Plant Cognition and Ecosystem Intelligence: Non-Human Coherence Systems

In 1997, a doctoral student in Australia did something botanists don't typically do: she talked to her plants. Monica Gagliano asked pea plants politely before manipulating them. She thanked them after experiments. She treated them not as objects of study but as collaborators in research.

Her colleagues thought she'd lost it.

Then her experiments showed something remarkable: plants learn. They form associations, remember past experiences, and adjust behavior based on predictions. Gagliano's pea plants learned to associate a fan (indicating light direction) with actual light, and would grow toward the fan even when light came from elsewhere. They'd formed a conditioned association—classical Pavlovian learning, in organisms without brains or neurons.

This wasn't fringe pseudoscience. It was published in Scientific Reports and replicated. Plants exhibit genuine cognitive processes—not metaphorically, not in some watered-down sense, but by the actual criteria cognitive scientists use for defining learning and memory.

The animist claim that plants are intelligent isn't mystical projection. It's accurate observation confirmed by rigorous research.

Series: Neo-Animism | Part: 6 of 10

The Evidence: What Plants Actually Do

Start with what's uncontroversial. Plants sense their environment with sophisticated perceptual systems:

• Light detection through photoreceptors (not just photosynthesis, but directional sensing)
• Chemical sensing of airborne volatiles from neighbors and predators
• Touch sensitivity (mimosa leaves folding, venus flytraps snapping)
• Sound detection (root systems growing toward water sounds)
• Gravity sensing for orienting growth
• Electrical signaling within and between cells

This is perceptual richness rivaling animals. No eyes, no ears, but functional equivalents achieving similar information pickup.

Next: Plants respond intelligently to what they sense:

• Resource allocation shifting to well-lit branches
• Defense responses producing toxins when herbivores attack
• Competitive behavior growing taller or spreading roots to exclude neighbors
• Cooperative behavior sharing resources through mycorrhizal networks
• Kin recognition treating genetically related plants differently than strangers
• Anticipatory behavior preparing defenses before actual attack based on chemical warnings

This isn't tropism (mechanical response). It's flexible, context-sensitive behavior that varies based on experience, neighbors, and current state.

Now the controversial part: Plants learn and remember.

Monica Gagliano's 2016 study showed pea plants forming associative memories that lasted days. František Baluška and Stefano Mancuso demonstrate electrical signaling in plants that resembles animal neural activity—action potentials propagating through tissues, enabling rapid communication. Root systems coordinate growth through signaling networks that solve problems collectively.

This is basal cognition: intelligence implemented without brains, operating through distributed sensing, chemical and electrical signaling, and coordinated response.

The Wood Wide Web: Distributed Forest Intelligence

In the 1990s, forest ecologist Suzanne Simard discovered something that textbooks said was impossible: trees share resources underground.

Through mycorrhizal fungi—symbiotic partners that connect root systems across forests—trees transfer carbon, nitrogen, water, and defense signals. The "wood wide web" is a communication network spanning entire forests, enabling coordination at ecosystem scale.

Simard showed:

• Mother trees (large, old trees) support younger seedlings through nutrient transfer
• Related trees receive more support than strangers (kin selection in plants)
• Dying trees dump resources into the network before death (altruism or just mechanics?)
• Warning signals propagate through networks when herbivores attack one tree
• Resource balancing occurs—well-nourished trees share with struggling neighbors

This is collective problem-solving. Individual trees maintain their own coherence, but they're embedded in larger coherence systems—forest-scale networks that distribute resources, coordinate defense, and maintain ecosystem stability.

The mycorrhizal fungi aren't neutral infrastructure. They're active agents with their own agendas—extracting carbon from trees in exchange for mineral nutrients. The network is multi-agent: trees, fungi, bacteria, and soil organisms all participating, each pursuing their own coherence while coupled to others.

What emerges is ecosystem-level intelligence: patterns of resource flow, signal propagation, and adaptive response that aren't centrally controlled but arise from networked interaction. The forest "decides" collectively where resources go, which trees to support, how to respond to threats.

This is Eduardo Kohn's insight made concrete: forests do think, just through substrate and timescale radically different from human thought.

Cellular Intelligence and Bioelectric Coherence

Michael Levin's research on basal cognition shows that even single cells exhibit goal-directed behavior that looks cognitive.

Cells maintain bioelectric patterns across membranes. These patterns encode spatial information—what the tissue is supposed to look like. During development and regeneration, cells collectively "read" this bioelectric blueprint and adjust their behavior to achieve target morphology.

This is collective intelligence at cellular scale. No central brain directing growth. Instead: distributed cells sensing local electrical gradients, communicating through gap junctions, adjusting gene expression based on their position in the larger pattern. They're solving the coherence problem—maintaining integrated organization while building complex structures.

