closely linked to appetite — precisely the kind of 'movement' associated with plant tropism towards a source of light (Keane, 1966).

References

Baldner, S. (2018). Thomas Aquinas and natural inclination in non-living nature. Proceedings of the ACPA, 92, 211–222.

Baluška, F., Volkmann, D., Hlavacka, A., Mancuso, S., & Barlow, P. W. (2006). Neurobiological view of plants and their body plan. In F. Baluška, S. Mancuso, & D. Volkmann (Eds.), Communication in plants (pp. 19–35). Springer.

Baluška, F., & Mancuso, S. (2007). Plant neurobiology as a paradigm shift not only in the plant. Sciences Plant Signaling & Behavior, 2(4), 205–207.

Baluska, F., Schlicht, M., Volkmann, D., & Mancuso, S. (2008). Vesicular secretion of auxin; evidences and implications. Plant Signaling & Behavior, 3, 254–256.

Biffi, I. (1974). Il giudizio “per quandam connaturalitatem” o “per modum inclinationis” secondo San Tommaso: analisi e prospettive. Rivista Di Filosofia Neo-Scolastica, 66(2/4), 356–393.

Gagliano, M., Vyazovskiy, V., Borbély, A. A., Grimonprez, M., & Depczynski, M. (2016). Learning by association in plants. Scientific Reports, 6, 1–9, https://www.nature.com/articles/srep38427

Keane, H. V. (1966). Knowledge by Connaturality in St. Thomas Aquinas [PhD dissertation, Marquett University]. Wisconsin.

Garzón, P. C., & Keijzer, F. (2011). Plants: Adaptive behavior, root-brains, and minimal cognition. Adaptive Behavior, 19(3), 155–171. https://doi.org/10.1177/1059712311409446

Torralba, J. M., & Llano, A. (2008). Intention. Conference paper held in Rome, at the Pontif ical University of the Holy Cross, international conference about G.E.M. Anscombe, 28–29 February.

Trewavas, A. J. (2009). What is plant behaviour? Plant and Cell Environment, 32, 606–616. Trewavas, A. J. (2014). Plant behaviour and intelligence. Oxford University Press. Trewavas, A. (2016). Intelligence, cognition, and language of green plants. Frontiers in Psychology, 7(588), 1–9. https://www.frontiersin.org/articles/10.3389/fpsyg.2016.00588/full

Ulivi, L.U., Fisogni, P. (2024). Intelligent Systems Many Manners of Adapting to Environment. In: Minati, G., Pietronilla Penna, M. (eds) Multiple Systems. AIRSNC 2023. Contributions to Management Science. Springer, Cham. https://doi.org/10.1007/978-3-031-44685-6_6