The decentralized intelligence of plants

From a very beautiful essay by Kevin Kelly at the Technium, which covers the intelligence of both plants and insects.

An excerpt on plant intelligence:

“Plants, too, posses a decentralized type of intelligence. As Anthony Trewavas argues in his remarkable paper, “Aspects of Plant Intelligence,” plants demonstrate a slow version of problem solving that fit most of our definitions of animal intelligence. They perceive their environment in great detail, they assess threats and competition, then they take action to either adapt or remedy the problems, and anticipate future states. Time-lapse motion pictures that speed up the action of vine tendrils probing their neighborhood make it clear that plants are closer to animals in their behavior than our fast lives permit us to see. Charles Darwin may have been the first to observe this. He wrote in 1822, “It is hardly an exaggeration to say that the tip of the root acts like the brain of one of the lower animals.” Like sensitive fingers, roots will caress the soil, seeking out moisture and nutrients much as a nose or trunk of a herbivore might dig in the earth.

Plants share with animals an almost mathematical ability to optimize their energy efficiency while gathering the most nutrients for the least effort. Plant and animal “foraging” models are almost identical. Roots search for fertile areas while avoiding adversarial competitors. A distant rootlet can also recognize another rootlet as its own among many the underground tangle of roots, even when all the neighboring plants are genetic clones. Thus, says Trewavas, “Individual plants are able to distinguish self from non-self.”

Plants are in constant motion because their world is in motion. The microclimates around a plant vary by height above ground. The density of carbon dioxide and sunlight can vary by the minute as wind blows and shade shifts. Available nutrients vary by the day as other plants thrive nearby. Growth factors vary by the seasons and temperature, and they vary by the decade as the ecological progression changes. A plant’s entire shape, metabolism, and behavior will thus change by the minute as well, as if it is being governed by a nervous system. It can quickly fill its green leaves with toxins or anti-fungal pesticides to retaliate if animals or parasites munch on it. As competing plants invade its territory a plant can alter the orientation and the structure of its parts by deflating the stomata on one side of its leaves to bend them in certain directions. A plant can thus “see” its environment and move in response to this sight. Some plants walk across a landscape, branch bent to root raised to branch again, on the scale of decades. The ability of a leaf to follow the sun (heliotropism) to gain optimal light exposure can be replicated in a machine, but only by using a fairly sophisticated computer chip as a brain. A plant thinks without a brain. It uses a vast network of transducing molecular signals instead of electronic nerves to carry and process information.

Remarkably a plant mind also contains a memory. There are numerous examples of plants remembering signals for days, and even years. A memory is a way to move information from the past into the present. Plants can also move information from the present into future, or anticipate, which is a true mark of the most primitive intelligence. When a nearby competing plant dies, opening up previous shade to light, some plants send out “exploratory speculative growth” in order to test the new zone with small investments of chlorophyll before spending big time on expensive branches and leaves. Light reflected from nearby vegetation is richer in far-red wavelengths than unreflected light. Plants can use this information to not only see shade, but to anticipate the likelihood of shading by a competitor in the future. “When a change in the balance of red to far-red radiation is perceived,” says Trewavas, “an integrated adaptive response in phenotype structure [of the plant] results. New branches grow away from the putative competitor, stem growth is increased; the rate of branching diminishes, and such branches assume a more vertical direction: leaf area increases in anticipation of reduced incident flux; and the number of layers of leaf cells containing chlorophyll diminishes.”

Plants exhibit all the characteristics of intelligence, except they do it without a centralized brain, and in slow motion. Decentralized minds and slow minds are actually quite common in nature, and occur at many levels throughout the six kingdoms of life. A slime mold colony can solve the shortest distance to food in a maze, much like a rat. The animal immune system, whose primary purpose is to distinguish between self and non-self, retains a memory of outside antigens it has encountered in the past. It learns in a darwinian process, and in a sense also anticipates future variations of antigens. And throughout the animal kingdom collective intelligence is expressed in hundreds of ways, including the famous hive minds of social insects.”

3 Comments The decentralized intelligence of plants

  1. AvatarLytton

    I had a theory that potentially prove the fact that intelligence, or consciousness, does not come from the brain. Seing as plants do not have a brain but are intelligent, or conscious of their surroundings, it is clear to me that consciousness is not a product of the brain and that my heory is correct. Therefore, this disproves the idea that most, if not all, mainstream scientists have: that consciousness comes from the brain. This leads me to my personal belief, that consciousness is the foundation of our universe, from which all physical entities are created. This is more commonly reffered to as God or spirit.

  2. AvatarJames Jones

    I would contend that any plant response to a single change in environment can be reduced to a mechanistic expression of genetically defined boundaries constantly altering the cellular chemistry in response to external factors, and internal chemical signals. This would discount this “Intelligence” as being anything beyond multitudes of feedback loops in action.

    No “god” or “spirit” is needed to cloud the issue.

    Emergent behavior is complex even in robots with 4 or 5 rules at play. In a plant how many hundred or thousand rules for homeostasis are simultaneously in play? While this can be labeled as intelligence, I feel that it is simply a threshold of sophistication several orders of magnitude above our current capabilities. the “knowledge” in the process is the accumulation of BILLIONS of years of refinement.

    That we have gone from no (practical) awareness of this 5 to 4 hundred years ago, to an ability to intervene in the process is rather more rapid.

    Our systems are much simpler, but like a group of children who’ve just learned their alphabet, it would be unfair to judge their abilities by handing them Dostoevsky in the original Russian, which I feel is an apt analogy to our comprehension of the collective complexity present in even simple plants. A human brain is a sharp instrument, but just as you wouldn’t cut down a tree with a scalpel, some problems (Rain-forest ecology?, unintended consequences?) are too big to comprehend in their totality.

  3. AvatarDelton

    Given that plants (autotrophs) have evolved with a biological model that is different to animals (heterotrophs), based on the need to bio-sequester carbon for food- it follows that the and thermodynamic model of plants is the complementary opposite of animals. Plants have a decentralised intelligence, as a requirement to reduce the entropy of carbon by absorbing diffuse solar radiation (trapping photons in chloroplast) in a reward-for-risk reduction model – whereas animals reverse the process. Animals take the opposite pathway, in terms of the entropic release of carbon, and hence animals must follow the risk-for-reward model – thus requiring centralised intelligence to make the decision for which choices to make to maximise efficiency. The answers are tied to the thermodynamics of energy flow – and the intelligence component is needed in different dimensions – decentralised versus centralised.
    D.

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