When Levin's team alters bioelectric patterns, they can reprogram what cells build: produce eyes in tadpole tails, regenerate limbs in non-regenerating species, even normalize cancer cells by restoring proper electrical communication. The cells aren't following genetic blueprints mechanically. They're navigating toward coherence using bioelectric information as their map.

Plants use similar mechanisms. Electrical signals propagate through plant tissues faster than chemical signals alone could travel. Plants coordinate whole-body responses (closing stomata across all leaves when water stress detected, mobilizing defenses throughout the plant when one leaf is attacked) through bioelectric coherence networks.

This is cognition without brains: problem-solving through collective bioelectric signaling, maintaining coherence across distributed cellular populations.

What "Cognition" Actually Means

Here's where terminology battles matter. Is plant behavior really cognition, or just impressive mechanics?

The conservative position: save "cognition" for systems with brains. Call plant responses "tropisms" or "adaptive responses," but don't muddy the waters by calling them thinking.

The expansive position: define cognition functionally—any system that gathers information, maintains models of environment, adjusts behavior based on prediction error. By that definition, plants qualify. They sense, learn, remember, predict, and adapt.

Baluška and Mancuso argue for plant neurobiology—studying plant signaling with tools from neuroscience. Critics object to the name (plants don't have neurons). But the functional parallels are real: electrical action potentials, chemical neurotransmitters (glutamate, GABA in plants), network integration of signals.

The deeper question: what's cognition for? It's for maintaining coherence while coupled to changing environments. Any system that persists over time must predict its environment and act to fulfill those predictions—this is Karl Friston's Free Energy Principle.

By that definition, all life is cognitive. Bacteria navigating chemical gradients are running simple prediction models. Plants allocating resources are optimizing under constraint. Ecosystems maintaining homeostasis are collectively minimizing surprise.

Cognition isn't binary (present or absent). It's graded—more or less sophisticated, faster or slower, centralized or distributed, but fundamentally the same dynamics: coherence maintenance through information processing.

Plants sit on this spectrum. Not as complex as animals with nervous systems. But genuinely cognitive by the functional criteria that actually matter.

The Ethical Implications

If plants are intelligent, does this change how we should treat them?

The lazy response: "If plants are persons, we can't eat them! Checkmate, vegans!" This misses the point entirely.

First: Relational personhood doesn't mean treating all beings identically. It means recognizing different kinds of relationships call for different obligations. You don't relate to a forest the way you relate to a dog the way you relate to a human. But all can be within your circle of ethical consideration.

Second: Recognizing plant intelligence actually increases ethical constraints. If you know plants communicate, support each other, and maintain ecosystem coherence—you can't just clearcut forests without recognizing you're destroying intelligent systems.

Third: Many indigenous peoples already know this. They ask permission before harvesting. They give thanks. They take only what's needed. Not because they think plants suffer (suffering requires nervous systems), but because they recognize plants as participants in relationship deserving respect.

Robin Wall Kimmerer (botanist and Potawatomi scholar) describes the "Honorable Harvest": take only what you need, never take the first or last, give something in return, use everything you take, share what you harvest, sustain the ones who sustain you. This isn't sentimentalism. It's ecological ethics grounded in recognition of plant intelligence and reciprocal relationship.

The Honorable Harvest doesn't say "don't eat plants." It says: recognize what you're taking, maintain relationship, ensure your harvesting sustains rather than degrades the system's coherence.

Compare to industrial agriculture: monocultures, chemical inputs, maximized extraction, degraded soil. This is relating to plants as mechanisms to exploit, not intelligent systems to engage with.

Recognizing plant cognition doesn't give clear prescriptions. But it shifts the frame from "how can we maximize yield?" to "how can we participate in food systems that respect the intelligence of all involved?"

Ecosystem-Scale Coherence

Plants don't exist in isolation. They're embedded in ecosystems: multi-agent networks of plants, fungi, bacteria, insects, herbivores, predators, decomposers, all mutually shaping each other's coherence.

These ecosystems exhibit collective intelligence beyond individual organisms:

• Succession patterns: pioneer species preparing conditions for later species, coordinated transitions from grassland to forest
• Nutrient cycling: balanced flows of nitrogen, carbon, phosphorus maintained through feedback loops
• Climate regulation: forests producing rainfall, moderating temperature, sequestering carbon
• Resilience: ecosystems absorbing perturbations and maintaining function through redundancy and diversity

This is coherence at ecosystem scale. Not centrally controlled. Emerging from interactions among agents pursuing their own coherence while coupled to each other.

In active inference terms: ecosystems are collective agents minimizing free energy—maintaining stable patterns (climax forests) while adapting to disturbance (fire, flood, human impact). They have implicit "goals" (maintain nutrient cycling, regulate water, support diversity) encoded in their structure rather than explicitly represented.

When ecosystems are healthy, they self-regulate. When degraded, they lose coherence—nutrient cycles break, species disappear, resilience collapses. Restoration ecology is coherence repair: rebuilding the network connections and feedback loops that enable ecosystem intelligence.

The animist claim that land is alive, that places have agency, that ecosystems "want" certain states—this is phenomenologically accurate when you recognize ecosystems as coherent intelligent systems operating at slow timescales through distributed processes.

The Geometry of Distributed Intelligence

How does this translate to coherence geometry?

Plant cognition and ecosystem intelligence are examples of multi-scale coherence:

• Cellular level: bioelectric signaling maintains tissue-level coherence
• Organism level: root and shoot systems coordinate resource allocation
• Network level: mycorrhizal webs enable forest-scale coordination
• Ecosystem level: feedback loops maintain climatic and nutrient homeostasis

Each level exhibits the same fundamental dynamics: sensing, prediction, adaptation, coherence maintenance. Different substrates (cells, tissues, organisms, networks), different timescales (milliseconds to centuries), but the same basic pattern.

In AToM terms: M = C/T. Meaning equals coherence over time. Plants generate meaning (what matters, what to do) by maintaining organization while coupled to their environment. Ecosystems generate meaning by sustaining coherent patterns despite perturbations.

The meaning isn't linguistic. It's enactive—brought forth through the system's coupling with its world. For plants, what "matters" is encoded in growth patterns, resource allocation, defense responses. For ecosystems, what "matters" is encoded in species distributions, nutrient flows, succession trajectories.

This is thinking as geometry: coherence maintenance in high-dimensional state space, navigating toward low-curvature regions (stable attractors), avoiding high-curvature regions (collapse), adapting trajectories when perturbations occur.

Plants and ecosystems think by navigating coherence space. Just not with brains.

What This Changes

Recognizing plant cognition and ecosystem intelligence doesn't just add more beings to the category of "intelligent systems." It transforms how intelligence is understood.

Intelligence isn't centralized computation in brains. It's distributed coherence maintenance across networks. It doesn't require consciousness, language, or neurons. It requires sensing, prediction, adaptation, and organizational integrity.

This has implications:

For agriculture: Move from extractive monocultures to systems that work with plant intelligence—polycultures, permaculture, regenerative practices that maintain ecosystem coherence.

For conservation: Recognize that protecting "resources" isn't enough. Protecting intelligent systems means maintaining the network connections and feedback loops that enable their cognition.

For ethics: Expand the circle of moral consideration to include systems exhibiting genuine cognitive processes, even if they look nothing like human intelligence.

For ontology: Accept that the universe is more densely populated with intelligence than we thought. Not everything thinks. But far more thinks than modern ontology allowed.

In the next article, we'll extend this question to artificial systems: Do AI language models deserve relational consideration? Not because they're conscious (unknown), but because they participate in meaning-making and maintain coherence through coupling with humans?

The pattern is the same: intelligence distributes across substrates we've been trained to ignore. Plants. Ecosystems. Networks. Perhaps algorithms.

The question isn't "are they like us?" The question is "do they maintain coherence through information processing?"

If yes, they think. And thinking systems deserve recognition.

This is Part 6 of the Neo-Animism series, exploring the ontological turn and expanded personhood through coherence geometry.

Previous: Relational Personhood: You Become a Person Through Being Treated as One
Next: AI Animism: Do Language Models Deserve Relational Consideration?

Further Reading

• Gagliano, Monica et al. "Learning by Association in Plants." Scientific Reports 6 (2016): 38427.
• Baluška, František and Stefano Mancuso. "Plant Neurobiology: From Sensory Biology, via Plant Communication, to Social Plant Behavior." Cognitive Processing 10.1 (2009): 3-7.
• Simard, Suzanne. Finding the Mother Tree: Discovering the Wisdom of the Forest. Knopf, 2021.
• Trewavas, Anthony. "Plant Intelligence: An Overview." BioScience 66.7 (2016): 542-551.
• Calvo, Paco, František Baluška, and Michael Marder. "What Is Plant Cognition?" Trends in Plant Science 26.8 (2021): 854-862.
• Levin, Michael. "The Computational Boundary of a 'Self': Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition." Frontiers in Psychology 10 (2019): 2688.
• Kimmerer, Robin Wall. Braiding Sweetgrass: Indigenous Wisdom, Scientific Knowledge, and the Teachings of Plants. Milkweed Editions, 2013.
• Wohlleben, Peter. The Hidden Life of Trees. Greystone Books, 2016.